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The design of batch food processing plants is complex which requires the use of advanced simulation and optimisation methods. This paper presents how existing methods for multi-scale design and multi-objective optimisation can be combined together while carrying out the integrative design of these complex systems. To implement the Methodology for the Integrated, Multi-scale and Multi-Objective Design of Systems (MIMMODS), 8 tasks must be completed. The goal of the first 6 tasks is to build a design support tool that (i) simulates the behaviour of the processing plant and estimates its performance at different functional levels and whatever design variables it is made up of, (ii) takes into account the preferences of the decision-maker to convert the performances of a design solution into desirability indices and (iii) searches for the design solution(s) that best satisfies the design objectives and the preferences of the decision-maker. When the design support tool is functioning, the results have to be visualised and analysed in order to validate whether the resulting design solution is satisfactory, realistic, feasible and consistent or whether a new iteration of the methodology needs to be conducted to refine the design support tool. [ABSTRACT FROM AUTHOR]

As a solid waste from steel making, steel slag can be recycled to replace natural aggregates (NA) for developing steel slag aggregate (SSA) concrete, an environmentally friendly construction material. In order to evaluate the effect of steel slag on the permeability of SSA concrete, which may have a potential impact on the structure durability, this study presented a multi-scale finite element (FE) method for investigating the seepage process and mechanism inside the SSA concrete. The above FE method consisted of a microscale mortar model and a mesoscale concrete model, developed by integrating image processing technique and random aggregate method. The permeability coefficient of SSA concrete was evaluated with the above multi-scale FE method and was validated with experiment. The relative differences between the numerical simulation and experimental mean values of the permeability coefficients are 3.38∼5.94 %. Based on the validated method, the effects of steel slag on the seepage characteristics of concrete were analyzed. Results show that the incorporation of steel slag could decrease the permeability of concrete by reducing the mortar porosity in the microscale and reducing the thickness of the interfacial transition zone (ITZ) between aggregate and mortar in the mesoscale. Using over-simplified aggregate shapes in numerical simulation may underestimate the permeability coefficient of concrete, which emphasizes the importance of refined modelling. The permeability coefficient of concrete may exhibit anisotropy. When considering lateral water permeation, aggregates with aspect ratios close to one may offer superior resistance to seepage. The analysis findings provide insights for better material design of concrete with recycled materials. • Developed and validated multi-scale model of concrete containing steel slag aggregate for prediction of permeability. • Measured permeability of concrete and aggregate and observed interfacial transition zone of concrete using microscopy imaging. • Analyzed effects of steel slag on seepage characteristics and permeability of concrete. [ABSTRACT FROM AUTHOR]

Paper, a porous-fibrous network, is made up of hydrophilic fibres, which are notably susceptible to deformations due to variations in moisture content. The response of paper sheets to full or partial wetting, based on the water-induced fibre swelling, has mostly been predicted in the past using highly idealised two-dimensional network geometries. The purpose of the present paper is to establish how precisely the two-stage process of determining effective hygro-expansivity under uniform wetting by a two-dimensional model followed by bending analysis using a continuum model predicts the curl of a fully three-dimensional network. In the present multi-scale modelling work, the moisture-induced homogenised sheet scale curl, derived from hygro-elastic deformations using non-uniform moisture profiles, is analysed based on an idealised non-woven three-dimensional fibrous network finite element model. First, the effective paper sheet swelling properties, derived computationally for the uniform wetting condition, are compared with analytically homogenised hygro-elastic properties. Whereas the analytically predicted elastic modulus has an inaccuracy of only ∼ 5%, the hygro-expansivity coefficient is over-predicted by roughly a third for a network with straight fibres. The difference is smaller if waviness of the fibres and wrap-around in the fibre bonds are taken into account. Fibre alignment turns out to have little influence. Subsequently, paper sheet curl predictions made by the analytical model are compared with that computed from the three-dimensional network model. The inaccuracy of the fully analytical model, based on the two-dimensional network description, relative to the fully detailed three-dimensional computational model with straight fibres is on the order of 40%–50%. The fidelity of the simple model is primarily constrained by the inaccuracy of the effective hygro-expansion coefficient. If the expansivity extracted from the three-dimensional simulations under uniform wetting is inserted, the inaccuracy drops to less than 10%. The continuum bending description hence performs adequately, provided it is based on a reliable estimation of the uniform expansion behaviour of the material. • Hygroscopic curl of paper sheets may be predicted using homogenised models. • We assess the accuracy of such predictions. • As a reference simulations of an idealised three-dimensional fibre network are used. • The predictions are accurate provided an accurate hygro-expansivity is used. • Two-dimensional network models may not be sufficient for this. [ABSTRACT FROM AUTHOR]

The pin-on-disc test is a widely employed method for investigating the friction and wear performance of materials in conformal contact. In a typical pin-on-disc system, self-aligning pin holders are frequently utilized to ensure proper surface contact. This study reveals that in such a setup, pin inclination has a significant impact on test reliability, particularly under oil-lubricated conditions, which may overweight the influence of other parameters such as roughness or texture elements. Utilizing in-situ measurements, we captured the dynamic changes in pin inclination during rotational sliding. Our findings indicate that the pin inclination varies with sliding speed, showing a pitch angle difference of approximately 0.01°as the speed decreases from 2 m/s to 0.04 m/s in our test setup. Importantly, a robust correlation was identified between the friction coefficient and pin inclination, which is supported by the numerical investigation. This study underscores concerns regarding the test reliability of pin-on-disc tribometers, prompting a reconsideration of the assumptions associated with self-aligning pin holders in such experimental configurations. • In-situ pin inclination was successfully measured for the pin-on-disc sliding test. • Robust correlation was observed between the friction coefficient and pin inclination. • The significant effect of pin inclination was supported by numerical investigations. [ABSTRACT FROM AUTHOR]

Mechanistic multi-scale modelling holds the potential to inform fuel performance codes by incorporating high-fidelity models, algorithms, parameters, and material properties. In this context, meso-scale codes emerge as valuable tools for developing detailed models and performing separate verification and validation steps. This work focuses on SCIANTIX, an open-source 0D meso-scale code designed to describe the behaviour of gaseous and volatile fission products in nuclear oxide fuel. The code predominantly employs engineering physics-based behavioural models featuring computational times that align with typical fuel performance code requirements. Given the numerical foundation of the code, it is applicable to both stationary and transient conditions. Following a recent work outlining the standalone SCIANTIX (version 2.0) performance and its separate-effect validation database, we present its performance when coupled with fuel performance codes to simulate light water reactor fuel rods. The experiments selected for the comparative analysis constitute an initial integral validation database. The comparison focuses on conventional engineering quantities of interest, such as integral fission gas release, demonstrating the satisfactory performance of the code. Additionally, it highlights the potential advantages of multi-scale modelling over conventional semi-empirical approaches. • The integral validation database of SCIANTIX is detailed. • The code is coupled with the thermo-mechanical fuel performance codes TRANSURANUS, FRAPCON and OFFBEAT. • The validation database includes Light Water Reactor fuel rods operating in nominal operative and transient conditions. • The comparison is performed against engineering quantities such as the integral fission gas release. • Potential advantages of the multi-scale modelling and future developments are outlined. [ABSTRACT FROM AUTHOR]

Architected materials and mechanical metamaterials are known for their unique macroscopic properties and complex behaviour that often defy conventional continuum mechanics. Therefore, in this contribution, a recent multi-scale second-order computational homogenisation method (Dos Santos et al., 2023) is employed to explore these materials under finite strains. The approach combines a second gradient continuum theory at the macro-scale and a representative volume element (RVE) with classical first-order continuum mechanics at the micro-scale. The Method of Multi-scale Virtual Power ensures a consistent scale transition. The predictive capability and applicability of the second-order computational strategy are evaluated through coupled multi-scale numerical simulations. These simulations involve two- and three-dimensional problems, with a strong focus on the development of novel metamaterials, while also accounting for diverse loading conditions, such as tension/compression-induced undulation, bending, and compression-induced torsion. Comparisons with first-order homogenisation and Direct Numerical Simulations validate the approach. Analysis of homogenised consistent tangents reveals valuable insights into macroscopic properties. Overall, the results highlight the capability of the second-order strategy to capture significant phenomena, including second-order deformation modes, coupling deformation mechanisms, and size effects. • A multi-scale second-order homogenisation method is used to explore metamaterials. • A second gradient continuum theory is combined with first-order continuum mechanics. • An assessment is conducted through coupled multi-scale numerical simulations. • Novel metamaterials are investigated for diverse loading conditions. • Higher-order deformation modes, coupling mechanisms and size effects are captured. [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]

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]

The stiffness of mechanically fastened joints influences static and dynamic characteristics of machine tools. The conventional contact stiffness model considers only the deformation of roughness asperities based on uncertain topographic parameters. This study presents a holistic contact stiffness model considering the subsurface deformation and avoiding assumptions of topographic characteristics, which tend to introduce uncertainty. Subsurface deformation was also investigated via stress distribution measurements and finite element simulations. Using the proposed model, the stiffness of jointed parts was estimated with an error <15%. Moreover, the subsurface deformation's influence on contact surface design was discussed. [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]

• Neointimal hyperplasia (NIH) is a major obstacle to peripheral graft patency. • NIH progression is influenced by haemodynamic forces in the lumen. • Compliance mismatch between host vessel and graft can impact these forces. • We used computational fluid dynamics and a model of NIH to assess this impact. • We observed a small impact of compliance in the cases analysed. Neointimal hyperplasia (NIH) is a major obstacle to graft patency in the peripheral arteries. A complex interaction of biomechanical factors contribute to NIH development and progression, and although haemodynamic markers such as wall shear stress have been linked to the disease, these have so far been insufficient to fully capture its behaviour. Using a computational model linking computational fluid dynamics (CFD) simulations of blood flow with a biochemical model representing NIH growth mechanisms, we analyse the effect of compliance mismatch, due to the presence of surgical stitches and/or to the change in distensibility between artery and vein graft, on the haemodynamics in the lumen and, subsequently, on NIH progression. The model enabled to simulate NIH at proximal and distal anastomoses of three patient-specific end-to-side saphenous vein grafts under two compliance-mismatch configurations, and a rigid wall case for comparison, obtaining values of stenosis similar to those observed in the computed tomography (CT) scans. The maximum difference in time-averaged wall shear stress between the rigid and compliant models was 3.4 Pa, and differences in estimation of NIH progression were only observed in one patient. The impact of compliance on the haemodynamic-driven development of NIH was small in the patient-specific cases considered. [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]

• Multi-scale combined RVE-cohesive elements approach is accurate in reproducing the mechanical response of FDM-printed components. • The effect of the main controllable printing parameters on mechanical properties is examined experimentally and numerically. • Different damage mechanisms taking place are investigated starting from microscope observations. • Finite-Elements simulations accurately reproduce the experiments. • Homogenization technique is useful to model macroscopic 3D-printed parts by assigning homogenized properties. Mechanical strength of 3D-printed components dramatically depends on printing process parameters. These can be usually set over a relatively wide range, in combinations that determine the microstructure morphology and the resulting mechanical behaviour. The present investigation focuses on the relationship between revealed structure and resulting mechanical properties of FDM-printed ABS specimens. The peculiar structures, examined at the meso- and microscale, are modelled by a finite-element Representative Volume Element (RVE) approach, in conjunction with cohesive elements to reproduce the sealing efficiency between fused filaments. The simulation of the tensile response up to failure falls within the 95% of confidence with experiments. Also, homogenized response of RVE determines spatial material constants useful for the effective numerical simulations of functional components, and intra- and inter-layer damage mechanisms are distinguished providing hints for the structural optimization. [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]

• Multi-scale modelling illuminates concrete deterioration at varying length scales. • Multi-scale modelling significantly contributes to sustainable infrastructure. • Challenges like data accuracy and computational complexity necessitate advancements. • Facilitates precise performance predictions, aiding informed decisions in maintenance. The properties of concrete are degraded during service by coupled physical and chemical processes that operate at several length scales, and the prediction of its performance in engineering structures requires multi-physics, multi-scale modelling approaches. The aim of this paper is to provide a comprehensive overview of the current modelling techniques for analysis of concrete deterioration. The paper covers the fundamentals of modelling at several length scales, as well as the bridging/transition between scales, and the numerical methods based on continuum and discrete formulations appropriate to different scales. Considered are the key chemical and physical deterioration processes of carbonation, chloride ingress, freeze–thaw damage, and abrasion. The paper also reviews the validation and verification of multi-scale models and discusses future trends such as data science integration and sustainable concrete design. It is expected that the information presented here will be a valuable resource for researchers and practitioners in the field, highlighting advancements and stimulating future research in multi-scale modelling of concrete deterioration. [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]

The mechanical anisotropy of FCC aluminium alloy is influenced by the polycrystalline orientations transformed by cold rolling. The relationship between mechanical anisotropy and evolution of crystallographic textures was established using the crystal plasticity finite element method (CPFEM) based on measured polycrystalline orientation density functions (ODFs) and used to determine the parameters of a phenomenological convex anisotropic yield function which are solved with an implicit finite element (FE) stress integration code. A multi-scale modelling system is generated by combining CPFEM and the phenomenological yield function enabling accurate simulations of forming operations without the need for conventional physical mechanical testing of the material. • Quantify the evolution of texture induced anisotropy of FCC aluminium alloy sheet during cold rolling process. • A multi-scale modelling system is generated by combining crystal plasticity method and phenomenological approach. • The multi-scale modelling system has been shown to accurately predict the deformation of sheet metal in forming process. [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]

Highlights • A multi-scale model of heterogeneous aluminium sheets was developed using the DIGIMAT software. • Nonlinear 3D FE-analyses of quad core aluminium sandwich panels with a crack was reviewed. • The damage process was implemented in ABAQUS software. • The theoretical approach was performed using energy methods. • The fatigue damage mechanical model was developed. Abstract This paper develops a multi-scale analysis of fatigue damage behaviour of a quad-core sandwich panel with a heterogeneous aluminium alloy containing silicon in a ductile aluminium matrix. The analysis is based on the Representative Volume Element (RVE)-concept. Because of their capacity and high strength-to-weight ratio, these materials can be increasingly used in industry. Here, an elastic-plastic fracture analysis has been clearly considered on the heterogeneous aluminium undergoing tensile deformation. A nonlinear fatigue damage analysis of quad-core (WF51 PMI foam, H100 PVC foam, aluminium foam, and WF110 PMI foam) sandwich panel has been mainly investigated. The model proposed in the commercial software of ABAQUS with the robust nonlinear functions has been also implemented. The theoretical and analytical results are in good agreement with damage evolution and its variations. [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]

Highlights • A novel constitutive modelling framework ( μ -GM) for granular materials is developed based primarily on micromechanical considerations. • The constitutive model is founded on the decomposition of particle-scale mechanisms into dissipative and non-dissipative, which is different from common elastic/plastic dichotomy. • By including only three calibration parameters, the μ -GM constitutive model is shown to successfully predict stress-strain response, as well as the evolution of key micro-variables such as fabric anisotropy and coordination number for 2D granular assemblies. • Within a boundary-value problem setting, μ -GM constitutive model gives access to rich local particle-scale information, thus circumventing computationally expensive DEM simulations of large granular assemblies. Abstract A strictly micromechanical framework is proposed for the constitutive modelling of granular materials as a variant to existing micromechanically-enriched continuum models. The theory hinges on the fact that the constitutive behaviour of granular materials can be formally written via an incrementally non-linear expression of stress and strain derived from an exhaustive set of key microvariables that statistically describe contact normals and force networks at the lower scale. The model also incorporates key physics uncovered by micromechanical findings of granular material behaviour such as dissipative and non-dissipative deformational mechanisms, including the existence of a unique surface, named Stable Evolution State as a bounding surface to quasi-static stable evolutionary states that generalizes the well-known critical state in soil mechanics. The proposed model, herein coined as μ -GM, acts as a surrogate for a full-blown discrete element method model in that it includes only three intrinsic material parameters complemented with three calibration ones to reveal most salient microstructural information and their evolution during loading history. As such, it can be readily incorporated into standard finite element simulations of boundary-value problems with computations to the resolution of the microscale. The present model currently formulated in 2D conditions can be readily extended to 3D to explore more complex problems with rotation of principal stresses. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Coloured Hybrid Petri Nets are proposed to model complex biological networks that exhibit multiple spatial and temporal scales. • Hybrid simulation is shown to be a powerful tool to analyze biological models with multiple time scales. • Two case studies illustrate the applicability of the approach for addressing the multiscale challenges of biological systems. Abstract Coloured Petri nets are an excellent choice for exploring large biological models, particularly when there are repetitions of components. Such models can be easily adapted by slight modifications of parameter values related to colours. Similarly, multi-scale models could involve multiple spatial scales in addition to multiple time scales. Thus, they require the full interplay between stochastic as well as deterministic processes. In this paper we take these two aspects into account and present a modelling and simulation approach for multi-scale biochemical networks using Coloured Generalised Hybrid Petri Nets (G H P N C). G H P N C are a Petri net class that associates colours to Generalised Hybrid Petri Nets (G H P N), which incorporate discrete and continuous places in addition to stochastic and continuous transitions. Moreover, we present two case studies to illustrate typical applications taking advantage of such a Petri net class. [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]

This paper suggests a methodology to obtain homogenised material properties from a transient dynamic numerical model. The standard Hill–Mandel Principle, based on spatial averages, is extended with time averaging. Thus, in addition to a sufficiently large Representative Volume Element (RVE) to carry out the averaging in space, a sufficiently large time window is required to carry out the time averaging. The space–time averaging procedure is validated for a periodic laminate bar subjected to a variety of boundary conditions, impedance contrasts and loading conditions. The homogenised results converge to the analytical solutions and confirm that having a higher impedance contrast between laminate components requires not only larger RVE sizes but also longer time averaging windows. The most efficient macroscopic approximation is obtained by a balanced increase in RVE size and time averaging window. • Space averaging of the Hill–Mandel principle is extended to space–time averaging. • The equivalent of Representative Volume in the time domain is established. • A scheme for transient numerical homogenisation is proposed. [ABSTRACT FROM AUTHOR]

High-temperature oxidation can precipitate chemical and mechanical degradations in materials, potentially leading to catastrophic failures. Thus, understanding the mechanisms behind high-temperature oxidation and enhancing the oxidation resistance of thermal structural materials are endeavors of significant technical and economic value. Addressing these challenges often involves dissecting phenomena that span a broad range of scales, from micro to macro, a task that can prove challenging and costly through in-situ experimental approaches alone. Advancements in computational techniques have revolutionized the study of high-temperature oxidation. Various calculation and simulation methodologies now offer the means to rapidly acquire data with cost efficiency, providing a powerful complement to traditional experimental research. This review concentrates on the evolution and utility of these computational approaches in the domain of high-temperature oxidation. It underscores the critical role of calculation and simulation in materials science, offering insights into mass transport, mechanical failure, chemical reactions, and other multi-scale phenomena associated with oxidation processes. In this context, detailed discussions are presented on computational analyses at both atomic and mesoscopic levels, elucidating their respective contributions to our understanding of high-temperature oxidation mechanisms. Furthermore, the review highlights the impact of high-throughput computing in streamlining research and development processes, facilitating a more expedited exploration of innovative solutions in materials science. Through these discussions, the review aims to illustrate the indispensable nature of computational methods in advancing our comprehension and management of high-temperature oxidation phenomena. [ABSTRACT FROM AUTHOR]

Abstract Prosthetic heart valves deployed in the left heart (aortic and mitral) are subjected to harsh hemodynamical conditions. Most of the tissue engineered heart valves have been developed for the low pressure pulmonary position because of the difficulties in fabricating a mechanically strong valve, able to withstand the systemic circulation. This necessitates the use of reinforcing scaffolds, resulting in a tissue-engineered textile reinforced tubular aortic heart valve. Therefore, to better design these implants, material behaviour of the composite, valve kinematics and its hemodynamical response need to be evaluated. Experimental assessment can be immensely time consuming and expensive, paving way for numerical studies. In this work, the material properties obtained using the previously proposed multi-scale numerical method for textile composites was evaluated for its accuracy. An in silico immersed boundary (IB) fluid structure interaction (FSI) simulation emulating the in vitro experiment was set-up to evaluate and compare the geometric orifice area and flow rate for one beat cycle. Results from the in silico FSI simulation were found to be in good coherence with the in vitro test during the systolic phase, while mean deviation of approximately 9% was observed during the diastolic phase of a beat cycle. Merits and demerits of the in silico IB-FSI method for the presented case study has been discussed with the advantages outweighing the drawbacks, indicating the potential towards an effective use of this framework in the development and analysis of heart valves. [ABSTRACT FROM AUTHOR]

This manuscript shows how computational models, mainly based on Computational Fluid Dynamics (CFD), can be used to simulate different parts of an industrial freeze-drying equipment and to properly design them; in particular, the freeze-dryer chamber and the duct connecting the chamber with the condenser, with the valves and vanes eventually present are analysed in this work. In Part 1, it will be shown how CFD can be employed to improve specific designs, to perform geometry optimization, to evaluate different design choices and how it is useful to evaluate the effect on product drying and batch variance. Such an approach allows an in-depth process understanding and assessment of the critical aspects of lyophilisation. This can be done by running either steady-state or transient simulations with imposed sublimation rates or with multi-scale approaches. This methodology will be demonstrated on freeze-drying equipment of different sizes, investigating the influence of the equipment geometry and shelf inter-distance. The effect of valve type (butterfly and mushroom) and shape on duct conductance and critical flow conditions will be instead investigated in Part 2. [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]

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]

Most suspension descriptions nowadays employed are based on Jeffery model and some of its phenomenological adaptations that do not take into account the possible existence of a relative velocity between the fibres and the suspending fluid when the fibre interactions increase. It is expected that at very low density of contacts, as predicted by standard suspension models, fibres move with the suspending fluid velocity. When the density of fibre interactions becomes extremely high and a percolated network of fibre contacts is established within the suspension, fibres cannot move anymore and then the fluid flows throughout the rigid or moderately deformable entangled fibre skeleton, like a fluid flowing through a porous medium. In between these two limit cases, one could expect that fibres move but with a velocity lower than the one of the suspending fluid. Thus, two contributions are expected, one coming from standard suspension theory in which fibres and fluid move with the same velocity, and the other resulting in a Darcy contribution consisting of the relative fibre/fluid velocity. In this paper, we elaborate a general model able to adapt continuously to all these flow regimes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-scale modelling of a fluidized bed biomass gasifier of industrial size. • A detailed particle model (PM) resolving gradients is coupled to CFD reactor model. • Comparison to the simplified modelling approach commonly employed in literature. • Analysis of particle tracks and gas release stress the need to use a detailed PM. • Feasibility of the coupled model was shown for a plant of relevant size (1 MW) Fluidized bed biomass gasification is a complex process whereby gas source terms are released by reactions at the particle level during the movement of fuel particles throughout the reactor. The current study presents for the first time the application of a multi-scale modelling approach for a fluidized bed biomass gasifier of industrial size, coupling a detailed one-dimensional particle model based on the progressive conversion model (PCM) with a commercial CFD software. Results of particle movement and gas source terms are compared with results of an additional simulation employing the simplified uniform conversion model (UCM) which is commonly used in literature. Validation at the particle level showed that the UCM leads to a massive underprediction of the time needed for pyrolysis whereas the PCM is in good agreement with experimental data. This heavily influences the gas sources released during pyrolysis of the biomass particles in the coupled reactor simulations. Volatiles are much more concentrated to the close proximity of the fuel feed when using the UCM whereas the PCM leads to a more homogeneous distribution over the reactor cross-section. The calculation time analysis of the coupled simulations showed that despite the increased complexity, the PCM shows only an increase of 20% in calculation time when compared to the UCM, whereas it is much better suited for these conditions. The coupled multi-scale simulations using the PCM showed the numerical feasibility of the modelling approach for 1,200,000 bed parcels and about 80,000 reacting fuel parcels and furthermore highlighted the importance of a comprehensive description of the particle level. [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]

The present work deals with the main mechanisms involved in caking of amorphous powders and its theoretical background. After a brief outline of the general basics, the review continues with summarizing available models and their analytical solutions predicting inter-particle bridge formation as the micro scale description of caking. Outputs of numerical techniques including conventional computational fluid dynamics (CFD) methods alongside with some newer methods such as lattice Boltzmann method (LBM), on capturing the inter-particle bridge interface when two particles are sticking together are also investigated. With an overview on the applications of numerical methods for describing multi-particle caking as an intermediate scale, the review continues through investigation of simulations carried out for macro scale caking. The macro scale study surveys numerical methods belonging to the discrete viewpoint – discrete element method (DEM) particularly – while continuum point of view was out of purpose. This review summarizes the basics in caking of amorphous powders along with the modeling approaches predicting viscous sintering mechanism and the use of analytical and numerical methods provided to solve such models. The review characterizes competencies and limitations of the listed methods. Prospects for future research in this area are also highlighted. The result of this study will be useful in identifying the future research directions needed in order to understand leading mechanisms in caking of amorphous powders and also to facilitate the development of more accurate and sophisticated models to predict the kinetics of this phenomenon in process industries. [ABSTRACT FROM AUTHOR]

Viral pathogens are a significant source of human morbidity and mortality, and have a major impact on societies and economies around the world. One of the challenges inherent in targeting these pathogens with drugs is the tight integration of the viral life cycle with the host's cellular machinery. However, the reliance of the virus on the host cell replication machinery is also an opportunity for therapeutic targeting, as successful entry- and exit-inhibitors have demonstrated. An understanding of the extracellular and intracellular structure and dynamics of the virion – as well as of the entry and exit pathways in host and vector cells – is therefore crucial to the advancement of novel antivirals. In recent years, advances in computing architecture and algorithms have begun to allow us to use simulations to study the structure and dynamics of viral ultrastructures at various stages of their life cycle in atomistic or near-atomistic detail. In this review, we outline specific challenges and solutions that have emerged to allow for structurally detailed modelling of viruses in silico . We focus on the history and state of the art of atomistic and coarse-grained approaches to simulate the dynamics of the large, macromolecular structures associated with viral infection, and on their usefulness in explaining and expanding upon experimental data. We discuss the types of interactions that need to be modeled to describe major components of the virus particle and advances in modelling techniques that allow for the treatment of these systems, highlighting recent key simulation studies. [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]