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Understanding the impact of the relativistic motion of a chiral molecule on its optical response is a prime challenge for fundamental science, but it also has a direct practical relevance in our search for extraterrestrial life. To contribute to these significant developments, we describe a multi–scale computational framework that combines quantum chemistry calculations and full–wave optical simulations to predict the chiral optical response from molecules moving at relativistic speeds. Specifically, the effect of a relativistic motion on the transmission circular dichroism (TCD) of three life–essential biomolecules, namely, B–DNA, chlorophyll a, and chlorophyll b, is investigated. Inspired by previous experiments to detect interstellar chiral molecules, we assume that the molecules move between a stationary observer and a light source, and we study the rotationally averaged TCD as a function of the speed of the molecule.We find that the TCD spectrum that contains the signatures of the molecules shifts with increasing speed to shorter wavelengths, with the effects already being visible for moderate velocities. [ABSTRACT FROM AUTHOR]

Recently, physics-informed neural networks (PINNs) have offered a powerful new paradigm for solving problems relating to differential equations. Compared to classical numerical methods, PINNs have several advantages, for example their ability to provide mesh-free solutions of differential equations and their ability to carry out forward and inverse modelling within the same optimisation problem. Whilst promising, a key limitation to date is that PINNs have struggled to accurately and efficiently solve problems with large domains and/or multi-scale solutions, which is crucial for their real-world application. Multiple significant and related factors contribute to this issue, including the increasing complexity of the underlying PINN optimisation problem as the problem size grows and the spectral bias of neural networks. In this work, we propose a new, scalable approach for solving large problems relating to differential equations called finite basis physics-informed neural networks (FBPINNs). FBPINNs are inspired by classical finite element methods, where the solution of the differential equation is expressed as the sum of a finite set of basis functions with compact support. In FBPINNs, neural networks are used to learn these basis functions, which are defined over small, overlapping subdomains. FBINNs are designed to address the spectral bias of neural networks by using separate input normalisation over each subdomain and reduce the complexity of the underlying optimisation problem by using many smaller neural networks in a parallel divide-and-conquer approach. Our numerical experiments show that FBPINNs are effective in solving both small and larger, multi-scale problems, outperforming standard PINNs in both accuracy and computational resources required, potentially paving the way to the application of PINNs on large, real-world problems. [ABSTRACT FROM AUTHOR]

The discrete element method (DEM) is the most dominant method for the numerical prediction of dynamic behaviour at grain or particle scale. Nevertheless, due to its discontinuous nature, the DEM is inherently unable to describe microscopic features of individual bodies which can be considered as continuous bodies. To incorporate microscopic features, efficient numerical coupling of the DEM with a continuous method is generally necessary. Thus, a generalised multi-scale PD–DEM framework is developed in this work. In the developed framework, meshfree discretised Peridynamics (PD) is used to describe intra-particle forces within bodies to capture microscopic features. The inter-particle forces of rigid bodies are defined by the DEM whereas a hybrid approach is applied at the PD–DEM interface. In addition, a staggered multi-scale time integration scheme is formulated to allow for an efficient numerical treatment of both methods. Validation examples are presented and the applicability of the developed framework to capture the characteristics mixtures with rigid and deformable bodies is shown. [ABSTRACT FROM AUTHOR]

To relate the thermomechanical behaviour and microstructural evolution of the heat-assisted incremental sheet forming (SPIF) for Ti–6Al–4 V sheet, multi-scale models based on crystal plasticity finite element model (CPFEM), representative elementary volume (RVE), and cellular automaton (CA) were established in this article. An experimental-scale CPFEM was built in advance to provide macrograin level strain, strain rate, and temperature output data, which were then used in RVE and CA as inputs to simulate the microstructural evolution throughout the SPIF process. The output results include the pole figures, dynamic recrystallisation (DRX) maps, and statistics results of the alpha (α) phase of the Ti–6Al–4 V (α-Ti) alloy from stage to stage throughout the 700 ∘ C SPIF. The obtained statistics results of dislocation density, grain orientation angles, and grain size were verified with electron backscatter diffraction (EBSD). The CA analysis of the DRX progress at the upper, centre, and lower regions of the deformed workpiece has discovered that the incremental increase of the strain rate has significant effects on the dislocation density that produced a proportional relationship to the DRX percentage. The results revealed that the strain rate has strong domination in affecting the slip of grains orientation, which overcomes the effect of temperature increase in this SPIF process. Furthermore, it was found that a large amount of DRXed grains were generated at the grain boundaries, which reduced the mean grain size and increased the DRX percentage, which produced an inversely proportional relationship to the dislocation density. The thermomechanical behaviour on the SPIF workpiece was increased incrementally, which is insufficient for DRX initiation in the upper region, and the behaviour was enhanced at the centre and lower region, which can be corresponded to the microstructural evolution throughout the process. [ABSTRACT FROM AUTHOR]

In this review paper, a critical assessment of the main degradation processes in three key components of solid oxide fuel cells and electrolysers (negative and positive electrodes and the interconnect) is undertaken, attempting prioritization of respective degradation effects and recommendation of the best approaches in their experimental ascertainment and numerical modeling. Besides different approaches to quantifying the degradation rate of an operating solid oxide cell (SOC), the latest advancements in microstructural representation (3D imaging and reconstruction) of SOC electrodes are reviewed, applied to the quantification of triple‐phase boundary (TPB) lengths and morphology evolution over time. The intrinsic degradation processes in the negative (fuel) electrode and the positive (oxygen) electrode are discussed, covering first the composition and governing mechanisms of the respective electrodes, followed by a comprehensive evaluation of the most important factors of degradation during operation. By this systematic identification of dominant degradation processes, measurement techniques, and modeling approaches, the foundations are laid for the definition of meaningful accelerated stress testing of SOC cells and stacks, which will help the technology achieve the constantly more demanding durability targets in market applications. [ABSTRACT FROM AUTHOR]

Increasing efforts points to the understanding of how to maximize the capabilities of the adaptive immune system to fight against the development of immune and inflammatory disorders. Here we focus on the role of T cells as immune cells which subtype imbalance may lead to disease onset. Specifically, we propose that autoimmune disorders may develop as a consequence of a metabolic imbalance that modulates switching between T cell phenotypes. We highlight a Systems Biology strategy that integrates computational metabolic modelling with experimental data to investigate the metabolic requirements of T cell phenotypes, and to predict metabolic genes that may be targeted in autoimmune inflammatory diseases. Thus, we propose a new perspective of targeting T cell metabolism to modulate the immune response and prevent T cell phenotype imbalance, which may help to repurpose already existing drugs targeting metabolism for therapeutic treatment. [ABSTRACT FROM AUTHOR]

In this work, we investigated the effect of carbon nanotubes addition and agglomeration formation on the mechanical and electrical properties of CNT–polymer-based nanocomposites. Six specimens with carbon nanotubes (CNTs) fractions of 0%, 0.5%, 1%, 2%, 4% and 5% were manufactured and characterized by dynamic mechanical analysis (DMA) and four-probe method. The stress–strain curves and electrical conductivity properties were obtained. Scanning electron microscopy (SEM) was used to characterize both agglomeration and porosity formation. By employing micromechanics, through representative volume element (RVE), finite element analysis (FEA) and resistor network model (RNM), the Young's modulus and electrical conductivity values were calculated. The samples' elastic moduli showed an increment, reaching the maximum value at a CNTs fraction of 2%, thereafter an adverse effect was caused in the high CNT percentage samples. The final electrical conductivity seemed greatly altered with the addition of CNTs, reaching the percolation threshold at 2%. The unavoidable formation of CNT agglomerates appeared to influence the final physical properties. The CNT agglomerates adversely affect the mechanical performance of high-CNT-percentage samples. Conversely, an exponential increment in the electrical conductivity was presented as the agglomerates formed networks allowing the transport of electrons through the tunnelling effect. These phenomena were experimentally and numerically confirmed, showing a good correlation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Lewis number deviates from one in the entrance length. • The catalyst activity do not modify the initial Nu and Sh inside of the channels. • Re modifies the thermal entrance length because of the reduction of the flow area. This paper is devoted to the multi-scale model of the heat and mass transfer inside of a honeycomb monolith substrate. Due to computational limitations, monoliths are modelled as a continuum in full-scale catalytic reactors models. That makes it necessary to use correlations or sub-models derived from channel scale results to account for a physically consistent heat and mass transfer inside of the substrate. In this paper detailed computational models at a channel and reactor scales are analyzed. Catalytic oxidation of CO is used as a reaction and the fluid properties are considered to be temperature-dependent. First, a channel scale model is used to analyze Nusselt, Sherwood, Lewis, and Damköhler numbers inside of the monolith channels. Secondly, sub-models obtained at a channel level are implemented in a full-scale reactor model using the continuum approach, to evaluate the impact of using detailed vs. highly simplified correlations for heat and mass transfer. The reactor scale model accounts for the transitions of the flow regime, entrance length effects, an-isotropic substrate thermal conductivity and temperature-dependent fluid properties. According to the results, the Lewis number can deviate significantly from one in the entrance length, however, it approaches asymptotically to unity as the flow develops. Regarding Nusselt and Sherwood, current interpolating methodologies are not able to predict the correct value in the entrance region when Damköhler is low, nonetheless, are reasonably accurate for the asymptotic one. [ABSTRACT FROM AUTHOR]

In this paper, a multi-scale modelling approach has been developed to predict the progressive damage and failure behaviour of 2D woven SiC/SiC composites. At the tow scale, non-linear tow properties have been determined by a micromechanics-based damage model, in which two scalar damage variables were introduced to characterize the fibre-dominated and matrix-dominated damage, respectively. Based on periodic boundary conditions, a meso-scale unit cell model has been established to simulate the macroscopic stress-strain responses and progressive damage processes of the composite under uniaxial tensile, compressive and in-plane shear loadings, respectively. In the numerical method, the non-linear properties of constituent materials have been implemented by the user defined subroutine, USDFLD of the finite element package, Abaqus. The numerical results and their comparisons with experimental stress-strain curves have been presented. The failure mechanisms of the composite under each loading have been also discussed. The high efficiency and prediction accuracy of the model make it possible to analyse large scale woven composites. [ABSTRACT FROM AUTHOR]

This study proposed a crystallographic texture-based multi-scale modelling framework to predict mechanical anisotropy of textured aluminium alloy sheet. The multi-scale scheme was constructed by the combination of a full-field crystal plasticity model in mesoscopic scale and a newly developed phenomenological yield function in continuum scale. In this approach, the mechanical anisotropy of materials is directly obtained from crystal plasticity (CP) modelling without extensive directional tensile tests. The results show that the multi-scale scheme predicted earing profiles coincide well with experimental measurements. This multi-scale modelling could be utilised to design an optimised blank shape with minimum earing for the deep-drawn component, and a convoluted cut-edge was devised accordingly. [ABSTRACT FROM AUTHOR]

Ship-induced waves are an increasingly relevant hydrodynamic forcing factor in waterways travelled by large seagoing ships. The discrepancy between the small-scale wave-structure interaction near embankments and the larger-scale wave generation and propagation poses challenges for the prediction of ship-induced waves as a multi-scale problem. Therefore, a novel hydrodynamic coupling interface is presented that allows information transfer from the shallow-water-equation (SWE) solver REEF3D::SFLOW to the 3D-RANS-solver REEF3D::CFD. The implementation consists of a one-way coupling, where the solution from the SWE solver is imposed to one or multiple relaxation zones of the CFD solver. A series of verification cases shows that the implementation of the interface is accurate and only small deviations are introduced due to the 2D-3D dimensional mismatch of the numerical models involved. An application is presented, showing how the coupled SWE-CFD model can be employed to study ship-induced groin overtopping. • Presentation of a coupling interface between a SWE solver and a RANSE-solver. • The error induced by a vertical velocity assumption in the interface is found to be small. • The versatility of the approach is showcased by simulating ship-induced groin overtopping. [ABSTRACT FROM AUTHOR]

The present contribution focuses on the analysis of diverse deformation mechanisms that impact the behaviour of PC/ABS blends using computational homogenisation. This includes analysing internal particle cavitation, PC/ABS interface debonding, and PC matrix shear-yielding. The goal is to investigate the optimal composition for specific applications and create tailored materials. The work involves establishing a microstructure Representative Volume Element, defining the constitutive description of both material phases, and explicitly modelling PC/ABS interfaces and matrix damage to achieve accurate predictions. A Python programme is devised to efficiently integrate zero-thickness cohesive interface elements around ABS particles, incorporating the PPR potential-based cohesive model to characterise the interface. Additionally, the finite strain visco-elastic visco-plastic constitutive model of the PC matrix is extended to incorporate a damage variable, addressing the shear-yielding failure mechanism. The PC/ABS blend's thermomechanical response is homogenised using first-order hierarchical multi-scale analyses. The impact of considering the interface phase in the microstructure is assessed through various numerical analyses. The synergy between the constitutive models effectively captures the blend's behaviour. These findings lay the foundation for broader applicability beyond PC/ABS blends, paving the way for future studies in the field. • Development of a homogenisation framework to study the behaviour of PC/ABS blends. • Examining the individual influence and synergistic effects of the deformation mechanisms. • Determining the optimal size and mesh discretisation for Representative Volume Elements. • Analysing how interfacial and bulk material parameters impact the behaviour. • Evaluating which loading conditions are most affected by considering realistic interfaces. [ABSTRACT FROM AUTHOR]

In this work, a multi-scale model established from the concept of periodic homogenization is utilized to predict the cyclic and time-dependent response of thermoplastic-based woven composites. The macroscopic behaviour of the composite is determined from finite element simulations of the representative unit cell of the periodic microstructure, where the local non-linear constitutive laws of the components are directly integrated, namely, the matrix and the yarns. The thermoplastic matrix is described by a phenomenological multi-mechanisms constitutive model accounting for viscoelasticity, viscoplasticity and ductile damage. For the yarns, a hybrid micromechanical–phenomenological constitutive model accounting for anisotropic damage and anelasticity induced by the presence of a diffuse micro-crack network is utilized. The capabilities of the overall multi-scale model are validated by comparing the numerical predictions with experimental data. Further illustrative examples are also provided, where the composite undergoes time-dependent deformations under uni-axial and non-proportional multi-axial loading paths. The multi-scale model is also employed to analyze the influence of the local deformation processes on the macroscopic response of the composite. [ABSTRACT FROM AUTHOR]

Ternary Al–Mg–Si alloys have been modelled based on a multi-scale approach that spans across atomistic and mesoscale models and uses theoretically determined parameters. First, a cluster expansion model for total energy has been trained for atomistic configurations (FCC lattice) based on the data from density functional simulations of electronic structure. Free energy curves as a function of solute (Mg, Si) concentrations and disorder have been obtained by using this parameterisation together with meta-dynamics Monte Carlo sampling. In addition, free energy data, surface tensions as well as strain energy using the linear elasticity theory have been collected to be combined for a mesoscale phase-field model. The application of this approach shows that the formation of a layered MgSi phase, with (100) planes, is a particularly stable solute aggregation motif within the Al host matrix. Moreover, the phase-field model demonstrates that the preferred shape of the MgSi precipitates is needle-like (in FCC), and they can act as precursors for the important and well-known β ″-type precipitates which are formed by translating one Mg column by a 1/2 lattice vector. The results provide theoretical evidence that the solute aggregation into needle-like MgSi domains (precipitates) is an inherent property of Al-Mg-Si alloys, and that it takes place even without the presence of vacancies which is a precondition for the eventual formation β ″ precipitates. Image, graphical abstract [ABSTRACT FROM AUTHOR]

The article offers information on different types of raw materials. Topics include forgotten contributions to science and engineering also mark the origins of materials science; sophisticated (technical instruments to explore the world around us at the smallest and the largest length scales; and simplest version of the molecular Nano machineries.

This paper represents an overview of the elements of the user-friendly simulation system, developed for computational analysis and optimization of the quality and productivity of the electromagnetically direct-chill cast semi-products from aluminium alloys. The system also allows the computational estimation of the design changes of the casting equipment. To achieve this goal, the electromagnetic and the thermofluid process parameters are coupled to the evolution of Lorentz force, temperature, velocity, concentration, strain and stress fields as well as microstructure evolution. This forms a multi-physics and multi-scale problem of great complexity, which has not been demonstrated before. The macroscopic fluid mechanics, solid mechanics, and electromagnetic solution framework is based on local strong-form meshless formulation, involving the radial basis functions and monomials as trial functions, and local collocation or weighted least squares approximation. It is coupled to the micro-scale by incorporating the point automata solution concept. The entire macro-micro solution concept does not require meshing and space integration. The solution procedure can be easily and efficiently automatically adapted in node redistribution and/or refinement sense, which is of utmost importance when coping with fields exhibiting sharp gradients, which occur in the phase-change problems. The simulation system is coded from scratch in modern Fortran. The elements of the experimental validation of the system and the demonstration of its use for round billet casting in IMPOL Aluminium Industry are shown. [ABSTRACT FROM AUTHOR]

The single crystal elastic anisotropy is one of the most important properties affecting the macroscopic response of polycrystalline materials, both in the elastic regime and the early stages of plastic deformation. In this work, the impact of monocrystalline parameters on the mechanical behaviour of cubic polycrystals is studied in detail. The analysis is conducted with an RVE-based computational homogenisation framework which includes several original strategies and criteria developed to enable the efficient statistical analysis of virtual micro-structures. In particular, these developments include a stress-driven adaptation to the usually employed strain-driven homogenisation approach, used to study the plastic polycrystalline response in stress space. The effects of number of grains and realisations considered, finite element mesh discretisation level, and algorithms used to generate both the grain morphology and orientation distribution are also assessed. Considering a number of materials with cubic symmetry, expressions for the number of grains required for an elastically isotropic response are deduced, along with bounds for the homogenised elastic stiffness components of oligocrystals, in both cases as a function of the monocrystalline elastic anisotropy. In the plastic domain, multiple microscopic and macroscopic criteria to describe the yield onset of such polycrystals are evaluated and compared. This is done for both elastically isotropic and anisotropic polycrystals, where once again the effect of different levels of monocrystalline elastic anisotropy are evaluated. The numerically derived yield surface of isotropic polycrystals is fitted to both Tresca and von Mises yield functions, and for anisotropic oligocrystals, the statistical bounds for the expected distribution of micro-yield stresses are deduced, in terms of both the number of grains and of the level of single crystal elastic anisotropy. The results obtained are thus a step towards clarifying the effect of important micro-structural parameters in establishing the minimum representative volume element (RVE) size for metallic alloys in elasto-plastic applications. • The role of monocrystalline elastic anisotropy on the macroscopic response of cubic polycrystals is quantified. • RVE size expressions (minimum number of grains) are deduced for elastic cubic polycrystals in terms of elastic anisotropy. • Elastic stiffness bounds are derived for anisotropic oligocrystals, as a function of microstructural features. • For isotropic aggregates, Tresca and von Mises yield functions are calibrated from stress-driven homogenisation analyses. • Statistical bounds for the expected distribution of micro-yield stresses are deduced for cubic oligocrystals. [ABSTRACT FROM AUTHOR]

Aim: Deforestation is rapidly altering Southeast Asian landscapes, resulting in some of the highest rates of habitat loss worldwide. Among the many species facing declines in this region, clouded leopards rank notably for their ambassadorial potential and capacity to act as powerful levers for broader forest conservation programmes. Thus, identifying core habitat and conservation opportunities are critical for curbing further Neofelis declines and extending umbrella protection for diverse forest biota similarly threatened by widespread habitat loss. Furthermore, a recent comprehensive habitat assessment of Sunda clouded leopards (N. diardi) highlights the lack of such information for the mainland species (N. nebulosa) and facilitates a comparative assessment. Location: Southeast Asia. Methods: Species–habitat relationships are scale‐dependent, yet <5% of all recent habitat modelling papers apply robust approaches to optimize multivariate scale relationships. Using one of the largest camera trap datasets ever collected, we developed scale‐optimized species distribution models for two con‐generic carnivores, and quantitatively compared their habitat niches. Results: We identified core habitat, connectivity corridors, and ranked remaining habitat patches for conservation prioritization. Closed‐canopy forest was the strongest predictor, with ~25% lower Neofelis detections when forest cover declined from 100 to 65%. A strong, positive association with increasing precipitation suggests ongoing climate change as a growing threat along drier edges of the species' range. While deforestation and land use conversion were deleterious for both species, N. nebulosa was uniquely associated with shrublands and grasslands. We identified 800 km2 as a minimum patch size for supporting clouded leopard conservation. Main conclusions: We illustrate the utility of multi‐scale modelling for identifying key habitat requirements, optimal scales of use and critical targets for guiding conservation prioritization. Curbing deforestation and development within remaining core habitat and dispersal corridors, particularly in Myanmar, Laos and Malaysia, is critical for supporting evolutionary potential of clouded leopards and conservation of associated forest biodiversity. [ABSTRACT FROM AUTHOR]

• Long-distance avian migrants across different taxa are faced with global declines. • Nightjars use general habitat characteristics for high-order habitat selection. • Fine scale selection is reliant on variables related to a habitat's suitability. • Landscape composition and -configuration both influence selection decisions. • Selecting diverse landscapes may allow individuals to minimize time during migration. Long-distance migrants are constrained by widely separated hospitable habitats in geographically isolated locations, making them vulnerable to environmental change, both through natural and anthropogenic causes. Knowledge about their resource selection decisions is imperative to understand the drivers of their declines. The distinct periods within an annual cycle, when individuals experience different environmental circumstances, are inextricably linked through carry-over effects which can have important consequences for the individual, and consequently the population. In this study, we employ precise archival GPS-tracking data of European Nightjars (Caprimulgus europaeus) and high-resolution global land cover data to examine habitat selection during the sedentary wintering and breeding periods, as well as during autumn and spring migration, using a correlational approach. We demonstrate how nightjars use general habitat characteristics, such as landscape diversity, for high-order habitat selection, while resource selection at a finer spatial scale is reliant on fine-scale variables related to a habitat's suitability, such as surface area of grassland and shrubland. We show that nightjars favour spatially diverse landscapes, which allows them to minimize time spent searching for optimal habitats. The considerable variation in the drivers of habitat selection between and within seasons shows how anthropogenic land-use change can have an array of different impacts on migrants by influencing large- and fine-scale habitat selection. This study shows the advantages of an individual based GPS-tracking approach, combined with high spatial resolution remote sensing data, and highlights the need for full annual-cycle research on scale dependent habitat selection of long-distance avian migrants. [ABSTRACT FROM AUTHOR]

We developed a multi-scale model for the prediction of precipitation kinetics of binary alloys and present its application to the formation of Guinier–Preston zones (GPZ) in Al-rich binary Al–Cu alloys. The approach is covering three length scales: (i) Starting from density functional theory (DFT) calculations a Cluster Expansion (CE) for the binary Al–Cu system on the fcc lattice is constructed. Based on the obtained CE (ii) a lattice Monte Carlo (MC) sampling technique, known as the overlapping distribution method, is used to calculate cluster free energies of precipitate clusters. Finally (iii) a meso-scale Cluster Dynamics (CD) model is constructed by taking the cluster free energies as input. The result is a fast, parameter free method that is able to predict the evolution of precipitate size distributions. To validate the model kinetic MC simulations on the precipitation of GPZ are conducted. The results agree well with those obtained by our model. When comparing our results to experimental data a problem of time scaling arises, which is discussed in the results section. Image 1 • A model for the prediction of GPZ precipitation in Al–Cu alloys is constructed. • The approach includes DFT, Cluster Expansion, Monte Carlo and Cluster Dynamics. • The model's results show a good comparability to results from kinetic Monte Carlo. [ABSTRACT FROM AUTHOR]

Highlights • Contextualized multi-scale design factors is assessed against building energy performance responses. • Statistical sensitivity analysis methodology is coupled to an urban energy model. • Two new urban form metrics proposed presents relevant influence over heating loads of buildings. • Patio aspect ratio and standard-deviation of height accounts for 50% of overall impact in closed urban block. • Building and envelope scale factors have major impact on cooling demand of buildings. Abstract This research aims to identify the statistical sensitivity of multi-scale urban design factors regarding buildings' energy demand located in three districts in the city of Toulouse, France. The research method is composed of four main steps: (a) three typical urban blocks of Toulouse are parametrized, considering factors ranging from the urban form to the building material scales; (b) a fractional factorial sampling method is applied which allows elaborating statistically representative and non-redundant scenarios from all design variables and for each specific urban district; (c) the urban energy models generated are interactively assessed regarding the annual buildings' heating and cooling loads for the temperate climate context of Toulouse, France; (d) through a global sensitivity analysis, results obtained are estimated through a statistic hypothesis test, which allows identifying the influence of the design variables on each energy response of interest. Results show that urban multi-scale design variables may have divergent influence on the same energy response when the urban form context changes. For traditional urban compact blocks, two less current urban form factors considered in this study (the courtyard aspect ratio and the standard-deviation of the built height) account for almost 50% of the overall impact on heating demand of buildings while building and envelope scale factors, such as glazing window properties, have more influence for pavilions and slabs urban blocks. The relevance of certain factors was strongly linked to their typologies or to their urban environment. [ABSTRACT FROM AUTHOR]

Abstract The hybrid Molecular Dynamics - Fluctuating Hydrodynamics model is extended for multi-resolution simulations of molecular diffusion in water under a steady shear flow. Cases of water self-diffusion and a small protein diffusion in water are considered. For the switched-off flow effect, the model is validated in comparison with the reference all-atom equilibrium molecular dynamics solution. With the flow effect included, the multiscale model correctly captures the mean flow velocity distribution as well as the difference between mean square deviations in different directions with respect to the flow in accordance with the diffusion theory. Results of the simulations are analysed in the context of using hydrodynamic flow gradients for molecular diffusion focusing. Highlights • A novel method is developed for multiscale simulations of liquids under Couette flow. • The model correctly captures structure and transport properties of a peptide in water. • The diffusion predictions for shear flow are in agreement with the previous results. • Application of a velocity strain to peptide diffusion in water has a focusing effect. • An analytical model is developed to explain the peptide diffusion simulation results. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Development of a novel multi-scale modelling approach for multi-phase steels. • Derivation of micro-scale plastic potential functions of FCC/BCC single crystals. • Validation via numerical-experimental comparison of tensile and diffraction tests. • Good correspondence of the homogenized stress-strain and the lattice strain curves. • Yield locus prediction of multi-phase materials through microstructural simulations. Abstract In this article, a novel material modelling approach to predict the anisotropic material response of multi-phase steels is developed. The macroscopic material behaviour of the model is characterized by the homogenized response of a meso-scale Representative Volume Element (RVE), derived by Finite Element (FE) simulations. The RVE holds the most relevant microstructural features of the material under consideration, such as phase distribution, grain orientation, morphology etc., in sufficient detail, in order to capture the anisotropy and phase interactions. The micro-scale material models of individual phases are described with specific plastic potential functions, the components of which are derived from Crystal Plasticity (CP) laws. The plastic potential functions are constructed using the Facet method for each phase in the microstructure at the level of single grains, and are used in conjuncture with phase specific, isotropic grain hardening laws. The proposed model is evaluated through numerical experiments performed on a synthetic microstructure of Duplex steel, constructed from statistical material parameters extracted from literature. The RVE flow curves depicted very good correspondence with the experimental data reported for the same grade of Duplex Stainless Steel. The anisotropy prediction was further assessed through comparison between virtual diffraction experiments performed on the statistical microstructure and the actual Neutron Diffraction (ND) experimental data of the reference material. It was found that the model captured the overall trend of the diffraction curves for the individual phases with good accuracy, but obtaining an exact correspondence to the experimental values was not feasible with the performed simulations on statistical microstructures. Finally, an approach to predict the anisotropic yield locus of a multi-phase material is also presented. [ABSTRACT FROM AUTHOR]

A multi-scale model for the analysis of granular systems is proposed, which combines the principles of a coupled FEM-DEM approach with a novel servo-control methodology for the implementation of appropriate micro-scale boundary conditions. A mesh convergence study is performed, whereby the results of a quasi-static biaxial compression test are compared with those obtained by direct numerical simulations. The comparison demonstrates the capability of the multi-scale method to realistically capture the macro-scale response, even for macroscopic domains characterized by a relatively coarse mesh; this makes it possible to accurately analyse large-scale granular systems in a computationally efficient manner. The multi-scale framework is applied to study in a systematic manner the role of individual micro-structural characteristics on the effective macro-scale response. The effect of particle contact friction, particle rotation, and initial fabric anisotropy on the overall response is considered, as measured in terms of the evolution of the effective stress, the volumetric deformation, the average coordination number and the induced anisotropy. The trends observed are in accordance with notions from physics, and observations from experiments and other DEM simulations presented in the literature. Hence, it is concluded that the present framework provides an adequate tool for exploring the effect of micro-structural characteristics on the macroscopic response of large-scale granular structures. [ABSTRACT FROM AUTHOR]

This paper reviews the current status of boiling heat transfer modelling, discusses the need for its improvement due to unresolved intriguing experimental findings and emergence of novel technical applications and outlines the directions for an advanced modelling approach. The state-of-the-art of computational boiling heat transfer studies is given for: macro-scale boiling models applied in two-fluid liquid-vapour interpenetrating media approach, micro-, meso-scale boiling computations by interface capturing methods, and nano-scale boiling simulations by molecular dynamics tools. Advantages, limitations and shortcomings of each approach, which originate from its grounding formulations, are discussed and illustrated on results obtained by the boiling model developed in our research group. Based on these issues, we stress the importance of adaptation of a multi-scale approach for development of an advanced boiling predictive methodology. A general road-map is outlined for achieving this challenging goal, which should include: improvement of existing methods for computation of boiling on different scales and development of conceptually new algorithms for linking of individual scale methods. As dramatically different time steps of integration for different boiling scales hinder the application of full multi-scale methodology on boiling problems of practical significance, we emphasise the importance of development of another algorithm for the determination of sub-domains within a macro-scale boiling region, which are relevant for conductance of small-scale simulations. [ABSTRACT FROM AUTHOR]

Abstract Composites reinforced with braided textiles exhibit high structural stability and excellent damage tolerance, making them very attractive for defence, aerospace, automotive and energy industries. Considering the real-life service environment, it is crucial to study a dynamic response of a composite structure and its energy-dissipation ability, especially under repeated low-velocity impacts. So, a series of drop-weight tests were carried out followed by X-ray computed micro-tomography to characterize damage morphology of braided composite specimens. Meanwhile, a multi-scale computational approach was explored and implemented as a user-defined-material subroutine (VUMAT) for ABAQUS/Explicit to capture main damage modes of a braided textile composite, while its delamination was modelled by employing cohesive-zone elements. Load- and energy-time curves were obtained both experimentally and numerically. The predicted levels of peak forces and absorbed energy were found to agree with the experimental data. An extent of delamination and damage accumulation in the braided composite was predicted numerically and analysed; it was found that material responses to repeated impacts had two types depending on the level of normalised impact energy. The presented modelling capability could contribute to design of braided composite structures for various applications. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a test method of twin-fibre single-lap joint bonded with a micro-droplet of epoxy and subjected to tensile loading for determining fibre-matrix interfacial shear strength (IFSS). Twenty-five carbon fibre (CF)/epoxy specimens and fifty-six carbon nanotube (CNT)-grafted CF/epoxy specimens were prepared and tested. The average IFSS measured for specimens with a mean grafting density of 10.9, 25.8, 35.1 or 58.8 CNTs per μm2 can be improved by 51%, 101%, 155% and 273% (223%) respectively comparing to that without grafted CNTs. A multi-scale analytical model that relates micro-scale IFSS to nanoscale CNT grafting strength and density is developed and then used for predicting the IFSS of CNT-CF reinforced composites. There exists a good correlation between the measured and predicted IFSS of specimens with different grafting densities. [ABSTRACT FROM AUTHOR]

In this work we develop a multi-scale model to characterise the large scale constitutive behaviour of a material featuring a small scale fibrous architecture. The Method of Multi-scale Virtual Power (MMVP) is employed to construct the model. At the macro-scale, a classical continuum mechanics problem is formulated in the finite strain regime. At the micro-scale, a network of fibres, modelled as one-dimensional continua, composes the representative volume element (RVE). The MMVP provides a full characterisation of the equilibrium problem at the RVE, with consistent boundary conditions, as well as the homogenisation formula which defines the first Piola–Kirchhoff stress tensor. Particular attention is given to the fact that the macro-scale continuum could be considered incompressible. Numerical experiments are presented and model consistency is verified against well-known phenomenological constitutive equations. Scenarios departing from the hypotheses of such phenomenological material models are discussed. [ABSTRACT FROM AUTHOR]

Coupled multi-scale finite element analyses have gained traction over the last years due to the increasing available computational resources. Nevertheless, in the pursuit of accurate results within a reasonable time frame, replacing these high-fidelity micromechanical simulations with reduced-order data-driven models has been explored recently by the modelling community. In this work, two classes of machine learning models are trained for a porous hyperelastic microstructure to predict (i) whether the microscopic equilibrium problem is likely to fail and (ii) the stress–strain response. The former may be used to identify critical macroscopic points where one may fall back to the high-fidelity analysis and possibly apply convergence bowl-widening techniques. For the latter, both a linear regression with polynomial features and artificial Neural Networks have been used, and the required stress–strain derivatives for solving the equilibrium problem have been derived analytically. A weight regularisation is introduced to stabilise the tangent operator and several strategies are discussed for imposing null stresses in undeformed configurations for both regression models. The regression techniques, here analysed exclusively in the context of porous hyperelastic materials, evidence very promising prospects to accelerate multi-scale analyses of solids under large deformation. • Methodology to speed up the high computational time of coupled multi-scale analyses. • Benchmark of classification techniques to identify critical analysis points. • Comparison of regression models to predict the stress–strain response and derivates. • New insights on strategies to enforce zero stress in absence of deformation. • Integration of classification and regression models towards a robust framework. [ABSTRACT FROM AUTHOR]

Advanced fibre composite materials are often used for weight-efficient thin-walled designs, making a plate-based modelling approach suitable for their structural assessment. However, as the sub-structural geometrical features of these materials govern much of their behaviour, a multi-scale approach is necessary. A related challenge, however, is that the in-plane variation of these sub-structural features may be much larger than the total thickness of the material, whereby tailored homogenisation techniques for shell elements are needed. Existing frameworks for plate- and shell-based homogenisation are typically developed using second-order homogenisation in combination with the Hill–Mandel (macro-homogeneity) condition. However, it has been reported in the literature that this approach can lead to kinematic inconsistencies in the macro- to micro-scale transition. One inconsistency that is commonly reported, is the inability to correctly account for the macro-scale transverse shear behaviour on the sub-scale level. In this contribution, we show how the method of Variationally Consistent Homogenisation (VCH) can be used to develop a homogenisation framework for Reissner-Mindlin plate elements, which guarantees kinematically consistent prolongation and homogenisation operations. The homogenisation approach is demonstrated in four numerical examples, where it is shown that the method accurately homogenise the effective sectional plate stiffnesses of homogeneous and heterogeneous sub-structures. [ABSTRACT FROM AUTHOR]

[Display omitted] • The use of Machine Learning (ML) tools for supporting nanoindentation is reviewed. • Applications of ML for understanding load-depth data are investigated. • The use of ML for analysis large datasets from high-speed nanoindentation is also reviewed. • The potential impact of Artificial intelligence for nanomechanics is finally discussed. The solution of instrumented indentation inverse problems by physically-based models still represents a complex challenge yet to be solved in metallurgy and materials science. In recent years, Machine Learning (ML) tools have emerged as a feasible and more efficient alternative to extract complex microstructure-property correlations from instrumented indentation data in advanced materials. On this basis, the main objective of this review article is to summarize the extent to which different ML tools have been recently employed in the analysis of both numerical and experimental data obtained by instrumented indentation testing, either using spherical or sharp indenters, particularly by nanoindentation. Also, the impact of using ML could have in better understanding the microstructure-mechanical properties-performance relationships of a wide range of materials tested at this length scale has been addressed. The analysis of the recent literature indicates that a combination of advanced nanomechanical/microstructural characterization with finite element simulation and different ML algorithms constitutes a powerful tool to bring ground-breaking innovation in materials science. These research means can be employed not only for extracting mechanical properties of both homogeneous and heterogeneous materials at multiple length scales, but also could assist in understanding how these properties change with the compositional and microstructural in-service modifications. Furthermore, they can be used for design and synthesis of novel multi-phase materials. [ABSTRACT FROM AUTHOR]

Self-healing prostheses that can replace damaged native organs, like tissue-engineered valvular implants, are under development. Engineered soft tissues can greatly benefit from reinforcements to attain mechanical properties comparable with the native organs. Complex interactions at various levels between the reinforcements and engineered tissue make the selection of the most optimized reinforcing scaffold difficult and subject to an enormous amount of experimental evaluation. Hence, to reduce the extent of prototyping, it is prudent to develop a simulation based development approach. In the example of valvular prostheses which are textile-tissue composites, we test a simulation approach based on multi-scale modelling, often used for evaluating/predicting the behaviour of composites. A textile scaffold embedded in silicone is used as a replacement for the textile-tissue composite. The modelling technique provides a good correlation with the experimental results, laying the pathway to further study the complex interaction between the engineered tissue and the reinforcing scaffold. This method can further form the basis for evaluating the mechanical compatibility of scaffolds and their interaction with engineered tissues at various scales and levels. [ABSTRACT FROM AUTHOR]

The advent of new more complex classes of strongly heterogeneous materials, such as 3D woven composites, introduces new challenges for well-established finite element multiscale modelling approaches. These materials' internal architecture dominates the local stress concentrations, damage initiation and damage progression. Additionally, the material loses periodicity during manufacture and conventional homogenization approaches become inapplicable. In this paper, a multiscale modelling approach based on domain decomposition and homogenization is proposed to model the mechanical behaviour of these materials. The proposed model formulates a set of displacement and force compatibility conditions between the various subdomains. The compatibility conditions are formulated by limiting the set of kinematically admissible solutions on the smaller scales in order to satisfy the larger scale basis functions at the interfaces. The different subdomains are solved alongside the compatibility conditions in an iterative process. The proposed multiscale framework reduces the stress artefacts on the subdomains' boundaries. This feature allows the 3D woven material internal architecture represented at the smaller scales to control the structural response at the global scale. Additionally, this framework allows for selective application of nonlinear material models to the subdomains of interest through its ability to redistribute stresses across the subdomains boundaries. [ABSTRACT FROM AUTHOR]

In the paper numerical simulation of the foamed metal structures using numerical homogenization algorithm is prescribed. The first, numerical model of heterogeneous porous simplified structures of typical foamed metal, based on the FEM was built and material parameters (coefficients of elasticity matrix of the considered structure) were determined with use of numerical homogenization algorithm. In the work the different RVE models of structure were created and their properties were compared at different relative density, different numbers and the size and structure of the arrangement of voids. Finally, obtained results were used in modeling of typical elements made from foam metals structures - sandwich structures and hollow profiles filling with metal foam. Three point bending test was performed for sandwich structures. Simulation were done for different dimensions of cladding and core. Additionally, the torsion test was performed for profiles filling with metal foam. Typical behavior for torsion was observed. [ABSTRACT FROM AUTHOR]

The benefits of decentralised energy systems can be realised through the optimal siting of distributed energy systems and the design of highly interlinked district heating networks within existing electrical and gas networks. The problem is often formulated as a Mixed Integer Linear Programming (MILP) problem. MILP formulations are efficient and reliable, however the computational burden increases drastically with the number of integer variables, making detailed optimisation infeasible at large urban scales. To tackle complex problems at large scale the development of an efficient and robust simplification method is required. This paper presents an aggregation schema to facilitate the optimisation of urban energy systems at city scale. Currently, spatial and/or temporal aggregation are commonly employed when modelling energy systems at spatio-temporal resolutions from plant scheduling up to national scenarios. This paper argues for solving different scales separately using a bottom-up approach, while keeping track of the error made by reducing the resolution when moving from building to urban scale. Novel modelling formulations and optimisation techniques are presented. They enable drastic reduction of the computational time (by up to a factor of 100) required to find an optimal solution in reasonable time without sacrificing the quality of the results (no more than 1% loss in accuracy). A density-based clustering algorithm enables intelligent division of a large city-scale problem into sub-optimisation problems by creating clusters of different density. In each cluster, the trade-off between centralised and decentralised energy systems and the associated district heating network design is evaluated. A solution is selected based on a local optimisation of the network costs. Demand profiles of each building are assigned appropriately, then at an upper level the energy optimisation problem is solved considering the network losses at lower levels. This method enables large-scale modelling of urban energy systems while taking into account building-scale levels of detail. The clustering method enables assessment of the potential of district heating networks on city scale based on building characteristics and available urban energy systems. [ABSTRACT FROM AUTHOR]

Accurate modelling of local evolving texture and yield surface evolution in complex strain path are of crucial importance to the accurate sheet metal forming simulations. This work proposed a novel multi-scale computational scheme, in which the full-field crystal plasticity (CP) modelling is mapped and real-time updated into each integration point following the local strain path in the finite element (FE) model. By the real-time close-loop feedback and update between the FE model and CP model, the evolving texture and its induced anisotropic plasticity evolution are considered utilizing on-the-fly virtual tests in the full deformation field. To carefully verify the developed computational framework, a comprehensive validation including plastic anisotropy characterization, cyclic hardening tests and deep drawing tests is conducted in an AA6016-T4 aluminium sheet with strong cube texture using ESAFORM Benchmark 2021. By comparison with experimental results and the conventional approaches with constant yield surface for the forming case, the newly developed method is thoroughly validated, showing that the significant texture evolution is observed in large plastic deformation and various strain paths lead to different texture evolution. The local evolving texture induced plastic anisotropy evolution has a considerable effect on the prediction accuracy of the deep drawing simulations, such as earing profile, wall thickness and loading history. Additionally, this method does not increase too much computation cost, enabling cost-effectively simulation of complex forming processes. [Display omitted] • A multi-scale modelling framework for evolving texture and anisotropy is established. • The developed methods enable the analysis of complex plasticity behaviours. • The multi-scale model shows superior accuracy than conventional approaches. • The local texture evolution during forming is successfully predicted. [ABSTRACT FROM AUTHOR]

Porosity is a major manufacturing defect which affects the matrix dominate properties of continuous fibre composites, in particular the transverse strength. The simulation of porosity allows for predictions on the reduction of strength to be made, however, there is a trade-off between accuracy and computational efficiency. The multi-scale modelling approach presented here allows for accurate 3-dimensional geometry data of voids to be used. This is accomplished by first evaluating the effect the porosity has on degrading the matrix then subsequently, by using a representative unit cell, ply level strength can be predicted. The model is validated against empirical tensile and compressive testing of unidirectional autoclave cured prepreg with strong correlation. The approach allows for a reduction in overengineered structures by predicting accurate material properties for a given porosity generation. [ABSTRACT FROM AUTHOR]

Model coupling is an important approach to studying the dynamics of complex systems, but by introducing new feedback loops, the dynamics of coupled models can be artificially distorted. This paper describes a new method of model coupling which addresses this problem through a dynamic form of regularization. The method allows the time series evolution of model variables to be mutually informed by multiple models, and models to influence each other in proportion to their degree of certainty. Uncoupled forms of the coupled models can act as dynamic priors on the trajectory of coupled variables, strengthening model stability and offering additional calibration of the coupling process. Finally, models that describe different spatial scales can be coupled into multi-scale models, so that, for example, spatially-distributed models can be coupled with aggregate models, and influence one another. We apply this technique to a coupled socio-ecological system of population growth and ecosystem harvesting. [ABSTRACT FROM AUTHOR]

Aluminium metal production through electrolytic reduction of alumina in a cryolite bath is a complex, multi-physics, multi-scale process, including magneto-hydrodynamics (MHD), bubble flow, thermal convection, melting and solidification phenomena based on a set of chemical reactions. Through interactions of the different forces applied to the liquid bath combined with the different time and length scales, self-organised fluctuations occur. Moreover, the MHD behaviour causes a complex metal pad profile and a series of surface waves due to the meta-stable condition of the metal/cryolite interface. The large aspect ratio of an industrial cell, with a footprint of 20 by 4 m and at the same time having dimensions approaching just 30 mm of height for the reaction zone, prevents an integrated approach where all relevant physics are included in a single mathematical model of this large degree of freedom system. In order to overcome these challenges, different modelling approaches have been established in ANSYS ® FLUENT ® ; Three models are used to predict details of specific physics: one to predict the electro-magnetic forces and hence the metal pad profile, a second that resolves details of the local bubble dynamics around a single anode and a third for the full cell bath flow. Results from these models are coupled to allow integration of the different phenomena into a full cell alumina distribution model. The current paper outlines each of the approaches and presents how the coupling between them can be realized in a complete framework, aiming to provide new insight into the process. [ABSTRACT FROM AUTHOR]

Traditional carbon-steel armour wires pose limitations ( e.g. long spans, weight reduction, corrosion and fatigue) for flexible risers to operate in demanding and deeper water environments. In this context, an alternative to carbon-steel tensile armour wires is proposed recently by the authors (Gautam et al ., 2016), comprising of hexagonally packed polymer composite rods with uni-directional fibres and an over-braided ( i.e. bi-axial braid with high performance fibres) sleeve. These hybrid composite wires offer opportunities to tailor their mechanical properties by varying the geometrical ( e.g. rod diameter, packing) and processing parameters ( e.g. material selection, braid pattern) involved. In order to understand the mechanical behaviour of these hybrid composite armour wires, this paper presents a multi-scale model developed by using a combined analytical-computational approach. The multi-scale model is developed to predict the torsional and flexural behaviour of the hybrid composite wires; and the role of over-braid structural parameters, pre-tension and internal friction are investigated. The behaviour of the multiscale model is found to be in good agreement with the experimentally observed behaviour. After validating the multi-scale model with the experimental data available for specific configurations, parametric studies are conducted on the torsional and flexural behaviour of the hybrid composite wires to study the role of internal friction between un-bonded components and the braid tow tension in the over-braided sleeves. [ABSTRACT FROM AUTHOR]

To accurately predict buffeting-induced stresses in a long-span cable-stayed bridge with a twin-box deck, buffeting analyses should take into account the cross-sectional distribution of both aerodynamic and aeroelastic forces over the surface of the bridge deck. They should also be performed on an accurate multi-scale model rather than a spine-beam model of the bridge. This paper proposes a framework for stress-level buffeting analysis of a long-span cable-stayed bridge with a twin-box deck under distributed wind loads. Methods to obtain distributed aerodynamic and aeroelastic forces on the bridge deck are introduced. The proposed framework synthesizes the buffeting analysis with distributed wind loads and the multi-scale modelling and model updating of long-span bridges. The proposed framework is applied to the Stonecutters cable-stayed bridge in Hong Kong. The responses computed using the proposed buffeting analysis framework are compared with those computed using the sectional-force-based traditional method on a spine-beam model. The comparative results show significant differences in stress distribution on the twin-box deck and the multi-scale model yields larger maximum stress responses compared with the spine beam model. [ABSTRACT FROM AUTHOR]

In this paper we investigate micro–macro mechanical relations in Palmetto wood, a natural composite, by means of a computational homogenisation-based multi-scale modeling approach. The homogenisation procedure is solved sequentially at multiple length scales by following a bottom-up approach. The proposed strategy consists of homogenising the three length-scales by means of representative volume elements of material. The resulting effective macroscopic properties allow us to compute the mechanical response of individual macro-fibres and bulk wood specimens by means of a standard finite element procedure. The numerical predictions are compared successfully with experimental measurements. Following the validation, a parametric study is performed to investigate the micro–macro relations in Palmetto wood. The influence of several micro-structural features present at different length scales are investigated, such as the cellulose content and its crystallinity, the microfibril angle, the cell-wall thickness of micro-fibres, and the porosity of macro-fibres and their surrounding matrix, among others. The effects of such microscopic parameters are investigated on the Young’s modulus and density of Palmetto bulk wood. These results show that the present strategy can pave the way for further studies on complex microstructure–property relationships existing in different wood species, and on the possible development of more advanced bio-inspired composite materials. [ABSTRACT FROM AUTHOR]

The quality of high-performance composite structures is difficult to predict. Variability in the macroscopic performance is dominated by the spatial randomness in the geometrical characteristics of the reinforcement, especially for textile composites. This work provides a roadmap for generating realistic virtual textile specimens spanning multiple unit cells, which are required to perform high-fidelity simulations. First, the geometrical variability in the reinforcement structure is experimentally quantified on the meso- and macro-scale in terms of average trends, standard deviations and correlation lengths. Next, each reinforcement parameter is modelled by the sum of its average trend and its zero-mean deviations, which are both determined by analysing experiments. Virtual specimens are then created using advanced simulation techniques that match the experimental statistics. Depending on the nature of measured correlations, the simulation technique is either a Monte Carlo Markov Chain method, a cross-correlated Karhunen–Loève Series Expansion technique or a Fourier Transform method used in combination with a Markov Chain algorithm. In a last step, a virtual representation of the textile geometry is constructed in geometrical modelling software, such as the commercially available WiseTex software. The multi-scale framework is validated using data for a carbon–epoxy 2/2 twill woven composite produced by resin transfer moulding: the simulated tow deviations trends replicate the target statistics. [ABSTRACT FROM AUTHOR]

[Display omitted] Mesoscale elasto-plastic models, with statistically distributed structural properties and elastic coupling between discrete blocks, have been shown to quantitatively reproduce the main phenomenology observed in the stationary flow state of glasses as modelled at the atomic scale [1]. In the present study, an extension of such approaches is proposed to describe the transient mechanical response of glasses from different off-equilibrium states in the athermal quasi-static limit. Equilibrated liquids are simulated using two-dimensional molecular dynamics, quenched instantaneously to zero temperature, and then sheared. The mechanical observables measured in atomistic and elasto-plastic models are compared at the same length scales to calibrate a state-dependent constitutive law. A physical mechanism is proposed where the structural properties' evolution rate depends on the magnitude of local plastic deformation events, introducing an effective local memory of previous states in the system. This mechanism naturally leads to a brittle-ductile transition in the mechanical response of glasses, which depends exclusively on the quenched structure. Specifically, initially stable glasses exhibit strain-softening and localization, where the memory of the initial states is lost abruptly after the first plastic rearrangements. On the other hand, systems quenched from high-temperature liquids show a slow strain-hardening with statistically homogeneous plastic deformation. In these initially soft glasses, numerous plastic rearrangements are required to converge toward the stationary flow state. The elasto-plastic model successfully reproduces the stress-strain curves in the transient regime for the whole range of parent temperatures by including this local memory mechanism. The limitations of the model are finally discussed, together with possible improvements. [ABSTRACT FROM AUTHOR]

• An efficient homogenisation scheme is proposed and validated. • Orthotropic properties of masonry are calculated from its isotropic constituents. • Stresses and strains in joints and units are calculated from macroscopic strain. • Damage due to mechanical action on the joints and units can be simply quantified. [ABSTRACT FROM AUTHOR]

This paper presents a detailed numerical analysis of two types of 3D woven composite architecture. a unit cell, full finite element meso model, and a mosaic macro model are developed to simulate the elastic and damage progression behaviour of the two weave types. Both models predicted the tensile modulus and strength within 20% of the experimentally measured values, and the predicted failure sequence was similar to the experimental observation. [ABSTRACT FROM AUTHOR]

Laminated composite structures operating in a marine environment are subject to moisture ingress. Due to the slow diffusion process of moisture, the distribution of moisture is not uniform so that the laminates can develop hygrothermal stresses. An accurate prediction of the moisture concentration and the associated hygrothermal stress is vital to the understanding of the effect of marine environment on failure initiation. The present paper investigates the time-dependent moisture diffusion and the stress distribution in carbon fibre reinforced polymeric (CFRP) composites by means of experimental study and Finite Element Analysis (FEA). Samples were made from CFRP pre-preg autoclave-cured, and then immersed in fresh water and sea water at a constant 50 °C for accelerated moisture diffusion. Laminates with [0] 16 , [90] 16 , [±45] 4s lay-up sequences were investigated. A multiscale 3D FEA model was developed to evaluate the interfacial stresses between polymer matrix and carbon fibre and the stress distribution in the composite laminates. The analysis revealed that both the stress distribution and stress level are time-dependent due to moisture diffusion, and the interphase between fibres and matrix plays an important role in both the process of moisture diffusion and the stress/strain transfer. The interlaminar shear stresses of the laminates induced by hygrothermal expansion exhibited a significant specimen edge effect. This is correlated with the experimental observations of the flexural failure of laminates. [ABSTRACT FROM AUTHOR]