279 results on '"Patrick Jenny"'
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52. Energy Extraction from Onflow Inhomogeneity in the Spanwise Direction. A Theoretical Study.
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Vitaly Dmitriev and Patrick Jenny
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- 2013
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53. A consistent dual-mesh framework for hybrid LES/RANS modeling.
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Heng Xiao and Patrick Jenny
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- 2012
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54. The stochastic counterpart of conservation laws with heterogeneous conductivity fields: Application to deterministic problems and uncertainty quantification.
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Amir H. Delgoshaie, Peter W. Glynn, Patrick Jenny, and Hamdi A. Tchelepi
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- 2019
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55. A hierarchical fracture model for the iterative multiscale finite volume method.
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Hadi Hajibeygi, Dimitris Karvounis, and Patrick Jenny
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- 2011
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56. Adaptive iterative multiscale finite volume method.
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Hadi Hajibeygi and Patrick Jenny
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- 2011
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57. A solution algorithm for the fluid dynamic equations based on a stochastic model for molecular motion.
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Patrick Jenny, Manuel Torrilhon, and Stefan Heinz 0002
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- 2010
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58. Micromixing models for turbulent flows.
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Daniel W. Meyer and Patrick Jenny
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- 2009
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59. Modeling complex wells with the multi-scale finite-volume method.
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Patrick Jenny and Ivan Lunati
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- 2009
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60. Stochastic modeling of evaporating sprays within a consistent hybrid joint PDF framework.
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Gaurav Anand and Patrick Jenny
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- 2009
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61. An efficient multi-scale Poisson solver for the incompressible Navier-Stokes equations with immersed boundaries.
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Giuseppe Bonfigli and Patrick Jenny
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- 2009
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62. Unconditionally convergent nonlinear solver for hyperbolic conservation laws with S-shaped flux functions.
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Patrick Jenny, Hamdi A. Tchelepi, and Seong H. Lee
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- 2009
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63. Multiscale finite-volume method for parabolic problems arising from compressible multiphase flow in porous media.
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Hadi Hajibeygi and Patrick Jenny
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- 2009
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64. Statistical analysis and modeling of particle trajectories in 2-D fractured porous media
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Ranit Monga, Oliver Brenner, Daniel W. Meyer, and Patrick Jenny
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Non-Fickian transport ,Macrodispersion ,Fractured porous media ,Random walk ,Heterogeneity ,Bimodal log-conductivity distribution ,Water Science and Technology - Abstract
Solute transport observed in subsurface formations shows complex behavior, particularly in the presence of fractures. In this work, we focus on formations with fractures that are smaller compared to the domain of interest and which are distributed in a heterogeneous matrix at densities below the percolation threshold. We developed a simplified Lagrangian approach to characterize and predict advective transport in 2-D domains containing differently oriented fractures. To this end, we performed Monte Carlo simulation (MCS) studies using ensembles of random domain realizations and gathered/analyzed tracer particle displacement statistics. The series of displacement steps were defined by the locations of particles entering the matrix after traversing through one or several connected fractures. Then, we identify key correlation structures in the evolution of and between displacement step coordinates, namely, the step length, its orientation and the traverse time. Subsequently, a correlated random walk model was derived which is able to accurately reproduce longitudinal and transverse macrodispersion as recorded in the MCS. Finally, we explored the predictive capabilities of our stochastic model by simulating macrodispersion in stratified media composed of heterogeneous zones with different fracture orientations., Advances in Water Resources, 161, ISSN:0309-1708, ISSN:1872-9657
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- 2022
65. A Lagrangian, stochastic modeling framework for multi-phase flow in porous media.
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Manav Tyagi, Patrick Jenny, Ivan Lunati, and Hamdi A. Tchelepi
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- 2008
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66. Iterative multiscale finite-volume method.
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Hadi Hajibeygi, Giuseppe Bonfigli, Marc Andre Hesse, and Patrick Jenny
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- 2008
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67. Consistent inflow and outflow boundary conditions for transported probability density function methods.
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Daniel W. Meyer and Patrick Jenny
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- 2007
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68. Treating Highly Anisotropic Subsurface Flow with the Multiscale Finite-Volume Method.
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Ivan Lunati and Patrick Jenny
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- 2007
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69. A multiblock joint PDF finite-volume hybrid algorithm for the computation of turbulent flows in complex geometries.
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Benjamin Rembold and Patrick Jenny
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- 2006
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70. Multiscale finite-volume method for compressible multiphase flow in porous media.
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Ivan Lunati and Patrick Jenny
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- 2006
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71. Adaptive fully implicit multi-scale finite-volume method for multi-phase flow and transport in heterogeneous porous media.
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Patrick Jenny, Seong H. Lee, and Hamdi A. Tchelepi
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- 2006
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72. Adaptive Multiscale Finite-Volume Method for Multiphase Flow and Transport in Porous Media.
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Patrick Jenny, Seong H. Lee, and Hamdi A. Tchelepi
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- 2005
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73. Numerical modeling and design decisions for aerostatic bearings with relatively large nozzle sizes in Magic-Angle Spinning (MAS) systems
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Rajdeep Deb, Andreas Hunkeler, Dirk Wilhelm, Patrick Jenny, and Beat H. Meier
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Nozzle diameter ,530: Physik ,Mechanical Engineering ,Nozzle restriction parameter ,Surfaces and Interfaces ,Surfaces, Coatings and Films ,Nuclear magnetic resonance ,Bearing number ,Reynolds equation ,Magic-angle spinning ,Aerostatic bearing ,Magic angle spinning ,Mechanics of Materials - Abstract
Numerical stability analysis for aerostatic bearings was performed to obtain optimized design parameters for small submillimeter to millimeter range diameter cylindrical rotors. Such rotors are used in nuclear magnetic resonance (NMR) application to rotate sample around an axis inclined by magic angle (54.74°) relative to the magnetic field direction at rotational frequencies of about 100 kHz (magic-angle spinning, MAS). The governing Reynolds equation for the fluid film between rotor and bearing was modified for small size aerostatic bearings with relatively large nozzle diameters. The modified Reynolds equation was solved using a finite-volume method to obtain pressure and film thickness around the rotor. This led to the solution of the maximum stable inertial force as a function of rotational frequency and design parameters. The comparison with aerostatic bearings with infinitesimal nozzle sizes was obtained for supported rotor weight and critical vibrational frequency of the rotor. The stable inertial force was found to correspond to a specific nozzle diameter and a specific rotor–bearing clearance. Numerical investigation also shows an enhancement of stable inertial force with decreasing nozzle number or increasing molecular mass of the impinging gas for a specific range of nozzle parameters. Experimental observations further confirmed the role of nozzle diameter, nozzle number and molecular weight of the gas in enhancing the rotor spinning frequency. Further, design decisions were made based on such analysis and were tested for varying rotor size and bearing properties. Using design optimization based on numerical simulation, the maximum frequency of rotation for a home-built 0.4 mm MAS rotor could be enhanced from 25 kHz up to 110 kHz, still below the extrapolation from large rotors., Tribology International, 175, ISSN:0301-679X
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- 2022
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74. Heat transfer analysis of high pressure hydrogen tank fillings
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Arthur Couteau, Panayotis Dimopoulos Eggenschwiler, and Patrick Jenny
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Fuel Technology ,Renewable Energy, Sustainability and the Environment ,Energy Engineering and Power Technology ,Condensed Matter Physics - Abstract
Fast fillings of hydrogen vehicles require proper control of the temperature to ensure the integrity of the storage tanks. This study presents an analysis of heat transfer during filling of a hydrogen tank. A conjugate heat transfer based on energy balance is introduced. The numerical model is validated against fast filling experiments of hydrogen in a Type IV tank by comparing the gas temperature evolution. The impact of filling parameters, such as initial temperature, inlet nozzle diameter and filling time is then assessed. For the considered Type IV tank, the results show that both a higher and lower tank shell thermal conductivity results in lower inner wall peak temperatures. The presented model provides an analytical description of the temperature evolution in the gas and in the tank shell, and is thus a useful tool to explore a broad range of parameters, e.g., to determine new hydrogen filling protocols., International Journal of Hydrogen Energy, 47 (54), ISSN:1879-3487, ISSN:0360-3199
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- 2022
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75. Vector boson scattering from the lattice
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Patrick Jenny, Bernd Riederer, and Axel Maas
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High Energy Physics - Phenomenology ,High Energy Physics - Experiment (hep-ex) ,High Energy Physics - Lattice ,High Energy Physics - Phenomenology (hep-ph) ,High Energy Physics::Lattice ,High Energy Physics - Lattice (hep-lat) ,FOS: Physical sciences ,High Energy Physics - Experiment - Abstract
We study vector-boson scattering of the physical, gauge-invariant states in a reduced standard-model setup on the lattice for various parameter sets. To this end, the phase shift in the scalar channel is determined using a L\"uscher-type analysis. The results can be readily interpreted in terms of the Higgs properties and a reunitarized Fr\"ohlich-Morchio-Strocchi analysis at Born level. The only deviation appears for a Higgs mass below the elastic threshold, where we find a negative scattering length indicative of the bound-state nature of the physical scalar degree of freedom. We assess the possible implications for an experimental detection of the effect., Comment: 21 pages, 8 figures, 9 tables; v2: minor corrections to text, small modification to Figs. 3 - 5, version to appear in PRD
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- 2022
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76. Adaptive conservative time integration for transport in fractured porous media
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Michael Liem, Stephan Matthai, and Patrick Jenny
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CFL ,Fractured porous media ,Adaptive time stepping ,Sub-time steps ,Scalar transport ,Higher-order flux scheme ,Water Science and Technology - Abstract
The time step of an explicit time integration scheme for solving time-dependent hyperbolic partial differential equations in a finite volume method (FVM) framework is restricted by the Courant–Friedrichs–Lewy (CFL) criterion. Conventional time stepping integrates all grid cells with the same time step. This causes unnecessary computational costs when wave speeds and/or grid spacing vary considerably throughout the domain, and a few critical cells dictate the global time step, although most cells could be advanced with a much larger time step. Adaptive time stepping overcomes this issue by allowing different local time step sizes for each grid cell. The adaptive conservative time integration (ACTI) scheme is a recently developed adaptive time stepping method which relies on local time steps that are equal to the largest time step divided by powers of two. This work extends the ACTI scheme to tracer transport in fractured porous media. When fluid velocity within highly permeable fractures is higher than in the rock matrix and local grid refinement is applied around fractures, the CFL restriction would require prohibitively small time steps in the vicinity of fractures. For two-dimensional discrete fracture and matrix models of fracture patterns we demonstrate that ACTI reduces the computational cost by orders of magnitude compared to global time stepping while retaining solution accuracy. Empirically, we show that ACTI is stable in combination with a first-order explicit flux discretization scheme. Since combination with a standard higher-order MUSCL scheme can lead to spurious oscillations in the solution, we propose a modified MUSCL scheme relying on advection of an inclined reconstruction (MUSCL-AIR)., Advances in Water Resources, 165, ISSN:0309-1708, ISSN:1872-9657
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- 2022
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77. Tightly Coupled Hyperbolic Treatment of Buoyant Two-Phase Flow and Transport in Porous Media
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Patrick Jenny, Rasim Hasanzade, and Hamdi Tchelepi
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Computational Mathematics ,Numerical Analysis ,History ,Physics and Astronomy (miscellaneous) ,Polymers and Plastics ,Applied Mathematics ,Modeling and Simulation ,Business and International Management ,Industrial and Manufacturing Engineering ,Computer Science Applications - Published
- 2022
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78. Data-Driven Stochastic Particle Scheme for Collisional Plasma Simulations
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kyoungseoun chung, Fei Fei, Mohammad Hossein Gorji, and Patrick Jenny
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History ,Polymers and Plastics ,Business and International Management ,Industrial and Manufacturing Engineering - Published
- 2022
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79. Consistent upwinding for sequential fully implicit multiscale compositional simulation
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Arthur Moncorgé, Olav Møyner, Hamdi A. Tchelepi, and Patrick Jenny
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Capillary pressure ,Buoyancy ,Numerical analysis ,Upwind scheme ,010103 numerical & computational mathematics ,Decoupling (cosmology) ,engineering.material ,01 natural sciences ,Computer Science Applications ,Computational Mathematics ,Computational Theory and Mathematics ,Rate of convergence ,Convergence (routing) ,engineering ,Applied mathematics ,0101 mathematics ,Computers in Earth Sciences ,Temporal discretization ,Mathematics - Abstract
There is strong interest to design sequential fully implicit (SFI) methods for compositional flow simulations with convergence properties that are comparable to fully implicit (FI) methods. SFI methods decompose the fully coupled system into a pressure equation and a transport system of the components. During the pressure update, the compositions are frozen, and during the transport calculations, both the pressure and total velocity are kept constant. The two systems are solved sequentially, and the solution, which is a fully implicit one, is obtained by controlling the splitting errors due to the decoupling. Having an SFI scheme that enjoys a convergence rate similar to FI makes it possible to design specialized numerical methods optimized for the different parabolic and the hyperbolic operators, as well as the use of high-order spatial and temporal discretization schemes. Here, we use the multiscale restriction-smoothed basis (MsRSB) method for the parabolic operator. We also show that phase-potential upwinding is incompatible with the total velocity formulation of the fluxes, which is common in SFI schemes. We observe that in cases with strong gravity or capillary pressure, it is possible to have flow reversals. These reversals can strongly affect the convergence rate of SFI methods. In this work, we employ phase upwinding (PU) as well as implicit hybrid upwinding (IHU) with a SFI method. IHU determines the upwinding direction differently for the viscous, buoyancy, and capillary pressure terms in the phase velocity expressions. The use of IHU leads to a consistent SFI scheme in terms of both pressure and compositions, and it improves the SFI convergence significantly in settings with strong buoyancy or capillarity. We demonstrate the robustness of the IHU-based SFI algorithm across a wide parameter range. Realistic compositional models with gas and water injection are presented and discussed.
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- 2019
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80. Results from Canton Grisons of Switzerland Suggest Repetitive Testing Reduces SARS-CoV-2 Incidence (February-March 2021)
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Fabian Rudolf, Ivan Lunati, Martin Bühler, Patrick Jenny, Wolf-Dietrich Hardt, Adrian Sommer, Beatriz Vidondo, Lorenz Risch, Doortje Engel, Marina Jamnicki, Alexa Caduff, Hossein Gorji, Rudolf Leuthold, Jörg Schneider, and Martin Risch
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Coronavirus disease 2019 (COVID-19) ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Population ,law.invention ,law ,Quarantine ,Pandemic ,Humans ,Medicine ,630 Landwirtschaft ,education ,Pandemics ,education.field_of_study ,630 Agriculture ,SARS-CoV-2 ,business.industry ,Incidence ,Incidence (epidemiology) ,COVID-19 ,Test (assessment) ,Data processing ,Viral infection ,Turnover ,business ,Switzerland ,Demography - Abstract
In February 2021, in response to emergence of more transmissible SARS-CoV-2 virus variants, the Canton Grisons launched a unique RNA mass testing program targeting the labour force in local businesses. Employees were offered weekly tests free of charge and on a voluntary basis. If tested positive, they were required to self-isolate for ten days and their contacts were subjected to daily testing at work. Thereby, the quarantine of contact persons could be waved.Here, we evaluate the effects of the testing program on the tested cohorts. We examined 121,364 test results from 27,514 participants during February–March 2021. By distinguishing different cohorts of employees, we observe a noticeable decrease in the test positivity rate and a statistically significant reduction in the associated incidence rate over the considered period. The reduction in the latter ranges between 18 and 50%. The variability is partly explained by different exposures to exogenous infection sources (e.g., contacts with visiting tourists or cross-border commuters). Our analysis provides the first empirical evidence that applying repetitive mass testing to a real population over an extended period of time can prevent spread of COVID-19 pandemic. However, to overcome logistic, uptake, and adherence challenges it is important that the program is carefully designed and that disease incursion from the population outside of the program is considered and controlled., Scientific Reports, 12, ISSN:2045-2322
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- 2021
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81. Embedded Computational Heart Model for External Ventricular Assist Device Investigations
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Thomas Kummer, Simone Rossi, Stijn Vandenberghe, Stefanos Demertzis, and Patrick Jenny
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Direct cardiac contractor ,Heart Failure ,Heart Ventricles ,Biomedical Engineering ,Models, Cardiovascular ,Heart ,Three dimensional heart modeling ,Medical device development ,Hydraulic network model ,Lumped parameter circulation ,Active strain actuation ,External ventricular assist device ,Humans ,Computer Simulation ,Heart-Assist Devices ,Cardiology and Cardiovascular Medicine - Abstract
Purpose External cardiac assist devices are based on a promising and simple concept for treating heart failure, but they are surprisingly difficult to design. Thus, a structured approach combining experiments with computer-based optimization is essential. The latter provides the motivation for the work presented in this paper. Methods We present a computational modeling framework for realistic representation of the heart's tissue structure, electrophysiology and actuation. The passive heart tissue is described by a nonlinear anisotropic material law, considering fiber and sheetlet directions. For muscle contraction, an orthotropic active-strain model is employed, initiated by a periodically propagating electrical potential. The model allows for boundary conditions at the epicardium accounting for external assist devices, and it is coupled to a circulation network providing appropriate pressure boundary conditions inside the ventricles. Results Simulated results from an unsupported healthy and a pathological heart model are presented and reproduce accurate deformations compared to phenomenological measurements. Moreover, cardiac output and ventricular pressure signals are in good agreement too. By investigating the impact of applying an exemplary external actuation to the pathological heart model, it shows that cardiac patches can restore a healthy blood flow. Conclusion We demonstrate that the devised computational modeling framework is capable of predicting characteristic trends (e.g. apex shortening, wall thickening and apex twisting) of a healthy heart, and that it can be used to study pathological hearts and external activation thereof., Cardiovascular Engineering and Technology, 13 (5), ISSN:1869-408X, ISSN:1869-4098
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- 2021
82. The severity of microstrokes depends on local vascular topology and baseline perfusion
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Giulia Conti, Patrick Jenny, Franca Schmid, Bruno Weber, University of Zurich, Schmid, Franca, and Weber, Bruno
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Mouse ,Capillary network ,10050 Institute of Pharmacology and Toxicology ,Severity of Illness Index ,capillary ,Entire brain ,Mice ,0302 clinical medicine ,2400 General Immunology and Microbiology ,blood flow ,Biology (General) ,Stroke ,0303 health sciences ,General Neuroscience ,2800 General Neuroscience ,Brain ,General Medicine ,stroke ,Perfusion ,medicine.anatomical_structure ,Cardiology ,Medicine ,Cerebral amyloid angiopathy ,Research Article ,microvasculature ,Blood vessel ,medicine.medical_specialty ,QH301-705.5 ,Science ,610 Medicine & health ,Genetics and Molecular Biology ,occlusion ,energy supply ,Topology ,Models, Biological ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,1300 General Biochemistry, Genetics and Molecular Biology ,Internal medicine ,medicine ,Animals ,030304 developmental biology ,Mouse cortex ,General Immunology and Microbiology ,business.industry ,Disease progression ,Hemodynamics ,Blood flow ,medicine.disease ,Capillaries ,Oxygen ,General Biochemistry ,Microvessels ,570 Life sciences ,biology ,business ,030217 neurology & neurosurgery ,Neuroscience - Abstract
Cortical microinfarcts are linked to pathologies like cerebral amyloid angiopathy and dementia. Despite their relevance for disease progression, microinfarcts often remain undetected and the smallest scale of blood flow disturbance has not yet been identified. We employed blood flow simulations in realistic microvascular networks from the mouse cortex to quantify the impact of single capillary occlusions. Our simulations reveal that the severity of a microstroke is strongly affected by the local vascular topology and the baseline flow rate in the occluded capillary. The largest changes in perfusion are observed in capillaries with two in- and two outflows. This specific topological configuration only occurs with a frequency of 8%. The majority of capillaries has one in- and one outflow and is likely designed to efficiently supply oxygen and nutrients. Taken together, microstrokes bear potential to induce a cascade of local disturbances in the surrounding tissue, which might accumulate and impair energy supply locally., eLife, 10, ISSN:2050-084X
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- 2021
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83. Author response: The severity of microstrokes depends on local vascular topology and baseline perfusion
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Giulia Conti, Franca Schmid, Patrick Jenny, and Bruno Weber
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medicine.medical_specialty ,business.industry ,Internal medicine ,Cardiology ,Medicine ,Topology (electrical circuits) ,business ,Baseline (configuration management) ,Perfusion - Published
- 2021
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84. On droplets that cluster and evaporate in reactive turbulence
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Philipp Weiss, Sthavishtha R. Bhopalam, Daniel W. Meyer, and Patrick Jenny
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Fluid Flow and Transfer Processes ,Physics ,Turbulence ,Mechanical Engineering ,Isotropy ,Computational Mechanics ,Reynolds number ,Mechanics ,Condensed Matter Physics ,Mass loading ,Physics::Fluid Dynamics ,symbols.namesake ,Mechanics of Materials ,Homogeneous ,symbols ,Cluster (physics) ,Diffusion (business) ,Physics::Chemical Physics ,Stokes number - Abstract
This paper examines droplets that cluster and evaporate in reactive turbulence with direct numerical simulations. The flows are statistically homogeneous and isotropic with mass loadings of about 0.1, Stokes numbers of about 1, and Taylor-scale Reynolds numbers of about 40. Our simulation results reveal diffusion and premixed flames. When the mass loading is small or the Stokes number is large, clusters contain few droplets such that diffusion flames surround single droplets. However, when the mass loading is large or the Stokes number is small, clusters contain many droplets such that premixed flames propagate through clusters and diffusion flames surround clusters. ISSN:1070-6631 ISSN:1089-7666 ISSN:0031-9171
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- 2021
85. Dynamic modelling to identify mitigation strategies for the COVID-19 pandemic
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Markus Arnoldini, David Jenny, Hossein Gorji, Patrick Jenny, and Wolf-Dietrich Hardt
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Guiding Principles ,business.industry ,Population size ,Social distance ,Mortality rate ,Physical Distancing ,COVID-19 ,General Medicine ,Models, Theoretical ,COVID-19 Testing ,Risk analysis (engineering) ,Intensive care ,Economic cost ,Humans ,Mass Screening ,Medicine ,business ,Set (psychology) ,Asymptomatic Infections ,Pandemics ,Mass screening - Abstract
Relevant pandemic-spread scenario simulations can provide guiding principles for containment and mitigation policies. We devised a compartmental model to predict the effectiveness of different mitigation strategies with a main focus on mass testing. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries, and the number of COVID-19-inflicted deaths. We assumed that COVID-19 survivors are immune (e.g., mutations are not considered) and that the virus is primarily passed on by asymptomatic and pre-symptomatic individuals. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. The model parameters have been chosen in a plausible range based on information found in the literature, but it is easily adaptable, i.e., these values can be replaced by updated information any time. We compared infection rates, the total number of people getting infected and the number of deaths in different scenarios. Social distancing or mass testing can contain or drastically reduce the infections and the predicted number of deaths when compared with a situation without mitigation. We found that mass testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. It is of high practical relevance that a relationship between testing frequency and the effective reproduction number of the virus can be provided. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economic costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the COVID-19 pandemic. Moreover, we quantify the theoretical limit of contact tracing and by how much the effect of testing is enhanced, if applied to sub-populations with increased exposure risk or prevalence., Swiss Medical Weekly, 151, ISSN:1424-7860, ISSN:1424-3997
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- 2021
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86. On the mechanical power output required for human running – Insight from an analytical model
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David Jenny and Patrick Jenny
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Mechanical power output ,Rehabilitation ,Biomedical Engineering ,Biophysics ,Dissipation ,Mechanics ,Potential energy ,Wind speed ,Biomechanical Phenomena ,Running ,Center of mass dynamics ,Control theory ,Model ,Aerodynamic drag ,Trajectory ,Humans ,Orthopedics and Sports Medicine ,Center of mass ,Ground reaction force ,Mechanical energy ,Locomotion ,Mathematics - Abstract
In this paper the dynamics of human running on flat terrain and the required mechanical power output with its dependency on various parameters is investigated. Knowing the required mechanical power output is of relevance due to its relationship with the metabolic power. For example, a better understanding of the dependencies of required mechanical power output on weight, running and wind speed, step frequency, ground contact time etc. is very valuable for the assessment, analysis and optimization of running performance. Therefore, a mathematical model based on very few assumptions is devised. The purpose of the proposed model is to relate running speed and required mechanical power output as an algebraic function of the runner’s mass, height, step rate, ground contact time and wind speed. This is relevant in order to better understand the mechanical energy cost of locomotion, and how much it depends on which parameters. The first of the main energy dissipation mechanisms is due to vertical oscillation, i.e., during each step some of the potential energy difference gets transformed into heat. The second mechanism is due to the anterior ground reaction force during the first part of stance and the third is due to aerodynamic drag. With the approximations of constant running speed and a sinusoidal vertical ground reaction force profile one obtains closed algebraic expressions for the center of mass trajectory and the required mechanical power output. Comparisons of model predictions and reported performance data suggest that approximately a quarter of the ground impact energy is stored during the first part of ground contact and then released during the remaining stance phase. Further, one can conclude from the model that less mechanical power output is required when running with higher step rates and a higher center of mass. Non intuitive is the result that a shorter ground contact time is beneficial for fast runs, while the opposite holds for slow runs. An important advantage of the devised model compared to others is that it leads to closed algebraic expressions for the center of mass trajectory and mechanical power output, which are functions of measurable quantities, i.e., of step rate, ground contact time, running speed, runner’s mass, center of mass height, aerodynamic drag at some given speed, wind speed and heart rate. Moreover, the model relies on very few assumptions, which have been verified, and the only tuning parameter is the ratio of recovered elastic energy., Journal of Biomechanics, 110, ISSN:0021-9290, ISSN:1873-2380
- Published
- 2020
87. Sub-representative elementary volume homogenization of flow in porous media with isolated embedded fractures
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Patrick Jenny
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010504 meteorology & atmospheric sciences ,Mechanical Engineering ,Monte Carlo method ,010103 numerical & computational mathematics ,Mechanics ,Condensed Matter Physics ,01 natural sciences ,Homogenization (chemistry) ,Volumetric flow rate ,Mechanics of Materials ,Representative elementary volume ,Mean flow ,0101 mathematics ,Relative permeability ,Porous medium ,Pressure gradient ,0105 earth and related environmental sciences ,Mathematics - Abstract
This paper deals with homogenization of flow in porous media with large inhomogeneities. Classical homogenization relies on representative elementary volumes (REV) large enough that asymptotic macroscopic parameters, e.g. effective permeabilities, can be employed to describe the expected or mean behaviour. In this way, Darcy's law, which describes the relationship between macroscopic pressure gradient and volumetric flow rate, was derived. In the presence of large features, however, the required REV size may reach the same order as the geometric reference scale of the problem, and thus effective permeabilities obtained from classical homogenization studies may be unsuited. This is in particular the case for reservoirs with isolated, highly conductive fractures. To see this, consider flow from left to right through a block of finite size. If the latter is small enough, such that some fractures are connected to both left and right boundaries, then the resulting flow will be larger for the same average pressure gradient than through a wider block. In this paper, a new sub-REV continuum model to describe this pre-asymptotic flow behaviour is presented. The model relies on a non-local multi-media description based on coupled integral–differential equations. The only empirical information required for calibration is the effective permeability of an infinitely large domain, e.g. as obtained from classical homogenization. With a series of numerical studies and comparison with Monte Carlo reference data it is demonstrated that the devised sub-REV model accurately captures mean flow rates and pressure profiles for arbitrary domain sizes.
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- 2020
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88. Investigation of gas separation technique based on selective rotational excitation of different species by a laser
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Nemanja Andric and Patrick Jenny
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Fluid Flow and Transfer Processes ,Physics ,Work (thermodynamics) ,Scattering ,Mechanical Engineering ,Computational Mechanics ,Condensed Matter Physics ,Laser ,Thermal diffusivity ,01 natural sciences ,010305 fluids & plasmas ,law.invention ,Rotational energy ,Computational physics ,Mechanics of Materials ,law ,Excited state ,0103 physical sciences ,Gas separation ,010306 general physics ,Excitation - Abstract
In this work, a gas separation approach based on the selective rotational excitation of different species is investigated. The presented method is particularly suitable for separating gases of similar or equal masses, such as isotopes and isomers. The selective rotational excitation is achieved by a targeted application of multiple non-resonant ultrashort laser pulses. Upon collision with a solid surface, a part of the excited rotational energy gets transferred into translational energy. By creating a discernible difference in average thermal velocities between the species of similar masses, an increased diffusivity of the excited species can be utilized for its successful separation. In order to test the validity of the novel separation technique, a comprehensive computational framework was developed. The energy transfer in gas-surface collisions was analyzed in great detail using a state-of-the-art molecular dynamics code, and the obtained data offered invaluable insight into the nature of scattering dynamics. Furthermore, a novel data-driven approach to gas-surface interaction modeling based on the recently introduced distribution element tree method was proposed. Relevant numerical and experimental data on the selective rotational excitation were gathered, and they served as an input for the performed numerical simulations. Using the developed computational framework, the validity of the proposed separation scheme was tested on a mixture of two species with identical mass. The obtained data offer numerical evidence supporting the proposed separation concept. ISSN:1070-6631 ISSN:1089-7666 ISSN:0031-9171
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- 2020
89. STeCC: Smart Testing with Contact Counting Enhances Covid-19 Mitigation by Bluetooth App Based Contact Tracing
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Hossein Gorji, Markus Arnoldini, David F. Jenny, Alexandre Duc, Wolf-Dietrich Hardt, and Patrick Jenny
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Isolation (health care) ,Guiding Principles ,Risk analysis (engineering) ,Computer science ,Mortality rate ,Intensive care ,Social distance ,Pandemic ,Set (psychology) ,Contact tracing - Abstract
Relevant pandemic-spread scenario simulations provide guiding principles for containment and mitigation policy developments. Here we devise a simple model to predict the effectiveness of different mitigation strategies. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries and the number of Covid-19-inflicted deaths. For simplification, we assume that Covid-19 survivors are immune (e.g. mutations are not considered) and that the virus can only be passed on by persons with undetected infections. While the latter assumption is a simplification (it is neglected that e.g. hospital staff may be infected by detected patients with symptoms), it was introduced here to keep the model as simple as possible. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. Some of the model parameters have been fitted to the reported cases outside of China1 from January 22 to March 12 of the 2020 Covid-19 pandemic. The other parameters were chosen in a plausible range to the best of our knowledge. We compared infection rates, the total number of people getting infected and the number of deaths in six different scenarios. Social distancing or increased testing can contain or drastically reduce the infections and the predicted number of deaths when compared to a situation without mitigation. We find that mass-testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economical costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the Covid-19 pandemic. The website corona-lab.ch provides an interactive simulation tool based on the presented model.
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- 2020
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90. A Flexible Temporal Velocity Model for Fast Contaminant Transport Simulations in Porous Media
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Peter W. Glynn, Amir H. Delgoshaie, Patrick Jenny, and Hamdi A. Tchelepi
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Physics ,0208 environmental biotechnology ,02 engineering and technology ,Mechanics ,Markov model ,Porous medium ,020801 environmental engineering ,Water Science and Technology - Published
- 2018
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91. Porous membrane cleaning using supercritical carbon dioxide. Part 2: Development of mathematical model and CFD simulations
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Marek Henczka, Jan Krzysztoforski, and Patrick Jenny
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Supercritical carbon dioxide ,Materials science ,business.industry ,General Chemical Engineering ,Microfiltration ,02 engineering and technology ,Computational fluid dynamics ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,020401 chemical engineering ,Scientific method ,Mass transfer ,Volume of fluid method ,Process optimization ,0204 chemical engineering ,Physical and Theoretical Chemistry ,0210 nano-technology ,Porosity ,Process engineering ,business - Abstract
The process of cleaning microfiltration membranes contaminated with soybean oil, using pure supercritical carbon dioxide as cleaning fluid, was considered. A mathematical model of the process was developed, implemented into CFD software and validated using experimental results. The mathematical model is based on the Volume of Fluid approach and includes porous zone treatment, variable fluid phase composition due to mutual solubility of the contaminant and the solvent, as well as phase transition. The developed model was implemented into the OpenFOAM toolbox and validated using experimental results. The results of CFD simulations using the mathematical model show a good agreement with experimental results. CFD simulations were performed in order to analyze the effect of solvent flow rate and the effect of oil phase swelling on the course of the process. The mass transfer mechanisms were identified. The developed model is an efficient tool for process optimization, scale-up, and high-pressure equipment design.
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- 2018
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92. Temporal Markov Processes for Transport in Porous Media: Random Lattice Networks
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Hamdi A. Tchelepi, Amir H. Delgoshaie, and Patrick Jenny
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FOS: Computer and information sciences ,Computer science ,0208 environmental biotechnology ,Monte Carlo method ,Fluid Dynamics (physics.flu-dyn) ,FOS: Physical sciences ,Markov process ,Physics - Fluid Dynamics ,02 engineering and technology ,Computational Physics (physics.comp-ph) ,Markov model ,020801 environmental engineering ,Computational Engineering, Finance, and Science (cs.CE) ,Stochastic differential equation ,symbols.namesake ,Distribution (mathematics) ,symbols ,State space ,Statistical physics ,Diffusion (business) ,Computer Science - Computational Engineering, Finance, and Science ,Porous medium ,Physics - Computational Physics ,Water Science and Technology - Abstract
Monte Carlo (MC) simulations of transport in random porous networks indicate that for high variances of the log-normal permeability distribution, the transport of a passive tracer is non-Fickian. Here we model this non-Fickian dispersion in random porous networks using discrete temporal Markov models. We show that such temporal models capture the spreading behavior accurately. This is true despite the fact that the slow velocities are strongly correlated in time, and some studies have suggested that the persistence of low velocities would render the temporal Markovian model inapplicable. Compared to previously proposed temporal stochastic differential equations with case specific drift and diffusion terms, the models presented here require fewer modeling assumptions. Moreover, we show that discrete temporal Markov models can be used to represent dispersion in unstructured networks, which are widely used to model porous media. A new method is proposed to extend the state space of temporal Markov models to improve the model predictions in the presence of extremely low velocities in particle trajectories and extend the applicability of the model to higher temporal resolutions. Finally, it is shown that by combining multiple transitions, temporal models are more efficient for computing particle evolution compared to correlated CTRW with spatial increments that are equal to the lengths of the links in the network.
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- 2018
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93. Molecular beam scattering of a diatomic molecule from a solid surface in case of strong rotational non-equilibrium
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Nemanja Andric and Patrick Jenny
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Fluid Flow and Transfer Processes ,Mechanics of Materials ,Mechanical Engineering ,Computational Mechanics ,Condensed Matter Physics - Abstract
In this work, a numerical study on molecular beam scattering of a nitrogen molecule from a graphite surface has been performed. The study was carried out using the molecular dynamics method. The focus of the study is mainly placed on investigating the scattering dynamics in the case of strong rotational non-equilibrium, defined here as a state in which rotational temperature of a molecule strongly deviates from the room temperature. To that end, the incident beam velocity and initial rotational energy of nitrogen molecules have been varied greatly in order to capture a broad range of possible initial states. The obtained results provide valuable insight into the nature of energy transfer occurring during collisions and help to quantify the intensity of rotational-translational coupling between inner kinetic modes in gas-surface collisions. Consequently, the collected data can potentially be used for more accurate characterization of the respective phenomena and improve the quality of boundary models used in rarefied gas flow simulations. ISSN:1070-6631 ISSN:1089-7666 ISSN:0031-9171
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- 2022
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94. Modeling of shear failure in fractured reservoirs with a porous matrix
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Patrick Jenny and Rajdeep Deb
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Shearing (physics) ,Finite volume method ,business.industry ,Numerical analysis ,Poromechanics ,Linear elasticity ,0211 other engineering and technologies ,Basis function ,02 engineering and technology ,Slip (materials science) ,Structural engineering ,Mechanics ,01 natural sciences ,Physics::Geophysics ,Computer Science Applications ,Physics::Fluid Dynamics ,010101 applied mathematics ,Computational Mathematics ,Computational Theory and Mathematics ,Fluid dynamics ,0101 mathematics ,Computers in Earth Sciences ,business ,Geology ,021101 geological & geomatics engineering - Abstract
A finite volume-based numerical modeling framework using a hierarchical fracture representation (HFR) has been developed to compute flow-induced shear failure. To accurately capture the mechanics near fracture manifolds, discontinuous basis functions are employed which ensure continuity of the displacement gradient across fractures. With these special basis functions, traction and compressive forces on the fracture segment can be calculated without any additional constraints, which is extremely useful for estimating the irreversible displacement along the fracture (slip) based on a constitutive friction law. The method is further extended to include slip-dependent hydraulic aperture change and grid convergent results are obtained. Further, the change in hydraulic aperture is modeled using an asymptotic representation which respects the experimentally observed behavior of pore volume dilation due to shear slip. The model allows the initial rapid increase in hydraulic aperture due to shear slip and asymptotically approaches a finite value after repeated shearing of a fracture segment. This aperture increase is the only feedback for mechanics into the fluid flow for a linear elastic mechanics problem. The same model is also extended to include poroelastic relations between flow and mechanics solver. The grid convergence result in the case of poroelastic flow-mechanics coupling for flow-induced shear failure is also obtained. This proves the robustness of the numerical and analytical modeling of fracture and friction in the extended finite volume method (XFVM) set-up. Finally, a grid convergent result for seismic moment magnitude for single fracture and fracture network with random initial hydraulic and friction properties is also obtained. The b-value, which represents the slope of seismic moment occurrence frequency decay vs seismic moment magnitude, which is approximately constant in a semi-logarithmic plot, is estimated. The numerical method leads to converged b-values for both single fracture and fracture network simulations, as grid and time resolutions are increased. For the resulting linear system, a sequential approach is used, that is, first, the flow and then the mechanics problems are solved. The new modeling framework is very useful to predict seismicity, permeability, and flow evolution in geological reservoirs. This is demonstrated with numerical simulations of enhancing a geothermal system.
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- 2017
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95. Finite volume-based modeling of flow-induced shear failure along fracture manifolds
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Patrick Jenny and Rajdeep Deb
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business.industry ,Computational Mechanics ,010103 numerical & computational mathematics ,Mechanics ,Structural engineering ,Geotechnical Engineering and Engineering Geology ,01 natural sciences ,Physics::Geophysics ,Physics::Fluid Dynamics ,010101 applied mathematics ,Shear modulus ,Shear rate ,Simple shear ,Mechanics of Materials ,Critical resolved shear stress ,Shear stress ,Shear strength ,General Materials Science ,Shear velocity ,0101 mathematics ,Shear flow ,business - Abstract
Summary In this paper, a numerical model to predict flow-induced shear failure along pre-existing fractures is presented. The framework is based on a discrete fracture representation embedded in a continuum describing the damaged matrix. A finite volume method is used to compute both flow and mechanical equilibrium, whereas specifically tailored basis functions are used to account for the physics at discontinuities. The failure criterion is based on a maximum shear strength limit, which changes with varying compressive stress on the fracture manifold. The displacements along fracture manifolds are obtained such that force balance is achieved under conditions, where shear stress of the failing fracture segment is constrained to the maximum shear strength at the segment. Simultaneously, the fluid pressure is computed independently of the shear slip. A relaxation model approach is used to obtain the maximum shear limit on the fracture manifold, which leads to grid convergence.
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- 2017
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96. Modeling wetting-phase relative permeability hysteresis based on subphase evolution
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Patrick Jenny and Karim Khayrat
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Hydrogeology ,Materials science ,0208 environmental biotechnology ,Flow (psychology) ,Thermodynamics ,02 engineering and technology ,020801 environmental engineering ,Computer Science Applications ,Computational Mathematics ,Hysteresis ,Computational Theory and Mathematics ,Volume (thermodynamics) ,Phase (matter) ,Imbibition ,Geotechnical engineering ,Wetting ,Computers in Earth Sciences ,Relative permeability - Abstract
A recently introduced subphase framework for modeling the nonwetting phase relative permeability is extended to the wetting phase. Within this framework, the wetting phase is divided into four subphases, which are distinguished by their connectivity; backbone, dendritic, isolated and corner-film subphases. The subphase saturations evolve according to inter-subphase volume transfer terms, which require modeling. An advantage of distinguishing the subphases is that wetting phase relative permeability relations as functions of these constituent subphases can be developed. In order to develop models for the inter-subphase volume transfer and the wetting phase relative permeability in a strongly wetted system, quasi-static flow simulations in pore networks were conducted to analyze the evolution of the wetting subphases during drainage and imbibition. The simulation results suggest that hysteresis trends apparent in experimentally obtained wetting phase relative permeability curves for Berea sandstone may be explained by accounting for corner-film flow.
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- 2017
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97. HE-LHC: The High-Energy Large Hadron Collider Future Circular Collider Conceptual Design Report Volume 4
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Pushpalatha C Bhat, B. Seeber, C. Pagliarone, Marco Statera, Victor P. Goncalves, Daria Astapovych, W. Bartmann, S. Iwamoto, M. Mentink, Alessandro Tricoli, E. R. Bielert, Laurent Chevalier, Patrick Koppenburg, Marco Calviani, C. Montag, P. Spiller, Jan Uythoven, P. Di Nezza, G. Guillermo Canton, B. Sailer, Markus Elsing, Sara Khatibi, Luca Vecchi, Luigi Palumbo, J. P. Penttinen, T. Podzorny, Maneesh Kumar, J. M. Rifflet, C. Kotnig, Jean Zinn-Justin, Christopher B. Verhaaren, A. Chernoded, Alessandro Bertarelli, L. M. Tkachenko, C. Koeberl, P. J. Mallon, M. Takeuchi, W. Venturini Delsolaro, G. Lamanna, S. Weinzierl, J. Gao, W. Kaabi, David D'Enterria, D. Barna, Paolo Castelnovo, Rajat Gupta, Oliver Boine-Frankenheim, Adarsh Pyarelal, Andreas Salzburger, Tessa Charles, M.E. Biagini, O. Panella, M. Stuart, A. Kollegger, V. Garcia Diaz, Olcay Bolukbasi, Maurizio Pierini, H. Aksakal, Tord Riemann, Abhishek M. Iyer, V. Shiltsev, D. Buttazzo, J. Blümlein, Prateek Agrawal, L. Sestini, Martin Bauer, Felicitas Pauss, S. Fiorendi, F. Bossu, Marco Nardecchia, C. Leonidopoulos, Wojciech Kotlarski, A. Saba, I. Bautista-Guzmán, W. Hillert, Giorgio Ambrosio, T. Lehtinen, Michael Andrew Parker, Silvia Taroni, Gian F. Giudice, Ph. Lebrun, Johann A. Briffa, T. Risselada, Giuseppe Lerner, A. Lechner, L. S. Miralles, M. Kuze, J. M. Valet, P. S. B. Dev, S. Holleis, Ph. Schwemling, M. Biglietti, S. Banerjee, Thomas Schörner-Sadenius, A. Sanz Ull, V. Tikhomirov, S. Savelyeva, Jiayin Gu, D. Zhou, Federico Ravotti, S. A. Bogacz, Daniele Mirarchi, R. Tomás García, Yann Coadou, F. Yu, Y. Cai, T. Lari, F. Holdener, D. Shwartz, C. Bhat, Ramesh Gupta, Markus Klute, E. Palmieri, P. Collier, Branislav Sitar, Yves Sirois, Livio Fanò, S. Rojas-Torres, E. Locci, Ruben Garcia Alia, I. Božović Jelisavić, R. Chehab, J. A. Aguilar-Saavedra, M. Pasquali, A. Di Cicco, Bernhard Auchmann, Klaus Heinemann, Alessia Tricomi, D. Lucchesi, B. Haerer, M. Morrone, Paolo Giacomelli, Sonia Carra, A. Senol, Ivan Koop, Luca Silvestrini, Anna Stakia, Heather Gray, E. Skordis, A. D. Kovalenko, Paul Langacker, R. Li, Bernardo Bordini, R. Rata, Arjan Verweij, Shehu S. AbdusSalam, Andrey Karyukhin, U. van Rienen, Gianluigi Arduini, Bernhard Holzer, S. A. Nikitin, S. S. Kozub, Satoshi Mishima, B. Di Micco, S. Izquierdo Bermudez, N. Pukhaeva, Nigel Watson, F. Prino, Jean-Michel Sallese, Sotirios Vlachos, Alessandro Vicini, A. Valassi, Daniel Treille, F. Dordei, A. M. Fernandez Navarro, B. Dziewit, Marcello Abbrescia, J. M. Hauptman, I. Chaikovska, Paolo Giubellino, Michael J. Baker, V.V. Kashikhin, Friedrich Lackner, Filippo Sala, A. Langner, D. Pulikowski, H. Eriksson, Matteo Turri, Andrea Wulzer, M. Aiba, Lisa Borgonovi, I. Morozov, V. Haurylavets, J. F. Croteau, S. Boselli, L. A. Gonzalez Gomez, Claudia Tambasco, F. Mahmoudi, Sébastien Descotes-Genon, A. Luciani, Pavel Piminov, M. Varasteh, T. Herzig, Sandra Aumon, Cristina Bernini, Joseph Bramante, Roberta Arnaldi, G. Zick, Daniel Schulte, R. Santoro, Anna Kulesza, I. Turk Cakir, M. Nonis, Silvia Posada Arias, Livia Soffi, T. Wojtoń, E. Cennini, Florian Bauer, B. Rousset, J.-L. Grenard, C. Neubüser, Frederic Derue, Loukas Gouskos, Rainer Wallny, G. Calderini, M. Merk, M. Mühlegger, Roberto Cimino, M. Ramsey-Musolf, P. Rebello Teles, Mario Galanti, Mikhail Shaposhnikov, A. Andreazza, Maria Vittoria Garzelli, Masaya Ishino, José W. F. Valle, Colin Bernet, G. Velev, Cristina Botta, E. Fischer, J. Malclés, Giuseppe Montenero, Tripurari Srivastava, E. Renner, Shahnam Gorgi Zadeh, D. Cantore-Cavalli, Paul Laycock, J. Komppula, Simon C. Hopkins, Helmut Burkhardt, Eric Lancon, I. Aichinger, Andre Sznajder, F. Bordry, Massimo Giovannozzi, Aidan Robson, Anna Giunta, A. Carvalho, S. Farinon, Daniel Wollmann, M. Fouaidy, Martti Raidal, R. Gerard, Giovanni Volpini, U. Niedermayer, A. Alekou, Alexander J.G. Lunt, Vincenzo Cavasinni, Andrzej Siodmok, U. Kaya, Matthias Schott, Marumi Kado, S. A. Arsenyev, José Zurita, John Osborne, Patrick Meade, Gianmarco Bovone, G. Li, Klaus Schlenga, Antti Stenvall, D. Duellmann, Werner Riegler, I. Garzia, Yasuyuki Okumura, G. Pikurs, F. Maltoni, Massimo Sorbi, M. Arzeo, B. Strauss, Y. W. Baek, Mauro Chiesa, K. Ilyina-Brunner, Javier L. Albacete, R. Farinelli, C. Pes, Nicolas Morange, S. M. Zernov, U. Wagner, Emmanuelle Perez, G. G. Da Silveira, J. Neundorf, Néstor Armesto, T. Hahn, Roman N. Lee, Roderik Bruce, B. Y. Sharkov, T. du Pree, G. Cibinetto, Evelin Meoni, R. Rinaldesi, James A. Ellison, Radim Slovak, Silvia Franchino, Mikko Laine, T. Pugnat, S. P. Das, Yuji Enari, Emanuela Barzi, Cihan Bayindir, R. Boels, Jana Faltova, M. Moreno Llácer, Scott A. Yost, Michael Spannowsky, Florian Burkart, Marcin Chrzaszcz, K. Suzuki, Luca Trentadue, S. Masciocchi, Gilad Perez, Steve Peggs, K. Sugita, Eleonora Belli, Carmine Senatore, K. Y. Oyulmaz, Aldo Deandrea, Irakli Minashvili, Desmond P. Barber, M. I. Martínez-Hernández, A. Apyan, S. Petracca, Mikael Chala, Urs Achim Wiedemann, T. Sian, Olivier Deschamps, R. Monge, G. Avrillaud, Jan Kieseler, Hubert Spiesberger, J. Maitre, G. D. Shirkov, M. Hofer, Emanuela Sirtori, Sinan Kuday, Kirill Skovpen, Sara Casalbuoni, Johann Usovitsch, N. Chen, G. Tejeda-Muñoz, F. Bellini, E. Chyhyrynets, Michael Stöger-Pollach, M. Vogel, J. G. Mendes Saraiva, A. Rivetti, M. Podeur, Luc Poggioli, V. A. Gromov, R. Sirvinskaite, S. B. Leith, Giancarlo D'Ambrosio, Tony Price, Philippe Mermod, Rabindra N. Mohapatra, T. Mitshuhashi, Koji Terashi, Leonel Ferreira, L. Vale Silva, N. Muchnoi, J. L. Stanyard, Thomas Marriott-Dodington, A. Andriatis, Oleg Solovyanov, A. Daljevec, A. Butterworth, S. Myers, D. Chanal, Tatiana Pieloni, M. Rodríguez-Cahuantzi, G. Nardini, D. Boscherini, Kazuhito Ohmi, James Molson, S. Kowalski, Christoph Haberstroh, Martin Aleksa, K. Kershaw, M. Mulder, Leonid Rivkin, G. Vorotnikov, Luigi Salvatore Esposito, J. Kalinowski, Michele Cascella, Francesco Giffoni, Alessandro Polini, Georges Azuelos, M. Prioli, Wolfgang Altmannshofer, S. K. Patra, H. J. He, J. J. Aguilera-Verdugo, Hannu Paukkunen, P. Chomaz, Shoji Asai, Nicolas Magnin, Gavin P. Salam, R. Wang, F. Avino, Alexander Romanenko, A. Rossi, Steve Muanza, Richard Ruiz, Dmitry Teytelman, S. Klöppel, S. Atieh, M. Mohammadi Najafabadi, L. Apolinario, Andrea Tesi, M. Maggiora, A. Falkowski, Janusz Gluza, M. Sauvain, Hamzeh Khanpour, S. Chance, Ansgar Denner, Ma. Greco, Andreas Papaefstathiou, Manuela Boscolo, Joydeep Chakrabortty, E. Franco, R. R. Bosley, G. Peón, Fred Olness, Simone Alioli, Andrea Gaddi, M. K. Sullivan, M. Segreti, M. Panareo, Florian Goertz, Z. G. Zhao, H. Chanal, O. Martin, P. Azzurri, Agnieszka Chmielinska, M. Kordiaczyńska, O. Brunner, J. Von Ahnen, Jose Santiago, K. Foraz, Y. Alexahin, Marcello Mannelli, Christian Schwanenberger, S. Ganjour, Simone Marzani, T. M. Taylor, S. Di Vita, J. Womersley, I. Karpov, Valentina Morretta, Saverio D'Auria, Patrick Draper, B. Hacışahinoğlu, E. Gorini, Andrew J. Long, S. La Mendola, G. Zevi Dell Porta, I. Abdyukhanov, M. Cobal, Luca Marzola, E. Rochepault, A. Kusina, German Rodrigo, R. Schmidt, Jan Steggemann, E. Premat, P. Slavich, F. Gianotti, P. Jarry, Ram Krishna Dewanjee, L. Felsberger, T. Martinez, A. Niemi, Jürgen Reuter, P. A. Bruckman de Renstrom, Ryu Sawada, J. T. Childers, Gelsomina Catalano, P. Barjhoux, O. R. Blanco-García, Pilar Hernández, H. Correia-Rodrigues, V. Ippolito, S. De Curtis, Juan Rojo, Ayberk Yilmaz, S. Baird, Morteza Khatiri Yanehsari, Enrico Scomparin, Daniel Appelö, J. Kozaczuk, Matthew Jones, B. Caiffi, C. Del Bo, Susanna Guiducci, Giuliano Panico, M. Knecht, J. Coupard, M. Ciuchini, H. Kritscher, Claire Gwenlan, P. Costa Pinto, Thibaut Lefèvre, N. Bellegarde, Christian Scheuerlein, P. Ferreira da Silva, M. Verducci, X. Ruan, H. Pikhartova, Juan M. O'Callaghan, Kazuro Furukawa, D. Saez de Jauregui, Maria Rescigno, Stephan Eisenhardt, Andrea Dainese, Z. Drásal, G. H. Corral, J. M. Camalich, John Ellis, E. Gabrielli, L. Rumyantsev, A. Caliskan, K. Brunner, K. Tang, P. Sopicki, J. Fan, Marcin Kucharczyk, S. Gorgi Zadeh, Carlos A. Salgado, Simone Bologna, Y. Muttoni, A. Chancé, Patrick Jenny, Mark Boland, G. Yang, G. Wilkinson, Roger J. Hernández-Pinto, M. Novák, Gennady Stupakov, E. Jensen, Lance D. Cooley, Torbjörn Sjöstrand, S. Su, Matthew Luzum, J. Casas, Per Osland, T. Robens, Oscar A. Sampayo, Evgeny Levichev, P. N. Ratoff, G. Rolandi, M. A. Valdivia Garcia, Anthony Keith Morley, L. van Riesen-Haupt, A. Sublet, M. A. Mazzoni, J.L. Gutierrez, A. Abramov, Abbas Kenan Ciftci, A. Provino, L. Delle Rose, John Fox, Barry M. Dillon, V. Smirnov, G. N. Taylor, Anke-Susanne Müller, C. Pira, Fulvio Piccinini, A. Faus-Golfe, Pietro Antonioli, S. Sanfilippo, Julien Cogan, A. Ribon, Andrew Hutton, Frank Zimmermann, Lev Dudko, Erez Etzion, J. Polinski, G. Bencivenni, M. Gil Costa, L. K. Gladilin, Yannis Papaphilippou, Michael Spira, Maria Paola Lombardo, M. Fiascaris, Darius A. Faroughy, S. O. Kara, Peter Braun-Munzinger, A. Wohlfahrt, A. A. Krasnov, S.A. Gourlay, W. Da Silva, Jacqueline Keintzel, Radja Boughezal, Renat Sadykov, L. R. Sulak, Valentin V. Khoze, T. Tydecks, S. Puławski, Daniel de Florian, Pedro Schwaller, A. Akay, Nicola Serra, Sukanta Dutta, Christophe Royon, Alessandro Ricci, A. Kuendig, C. G. Honorato, K. Kołodziej, L. Deniau, Michael Kramer, J. Ferradas Troitino, A. Arbey, A. M. Staśto, Marcel Demarteau, Ralph Aßmann, O. Grimm, D. Forkel-Wirth, Owain Rhodri Jones, A. M. Kolano, G. Chiarello, William Trischuk, Andrea Dell'Acqua, Elisabetta Gallo, H. Song, Frank Petriello, N. Ibarrola, C. Colldelram, A. I. Ryazanov, A. Meier, Phillip Allport, J. de Blas, S. Chattopadhyay, Massimo Florio, X. Jiang, Bertrand Baudouy, T. Otto, Tevong You, Christoph Englert, Roberto Pittau, G. M. Bilei, Matthew McCullough, N. S. Ramírez-Uribe, J. Charles, Amalia Ballarino, Federico Antinori, A. V. Kotwal, P. Le Guen, Berndt Müller, Chiara Roda, Xavier Buffat, D. K. Hong, Matthias Liepe, G. Gorine, V. A. Okorokov, D. Bozzini, N. Simand, Giuseppe Francesco Tartarelli, C. Marquet, R. Contino, A. M. Teixeira, R. Trant, Roberto Losito, M. Quispe, Valery I. Telnov, Helga Timko, D. Lissauer, Giulio Aielli, Giorgio Chiarelli, M. J. Baldwin, A. Winter, X. Sarasola, E. E. Boos, Aleandro Nisati, Cedric Garion, Monica D'Onofrio, S. M. Gascon-Shotkin, Daniele Barducci, G. Rosaz, Nathaniel Craig, L. D’Aloia Schwartzentruber, A. Falou, A. Henriques, Tobias Hurth, Michael Eisterer, Andreas Grau, Austin Ball, D. Delikaris, P. A. McIntosh, E. Graverini, Kadri Ozdemir, F. Valchkova, Marco Zanetti, Guenakh Mitselmakher, S. Albergo, Peter Levai, Caterina Vernieri, F. Stivanello, Michael Barnes, Henri Bachacou, Daniel Fournier, L. T. Wang, D. Boutin, S. Moretti, B. Riemann, Michael Murray, Aleksandr Azatov, C. T. A. Cook, Valentina Maria Cairo, J. B. De Vivie De Regie, H. Schmickler, M. Schenk, Georgios Voutsinas, André Schöning, S. G. Bondarenko, Giorgio Bellomo, Andrei Seryi, Jane Nachtman, Clement Helsens, E. De Lucia, Jakob Salfeld-Nebgen, Lorenzo Pezzotti, Z. Townsend, B. Dalena, Mogens Dam, Yasar Onel, Yi-Ming Zhong, B. Curé, A. A. Kolomiets, A. M. Valente-Feliciano, Laurette Ponce, David Olivier Jamin, P. Krkotic, Alexandre Louzguiti, Marina Putti, Holger Podlech, Petr Volkov, M. Angelucci, F. Duval, I. Hiekkanen, W. M. Yao, Giancarlo Ferrera, C. Lorin, Y. Dydyshka, Kurt R. Peters, Gergely Gabor Barnafoldi, V. Vysotsky, V. Arı, E. Pilicer, M. Chamizo-Llatas, G. Kuhlmann, Hans Quack, R. Valizadeh, Tiina Salmi, Thomas Kramer, Adam Jeff, A. Abada, J. M. Duval, J. Abelleira Fernandez, A. Leveratto, E. Tal Hod, X. Wu, Laurent Serin, Sarah Aull, Samuele Mariotto, A. Poiron, Sabine Riemann, P. Selva, V. I. Pantsyrny, Gianluca Valentino, K. Kahle, S. Aune, K. Potamianos, Eros Cazzato, M. Giovannetti, Petr Mandrik, S. Sidorov, F. 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Gobbi, Michael Hance, A. J. Barr, V. Del Duca, V. Guzey, M. Pont, Michele Selvaggi, Oliver Brüning, J. Barreiro Guimarães da Costa, A. Drago, Y. Zhang, Giovanni Punzi, Viktor Matveev, Anadi Canepa, Clemens Lange, B. L. Militsyn, Martijn Mulders, Max Klein, V. D’Auria, M. Mylona, Valeria Braccini, S. DasBakshi, David Calvet, Sophia Borowka, David Marzocca, S. Jadach, A. A. Pankov, Christophe Ochando, A. A. Tudora, I. Masina, Jure Zupan, A. Preinerstorfer, Benjamin Fuks, H. K. Soltveit, G. Rolando, E.E. Perepelkin, T. G. Rizzo, Saleh Sultansoy, Federico Roncarolo, K. Elsener, R. Q. Pan, P. Zhuang, David Attié, Jac Perez, K. Kravalis, F. Anulli, V. Ruhlmann-Kleider, S. Malvezzi, Steffen A. Bass, E. La Francesca, Heinz Pernegger, K. Grzanka, M. T. Tiirakari, Alberto Ventura, Alessandro Cerri, Marco Peruzzi, Eric Montesinos, O. Etisken, F. Grancagnolo, S. Kartal, H. Humer, Oliver Fischer, M. Primavera, Marco Toliman Lucchini, P. Vedrine, Felix Kling, M. Altınlı, Sergio Calatroni, C. Han, Olivier Leroy, R. T. D’Agnolo, N. Klinkenberg, A. Audurier, Tatsushi Nakamoto, Ali Bozbey, Bernd A. Kniehl, Carl J. Debono, I. P. J. Shipsey, Gregorio Bernardi, Paolo Nason, William James Fawcett, J. M. Jiménez, D. Denisov, M. Serluca, David Curtin, Arif Akhundov, M. García Pérez, Iacopo Vivarelli, Emanuele Bacchiocchi, Markus Zerlauth, Julia Hrdinka, F. Butin, F. Müller, D. Tikhonov, Jorg Wenninger, A. Kilic, Fabrizio Ferro, J. Tanaka, S. A. Antipov, Miroslav Atanasov, S. Kuttimalai, A. Y. Starikov, F. R. Blánquez, S. V. Furuseth, G. Gaudio, L. Malgeri, J. Curti, B. Turbiarz, S. Li, A. Romanov, Costas G. Papadopoulos, Brennan Goddard, Frank Krauss, Lidija Zivkovic, Toms Torims, Michaela Lackner, D. A. Lyubimtsev, G. Borghello, J. F. Grosse-Oetringhaus, A. Bogomyagkov, H. Duran Yildiz, N. Foppiani, Arthur Schaffer, J. Zhou, D. Liberati, Vincenzo Guidi, Naeem A. Tahir, M. Besançon, Daniel Schoerling, Joe Incandela, Giacomo Polesello, O. Cakir, I. Ruehl, Ruggero Vaglio, Z. 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Zurita, J, Işık Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü, Işık University, Faculty of Engineering, Department of Civil Engineering, Bayındır, Cihan, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. RF&MW - Grup de Recerca de sistemes, dispositius i materials de RF i microones, Abada A., Abbrescia M., AbdusSalam S.S., Abdyukhanov I., Abelleira Fernandez J., Abramov A., Aburaia M., Acar A.O., Adzic P.R., Agrawal P., Aguilar-Saavedra J.A., Aguilera-Verdugo J.J., Aiba M., Aichinger I., Aielli G., Akay A., Akhundov A., Aksakal H., Albacete J.L., Albergo S., Alekou A., Aleksa M., Aleksan R., Alemany Fernandez R.M., Alexahin Y., Alia R.G., Alioli S., Alipour Tehrani N., Allanach B.C., Allport P.P., Altinli M., Altmannshofer W., Ambrosio G., Amorim D., Amstutz O., Anderlini L., Andreazza A., Andreini M., Andriatis A., Andris C., Andronic A., Angelucci M., Antinori F., Antipov S.A., Antonelli M., Antonello M., Antonioli P., Antusch S., Anulli F., Apolinario L., Apollinari G., Apollonio A., Appelo D., Appleby R.B., Apyan A., Arbey A., Arbuzov A., Arduini G., Ari V., Arias S., Armesto N., Arnaldi R., Arsenyev S.A., Arzeo M., Asai S., Aslanides E., Assmann R.W., Astapovych D., Atanasov M., Atieh S., Attie D., Auchmann B., Audurier A., Aull S., Aumon S., Aune S., Avino F., Avrillaud G., Aydin G., Azatov A., Azuelos G., Azzi P., Azzolini O., Azzurri P., Bacchetta N., Bacchiocchi E., Bachacou H., Baek Y.W., Baglin V., Bai Y., Baird S., Baker M.J., Baldwin M.J., Ball A.H., Ballarino A., Banerjee S., Barber D.P., Barducci D., Barjhoux P., Barna D., Barnafoldi G.G., Barnes M.J., Barr A., Barranco Garcia J., Barreiro Guimaraes da Costa J., Bartmann W., Baryshevsky V., Barzi E., Bass S.A., Bastianin A., Baudouy B., Bauer F., Bauer M., Baumgartner T., Bautista-Guzman I., Bayindir C., Beaudette F., Bedeschi F., Beguin M., Bellafont I., Bellagamba L., Bellegarde N., Belli E., Bellingeri E., Bellini F., Bellomo G., Belomestnykh S., Bencivenni G., Benedikt M., Bernardi G., Bernardi J., Bernet C., Bernhardt J.M., Bernini C., Berriaud C., Bertarelli A., Bertolucci S., Besana M.I., Besancon M., Beznosov O., Bhat P., Bhat C., Biagini M.E., Biarrotte J.-L., Bibet Chevalier A., Bielert E.R., Biglietti M., Bilei G.M., Bilki B., Biscari C., Bishara F., Blanco-Garcia O.R., Blanquez F.R., Blekman F., Blondel A., Blumlein J., Boccali T., Boels R., Bogacz S.A., Bogomyagkov A., Boine-Frankenheim O., Boland M.J., Bologna S., Bolukbasi O., Bomben M., Bondarenko S., Bonvini M., Boos E., Bordini B., Bordry F., Borghello G., Borgonovi L., Borowka S., Bortoletto D., Boscherini D., Boscolo M., Boselli S., Bosley R.R., Bossu F., Botta C., Bottura L., Boughezal R., Boutin D., Bovone G., Bozovic Jelisavic I., Bozbey A., Bozzi C., Bozzini D., Braccini V., Braibant-Giacomelli S., Bramante J., Braun-Munzinger P., Briffa J.A., Britzger D., Brodsky S.J., Brooke J.J., Bruce R., Bruckman De Renstrom P., Bruna E., Bruning O., Brunner O., Brunner K., Bruzzone P., Buffat X., Bulyak E., Burkart F., Burkhardt H., Burnet J.-P., Butin F., Buttazzo D., Butterworth A., Caccia M., Cai Y., Caiffi B., Cairo V., Cakir O., Calaga R., Calatroni S., Calderini G., Calderola G., Caliskan A., Calvet D., Calviani M., Camalich J.M., Camarri P., Campanelli M., Camporesi T., Canbay A.C., Canepa A., Cantergiani E., Cantore-Cavalli D., Capeans M., Cardarelli R., Cardella U., Cardini A., Carloni Calame C.M., Carra F., Carra S., Carvalho A., Casalbuoni S., Casas J., Cascella M., Castelnovo P., Castorina G., Catalano G., Cavasinni V., Cazzato E., Cennini E., Cerri A., Cerutti F., Cervantes J., Chaikovska I., Chakrabortty J., Chala M., Chamizo-Llatas M., Chanal H., Chanal D., Chance S., Chance A., Charitos P., Charles J., Charles T.K., Chattopadhyay S., Chehab R., Chekanov S.V., Chen N., Chernoded A., Chetvertkova V., Chevalier L., Chiarelli G., Chiarello G., Chiesa M., Chiggiato P., Childers J.T., Chmielinska A., Cholakian A., Chomaz P., Chorowski M., Chou W., Chrzaszcz M., Chyhyrynets E., Cibinetto G., Ciftci A.K., Ciftci R., Cimino R., Ciuchini M., Clark P.J., Coadou Y., Cobal M., Coccaro A., Cogan J., Cogneras E., Collamati F., Colldelram C., Collier P., Collot J., Contino R., Conventi F., Cook C.T.A., Cooley L., Corcella G., Cornell A.S., Corral G.H., Correia-Rodrigues H., Costanza F., Costa Pinto P., Couderc F., Coupard J., Craig N., Crespo Garrido I., Crivellin A., Croteau J.F., Crouch M., Cruz Alaniz E., Cure B., Curti J., Curtin D., Czech M., Dachauer C., D'Agnolo R.T., Daibo M., Dainese A., Dalena B., Daljevec A., Dallapiazza W., D'Aloia Schwartzentruber L., Dam M., D'Ambrosio G., Das S.P., DasBakshi S., da Silva W., da Silveira G.G., D'Auria V., D'Auria S., David A., Davidek T., Deandrea A., de Blas J., Debono C.J., De Curtis S., De Filippis N., de Florian D., Deghaye S., de Jong S.J., Del Bo C., Del Duca V., Delikaris D., Deliot F., Dell'Acqua A., Delle Rose L., Delmastro M., De Lucia E., Demarteau M., Denegri D., Deniau L., Denisov D., Denizli H., Denner A., d'Enterria D., de Rijk G., De Roeck A., Derue F., Deschamps O., Descotes-Genon S., Dev P.S.B., de Vivie de Regie J.B., Dewanjee R.K., Di Ciaccio A., Di Cicco A., Dillon B.M., Di Micco B., Di Nezza P., Di Vita S., Doblhammer A., Dominjon A., D'Onofrio M., Dordei F., Drago A., Draper P., Drasal Z., Drewes M., Duarte L., Dubovyk I., Duda P., Dudarev A., Dudko L., Duellmann D., Dunser M., du Pree T., Durante M., Duran Yildiz H., Dutta S., Duval F., Duval J.M., Dydyshka Y., Dziewit B., Eisenhardt S., Eisterer M., Ekelof T., El Khechen D., Ellis S.A., Ellis J., Ellison J.A., Elsener K., Elsing M., Enari Y., Englert C., Eriksson H., Eskola K.J., Esposito L.S., Etisken O., Etzion E., Fabbricatore P., Falkowski A., Falou A., Faltova J., Fan J., Fano L., Farilla A., Farinelli R., Farinon S., Faroughy D.A., Fartoukh S.D., Faus-Golfe A., Fawcett W.J., Felici G., Felsberger L., Ferdeghini C., Fernandez Navarro A.M., Fernandez-Tellez A., Ferradas Troitino J., Ferrara G., Ferrari R., Ferreira L., Ferreira da Silva P., Ferrera G., Ferro F., Fiascaris M., Fiorendi S., Fiorio C., Fischer O., Fischer E., Flieger W., Florio M., Fonnesu D., Fontanesi E., Foppiani N., Foraz K., Forkel-Wirth D., Forte S., Fouaidy M., Fournier D., Fowler T., Fox J., Francavilla P., Franceschini R., Franchino S., Franco E., Freitas A., Fuks B., Furukawa K., Furuseth S.V., Gabrielli E., Gaddi A., Galanti M., Gallo E., Ganjour S., Gao J., Garcia Diaz V., Garcia Perez M., Garcia Tabares L., Garion C., Garzelli M.V., Garzia I., Gascon-Shotkin S.M., Gaudio G., Gay P., Ge S.-F., Gehrmann T., Genest M.H., Gerard R., Gerigk F., Gerwig H., Giacomelli P., Giagu S., Gianfelice-Wendt E., Gianotti F., Giffoni F., Gilardoni S.S., Gil Costa M., Giovannetti M., Giovannozzi M., Giubellino P., Giudice G.F., Giunta A., Gladilin L.K., Glukhov S., Gluza J., Gobbi G., Goddard B., Goertz F., Golling T., Goncalves V.P., Goncalo R., Gonzalez Gomez L.A., Gorgi Zadeh S., Gorine G., Gorini E., Gourlay S.A., Gouskos L., Grancagnolo F., Grassellino A., Grau A., Graverini E., Gray H.M., Greco M., Grenard J.-L., Grimm O., Grojean C., Gromov V.A., Grosse-Oetringhaus J.F., Grudiev A., Grzanka K., Gu J., Guadagnoli D., Guidi V., Guiducci S., Guillermo Canton G., Gunaydin Y.O., Gupta R., Gupta R.S., Gutierrez J., Gutleber J., Guyot C., Guzey V., Gwenlan C., Haberstroh C., Hacisahinoglu B., Haerer B., Hahn K., Hahn T., Hammad A., Han C., Hance M., Hannah A., Harris P.C., Hati C., Haug S., Hauptman J., Haurylavets V., He H.-J., Hegglin A., Hegner B., Heinemann K., Heinemeyer S., Helsens C., Henriques A., Hernandez P., Hernandez-Pinto R.J., Hernandez-Sanchez J., Herzig T., Hiekkanen I., Hillert W., Hoehn T., Hofer M., Hofle W., Holdener F., Holleis S., Holzer B., Hong D.K., Honorato C.G., Hopkins S.C., Hrdinka J., Hug F., Humann B., Humer H., Hurth T., Hutton A., Iacobucci G., Ibarrola N., Iconomidou-Fayard L., Ilyina-Brunner K., Incandela J., Infantino A., Ippolito V., Ishino M., Islam R., Ita H., Ivanovs A., Iwamoto S., Iyer A., Izquierdo Bermudez S., Jadach S., Jamin D.O., Janot P., Jarry P., Jeff A., Jenny P., Jensen E., Jensen M., Jiang X., Jimenez J.M., Jones M.A., Jones O.R., Jowett J.M., Jung S., Kaabi W., Kado M., Kahle K., Kalinovskaya L., Kalinowski J., Kamenik J.F., Kannike K., Kara S.O., Karadeniz H., Karaventzas V., Karpov I., Kartal S., Karyukhin A., Kashikhin V., Katharina Behr J., Kaya U., Keintzel J., Keinz P.A., Keppel K., Kersevan R., Kershaw K., Khanpour H., Khatibi S., Khatiri Yanehsari M., Khoze V.V., Kieseler J., Kilic A., Kilpinen A., Kim Y.-K., Kim D.W., Klein U., Klein M., Kling F., Klinkenberg N., Kloppel S., Klute M., Klyukhin V.I., Knecht M., Kniehl B., Kocak F., Koeberl C., Kolano A.M., Kollegger A., Kolodziej K., Kolomiets A.A., Komppula J., Koop I., Koppenburg P., Koratzinos M., Kordiaczynska M., Korjik M., Kortner O., Kostka P., Kotlarski W., Kotnig C., Kottig T., Kotwal A.V., Kovalenko A.D., Kowalski S., Kozaczuk J., Kozlov G.A., Kozub S.S., Krainer A.M., Kramer T., Kramer M., Krammer M., Krasnov A.A., Krauss F., Kravalis K., Kretzschmar L., Kriske R.M., Kritscher H., Krkotic P., Kroha H., Kucharczyk M., Kuday S., Kuendig A., Kuhlmann G., Kulesza A., Kumar M., Kusina A., Kuttimalai S., Kuze M., Kwon T., Lackner F., Lackner M., La Francesca E., Laine M., Lamanna G., La Mendola S., Lancon E., Landsberg G., Langacker P., Lange C., Langner A., Lankford A.J., Lansberg J.P., Lari T., Laycock P.J., Lebrun P., Lechner A., Lee K., Lee S., Lee R., Lefevre T., Le Guen P., Lehtinen T., Leith S.B., Lenzi P., Leogrande E., Leonidopoulos C., Leon-Monzon I., Lerner G., Leroy O., Lesiak T., Levai P., Leveratto A., Levichev E., Li G., Li S., Li R., Liberati D., Liepe M., Lissauer D.A., Liu Z., Lobko A., Locci E., Logothetis Agaliotis E., Lombardo M.P., Long A.J., Lorin C., Losito R., Louzguiti A., Low I., Lucchesi D., Lucchini M.T., Luciani A., Lueckhof M., Lunt A.J.G., Luzum M., Lyubimtsev D.A., Maggiora M., Magnin N., Mahmoud M.A., Mahmoudi F., Maitre J., Makarenko V., Malagoli A., Malcles J., Malgeri L., Mallon P.J., Maltoni F., Malvezzi S., Malyshev O.B., Mancinelli G., Mandrik P., Manfrinetti P., Mangano M., Manil P., Mannelli M., Marchiori G., Marhauser F., Mariani V., Marinozzi V., Mariotto S., Marquard P., Marquet C., Marriott-Dodington T., Martin R., Martin O., Martin Camalich J., Martinez T., Martinez Bruzual H., Martinez-Hernandez M.I., Martins D.E., Marzani S., Marzocca D., Marzola L., Masciocchi S., Masina I., Massimiliano A., Massironi A., Masubuchi T., Matveev V.A., Mazzoni M.A., McCullough M., McIntosh P.A., Meade P., Medina L., Meier A., Meignan J., Mele B., Mendes Saraiva J.G., Menez F., Mentink M., Meoni E., Meridiani P., Merk M., Mermod P., Mertens V., Mether L., Metral E., Migliorati M., Milanese A., Milardi C., Milhano G., Militsyn B.L., Millet F., Minashvili I., Minervini J.V., Miralles L.S., Mirarchi D., Mishima S., Missiaen D.P., Mitselmakher G., Mitshuhashi T., Mnich J., Mohammadi Najafabadi M., Mohapatra R.N., Mokhov N., Molson J.G., Monge R., Montag C., Montagna G., Monteil S., Montenero G., Montesinos E., Moortgat F., Morange N., Morello G., Moreno Llacer M., Moretti M., Moretti S., Morley A.K., Moros A., Morozov I., Morretta V., Morrone M., Mostacci A., Muanza S., Muchnoi N., Muhlegger M., Mulder M., Mulders M., Muller B., Muller F., Muller A.-S., Munilla J., Murray M.J., Muttoni Y., Myers S., Mylona M., Nachtman J., Nakamoto T., Nardecchia M., Nardini G., Nason P., Nergiz Z., Nesterenko A.V., Netto J.A., Nettstrater A., Neubuser C., Neundorf J., Niccoli F., Nicrosini O., Nie Y., Niedermayer U., Niedziela J., Niemi A., Nikitin S.A., Nisati A., No J.M., Nonis M., Nosochkov Y., Novak M., Novokhatski A., O'Callaghan J.M., Ochando C., Ogur S., Ohmi K., Oide K., Okorokov V.A., Okumura Y., Oleari C., Olness F.I., Onel Y., Ortino M., Osborne J., Osland P., Otto T., Oyulmaz K.Y., Ozansoy A., Ozcan V., Ozdemir K., Pagliarone C.E., Pais da Silva H.F., Palmieri E., Palumbo L., Pampaloni A., Pan R.-Q., Panareo M., Panella O., Panico G., Panizzo G., Pankov A.A., Pantsyrny V., Papadopoulos C.G., Papaefstathiou A., Papaphilippou Y., Parker M.A., Parma V., Pasquali M., Patra S.K., Patterson R., Paukkunen H., Pauss F., Peggs S., Penttinen J.-P., Peon G., Perepelkin E.E., Perez E., Perez J.C., Perez G., Perez F., Perez Codina E., Perez Morales J., Perfilov M., Pernegger H., Peruzzi M., Pes C., Peters K., Petracca S., Petriello F., Pezzotti L., Pfeiffer S., Piccinini F., Pieloni T., Pierini M., Pikhartova H., Pikurs G., Pilicer E., Piminov P., Pira C., Pittau R., Placzek W., Plagge M., Plehn T., Pleier M.-A., Ploskon M., Podeur M., Podlech H., Podzorny T., Poggioli L., Poiron A., Polesello G., Poli Lener M., Polini A., Polinski J., Polozov S.M., Ponce L., Pont M., Pontecorvo L., Portaluri T., Potamianos K., Prasse C., Prausa M., Preinerstorfer A., Premat E., Price T., Primavera M., Prino F., Prioli M., Proudfoot J., Provino A., Pugnat T., Pukhaeva N., Pulawski S., Pulikowski D., Punzi G., Putti M., Pyarelal A., Quack H., Quispe M., Racioppi A., Rafique H., Raginel V., Raidal M., Ramirez-Uribe N.S., Ramsey-Musolf M.J., Rata R., Ratoff P., Ravotti F., Rebello Teles P., Reboud M., Redaelli S., Renner E., Renteria-Olivo A.E., Rescigno M., Reuter J., Ribon A., Ricci A.M., Riegler W., Riemann S., Riemann B., Riemann T., Rifflet J.M., Rimmer R.A., Rinaldesi R., Rinolfi L., Rios Rubiras O., Risselada T., Rivetti A., Rivkin L., Rizzo T., Robens T., Robert F., Robson A.J., Rochepault E., Roda C., Rodrigo G., Rodriguez-Cahuantzi M., Rogan C., Roig M., Rojas-Torres S., Rojo J., Rolandi G., Rolando G., Roloff P., Romanenko A., Romanov A., Roncarolo F., Rosado Sanchez A., Rosaz G., Rossi L., Rossi A., Rossmanith R., Rousset B., Royon C., Ruan X., Ruehl I., Ruhlmann-Kleider V., Ruiz R., Rumyantsev L., Ruprecht R., Ryazanov A.I., Saba A., Sadykov R., Saez de Jauregui D., Sahin M., Sailer B., Saito M., Sala F., Salam G.P., Salfeld-Nebgen J., Salgado C.A., Salini S., Sallese J.M., Salmi T., Salzburger A., Sampayo O.A., Sanfilippo S., Santiago J., Santopinto E., Santoro R., Sanz Ull A., Sarasola X., Sarpun I.H., Sauvain M., Savelyeva S., Sawada R., Sborlini G.F.R., Schaffer A., Schaumann M., Schenk M., Scheuerlein C., Schienbein I., Schlenga K., Schmickler H., Schmidt R., Schoerling D., Schoning A., Schorner-Sadenius T., Schott M., Schulte D., Schwaller P., Schwanenberger C., Schwemling P., Schwerg N., Scibile L., Sciuto A., Scomparin E., Sebastiani C., Seeber B., Segreti M., Selva P., Selvaggi M., Senatore C., Senol A., Serin L., Serluca M., Serra N., Seryi A., Sestini L., Sfyrla A., Shaposhnikov M., Shaposhnikova E., Sharkov B.Y., Shatilov D., Shelton J., Shiltsev V., Shipsey I.P., Shirkov G.D., Shivaji A., Shwartz D., Sian T., Sidorov S., Siemko A., Silvestrini L., Simand N., Simon F., Singh B.K., Siodmok A., Sirois Y., Sirtori E., Sirvinskaite R., Sitar B., Sjostrand T., Skands P., Skordis E., Skovpen K., Skrzypek M., Slade E., Slavich P., Slovak R., Smaluk V., Smirnov V., Snoeys W., Soffi L., Sollander P., Solovyanov O., Soltveit H.K., Song H., Sopicki P., Sorbi M., Spallino L., Spannowsky M., Spataro B., Sphicas P., Spiesberger H., Spiller P., Spira M., Srivastava T., Stachel J., Stakia A., Stanyard J.L., Starchenko E., Starikov A.Y., Stasto A.M., Statera M., Steerenberg R., Steggemann J., Stenvall A., Stivanello F., Stockinger D., Stoel L.S., Stoger-Pollach M., Strauss B., Stuart M., Stupakov G., Su S., Sublet A., Sugita K., Sulak L., Sullivan M.K., Sultansoy S., Sumida T., Suzuki K., Sylva G., Syphers M.J., Sznajder A., Taborelli M., Tahir N.A., Takeuchi M., Tal Hod E., Tambasco C., Tanaka J., Tang K., Tapan I., Taroni S., Tartarelli G.F., Tassielli G., Tavian L., Taylor T.M., Taylor G.N., Teixeira A.M., Tejeda-Munoz G., Telnov V.I., Tenchini R., ten Kate H.H.J., Terashi K., Tesi A., Testa M., Tetrel C., Teytelman D., Thaler J., Thamm A., Thomas S., Tiirakari M.T., Tikhomirov V., Tikhonov D., Timko H., Tisserand V., Tkachenko L.M., Tkaczuk J., Tock J.P., Todd B., Todesco E., Tomas Garcia R., Tommasini D., Tonelli G., Toral F., Torims T., Torre R., Townsend Z., Trant R., Treille D., Trentadue L., Tricoli A., Tricomi A., Trischuk W., Tropin I.S., Tuchming B., Tudora A.A., Turbiarz B., Turk Cakir I., Turri M., Tydecks T., Usovitsch J., Uythoven J., Vaglio R., Valassi A., Valchkova F., Valdivia Garcia M.A., Valente P., Valente R.U., Valente-Feliciano A.-M., Valentino G., Vale Silva L., Valet J.M., Valizadeh R., Valle J.W.F., Vallecorsa S., Vallone G., van Leeuwen M., van Rienen U.H., van Riesen-Haupt L., Varasteh M., Vecchi L., Vedrine P., Velev G., Veness R., Ventura A., Venturini Delsolaro W., Verducci M., Verhaaren C.B., Vernieri C., Verweij A.P., Verwilligen O., Viazlo O., Vicini A., Viehhauser G., Vignaroli N., Vignolo M., Vitrano A., Vivarelli I., Vlachos S., Vogel M., Vogt D.M., Volkl V., Volkov P., Volpini G., von Ahnen J., Vorotnikov G., Voutsinas G.G., Vysotsky V., Wagner U., Wallny R., Wang L.-T., Wang R., Wang K., Ward B.F.L., Watson T.P., Watson N.K., Ws Z., Weiland C., Weinzierl S., Welsch C.P., Wenninger J., Widorski M., Wiedemann U.A., Wienands H.-U., Wilkinson G., Williams P.H., Winter A., Wohlfahrt A., Wojton T., Wollmann D., Womersley J., Woog D., Wu X., Wulzer A., Yanehsari M.K., Yang G., Yang H.J., Yao W.-M., Yazgan E., Yermolchik V., Yilmaz A., Yoo H.-D., Yost S.A., You T., Young C., Yu T.-T., Yu F., Zaborowska A., Zadeh S.G., Zahnd M., Zanetti M., Zanotto L., Zawiejski L., Zeiler P., Zerlauth M., Zernov S.M., Zevi Dell Porta G., Zhang Z., Zhang Y., Zhang C., Zhang H., Zhao Z., Zhong Y.-M., Zhou J., Zhou D., Zhuang P., Zick G., Zimmermann F., Zinn-Justin J., Zivkovic L., Zlobin A.V., Zobov M., Zupan J., Zurita J., BAİBÜ, Fen Edebiyat Fakültesi, Fizik Bölümü, Denizli, Haluk, TOBB ETU, Faculty of Engineering, Department of Electrical & Electronics Engineering, TOBB ETU, Faculty of Engineering, Department of Material Science & Nanotechnology Engineering, TOBB ETÜ, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, TOBB ETÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü, Bozbey, Ali, Sultansoy, Saleh, Özdemir, Kadri, Giresun Üniversitesi, UCL - SST/IRMP - Institut de recherche en mathématique et physique, and Ege Üniversitesi
- Subjects
Beam losses ,IMPACT ,Physics::Instrumentation and Detectors ,Physics beyond the Standard Model ,EVENT BUILDER ,hadron collider ,General Physics and Astronomy ,Mathematics and natural science: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP] ,01 natural sciences ,7. Clean energy ,law.invention ,Subatomär fysik ,chemistry.chemical_compound ,Conceptual design ,Colliding beam accelerators ,law ,HE-LHC ,Subatomic Physics ,General Materials Science ,Hadron colliders ,Física::Física de partícules::Hadrons [Àrees temàtiques de la UPC] ,Large Hadron Collider ,Acceleradors de partícules ,Physics ,Settore FIS/01 - Fisica Sperimentale ,Beams (radiation) ,Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici ,Upgrade ,Impact ,collimators ,partikkelfysikk ,Future Circular Collider ,High-Energy ,Systems engineering ,HE-LHC: The High-Energy Large Hadron Collider ,Col·lisionadors d'hadrons ,Applied physics ,Collimators ,Socio-culturale ,Fizik ,Hadrons ,Accelerator Physics and Instrumentation ,HE-LHC physics ,Condensed Matter::Materials Science ,0103 physical sciences ,Physics::Atomic and Molecular Clusters ,beam losses ,ddc:530 ,High Energy Physics ,partikkelakselerator ,Physical and Theoretical Chemistry ,Niobium-tin ,010306 general physics ,Collider ,Particle Physics ,Beams (radiation) | Collimators | Beam losses ,Energies::Energia nuclear [Àrees temàtiques de la UPC] ,Large Hadron Collider HE-LHC ,010308 nuclear & particles physics ,High Energy Physics::Phenomenology ,Colliders (Nuclear physics) ,Acceleratorfysik och instrumentering ,Event builder ,Accelerators and Storage Rings ,Particle accelerators ,chemistry ,Experimental High Energy Physics ,Physics::Accelerator Physics ,High Energy Physics::Experiment ,Future Colliders - Abstract
Authors: A. AbadaM. AbbresciaS. S. AbdusSalamI. AbdyukhanovJ. Abelleira FernandezA. AbramovM. AburaiaA. O. AcarP. R. AdzicP. AgrawalJ. A. Aguilar-SaavedraJ. J. Aguilera-VerdugoM. AibaI. AichingerG. AielliA. AkayA. AkhundovH. AksakalJ. L. AlbaceteS. AlbergoA. AlekouM. AleksaR. AleksanR. M. Alemany FernandezY. AlexahinR. G. AlíaS. AlioliN. Alipour TehraniB. C. AllanachP. P. AllportM. AltınlıW. AltmannshoferG. AmbrosioD. AmorimO. AmstutzL. AnderliniA. AndreazzaM. AndreiniA. AndriatisC. AndrisA. AndronicM. AngelucciF. AntinoriS. A. AntipovM. AntonelliM. AntonelloP. AntonioliS. AntuschF. AnulliL. ApolinárioG. ApollinariA. ApollonioD. AppelöR. B. ApplebyA. ApyanA. ApyanA. ArbeyA. ArbuzovG. ArduiniV. ArıS. AriasN. ArmestoR. ArnaldiS. A. ArsenyevM. ArzeoS. AsaiE. AslanidesR. W. AßmannD. AstapovychM. AtanasovS. AtiehD. AttiéB. AuchmannA. AudurierS. AullS. AumonS. AuneF. AvinoG. AvrillaudG. AydınA. AzatovG. AzuelosP. AzziO. AzzoliniP. AzzurriN. BacchettaE. BacchiocchiH. BachacouY. W. BaekV. BaglinY. BaiS. BairdM. J. BakerM. J. BaldwinA. H. BallA. BallarinoS. BanerjeeD. P. BarberD. BarducciP. BarjhouxD. BarnaG. G. BarnaföldiM. J. BarnesA. BarrJ. Barranco GarcíaJ. Barreiro Guimarães da CostaW. BartmannV. BaryshevskyE. BarziS. A. BassA. BastianinB. BaudouyF. BauerM. BauerT. BaumgartnerI. Bautista-GuzmánC. BayındırF. BeaudetteF. BedeschiM. BéguinI. BellafontL. BellagambaN. BellegardeE. BelliE. BellingeriF. BelliniG. BellomoS. BelomestnykhG. BencivenniM. BenediktG. BernardiJ. BernardiC. BernetJ. M. BernhardtC. BerniniC. BerriaudA. BertarelliS. BertolucciM. I. BesanaM. BesançonO. BeznosovP. BhatC. BhatM. E. BiaginiJ. -L. BiarrotteA. Bibet ChevalierE. R. BielertM. BigliettiG. M. BileiB. BilkiC. BiscariF. BisharaO. R. Blanco-GarcíaF. R. BlánquezF. BlekmanA. BlondelJ. BlümleinT. BoccaliR. BoelsS. A. BogaczA. BogomyagkovO. Boine-FrankenheimM. J. BolandS. BolognaO. BolukbasiM. BombenS. BondarenkoM. BonviniE. BoosB. BordiniF. BordryG. BorghelloL. BorgonoviS. BorowkaD. BortolettoD. BoscheriniM. BoscoloS. BoselliR. R. BosleyF. BossuC. BottaL. BotturaR. BoughezalD. BoutinG. BovoneI. Božović JelisavićA. BozbeyC. BozziD. BozziniV. BracciniS. Braibant-GiacomelliJ. BramanteP. Braun-MunzingerJ. A. BriffaD. BritzgerS. J. BrodskyJ. J. BrookeR. BruceP. Brückman De RenstromE. BrunaO. BrüningO. BrunnerK. BrunnerP. BruzzoneX. BuffatE. BulyakF. BurkartH. BurkhardtJ. -P. BurnetF. ButinD. ButtazzoA. ButterworthM. CacciaY. CaiB. CaiffiV. CairoO. CakirR. CalagaS. CalatroniG. CalderiniG. CalderolaA. CaliskanD. CalvetM. CalvianiJ. M. CamalichP. CamarriM. CampanelliT. CamporesiA. C. CanbayA. CanepaE. CantergianiD. Cantore-CavalliM. CapeansR. CardarelliU. CardellaA. CardiniC. M. Carloni CalameF. CarraS. CarraA. CarvalhoS. CasalbuoniJ. CasasM. CascellaP. CastelnovoG. CastorinaG. CatalanoV. CavasinniE. CazzatoE. CenniniA. CerriF. CeruttiJ. CervantesI. ChaikovskaJ. ChakraborttyM. ChalaM. Chamizo-LlatasH. ChanalD. ChanalS. ChanceA. ChancéP. CharitosJ. CharlesT. K. CharlesS. ChattopadhyayR. ChehabS. V. ChekanovN. ChenA. ChernodedV. ChetvertkovaL. ChevalierG. ChiarelliG. ChiarelloM. ChiesaP. ChiggiatoJ. T. ChildersA. ChmielińskaA. CholakianP. ChomazM. ChorowskiW. ChouM. ChrzaszczE. ChyhyrynetsG. CibinettoA. K. CiftciR. CiftciR. CiminoM. CiuchiniP. J. ClarkY. CoadouM. CobalA. CoccaroJ. CoganE. CognerasF. CollamatiC. ColldelramP. CollierJ. CollotR. ContinoF. ConventiC. T. A. CookL. CooleyG. CorcellaA. S. CornellG. H. CorralH. Correia-RodriguesF. CostanzaP. Costa PintoF. CoudercJ. CoupardN. CraigI. Crespo GarridoA. CrivellinJ. F. CroteauM. CrouchE. Cruz AlanizB. CuréJ. CurtiD. CurtinM. CzechC. DachauerR. T. D’AgnoloM. DaiboA. DaineseB. DalenaA. DaljevecW. DallapiazzaL. D’Aloia SchwartzentruberM. DamG. D’AmbrosioS. P. DasS. DasBakshiW. da SilvaG. G. da SilveiraV. D’AuriaS. D’AuriaA. DavidT. DavidekA. DeandreaJ. de BlasC. J. DebonoS. De CurtisN. De FilippisD. de FlorianS. DeghayeS. J. de JongC. Del BoV. Del DucaD. DelikarisF. DeliotA. Dell’AcquaL. Delle RoseM. DelmastroE. De LuciaM. DemarteauD. DenegriL. DeniauD. DenisovH. DenizliA. DennerD. d’EnterriaG. de RijkA. De RoeckF. DerueO. DeschampsS. Descotes-GenonP. S. B. DevJ. B. de Vivie de RégieR. K. DewanjeeA. Di CiaccioA. Di CiccoB. M. DillonB. Di MiccoP. Di NezzaS. Di VitaA. DoblhammerA. DominjonM. D’OnofrioF. DordeiA. DragoP. DraperZ. DrasalM. DrewesL. DuarteI. DubovykP. DudaA. DudarevL. DudkoD. DuellmannM. DünserT. du PreeM. DuranteH. Duran YildizS. DuttaF. DuvalJ. M. DuvalY. DydyshkaB. DziewitS. EisenhardtM. EistererT. EkelofD. El KhechenS. A. EllisJ. EllisJ. A. EllisonK. ElsenerM. ElsingY. EnariC. EnglertH. ErikssonK. J. EskolaL. S. EspositoO. EtiskenE. EtzionP. FabbricatoreA. FalkowskiA. FalouJ. FaltovaJ. FanL. FanòA. FarillaR. FarinelliS. FarinonD. A. FaroughyS. D. FartoukhA. Faus-GolfeW. J. FawcettG. FeliciL. FelsbergerC. FerdeghiniA. M. Fernandez NavarroA. Fernández-TéllezJ. Ferradas TroitinoG. FerraraR. FerrariL. FerreiraP. Ferreira da SilvaG. FerreraF. FerroM. FiascarisS. 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KashikhinJ. Katharina BehrU. KayaJ. KeintzelP. A. KeinzK. KeppelR. KersevanK. KershawH. KhanpourS. KhatibiM. Khatiri YanehsariV. V. KhozeJ. KieselerA. KilicA. KilpinenY. -K. KimD. W. KimU. KleinM. KleinF. KlingN. KlinkenbergS. KlöppelM. KluteV. I. KlyukhinM. KnechtB. KniehlF. KocakC. KoeberlA. M. KolanoA. KolleggerK. KołodziejA. A. KolomietsJ. KomppulaI. KoopP. KoppenburgM. KoratzinosM. KordiaczyńskaM. KorjikO. KortnerP. KostkaW. KotlarskiC. KotnigT. KöttigA. V. KotwalA. D. KovalenkoS. KowalskiJ. KozaczukG. A. KozlovS. S. KozubA. M. KrainerT. KramerM. KrämerM. KrammerA. A. KrasnovF. KraussK. KravalisL. KretzschmarR. M. KriskeH. KritscherP. KrkoticH. KrohaM. KucharczykS. KudayA. KuendigG. KuhlmannA. KuleszaM. KumarM. KumarA. KusinaS. KuttimalaiM. KuzeT. KwonF. LacknerM. LacknerE. La FrancescaM. LaineG. LamannaS. La MendolaE. LançonG. LandsbergP. LangackerC. LangeA. LangnerA. J. LankfordJ. P. LansbergT. LariP. J. LaycockP. LebrunA. LechnerK. LeeS. LeeR. LeeT. LefevreP. Le GuenT. LehtinenS. B. LeithP. LenziE. LeograndeC. LeonidopoulosI. Leon-MonzonG. LernerO. LeroyT. LesiakP. LévaiA. LeverattoE. LevichevG. LiS. LiR. LiD. LiberatiM. LiepeD. A. LissauerZ. LiuA. LobkoE. LocciE. Logothetis AgaliotisM. P. LombardoA. J. LongC. LorinR. LositoA. LouzguitiI. LowD. LucchesiM. T. LucchiniA. LucianiM. LueckhofA. J. G. LuntM. LuzumD. A. LyubimtsevM. MaggioraN. MagninM. A. MahmoudF. MahmoudiJ. MaitreV. MakarenkoA. MalagoliJ. MalclésL. MalgeriP. J. MallonF. MaltoniS. MalvezziO. B. MalyshevG. MancinelliP. MandrikP. ManfrinettiM. ManganoP. ManilM. MannelliG. MarchioriF. MarhauserV. MarianiV. MarinozziS. MariottoP. MarquardC. MarquetT. Marriott-DodingtonR. MartinO. MartinJ. Martin CamalichT. MartinezH. Martinez BruzualM. I. Martínez-HernándezD. E. MartinsS. MarzaniD. MarzoccaL. MarzolaS. MasciocchiI. MasinaA. MassimilianoA. MassironiT. MasubuchiV. A. MatveevM. A. MazzoniM. McCulloughP. A. McIntoshP. MeadeL. MedinaA. MeierJ. MeignanB. MeleJ. G. Mendes SaraivaF. MenezM. MentinkE. MeoniP. MeridianiM. MerkP. MermodV. MertensL. MetherE. MétralM. MiglioratiA. MilaneseC. MilardiG. MilhanoB. L. MilitsynF. MilletI. MinashviliJ. V. MinerviniL. S. MirallesD. MirarchiS. MishimaD. P. MissiaenG. MitselmakherT. MitshuhashiJ. MnichM. Mohammadi NajafabadiR. N. MohapatraN. MokhovJ. G. MolsonR. MongeC. MontagG. MontagnaS. MonteilG. MonteneroE. MontesinosF. MoortgatN. MorangeG. MorelloM. Moreno LlácerM. MorettiS. MorettiA. K. MorleyA. MorosI. MorozovV. MorrettaM. MorroneA. MostacciS. MuanzaN. MuchnoiM. MühleggerM. MulderM. MuldersB. MüllerF. MüllerA. -S. MüllerJ. MunillaM. J. MurrayY. MuttoniS. MyersM. MylonaJ. NachtmanT. NakamotoM. NardecchiaG. NardiniP. NasonZ. NergizA. V. NesterenkoJ. A. NettoA. NettsträterC. NeubüserJ. NeundorfF. NiccoliO. NicrosiniY. NieU. NiedermayerJ. NiedzielaA. NiemiS. A. NikitinA. NisatiJ. M. NoM. NonisY. NosochkovM. NovákA. NovokhatskiJ. M. O’CallaghanC. OchandoS. OgurK. OhmiK. OideV. A. OkorokovY. OkumuraC. OleariF. I. OlnessY. OnelM. OrtinoJ. OsborneP. OslandT. OttoK. Y. OyulmazA. OzansoyV. ÖzcanK. ÖzdemirC. E. PagliaroneH. F. Pais da SilvaE. PalmieriL. PalumboA. PampaloniR. -Q. PanM. PanareoO. PanellaG. PanicoG. PanizzoA. A. PankovV. PantsyrnyC. G. PapadopoulosA. PapaefstathiouY. PapaphilippouM. A. ParkerV. ParmaM. PasqualiS. K. PatraR. PattersonH. PaukkunenF. PaussS. PeggsJ. -P. PenttinenG. PeónE. E. PerepelkinE. PerezJ. C. PerezG. PerezF. PérezE. Perez CodinaJ. Perez MoralesM. PerfilovH. PerneggerM. PeruzziC. PesK. PetersS. PetraccaF. PetrielloL. PezzottiS. PfeifferF. PiccininiT. PieloniM. PieriniH. PikhartovaG. PikursE. PilicerP. PiminovC. PiraR. PittauW. PłaczekM. PlaggeT. PlehnM. -A. PleierM. PłoskońM. PodeurH. PodlechT. PodzornyL. PoggioliA. PoironG. PoleselloM. Poli LenerA. PoliniJ. PolinskiS. M. PolozovL. PonceM. PontL. PontecorvoT. PortaluriK. PotamianosC. PrasseM. PrausaA. PreinerstorferE. PrematT. PriceM. PrimaveraF. PrinoM. PrioliJ. ProudfootA. ProvinoT. PugnatN. PukhaevaS. PuławskiD. PulikowskiG. PunziM. PuttiA. PyarelalH. QuackM. QuispeA. RacioppiH. RafiqueV. RaginelM. RaidalN. S. Ramírez-UribeM. J. Ramsey-MusolfR. RataP. RatoffF. RavottiP. Rebello TelesM. ReboudS. RedaelliE. RennerA. E. Rentería-OlivoM. RescignoJ. ReuterA. RibonA. M. RicciW. RieglerS. RiemannB. RiemannT. RiemannJ. M. RiffletR. A. RimmerR. RinaldesiL. RinolfiO. Rios RubirasT. RisseladaA. RivettiL. RivkinT. RizzoT. RobensF. RobertA. J. RobsonE. RochepaultC. RodaG. RodrigoM. Rodríguez-CahuantziC. RoganM. RoigS. Rojas-TorresJ. RojoG. RolandiG. RolandoP. RoloffA. RomanenkoA. RomanovF. RoncaroloA. Rosado SanchezG. RosazL. RossiA. RossiR. RossmanithB. RoussetC. RoyonX. RuanI. RuehlV. Ruhlmann-KleiderR. RuizL. RumyantsevR. RuprechtA. I. RyazanovA. SabaR. SadykovD. Saez de JaureguiM. SahinB. SailerM. SaitoF. SalaG. P. SalamJ. Salfeld-NebgenC. A. SalgadoS. SaliniJ. M. SalleseT. SalmiA. SalzburgerO. A. SampayoS. SanfilippoJ. SantiagoE. SantopintoR. SantoroA. Sanz UllX. SarasolaI. H. SarpünM. SauvainS. SavelyevaR. SawadaG. F. R. SborliniA. SchafferM. SchaumannM. SchenkC. ScheuerleinI. SchienbeinK. SchlengaH. SchmicklerR. SchmidtD. SchoerlingA. SchoningT. Schörner-SadeniusM. SchottD. SchulteP. SchwallerC. SchwanenbergerP. SchwemlingN. SchwergL. ScibileA. SciutoE. ScomparinC. SebastianiB. SeeberM. SegretiP. SelvaM. SelvaggiC. SenatoreA. SenolL. SerinM. SerlucaN. SerraA. SeryiL. SestiniA. SfyrlaM. ShaposhnikovE. ShaposhnikovaB. Y. SharkovD. ShatilovJ. SheltonV. ShiltsevI. P. ShipseyG. D. ShirkovA. ShivajiD. ShwartzT. SianS. SidorovA. SiemkoL. SilvestriniN. SimandF. SimonB. K. SinghA. SiódmokY. SiroisE. SirtoriR. SirvinskaiteB. SitarT. SjöstrandP. SkandsE. SkordisK. SkovpenM. SkrzypekE. SladeP. SlavichR. SlovakV. SmalukV. SmirnovW. SnoeysL. SoffiP. SollanderO. SolovyanovH. K. SoltveitH. SongP. SopickiM. SorbiL. SpallinoM. SpannowskyB. SpataroP. SphicasH. SpiesbergerP. SpillerM. SpiraT. SrivastavaJ. StachelA. StakiaJ. L. StanyardE. StarchenkoA. Y. StarikovA. M. StaśtoM. StateraR. SteerenbergJ. SteggemannA. StenvallF. StivanelloD. StöckingerL. S. StoelM. Stöger-PollachB. StraussM. StuartG. StupakovS. SuA. SubletK. SugitaL. SulakM. K. SullivanS. SultansoyT. SumidaK. SuzukiG. SylvaM. J. SyphersA. SznajderM. TaborelliN. A. TahirM. TakeuchiE. Tal HodC. TambascoJ. TanakaK. TangI. TapanS. TaroniG. F. TartarelliG. TassielliL. TavianT. M. TaylorG. N. TaylorA. M. TeixeiraG. Tejeda-MuñozV. I. TelnovR. TenchiniH. H. J. ten KateK. TerashiA. TesiM. TestaC. TetrelD. TeytelmanJ. ThalerA. ThammS. ThomasM. T. TiirakariV. TikhomirovD. TikhonovH. TimkoV. TisserandL. M. TkachenkoJ. TkaczukJ. P. TockB. ToddE. TodescoR. Tomás GarciaD. TommasiniG. TonelliF. ToralT. TorimsR. TorreZ. TownsendR. TrantD. TreilleL. TrentadueA. TricoliA. TricomiW. TrischukI. S. TropinB. TuchmingA. A. TudoraB. TurbiarzI. Turk CakirM. TurriT. TydecksJ. UsovitschJ. UythovenR. VaglioA. ValassiF. ValchkovaM. A. Valdivia GarciaP. ValenteR. U. ValenteA. -M. Valente-FelicianoG. ValentinoL. Vale SilvaJ. M. ValetR. ValizadehJ. W. F. ValleS. VallecorsaG. ValloneM. van LeeuwenU. H. van RienenL. van Riesen-HauptM. VarastehL. VecchiP. VedrineG. VelevR. VenessA. VenturaW. Venturini DelsolaroM. VerducciC. B. VerhaarenC. VernieriA. P. VerweijO. VerwilligenO. ViazloA. ViciniG. ViehhauserN. VignaroliM. VignoloA. VitranoI. VivarelliS. VlachosM. VogelD. M. VogtV. VölklP. VolkovG. VolpiniJ. von AhnenG. VorotnikovG. G. VoutsinasV. VysotskyU. WagnerR. WallnyL. -T. WangR. WangK. WangB. F. L. WardT. P. WatsonN. K. WatsonZ. WsC. WeilandS. WeinzierlC. P. WelschJ. WenningerM. WidorskiU. A. WiedemannH. -U. WienandsG. WilkinsonP. H. WilliamsA. WinterA. WohlfahrtT. WojtońD. WollmannJ. WomersleyD. WoogX. WuA. WulzerM. K. YanehsariG. YangH. J. YangW. -M. YaoE. YazganV. YermolchikA. YilmazA. YilmazH. -D. YooS. A. YostT. YouC. YoungT. -T. YuF. YuA. ZaborowskaS. G. ZadehM. ZahndM. ZanettiL. ZanottoL. ZawiejskiP. ZeilerM. ZerlauthS. M. ZernovG. Zevi Dell PortaZ. ZhangY. ZhangC. ZhangH. ZhangZ. ZhaoY. -M. ZhongJ. ZhouD. ZhouP. ZhuangG. ZickF. ZimmermannEmail authorJ. Zinn-JustinL. ZivkovicA. V. ZlobinM. ZobovJ. ZupanJ. Zuritathe FCC Collaboration, In response to the 2013 Update of the European Strategy for Particle Physics (EPPSU), the Future Circular Collider (FCC) study was launched as a world-wide international collaboration hosted by CERN. The FCC study covered an energy-frontier hadron collider (FCC-hh), a highest-luminosity high-energy lepton collider (FCC-ee), the corresponding 100km tunnel infrastructure, as well as the physics opportunities of these two colliders, and a high-energy LHC, based on FCC-hh technology. This document constitutes the fourth volume of the FCC Conceptual Design Report, devoted to the High-Energy Large Hadron Collider HE-LHC. It summarizes the HE-LHC physics discovery opportunities, presents the HE-LHC accelerator design, performance reach, and operation plan, discusses the underlying technologies, the civil engineering and technical infrastructure, and also sketches a possible implementation. Combining ingredients from the Large Hadron Collider (LHC), the high-luminosity LHC upgrade and adding novel technologies and approaches, the HE-LHC design aims at a hadron collider with about twice the centre-of-mass collision energy that the LHC can reach. Its performance aims at exploring physics beyond the Standard Model, signi cantly extending the LHC's direct and indirect sensitivity to new physics and discoveries.
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- 2020
- Full Text
- View/download PDF
98. Two-Stage Ensemble Kalman Filter Approach for Data Assimilation Applied to Flow in Fractured Media
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Patrick Jenny and M. Liem
- Subjects
Reservoir simulation ,Permeability (earth sciences) ,Data assimilation ,Aperture ,Probabilistic logic ,A priori and a posteriori ,Ensemble Kalman filter ,Kalman filter ,Mechanics ,Geology - Abstract
Summary The permeability field in a reservoir simulation greatly influences the resulting flow field and therefore a thorough knowledge of it is crucial. However, the permeability field is usually associated with a high degree of uncertainty since only few measurements of reservoir properties are available. Fractures can form highly conductive shortcuts through the matrix domain. Therefore, it is important to estimate fracture parameters such as location, orientation and size as precisely as possible. Ensemble Kalman filters (EnKF) are widely used for history matching (or data assimilation) in the context of sub-surface flows in order to estimate parameters, reduce uncertainty and improve simulation results. This work studies the evolution of a reservoir as it might occur e.g. during reservoir stimulation of a geothermal system. During the first stage, large isolated fractures with a preferred orientation arise one after the other. During the second stage, these fractures get connected by others, which have a different preferred orientation. We assume that location, orientation and length of all fractures are known a priori. The only uncertainty therefore lies in the hydraulic aperture of each fracture segment. Further we assume that prior probabilistic knowledge of the hydraulic aperture is available, e.g. from seismic measurements. We upscale the fractures and simulate the flow in the reservoir with a single-continuum model. We reduce the uncertainty of the hydraulic apertures with an iterative EnKF using empirical measurement data; here from a reference simulation. During the formation of the fractures, we use pressure and flow at in- and outlet boundaries as measurements. Once the whole reservoir is developed, a tracer is injected at the inlet and its concentration at the outlet boundary is used as measurement. In this context also the effect of different fracture-matrix permeability ratios is studied.
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- 2020
- Full Text
- View/download PDF
99. Particle Transport Scheme for Embedded Discrete Fracture Models
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Rajdep Deb, Daniel W. Meyer, Patrick Jenny, and Ranit Monga
- Subjects
Matrix (mathematics) ,Work (thermodynamics) ,Field (physics) ,Computer science ,Fracture (geology) ,Conformal map ,Mechanics ,Tracking (particle physics) ,Porous medium ,Random walk ,Physics::Geophysics - Abstract
Summary Embedded Discrete Fracture Models (EDFMs) for fractured porous media are preferable over Discrete Fracture Models if complex fracture geometries are to be fully resolved and the fractures and matrix discretizations are conformal. Lagrangian particle-tracking schemes offer convenient means for solute transport modeling because in EDFM frameworks, an orthogonal grid can be used irrespective of the fracture geometries. However, the absence of resolved fracture-matrix interfaces and different dimensionalities of the matrix and fracture continua motivate the use of a stochastic framework for particle-tracking. In this work, we developed a stochastic, time-adaptive particle-tracking scheme for EDFM models of fractured media with a permeable matrix. We formulated the probabilities of inter-continuum particle transfer, which have dependency on the particle travel time through the matrix/fracture control volumes. We showcase the conservative nature of the proposed particle-tracking scheme and additionally, illustrate the estimation of averaged solute concentration field. Such an illustration hints at the potential extensions of the tracking scheme, e.g., modeling of solute transport with kinetic reactions, and its incorporation into random walk models for dispersion in fractured media.
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- 2020
- Full Text
- View/download PDF
100. Extended Finite Volume Method (XFVM) for Flow Induced Tensile Failure in Fractured Reservoirs
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A.A. Habibabadi, Rajdeep Deb, and Patrick Jenny
- Subjects
Finite volume method ,Materials science ,Flow (mathematics) ,Ultimate tensile strength ,Mechanics - Published
- 2020
- Full Text
- View/download PDF
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