Multiscale Modeling Methods Research Articles

A multiscale modeling methodfor therapeutic antibodies in ion exchange chromatography.

The development of biopharmaceutical downstream processes relies on exhaustive experimental studies. The root cause is the poorly understood relationship between the protein structure of monoclonal antibodies (mAbs) and their macroscopic process behavior. Especially the development of preparative chromatography processes is challenged by the increasing structural complexity of novel antibody formats and accelerated development timelines. This study introduces a multiscale in silico model consisting of homology modeling, quantitative structure-property relationships (QSPR), and mechanistic chromatography modeling leading from the amino acid sequence of a mAb to the digital representation of its cation exchange chromatography (CEX) process. The model leverages the mAbs' structural characteristics and experimental data of a diverse set of 21 therapeutic antibodies to predict elution profiles of two mAbs that were removed from the training data set. QSPR modeling identified mAb-specific protein descriptors relevant for the prediction of the thermodynamic equilibrium and the stoichiometric coefficient of the adsorption reaction. The consideration of two discrete conformational states of IgG4 mAbs enabled prediction of split-peak elution profiles. Starting from the sequence, the presented multiscale model allows in silico development of chromatography processes before protein material is available for experimental studies.

The evolutionary advantage of an aromatic clamp in plant family 3 glycoside exo-hydrolases

In the barley β-d-glucan glucohydrolase, a glycoside hydrolase family 3 (GH3) enzyme, the Trp286/Trp434 clamp ensures β-d-glucosides binding, which is fundamental for substrate hydrolysis during plant growth and development. We employ mutagenesis, high-resolution X-ray crystallography, and multi-scale molecular modelling methods to examine the binding and conformational behaviour of isomeric β-d-glucosides during substrate-product assisted processive catalysis that operates in GH3 hydrolases. Enzyme kinetics reveals that the W434H mutant retains broad specificity, while W434A behaves as a strict (1,3)-β-d-glucosidase. Investigations of reactant movements on the nanoscale reveal that processivity is sensitive to mutation-specific alterations of the tryptophan clamp. While wild-type and W434H utilise a lateral cavity for glucose displacement and sliding of (1,3)-linked hydrolytic products through the catalytic site without dissociation, consistent with their high hydrolytic rates, W434A does not adopt processive catalysis. Phylogenomic analyses of GH3 hydrolases disclose the evolutionary advantage of the tryptophan clamp that confers broad specificity, high catalytic efficiency, and processivity.

Experimental and theoretical studies on friction contact of bolted joint interfaces

This paper presents experimental and theoretical modeling studies on the tangential contact stiffness and friction hysteresis of bolted joint interfaces under transversal vibration. A new test rig was developed to measure the interface fretting response of bolted joints. This rig is based on a servo-hydraulic fatigue testing system in which the contact surfaces are arranged symmetrically to avoid bending of the specimen that could affect the friction measurement. Force-displacement curves were measured under different tangential loads and compared with those found in the literature. A multi-scale contact modeling method was proposed to calculate the tangential contact stiffness and reproduce the friction hysteresis of bolted joint interfaces. This method overcomes the complexity of identifying contact stiffness, which usually requires a model of the dynamic behavior of the joint and frequency responses measured with dedicated fretting test stands. Specifically, this method comprehensively considers the multi-scale features of randomly rough surfaces, the non-uniform contact pressure distribution, and the convenience of phenomenological contact models in simulating frictional hysteresis, relying on fractal contact theory and discretized Iwan model. The effectiveness of the proposed method was verified by comparing the simulation results with the experimental counterparts in different cases of tangential loading. The successful validation demonstrates the potential of the proposed modeling method for application to structures with bolted joint.

Tradeoff between the Ion Exchange-Induced Residual Stress and Ion Transport in Solid Electrolytes

Rapid filament growth of lithium is limiting the commercialization of solid-state lithium metal anode batteries. Recent work demonstrated that lithium filaments grow into pre-existing or nascent cracks in the solid electrolyte, suggesting that increasing the fracture toughness of the solid electrolytes will inhibit filament penetration. It has been suggested that introducing residual compressive stresses at the surface of the solid electrolyte can provide this additional fracture toughness. One of the ways to induce these residual compressive stresses is by exchanging lithium ions (Li+) with larger isovalent ions such as potassium (K+). On the other hand, incorporation of too much potassium can alter the lithium-ion diffusion pathway and lower the diffusivity, thus limiting the performance of the solid-state electrolyte. Using multiscale modeling methods, we optimize this tradeoff and predict that exchanging 3.4% potassium ions up to a depth twice the grain sizes in Li7La3Zr2O12 solid electrolyte can induce a maximum residual compressive stress of around 1.1 GPa, corresponding to an increase in fracture strength by ∼8 times, while lowering the diffusivity in the ion-exchanged region by a factor of 5 at room temperature. The reduction of lithium diffusivity is due to K+-induced stress and (mainly) blockage of lithium ion pathways in the shallow ion-exchanged layer.

A consistency evaluation method for digital twin models

Digital twin has shown its great application values in various fields in the past few years, especially manufacturing. During the process of digital twin implementation, the digital twin model is one of the most important foundations. Because the effectiveness and accuracy of digital twin models could directly affect the quality of related services. Nowadays, some efforts have been made on digital twin modeling methods, e.g. multi-disciplinary modeling method, multi-dimension modeling method, and multi-scale modeling method. Besides, the research on Industrial Internet of Things makes it possible to realize the synchronization between digital twin models and the corresponding physical objects. However, the attention on how to conduct a comprehensive consistency evaluation between the models and corresponding physical objects is not enough. Against the background, this paper proposed a consistency evaluation framework towards digital twin shop-floor (DTS) models. The consistency evaluation method mainly contains two phases, i.e. before and after model assembly and model fusion. Before model assembly and model fusion, the geometry models, physics models, behavior models, and rule models are mainly considered. After model assembly and fusion, the overall performance of assembled models and fusion models is paid more attention. Furthermore, the analytic hierarchy process(AHP) is used to form a comprehensive consistency evaluation result for DTS models. At last, a specific application scenario in complex product AIT (Assembly, Integration and Test) shop-floor is given to explain how to apply the proposed framework and method.

Understanding Interfacial Nanoparticle Organization through Simulation and Theory: A Review.

Understanding the behaviors of nanoparticles at interfaces is crucial not only for the design of novel nanostructured materials with superior properties but also for a better understanding of many biological systems where nanoscale objects such as drug molecules, viruses, and proteins can interact with various interfaces. Theoretical studies and tailored computer simulations offer unique approaches to investigating the evolution and formation of structures as well as to determining structure-property relationships regarding the interfacial nanostructures. In this feature article, we summarize our efforts to exploit computational approaches as well as theoretical modeling in understanding the organization of nanoscale objects at the interfaces of various systems. First, we present the latest research advances and state-of-the-art computational techniques for the simulation of nanoparticles at interfaces. Then we introduce the applications of multiscale modeling and simulation methods as well as theoretical analysis to explore the basic science and the fundamental principles in the interfacial nanoparticle organization, covering the interfaces of polymer, nanoscience, biomacromolecules, and biomembranes. Finally, we discuss future directions to signify the framework in tailoring the interfacial organization of nanoparticles based on the computational design. This feature article could promote further efforts toward fundamental research and the wide applications of theoretical approaches in designing interfacial assemblies for new types of functional nanomaterials and beyond.

Investigation of the Second Harmonic Generation at the Water-Vacuum Interface by Using Multi-Scale Modeling Methods.

The Sequential Quantum Mechanics/Molecular Mechanics scheme has been enacted to perform a systematic investigation of the polarizability (α) and first hyperpolarizability (β) responses at the water-vacuum interface. After performing classical molecular dynamics simulations to provide snapshots of the structures, quantum chemistry calculations of the linear and nonlinear optical responses have been performed for clusters of five water molecules at the time-dependent DFT level in combination with different embedding schemes, ranging from point charges to polarizable point charges, with and without local field effects. When going from the bulk to the interface, the main observations of these calculations encompass i) a modest increase of the average polarizability but an increase by about a factor of two of its anisotropy, ii) an increase by about 20 % of the βHRS response, accompanied by a small increase of its depolarization ratio, and iii) a net increase of the component of the β tensor normal to the interface (βzzz ) as well as of β// . Globally, the interfacial effects on β are localized at the first molecular layer while they are observed up to the fourth molecular layer on α.

Towards understanding deformation and fracture in cementitious lattice materials: Insights from multiscale experiments and simulations

Tailoring lattice structures is a commonly used method to develop lattice materials with desired mechanical properties. However, for cementitious lattice materials, besides the macroscopic lattice structure, the multi-phase microstructure of cement paste may have substantial impact on the mechanical responses. Therefore, this work proposes a multi-scale numerical modelling method to simulate the deformation and fracture behavior of cementitious lattice materials, such that the influence of cement paste microstructure can be properly captured. On the microscale, the load–displacement response of cement paste is numerically simulated then experimentally validated. In order to rationally investigate the role of cement paste microstructure, the obtained load–displacement response was then formulated to several types of model inputs reflecting different degree of brittleness. These inputs were then used for simulating the mechanical response of macroscale cementitious lattices. By comparing the simulation to experiment, multi-linear behavior (ML) was found to an appropriate method to include the realistic pre-critical cracking and post-peak softening of cement paste in the model. Compared to ideally brittle behavior, using ML as input, the discrepancy between simulated and experimentally tested fracture energy decreases from 37.4% to 12.4%. In addition, the influence of lattice structure on the strength of cementitious lattices was also accurately captured by the proposed model. Randomized cementitious lattice has 21.6% (22.0% from simulation) lower strength than regular lattice. Moreover, the influence of fracture criterion of the proposed model is discussed and elaborated. Owning to the high simulation accuracy, the proposed multi-scale method in this work could be helpful for tailoring the fracture cementitious lattice materials for future studies.

Multi-scale modeling method for polycrystalline materials considering grain boundary misorientation angle

Grain boundaries (GBs) are microstructures in polycrystalline materials, which influence the mechanical properties of materials significantly. Simulation is an indispensable means to study GBs due to its high flexibility. However, the existing GB simulation models mostly focus on a single simulation scale, lack the consideration of the grain boundary misorientation angle (GBMA) characteristic and fail to describe the coupled elastic–plastic damage behavior between grains and GBs accurately. To describe the influence mechanism of GB on the mechanical behavior of materials accurately, a GBMA-considered multi-scale modeling method for polycrystalline materials is proposed in this paper. The method is based on molecular dynamics (MD), the crystal plasticity finite element method and the cohesive zone model, which considers the GBMA information at grain and atomic scales comprehensively. Firstly, a GB geometric model containing GBMA characteristic is generated at grain scale through EBSD information. Then the GB cohesive parameters are obtained at the atomic scale by MD simulation. Finally, some experiments are performed for verification, which indicates the high accuracy of the proposed method. Furthermore, three models with the same geometric shape and different grain orientation and GBMA are established to study the influence of GBMA on the mechanical properties of polycrystalline materials.

A multiscale soft-contact modelling method for rough surfaces in contact with coupled slipping/sliding and rolling

This paper presents a multiscale soft-contact modelling (SCM) method for characterising the rough surfaces in contact with coupled slipping/sliding and rolling. The microscale flattening of the random surface asperities subjected to a plastically deformed substrate was accommodated by a statistical analysis with a dynamic explicit finite element analysis (FEA). A soft-contact algorithm was developed to effectively treat the cross-scale deformation of the microscopic asperities and that of the macroscopic body. An efficient modularised strategy including an input module and a hybrid SCM-FEA module was established to analyse the interaction at the interface of the two contacting bodies associated with coupled slipping/sliding and rolling. The modelling method was validated by a typical metal forming process, cold rolling of metal strips.

A multiscale numerical homogenization-based method for the prediction of elastic properties of components produced with the fused deposition modelling process

Industry is increasingly using additive manufacturing processes because of the speed and economy with which they can produce components of complex geometry. Among these processes, one of the most interesting is the Fused Filament Fabrication (FFF) technique, which allows the moulding of thermoplastic polymers reinforced with chopped or continuous fibres. The applicability of this technology on an industrial scale is linked to the ability to model and predict the mechanical properties of the produced parts. To date there is no universally accepted strategy to solve this issue. In this study, a multiscale modelling method based on numerical homogenization is proposed to properly simulate the mechanical performance of parts manufactured by using FFF. The mechanical behaviour of specimens was studied by means of a FEM software at different scales: microscopic, mesoscopic and macroscopic, showing the influence of the specific microstructure of each size level on the next scale. The effectiveness of the proposed models was evaluated by means of a wide experimental campaign, which tested specimens reinforced with short fibres and specimens reinforced with a combination of chopped and continuous fibres. The comparison of the mechanical properties estimated by using the numerical models with the experimental data showed a good correlation demonstrating the capabilities of the proposed approach.

Multiscale modeling and design of lattice truss core sandwich metastructures for broadband low-frequency vibration reduction

Lattice truss core sandwich structures are advanced lightweight structures that have broad application prospects in many fields, but the attenuation of low-frequency vibrations in these structures is still challenging. To achieve broadband low-frequency vibration reduction in lattice truss core sandwich structures, we propose a design of multiscale lattice truss core sandwich metastructures which exhibit a coupling effect of local resonance and Bragg scattering mechanisms. For ease of analysis and design of such multiscale metastructures, we develop an efficient semi-analytical multiscale modeling method based on a combination of the dynamic homogenization method and the spectral element method. The multiscale modeling method is verified by comparing it with the conventional finite element method, and it is further employed to design multiscale metastructures. Numerical and experimental results demonstrate that the low-frequency bandgap and vibration reduction band can be greatly broadened via an appropriate multiscale design. Specifically, a typical multiscale finite metastructure, fabricated by embedding only three identical local resonators, achieves a significant vibration reduction within the super-wide low-frequency range of 295–905.4 Hz. The normalized vibration reduction bandwidth is as large as 1.02, which is much broader than that of a conventional equi-scale metastructure designed with the same added resonator mass ratio.

Multiscale modelling framework for elasticity of ultra high strength concrete using nano/microscale characterization and finite element representative volume element analysis

Ultra-High Strength Concrete (UHSC) (greater than 100 MPa) is a mechanically superior material compared with the Normal Strength Concrete (NSC) due to its inherent performance characteristics. Improved modulus of elasticity is one of the key target characteristics in the development of UHSC. Macroscopic response of UHSC is a result of a multitude of phases in different spatial length scales such as mesoscale, microscale, nanoscale etc. and investigating these spatial scales can yield a better understanding about contribution of each heterogenous phases to the macroscopic behaviour of UHSC. In this paper, a new multiscale modelling method including procedures to obtain micro/nano scale properties is proposed to predict the macroscopic elastic modulus using nanoindentation experiments, hydration simulations, Scanning Electron Microscopy (SEM) and Finite Element Representative Volume Element (FE-RVE) modelling.Characterization of nanomechanical properties of the cementitious composite was carried out using nanoindentation, microstructural characterization was performed using scanning electron microscopy, and hydration simulation of the cementitious paste was carried out using Virtual Cement and Concrete Testing Laboratory (VCCTL) software. A five-level multiscale framework is proposed for UHSC and results from these experimental testing and simulations were used as inputs in the proposed framework.A novel algorithm which can model any volume fraction of different phases was developed to generate geometries for RVEs to be used in FE-RVE simulations. Upscaling of elastic modulus using FE-RVE was found to be very accurate, and this method can generate detailed variation of microfields inside the RVE. A parametric study was carried out on how varying inhomogeneities in the RVE, boundary conditions, and the shape of the inhomogeneities would affect the homogenized elastic modulus.Continuum micromechanics models such as Mori-Tanaka method and Self Consistent Scheme were used for the analytical homogenization at each scale for comparison with FE-RVE method. The results of the proposed FE-RVE analysis, the Mean Field Homogenization (MFH) method, and experiment were compared and found to be a very good fit.

Modelling of Environmental Ageing of Polymers and Polymer Composites-Durability Prediction Methods.

Polymers and polymer composites are negatively impacted by environmental ageing, reducing their service lifetimes. The uncertainty of the material interaction with the environment compromises their superior strength and stiffness. Validation of new composite materials and structures often involves lengthy and expensive testing programs. Therefore, modelling is an affordable alternative that can partly replace extensive testing and thus reduce validation costs. Durability prediction models are often subject to conflicting requirements of versatility and minimum experimental efforts required for their validation. Based on physical observations of composite macroproperties, engineering and phenomenological models provide manageable representations of complex mechanistic models. This review offers a systematised overview of the state-of-the-art models and accelerated testing methodologies for predicting the long-term mechanical performance of polymers and polymer composites. Accelerated testing methods for predicting static, creep, and fatig ue lifetime of various polymers and polymer composites under environmental factors’ single or coupled influence are overviewed. Service lifetimes are predicted by means of degradation rate models, superposition principles, and parametrisation techniques. This review is a continuation of the authors’ work on modelling environmental ageing of polymer composites: the first part of the review covered multiscale and modular modelling methods of environmental degradation. The present work is focused on modelling engineering mechanical properties.

Parametric analyses on multiscale elastic behavior of 3D braided composites with pore defects

The manufacturing-induced pore defects are inevitable, and show detrimental effects on the mechanical behavior of 3D braided composites. In this paper, two different multiscale modeling methods of pore defects are established to investigate the void type on the elastic behavior of 3D braided composites. The multiscale elastic responses under various loading conditions are also discussed. The parametric analyses have been conducted including the void characteristics (i.e. void distribution and void content), and braiding features (i.e. fiber content and braiding angles). Also, a homogenization method has been proposed to simplify the calculation of effective constants considering pore defects. Results show that the void type and void distribution have negligible effects on the elastic properties of yarns and braided composites. Oppositely, the void content shows the decisive influences. The fiber distribution has limited effects on the elastic behavior of yarns, but the opposite conclusion has been obtained for the fiber content and braiding angles. The matrix, fibers, axial and braiding yarns show diverse load-bearing responses under various loadings across scales. The present multiscale homogenization scheme is effective to predict the effective elastic constants of 3D braided composites. This method can simplify the elastic analyses of 3D braided composites considering pore defects.

Multiscale modeling based failure criterion of injection molded SFRP composites considering skin-core-skin layered microstructure and variable parameters

Injection molded short fiber reinforced polymer (IMSFRP) composites are superior lightweight materials with great potential application in many industries. One of the most challenging tasks is to predict the failure strength of the materials containing complicated fiber distributions. In this study, a parameterized failure criterion of IMSFRP composites is proposed based on multiscale modeling method. On the microscale, the RVE models with multiple constituents and different fiber orientation distributions are built to predict the failure envelopes of the microstructures. The constitutive model of single layer is proposed to describe micromechanical behaviors of the materials. On the mesoscale, a skin-core-skin (SCS) model is proposed considering the variation of fiber orientation in the thickness direction, namely layered structure. Three parameters of SCS model are extracted from the result of injection molding simulation and the relationships between the microstructural parameters and mechanical properties are built by means of surrogate modeling technique. Finally, a parameterized failure criterion is established which considers the layered structures of the materials and is capable to capture the variation of strength at different locations on a practical component. The numerical analysis and bench tests of an automobile IMSFRP composite liftgate inner verify the effectiveness and accuracy of the proposed parameterized failure criterion.

Multi-scale modeling and simulation for multi-pass processing of Ta-2.5 W alloy

Multi-pass deformation and annealing process is commonly utilized to prepare billets with homogeneous fine microstructure. Characterizing the deformation and microstructural evolution is not easy due to the complex process. This study proposed a multi-scale modeling and simulation method for the multi-pass processing and it was validated by experiments. Firstly, an integrate multi-scale model involving strain hardening and static softening equations was developed based on multi-pass cold deformation and annealing tests of Ta-2.5 W alloy. Of note, the model captures both deformation behavior and static softening and the model equations of each pass were integrated into a unified manner. Then, multi-scale simulation including finite element (FE) and cellular automatic (CA) methods was coupled with the developed model for static recrystallization (SRX) analysis. FE analysis was firstly performed to predict the distributions of strain, dislocation density as well as SRX. Simultaneously, the predicted data was used for generation of the initial conditions for mesoscopic model. Finally, a CA method was applied for further analysis on recrystallization nucleation and grain growth. The modeling and simulation method is examined by multi-pass cold deformation and annealing test and a reasonable consistency is obtained between experimental and predicted results.

Multiscale Analysis of Short Fiber Reinforced Composites Using Machine Learning

A new data-driven multi-scale material modeling method called Deep Material Network (DMN), based on the Representative Volume Element (RVE) method and machine learning techniques, has been developed to predict physical properties with high accuracy and speed. DMN represents the response of RVE by forming a network using a mechanical building block that avoids the loss of intrinsic physics that occurs in common neural networks. The network can be constructed based on the analysis of linear elastic RVEs and can predict the nonlinear characteristics of various RVEs. In this paper, the basic concept of DMN is explained and its application to short-fiber reinforced composites is verified. The results confirm that DMN can reproduce the nonlinear response of the RVE with the same accuracy and orders of magnitude faster than the results of direct numerical simulations.

A multi-scale modeling method for digital twin shop-floor

Digital twin has attracted more and more attentions in the past few years. To put digital twin into practice, modeling is one of the most important foundations. Under this background, some modeling research on digital twin shop-floor which is regarded as the basic unit for realizing smart manufacturing has been carried out. However, current research pays scant attention to the multi-scale features of shop-floor, which hinders the effective application of digital twin shop-floor. As for the problem about how to realize the model construction from the perspective of time-scale and space-scale, this paper firstly proposed a multi-layer modeling framework for supporting model construction from unit layer to system layer to system of system layer. Moreover, the mechanism of model changes over time is also considered. Then, the specific procedures and methods of model assembly, model fusion and model update towards machines and shop-floor are discussed respectively. Finally, a satellite AIT(Assembly, Integration and Test) shop-floor is chosen as the case to validate the correctness and feasibility of proposed framework, procedures and methods.

Size Effect on Mechanical Behaviors of Intact Rocks Based on Enlarged Digital Models

The size effect on mechanical behaviors of rock materials has been a challenging topic. The previous research is mainly to study the relationship between known large-scale models and representative element volumes. However, only limited scale models can be obtained in situ or laboratory in many cases, so tests or simulations of mechanical response behaviors of large-scale models cannot be carried out. In order to obtain large-scale models, this paper proposes a multi-scale enlarged digital modeling method to synthesize granite models based on texture self-similarity. The representational ability of synthetic granite is analyzed by using mathematical statistics and finite-difference numerical method. The results show that synthetic granite can characterize the natural rock well in terms of texture morphology, geometric characteristics, and mechanical behaviors. Then, the size effect on mechanical behaviors of intact granite is performed based on an enlarged digital model. The results show that the uniaxial compressive strength of intact granite increases with the increase of model size. In addition, the relationship between heterogeneity and homogeneity is established at different unit scales by using the synthetic digital granite model. The enlarged digital rock model has great potential in studying size effects with rock heterogeneity.