Modeling Of Material Behavior Research Articles

Automated segmentation of large image datasets using artificial intelligence for microstructure characterisation and damage analysis

Many properties of commonly used materials are driven by their microstructure, which can be influenced by the composition and manufacturing processes. To optimise future materials, understanding the microstructure is critically important. Here, we present two novel approaches based on artificial intelligence that allow the segmentation of the phases of a microstructure for which simple numerical approaches, such as thresholding, are not applicable: One is based on the nnU-Net neural network, and the other on generative adversarial networks (GAN).Using scanning electron microscopy images collected from large areas (∼1 mm2) of dual-phase steels as a case study, we demonstrate how both methods effectively segment intricate microstructural details, including martensite, ferrite, and damage sites, for subsequent analysis.Either method shows substantial generalizability across a range of image sizes and conditions, including heat-treated microstructures with different phase configurations. The nnU-Net excels in mapping large image areas. Conversely, the GAN-based method performs reliably on smaller images, providing greater step-by-step control and flexibility over the segmentation process.This study highlights the benefits of segmented microstructural data for various purposes, such as calculating phase fractions, modelling material behaviour through finite element simulation, and conducting geometrical analyses of damage sites and the local properties of their surrounding microstructure.

Insight into single-helix intelligent shape memory polymer cables: modeling and optimization under finite sliding contact

This pioneering study focuses on the finite element analysis (FEA) of thermomechanical properties of shape memory polymer (SMP) wire ropes and their components under both small- and finite-sliding contact deformation. To validate the FEA, we need to validate both geometric modeling and non-linear material behavior. Owing to intricate geometry, as well as excessive wire interactions in the structure, this part is studied by simulating a 1 × 37 steel wire rope and then comparing it with existing experimental data. To evaluate the response of non-linear material behavior, we employ the available numerical results to model the thermomechanical property of an SMP rectangular bar under a uniaxial test and then verify both constrained and unconstrained recovery behavior. After rigorous validation, two configurations of 1 × 7 and 1 × 27 SMP cables are modeled based on the thermo-visco-hyperelastic constitutive framework for acrylate polymer systems. Upon exerting an axially tensile load on these 1 × 7 and 1 × 27 SMP wire ropes, the response of force and shape recovery, as well as the normal and shear stress distributions, are measured under constrained and unconstrained conditions. For a deeper physical understanding, the influences of different temperature rates (5 and 1 °C min−1), inter-wire sliding frictional coefficient (0.1–0.6), and multiple-shape programming on the stress-strain-temperature relations of these SMP cables are also investigated. Furthermore, based on optimizing two cable factors of diameter and helix angle, and using the design of experiments method, the specific energy of a 1 × 6 SMP cable is maximized. Under different thermomechanical loadings, this study tries to cast light on the remarkable features and possible potential applications of these newly developed SMP actuators which may foster unparalleled advancements in various industries.

Nonlinear electro-elastic finite element analysis with neural network constitutive models

In the present work, the applicability of physics-augmented neural network (PANN) constitutive models for complex electro-elastic finite element analysis is demonstrated. For the investigations, PANN models for electro-elastic material behavior at finite deformations are calibrated to different synthetically generated datasets describing the constitutive response of dielectric elastomers. These include an analytical isotropic potential, a homogenised rank-one laminate, and a homogenised metamaterial with a spherical inclusion. Subsequently, boundary value problems inspired by engineering applications of composite electro-elastic materials are considered. Scenarios with large electrically induced deformations and instabilities are particularly challenging and thus necessitate extensive investigations of the PANN constitutive models in the context of finite element analyses. First of all, an excellent prediction quality of the model is required for very general load cases occurring in the simulation. Furthermore, simulation of large deformations and instabilities poses challenges on the stability of the numerical solver, which is closely related to the constitutive model. In all cases studied, the PANN models yield excellent prediction qualities and a stable numerical behavior even in highly nonlinear scenarios. This can be traced back to the PANN models excellent performance in learning both the first and second derivatives of the ground truth electro-elastic potentials, even though it is only calibrated on the first derivatives. Overall, this work demonstrates the applicability of PANN constitutive models for the efficient and robust simulation of engineering applications of composite electro-elastic materials.

An efficient method for multiscale modelling of the mechanical properties of additively manufactured parts with site-specific microstructures

The ability to modulate microstructures at different locations within a part (i.e., site-specific microstructures) can lead to tailored properties and enhanced performance. However, it remains challenging to efficiently model the mechanical response of such materials due to the need for extensive multiscale analysis. To address this issue, we demonstrate through microstructure-based finite element simulations, that the mechanical properties of a randomly distributed two-phase microstructure are primarily dependent on the phase fraction. Therefore, by establishing a mathematical relationship between the phase fraction and mechanical properties, the local material properties can be efficiently calculated from the local microstructure. Later, these site-specific properties were incorporated into a finite element structure to predict the global mechanical properties of the sample part. To validate the effectiveness of the proposed method, low alloy steel with site-specific microstructures was fabricated using binder jet additive manufacturing by depositing varying concentrations of carbon binder at different locations inside the part. We observed a strong agreement between the experimental and simulation stress-strain responses of the steel samples. This method can potentially pave the way for the development of a non-destructive qualification method for additively manufactured parts, as well as provide an efficient approach to multiscale modeling of material behavior, which may help accelerate the design and innovation of novel material systems.

Assessment of the Influence of Protective Polymer Coating on Panda Fiber Performance Based on the Results of Multivariant Numerical Simulation.

This article considers the deformation behavior of Panda optical fiber using different models of material behavior for the tasks of predicting residual stresses after drawing when cooling from 2000 °C to room temperature (23 °C) and indenting the fiber into an aluminum half-space at different parameters. These studies were conducted for single- and double-layer protective coatings (PCs), at different values of external load and thickness of single-layer PC. This paper determined the fields of residual stresses in the fiber formed during the drawing process. They are taken into account in modeling the fiber performance in the further process of this research. This article investigated two variants of PC behavior. The influence of behavior models and the number of covering layers on the deformation of the "fiber-half-space" system was analyzed. This paper establishes qualitative and quantitative regularities of the influence of the external load magnitude and relaxation properties of PCs on the deformation and optical characteristics of Panda optical fiber.

Calibrating DC01 Material Properties for Finite Element Analysis with Abaqus and Isight

Abstract This article explores the process of calibrating the properties of DC01 materials for finite element analysis using ABAQUS and Isight. Precise calibration of yield strength and tensile strength is crucial for accurately modeling material behavior under various loading conditions. The article details the sample preparation process, deformation measurements, and tensile tests to obtain experimental data. These data are then used to calibrate the DC01 material model in ABAQUS with the assistance of Isight, ensuring that the simulations accurately reflect real-world behavior. The results indicate the success of the calibration, facilitating the design and testing of products in a predictive virtual environment. Precise calibration is essential for predicting material behavior in real-world conditions and minimizing the risk of implementation failures.

Phase equilibrium in canonical cubic structure I (sI) and II (sII) and hexagonal (sH) gas hydrate solid solutions

Canonical clathrate or gas hydrates of structure I, II and H are the main interest of engineers and scientists in a variety of technological fields including flow assurance in hydrocarbon pipelines and processing facilities, natural gas recovery from the earth's hydrates, CO2 capture and storage, methane and H2 storage etc. Clathrate hydrate systems exhibit a variety of phase equilibria and the knowledge of the relevant phase diagrams is necessary for the design of relevant processes and facilities. In this work, the various types of canonical hydrate phase equilibria of interest, models of material behaviour for phases encountered in gas hydrate systems and computational methods of phase equilibria are discussed. The term model refers to thermodynamic models for the calculation of fugacities or activity coefficients. The term method refers to hydrate equilibrium computational procedures based on combinations of the hydrate statistical thermodynamics van der Waals and Platteuw (vPW) or its improved versions with various fluid phase thermodynamic models such as equations of state and activity coefficient models. Our discussion and presentation follows a deductive approach to distinguish it from other works that are a collection of all computational methods to calculate hydrate equilibria and which often use the terms method and model interchangeably. Original references are cited as well as the current status and recent advances and challenges are considered. The advent of machine learning techniques for gas hydrate and thermodynamic calculations is also discussed.

Lateral ring compression test applied to a small caliber steel jacket: Identification of a constitutive model

The evolution of threats and scenarios requires continuous performance improvements of ballistic protections for armed forces. From a modeling point of view, it is necessary to use sufficiently precise material behavior models to accurately describe the phenomena observed during the impact of a projectile on a protective equipment. In this context, the goal of this paper is to characterize the behavior of a small caliber steel jacket by combining experimental and numerical approaches. The experimental method is based on the lateral compression of ring specimens directly machined from the thin and small ammunition. Various speeds and temperatures are considered in a quasi-static regime in order to reveal the strain rate and temperature dependencies of the tested material. The Finite Element Updating Method (FEMU) is used. Experimental results are coupled with an inverse optimization method and a finite element numerical model in order to determine the parameters of a constitutive model representative of the jacket material. Predictions of the present model are verified against experimental results and a parametric study as well as a discussion on the identified material parameters are proposed. The results indicate that the strain hardening parameter can be neglected and the behavior of the thin steel jacket can be described by a modeling without strain hardening sensitivity.

Anisotropic modeling of material behavior for additively manufactured parts made by material extrusion

Anisotropic modeling of material behavior for additively manufactured parts made by material extrusion

A data-based derivation of the internal stress in the discrete-continuum transition regime of dislocation based plasticity

Effectively homogenizing microstructure heterogeneity within the coarse-graining volume is a long-lasting challenge in crystal plasticity theories. In this paper, we propose a data-based homogenization method that utilizes discrete dislocation dynamic simulations to derive the nearfield correction stress (back stress) for continuum models. This stress accounts for the effective stress field induced by microstructure heterogeneity under the length scale of a coarse-graining volume, providing a physically based homogenization approach. To bridge the gap between discrete and continuous regimes, we introduce two versions of the nearfield correction stress, as well as a criterion based on microstructure and numerical parameters to determine the discrete and continuous transition. Moreover, by analyzing the mathematical connections with the work-conjugated gradient plasticity theory, we further provide a physical explanation for the observed material length scale in the thermodynamically consistent back stress term. This work presents a novel methodology for effectively addressing microstructure heterogeneity and advancing the understanding and modeling of material behavior bridging different length scales.

BARIK: an extended Hoek–Brown-based anisotropic constitutive model for fractured crystalline rock

Abstract. The disposal of heat-generating radioactive waste in deep geologic formations is a global concern. Numerical methods play a key role in understanding and assessing the disposal scenarios of radioactive waste in deep geological repositories. However, the complexities of the thermal, hydrological, mechanical, chemical, and biological processes associated with the disposal of radioactive waste in porous and fractured materials constitute significant challenges. One of the most challenging issues in this field is the complex material behavior of fractured crystalline rock. The presence of fractures makes the rock anisotropic, nonlinear, and dependent on loading paths. Additionally, the Biot coefficient cannot be considered constant throughout the critical and subcritical fracture development regions. These factors make the development of an accurate constitutive model for fractured crystalline hard rock a critical component of any deep geological disposal project. Furthermore, to demonstrate the integrity of the containment-providing rock zone in crystalline host rock, the qualitative integrity criteria must be quantified so that numerical simulation can be performed with concrete numerical values. Part of this assessment for a crystalline host rock is a dilatancy criterion, which is currently based on the Hoek–Brown constitutive model. BARIK is the German acronym for the research project on which this paper is based. This contribution provides an overview of the development and verification of the BARIK constitutive model, an extended Hoek–Brown model for fractured crystalline hard rock that takes into account up to three fracture systems. The model enables the consideration of the matrix and joint behavior of the rock separately, with each component having unique strength characteristics and failure criteria. These criteria are formulated such that suitable consideration of the strength-reducing properties of the respective fracture systems during barrier integrity verification is possible. The BARIK model has been implemented into two computer codes, FLAC3D and MFront for OpenGeoSys, allowing for the identification and evaluation of any inaccuracies that may arise from the use of different codes. The model enables isotropic–elastic, orthotropic–elastic, isotropic–elasto-plastic, and orthotropic–elasto-plastic calculations of the matrix, making it a valuable tool for the site selection process and for the construction and long-term safety of underground repositories. Furthermore, this poster presentation will show how the constitutive model was evaluated in relation to the dilatancy criterion and how the BARIK constitutive model's suitability for conducting an integrity assessment was validated. In conclusion, the development of BARIK is a significant step forward in the understanding and modeling of the complex material behavior of fractured crystalline hard rock. This contribution will provide insights into the development and verification of this model for the safe disposal of radioactive waste.

A new texture descriptor for data-driven constitutive modeling of anisotropic plasticity

Constitutive modeling of anisotropic plastic material behavior traditionally follows a deductive scheme, relying on empirical observations that are cast into analytic equations, the so-called phenomenological yield functions. Recently, data-driven constitutive modeling has emerged as an alternative to phenomenological models as it offers a more general way to describe the material behavior with no or fewer assumptions. In data-driven constitutive modeling, methods of statistical learning are applied to infer the yield function directly from a data set generated by experiments or numerical simulations. Currently these data sets solely consist of stresses and strains, considering the microstructure only implicitly. Similar to the phenomenological approach, this limits the generality of the inferred material model, as it is only valid for the specific material employed in the virtual or physical experiments. In this work, we present a new generic descriptor for crystallographic texture that allows an explicit consideration of the microstructure in data-driven constitutive modeling. This descriptor compromises between generality and complexity and is based on an approximately equidistant discretization of the orientation space. We prove its ability to capture the structure–property relationships between a variety of cubic–orthorhombic textures and their anisotropic plastic behavior expressed by the yield function Yld2004-18p. Three different machine learning models trained with the descriptor can predict yield loci as well as r-values of unseen microstructures with sufficient accuracy. The descriptor allows an explicit consideration of crystallographic texture, providing a pathway to microstructure-sensitive data-driven constitutive modeling.

The Study Influence Analysis of the Mathematical Model Choice for Describing Polymer Behavior.

The article considered the three types of description of the material behavior model: elastic, elastic-plastic, and viscoelastic. The problem is considered in the framework of deformable solid mechanics. The paper considers the possibility of describing modern polymeric and composite materials used as antifriction sliding layers in the viscoelasticity framework. A numerical procedure for finding the coefficients to describe the viscoelastic material behavior using the Prony model has been implemented. Numerical results and experimental data are compared. The model problem of spherical indenter penetration into polymer half-space is realized. The influence of the system discretization on the numerical solution is analyzed. The influence of the polymer behavior description in static and dynamic problem formulations is analyzed.

The effect analysis of the finite element approximation order on the protective polymer layer contact deformation

Problems implementation using the finite element method (FEM) is primarily associated with the proper selection of approximation order of the shape functions, material behavior models, the coupling nature analysis and the implementation techniques choice. The choice of numerical solution parameters affects the computational procedures. The paper solves problem of the FEM parameters selection and its realization methods in order to achieve a reasonable balance between the counting time and the solution quality. Simplex elements have shape functions with linear dependences on the coordinates. The FEM implementation with the use of simplex elements has proven itself during the last decades. However, one can note the description inaccuracy of curvilinear boundaries of research objects, which can introduce additional inaccuracies in the problem numerical solution. Second-order elements will allow describing curvilinear boundaries, but require a large expenditure of computational power especially for nonlinear mechanics problems. The development of numerical application software packages allows us to evaluate the influence of the FEM approximation degree on the problem solution with the use of grid methods and computer resources at the present time. The paper found that an increase in the numerical solution error is observed at the point of initial steel - polymer contact. The study considers the elements of order 1 and 2 to analyze the influence of the FEM approximation order on the problem numerical solution. The study is carried out within the framework of the classical Hertz problem. In addition the paper investigate obtained solutions for modeling different characters of contact surface coupling for the problem of contact between a spherical die and a steel half-space through a protective polymer coating 4 mm to 12 mm thick. The study reveal that the elements order has the least influence on the problem solution at ideal contact and the greatest one at frictional contact.

Three-dimensional simulation of granular materials by discrete element method (DEM) by considering the fracture effect of particles

Coarse-grained materials, such as sand and gravel, exhibit a significant dependence on particle failure rate, which greatly influences their engineering behavior. This research focuses on the three-dimensional modeling of grain material behavior using the discrete element method (DEM) with PFC3D software and FISH programming language. The specific objective is to model the particle breakage phenomenon and its impact on resistance behavior and deformation. To accurately represent the non-spherical shape of the particles, an interconnected sphere approach was employed. The modeling of grain failure was achieved by establishing a failure criterion that considers two critical conditions: the heterogeneity of contact forces and stress within the particle. The proposed model and criteria were validated through comparison with triaxial experimental results obtained from the Purulia dam gravel. The results demonstrate that the developed model successfully captures the essential aspects of particle failure and its influence on the behavior of the granular environment. The simulations accurately represent the resistance behavior and deformation characteristics observed in the triaxial experiments. This validates the effectiveness of the proposed model in simulating the significant effects of particle failure on the behavior of coarse-grained materials. The findings of this study contribute to a deeper understanding of the complex behavior of coarse-grained materials, particularly in terms of their response to particle failure. The developed DEM model, incorporating the particle breakage phenomenon, provides a valuable tool for accurately predicting and analyzing the behavior of granular materials in various engineering applications.

A microscale constitutive model for thin stainless steel sheets considering size effect

This research is focused on the modeling of the deformation behavior of thin austenitic stainless steel sheets to consider size effect in microscale. First, the material with two different thicknesses is heat treated to obtain different grain sizes, and then they are characterized by the uniaxial tensile tests. The experimental results show that flow stress decreases with the reduction of the sheet thickness and the increase of the grain size. The decline of the flow stress curve is associated with the decrease of the strength coefficient and increase of the hardening exponent as the plastic deformation is scaled down to the microscale. To better model the behavior of the material in the microscale, a new constitutive model is proposed based on the Swift equation to take into account the geometry and grain size effect. This model is also defined in the finite element model of the uniaxial tensile test. It is found that the flow stress curve predicted by the proposed constitutive model shifts down by the decrease of the number of grains across the thickness, which are consistent with the experimental results. In addition, the finite element model with the proposed constitutive model predicts accurately the deformation load in the uniaxial tensile tests. It can be concluded that the proposed constitutive model can provide a good description of the flow stress by considering the interactive effect of specimen and grain sizes and can be used in the modeling of material behavior in microforming processes.

Constitutive Modeling with Single and Dual Internal Variables.

Phenomenological constitutive models with internal variables have been applied for a wide range of material behavior. The developed models can be classified as related to the single internal variable formalism based on the thermodynamic approach by Coleman and Gurtin. The extension of this theory to so-called dual internal variables opens up new avenues for the constitutive modeling of macroscopic material behavior. This paper reveals the distinction between constitutive modeling with single and dual internal variables using examples of heat conduction in rigid solids, linear thermoelasticity, and viscous fluids. A thermodynamically consistent framework for treating internal variables with as little a priori knowledge as possible is presented. This framework is based on the exploitation of the Clausius-Duhem inequality. Since the considered internal variables are "observable but not controllable", only the Onsagerian procedure with the use of the extra entropy flux is appropriate for the derivation of evolution equations for internal variables. The key distinctions between single and dual internal variables are that the evolution equations are parabolic in the case of a single internal variable and hyperbolic if dual internal variables are employed.

Model-free damage prediction of brittle materials based on particle swarm optimization coupled with a probabilistic fission method

This study aims to develop a model-free damage prediction algorithm to predict directly local mesoscopic elasticity modulus and damage distribution of brittle materials based on only the monitored global structural response such as force–displacement curve, which can overcome complex theoretical modeling material behavior. The algorithm is established based on the modification of particle swarm optimization algorithm by establishing a probabilistic fission method, which can consider the physical mechanism that damage is correlatedpositivelywiththe stress level in the optimization process. A representative numerical example of a Brazilian disk test is implemented to verify the algorithm. The damage prediction result is compared with the result obtained from the traditional particle swarm optimization algorithm and the corresponding experimental result. As can be seen from the comparison results, the ability and effectiveness of the algorithm are supported. Furthermore, the effect of different divisions of representativevolumeelementsin the algorithm is analyzed to support the conclusion that fine division of representativevolumeelementscan obtain refined prediction results, but it can significantly increase the prediction error and computation time. The recommended size of representativevolumeelementis about 2 mm for the numerical case in this study.

Probabilistic impact fragility analysis of bridges under Barge collision and local scour

Vessel collision is a common cause of structural failure to bridges crossing navigable waterways. Although numerous efforts focus on the safety evaluation of bridge structures under vessel impact, very few jointly consider a more threatening situation that involves a scoured bridge colliding with a vessel (e.g., a barge). In this work, an impact fragility analysis (IFA) process is proposed to understand a bridge's failure probability under the combined hazards. To achieve high-fidelity modeling of material behavior during the collision process, scaled pier-foundation models subjected to pendulum impacts are experimentally studied. Nonlinear material models and an explicit dynamic simulation procedure are verified, which are further adopted to develop a high-resolution finite-element model for a full-scale three-span bridge. The resulting impact-fragility models conditional upon impact velocities at different scour depths reveal essential insights into the failure modes of the bridge. The findings include that: (1) scour has a minor effect on the probability of slight and moderate damage at various impact velocities; (2) at a high impact velocity (when higher than an impact fragility velocity threshold), scour can significantly increase the probability of major damage and collapse; (3) barge-tonnage has a significant influence on the threshold value reflecting the significant scour effects.

Modeling of welding residual stress in a dissimilar metal butt-welded joint between P92 ferritic steel and SUS304 austenitic stainless steel

In this study, a butt-welded joint between P92 ferritic steel and SUS304 austenitic stainless steel was fabricated with a nickel-based filler material. Based on Sysweld software, three-dimensional thermal-metallurgical-mechanical coupled finite element analyses were performed to investigate the hardness and welding residual stress in the welded joint. In the material behavior model, various factors influencing the formation and distribution of hardness and welding residual stress were carefully considered, including the austenitic transformation, martensitic transformation, and the tempering of martensite in P92 steel; the isotropic strain hardening, annealing effect, and melting effect of all materials; and the differential thermal expansion between dissimilar metals. The neutron diffraction method and hole-drilling strain gauge method were applied to measure the profiles of residual stress of the welded joint, respectively. Hardness mapping was performed on a weld cross-section specimen. The predicted results of welding residual stress and hardness are in good agreement with the measurements, respectively. The peak residual stresses in longitudinal and transverse directions are above 600 MPa in P92 steel. There are high tensile residual stress and significant cold work near the weld root in SUS304 stainless steel. The solid-state phase transformation induces compressive longitudinal residual stress in the heat-affected zone, high tensile transverse residual stress near the weld toe in P92 steel, and a significant stress gradient. The tempering effect can reduce the hardness and tensile residual stress in the heat-affected zone of P92 steel. The formation mechanism of welding-induced residual stress was illustrated based on the Satoh test. The effects of peak temperature, internal restraint, and differential thermal expansion are found to be decisive for the formation of residual stress. Large tensile residual stress can be generated with internal restraints, which promote the stress increase and lead to material yielding. A restraint factor was proposed for the quantitative assessment of stress evolution.