Description Of Material Behavior Research Articles

Data-driven modeling for residual velocity of projectile penetrating reinforced concrete slabs

The penetration of projectiles into reinforced concrete (RC) structures is crucial for defense technology. However, accurately estimating the resistance of RC structures to projectile penetration is challenging due to complex parameter nonlinearities. This paper proposes a data-driven modeling methodology that combines validated finite element (FE) simulations with machine learning (ML) algorithms to investigate the penetration resistance of RC slabs against projectiles. The methodology employs an extreme learning machine (ELM) network to identify extreme conditions characterizing penetration resistance, reducing data requirements, and improving prediction efficiency. Predicted results from the ELM network are then used as input for a recurrent neural network (RNN) to predict residual velocity curves over time, a crucial metric for evaluating penetration resistance. To cover various loading scenarios, 64 sets of FE models with different incident velocities, caliber-radius-head (CRH), and projectile masses are developed based on available experimental studies. The Johnson-Holmquist II model and Johnson-Cook model are employed for concrete and steel, respectively, to describe material behavior at high strain rates. The FE prediction results form a training sample database, and ML models are established using CRH, incident velocity, and projectile mass as input layers and projectile residual velocity as the output layer. The results demonstrate high Pearson correlation coefficients of 0.984 and 0.991 for the ELM and RNN prediction results, respectively, with numerical simulation results. The proposed networks provide accurate and efficient alternatives to time-consuming FE simulations for predicting projectile penetration performance. This strategy offers a new ML-based method for rapid evaluation, particularly for in-situ applications.

FAST FOURIER TRANSFORM METHOD FOR PERIDYNAMIC BAR OF PERIODIC STRUCTURE

The basic feature of the peridynamics [introduced by Silling (2000)] considered is a continuum description of material behavior as the integrated nonlocal force interactions between infinitesimal material points. A heterogeneous bar of the periodic structure of constituents with peridynamic mechanical properties is analyzed. One introduces the volumetric periodic boundary conditions (PBCs) at the interaction boundary of a representative unit cell (UC), whose local limit implies the known locally elastic PBCs. This permits us to generalize the classical computational homogenization approach to its counterpart in peridynamic micromechanics (PM). Alternative to the finite element methods (FEM) for solving computational homogenization problems are the fast Fourier transforms (FFTs) methods developed in local micromechanics (LM). The Lippmann-Schwinger (L-S) equation-based approach of the FFT method in the LM is generalized to the PM counterpart. Instead of one convolution kernel in the L-S equation, we use three convolution kernels corresponding to the properties of the matrix, inclusions, and interaction interface. The Eshelby tensor in LM depending on the inclusion shape is replaced by PM counterparts depending on the inclusion size and interaction interface (although the Eshelby concept of homogeneous eigenfields does no work in PM). The mentioned tensors are estimated one time (as in LM) in a frequency domain (also by the FFT method). Numerical examples for 1-D peridynamic inhomogeneous bar are considered. Computational complexities O (N <i>log</i><sub>2</sub> N) of the FFT methods are the same in both LM and PM.

Isogeometric smooth crack-band model (isCBM) using spress–sprain relations adapted to microplane theory

Recent optimum fitting of the data from eleven different types of distinctive fracture tests of quasibrittle materials, including the gap tests and the size effect tests, revealed that the crack band model (CBM) with the M7 damage constitutive law outperforms all the other existing computational fracture models for concrete. This is attributed to physically correct boundary conditions, especially those at the crack faces,to the crack front of finite width which allows using a triaxial tensorial damage constitutive law, and to choosing for this law a realistic material behavior description, the M7. Nevertheless the CBM has limitations—the width of the crack band cannot be varied, the statistically smooth damage distribution across the band cannot be resolved, and the propagation direction is biased by the mesh orientation when a regular mesh is used. These limitations have been overcome by the smooth crack band model (sCBM), which uses unconventional homogenization of damage mechanics to yield an additional Helmholtz free energy density, called the “sprain energy”. This energy is a function of the curvature tensor (or a hessian) of the vectorial displacement field, called the “sprain curvature tensor” (or sprain tensor for brevity), which is a sum of the strain gradient tensor and, importantly, the rotation gradient tensor. But, in a previous study, difficulties arose in computational implementation—the use of constant-strain elements required the curvature to be resisted by sprain forces that represented the derivatives of sprain energy with respect to nodal displacements and had to be applied on the nodes of adjacent elements. The need for adjacent nodes is here avoided by a variational derivation of the Isogeometric Smooth Crack-Band Model (isCBM). The microplane damage constitutive model M7 for concrete is adopted, which is made possible by establishing the relations of the sprain stress (or spress, for brevity) and sprain on microplanes of arbitrary orientations. Using Isogeometric Analysis (IGA) based on non-uniform rational B-Splines (NURBS), the excessive displacement curvature and its resistance (spress) can be described by the shape functions with C1-continuity. Computational results show that the orientation bias of regular meshes is eliminated while keeping the constitutive law intact, which is important for compatibility with the existing material laws in general. In addition, comparisons with experimental data reveal that isCBM with M7 can reproduce the correspondence between the size of the fracture process zone and the fracture energy, as indicated by gap tests. Finally, the isCBM does not compromise the strain-path-dependence of material response.

Special Issue for KSTP30 Years Anniversary: Recent Steel Research in Mechanics of Plastic Deformation and Materials Processing

Special Issue for KSTP30 Years Anniversary: Recent Steel Research in Mechanics of Plastic Deformation and Materials Processing

Nonlinear strain gradient and micromorphic one-dimensional elastic continua: Comparison through strong ellipticity conditions

We discuss the strong ellipticity (SE) conditions for strain gradient and micromorphic continua considering them as an enhancement of a simple nonlinearly elastic material called in the following primary material. Recently both models are widely used for description of material behavior of beam-lattice metamaterials which may possess various types of material instabilities. We analyze how a possible loss of SE results in the behavior of enhanced models. We shown that SE conditions for a micromorphic medium is more restrictive than for its gradient counterpart. On the other hand we see that a violation of SE for a primary material affects solutions within enhanced models even if the SE conditions are fulfilled for them.

Simulation, analysis and comparison of cutting parameter during turning of Ti-6Al-4V alloy with assorted industrial coated carbide

This work focuses on studying the special effects of processing conditions on the J-C (Johnson-Cook) material model factors for orthogonal turning of Ti-6Al-4V. It is highly corrosive resistant materials. Two sets of factors of the Johnson-Cook material model describing material behavior of both alloy were investigated by comparing cutting forces, chip study, and chip tool interfaces temperature. A 2-D finite element model was made and validated with the results of published literature. Cutting tests were conducted at low, medium, and high-speed cutting speeds with three different cutting tools. Chip formation and cutting forces were compared for both numerical models. It was observed that cutting forces decrease as cutting speed increases. Three different types of cutting tools are used here with the same geometry so that the result can be compared attractively. The results are then compared with experimental references and more standard models: an ALE model developed with ABACUS (FEA software). It was observed that the Polycrystalline Diamond tool produces less force as compared to other tools. The results obtained through simulation analysis after including changes in the coefficient of friction and other material properties showed a good agreement with the experimental results.

Residual Properties in Damaged Laminated Composites through Nondestructive Testing: A Review.

The development of damage tolerance strategies in the design of composite structures constitutes a major challenge for the widespread application of composite materials. Damage tolerance approaches require a proper combination of material behavior description and nondestructive techniques. In contrast to metals, strength degradation approaches, i.e., the residual strength in presence of cracks, are not straightforwardly enforceable in composites. The nonhomogeneous nature of such materials gives rise to several failure mechanisms and, therefore, the definition of an ultimate load carrying capacity is ambiguous. Nondestructive techniques are thus increasingly required, where the damage severity is quantified not only in terms of damage extension, but also in terms of material response of the damaged region. Based on different approaches, many nondestructive techniques have been proposed in the literature, which are able to provide a quantitative description of the material state. In the present paper, a review of such nondestructive techniques for laminated composites is presented. The main objective is to analyze the damage indexes related to each method and to point out their significance with respect to the residual mechanical performances, as a result of the working principle of each retained technique. A possible guide for future research on this subject is thus outlined.

Mathematical modeling of single action pressing of powder materials under dry friction conditions

The paper presents a theoretical analysis of the single action pressing of powder materials featuring plasticity and compressibility. It takes into account dry external friction between the die material and side walls, which determines the strong nonlinearity of the problem considered. This problem has a number of features that complicate its numerical solution: the presence of external friction, the elastic-plastic law of material behavior description, as well as the calculation of large displacements and, as a consequence, strong geometric nonlinearity. To consider these features, a combination of Fleck–Kuhn–McMeeking and Gurson– Tvergaard–Needleman models was used to consider a wide range of changes in the porosity of materials. The numerical solution of the problem was carried out using finite element analysis with isoparametric elements. The increment of plastic deformations at each step was determined from nonlinear equations of plastic flow. Stresses at the Gaussian points were updated according to the specified increments of deformations to calculate the material behavior during deformation. Unknown density and strain values as functions of coordinate and time were calculated. The influence of the different height-to-diameter ratio of the blank and the value of external friction of the material stress-strain state and compaction kinetics were considered. The distribution of equivalent stresses and the value of volumetric plastic deformations in the material, as well as the nonuniformity of relative density at the end of the pressing period were studied. The theoretical analysis made it possible to study the basic compaction kinetics laws for powder materials with nonuniform density under conditions of dry friction on side walls. The results obtained are relevant for predicting possible negative changes in the blank geometry when implementing the single action pressing scheme for powder materials.

Imaging Metal Halide Perovskites Material and Properties at the Nanoscale

AbstractMetal halide perovskites exhibit optimal properties for optoelectronic devices, ranging from photovoltaics to light‐emitting diodes, utilizing simple fabrication routes that produce impressive electrical and optical tunability. As perovskite technologies continue to mature, an understanding of their fundamental properties at length scales relevant to their morphology is critical. In this review, an overview is presented of the key insights into perovskite material properties provided by measurement methods based on the atomic force microscopy (AFM). Specifically, the manner in which AFM‐based techniques supply valuable information regarding electrical and chemical heterogeneity, ferroelectricity and ferroelasticity, surface passivation and chemical modification, ionic migration, and material/device stability is discussed. Continued advances in perovskite materials will require multimodal approaches and machine learning, where the output of these scanning probe measurements is combined with high spatial resolution structural and chemical information to provide a complete nanoscale description of materials behavior and device performance.

Microstructure prediction in low and high strain deformation of Al6063 using artificial neural network and finite element simulation

The final microstructure of materials under interactive effects of critical elements of deformation: strain, strain-rate, and temperature, often follows complex trajectories. Capturing the existing process-structure linkages is fundamental for controlling product outcomes, yet it calls for establishing the constitutive relationships that describe material behavior. In this paper, a backpropagation Artificial Neural Network (ANN) is proposed for microstructure prediction for a wide range of strain, strain-rate, and temperature conditions. Microstructural changes in Al6063 are experimentally examined using (i) quasi-static universal testing apparatus, Drop Weight Impact Tester (DWIT), and Split Hopkinson Pressure Bar (SHPB) tests for low strain regimes at elevated temperatures, and (ii) Plane Strain Machining (PSM) for high strain, high strain-rate, and the accompanied temperature rise conditions. Two ANNs are established to predict microstructure responses, grain and subgrain sizes, in low and high strain regimes, respectively. Additionally, the stress-strain results obtained from the low strain regime are used to calculate the Johnson–Cook (J-C) material model constants, which are then incorporated in the finite element (FE) simulation along with the developed ANN algorithm, to predict microstructure response for different cutting conditions. The performance of the ANNs and the FE simulations was evaluated using statistical indices. The comparative assessment of the models’ outcomes indicates close agreements with the experimental results in both low- and high-level deformations. The accurate predictions from PSM conditions can potentially be applicable for microstructural prediction of the machined surface.

Numerical and experimental benchmarking of the dynamic response of SiC and TZM specimens in the MultiMat experiment

The MultiMat experiment was successfully conducted at CERN's HiRadMat facility, aiming to test novel high-performance materials for use in beam intercepting devices, allowing the derivation and validation of material constitutive models. This article provides an analysis of results for two materials tested in the experiment, namely Silicon Carbide and Titanium Zirconium Molybdenum, with the aim of benchmarking the material constitutive models currently available in literature with experimental results. The material models were implemented in numerical simulations, successfully modelling dynamic longitudinal and flexural phenomena. The article further studies the modelling of the complex boundary conditions present in the experiment, the internal damping characteristics of the materials, and the failure of certain specimens. The strength and failure models proved adequate to model a number of experimental scenarios tested, but require further study to describe the material behaviour at the high strain rates and temperatures induced by accidental particle beam impacts. A post-irradiation examination of the tested specimens was also performed to study the nature of failure in the specimens, and is to be coupled with quasi-static and high strain rate tests for both materials, allowing for the validation of the currently available models and the description of material behaviour across a wide range of strain rates and temperatures.

Расчет исполнительного элемента предохранительного механизма безопасной электрической розетки, выполненного из сплава с эффектом памяти формы

The article considers possibility of creating a safety element for a safe electrical outlet based on the shape memory effect. Numerical model of helical cylindrical spring of the shape memory alloy is developed. The phenomenological approach based on the phase transition diagram is used to describe material behavior. Shape memory effect is included using additional internal force factor i.e. the shape memory moment under torsion. An algorithm for constructing the relationship between the torque in cross section and the shape memory moment for isothermal loading is presented. The problem of simultaneous deformation of shape memory alloy spring and flat copper spring under heating is solved. The contact plate is replaced by an equivalent spring. Spring stiffness is obtained using a system of nonlinear differential equations describing the bending of a bar.

Artificial Neural Network Prediction of Silicon and Nickel recovery in Al-Si-Ni alloy Manufactured by Stir Casting

Artificial neural network (ANN) is a non-linear statistical technique that being used to describe material behavior. This paper proposes using artificial neural networks (ANNS) in predicting silicon and nickel recovery. During the experimental work, the used optimum parameters are reaction time is 25 min., temperature is 950 ᵒC, Ni2O3 /Al wt. (weight) ratio is 0.082, and Na2SiF6 / Al wt. ratio is 1. Some tests such as chemical analysis, microstructure examination (EDX mapping), XRD diffraction were carried out on the produced alloys. The obtained experimental results are used to train the artificial neural network (ANN). While reaction time, temperature, Ni2O3 /Al wt. ratio, and Na2SiF6 / Al wt. ratio are used as ANN's inputs. Silicon and nickel recovery are used as ANN's outputs. The used ANN consists of three layers; Input layer that includes 4 neurons, the hidden layer includes 9 neurons, while the output layer contains 2 neurons. The Levenberg-Marquardt (LM) is used as the training function. Optimal mean square errors (MSE) for the ANN during predicting and estimating silicon and nickel recovery equal 0.0358, 0.0034, respectively, when reaction time is the variable and other parameters are kept constant, MSE equal 1.4007e-04, 1.3478e-04 when temperature is variable and other parameters are kept constant, MSE equal 1.3839e-04, 9.9891e-05 when Ni2O3/Al wt. ratio was the variable and other parameters are kept constant and finally MSE equal 0.0287, 0.0263 when Na2SiF6 / Al wt. ratio is variable and other parameters are kept constant.

A semi-analytical model for inverse identification of cyclic material data from measured forces during roller levelling

Abstract The process of roller levelling is essential to ensure flatness of sheet metals and to reduce residual stresses within the material. Besides process parameters like machine geometry and roll positions, the process is sensitive to variations of material properties. In order to detect variations of the material properties, an inverse identification of material parameters from measured process data is desirable. Therefore, a semi-analytical levelling model based on bending theory that is capable to describe material behavior under low cyclic loading is introduced. This model calculates the levelling forces depending on given material data. Employing the model within an optimization loop, the model allows for an inverse determination of material data during levelling by comparing calculated and measured levelling forces. To validate the model, accompanying finite element (FE) simulations, levelling experiments as well as cyclic bending tests are performed. According to the results, the semi-analytical model is capable of calculating levelling forces in good agreement with FE results and much lower computation times. Furthermore, material data obtained directly from levelling experiments are in the same range as data determined from cyclic bending tests.

Cyclic plasticity model for fatigue with softening behaviour below macroscopic yielding

Experimental observations have evidenced the insufficiency of yield surface definition via monotonic loading to guarantee adequate description of material behaviour under fatigue tests. Therefore, mechanical property characterisation through simple experimental tests such as uniaxial monotonic extension/compression is favoured, considering different responses due to cyclic loading. Herein, a phenomenological cyclic plasticity model is formulated to capture the correct generation of plastic deformation under cyclic loading conditions, even for stress states lower than the yield stress. The unconventional extended subloading surface model is modified to include an additional internal variable describing the strain-softening phenomenon typical of low- to high-cycle fatigue problems. Implicit integration strategies, in the form of the cutting-plane and closest projection point return mapping algorithms, are implemented to reduce the computation time. The solution accuracies are compared to that of a forward Euler integration scheme, and exhibit fast and accurate performance.

Equivalent Uniaxial Cyclic Tensile Stress as an Energy Characteristic of Metal Fatigue under Multiparameter Loading

A concept of the equivalent stress as an energy characteristic of the material ability to resist deformation and fatigue cracking is introduced based on the principles of physical mesomechanics and synergetics. It is shown that the tensile curve of the material, the fatigue life diagram, and the kinetic curve for fatigue crack growth obtained under common experimental conditions can be considered as unified or "master" diagrams for material behavior description under multiparameter loading. Examples of determining the equivalent stress value and correction functions on the basis of the introduced concept are given for fatigue specimens subjected to biaxial cyclic loading and for in-service fatigue specimens of aircraft structures.

Material Behavior Description for a Large Range of Strain Rates from Low to High Temperatures: Application to High Strength Steel

Current needs in the design and optimization of complex protective structures lead to the development of more accurate numerical modelling of impact loadings. The aim of developing such a tool is to be able to predict the protection performance of structures using fewer experiments. Considering only the numerical approach, the most important issue to have a reliable simulation is to focus on the material behavior description in terms of constitutive relations and failure model for high strain rates, large field of temperatures and complex stress states. In this context, the present study deals with the dynamic thermo-mechanical behavior of a high strength steel (HSS) close to the Mars® 190 (Industeel France, Le Creusot, France). For the considered application, the material can undergo both quasi-static and dynamic loadings. Thus, the studied strain rate range is varying from 10−3–104 s−1. Due to the fast loading time, the local temperature increase during dynamic loading induces a thermal softening. The temperature sensitivity has been studied up to 473 K under quasi-static and dynamic conditions. Low temperature measurements (lower than the room temperature) are also reported in term of σ − ε | ε ˙ , T curves. Experimental results are then used to identify the parameters of several constitutive relations, such as the model developed initially by Johnson and Cook; Voyiadjis and Abed; and Rusinek and Klepaczko respectively termed Johnson–Cook (JC), Voyiadjis–Abed (VA), and Rusinek–Klepaczko (RK). Finally, comparisons between experimental results and model predictions are reported and compared.

Development and validation of an anisotropic damage constitutive model for C/SiC composite

Due to damage coupling and anisotropic evolution, constitutive models of Ceramic Matrix Composites are generally deficient in the description of material behavior under complex load conditions. This paper studied the mechanical behavior of a PIP prepared 3k carbon fabric plain woven C/SiC material under complex stress states. The phenomenon and mechanism of the anisotropy damage were analyzed. A constitutive model was proposed considering the anisotropy damage effect by load ratio functions, and only scalar damage variables were used to maintain a simple formulation. The constitutive model was validated against tensile tests of hat-shaped CMC components, and a FEM model of the experiments was established. The comparisons of strain results between the experiments and the FEM simulation showed good agreement under different loads. The model can be employed to facilitate structural analysis and design where material non-linearity is important.

Numerical and experimental investigation of Johnson–Cook material models for aluminum (Al 6061-T6) alloy using orthogonal machining approach

This research focuses on the study of the effects of processing conditions on the Johnson–Cook material model parameters for orthogonal machining of aluminum (Al 6061-T6) alloy. Two sets of parameters of Johnson–Cook material model describing material behavior of Al 6061-T6 were investigated by comparing cutting forces and chip morphology. A two-dimensional finite element model was developed and validated with the experimental results published literature. Cutting tests were conducted at low-, medium-, and high-speed cutting speeds. Chip formation and cutting forces were compared with the numerical model. A novel technique of cutting force measurement using power meter was also validated. It was found that the cutting forces decrease at higher cutting speeds as compared to the low and medium cutting speeds. The poor prediction of cutting forces by Johnson–Cook model at higher cutting speeds and feed rates showed the existence of a material behavior that does not exist at lower or medium cutting speeds. Two factors were considered responsible for the change in cutting forces at higher cutting speeds: change in coefficient of friction and thermal softening. The results obtained through numerical investigations after incorporated changes in coefficient of friction showed a good agreement with the experimental results.

Evaluation of thermodynamic equations of state across chemistry and structure in the materials project

Thermodynamic equations of state (EOS) for crystalline solids describe material behaviors under changes in pressure, volume, entropy and temperature, making them fundamental to scientific research in a wide range of fields including geophysics, energy storage and development of novel materials. Despite over a century of theoretical development and experimental testing of energy–volume (E–V) EOS for solids, there is still a lack of consensus with regard to which equation is indeed optimal, as well as to what metric is most appropriate for making this judgment. In this study, several metrics were used to evaluate quality of fit for 8 different EOS across 87 elements and over 100 compounds which appear in the literature. Our findings do not indicate a clear “best” EOS, but we identify three which consistently perform well relative to the rest of the set. Furthermore, we find that for the aggregate data set, the RMSrD is not strongly correlated with the nature of the compound, e.g., whether it is a metal, insulator, or semiconductor, nor the bulk modulus for any of the EOS, indicating that a single equation can be used across a broad range of classes of materials.