Phononic crystals (PnCs) and acoustic metamaterials (AMs) are advanced functional materials engineered to achieve broad bandgaps for wave manipulation through optimized spatial distribution. Despite significant progress, the efficient design of three-dimensional AMs with bi-connected topologies remains a major challenge using conventional topology optimization methods. The novel floating projection

The Interaction-Based Deep Material Network (IB-DMN) is reformulated to decouple the phase volume fraction from the topological parameters of the IB-DMN. Since the phase volume fraction is no longer influenced by the topological parameters, on the one hand the stochastic IB-DMN can predict the response of arbitrary phase volume fraction, and on the other hand the stochastic IB-DMN can be constructed

Soft particles in viscous flows are prevalent both in nature and in various industrial applications. Notable examples include biological cells such as blood cells and bacteria as well as hydrogels and vesicles. To model these intriguing particles, we present an extension of our recent, efficient, and versatile pseudo-rigid body approach, originally developed for initially spherical soft particles suspended

Physics-Informed Neural Networks (PINNs) are computationally efficient tools for addressing inverse problems in solid mechanics, but often face accuracy limitations when compared to traditional methods. We introduce a refined PINN approach that rigorously enforces certain physics constraints, improving accuracy while retaining the computational benefits of PINNs. Unlike conventional PINNs, which are

The Statistical Finite Element Method (statFEM) offers a Bayesian framework for integrating computational models with observational data, thus providing improved predictions for structural health monitoring and digital twinning. This paper presents a sampling-free statFEM tailored for non-conjugate, non-Gaussian prior probability densities. We assume that constitutive parameters, modeled as weakly

Two classes of non-linear elastic materials are derived via two-dimensional homogenization. These materials are equivalent to a periodic grid of axially-deformable and axially-preloaded structural elements, subject to incremental deformations that involve bending, shear, and normal forces. The unit cell of one class is characterized by elements where deformations are lumped within a finite-degrees-of-freedom

Accurate prediction of the fatigue life of API X65 steel is crucial in various applications. However, the traditional bootstrap method has inherent limitations, such as a tendency to deviate from the true distribution with insufficient sample sizes, difficulty in identifying extreme statistics, and an inability to generate distributions closer to the original sample. These deficiencies lead to overly

This paper proposes a procedure for analyzing crack propagation in complex structures based on lumped damage mechanics. This theory combines the concept of a plastic hinge with the procedures of damage and fracture mechanics. Models of damage for monotonic loading and high-cycle fatigue are proposed. The paper also describes the numerical implementation of the models in conventional finite-element

This study aims to investigate the tensile behavior of ultra-high performance concrete (UHPC) using a multiscale modeling approach. A micromechanics-based finite-element method is employed to investigate the evolution of microstructural damage and its effect on the macroscopic tensile strength of UHPC. X-ray computed tomography (CT) techniques are used to create a realistic microstructural geometry

Contact problems are of paramount importance in engineering but present significant challenges for numerical solutions due to their highly nonlinear nature. Recognizing that contact problems can be formulated as optimization problems with inequality constraints has paved the way for advanced techniques such as the Interior Point (IP) method. This study presents an Improved Edge-based Smoothed Particle

A novel staggered grid shell particle method (SGSPM) is proposed in this paper to model the shell structural damage subjected to underwater explosion. The material point method (MPM) is used to model the fluid in underwater explosion, and the solid shell material point method (SSMPM) is adopted to model the shell structures. A staggered grid scheme is employed to eliminate the cell crossing noise and

In this study, a novel active learning method is proposed and combined with Meta-IS-AK for hybrid reliability analysis under small failure probability. Considering the proportion of responses falling into the failure domain, the interval failure degree is introduced to describe the probability of misjudging the state for random samples. The novel active learning method (IAD) is proposed to select valuable

Neural surrogates for partial differential equations (PDEs) have become popular due to their potential to quickly simulate physics. With a few exceptions, neural surrogates generally treat the forward evolution of time-dependent PDEs as a black box by directly predicting the next state. While this is a natural and easy framework for applying neural surrogates, it can be an over-simplified and rigid

We present a geometrically exact 3D beam model that incorporates axial and radial swelling strains, both small and large, resulting from a rotationally symmetric, thermal or chemical diffusion. Isogeometric collocation is employed to discretize both the mechanical momentum balances and the axis-symmetric, steady-state 2D diffusion equation along the beam. The resulting coupled nonlinear problem for

In recent times, with the rise of nanoscale technologies, miniaturization of devices has prompted the need to study electromechanical phenomena at small scales. Most studies focus on the phenomena occurring at the bulk portion of the material, such as flexoelectricity, but neglect the effects that arise from the surfaces of the samples. Given the fact that, at such scales, surface-to-volume ratio is

Stefan problems describe heat transfer through a material undergoing phase change, and solving these problems poses a real challenge due to the existence of a time-dependent moving boundary at the phase change interface. We propose an efficient and reliable physics-informed extreme learning machine (PIELM) framework for solving Stefan problems, which is achieved by replacing deep neural networks in

Neural Operators are fast and accurate surrogates for nonlinear mappings between functional spaces within training domains. Extrapolation beyond the training domain remains a grand challenge across all application areas. We present Time-Conditioned UNet (TC-UNet) as an operator learning method to solve time-dependent PDEs continuously in time without any temporal discretization, including in extrapolation

This work aims to address the challenge of achieving continuity in beam element interpolation by introducing a geometrically exact beam finite element based on generalized B-spline interpolation on the special Euclidean group SE(3). The beam’s configuration is represented within the SE(3) framework and interpolated using a generalized B-spline approach, enabling high-order interpolation with enhanced

A numerical model has been developed to simulate microstructure evolution in stainless steel 316L components produced via Metal Extrusion Additive Manufacturing (MExAM). The model integrates key phenomena, including heat conduction, mechanical fields influenced by gravity, and phase-field equations, offering a robust framework to understand and control changes in thermomechanical properties during

Wrinkling is the phenomenon of out-of-plane deformation patterns in thin walled structures, as a result of a local compressive (internal) loads in combination with a large membrane stiffness and a small but non-zero bending stiffness. Numerical modelling typically involves thin shell formulations. As the mesh resolution depends on the wrinkle wave lengths, the analysis can become computationally expensive

A novel modeling method for DZ125 superalloy has been proposed, integrating a long short-term memory (LSTM) network into the Chaboche unified viscoplasticity constitutive model. Initially, the modified Chaboche constitutive model, incorporating the multimodal microstructure coupled with time-series damage, was developed and implemented using the UMAT subroutine in ABAQUS. Subsequently, damage parameters

A geometrically characteristic kinetic thermodynamic deformation theory is proposed for effective predictions over the full-life mechanical behaviour of crystalline solid. From a theoretic perspective, the proposed theory is distinguished from existing internal state variable theories at least in two aspects. Firstly, it is “geometrically characteristic” because the quantities employed for summarising

A wide range of solid dynamics problems include a central focus on fracture, fragmentation, and thermomechanical failure processes difficult to accommodate in current continuum, particle, or mixed particle-continuum formulations. In recent research the authors have developed a new mesh-free method for solid dynamics simulation which addresses this class of problems. The method uses a nonholonomic Hamiltonian

Jointed soft-hard composite rock masses are commonly encountered in engineering rock formations. The excavation-induced can lead to incompatible deformations between joints and soft-hard layers, resulting in more complex failure mechanisms compared to those under static loading. It is necessary to monitor rock micro-fracture events in real time during excavation to obtain the precursor information

The present work provides a modeling framework to capture the complex multi-physics electro-chemical-hydro-mechanical processes in membranes of multilayer Proton Exchange Membrane Water Electrolysis (PEMWE) cells. It relies on the Theory of Porous Media (TPM) to establish a continuum-based framework suitable for efficient simulation of the coupled interactions of porous multiphase materials. This macroscopic

A realistic and complete reproduction of the three-dimensional crack tip morphology and propagation process is of significant theoretical and practical importance for studying the fatigue issues of materials and components under cyclic loading. To this end, a marker load method for random spectra is proposed. This method, as a quantitative fractography approach, marks the crack tip in three dimensions

Erosion damage significantly reduces the fatigue life of engine blades. To satisfy modern aircraft lightweight requirements, particle-reinforced aluminum matrix composites are replacing traditional aluminum alloys. Assessing the erosion tolerance of these advanced materials is crucial for ensuring long-term performance. This study explores the effect of solid particle erosion on the fatigue behavior

Ti-6Al-4V is widely used in aero-engine compressor blades, but its low fretting fatigue resistance makes integrity challenging. Compound treatment has been recognized as a future technology with enhanced mechanical properties. However, these attempts were limited to low-cycle fatigue. The beneficial fretting fatigue performance enhancements through compound strengthening are still prominent. This study

Predicting the fatigue life of parts fabricated by laser powder bed fusion (LPBF) is essential for assessing their durability and reliability in mission-critical load-bearing structures. Herein, we propose a novel machine learning (ML) strategy for predicting fatigue life of LPBF parts. It combines three-stage feature screening, data augmentation, a hybrid clustering integrated regression model (H-CIRM)

Constructing constitutive models for compressible soft materials is essential for accurately describing their highly nonlinear, large deformation mechanical behavior and volumetric deformation. However, most existing constitutive models rely on predefined assumptions about the form of the strain energy function. Constructing compressible hyperelastic constitutive models is particularly challenging

This work presents an efficient phase field fracture methodology for modeling high-cycle fatigue crack growth in laser-based Directed Energy Deposition (LDED) produced components. The model incorporates a fatigue history variable that accounts for fatigue crack propagation with sensitivity to the mean load variations by introducing an accumulative energy term. Two distinct available degradation functions

A356 alloys produced by low pressure die casting (LPDC) typically contain casting defects and non-uniform microstructure. In this study, a multi-scale fatigue prediction method for the automotive wheel considering both hydrogen and shrinkage microporosity and secondary dendrite arm spacing (SDAS) has been developed. A three-dimensional cellular automata (CA) model is used to simulate both dendritic

Of the non-classical nonlinear elastic phenomena, slow dynamics (SD) has received particular attention due to recent modeling efforts and experiments in new systems. SD is characterized by a loss of stiffness after a minor conditioning strain, followed by a slow recovery back towards the original stiffness. It is observed in many imperfectly consolidated granular materials (e.g., rocks and concrete)

Elastic metamaterials possess flexible regulatory capabilities of elastodynamic field information and energy through engineering and tailoring wave amplitudes, phase, and polarization vectors. However, due to the lack of general wave quantities and dynamic mode characterization methods, it is difficult to describe and design customized elastic dispersions with prescribed eigenmodes of interest, especially

Multiphase thin films exhibit unique physical functionalities stemming from their dimensions and interactions among phases. In these materials, elasticity plays an important role both in their growth and physical performance. An outstanding problem in this regard is the elastic formulation of representative volume element (RVE) of thin film systems. As thin films RVEs lack translation invariance in

Bio-inspired composite materials with staggered microstructures exhibit superior mechanical properties compared to traditional composites, paving the way for the development of advanced functional materials. The existing analytical models mainly address the macroscale constitutive response along the staggering direction using plane strain or plane stress assumptions. Consequently, a significant gap

Compacted graphite iron (CGI) is widely used in automotive engines thanks to its excellent castability and thermal conductivity. Despite extensive research, the influence of its microstructure on the fracture behaviour has not been fully elucidated. In this work, four different damage models with realistic and simplified morphologies are compared. The developed models consider the effect of graphite-particle

Isogeometric Analysis (IGA) is a promising technique that integrates geometric modeling with numerical analysis. An essential step in IGA is domain parameterization, which aims to establish a parametric representation for a given computational domain. Specifically, it involves defining a spline-based mapping from the standard parametric domain to the computational domain. Typically, domain parameterization

Multiscale simulations are indispensable for connecting microstructural features to the macroscopic behavior of polycrystalline materials, but their high computational demands limit their practicality. Deep material networks (DMNs) have been proposed as efficient surrogate models, yet they fall short of capturing texture evolution. To address this limitation, we propose the orientation-aware interaction-based

Detection of abrupt spatial changes in physical properties representing unique geometric features such as buried objects, cavities, and fractures is an important problem in geophysics and many engineering disciplines. In this context, simultaneous spatial field and geometry estimation methods that explicitly parameterize the background spatial field and the geometry of the embedded anomalies are of

A new truly unbiased frictional contact formulation exclusively leveraging the midplane-based segment-to-segment (STS) interaction with a predictor–corrector approach is presented. Unlike the traditional master–slave based dual pass approaches, this formulation only requires a single pass providing a computational advantage in comparison. This work details the development of a penalty-regularised frictional

This work provides key advancements to a nascent simulation approach (Yue et al., 2018; Chen et al., 2021), which hybridizes two common simulation methodologies: discrete element methods and continuum methods. Discrete element methods (DEM), commonly used in granular media simulation, model every single micro-constituent and are thus accurate; however, in light of the enormous number of particles frequently

In Reliability-Based design Optimization (RBDO), the aim is to develop an optimal design characterized by high reliability through fulfilling design requirements at the targeted probability threshold. The goal of reliability optimization is to obtain excellent algorithms by focusing on evaluation and optimization. In RBDO, due to the selection of evaluation methods and the problem of updating reliable

This study proposes a stabilized LSMPS method for simulating free surface flows with moving wall. In this stabilized LSMPS method, a novel wall velocity model is proposed for velocity divergence calculation and velocity interpolation. The proposed method also combines type-A and type-B LSMPS to enhance both accuracy and stability. Type-A LSMPS is applied to internal particles, while type-B scheme is

This study presents a stochastic elasto-plastic fracture and fatigue analysis framework, leveraging the phase field method to address the complex fatigue phenomenon. Fatigue behaviour in elasto-plastic materials, governed by the intricate process of plastic damage accumulation, remains pivotal for precisely evaluating structural load-bearing capacities. Transitioning from static fracture analysis to

A fundamental understanding of the microstructure–property relationships (MPRs) is crucial for optimising the performances and functionality of multiphase composites. Image-based poro/micro-mechanical modelling offers a powerful non-invasive method to explore MPRs, but the inherent randomness in multiphase composites often necessitates extensive datasets of 3D digital microstructures for reliable statistical

This paper presents a novel space–time isogeometric topology optimization (ITO) framework for additive manufacturing, enabling concurrent optimization of structural shape and fabrication sequence with accurate geometric representation. The method integrates a density distribution function with a pseudo-time function to optimize build sequences for complex structures, with an objective function that

Mechanical metamaterials feature unique and complex architectures that produce properties not present in their base materials. Traditional design methods often fall short in exploring the vast 2D design space efficiently, necessitating advanced techniques that can accommodate the design of these metamaterials. This paper presents a comprehensive framework for the design and evaluation of 2D metamaterials

Stochastic partial differential equations (SPDEs) are commonly encountered in the realms of engineering and computational science. Solving SPDEs can be regarded as quantifying the impact of stochastic inputs on system responses or quantities of interest, which constitutes performing uncertainty quantification (UQ) for SPDEs. Recently, the application of neural networks to solve SPDEs has attracted

Stress-constrained and fracture-based topology optimization are both popular methods to enhance fracture resistance in engineering structures and materials. However, their comparative advantages and applicability to various design scenarios remain underexplored. In this study, we revisit both formulations and systematically compare them by analyzing their underlying physics and capabilities. The stress-constrained

In this paper we construct an explicit approximation for the Lagrangian hydrodynamics equations equipped with an arbitrary equation of state. The approximation of the state variable is done with piecewise constant finite elements and the approximation of the mesh motion is done with higher-order continuous finite elements. The method is invariant-domain preserving and locally mass conservative. The

This work investigates the interaction between two competing mechanisms on the fatigue life of 304L stainless steel, martensitic transformation and viscoplastic relaxation, as well as the potential fatigue life enhancement of a single hold time applied prior to cyclic loading. At 300 °C, a tensile load hold time of 15 h applied prior to alternating cyclic loading resulted in an increase in mean fatigue

Pervious concrete (PC) is a porous material widely used in medium-traffic roads due to its ability to facilitate water drainage, reducing stormwater runoff and improving water quality. However, its high porosity and low cement content result in reduced strength, making fatigue performance a critical design consideration. Despite its importance, limited studies have focused on the flexural fatigue behaviour

To boost the fatigue resistance characteristics of TC11 titanium alloy under thermo-mechanical coupling, the effects of plasma zirconizing (Zr), ultrasonic surface rolling process (USRP), and the plasma zirconizing followed by USRP treatment (Zr + USRP) on the high-temperature fatigue behavior of TC11 titanium alloy were investigated. The findings indicate that the plasma zirconizing induced microstructural

Myocardial infarction (MI), characterized by the death of myocytes in the myocardium, leads to high morbidity and mortality rates worldwide. The persistent imbalance of biomechanical stress and strain within the myocardium is a critical factor contributing to adverse growth and remodelling (G&R) following MI, such as wall thinning and chamber dilation. This study investigates the structural and functional

This paper introduces a novel multi-resolution topology optimization method that combines the parametric level set method (PLSM) and quasi-smooth manifold element (QSME) [1]. The QSME has high accuracy and high-order continuity, and its degrees of freedoms have clear physical meanings. By employing the QSME for structural analysis on a coarser analysis mesh and PLSM for updating design variables on

Data-driven digital reconstruction is a power tool for building digital microstructures for such heterogeneous materials as porous media and composites. It uses scanned images as reference and generates digital microstructures through optimisation procedures or computer vision methods. However, data-driven digital reconstruction methods do not apply to polycrystalline microstructures because their

Solving partial differential equations (PDEs) is widely used in scientific and engineering applications. Challenging scenarios include problems with complicated solutions and/or over complex domains. To solve these issues, tailored approximation space and specially designed meshes are introduced in traditional numerical methods, both of which require significant human efforts and computational costs