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A modified applied element model to simulate the behaviour of plain concrete continuum structures including discrete cracking is proposed in this study. In the classical applied element model, Poisson effects are fully ignored. To remediate this issue, diagonal elements are introduced to include the Poisson effect, and the constitutive parameters are rigorously determined using the Cauchy–Born rule and the hyper-elastic theory. The formulation is validated for linear elastic problems and the consistency and convergence behaviour of the numerical approach is shown. Tensile softening formulation using the concept of fracture energy is utilised for the nonlinear range. In this range, the approach is validated using the classical benchmark tests with pure tensile, split-tensile, combined shear-tensile and bending dominated push-over loading. The load–displacement behaviour and crack response were captured successfully, showing the proposed methodology can be used to quantify discrete cracks on large systems, such as dam monoliths, from initiation to significant damage levels. [ABSTRACT FROM AUTHOR]

Floating Car Data (FCD) are being increasingly used as an alternative traffic data source due to its lower cost and high coverage area. FCD can be obtained by tracking vehicle trajectories individually or by processing multiple tracks anonymously to produce average speed information commercially. For commercial FCD, the spatio-temporal distribution of these vehicles in actual traffic, traffic Penetration Rate (PR) is the most important factor affecting the accuracy of speed estimations, despite the high number of registered vehicles feeding to an FCD provider, denoting the market PR. This study proposes a method for assessing the traffic PR of commercial FCD by evaluating its speed estimation quality compared to Ground Truth (GT) data. GT speed data were employed to generate different levels of traffic PR using Monte Carlo (MC) simulations, which resulted in the development of Quality-PR (Q-PR) relations for Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) as selected Measures of Effectiveness (MoE). Simulation-based FCD results at an urban road segment in Ankara (Turkey) showed that a quality of FCD with traffic PR of 15% or more would improve significantly. Use of the developed Q-PR relations suggested an approximately 5% traffic PR for the commercial FCD speeds at the location. [ABSTRACT FROM AUTHOR]

Abstract Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack of sufficient information, resulting in the construction of spurious or incomplete TRNs. We develop a methodology, TRND, that integrates a preliminary TRN, microarray data, gene ontology and phylogenic similarity to accurately discover TRNs and apply the method to E. coli K12. The approach can easily be extended to include other methodologies. Although gene ontology and phylogenic similarity have been used in the context of gene-gene networks, we show that more information can be extracted when gene-gene scores are transformed to gene-transcription factor (TF) scores using a preliminary TRN. This seems to be preferable over the construction of gene-gene interaction networks in light of the observed fact that gene expression and activity of a TF made of a component encoded by that gene is often out of phase. TRND multi-method integration is found to be facilitated by the use of a Bayesian framework for each method derived from its individual scoring measure and a training set of gene/TF regulatory interactions. The TRNs we construct are in better agreement with microarray data. The number of gene/TF interactions we discover is actually double that of existing networks.

Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of cellular processes and the calibration of the associated physicochemical parameters. We have demonstrated these concepts in the context of gene regulation understood through the analysis of gene expression microarray time series data. Casting the approach in a probabilistic framework has allowed us to address the uncertainties in gene expression microarray data. Our approach was found to be robust to error in the gene expression microarray data and mistakes in a proposed TRN.

A vast number of numerical approaches have been used to simulate the non-linear behaviour of concrete and reinforced concrete members at different scales. Most approaches were based on the finite-element method and have a variety of disadvantages when modelling brittle materials. Thanks to increasing computational power, mesoscale lattice models have been developed to achieve more accurate results for the width and pattern of cracks. Among different element choices for the lattice network, the use of truss elements is more efficient than beam or shear elements. In this study, a two-dimensional mesoscale lattice model is proposed with the novelty of grid perturbation to enable the prediction of compression failure as a consequence of tension failure. A novel calibration technique is proposed to determine the magnitude of grid perturbation. Uniaxial compression simulations to investigate the relationship between tensile and compressive strengths are described. The length scale and grid dependency of the model are investigated numerically. In addition, compression strut experiments and overreinforced concrete beam tests are simulated to validate the proposed approach. Promising numerical results show that compression failure can be estimated using lattice models that have tension failure only. [ABSTRACT FROM AUTHOR]

Introduction: There are significant differences in the active cases and fatality rates of Covid-19 for different European countries. Methodology: The present study employs Monte Carlo based transmission growth simulations for Italy, Germany and Turkey. The probabilities of transmission at home, work and social networks and the number of initial cases have been calibrated to match the basic reproduction number and the reported fatality curves. Parametric studies were conducted to observe the effect of social distancing, work closure, testing and quarantine of the family and colleagues of positively tested individuals. Results: It is observed that estimates of the number of initial cases in Italy compared to Turkey and Germany are higher. Turkey will probably experience about 30% less number of fatalities than Germany due its smaller elderly population. If social distancing and work contacts are limited to 25% of daily routines, Germany and Turkey may limit the number of fatalities to a few thousands as the reproduction number decreases to about 1.3 from 2.8. Random testing may reduce the number of fatalities by 10% upon testing least 5/1000 of the population. Quarantining of family and workmates of positively tested individuals may reduce the total number of fatalities by about 50%. Conclusions: The fatality rate of Covid-19 is estimated to be about 1.5% based on the simulation results. This may further be reduced by limiting the number of non-family contacts to two, conducting tests more than 0.5% of the population and immediate quarantine of the contacts for positively tested individuals. [ABSTRACT FROM AUTHOR]

A classical density functional formalism has been developed to predict the position-orientation number density of structured fluids. It is applied to the liquid–vapor interface of pure water, where it consists of a classical term, a gradient correction, and an anisotropic term that yields order through density gradients. The model is calibrated to predict that water molecules have their dipole moments almost parallel to a planar interface, while the molecular plane is parallel to it on the liquid side and perpendicular to it on the vapor side. For a planar interface, the surface tension obtained is twice its experimental value, while the surface potential is in qualitative agreement with that calculated by others. The model is also used to predict the orientation of water molecules near the surface of droplets, as well as the dependence of equilibrium vapor pressure around them on their size. © 2004 American Institute of Physics. [ABSTRACT FROM AUTHOR]

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Modeling concrete fracture is important in order to uncover accurately the sources of distress which lead to the damage or failure of structures. Many different numerical approaches have been used in the past employing either a smeared or a discrete cracking approach. Those models have difficulty in capturing the local nature of cracking, as well as the direction of crack propagation. Lattice modeling and peridynamics (PD) are some of the more recent nonlocal fracture simulation tools which possess advantages, such as ease of modeling and accuracy of crack propagation simulations with few key parameters. In this work, we employ an overlapping lattice approach, where the continuum is discretized using truss elements extending over a predefined horizon similar to the concept used in PD with the sequentially linear analysis technique. Simulation results for several reinforced concrete (RC) and un‐RC tests demonstrate the ability to estimate crack propagation directions and widths accurately, with the proposed modeling approach also offering a rather simple and intuitive approach. [ABSTRACT FROM AUTHOR]

Underwater pipelines are often necessary to transport valuable resources between patches of land, and are expected to have increased utilization across the globe with the steep population increase on one hand, and unbalanced depletion of resources on the other. It is desirable to automate monitoring of various performance parameters associated with the pipelines through wireless sensor networks to ensure longevity of use and reduced running costs. However, such pipelines are not easily accessible, and are subject to harsh environments such as salt water and underwater currents. Therefore, an ideal node in this sort of network is embedded into the pipeline, and does not require batteries with regular replacement provisions. Using an energy harvester as the power source becomes a viable option. A method for near-optimal piezoelectric bimorph energy harvester module design is presented in this paper to enable a self-powered wireless sensor node for in-pipe monitoring using kinetic energy of water flow. A crude analytical model provides a starting point for the design, which is tuned through finite element modeling and simulation. Recently constructed Turkey-Cyprus water pipeline project is considered as a realistic application for determining boundary conditions. With an average water velocity of 1.4 m/s, the designed energy harvester is scalable to produce power between 820~\mu \textW (single) to 12.3 mW (15 in parallel) with a negligible impact of 1.5 mm additional head loss. The method developed to deliver a finely modeled, scalable harvester design with minimum quantified impact to pipe performance is first of its kind to our knowledge. [ABSTRACT FROM PUBLISHER]

A two-dimensional density-dependent reactive transport model, which couples groundwater flow and biogeochemical reactions, is used to investigate the fate of nutrients (NO3−, NH4+, and PO4) in idealized subterranean estuaries representing four end-members of oxic/anoxic aquifer and seawater redox conditions. Results from the simplified model representations show that the prevalent flow characteristics and redox conditions in the freshwater-seawater mixing zone determine the extent of nutrient removal and the input of nitrogen and phosphorus to coastal waters. At low to moderate groundwater velocities, simultaneous nitrification and denitrification can lead to a reversal in the depth of freshwater NO3− and NH4+-PO4 plumes, compared to their original positions at the landward source. Model results suggest that autotrophic denitrification pathways with Fe2+ or FeS2 may provide an important, often overlooked link between nitrogen and phosphorus biogeochemistry through the precipitation of iron oxides and subsequent binding of phosphorus. Simulations also highlight that deviations of nutrient data from conservative mixing curves do not necessarily indicate nutrient removal. [ABSTRACT FROM AUTHOR]

Transcriptional regulatory network (TRN) discovery using information from a single source does not seem feasible due to lack of sufficient information, resulting in the construction of spurious or incomplete TRNs. A methodology, TRND, that integrates a preliminary TRN, gene expression data and gene ontology is developed to discover TRNs. The method is applied to a comprehensive set of expression data on B cell and a preliminary TRN that included 1,335 genes, 443 transcription factors (TFs) and 4032 gene/TF interactions. Predictions were obtained for 443 TFs and 9,589 genes. 14,616 of 4,247,927 possible gene/TF interactions scored higher than the imposed threshold. Results for three TFs, E2F-4, p130 and c-Myc, were examined in more detail to assess the accuracy of the integrated methodology. Although the training sets for E2F-4 and p130 were rather limited, the activities of these two TFs were found to be highly correlated and a large set of coregulated genes is predicted. These predictions were confirmed with published experimental results not used in the training set. A similar test was run for the c-Myc TF using the comprehensive resource www.myccancergene.org. In addition, correlations between expression of genes that encode TFs and TF activities were calculated and showed that the assumption of TF activity correlates with encoding gene expression might be misleading. The constructed B cell TRN, and scores for individual methodologies and the integrated approach are available at systemsbiology.indiana.edu/trndresults. [ABSTRACT FROM AUTHOR]

We present a seismic waveform inversion methodology based on the Gauss–Newton method from pre-stack seismic data. The inversion employs a staggered-grid finite difference solution of the 2-D elastic wave equation in the time domain, allowing accurate simulation of all possible waves in elastic media. The partial derivatives for the Gauss–Newton method are obtained from the differential equation of the wave equation in terms of model parameters. The resulting wave equation and virtual sources from the reciprocity principle allow us to apply the Gauss–Newton method to seismic waveform inversion. The partial derivative wavefields are explicitly computed by convolution of forward wavefields propagated from each source with reciprocal wavefields from each receiver. The Gauss–Newton method for seismic waveform inversion was proposed in the 1980s but has rarely been studied. Extensive computational and memory requirements have been principal difficulties which are addressed in this work. We used different sizes of grids for the inversion, temporal windowing, approximation of virtual sources, and parallelizing computations. With numerical experiments, we show that the Gauss–Newton method has significantly higher resolving power and convergence rate over the gradient method, and demonstrate potential applications to real seismic data. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) landfills are not only used to dispose the refuse in most economical way but also utilized as a viable land in today’s waste management strategy. Settlement prediction is an important issue in order to guarantee the integrity of any postclosure structure on landfills. In this study, landfill settlement in saturated and unsaturated landfills is investigated by developing a one-dimensional mathematical model and performing numerical experiments. Under the saturated conditions, the landfill is considered to be completely liquid saturated by preventing gas generation at all times. On the other hand, for the unsaturated case, we assume that a gas mixture comprised of methane and carbon dioxide is generated as a result of microbial decomposition of MSW deposited. The gas generation is assumed to follow a first-order kinetic approach. The liquid phase and gas mixture are considered compressible as well as the solid matrix (landfill body). After the governing equations were discretized using the Galerkin finite-element method, the Gaussian elimination technique is employed for a solution. In saturated landfills, the settlement is mainly caused by the overburden weight of the waste deposited. Further, the mass loss due to waste decomposition contributes for an additional settlement in unsaturated landfills. The predicted settlements are within the range reported in the literature. The model developed can simulate porosity, pressures, saturations, and stress profiles in settling landfills as well as to predict the transient and ultimate settlements in saturated and unsaturated landfills. [ABSTRACT FROM AUTHOR]

Abstract: Elemental turnover in porous media depends on substrate concentrations at the pore-scale. In this study, the effect of small scale variability in concentration fields on reaction rate estimates and the validity of the continuum approximation in reactive transport models are investigated via a pore-scale numerical model. Artificial porous media are generated using an identical overlapping sphere algorithm. By comparison between explicit pore-scale simulations and macroscopic continuum approximations, it is shown that inhomogeneous solute distribution within the pores can affect estimates of elemental turnover rates. The error associated with large scale rate estimates depends on the type of reaction, pore geometry, reaction kinetics and macroscopic concentration gradient. A correction term that involves a phenomenological parameter which can be evaluated numerically and macroscopic concentration gradients is introduced to improve the accuracy of upscaled homogeneous reaction rates. Implications for macroscopic descriptions of surface processes and surface attached microbial populations are discussed and it is shown that pore-scale heterogeneity can substantially affect estimates of heterogeneous reactions, while for homogeneous reactions, the error amounts to only a couple of percents. [Copyright &y& Elsevier]

A one-dimensional multiphase numerical model is developed to simulate the vertical settlement involving liquid and gas flows in a deformable (settling) municipal solid waste (MSW) landfill. MSW is represented by a chemical composition, and a global stoichiometric reaction is used to estimate the maximum yield of gas generation. Following the general assumption accepted in the literature, the gas generated by waste decomposition is assumed to comprise of methane (CH4) and carbon dioxide (CO2). The gas generation rate follows an exponentially decaying function of time. The gas generation model developed based on a first-order kinetic single-bioreactor approach includes the governing equations of gas migration, liquid flow, and landfill deformation. The Galerkin finite element method is used to solve the resulting equations. The model developed can be used to estimate the transient and ultimate settlements due to waste decomposition and gas generation in MSW landfills. The proposed model can estimate the waste porosity, gas pressure, liquid pressure, gas saturation, liquid saturation, and stress distributions in settling landfills. The results obtained for a deformable landfill are compared with a landfill having a rigid solid skeleton. Due to settlement, the depth of waste is 27% smaller in deformable landfills than that of the rigid ones. [ABSTRACT FROM AUTHOR]

A data assimilation approach is demonstrated whereby seismic inversion is both automated and enhanced using a comprehensive numerical sedimentary basin simulator to study the physics and chemistry of sedimentary basin processes in response to geothermal gradient in much greater detail than previously attempted. The approach not only reduces costs by integrating the basin analysis and seismic inversion activities to understand the sedimentary basin evolution with respect to geodynamic parameters—but the technique also has the potential for serving as a geoinfomatics platform for understanding various physical and chemical processes operating at different scales within a sedimentary basin. Tectonic history has a first-order effect on the physical and chemical processes that govern the evolution of sedimentary basins. We demonstrate how such tectonic parameters may be estimated by minimizing the difference between observed seismic reflection data and synthetic ones constructed from the output of a reaction, transport, mechanical (RTM) basin model. We demonstrate the method by reconstructing the geothermal gradient. As thermal history strongly affects the rate of RTM processes operating in a sedimentary basin, variations in geothermal gradient history alter the present-day fluid pressure, effective stress, porosity, fracture statistics and hydrocarbon distribution. All these properties, in turn, affect the mechanical wave velocity and sediment density profiles for a sedimentary basin. The present-day state of the sedimentary basin is imaged by reflection seismology data to a high degree of resolution, but it does not give any indication of the processes that contributed to the evolution of the basin or causes for heterogeneities within the basin that are being imaged. Using texture and fluid properties predicted by our Basin RTM simulator, we generate synthetic seismograms. Linear correlation using power spectra as an error measure and an efficient quadratic optimization technique are found to be most effective in determining the optimal value of the tectonic parameters. Preliminary 1-D studies indicate that one can determine the geothermal gradient even in the presence of observation and numerical uncertainties. The algorithm succeeds even when the synthetic data has detailed information only in a limited depth interval and has a different dominant frequency in the synthetic and observed seismograms. The methodology presented here even works when the basin input data contains only 75 per cent of the stratigraphic layering information compared with the actual basin in a limited depth interval. [ABSTRACT FROM AUTHOR]

Presents a theory for one-dimensional self-weight subsidence of saturated soft porous media. Theory of finite-strain subsidence; Nondimensionalization of governing equations; Exact solutions for steady-state condition; Conclusions.

Discusses a theory for the consolidation of elastic porous media saturated by two immiscible Newtonian fluids. Volume averaging theorems; Microscopic constitutive relations; Mass and momentum balance equations; Macroscopic constitutive relations; Macroscopic equilibrium equations; Consolidation of porous column saturated by oil and water phases.

When a light, immiscible oil leaks above an unconfined aquifer, it spreads and forms a floating mound on the water table. The oil mound migrates in the direction of ambient groundwater flow. In this study we present a governing equation for the migrating mound thickness by averaging the oil phase mass balance equation. Analytical and numerical solutions to an advective-dispersive type equation are presented to estimate the temporal and spatial distribution of the migrating oil mound thickness for two problems of practical importance: formation, spreading, and migration of an oil mound on the water table and spreading and migration of an established layer of oil with ambient groundwater flow. The model results compare favorably with test data obtained by laboratory flume experiments. Although the model has some simplifying assumptions such as the absence of capillary pressure gradients, sharp saturation changes across the phase interfaces, and single mobile phase (i.e., oil flow only), it can be useful as a screening or site assessment tool because of its relative simplicity. [ABSTRACT FROM AUTHOR]

An effective stress principle for saturated fractured porous media is proposed based on the double-porosity representation. Both the solid grains and the fractured porous medium are assumed to be linearly elastic materials. The derivation employs volume averaging technique to obtain macroscopic scale expressions. Two parameters, the bulk modulus of the fractured medium and bulk modulus of the porous matrix, are introduced in the formulation. The final expression reduces to the one obtained by Biot and Willis [1957], Skempton [1960], Nur and Byeerle [1971], and Verruijt [1984] when the volume fraction of the fractures vanishes, that is, for a nonfractured porous medium. [ABSTRACT FROM AUTHOR]

Leaks in geomembrane liners of waste landfills and liquid impoundments cause chemical contaminants to leak into the subsurface environment. A mathematical model is presented to simulate electrophoretic sealing of impoundment leaks. The model describes the formation of a compressible clay cake because of electrical and gravitational forces. The model includes mass balance equations for the solid particles and liquid phase, modified Darcy's law in an electrical field, and Terzaghi's definition of effective stress. The formulation is presented in the Eulerian coordinates. The resulting second-order, nonlinear partial differential equation and the lower boundary condition are linearized to obtain an analytical solution for time-dependent settlement. After discretizing in time the analytical solution is applied to simulate compression of an accreting sediment. In the simulation of an accreting sediment, solid fluxes on either side of suspension/sediment interface are coupled using a no-jump condition. The velocity of a discrete particle in the suspension zone is assumed to be equal to the algebraic sum of electrophoretic and Stoke's settling velocities. An empirical relationship available in the literature is used to account for the effect of concentration on the velocity of solid particles in the suspension zone. The validity of the semianalytical approach is partially verified using an exact steady state solution for self-weight consolidation. The simulation results obtained for a set of material parameters are presented graphically. It is noted that the electrokinetic consolidation of sediment continues even after the completion of electrophoretic settling of all clay particles. An analysis reveals that the electrophoretic cake formation process is quite sensitive to voltage gradient and the coefficient of compressibility. [ABSTRACT FROM AUTHOR]

Petroleum products, such as gasoline, leaked from an underground storage tank can be recovered successfully by two-pump operations. The success of the recovery effort depends on the accurate placement of the recovery well at the spill site. An effective recovery operation can minimize the remaining contamination mass in the subsurface. Therefore, a careful evaluation and determination has to be made as to where to locate the recovery well. The location of the well can be decided based on an estimation of the extent and thickness of free product on the water table. Such an estimation should be based on analysis of governing mechanisms. In this study we present analytical solutions to estimate the recovery of oil from an established oil lens. These solutions are obtained by applying the Laplace transformation to averaged linear partial differential equations governing the phenomenon. The governing equation for the free product thickness is derived by averaging the oil phase mass balance equation along the free product thickness and substituting the boundary conditions at the oil/water interface and oil surface. The analytical solutions estimate the temporal and spatial distribution of free product thickness on the water table for a number of recovery scenarios. Results are presented for the temporal and spatial variation of the free product thickness, temporal variation of the free product volume recovered, and recovery efficiency based on the readings at the monitoring wells. Since they can be utilized without a great deal of data, analytical solutions are quite attractive as screening tools in two-pump free product recovery operations. [ABSTRACT FROM AUTHOR]