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This study retrospectively examined the health and social determinants of the COVID-19 outbreak in 175 countries from a spatial epidemiological approach. We used spatial analysis to examine the cross-national determinants of confirmed cases of COVID-19 based on the World Health Organization official COVID-19 data and the World Bank Indicators of Interest to the COVID-19 outbreak. All models controlled for COVID-19 government measures. The percentage of the population age between 15-64 years (Age15-64), percentage smokers (SmokTot.), and out-of-pocket expenditure (OOPExp) significantly explained global variation in the current COVID-19 outbreak in 175 countries. The percentage population age group 15-64 and out of pocket expenditure were positively associated with COVID-19. Conversely, the percentage of the total population who smoke was inversely associated with COVID-19 at the global level. This study is timely and could serve as a potential geospatial guide to developing public health and epidemiological surveillance programs for the outbreak in multiple countries. Removal of catastrophic medical expenditure, smoking cessation, and observing public health guidelines will not only reduce illness related to COVID-19 but also prevent unecessary deaths. [ABSTRACT FROM AUTHOR]

On-board storage of hydrogen is a key challenge in the deployment of fuel cell technology for transportation and distributed energy generation. Hydrogen adsorption capacity of up to 6 wt% has been reported for the metal-organic framework MOF-5, at 30 bar and 77 K. However, powders of MOF-5 suffer from low volumetric storage density and poor thermal conductivity for practical use in adsorptive storage systems. Compaction of MOF-5 to form pellets and inclusion of expanded natural graphite (ENG) has been used to address these issues, but their effect on the overall refueling dynamics for a fixed-bed has not been studied. To this end, we use simulations of multiscale pellet-and-bed model (developed in a companion paper) to analyze the impact of pellet modification on the dynamics of hydrogen refueling under cryogenic conditions. We show that a fixed bed with 0.52 g/cc density pellets is recommended, compared to MOF-5 powder or lower-density pellets. In spite of some loss of gravimetric capacity, the former shows good performance in a fixed bed with improved volumetric capacity and reasonable refueling time. Although individual pellet behavior is improved by addition of ENG to the 0.52 g/cc pellets, this has only a minor effect on refueling dynamics of the fixed bed with pellet size of 6 mm or lower. Finally, the effect of pellet size, density and ENG addition is analyzed and recommendations for fixed bed adsorber design are presented. • Adsorption of H 2 in a fixed bed of MOF-5 pellets and MOF-5 powders compared • Effect of pellet densification on refueling dynamics investigated using multiscale model • Pellet densification improves storage capacity as well as refueling dynamics • Addition of ENG is recommended for pellet sizes larger than 6 mm • Map of optimum operating conditions for fixed-bed developed for H 2 cryo-adsorption [ABSTRACT FROM AUTHOR]

Reliable design, analysis and optimization of on-board adsorptive hydrogen storage systems require mathematical models that capture the key physics across multiple scales. Pellets of adsorbent may sometimes be preferred for adsorptive storage in fixed beds, compared to powders. Heat and mass transfer within individual pellets play a significant role in the overall dynamics of a fixed bed filled with adsorbent pellets. However, multiscale dynamical model that captures the effect of pellet behavior on the overall dynamics of adsorbent bed is so far missing. In this study, a combined bed–and–pellet "1D-plus-1D" model is developed and analyzed for hydrogen adsorption in a fixed bed of MOF-5 pellets at cryogenic temperatures. Specifically, a 1D axial bed model with mass, momentum and energy balance equations is coupled with a 1D radial pellet model comprising of mass and heat transfer with adsorption within the pellets present at different locations in the bed. The 1D bed and 1D pellet model equations are coupled through surface fluxes on the pellet. We show that internal diffusional resistances within pellets must be considered for pellets greater than 2 mm diameter, for parameters relevant to MOF-5 pellets. The role of various physical parameters of pellets is analyzed. • A multiscale model is developed for H 2 cryo-adsorption in a fixed bed of pellets. • Mass and energy balances within the pellet account for diffusion and adsorption. • Axial mass and energy balances in the bed are coupled with the pellet model. • Internal diffusional resistances are relevant for hydrogen adsorption in MOF-5 pellets. • Thermal diffusion time scale is defined to quantify the importance of internal diffusion. [ABSTRACT FROM AUTHOR]

Results are presented from developing a parallel code for a joint solution to the nonlinear three-dimensional heat equation and the Poisson equation in creating a multiscale model for phase-change memory based on amorphous carbon nanofilms (a-C). Their numerical convergence is investigated. The parallel effectiveness of the new code is examined on the IBM BlueGene/P supercomputer. [ABSTRACT FROM AUTHOR]

The onset of frictional motion couples complex spatiotemporal dynamics of discrete contacts with different orders of magnitude at time and length scales. In order to reveal how these individual scales affect the frictional sliding, we establish a 2D multiscale spring-block model for the frictional sliding at an elastic slider-rigid interface. In this model, the rupture of frictional interface is described by three different types of locally microscopic motion: pinned, sliding and dislocated states. By using realistic boundary conditions, our numerical results can precisely reproduce the loading curves found in previous experiments. The precursor events, corresponding to a discrete sequence of rapid crack-like fronts propagating partially in the contact zone, can also be shown in our simulation. From the analysis of the microscopic motion, we characterize the evolution of the real contact area and the corresponding interface motion at the mesoscale level, and show that the evolution corresponds to four distinct and inter-related phases: detachment, fast and slow slip motion, as well as the rest of slip. These mesoscale behaviors are completely consistent with the existing experimental results and their physical mechanisms can be explained by the detailed information of the numerical simulation. The study is established on a bottom-up multiscale model which provides a comprehensive picture about the complex spatiotemporal dynamics of frictional sliding. [ABSTRACT FROM AUTHOR]

The ionic conductivity of acceptor doped ceria is strongly influenced by grain boundaries and interfaces, with most experiments showing a conductivity decrease in these regions. Classical models explain this observation by the formation of space charge layers, that are depleted of mobile ionic charge carriers. However, some experiments demonstrate an increase in ionic conductivity and recent models show that the space charge layers can also be enriched in mobile ionic species. Because of these discrepancies, it is still not certain whether nanocrystalline or thin film ceria can offer superior ionic conductivity or not. Recently, we have demonstrated by means of Monte Carlo simulations that the ionic conductivity in space charge layers can indeed exceed the bulk value. In this work, we combine these Monte Carlo simulations with a continuum model to predict charge carrier concentration profiles. This multiscale approach allows for a realistic prediction of the grain boundary ionic conductivity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There are many challenges to coupling the macroscale to the microscale in temporal or spatial contexts. In order to examine effects of an individual movement and spatial control measures on a disease outbreak, we developed a multiscale model and extended the semi-stochastic simulation method by linking individual movements to pathogen’s diffusion, linking the slow dynamics for disease transmission at the population level to the fast dynamics for pathogen shedding/excretion at the individual level. Numerical simulations indicate that during a disease outbreak individuals with the same infection status show the property of clustering and, in particular, individuals’ rapid movements lead to an increase in the average reproduction number R 0 , the final size and the peak value of the outbreak. It is interesting that a high level of aggregation the individuals’ movement results in low new infections and a small final size of the infected population. Further, we obtained that either high diffusion rate of the pathogen or frequent environmental clearance lead to a decline in the total number of infected individuals, indicating the need for control measures such as improving air circulation or environmental hygiene. We found that the level of spatial heterogeneity when implementing control greatly affects the control efficacy, and in particular, an uniform isolation strategy leads to low a final size and small peak, compared with local measures, indicating that a large-scale isolation strategy with frequent clearance of the environment is beneficial for disease control. [ABSTRACT FROM AUTHOR]

Mathematical models can provide a quantitatively sophisticated description of tumor cell (TC) behaviors under mechanical microenvironment and help us better understand the role of specific biophysical factors based on their influences on the TC behaviors. To this end, we propose an off-lattice cell-based multiscale mathematical model to describe the dynamic growth-induced solid stress during tumor progression and investigate the influence of the mechanical microenvironment on TC invasion. At the cellular level, cell–cell and cell–matrix interactive forces depend on the mechanical properties of the cells and the cancer-associated fibroblasts in the stroma, respectively. The constitutive relationship between the interactive forces and cell migrations obeys the Hooke's law and damping effects. At the tissue level, the integrated growth-induced forces caused by proliferating cells within the simulation region are balanced by the external forces applied by the surrounding host tissues. Then, the cell movements are calculated according to the Newton's second law of motion, and the morphology of TC invasion is updated. The simulation results reveal the continuous changes of the macroscopic mechanical forces due to the interactions among the structural components and the microscopic environmental factors. Moreover, the simulation results demonstrate the adverse effect of the stiffness of tumor tissue on tumor growth and invasion. A decrease in the stiffness of tumor and matrix can promote TCs to proliferate at a much faster rate and invade into the surrounding healthy tissue more easily, whereas an increase in the stiffness can lead to an aggressive morphology of tumor invasion. We envision that the proposed model can be served as a quantitative theoretical platform to study the underlying biophysical role of the mechanical microenvironmental factors during tumor invasion and metastasis. [ABSTRACT FROM AUTHOR]

Designing of power electronics converters seldom considers multiscale coupling relationship between components and circuits. Although macroscale is computationally efficient, it barely contains the micro implications about aging, deterioration, transient performance, etc. Conversely, the microscale obtains multiple observation scope, however, with computational disaster. In this paper, the multiscale method is applied in the power electronic modeling which provides a qualitative methodology to combine the scales appropriately, and to obtain the dynamic response under the action of multiphysics accurately. Firstly, the concept of multiscale and the scale division of power electronic system are expounded. Considered the dynamic behavior of components and converters with different complexity, the framework of multiscale converters and modeling method is proposed. Afterwards, a scalable coupling separation method is presented, providing interfaces for the multiphysics and dielectric physics. Additionally, a multiscale conversion algorithm considering both efficiency and accuracy is designed. In the end, a DC/DC converter is taken for the verification. The feasibility and advantages of multiscale method and conversion algorithm have been demonstrated in accuracy, consistency and multiple analysis. By filling in the microscale observation, it is plausible to provide theoretical guidance for reducing margin, accurate analysis and reliability estimation of electronic components. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We investigate the effect of magneto-mechanical and magnetocrystalline anisotropies in a test application by coupling a multiscale magneto-mechanical model with a finite element method. This first application is composed of a cylindrical conductor surrounded by a ring composed of a non-oriented FeSi3% steel sheet which contains 396 representative grain orientations. Such an application can reveal the anisotropy due to the texture of the material by inducing a rotational flux density within the ring. Moreover, the effect of the texture and the magneto-mechanical characteristic of the steel sheets is analyzed in an axially laminated synchronous reluctance machine. The effect of stress strongly emphasizes the anisotropic behavior of NO steel sheets. [ABSTRACT FROM AUTHOR]

This paper focuses on the numerical modelling of autogenous and stimulated healing of cracks in fibre-reinforced cementitious composites, with the aim of showing the potential that a multiphysics and multi-scale discrete model has in capturing the complex hygro-thermo-chemo-mechanical processes governing concrete ageing and its capability of autonomously repairing cracks. This study expands a prior research on numerical modelling of self-healing of normal-strength concrete, to simulate the autogenous and stimulated healing of cracks in fibre-reinforced cement-based composites. The proposed extended model explicitly differentiates between (i) major cracks in the cementitious matrix and (ii) debonding cracks at matrix–fibre interface. The increased fibre-matrix bond due to the healing products along the interface cracks is explicitly implemented to capture the possibility of having a healing-induced mechanical recovery even when major cracks are totally or partially unhealed, complying with experimental evidence available in the literature. The model can also simulate the material ageing. After the model formulation and implementation in the Multiphysics-Lattice Discrete Particle Model (M-LDPM) framework, an example of calibration and validation for one of the Ultra High Performance Concrete (UHPC) mixes developed within the Horizon 2020 project ReSHEALience is presented. • Numerical model of crack autogenous and stimulated healing in FRCs. • The model is also able to simulate the material strength and stiffness build-up. • The model can be easily extended to simulate innovative cementitious materials. • The procedure for the model calibration and validation is presented. [ABSTRACT FROM AUTHOR]

Hepatitis C virus (HCV) can establish infection via two distinct modes: virus-to-cell infection and cell-to-cell transmission. These infections prompt the activation of two types of adaptive immune responses: the cytotoxic T lymphocyte response and the antibody response. In this paper, we study HCV dynamics by developing a multiscale model that incorporates both modes of infection as well as the two types of immune responses. We derive both the basic reproduction number of virus and four immune reproduction numbers for the model. We identify five equilibria, the existence of which depends on the values of basic reproduction number of virus and the immune reproduction numbers. We also establish the global asymptotic stability of the equilibria by employing Lyapunov functions, which further underscores the profound impact of the aforementioned reproduction numbers on the model's overall stability. [ABSTRACT FROM AUTHOR]

Clarifying species-environment relationships is crucial for the development of efficient conservation and restoration strategies. However, this work is often complicated by a lack of detailed information on species distribution and habitat features and tends to ignore the impact of scale and landscape features. Here, we tracked 11 Oriental White Storks (Ciconia boyciana) with GPS loggers during their wintering period at Poyang Lake and divided the tracking data into two parts (foraging and roosting states) according to the distribution of activity over the course of a day. Then, a three-step multiscale and multistate approach was employed to model habitat selection characteristics: (1) first, we minimized the search range of the scale for these two states based on daily movement characteristics; (2) second, we identified the optimized scale of each candidate variable; and (3) third, we fit a multiscale, multivariable habitat selection model in relation to natural features, human disturbance and especially landscape composition and configuration. Our findings reveal that habitat selection of the storks varied with spatial scale and that these scaling relationships were not consistent across different habitat requirements (foraging or roosting) and environmental features. Landscape configuration was a more powerful predictor for storks’ foraging habitat selection, while roosting was more sensitive to landscape composition. Incorporating high-precision spatiotemporal satellite tracking data and landscape features derived from satellite images from the same periods into a multiscale habitat selection model can greatly improve the understanding of species-environmental relationships and guide efficient recovery planning and legislation.

Mechanical stimulation can regulate cellular behavior, e.g., differentiation, proliferation, matrix production and mineralization. To apply fluid-induced wall shear stress (WSS) on cells, perfusion bioreactors have been commonly used in tissue engineering experiments. The WSS on cells depends on the nature of the micro-fluidic environment within scaffolds under medium perfusion. Simulating the fluidic environment within scaffolds will be important for gaining a better insight into the actual mechanical stimulation on cells in a tissue engineering experiment. However, biomaterial scaffolds used in tissue engineering experiments typically have highly irregular pore geometries. This complexity in scaffold geometry implies high computational costs for simulating the precise fluidic environment within the scaffolds. In this study, we propose a low-computational cost and feasible technique for quantifying the micro-fluidic environment within the scaffolds, which have highly irregular pore geometries. This technique is based on a multiscale computational fluid dynamics approach. It is demonstrated that this approach can capture the WSS distribution in most regions within the scaffold. Importantly, the central process unit time needed to run the model is considerably low. [ABSTRACT FROM AUTHOR]

Pressure ulcers are devastating injuries that disproportionately affect the older adult population. The initiating factor of pressure ulcers is local ischemia, or lack of perfusion at the microvascular level, following tissue compression against bony prominences. In turn, lack of blood flow leads to a drop in oxygen concentration, i.e, hypoxia, that ultimately leads to cell death, tissue necrosis, and disruption of tissue continuity. Despite our qualitative understanding of the initiating mechanisms of pressure ulcers, we are lacking quantitative knowledge of the relationship between applied pressure, skin mechanical properties as well as structure, and tissue hypoxia. This gap in our understanding is, at least in part, due to the limitations of current imaging technologies that cannot simultaneously image the microvascular architecture, while quantifying tissue deformation. We overcome this limitation in our work by combining realistic microvascular geometries with appropriate mechanical constitutive models into a microscale finite element model of the skin. By solving boundary value problems on a representative volume element via the finite element method, we can predict blood volume fractions in response to physiological skin loading conditions (i.e., shear and compression). We then use blood volume fraction as a homogenized variable to couple tissue-level skin mechanics to an oxygen diffusion model. With our model, we find that moderate levels of pressure applied to the outer skin surface lead to oxygen concentration contours indicative of tissue hypoxia. For instance, we show that applying a pressure of 60 kPa at the skin surface leads to a decrease in oxygen partial pressure from a physiological value of 65 mmHg to a hypoxic level of 31 mmHg. Additionally, we explore the sensitivity of local oxygen concentration to skin thickness and tissue stiffness, two age-related skin parameters. We find that, for a given pressure, oxygen concentration decreases with decreasing skin thickness and skin stiffness. Future work will include rigorous calibration and validation of this model, which may render our work an important tool toward developing better prevention and treatment tools for pressure ulcers specifically targeted toward the older adult patient population. [ABSTRACT FROM AUTHOR]

Knee articular cartilage is characterized by a complex mechanical behavior, posing a challenge to develop an efficient and precise model. We argue that the cartilage damage, in general, can be traced to the fibril level as a plastic deformation, defined as micro-defects. To investigate these micro-defects, we have developed a detailed finite element model of the entire healthy tibiofemoral joint (TF) including a multiscale constitutive model which considers the structural hierarchies of the articular cartilage. The net model was simulated under physiological loading conditions to predict joint response under 2000 N axial compression and damage initiation under high axial loading (max 7 KN) when the TF joint flexed to 30°. Computed results sufficiently agreed with earlier experimental and numerical studies. Further, initiation and propagation of damage in fibrils were computed at the tibial cartilage located mainly in the superficial and middle layers. Our simulation results also indicated that the stiffer the fibril is (higher cross-link densities), the higher the contact stress required to elicit a fibril yield and the higher the rate of yielding as a function of increased contact stress. To the best of our knowledge, this is the first model that combines macro-continuum joint mechanics and micromechanics at the tissue level. The computational construct presented here serves as a simulation platform to explore the interplay between acute cartilage damage and micromechanics characteristics at the tropocollagen level. [ABSTRACT FROM AUTHOR]

• High performance RPC was prepared with a new procedure. • A series conventional triaxial compression tests for RPC pastes was carried out. • The effects of porosity on mechanical behaviors of RPC pastes were investigated. • A multiscale constitutive model for RPC pastes under compression was presented. This paper presents experimental and numerical studies on the triaxial mechanical behaviors of reactive powder cement (RPC) pastes prepared with an alcohol-based shrink-reducing admixture (ASRA) and ice-replaced mixing procedure. Standard cylindrical samples were cored from three kinds of high strength RPC pastes. For each kind of RPC pastes, a series of triaxial compression tests were performed under different confining pressures. It is shown that the RPC pastes under consideration present a typical quasi-brittle behaviours, including nonlinearity of stress-strain curves, strain hardening/softening, pressure sensitivity, volumetric dilatancy, triaxial strength nonlinearity, etc.For completeness, triaxial cyclic tests with two different confining pressure were conducted to analyse the mechanical damage characteristics of RPC pastes. Based on the experimental investigations and considering the mircostructure evolution of RPC pastes, a two-step homogenization-based multiscale constitutive model was developed. The model allows to take into account the influence of porosity on elastic constants, material damage induced by mesocracking as well as plastic deformation caused by frictional sliding. There is a good agreement between numerical simulations and experimental data. [ABSTRACT FROM AUTHOR]

Loading assumptions used for the structural design of segmental linings often improperly reflect the complex load combinations that develop during the construction of a bored tunnel. Therefore segment designs used in practice tend to be on the safe side and often rely on conventional reinforcement methods instead of including other reinforcement concepts, such as steel fibres. In this contribution, a multi‐scale computational modelling framework is proposed to investigate the response of steel‐fibre reinforced, traditionally reinforced, and hybrid‐reinforced lining segments to radial loadings with an emphasis on the longitudinal joints. This modelling approach offers an opportunity to directly investigate the influence of type and content of steel fibres on the performance of segmented linings at the structural scale. Using this framework, a method for robust optimization is applied in order to generate damage‐tolerant hybrid segment designs. [ABSTRACT FROM AUTHOR]

Due to the nonlinear properties of superconductors, modeling of high-temperature superconducting (HTS) devices is difficult, especially for the ones in large scale. In this paper, we develop the multiscale model from a two-dimensional (2-D) planar geometry to a 2-D axisymmetric geometry to successfully calculate ac loss of large-scale HTS coils. By applying appropriate boundary conditions, the infinite-turn coil is built in the 2-D-axisymmetric model to produce approximated current density for an HTS coil. Besides, the multiscale model is improved in terms of coupling, so that submodels can be connected in one file and the external data processing is not needed. Validation on accuracy and efficiency is demonstrated through a double-pancake coil. Results are compared with a conventional model that considers the superconducting characteristics on each turn of the coil in actual size. This paper shows the development and improvement of multiscale model in the 2-D axisymmetric geometry is feasible. Due to its high accuracy and efficiency, the developed multiscale model can be a useful approach to analyze electromagnetic characteristics and calculate ac losses in large-scale HTS magnets. [ABSTRACT FROM AUTHOR]

In electrochemical devices such as solid oxide cell stacks, many physical phenomena are interacting on many different length scales in an intricate geometry. Modeling is a strong tool to understand the interior of such devices during operation, enhance their design and investigate long-term response (degradation). Computations can however be challenging as the many geometric details and coupled physical phenomena require a significant computational power, and in some cases, even state-of-the-art clusters will not be sufficient. This hinders the use of the models for the further development of the technology. In this work, we present an original type of solid oxide cell stack model, which is highly computationally efficient, resulting in computations which are two orders of magnitude faster than the conventional type of stack models with all geometric details explicitly represented. In the model presented here, the geometric details are implicitly represented by using the so-called homogenization. The resulting homogeneous anisotropic media provides the correct overall response (temperature, species, molar fractions, etc.). Local details as the mechanical stress in the electrolyte are not represented explicitly. These can be retrieved by localization through sub-models (multiscale model), in some cases without loss of computational efficiency, as demonstrated. • Homogenization decreases the computational times by two orders of magnitude. • All relevant physics and couplings for solid oxide cells stack are homogenized. • Local conditions can be retrieved by localization, i.e. using sub-models. • Sub- and homogenized models constitute a multi-scale model. • The multi-scale model provides full detail with fast computations. [ABSTRACT FROM AUTHOR]

Free-radical emulsion polymerization is a heterogeneous process where simultaneous and competitive physicochemical events occur over a wide range of time/length scales. Although a highly accurate representation of the process is possible by multiscale modeling, common approaches face several issues, including the stochastic nature of finer scales, the timely exchange of information between scales, and the high computational load for the model solution. In this work, a reduced-order computationally-tractable multiscale model is proposed while preserving a good predictive capability. The model integrates microscopic-scale calculations based on kinetic Monte Carlo simulations (stochastic), a mesoscopic-scale representation of the particle size distribution through a novel statistical approach and a deterministic description of the macroscopic-scale. The proposed model resulted in faster satisfactory predictions (compared to the model based on the Fokker Planck Equation) of traditional macro and mesoscopic variables, along with the average number of free radicals and secondary nucleation on a microscopic scale. [ABSTRACT FROM AUTHOR]

Abstract A multiscale coupled model is developed to simulate the compressible fluid flow in fractured media aquifer system, where the flow is governed by Forchheimer's law in the fracture and continuum porous medium. Due to the fact that the thickness of fracture is much smaller than characteristic diameters of surrounding porous medium, the fracture is reduced to a lower dimensional interface and a more complicated transmission condition is derived on the fracture-interface. The coupled model is numerically solved by the finite difference method with an implicit iteration procedure. The fewest nodal points are used to construct the optimal scheme for approximating the multiscale Forchheimer–Forchheimer coupled model. Different degrees of freedom are located on both sides of fracture-interface in order to capture the jump of velocity. Second-order error estimates in discrete norms are derived on nonuniform staggered grids for both pressure and velocity. The proposed scheme can also be extended to high dimensional model without loss of accuracy. Numerical experiments are performed to demonstrate the efficiency and accuracy of the numerical method. [ABSTRACT FROM AUTHOR]

Expansion of concrete caused by external sulfate attack (ESA) is a multiscale chemomechanical response, mainly including internal stress evolution at the dormant period and significant cracking expansion for a detrimental duration in hardened cement paste (HCP). The internal stress generated in the dormant period of ESA can result in the microcracking of HCP and further significant volume expansion of concrete, which can reduce the durability of concrete structures. Based on the ESA-induced expansion mechanism, a multiscale model is developed to describe the expansion response of HCP in the dormant period of ESA. In this model, a saturated and homogeneous HCP and a representative volume element (RVE), which is composed of a pore and nearby cement paste, are regarded as macroscopic and microscopic objects, respectively. By using Fick's law and reaction kinetics, a diffusion-reaction model is proposed to simulate the macroscopic sulfate diffusion in HCP and microscopic chemical reaction to produce ettringite in RVE. According to the crystallization pressure theory and continuum mechanics, some mechanical models are constructed to investigate the microscopic mechanical response caused by the supersaturation of ettringite in RVE and its induced macroscopic mechanical response in HCP. Taking a HCP cylinder under different sulfate exposures as an example, a numerical simulation is performed to investigate its expansion response in the dormant period of ESA. [ABSTRACT FROM AUTHOR]

Abstract A new heat source model is proposed for the simulation of the temperature rises in the laser deposition melting additive manufacturing process. The obtained temperature histories in different layers can be used to predict the microstructural evolutions in a multiscale strategy including the grain cluster scale and single grain scale in Monte Carlo model. It is found that re-melting and re-heating due to different temperature histories of different layers are main factors to affect the microstructural evolutions in LAM. By use of the predicted microstructural and the self-consistent model, the flow stresses at different strain rates and temperatures are predicted. The predicted flow stress shows that the flow stress is higher in the middle of the as-built LAM product but lower near the top or the bottom surfaces. The increase of the scanning speed of laser can lead to the increase of the size of heat affected zone, which is the reason for the formation of larger grain sizes and more α generations in higher scanning speed. Higher α volume fraction is the main reason for higher mechanical property in higher scanning speed. [ABSTRACT FROM AUTHOR]

Erosive wear of hydraulic machines is a common issue, which results in efficiency degradation, the enhancement of cavitation, and the need for expensive maintenance. Although numerical simulations of the erosion process could be very useful, both for understanding and predicting the process, its multiscale nature renders it very difficult to simulate. A previously validated multiscale model of erosion is presented. It consists of two coupled sub-models: On the microscale, the sediment impacts are simulated by means of comprehensive physical models; on the macroscale, the turbulent sediment transport and erosion accumulation are calculated. A multiscale simulation of the erosion of a prototype-scale Pelton bucket impacted by a sediment-laden water jet is presented. The simulation results, namely the erodent flux and the distributions of average impact angle and velocity on the bucket surface, bring insight into the erosion process. Furthermore, the results explain the obtained erosion distribution, which is in very good agreement with the experimental erosion measurements available in the literature for the same test case. [ABSTRACT FROM AUTHOR]

Dynamical encoding models characterize neural activity with low-dimensional hidden states that dynamically evolve in time and gienerate behavior. Current methods have identified these models from single-scale activity, either spikes or fields. However, behavior is simultaneously encoded across multiple spatiotemporal scales of activity, from spikes of individual neurons to neural population activity measured through fields. Identifying a multiscale dynamical model to extract hidden states that simultaneously describe spike-field activities is challenging because of their fundamental differences. Spikes are binary-valued with fast millisecond time-scales while fields are continuous-valued with slower time-scales. Here, we develop a novel multiscale dynamical modeling and identification algorithm to simultaneously characterize multiscale spike-field dynamics and extract multiscale hidden states. We also devise a modal approach to dissociate task-relevant and task-irrelevant dynamics. Using extensive simulations, we show that the algorithm accurately identifies a multiscale dynamical model to simultaneously describe spike-field dynamics. Furthermore, the algorithm extracts hidden states that are multiscale, i.e., contain information from both spikes and fields and accurately predict behavior. Finally, the algorithm detects which of the identified dynamics are task-relevant and to what extent. This multiscale dynamical modeling and identification framework can help study neural dynamics across spatiotemporal scales and may facilitate future neurotechnologies. [ABSTRACT FROM AUTHOR]

Mathematical modeling has revealed the quantitative dynamics during the process of viral infection and evolved into an important tool in modern virology. Coupled with analyses of clinical and experimental data, the widely used basic model of viral dynamics described by ordinary differential equations (ODEs) has been well parameterized. In recent years, age-structured models, called "multiscale model," formulated by partial differential equations (PDEs) have also been developed and become useful tools for more detailed data analysis. However, in general, PDE models are considerably more difficult to subject to mathematical and numerical analyses. In our recently reported study, we successfully derived a mathematically identical ODE model from a PDE model, which helps to overcome the limitations of the PDE model with regard to clinical data analysis. Here, we derive the basic reproduction number from the identical ODE model and provide insight into the global stability of all possible steady states of the ODE model. [ABSTRACT FROM AUTHOR]

Highlights • A multi-scale model simulated the influence of conditions on thermosetting resins. • We simulated the effect on the structure and physical properties. • We focused on the synthesis of the phenol formaldehyde resin. • The comprehensive reaction model included the addition and condensation reactions. • The effectiveness of the reported model was validated. Abstract A multi-scale model that can simulate the influence of the synthetic conditions (e.g., molar ratio) on the structure and physical properties of thermosetting resins (e.g., phenol resin) through the introduction of a comprehensive reaction model that includes the addition reaction was developed and reported herein. The effectiveness of the model was validated by verifying the influence of the primary synthetic index, i.e., the molar ratio, on the physical and thermal properties (i.e., density and glass transition temperature) of Resol resins. This model can aid in developing more efficient and suitable synthetic conditions to obtain products exhibiting the desired material properties. [ABSTRACT FROM AUTHOR]

Osteoporotic hip fractures are a major healthcare problem. Fall severity and bone strength are important risk factors of hip fracture. This study aims to obtain a mechanistic explanation for fracture risk in dependence of these risk factors. A novel modelling approach is developed that combines models at different scales to overcome the challenge of a large space-time domain of interest and considers the variability of impact forces between potential falls in a subject. The multiscale model and its component models are verified with respect to numerical approximations made therein, the propagation of measurement uncertainties of model inputs is quantified, and model predictions are validated against experimental and clinical data. The main results are model predicted absolute risk of current fracture (ARF0) that ranged from 1.93 to 81.6% (median 36.1%) for subjects in a retrospective cohort of 98 postmenopausal British women (49 fracture cases and 49 controls); ARF0 was computed up to a precision of 1.92 percentage points (pp) due to numerical approximations made in the model; ARF0 possessed an uncertainty of 4.00 pp due to uncertainties in measuring model inputs; ARF0 classified observed fracture status in the above cohort with AUC = 0.852 (95% CI 0.753-0.918), 77.6% specificity (95% CI 63.4-86.5%) and 81.6% sensitivity (95% CI 68.3-91.1%). These results demonstrate that ARF0 can be computed using the model with sufficient precision to distinguish between subjects and that the novel mechanism of fracture risk determination based on fall dynamics, hip impact and bone strength can be considered validated. [ABSTRACT FROM AUTHOR]

Abstract Composite structures have been widely used in wind turbine equipment for their high stiffness to mass ratio and high strength. A major concern in the use of composite materials is their susceptibility to various micro damage, such as fiber breakage and matrix crack, which will lead to macroscopic structural fracture. In this paper, a multi-scale modeling strategy is proposed to investigate failure mechanisms and damage evolution of composite blades with initial defects from microscopic damage (including fiber fractures and matrix cracks) to macroscopic fracture. At the microscopic scale, an isoparametric micromechanical model is developed to calculate microscopic stresses and simulate microscopic damage. At the laminar scale, the classic laminate theory is employed to evaluate the laminate stiffness. At the structural scale, a reverse modeling technology is proposed to accurately acquire structural dimensions of a wind turbine blade, and a macroscopic 3D model is implemented into ANSYS/LS-DYNA software. By comparing with the experimental data, it is demonstrated that the proposed multi-scale method is suitable to predict mechanical properties of complex composite structures effectively. [ABSTRACT FROM AUTHOR]

Abstract Bone is a complex material showing a hierarchical and porous structure but also a natural ability to remodel thanks to cells sensitive to fluid flows. Based on these characteristics, a multiscale numerical model has been developed in order to represent the bone response under mechanical solicitation. It relies on the homogenization technique, simulating bone as a homogeneous structure having a porous microstructure saturated with bone fluid. The numerical modeling of the loading of a finite volume of bone enables the determination of an equivalent poroelastic stiffness. Focusing on two extreme fluid boundary conditions, the study of the corresponding structural response provides an overview of the fluid contribution to the poroelastic behavior, impacting the stiffness of the considered material. This parameter is either reduced (when the fluid can flow out of the structure) or increased (when the fluid is kept inside the structure) and quantified through this model. The presented poroelastic numerical model is here developed in the perspective of providing a bio-reliable model of bones, to determine the critical parameters that might impact bone remodeling. [ABSTRACT FROM AUTHOR]

• A three-dimensional multiscale numerical model of FRC was geometrically reconstructed. • A multiscale model for macro-mechanical behavior of FRC was proposed based on its compositions. • The stress response characteristics and mechanical properties of FRC were numerically investigated. A multiscale mechanical model is proposed to quantitatively describe the macro-mechanical behavior of fiber reinforced concrete (FRC) based on its multiscale material compositions. Firstly, according to the actual scale characteristics of compositions, the model of composite material at each scale of FRC, including hardened cement paste, cement mortar and meso -FRC, was geometrically reconstructed; Secondly, the equations of stiffness and strength of composite material at each scale were established by using the equivalent inclusion theory and Ottosen failure criterion, and a multiscale mechanical model of FRC was proposed by upscaling from stiffness and strength of microstructure to macro-mechanical behavior of FRC; Finally, after verified by the experimental results in the literature, the proposed model was used to numerically investigate the loading-induced stress response and the evolution of macro-mechanical properties of FRC in its curing process, as well as the influence of steel fiber parameters, such as volume fraction, aspect ratio and spatial orientation, on the mechanical properties of FRC. [ABSTRACT FROM AUTHOR]

A multiscale model of open-cell foams is developed for the characterization of heat exchangers. The model is applicable to a wide range of materials, cell sizes, and porosities. The microscopic geometry is based on a periodic model that is defined by the porosity and the specific surface area of the foam considered. The representative geometrical scales of the model are validated with microscope images and computed tomography scans. The outputs of the microscopic model are the coefficients of the pressure loss curve, the thermal conductivity, and the Nusselt number. These values are used as inputs of the macroscopic model that determines the thermal performance of a macroscopic system. The results given by the models are compared with experimental data obtained from the literature, and from an experimental setup built at CERN. It is concluded that the multiscale model provides accurate results in all open-cell foams considered. • A multiscale model of open-cell foams is developed. • The thermal performance of a heat exchanger is studied experimentally. • Numerical results from the multiscale model agree well with experimental data. [ABSTRACT FROM AUTHOR]

[Display omitted] • A multiscale method to predict mechanical properties of polymer composite is proposed. • The contributions include polymer matrix, particle filling and surface adhesion. • The comparisons between predictions and experimental measurements validate the model. • Further theoretical analysis on matrix composite and particle size distribution is performed. Owing to the multiscale structural characteristics and complex internal coupling, the evaluation of mechanical properties of a polymer composite upon its microstructural information is challenging. Herein, we propose a multiscale method for predicting the mechanical properties of polymer composites by accounting for the contributions of the polymer matrix and those from particle filling and particle–matrix interactions. The former contributions are addressed with the reference polymer matrix by means of molecular dynamic simulation, while the latter are described by a revised continuum model with the input from basic experimental data. The proposed model, validated with the corresponding experimental measurements, indicates that a small difference in the matrix composition can lead to a significant deviation of 60% in the ultimate stress at room temperature, and that the particle size distribution has a synergistic effect, resulting in a nonmonotonic dependence of the mechanical properties on the average particle size. This study provides a feasible engineering tool for evaluating the mechanical properties of polymer composites. [ABSTRACT FROM AUTHOR]

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms. [Display omitted] • Model of auditory thalamocortical circuits integrates multiscale experimental data • Simulates physiological membrane voltages, firing rates, LFP/CSD, and EEG signals • LFP/CSD oscillation events across frequencies match spontaneous in vivo data • Predicts cellular and circuit mechanisms underlying LFP/CSD oscillation events Dura-Bernal, Griffith, et al. developed a realistic computational model of macaque auditory thalamocortical circuits constrained by experimental data. Their model generates realistic physiological signals across scales, including voltages, spikes, LFP/CSD, and EEG. It reproduces in vivo spontaneous LFP/CSD oscillation events across frequencies and predicts their underlying cellular and circuit origins. [ABSTRACT FROM AUTHOR]

• Exploring the interdependence of HF MD physical process and geometric parameters. • Training and validation of multiscale and DNN models for flux prediction. • Proportional flux evolution to the flow rate oppositely to shell diameter. • Demonstration of better-predicted flux by DNN than multiscale model. • Validation of DNN model as a favorable tool for MD scale-up and module design. Membrane distillation (MD) is a promising emerging water desalination technology. Commercialization of MD modules has been hindered by ineffective heat recovery and temperature polarization effect. Although hollow fiber (HF) membranes provide the highest area-per-module, they are under-investigated compared to flat-sheet membranes due to the interconnection of geometric, thermal, and hydrodynamic parameters in HF MD process. In this work, the parameters impacting HF MD module design are performed based on multiscale and deep neural network (DNN) models. MD experiments are conducted to train and validate the machine learning and multiscale models. The developed models are used either to explain the effects of geometric, thermal, and hydrodynamic parameters on the permeate flux or to predict the flux of a given set of parameters. The results revealed an increase in flux with the flow rate, velocity, and feed temperature. However, it decreased with shell diameter and module length. Compared to the experimental fluxes, flux predictions using multiscale and DNN approaches were within 14% and 1.2%, respectively. The DNN model converged to a mean squared error of 1.21% (R2 = 0.96) within a few minutes and demonstrated its potential as a favorable tool for module design optimization due to its accuracy, speed, and low computational requirements. The present study effectively exhibits the advantages of using machine learning as a next-generation model for fast module design, optimization, and scale-up of MD technology. [ABSTRACT FROM AUTHOR]

Optimizing fired clay bricks to improve the thermo-mechanical performance requires a fundamental understanding of the links between brick microstructure and macro-properties. This is herein tackled by adopting a recently developed multiscale micromechanics model and challenging it with novel macroscopic test results for 18 fired clay bricks produced from seven different clays using different pore-forming additives. This comparison allows us to quantify the vitrification-induced strength increase of the microscopic binding matrix for clays with high carbonate and low illite contents. Micromechanics-based sensitivity analyses reveal optimization potentials regarding pore geometry and pore size distribution. • Compressive strength, stiffness, and thermal conductivity of 18 bricks are reported. • Structure-property relations are obtained from multiscale micromechanics modeling. • Optimization potentials for engineering the microstructures are revealed. • Pore-forming additives induce large microstress concentrations and low strengths. [ABSTRACT FROM AUTHOR]

Thermal conductivity (TC) is essential to characterize for thin-walled parts made of needled carbon/carbon (C/C) composites in the aviation sector. This paper thus proposes a hierarchical multiscale model to predict the TCs of needled C/C composites. This model can comprehensively consider the effects of the anisotropy of pyrolytic carbon matrices and the orientation and elongation of pores. At the microscale, representative volume element models of the needled fibers and weftless plies are established, respectively, and their TCs are estimated using the finite element homogenization method. Meanwhile, a combination of the finite element and orientation average method is developed for short-cut fiber plies. At the macroscale, a generated needled laminated model consisting of the weftless plies, short-cut fiber plies, and needled region, is established, where input properties are from homogenization results of microscale models. By comparing with experimental results, the proposed multiscale model is validated. The results show that effective TCs in the directions perpendicular and parallel to needled fibers drop by 13.18% and 13.06% respectively as the porosity increases from 6% to 14%. Additionally, it is found by microstructural parameter studies that it is possible to realize needled C/C composites with isotropic TCs. • A multiscale model of needled C/C composites is established. • The multiscale model agrees well with the Mori–Tanaka and experimental results. • Pores cause the almost same drop of thermal conductivities in X/Y and Z directions. • It provides roadmap for thermal-conductivity isotropic needled C/C composites. [ABSTRACT FROM AUTHOR]

Herein, a multiscale model comprising a quantum-chemical reaction path calculations, molecular dynamics (MD) simulations, and filament and laminate scale finite-element analyses (FEA) is proposed for predicting the failure of carbon-fiber-reinforced composites. In this study, the correlation between MD simulations and filament scale FEA was investigated and complemented. By this complementation, mechanical properties of a resin matrix used in FEA are evaluated by experiment-free MD simulations. The evaluated material properties, namely, failure properties and elasto-plastic properties of the resin matrix were validated using the results of compressive tests for neat resins DGEBA/4,4'-DDS, DGEBA/DETA, and TGDDM/4,4'-DDS. The predicted failure strain of the composites, under off-axis loads, were found to be in good agreement with previously reported experimental results. The FEA results revealed that both the failure and elasto-plastic properties of the resin matrix contribute to the failure of the composites, and the dominant properties vary for the laminate and load configuration. • Multiscale model to predict composite material failure from the atom to laminate scale. • FEA and MD simulations of the elasto-plastic and failure properties of resin matrices. • Theoretical correction and analysis applied to MD simulations for property analysis. • Detailed process of composite failure under off-axis loads revealed. [ABSTRACT FROM AUTHOR]