Material Model Research Articles

Predicting Mechanical Properties of Polymer Materials Using Rate-Dependent Material Models: Finite Element Analysis of Bespoke Upper Limb Orthoses

Three-dimensional printing—especially with fused deposition modeling (FDM)—is widely used in the medical field as it enables customization. FDM is versatile owing to the availability of various materials, but selecting the appropriate material for a certain application can be challenging. Understanding materials’ mechanical behaviors, particularly those of polymeric materials, is vital to determining their suitability for a given application. Physical testing with universal testing machines is the most used method for determining the mechanical behaviors of polymers. This method is resource-intensive and requires cylinders for compression testing and unique dumbbell-shaped specimens for tensile testing. Thus, a specialized fixture must be designed to conduct mechanical testing for the customized orthosis, which is costly and time-consuming. Finite element (FE) analysis using an appropriate material model must be performed to identify the mechanical behaviors of a customized shape (e.g., an orthosis). This study analyzed three material models, namely the Bergström–Boyce (BB), three-network (TN), and three-network viscoplastic (TNV) models, to determine the mechanical behaviors of polymer materials for personalized upper limb orthoses and examined three polymer materials: PLA, ABS, and PETG. The models were first calibrated for each material using experimental data. Once the models were calibrated and found to fit the data appropriately, they were employed to examine the customized orthosis’s mechanical behaviors through FE analysis. This approach is innovative in that it predicts the mechanical characteristics of a personalized orthosis by combining theoretical and experimental investigations.

Investigations on the Johnson-Cook Constitutive and Damage-Fracture Model Parameters of a Q345C Steel

Due to the rapid development of high-speed trains, the service safety of vehicle body materials and structures has become a focal point in transport and impact engineering. Numerical simulations on the collision resistance of vehicle materials and structures are crucial for the safety assessment and optimal structural design of high-speed trains but have not been fully investigated due to the lack of damage model parameters. This study focuses on the Johnson-Cook (J-C) constitutive and damage-fracture models of a typical vehicle material, Q345C steel. A series of mechanical tests are conducted on the Q345C steel, including the quasi-static and dynamic compression/tension tests, quasi-static tension tests at different temperatures, and fracture tests along different stress paths, using the material test system and the split Hopkinson pressure/tension bar. Then, the parameters of the Johnson-Cook constitutive and damage-fracture models are calibrated based on the experimental results. In terms of the damage parameters related to stress paths, a new method of combining experiments and simulations is proposed to obtain the real, local fracture strains of the Q345C steel samples. This method allows the measurements of equivalent plastic strain and stress triaxiality histories under nonlinear stress paths, which are hardly accessible from individual experiments, and facilitates the accurate calibration of stress-path-related damage parameters. In addition, a high-speed plate penetration test is used to validate the J-C parameters, which can be directly implemented in the commercial finite element software Abaqus. The projectile trajectories from the simulation and experiment agree well with each other, demonstrating the reliability of the model parameters for impact scenarios and the efficiency of the experimental procedures utilized for calibration.

Kinetic models of HMX decomposition via chemical reaction neural network

1,3,5,7-Tetranitro-1,3,5,7-tetrazocane (HMX) is commonly used in solid propellants and explosives as energetic materials. The study of its kinetics and decomposition mechanism is of great significance to its application in the aerospace industries. This work investigates the thermal decomposition of HMX based on the combined thermogravimetric (TG) measurements and chemical reaction neural network (CRNN). Two compact kinetic models for HMX are introduced, with one consisting of four substances and a single global reaction (4–1 model) and the other consisting of four substances and four reactions (4–4 model). In the 4–1 model, the calculated activation energy is 328.44 kJ·mol−1, which agrees with the experimental value. As for the 4–4 model, the substances and reactions are assigned based on a skeleton mechanism involving reactions of N-N and C-N bond cleavage and HONO elimination. Moreover, the catalytic effects of TiO2 and Al2O3 on HMX are well simulated using the aforementioned kinetic models. The CRNN models can reproduce the peak temperature with a reduced activation energy, but the initial decomposition temperature is overestimated owing to the complex nature of catalytic impact. This work presents the application of the CRNN model to obtain a decomposition mechanism of HMX, highlighting its efficacy in accurately capturing the thermal decomposition behavior. The potential extension of CRNN to kinetic modeling of other energetic materials is anticipated in future studies.

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT

Objective. In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e. bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models. Approach. DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson’s correlation and Czekanowski’s index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon’s signed rank test and the Kolmogorov-Smirnov two sample test returned p ≤ 0.05 for both tests. Main results. Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with all p ≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with all p < 10−6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric. Significance. Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system’s DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Inter-bead void reduction by crossing printing routes of fused filament fabricated composites

Purpose The use of continuous fiber-reinforced filaments improves the mechanical properties obtained with the fused filament fabrication (FFF) process. Yet, there is a lack of simulation tailored tools to assist in the design for additive manufacturing of continuous fiber composites. To build such models, a precise elastic model is required. As the porosity caused by interbead voids remains an important flaw of the process, this paper aims to build an elastic model integrating this aspect. Design/methodology/approach To study the amount of porosity, which could be a failure initiator, this study proposes a two step periodic homogenization method. The first step concerns the microscopic scale with a unit cell made of fiber and matrix. The second step is at the mesoscopic scale and combines the elastic material of the first step with the interbead voids. The void content has been set as a parameter of the model. The material models predicted with the periodic homogenization were compared with experimental results. Findings The comparison between periodic homogenization results and tensile test results shows a fair agreement between the experimental results and that of the numerical simulation, whatever the fibers’ orientations are. Moreover, a void content reduction has been observed by increasing the crossing angle from one layer to another. An empiric law giving the porosity according to this crossing angle was created. The model and the law can be further used for design evaluation and optimization of continuous fiber-reinforced FFF. Originality/value A new elastic model considering interbead voids and its variation with the crossing angle of the fibers has been built. It can be used in simulation tools to design high performance fused filament fabricated composite parts.

Determining the dynamic properties of spruce wood using the Taylor anvil test

Spruce wood is one of the most widely used materials in the production of lightweight wood-based composites in central Europe. The quality, weight, and geometric parameters of wood chips have a significant impact on the resulting quality of the manufactured composite product. Numerical simulations are necessary for advanced optimization of the quality of composite components and the manufacturing process itself. These simulations require adequate input material data and a model to produce results applicable to the output of industrial practice. In this study, a material model for spruce wood was established using the Taylor anvil test (TAT). This, in contrast to the commonly used Hopkinson compression test, corresponds better to the actual loading process. A new measurement method for shock pulses was developed to implement TAT obtained data for a realistic material model. The method was compared with numerical simulations in Ansys LS DYNA. Based on the results, parameters for the Johnson-Cook equation were determined, which can be applied in the production of disintegrations and, consequently, in the dynamic loading of spruce composite materials.

Study on the Influence of Adjacent Double Deep Foundation Pit Excavation Sequence on Existing Tunnel Deformation Based on HSS Constitutive Model

With the increase in the number of buildings along the subway, the impact of building construction on the adjacent subway tunnels has gradually come to the forefront and become an important problem to be solved in the engineering field. In particular, the excavation and unloading process of deep foundation pits will trigger an additional deformation of the subway structure, which may pose a serious threat to the safety and stability of subway tunnels. This article is based on a foundation pit project in the sub-center of Beijing, focusing on the form of a connected double foundation pit. Using the HSS constitutive model for soil materials, this study simulates the deformation response of adjacent existing subway tunnels under three excavation sequences: sequential excavation, simultaneous excavation, and the comprehensive excavation of the connected double foundation pits. The study shows that, from the point of view of the total displacement of the whole construction process, the impact of a synchronized excavation of double pits on the existing tunnel line is relatively large in the process, and the impact of sequential excavation is relatively small in the construction cycle. The result of the similarity of the excavation sequence is the similarity of the impact trend. The volume of excavated earth determines the value of displacement change for each excavation scenario in each working condition and is also responsible for the convergence of changes. The trend of total tunnel displacement is more consistent with that of vertical displacement, which is dominated by vertical displacement, with horizontal displacement having a relatively small influence. The maximum value of the total tunnel displacement occurs at the side of the tunnel near the excavation area, and the direction is inclined to the excavation area. The application of supporting structures, especially the center plate and the bottom plate, can suppress the vertical deformation of the tunnel bulge.

Enhancing frameworks for utilising Sankey diagrams in modelling the water-energy nexus and circularity

Understanding the connection between water supply and energy consumption in a circular economy is crucial for managing the demands of these resources. Sankey diagrams have the potential to enhance the visualisation of resource flows. However, there is a knowledge gap regarding the effective use of Sankey diagrams to capture the water-energy nexus and circularity of water. This study focused on effectively utilizing Sankey diagrams to model the nexus of water and energy flows and to assess the circularity of water. A comprehensive literature review was conducted on major studies on water material flows and modelling. This was supported by a review of approaches for modelling circularity, which have evolved from the material circularity index. The newly developed framework in this paper models water resource flows at all stages of the water supply chain, embedding the nexus as an interaction and considering resource intensity and material circularity index at each node. A city-level case study in South Africa was then used to apply the recommendations, model circularity, and the water-energy nexus using Sankey diagrams. In terms of circularity, the results indicate that water loss in the study area was very high, accounting for up to 40% of the total water supply and the water recycle rate was still very low, ranging from 3% to 7%. In terms of the nexus, the residential sector was found to have the highest energy intensity for water supply, primarily due to energy demand for water heating. Exploring the use of renewable or solar energy for water heating will be of interest and value. The new approach presented in this study allows for the simultaneous consideration of objectives, enabling a more robust analysis of energy-effective water use and water circularity along the water supply chain.

Coupled Processes at Micro- and Macroscopic Levels for Long-Term Performance Assessment Studies of Nuclear Waste Repositories

Performance assessment of nuclear waste repositories requires state-of-the-art knowledge of radionuclide transport properties. Additionally, the short-term development under thermal pulses and the long-term development of the near field—due to influences such as gas generation—must be evaluated. Key thermal-hydro-mechanical-chemical processes are strongly coupled on different spatial and temporal scales. To understand these coupling mechanisms, numerous material models and numerical codes have been developed. However, the existing constitutive approaches—which have been adapted to describe small-scale laboratory experiments and validated against real-scale field observations—are often unable to capture long-term material behavior with sufficient precision. To build the confidence, a more comprehensive understanding of the system at micro- and macroscopic scales is required. Most observed macroscopic processes result from microscopic changes in the crystal structure and/or crystalline aggregates, as well as changes in material properties under the influence of various factors. To characterize these physical fields in crystals, microscopic investigations, such as visualization, or geophysical methods are introduced to verify the understanding at the microscale. Two cases are demonstrated for the presented concept using microscale information: one deals with the mechanically and thermally driven migration of fluid inclusions in rock salt, the other with dilatancy-controlled gas transport in water-saturated clay material.

Finite element stress analysis and topological optimization of a commercial aircraft seat structure

In recent years, the Finite Element Method (FEM) has emerged as a cornerstone in the field of seating design, particularly within the aircraft industry. Over the past decade, significant advancements in Finite Element (FE) analysis techniques have revolutionized the seat industry, enabling the creation of safer and more cost-effective seat designs. The accuracy of FE analysis plays a pivotal role in this transformation. In the process of constructing a reliable finite element model, the selection and precise manipulation of key parameters are paramount. These crucial parameters encompass element size, time scale, analysis type, and material model. Properly defining and implementing these parameters ensures that the FE model produces accurate results, closely mirroring real-world performance. Verification of Finite Element Analysis (FEA) results is commonly accomplished through experimental methods. Notably, when the parameters are appropriately integrated into the modelling process, FE analysis outcomes closely align with experimental results. This study aims to leverage the power of FEM in performing static stress analysis and topology optimization of aircraft seats using the SOLIDWORKS commercial finite element platform. By simulating loading conditions, this research calculates static stresses and displacements experienced by the aircraft seat. Through a comprehensive topology optimization study, the weight of the airplane seat is remarkably reduced by up to 30%, while still prioritizing passenger safety. The success of this optimization showcases the potential for substantial weight savings in aircraft seat design without compromising safety standards.

Creep-induced subsidence along coastal Louisiana with GPS measurements and finite element modeling

Subsidence rates typically range between 2−7 mm/yr over the past one or two decades, as observed through GPS measurements at continuously operating reference stations along coastal Louisiana. The creep mechanism in Holocene sediments is adopted to quantitatively interpret the observed land subsidence along coastal Louisiana. An extended elasto-viscoplastic model is developed and implemented in ABAQUS. The material model is calibrated and validated based on both creep and constant rate of strain laboratory experiments conducted on Batiscan clays. Finite element models are then constructed to analyze creep-induced subsidence in Holocene sediments at four stations along coastal Louisiana. These models are calibrated with GPS-derived subsidence data to ensure consistency with measured values. Typical material parameters are used for lightly overconsolidated soils in the extended elasto-viscoplastic model. The modeled subsidence exhibits a negative correlation with both the initial overconsolidation ratio and strain-rate exponent. Subsidence accumulates over time at a decreasing rate. Creep-induced subsidence is predicted at four stations based on the calibrated finite element models, revealing an estimated 30.4 cm of subsidence over a span of 50 years (from 2005 to 2055) at station GRIS in Grand Isle. The significance of this study includes various aspects. The extended elasto-viscoplastic model improves the characterization of viscoplastic deformation in overconsolidated soils, typically associated with small strain rates (e.g., ɛ̇<10−8 s−1) observed in field measurements. The role of creep in subsidence in coastal Louisiana is confirmed, through a combination of GPS measurements and finite element modeling. The mechanism-based prediction of creep-induced subsidence can be applied to locations beyond coastal Louisiana.

Computational Mechanics for Turbofan Engine Blade Containment Testing: Fan Case Design and Blade Impact Dynamics by Finite Element Simulations

The harsh environment during airplane take-off and flights with complex operating conditions require a high dynamic and impact resistance capability of airplane engines. The design, development, and performance evaluation of new turbofan engines are generally performed through numerical simulations before a full-scale model or prototype experiment for certification. Simulations of fan blade containment tests can reduce trial–error testing and are currently the most convenient and inexpensive alternative for design; however, certification failure is always a risk if the calibration of material models is not correctly applied. This work presents a three-dimensional computational model of a turbofan for designing new engines that meet the certification requirements under the blade containment test. Two calibrated Johnson–Cook plasticity and damage laws for Ti64 are assessed in a simulation of a turbofan blade containment test, demonstrating the ability of the models to be used in the safe design of aircraft engine components subjected to dynamic impact loads with large deformations and adequate damage tolerance.

Identification of nickel-titanium alloy material model parameters based on experimental research

Identification of nickel-titanium alloy material model parameters based on experimental research

Development of new improved plastic collapse moment equations of pressurized different angled pipe bends under bending moments

In a piping system, pipe bends are more flexible than straight pipes because of their curved geometry, supplemented by higher stress and strain concentration, leading to one of the crucial components in piping industries. Therefore, safe design of pipe bends is essential for smooth running of the piping system, and plastic collapse moment is one of its criteria. This paper utilizes three-dimensional finite element analyses to model empirical solutions for the plastic collapse moment for different angled pipe bends subjected to combined pressure and in-plane closing, in-plane opening, and out-of-plane bending moments. Plastic collapse moments for 30∘ to 180∘ pipe bends are determined for elastic perfectly plastic and strain hardening materials, employing large geometry change option and internal pressure effect. It is observed from results that pressure effect is more prominent in thinner pipe bends of larger bend angle under all bending cases. For in-plane opening and out-of-plane bending moments, collapse moment increases and then decreases with increase in pressure intensity for all sizes of pipe bend. However, for in-plane opening bending moment, collapse moments keep on decreasing for thicker ([Formula: see text] = 11.33) pipe bends. Finally, the study presents new improved plastic collapse moment solutions for different angled pipe bends under bending moment and internal pressure, derived from the finite element results of elastic perfectly plastic and strain hardening material models.

Experimental and numerical analysis of bending performance for a glass-epoxy composite with integrated sheet-shaped shape memory alloy actuator elements

Shape memory alloys (SMA) belong to the group of smart materials and show particularly a promising potential for an active functionalization of lightweight composite structures with respect to enabling smart structures. In this work, various manufacturing concepts for the integration of thin sheet-shaped SMA actuator elements in a thin glass-epoxy composite beam are experimentally and numerically studied with regard to its bending deformation performance realized by thermal induced shape memory effect of the SMA actuator element. For numerical modeling, the shape memory effect of the SMA on structural level, a three-dimensional thermomechanical constitutive material model is applied. In the experiments, the same deformation pattern of the composite beam was observed for all integration concepts investigated, with the degree of deformation showing strong differences both when the shape memory effect is activated and deactivated. The complex material behavior of the SMA actuator under bending deformation is modeled via the finite element method with sufficient accuracy including existing tension and compression loads.

Numerical investigation of bond-slip behaviour between CFRP strips and concrete in shear tests under static and blast loads

The paper is structured into two main sections. In the first part, the focus is on the finite element (FE) analysis of bond slip in a single bond shear test between concrete and carbon fiber reinforced polymer (CFRP) strips under static loads. To model the test set-up, a plastic damage material model and an elastic material model are used for the concrete prism and the unidirectional CFRP strip respectively. Three approaches, including a perfect bond model, a cohesive bond model, and contact algorithms based on recent bond slip models, are employed to simulate the bond interface. The numerical model's validity is confirmed through comparison with experimental results from the literature. The paper predicts the debonding failure mode, the strain evolution along the bond length, and the delamination loads of the CFRP strip. The cohesive bond model exhibits good agreement between numerical and experimental data. In the second part of the paper, the developed FE model is tested under blast loading and compared to the experimental results of the blast tests conducted by the authors. The experimental and numerical findings highlight a significant dynamic enhancement effect on bond-slip properties due to the propagation of the blast wave within the concrete and the high loading rate.

Phase field modeling of hyperelastic material interfaces –Theory, implementation and application to phase transformations

Interface mechanics can significantly govern the evolution of multiple phases on smaller scales, e.g., determining the properties of TWIP- and TRIP-steels, geopolymers or Li-ion batteries. The present contribution is specifically centered around the influence of interface elasticity on mechanically induced phase transformations. A geometrically exact finite element framework is developed for this purpose based on incremental energy minimization. It is set up in three-dimensional space and comprises an Allen-Cahn type phase field formulation based on a Modica-Mortola double-well functional, as well as a Ginzburg-Landau type viscosity formulation. The phase field approximation of the interface deformation gradient is derived by means of homogenization theory. A monolithic solver is employed for the resulting set of non-linear coupled equations. The example of coalescing spheres shows that larger interface energies can amplify and accelerate coalescence. Lower interface energies, in contrast, allow for distinct spreading of the energetically favorable bulk phase. Deformation-dependent interface energies particularly add stress peaks to this process that are localized at the phase transition zone. The relaxation of a stepped interface shape showed that deformation-dependent interface energies favor a plane partition of the bulk phases. Yet, they also delay breakup events compared to simple constant interface energies. This peculiarity can be beneficial for calibration purposes. Strain dependence moreover causes an additional elastic stiffness in the direction of the interface tangent plane and constitutes thus another origin for anisotropy of the overall structure.

Iterative experimental design and identifiability analysis of composite material failure models

The parameter identification of failure models for composite plies can be cumbersome, due to multiple effects as the consequence of brittle fracture. Our work proposes an iterative, nonlinear design of experiments (DoE) approach that finds the most informative experimental data to identify the parameters of the Tsai-Wu, Tsai-Hill, Hoffman, Hashin, max stress and Puck failure models. Depending on the data, the models perform differently, therefore, the parameter identification is validated by the Euclidean distance of the measured points to the closest ones on the nominal surface. The resulting errors provide a base for the ranking of the models, which helps to select the best fitting. Following the validation, the sensitivity of the best model is calculated by partial differentiation, and a theoretical surface is generated. Lastly, an iterative design of the experiments is implemented to select the optimal set of experiments from which the parameters can be identified from the least data by minimizing the fitting error. In this way, the number of experiments required for the identification of a model of a composite material can be significantly reduced. We demonstrate how the proposed method selected the most optimal experiments out of generated data. The results indicate that if the dataset contains enough information, the method is robust and accurate. If the data set lacks the necessary information, novel material tests can be proposed based on the optimal points of the parameters' sensitivity of the generated failure model surface.

Effect of temperature on partial discharges activity and electrical trees propagation in XLPE

AbstractCross‐linked polyethylene (XLPE) cables are commonly used for constructing urban power lines due to their superior properties. Insulation defects can cause partial discharge (PD) and electrical tree, which can negatively impact the insulation performance of the cable and even lead to insulation failure. During operation, cables undergo hot and cold cycles, and the temperature of the insulation layer can affect the PD and electrical tree. An experimental platform with a needle‐plate electrode was developed to investigate this phenomenon. The platform was used to detect PD activity and electrical tree propagation in XLPE under a 50 Hz voltage at various temperatures. The results indicate that an increase in insulation temperature leads to an increase in the number of PDs and a decrease in the inception voltage. Simultaneously, it has been observed that a rise in temperature can facilitate the spread of electrical trees. To explicate the aforementioned PD result, a finite element analysis (FEA) model has been developed. Additionally, a molecular dynamics (MD) model of XLPE material was developed to clarify the phenomenon of electrical tree propagation. This study's findings aid in investigating the impact of temperature on XLPE defects, which is critical for assessing power cable performance.

Real‐Time Neural Materials using Block‐Compressed Features

AbstractNeural materials typically consist of a collection of neural features along with a decoder network. The main challenge in integrating such models in real‐time rendering pipelines lies in the large size required to store their features in GPU memory and the complexity of evaluating the network efficiently. We present a neural material model whose features and decoder are specifically designed to be used in real‐time rendering pipelines. Our framework leverages hardware‐based block compression (BC) texture formats to store the learned features and trains the model to output the material information continuously in space and scale. To achieve this, we organize the features in a block‐based manner and emulate BC6 decompression during training, making it possible to export them as regular BC6 textures. This structure allows us to use high resolution features while maintaining a low memory footprint. Consequently, this enhances our model's overall capability, enabling the use of a lightweight and simple decoder architecture that can be evaluated directly in a shader. Furthermore, since the learned features can be decoded continuously, it allows for random uv sampling and smooth transition between scales without needing any subsequent filtering. As a result, our neural material has a small memory footprint, can be decoded extremely fast adding a minimal computational overhead to the rendering pipeline.