The multiscale modeling and data mining of high-temperature dielectrics of SiO_2/SiO_2 composites

The high temperature dielectrics of Quartz fiber-reinforced silicon dioxide ceramic （Si02/SiO2 ） composites were studied both theoretically and experimentally. A multi-scale theoretical model was developed based on the theory of dielectrics. It was realized to predict dielectric properties at higher temperature （ 〉 1200 ℃） by experimental data mining for correlative coefficients in model. The results show that the dielectrics of SiO2/SiO2, which were calculated with the theoretical model, were in agreement with experimental measured value.

Multiscale modeling of mechanical behavior and failure mechanism of 3D angle-interlock woven aluminum composites subjected to warp/weft directional tension loading

The mechanical behavior and progressive damage mechanism of novel aluminum matrix composites reinforced with 3D angle-interlock woven carbon fibers were investigated using a multiscale modeling approach.The mechanical properties and failure of yarns were evaluated using a microscale model under different loading scenarios.On this basis,a mesoscale model was developed to analyze the tensile behavior and failure mechanism of the composites.The interfacial decohesion,matrix damage,and failure of fibers and yarns were incorporated into the microscopic and mesoscopic models.The stress–strain curves and fracture modes from simulation show good agreement with the experimental curves and fracture morphology.Local interface and matrix damage initiate first under warp directional tension.Thereafter,interfacial failure,weft yarn cracking,and matrix failure occur successively.Axial fracture of warp yarn,which displays a quasi-ductile fracture characteristic,dominates the ultimate composites failure.Under weft directional tension,interfacial failure and warp yarn rupture occur at the early and middle stages.Matrix failure and weft yarn fracture emerge simultaneously at the final stage,leading to the cata-strophic failure of composites.The weft directional strength and fracture strain are lower than the warp directional ones because of the lower weft density and the more serious brittle fracture of weft yarns.

A MULTISCALE MODELING APPROACH INCORPORATING ARIMA AND ANNS FOR FINANCIAL MARKET VOLATILITY FORECASTING

The financial market volatility forecasting is regarded as a challenging task because of irreg ularity, high fluctuation, and noise. In this study, a multiscale ensemble forecasting model is proposed. The original financial series are decomposed firstly different scale components （i.e., approximation and details） using the maximum overlap discrete wavelet transform （MODWT）. The approximation is pre- dicted by a hybrid forecasting model that combines autoregressive integrated moving average （ARIMA） with feedforward neural network （FNN）. ARIMA model is used to generate a linear forecast, and then FNN is developed as a tool for nonlinear pattern recognition to correct the estimation error in ARIMA forecast. Moreover, details are predicted by Elman neural networks. Three weekly exchange rates data are collected to establish and validate the forecasting model. Empirical results demonstrate consistent better performance of the proposed approach.

Multiscale modeling of the atmospheric environment over a forest canopy

Vegetation constitutes one of the fundamental types of land use on Earth.The presence of trees in urban areas can decrease local winds and exchange sensible and latent heat with the surrounding environments,thus exerting notable influences on the urban microenvironment.A better understanding of the turbulent transfer of momentum and scalars around vegetation canopy could significantly contribute to improvement of the urban environment.This work develops a large-eddy simulation(LES)method that is applicable to model the flow and scalar transport over the forest canopy.We study the atmospheric flow over complex forested areas under typical weather conditions by coupling LES to the mesoscale model.Models of radiation and energy balance have been developed with explicit treatment of the vegetation canopy.By examining the flow over a forest canopy under a range of stability conditions,we found that buoyancy enhances or suppresses turbulent mixing in unstable or stable atmosphere respectively,with decreasing or increasing wind shear,respectively.From the multiscale modeling of the Beijing Olympic Forest Park,the present coupling scheme proves to better resolve the diurnal variations in wind speed,temperature,and relative humidity over complex urban terrains.The coupling scheme is superior to the traditional mesoscale model in terms of wind field simulation.This is mainly because the coupling scheme not only takes the influences of external mesoscale flow into consideration,but also resolves the heterogeneous urban surface at a fine scale by downscaling,thus better reproducing the complex flow and turbulent transport in the urban roughness sublayer.

Method of cells-based multiscale modeling of elastic properties of filament wound C/C-SiC including free Si and matrix porosity

Three different multiscale models, based on the method of cells(generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent modeling of all phases using the generalized method of cells, synergistic(two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical(one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC.Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute. Finally, un-reacted Si(or free Si) and porosity in the C matrix are included in the multiscale model, and the effect of these new phases on the stiffness and local stresses are considered.

Compositional colored Petri net approach to multiscale modeling for systems biology

Colored Petri nets have been demonstrated as a powerful tool for modeling multiscale systems biology.However,the construction of colored Petri nets for biological systems requires prior knowledge about colored Petri nets and is often error-prone and cum-bersome for biologists,especially when the communication between components and hierarchical organization of components in a multiscale model are an issue.To address this problem,an established way is to develop small components and then compose them into bigger models.In this paper,we present a compositional colored Petri net approach to aid automatic modeling of systems biology,and demonstrate it with two case stud-ies.We focus on the modeling of communication between components and hierarchical organization of components as they are key to build multiscale models.

Sequential Multiscale Modeling Using Sparse Representation

The main obstacle in sequential multiscale modeling is the pre-computation of the constitutive relationwhich often involvesmany independent variables.The constitutive relation of a polymeric fluid is a function of six variables,even after making the simplifying assumption that stress depends only on the rate of strain.Precomputing such a function is usually considered too expensive.Consequently the value of sequential multiscale modeling is often limited to“parameter passing”.Here we demonstrate that sparse representations can be used to drastically reduce the computational cost for precomputing functions of many variables.This strategy dramatically increases the efficiency of sequential multiscale modeling,making it very competitive in many situations.

Mathematical Constraints in Multiscale Subgrid-Scale Modeling of Nonlinear Systems

To shed light on the subgrid-seale （SGS） modeling methodology of nonlinear systems such as the Navier-Stokes turbulence, we define the concepts of assumption and restriction in the modeling procedure, which are shown by generalized derivation of three general mathematical constraints for different combinations of restrictions. These constraints are verified numerically in a one-dimensional nonlinear advection equation. This study is expected to inspire future research on the SGS modeling methodology of nonlinear systems.

Multiscale tensegrity model for the tensile properties of DNA nanotubes

DNA nanotubes(DNTs)with user-defined shapes and functionalities have potential applications in many fields.So far,compared with numerous experimental studies,there have been only a handful of models on the mechanical properties of such DNTs.This paper aims at presenting a multiscale model to quantify the correlations among the pre-tension states,tensile properties,encapsulation structures of DNTs,and the surrounding factors.First,by combining a statistical worm-like-chain(WLC)model of single DNA deformation and Parsegian's mesoscopic model of DNA liquid crystal free energy,a multiscale tensegrity model is established,and the pre-tension state of DNTs is characterized theoretically for the first time.Then,by using the minimum potential energy principle,the force-extension curve and tensile rigidity of pre-tension DNTs are predicted.Finally,the effects of the encapsulation structure and surrounding factors on the tensile properties of DNTs are studied.The predictions for the tensile behaviors of DNTs can not only reproduce the existing experimental results,but also reveal that the competition of DNA intrachain and interchain interactions in the encapsulation structures determines the pre-tension states of DNTs and their tensile properties.The changes in the pre-tension states and environmental factors make the monotonic or non-monotonic changes in the tensile properties of DNTs under longitudinal loads.

A Multiscale Understanding of the Thermodynamic and Kinetic Mechanisms of Laser Additive Manufacturing

Selective laser melting （SLM） additive manufacturing （AM） technology has become an important option for the precise manufacturing of complex-shaped metallic parts with high performance. The SLM AM process involves complicated physicochemical phenomena, thermodynamic behavior, and phase transformation as a high-energy laser beam melts loose powder particles. This paper provides multiscale modeling and coordinated control for the SLM of metallic materials including an aluminum （Al）-based alloy （AlSi10Mg）, a nickel （Ni）-based super-alloy （Inconel 718）, and ceramic particle-reinforced Al-based and Ni-based composites. The migration and distribution mechanisms of aluminium nitride （AIN） particles in SLM-processed Al- based nanocomposites and the in situ formation of a gradient interface between the reinforcement and the matrix in SLM-processed tungsten carbide （WC）/Inconel 718 composites were studied in the microscale. The laser absorption and melting/densification behaviors of AISilOMg and Inconel 718 alloy powder were dis- closed in the mesoscale. Finally, the stress development during line-by-line localized laser scanning and the parameter-dependent control methods for the deformation of SLM-processed composites were proposed in the macroscale. Multiscale numerical simulation and experimental verification methods are beneficial in monitoring the complicated powder-laser interaction, heat and mass transfer behavior, and microstructural and mechanical properties development during the SLM AM process.

Multiscale Mechanics and Optimization of Gastropod Shells

A vast majority of mollusks grow a hard shell for protection. The structure of these shells comprises several levels of hierarchy that increase their strength and their resistance to natural threats. This article focuses on nacreous shells, which are composed of two distinct layers. The outer layer is made of calcite, which is a hard but brittle material, and the inner layer is made of nacre, a tough and ductile material. The inner and outer layers are therefore made of materials with distinct structures and properties. In this article, we demonstrate that this system is optimum to defeat attacks from predators. A two-scale mod- eling and optimization approach was used. At the macroscale, a two-layer finite element model of a seashell was developed to capture shell geometry. At the microscale, a representative volume element of the microstructure of nacre was used to model the elastic modulus of nacre as well as a multiaxial failure criterion, both expressed as function of microstructural parameters. Experiments were also performed on actual shells of red abalone to validate the results obtained from simulations and gain insight into the way the shell fails under sharp perforation. Both optimization and experimental results revealed that the shell displays optimum performance when two modes of failure coincide within the structure. Finally, guidelines for designing two-layer shells were proposed to improve the performance of engineered protective systems undergoing similar structural and loading conditions.

A MULTISCALE MECHANICAL MODEL FOR MATERIALS BASED ON VIRTUAL INTERNAL BOND THEORY

Only two macroscopic parameters are needed to describe the mechanical properties of linear elastic solids, i.e. the Poisson＇s ratio and Young＇s modulus. Correspondingly, there should be two microscopic parameters to determine the mechanical properties of material if the macroscopic mechanical properties of linear elastic solids are derived from the microscopic level. Enlightened by this idea, a multiscale mechanical model for material, the virtual multi-dimensional internal bonds （VMIB） model, is proposed by incorporating a shear bond into the virtual internal bond （VIB） model. By this modification, the VMIB model associates the macro mechanical properties of material with the microscopic mechanical properties of discrete structure and the corresponding relationship between micro and macro parameters is derived. The tensor quality of the energy density function, which contains coordinate vector, is mathematically proved. From the point of view of VMIB, the macroscopic nonlinear behaviors of material could be attributed to the evolution of virtual bond distribution density induced by the imposed deformation. With this theoretical hypothesis, as an application example, a uniaxial compressive failure of brittle material is simulated. Good agreement between the experimental results and the simulated ones is found.

Multiscale Characterization of Automotive Surface Coating Formation for Sustainable Manufacturing

Automotive surface coating manufacturing is one of the most sophisticated and expensive steps in automotive assembly. This step involves generating multiple thin layers of polymeric coatings on the vehicle surface through paint spray and curing in a multistage, dynamically changing environment. Traditionally, the quality control is solely post-process inspection based, and process operational adjustment is only experience based, thus the manufacturing may not be （highly） sustainable. In this article, a multiscale system modeling and analysis methodology is introduced for achieving a sustainable application of polymeric materials through paint spray and film curing in automotive surface coating manufacturing. By this methodology, the correlations among paint material, application processes and coating performance can be identified. The model-based analysis allows a comprehensive and deep study of the dynamic behaviors of the material, process, and product in a wide spectrum of length and time. Case studies illustrate the efficacy of the methodology for sustainable manufacturing.

Design of Sustainable Multifunctional Nanocoatings：A Goal-driven Multiscale Systems Approach

Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive,aerospace,ship-making,construction,and pharmaceutical industries.However,how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area.The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes.In this work,the challenging objectives of sustainable design and manufacturing are simultaneously accomplished by resorting to multiscale systems theory and engineering sustainability principles.The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials,product and associated manufacturing processes covering a wide range of length and time scales.Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled.The integration of different methods and theories at individual scales allows the quantitative prediction of macroscopic system performance from the fundamental molecular behavior.Furthermore,mathematically rigorous and methodologically viable approaches are pursued to achieve sustainability-goal-oriented design of material-process-product systems.The introduced methodology can greatly facilitate experimentalists in novel material invention and new knowledge discovery.At the same time,it can provide scientific guidance and reveal various new opportunities and effective strategies for achieving sustainable manufacturing.The methodological attractiveness will be fully demonstrated by a detailed case study on the design of thermoset nanocomposite coatings.

Very Large Eddy Simulation of Cavitation from Inception to Sheet/Cloud Regimes by A Multiscale Model

The cavitating flow in different regimes has the intricate flow structure with multiple time and space scales.The present work develops a multiscale model by coupling the volume of fluid(VOF)method and a discrete bubble model(DBM),to simulate the cavitating flow in a convergent-divergent test section.The Schnerr-Sauer cavitation model is used to calculate the mass transfer rate to obtain the macroscale phase structure,and the simplified Rayleigh-Plesset equation is applied to simulate the growing and collapsing of discrete bubbles.An algorithm for bridging between the macroscale cavities and microscale bubbles is also developed to achieve the multiscale simulation.For the flow field,the very large eddy simulation(VLES)approach is applied.Conditions from inception to sheet/cloud cavitation regimes are taken into account and simulations are conducted.Compared with the experimental observations,it is shown that the cavitation inception,bubble clouds formation and glass cavity generation are all well represented,indicating that the proposed VOF-DBM model is a promising approach to accurately and comprehensively reveal the multiscale phase field induced by cavitation.

Gravitational effects on global hemodynamics in different postures:A closed-loop multiscale mathematical analysis

We present a novel methodology and strategy to predict pressures and flow rates in the global cardiovascular network in different postures varying from supine to upright. A closed-loop, multiscale mathematical model of the entire cardiovascular system (CVS) is developed through an integration of one-dimensional (1D) modeling of the large systemic arteries and veins, and zero-dimensional (0D) lumped-parameter modeling of the heart, the cardiac-pulmonary circulation, the cardiac and venous valves, as well as the microcirculation. A versatile junction model is proposed and incorporated into the 1D model to cope with splitting and/or merging flows across a multibranched junction, which is validated to be capable of estimating both subcritical and supercritical flows while ensuring the mass conservation and total pressure continuity. To model gravitational effects on global hemodynamics during postural change, a robust venous valve model is further established for the 1D venous flows and distributed throughout the entire venous network with consideration of its anatomically realistic numbers and locations. The present integrated model is proven to enable reasonable prediction of pressure and flow rate waveforms associated with cardiopulmonary circulation, systemic circulation in arteries and veins, as well as microcirculation within normal physiological ranges, particularly in mean venous pressures, which well match the in vivo measurements. Applications of the cardiovascular model at different postures demonstrate that gravity exerts remarkable influence on arterial and venous pressures, venous returns and cardiac outputs whereas venous pressures below the heart level show a specific correlation between central venous and hydrostatic pressures in right atrium and veins.

A multiscale model for analyzing the synergy of CS and WSS on the endothelium in straight arteries

A multiscale model was proposed to calculate the circumferential stress （CS） and wall shear stress （WSS） and analyze the effects of global and local factors on the CS, WSS and their synergy on the arterial endothelium in large straight arteries. A parameter pair [Zs, SPA] （defined as the ratio of CS amplitude to WSS amplitude and the phase angle between CS and WSS for different harmonic components, respectively） was proposed to characterize the synergy of CS and WSS. The results demonstrated that the CS or WSS in the large straight arteries is determined by the global factors, i.e. the preloads and the afterloads, and the local factors, i.e. the local mechanical properties and the zero-stress states of arterial walls, whereas the Zs and SPA are primarily determined by the local factors and the afterloads. Because the arterial input impedance has been shown to reflect the physiological and pathological states of whole downstream arterial beds, the stress amplitude ratio Zs and the stress phase difference SPA might be appropriate indices to reflect the influences of the states of whole downstream arterial beds on the local blood flow-dependent phenomena such as angiogenesis, vascular remodeling and atherosgenesis.

Dynamic Elastic Modulus of Cement Paste at Early Age based on Nondestructive Test and Multiscale Prediction Model

This paper introduced a nondestructive testing method to evaluate the dynamic elastic modulus of cement paste. Moreover, the effect of water-cement ratio and conventional admixtures on the dynamic elastic modulus of cement paste was investigated, in which three kinds of admixtures were taken into account including viscosity modifying admixture （VMA）, silica.fume （SF）, and shrinkage-reducing admixture （SRA）. The experimental results indicate that the dynamic elastic modulus of cement paste increases with decreasing water-cement ratio. The addition of SF increases the dynamic elastic modulus, however, the overdosage of VMA causes its reduction. SRA reduces the dynamic elastic modulus at early age without affecting it in later period. Finally, a multiscale micromechanics approach coupled with a hydration model CEMHYD3D and percolation theory is utilized to predict the elastic modulus of cement paste, and the predictive results by the model are in accordance with the experimental data.

Numerical modeling and simulation of PEM fuel cells: Progress and perspective

This paper provides a comprehensive review on the research and development in multi-scale numerical modeling and simulation of PEM fuel cells. An overview of recent progress in PEM fuel cell modeling has been provided. Fundamental transport phenomena in PEM fuel cells and the corresponding mathematical formulation of macroscale models are analyzed. Various important issues in PEM fuel cell modeling and simulation are examined in detail, including fluid flow and species transport, electron and proton transport, heat transfer and thermal management, liquid water transport and water management, transient response behaviors, and cold-start processes. Key areas for further improvements have also been discussed.

Progresses on two-phase modeling of proton exchange membrane water electrolyzer

The Proton Exchange Membrane(PEM)water electrolyzer is considered one of the promising energy storing means for harnessing variable renewable energy sources to produce hydrogen.Understanding the internal fluid dynamics,which are often challenging to directly observe experimentally,has prompted the use of numerical models to investigate two-phase flow within PEM water electrolyzers.In this study,we provide a comprehensive review of prior research focusing on two-phase modeling of PEM electrolyzers,encompassing both components at mesoscopic scales and the full electrolyzer at the macroscopic level.We delve into the specifics of various modeling approaches for two-phase flow at different scales and summarize and discuss the current state of the art in the field.Presently,two-phase models for the full electrolyzer predominantly employ a macroscopic homogeneous assumption.However,mesoscopic and microscopic models capable of tracking phase interfaces are limited to components.Challenges persist in integrating various modeling scales into a comprehensive electrolyzer model,particularly in coupling two-phase flow between the channels and porous media.Future efforts should focus on developing multi-scale models and simulating two-phase flow under fluctuating input conditions.Additionally,given the structural similarities between PEM water electrolyzers and PEM fuel cells,we compare and discuss differences in two-phase modeling between the two technologies.This work offers the insights for researchers in the field of modeling of PEM water electrolyzers and even fuel cells.