Mechanical Behavior Of Materials Research Articles

Multiscale Modeling of Physical Properties of Nanoporous Frameworks: Predicting Mechanical, Thermal, and Adsorption Behavior.

ConspectusNanoporous frameworks are a large and diverse family of supramolecular materials, whose chemical building units (organic, inorganic, or both) are assembled into a 3D architecture with well-defined connectivity and topology, featuring intrinsic porosity. These materials play a key role in various industrial processes and applications, such as energy production and conversion, fluid separation, gas storage, water harvesting, and many more. The performance and suitability of nanoporous materials for each specific application are directly related to both their physical and chemical properties, and their determination is crucial for process engineering and optimization of performances. In this Account, we focus on some recent developments in the multiscale modeling of physical properties of nanoporous frameworks, highlighting the latest advances in three specific areas: mechanical properties, thermal properties, and adsorption.In the study of the mechanical behavior of nanoporous materials, the past few years have seen a rapid acceleration of research. For example, computational resources have been pooled to create a public large-scale database of elastic constants as part of the Materials Project initiative to accelerate innovation in materials research: those can serve as a basis for data-based discovery of materials with targeted properties, as well as the training of machine learning predictor models.The large-scale prediction of thermal behavior, in comparison, is not yet routinely performed at such a large scale. Tentative databases have been assembled at the DFT level on specific families of materials, such as zeolites, but prediction at larger scale currently requires the use of transferable classical force fields, whose accuracy can be limited.Finally, adsorption is naturally one of the most studied physical properties of nanoporous frameworks, as fluid separation or storage is often the primary target for these materials. We highlight the recent achievements and open challenges for adsorption prediction at a large scale, focusing in particular on the accuracy of computational models and the reliability of comparisons with experimental data available. We detail some recent methodological improvements in the prediction of adsorption-related properties: in particular, we describe the recent research efforts to go beyond the study of thermodynamic quantities (uptake, adsorption enthalpy, and thermodynamic selectivity) and predict transport properties using data-based methods and high-throughput computational schemes. Finally, we stress the importance of data-based methods of addressing all sources of uncertainty.The Account concludes with some perspectives about the latest developments and open questions in data-based approaches and the integration of computational and experimental data together in the materials discovery loop.

Report on “The 60<sup>th</sup> Workshop on X-Ray Studies on Mechanical Behaviour of Materials ―Research and Development and Technical Issues in Strength and Non-Destructive Evaluation for an Electric Society―”

Report on “The 60<sup>th</sup> Workshop on X-Ray Studies on Mechanical Behaviour of Materials ―Research and Development and Technical Issues in Strength and Non-Destructive Evaluation for an Electric Society―”

Triaxial Test and Discrete Element Numerical Simulation of Geogrid-Reinforced Clay Soil

Indoor triaxial tests on geogrid-reinforced clay elucidate the macroscopic changes in soil strength indices post-reinforcement, yet the underlying mechanisms of strength enhancement require further investigation. By conducting indoor triaxial tests and establishing a corresponding discrete element numerical model, we can delve into the fine-scale mechanisms of geogrid-reinforced soil. This includes analyzing changes in fine-scale parameters such as porosity, the coordination number, and contact stress between soil particles. The findings suggest that an increase in the number of geogrid reinforcement layers leads to a more pronounced improvement in peak strength and cohesion, albeit with minimal impact on the internal friction angle of the specimens. Furthermore, analysis of the triaxial test curves of reinforced soils indicates that the stress–strain relationship adheres to the Duncan–Chang model. Parameters derived from this model have been validated against experimental data, confirming their accuracy. The discrete element model was used to analyze the variations in fine-scale parameters such as porosity and coordination number. It revealed that reinforcement reduces the fluctuation amplitude of porosity and significantly increases the number of particle contacts, resulting in a denser soil structure. Further analysis of the change in contact stress between particles in the discrete element model revealed that the contact force between particles increased significantly after reinforcement and that the reinforcement played a role in restraining the soil particles and dispersing the reinforcement stress, which explains the increase in the strength of the mesh-reinforced clays from another perspective. This further elucidates the strength enhancement mechanism in geogrid-reinforced clay, offering a new perspective on the mechanical behavior and strength development of such materials.

Seeking the most informative design of test specimens for learning constitutive models

Accurate calibration of constitutive models is vital for predicting the mechanical behavior of engineering materials under various loading conditions. Traditionally, the calibration process involves a series of experiments on specimens with simple geometries to capture the complexities in the constitutive models. Each single test conveys a small amount of information that a well-trained human brain can handle, resulting in a large number of experiments needed for a complete calibration. Therefore, traditional calibration approaches are usually costly and time-consuming. With recent advancements in computational techniques, there is an emerging opportunity to leverage geometrically complex specimens in experiments to obtain a larger amount of information for computers to learn and calibrate the model. Despite some initial success, the most important question remains unsettled: How much information does a mechanical test convey? In this work, we answer this question by incorporating information entropy as a quantitative measure in the design of mechanical test specimens. We demonstrate the viability of the proposed approach by comparing the performance of selected test specimens for learning the plasticity model of sheet metal, e.g., the Hill48 anisotropic elastic-plastic model in this case. An optimal entropy criterion is proposed for selecting the appropriate heterogeneous test specimen for inverse calibration, depending on the cardinality of the stress state space considered in the model. Finally, Bayesian optimization is applied to uniaxial and biaxial tension specimens, using the stress state entropy as an objective function, to investigate the general principles of designing specimens with maximum information for learning constitutive models.

Evaluating flexure properties, hardness, roughness and microleakage of high-strength injectable dental composite: an in vitro study

BackgroundRecently, a new generation of high-strength flowable dental composites has been introduced by manufacturers. The manufacturers claim that these materials have enhanced mechanical and physical properties and are suitable for use in a wide range of direct anterior and posterior restorations, even in high-stress bearing areas.AimThe objective of this study was to assess certain physical and mechanical properties of these recently introduced high-strength flowable composites in comparison to conventional multipurpose dental composites.MethodsFour types of high-strength flowable composites (Genial Universal FLO, Gaenial Universal Injectable, Beautifil Injectable, and Beautifil Flow Plus) were tested in experimental groups, while a nanohybrid conventional composite (Filtek Z350 XT) was used as the control. For flexure properties, ten rectangular samples (2 × 2 × 25 mm) were prepared from each composite material and subjected to 5000 cycles of thermocycling. Samples were then subjected to flexural strength testing using the universal testing machine. Another twenty disc-shaped specimens of dimensions (5 mm diameter × 2 mm thickness) were fabricated from each composite material for surface roughness (Ra) (n = 10) and hardness (VHN) test (n = 10). All samples underwent 5000 cycles of thermocycling before testing. Additionally, microleakage testing was conducted on 60 standardized class V cavities prepared on molar teeth and divided randomly into five groups (n = 12). Cavities were then filled with composite according to the manufacturer’s instructions and subjected to thermocycling for 1000 cycles before testing using methylene blue solution and a stereomicroscope.ResultsAll tested materials were comparable to the control group in terms of flexural strength and surface roughness (p > 0.05), with Gaenial Universal FLO exhibiting significantly higher flexural strength compared to the other flowable composite materials tested. However, all tested materials demonstrated significantly lower elastic modulus and surface hardness than the control group (p < 0.05). The control group exhibited higher microleakage scores, while the lowest scores were observed in the Gaenial Universal FLO material (p < 0.05)ConclusionThe physical and mechanical behaviors of the different high-strength flowable composites investigated in this study varied. Some of these materials may serve as suitable alternatives to conventional composites in specific applications, emphasizing the importance of dentists being familiar with material properties before making material selections.

Mechanical Behavior and Thermal Stability of Nanocrystalline Metallic Materials with Thick Grain Boundaries

Mechanical Behavior and Thermal Stability of Nanocrystalline Metallic Materials with Thick Grain Boundaries

A micromechanical scheme with nonlinear concentration functions by physics-guided neural network

The mechanical behavior of heterogeneous materials has been reported to be significantly influenced by the nonlinear properties of both the matrix and interface. However, the micromechanical homogenization methods for predicting the effective properties are challenged in nonlinear problems due to the difficulties in solving the analytical form of the concentration tensors. In this study, we develop a nonlinear micromechanical scheme for heterogeneous materials with complex interfacial behaviors, where the key component, namely nonlinear concentration functions, is determined by the devised physics-guided neural network. In particular, the nonlinear Mori–Tanaka method (NMT) implemented within this new micromechanical scheme yields accurate solutions to axisymmetric nonlinear homogenization problems considering the effects of finite deformation, loading conditions, volume fraction, etc. Furthermore, the NMT is equivalent to the linear Mori–Tanaka method in the condition of the small deformation. Notably, this neural-network-based micromechanical scheme shows good generalization for different types of nonlinear interfaces, while the corresponding approach for generating training data via the finite element method (FEM) is cost-effective. This theoretical framework introduces a novel approach to nonlinear physical modeling, namely, not by the direct regression from the dataset but by deeply embedding neural networks in physical laws.

Atomistic-level analysis of nanoindentation-induced plasticity in arc-melted NiFeCrCo alloys: The role of stacking faults

Concentrated solid solution alloys (CSAs) have attracted attention for their promising properties; however, current manufacturing methods face challenges in complexity, high costs, and limited scalability, raising concerns about industrial viability. The prevalent technique, arc melting, yields high-purity samples with complex shapes. In this study, we explore nanoindentation tests at room temperature where arc-melted samples exhibit larger grain sizes, diminishing the effects of grain boundaries on the results. Motivated by these findings, our investigation focuses on the atomistic-level exploration of plasticity mechanisms, specifically dislocation nucleation and propagation during nanoindentation tests. The intricate chemistry of NiFeCrCo CSA influences pile-ups and slip traces, aiming to elucidate plastic deformation by considering both pristine and pre-existing stacking fault tetrahedra. Our analysis scrutinizes dynamic deformation processes, defect nucleation, and evolution, complemented by stress–strain and dislocation densities–strain curves illustrating the hardening mechanism of defective materials. Additionally, we examine surface morphology and plastic deformation through atomic shear strain and displacement mappings. This integrated approach provides insights into the complex interplay between the material structure and mechanical behavior, paving the way for an enhanced understanding and potential advancements in CSA applications.

Concurrent delamination propagation and deformation localization in semiconductor devices

In semiconductor devices, metals and polymers are often integrated as electrical conductors and insulators. Fabrication and operation of the devices cause stress in such an integrated structure. The stress can delaminate the metals and polymers, as well as deform them plastically. Here we show that the delamination can localize the deformation in the metals, which form necks to rupture the metals and sever electrical conduction. We simulate the coevolution of delamination propagation and deformation localization. The metals and polymers are modeled as elastic-plastic materials, and their adhesion is represented by a cohesive zone model. The simulation highlights that extensive delamination is a prerequisite for the metals to form necks, and that necking causes delamination to propagate further. Also highlighted are the impact of corners in the structure. Preexisting defects make the structure particularly vulnerable to concurrent delamination and necking. It is hoped that this study will draw renewed attention to the mechanical behavior of materials in the development of the semiconductor industry.

Constitutive model of viscoelastic dynamic damage for the material of gas obturator in modular-charge howitzer

In order to investigate the mechanical response behavior of the gas obturator of the breech mechanism, made of polychloroprene rubber (PCR), uniaxial compression experiments were carried out by using a universal testing machine and a split Hopkinson pressure bar (SHPB), obtaining stress-strain responses at different temperatures and strain rates. The results revealed that, in comparison to other polymers, the gas obturator material exhibited inconspicuous strain softening and hardening effects; meanwhile, the mechanical response was more affected by the strain rate than by temperature. Subsequently, a succinct viscoelastic damage constitutive model was developed based on the ZWT model, including ten undetermined parameters, formulated with incorporating three parallel components to capture the viscoelastic response at high strain rate and further enhanced by integrating a three-parameter Weibull function to describe the damage. Compared to the ZWT model, the modified model could effectively describe the mechanical response behavior of the gas obturator material at high strain rates. This research laid a theoretical foundation for further investigation into the influence of chamber sealing issues on artillery firing.

Environmental aging effects on mechanical behavior of an hemp based biocomposite material for structural strengthening

Biocomposites are innovative materials usually made of natural fibers embedded in a natural matrix. The mechanical behavior of such materials when exposed to the environmental agents (i.e. UV radiations, high/low temperature, variable humidity conditions) is a crucial issue. This paper is aimed to investigate an hemp based biocomposite for structural strengthening, addressing a gap in the existing literature concerning the mechanical characterization of the composite constituents (i.e. hemp ropes and natural matrices) under accelerated weathering conditions. In particular, this research involves the mechanical behavior assessment of hemp ropes, four distinct types of matrices (i.e. two organic binder based matrices and two mortar based matrices) and the hemp/matrix interface. Tensile tests, three point bending tests, uniaxial compression tests and pull-out tests are carried out to characterize these components. To simulate accelerated weathering, samples of the biocomposite constituents are subjected to cycles of hygrothermal stress and UV radiation using an accelerated weathering testing apparatus. Subsequently, experimental mechanical tests are performed on the aged biocomposite components, and their mechanical properties are assessed and compared to those of the non-aged materials. The results reveal that aging leads to a significant reduction in the mechanical properties of the hemp ropes, and varying effects on the mechanical properties of matrices depending on their nature (organic binder-based or mortar-based matrices).

Modeling of crack tip fields and fatigue crack growth in fcc crystals

Predicting the mechanical behavior of polycrystalline materials containing a crack under both monotonic and cyclic loading conditions is crucial for accurately assessing the integrity of engineering materials. This study focuses on the deformation characteristics of face-centered cubic (fcc) grains within the crack tip field and their significant role in governing the driving force for fatigue crack growth during cyclic loading. We employ a cyclic crystal plasticity finite element (CPFE) model to analyze the mechanical response of austenitic 316L stainless steel polycrystals by accounting for nonlinear kinematic hardening effects. Through CPFE simulations, we investigate the deformation fields in 316L grains at the crack tip, considering two different grain orientations under plane strain conditions. Our CPFE results under monotonic loading align consistently with previous theoretical and experimental findings, particularly in comparing CPFE-simulated and experimentally observed plastic sectors consisting of different slip traces on the specimen surface near the crack tip. Based on a critical plastic work criterion for crack advancement, cyclic CPFE simulations are used to determine the fatigue crack growth rate as a function of stress intensity factor range for the two crack tip grain orientations in stainless steel. The simulated Paris law exponent matches experimental values. Furthermore, we compare cyclic CPFE results with those from cyclic J2 plasticity finite element simulations. This study demonstrates a cyclic CPFE approach for determining crack tip fields, accounting for crystallographic effects on plastic deformation of crack tip grains. Our approach can be applied to effectively evaluate fatigue crack growth rates in fcc polycrystalline metals.

Investigation of plastic flow of rail vehicle wheels and its effects on rolling contact fatigue based on a dynamic method

To analyze the plastic flow of wheels and its impact on rolling contact fatigue (RCF), this article proposes a multibody dynamics approach that is simple to model and fast to compute, based on the mechanics of wheel-rail contact and Tresca yield criterion. This method is used to study the plastic flow of the wheels and is validated by comparing it with plastic flow analysis based on the shakedown theory. The study shows that the dynamics indicators of maximum shear stress, adhesion saturation and stress ratio effectively reflect the plastic deformation of the wheel. Additionally, increasing wheel speed and curve radius, and decreasing wheel-rail friction coefficient, can effectively reduce the area and severity of plastic deformation in the wheel. Ignoring the impact of temperature effects on RCF, it is found that the more severe the plastic flow, the greater the likelihood of RCF. That is, alleviating the plastic flow of the wheel can reduce RCF damage in wheels. This approach to managing the health of wheels provides a comprehensive understanding of the interplay between operational parameters and the mechanical behavior of wheel materials, guiding maintenance strategies and operational decisions to enhance safety and extend the lifespan of railway components.

Effective mechanical behaviors of transverse isotropic materials embedded compressible liquid inclusions with surface effects

Porous media with fluid-saturated microchannels, prevalent in biomaterials, tissue engineering materials and flexible electronic devices, can be modelled as transverse isotropic materials. Surface effects can influence significantly the macro-mechanical responses of such materials, particularly for soft materials with micro- or nano-scale channels. In this study, we first develop constitutive laws for fluid saturated porous materials with microchannels by integrating the top-down (homogenization) approach with the bottom-up (micromechanics) approach. We then explicitly establish a connection between surface effects and macro-mechanical responses. Employing the generalized self-consistent model (GSCM), we estimate the effective parameters (i.e., coefficients in constitutive equations governing macro-mechanical responses), with fluid compressibility and surface effects accounted for. Our findings reveal that, as surface energy increases, the effective transverse shear modulus is enlarged, the effective plane strain bulk modulus, the unit uniaxial straining modulus and the cross modulus are all reduced, but the axial shear modulus remains nearly unchanged. As an application, we characterize the mechanical behaviors of the transverse isotropic fluid-saturated porous material with surface effects by connecting the classic Mandel solution with the estimated effective parameters. The pore pressure exhibits the Mandel-Cryer effect. The insights gained from this study are valuable for comprehending and exploring the intricate ways in which surface effects influence the mechanical responses of transversely isotropic fluid-saturated porous materials featuring sufficiently small channels.

Micro-CT image-based computation of effective thermal and mechanical properties of fibrous porous materials

Fibrous porous materials are extensively employed as heat shielding material for space vehicles and capsules. To predict the performance of these materials using computational modeling at the vehicle/capsule scale, the effective material properties are needed. In this work, the effective thermal conductivity and elastic constants of a carbon fibrous porous material called FiberForm (precursor of PICA) were calculated using a direct image-based approach. In this image-based approach, the microstructures obtained using X-ray computed tomography technique are represented as binary voxel data. Nonlocal interactions are introduced between neighboring voxels. Integro-differential equations, with respect to spatial and temporal dimensions respectively, are developed to govern material thermal and mechanical behaviors. Using this approach, energy-based computational procedures were developed to calculate the effective material properties of fibrous and porous materials irrespective of the periodicity of underlying microstructures. The size of representative volume element was determined by convergence of effective properties with respect to microstructure size.

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.

Time-varying damage evolution of concrete under cyclic disturbance loading- an experimental observation utilizing AE and DIC

Cyclic disturbance loading affects the continuous operation of concrete structures. This study aims to better understand the failure behavior of concrete structures under cyclic disturbance loading. This study combined acoustic emission (AE) and digital image correlation (DIC) technologies to study mechanical failure behavior and damage evolution of concrete materials under cyclic disturbance loading and unloading. The AE event time-frequency characteristics, surface principal strain program, and damage parameters of samples with different cyclic disturbance amplitudes were obtained by theoretical calculation. The results reveal that when minor disturbance amplitudes are applied, the elastic modulus of concrete specimens tends to increase. When the disturbance amplitude is too large, the elastic modulus of the specimens drops, leading to faster specimen failure. The AE characteristic parameters exhibit a Felicity effect after the sample is subjected to a cyclic disturbance loading. Moreover, the larger the amplitude of the disturbance load, the more frequent the low-frequency and high-amplitude events generated during the final rupture, the higher the concentration of the principal strain on the sample's surface, and the wider the crack band distribution. AE energy and Effective crack are consistent in characterizing damage, and the changing trend of these two damage parameters can better reflect the deterioration process of concrete. The research results will provide practical and theoretical insights for safely operating and maintaining concrete structures.

Static Behavior of a 3D-Printed Short Carbon Fiber Polyamide: Influence of the Meso-Structure and Water Content.

The knowledge of the mechanical behavior of a 3D-printed material is fundamental for the 3D printing outbreaking technology to be considered for a range of applications. In this framework, the significance, reliability, and accuracy of the information obtained by testing material coupons assumes a pivotal role. The present work focuses on an evaluation of the static mechanical properties and failure modes of a 3D-printed short carbon fiber-reinforced polyamide in relation to the specimen's unique meso-structural morphology and water content. Within the manufacturing limitations of a commercially available printer, specimens of dedicated combinations of geometry and printing patterns were specifically conceived and tested. The specimens' meso-structure morphologies were investigated by micro-computed tomography. The material failure mechanisms were inferred from an analysis of the specimens' fracture surfaces and failure morphologies. The outcomes of the present analysis indicate that each test specimen retained proper mechanical properties, thereby suggesting that they should be accurately designed to deliver representative information of the underlying material beads or of their deposition layout. Suggestions on the adoption of preferred test specimens for evaluating specific material properties were proposed.

Crack-insensitive fracture of elastomer-based soft network materials under monotonic and cyclic loads

In various applications of stretchable electronics and soft robots, soft materials are subjected to long-term load-bearing conditions, requiring them to possess good extreme mechanical properties such as highly stretchable, strong, fracture-resistant and anti-fatigue. Conventional soft materials with a single polymer network typically exhibit relatively low fracture resistance, while commonly employed toughening method involves introducing mechanical dissipation into original polymer networks often require complicated chemical synthesis and result in significant hysteresis under cyclic loads. Designing soft solid materials into soft network materials with periodic lattice structure paving another effective route to improve the fracture-resistant performance of soft materials, which has not been reported in the literature. This work provides a combined experimental and computational study on the mechanical properties and fracture behaviors of elastomer-based soft network materials with/without a precut crack under monotonic and cyclic loads, aiming to present a structural design strategy for fracture-resistant soft materials. The elastomer-based soft network materials are proven to be crack-insensitive, low-hysteresis and anti-fatigue. The nonlinear finite element analysis (FEA) is employed to reveal the underlying mechanism of crack-insensitivity in elastomer-based soft network materials. Both the mechanical properties and deformed configurations of soft network materials with/without a precut crack are accurately predicted by the FEA method. The effect of microstructure geometry and network topology on the mechanical properties of soft network materials is systematically studied. Under various amplitudes of cyclic applied strain, the elastomer-based soft network materials can survive even after individual microstructures ruptured, and the fatigue fracture process slows down as the applied strain amplitude decreases. In contrast to the behavior observed in monotonic loads where fracture initiates at the microstructure located ahead of the crack tip, fatigue fracture initiation in soft network materials with a precut crack exhibits a random distribution.

Simulation of the Dynamic Responses of Layered Polymer Composites under Plate Impact Using the DSGZ Model

This paper presents a numerical study on the dynamic response and impact mitigation capabilities of layered ceramic–polymer–metal (CPM) composites under plate impact loading, focusing on the layer sequence effect. The layered structure, comprising a ceramic for hardness and thermal resistance, a polymer for energy absorption, and a metal for strength and ductility, is analyzed to evaluate its effectiveness in mitigating the impact loading. The simulations employed the VUMAT subroutine of DSGZ material models within Abaqus/Explicit to accurately represent the mechanical behavior of the polymeric materials in the composites. The VUMAT implementation incorporates the explicit time integration scheme and the implicit radial return mapping algorithm. A safe-version Newton–Raphson method is applied for numerically solving the differential equations of the J2 plastic flow theory. Analysis of the simulation results reveals that specific layer configurations significantly influence wave propagation, leading to variations in energy absorption and stress distribution within the material. Notably, certain layer sequences, such as P-C-M and C-P-M, exhibit enhanced impact mitigation with a superior ability to dissipate and redirect the impact energy. This phenomenon is tied to the interactions between the material properties of the ceramic, polymer, and metal, emphasizing the necessity of precise material characterization and enhanced understanding of the layer sequencing effect for optimizing composite designs for impact mitigation. The integration of empirical data with simulation methods provides a comprehensive framework for optimizing composite designs in high-impact scenarios. In the general fields of materials science and impact engineering, the current research offers some guidance for practical applications, underscoring the need for detailed simulations to capture the high-strain-rate dynamic responses of multilayered composites.