Material Parameters Research Articles

On the numerical assessment of bending- and torsion-induced stresses in idealised sawn timber beams

ABSTRACT When designing timber beams for bending, shear and torsion, it is common engineering practice to use analytical formulas that neglect the cylindrical nature of the orthotropic material, the annual ring orientation, spiral grain and so on. While they result in stresses that appear reasonable, the approach is in principle theoretically flawed. In this paper a 3D finite element model is used to analyse the stress levels in sawn timber beams, taking into account the radially varying and cylindrically orthotropic material parameters, as well as a number of geometrical features. The beams are assumed to be mechanically idealised without imperfections. Parametric analyses indicate that especially the annual ring orientation has a significant impact on the maximum stresses, even though the cross-sectional stress distributions have distinct similarities with common beam theory. Furthermore, a Monte Carlo simulation is performed, randomly varying all parameters within given intervals. The simulations reveal that the maximum stresses from the finite element model, in almost all cases are noticeably larger than predicted by the analytical formulas, rendering them on the unsafe side in a theoretical sense.

Wave propagation in bidirectional functionally graded tapered beams incorporating porosity effect

This study addresses wave propagation in beams made of bidirectional functionally graded materials (BDFG) and having nonuniform cross section by using a quasi-3D analytical solution. For the first time, this aspect will be studied. The mechanical characteristics of the beams are supposed to be variable in both axial and transvers direction according to a specific law depending on the porosity. The mathematical formulation used is based on a displacement field containing indeterminate terms and requiring a few variables to be determined. The thickness and width of the beams are assumed to be linearly variable in the longitudinal direction. The equations governing the simply supported beams are obtained by applying the principle of virtual work and are then analytically solved to obtain the phase velocities and wave frequencies. In addition, the validation results reveal excellent concordance of the proposed theory with those given in the literature. Then, a detailed parametric study is carried out to investigate the influence of the several geometrical and material parameters on the wave propagation in BDFG tapered beams. It is observed that these parameters have significant impact on the wave propagation in BDFG tapered porous beams. These results can be used as benchmark solutions for future studies.

Spectro-geometry dynamic analysis of FG-GPLRC cylindrical shell with periodically embedded dynamic vibration absorbers

This study presents a theoretical model of the functionally graded graphene platelet-reinforced composite (FG-GPLRC) cylindrical shell with periodically embedded dynamic vibration absorbers (DVAs) under different boundary constraints. The material parameters of the FG-GPLRC were first determined using the Halpin-Tsai micromechanical method and the general law of mixing. The energy expression for the system is developed based on the first-order shear deformation theory (FSDT). A simplified model of the DVA is carried out, which consists of a mass block, a linear damper and a linear spring after simplification. Displacement field vectors of the cylindrical shell are established based on the spectro-geometric method (SGM). The Rayleigh-Ritz method was used to determine the vibration response of the coupled model. The validity of the proposed method is confirmed through comparing with results from existing literature and finite element method (FEM) calculations. The effect of boundary conditions, FG-GPLRC material properties, geometrical parameters of cylindrical shells, distribution parameters of DVAs, and damping coefficient on the steady-state vibration of the coupled model is investigated on this basis.

Design and Control of the Natural Frequency of Brake Discs in the Aspect of the Gray Cast Iron Production Process.

The results of research on the influence of the chemical composition of cast iron and its potential changes in the production cycle on the elastic properties and the correctness of numerical simulations of the natural frequency of ventilated brake discs are presented. The tests were carried out for three grades of gray cast iron with flake graphite with a eutectic saturation coefficient ranging from 0.88 to 1.01. A quantitative metallographic assessment of the pearlitic cast iron matrix and graphite precipitates was carried out, and the hardness and compressive/tensile strength of individual cast iron grades were determined, taking into account the limit contents of the alloying elements. Next, ultrasonic tests were performed, and the elastic properties of cast iron were determined. Based on the obtained data, a numerical modal analysis of brake discs was performed, the results of which were compared with the actual values of an FRF frequency analysis. The error of the computer simulations was estimated at approx. 1%, and it was found that the accuracy of the calculations of the first natural frequency did not depend on the dimensions (size) of the discs and the chemical composition of the cast iron from which they were cast. The functional relationships between the chemical composition of cast iron, its strength and elasticity and the first natural frequency of the disc vibrations were determined, and a database of the material parameters of the produced cast iron grades was developed. An implementation example showed the validation of the brake disc design with natural frequency prediction and demonstrated a high convergence of the experimental results with the simulated values. Using I-MR control cards, both the effectiveness of designing and predicting the natural vibrations of brake discs based on the implemented material database as well as the stability of the gray cast iron production and disc casting processes were confirmed.

Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification

The open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine learning-based approach for start value prediction in order to calibrate a Gurson–Tvergaard–Needleman (GTN) and a Lemaitre damage model. As representative example case-hardened steel 16MnCrS5 is elaborated. An artificial neural network (ANN) is initially trained by using load–displacement curves derived from simulations of a boundary value problem—instead of using data generated for homogeneous states of deformation at material point or one-element level—with varying material parameter combinations. The ANN is then employed so as to predict sets of material parameters that already provide close solutions to the experiment. These predicted parameter sets serve as starting values for a subsequent multi-objective parameter identification by using ADAPT. ADAPT allows for the consideration of input data from multiple scales, including integral data such as load–displacement curves, full-field data such as displacement and strain fields, and high-resolution experimental void data at the micro-scale. The influence of each data set on prediction quality is analyzed. Using various types of input data introduces additional information, enhancing prediction accuracy. The validation is carried out with respect to experimental void measurements of forward rod extruded parts. The results demonstrate, by incorporating void measurements in the optimization process, that it is possible to improve the quantitative prediction of ductile damage in the sense of void area fractions by factor 28 in forward rod extrusion.

Effects of Impurities and Ageing on the Functional and Rheological Properties of Asphalts with Additives from Recovered and Pyrolysis-Processed Plastics.

This article is a continuation of work on the use of plastic waste (such as PP, PS, LDPE, HDPE, and their mixtures) processed in the proprietary pyrolysis process as asphalt additives. The article carried out detailed tests of the mixes of selected additives with pen-graded bitumen 50/70, taking into account, among others, the influence of impurities and the ratio of PE to PP in the additives as well as short- (RTFOT) and long-term (RTFOT + PAV) ageing. An extensive research program was carried out, including functional and rheological tests in a wide range of temperatures. First, tests of stability and adhesion to various types of aggregates were carried out, demonstrating the usefulness of the proposed additives. Then, the elastic recovery and the impact of technological ageing on penetration, Fraass breaking temperature, and plasticity range were assessed. The same binder mixes were subjected to rheological tests in a wide range of technological and operational temperatures, assessing, among others, viscosity, the norm of the complex shear modulus, elastic recovery and compliance in the MSCR test, and stiffness in the bending beam rheometer. This entire class of tests was carried out for clean samples and those containing impurities, indicating their impact on individual material parameters.

Gravity-driven thin film flow of a third-grade fluid on a movable inclined plane with slip boundary condition

The prime aim and essence of this study are to present a closed-form solution of the unidirectional velocity field for thin film flow generated by a third-grade liquid moving over a fixed or movable inclined plane in the presence of partial slip boundary condition. Consideration of partial slip makes this problem different from other published research works. Here lies the novelty of this study. The nondimensional, unidirectional velocity profiles rely on the material parameter of third-grade fluid, slip parameter and initial velocity of the movable plane. Study discloses that the fluid’s velocity decelerates with raising the material property of grade-3 fluid and it accelerates with the slip parameter and initial velocity of the inclined plane. The outcomes of this study are deliberated physically at length.

Machine learning driven performance enhancement of perovskite solar cells with CNT as both hole transport layer and back contact

We propose a machine learning-based approach to enhance the performance of perovskite solar cells (PSCs) using carbon nanotubes as both hole transport layer (HTL) and back contact. Carbon-based PSCs offer low fabrication costs, long-term mechanical stability, high charge transport, and broad wavelength transparency. Our study estimates and enhances power conversion efficiency (PCE) of carbon-based PSCs through machine learning. PSC with single-walled carbon nanotube (SWCNT)-based HTL and back contact is investigated in simulations using SCAPS-1D and achieved 14.24% PCE, closely aligning with experimental data. Additionally, we explore the impact of various easily tunable fabrication parameters, such as the band gap and electron affinity of SWCNT in HTL, HTL thickness, active layer thickness, electron transport layer (ETL) thickness, HTL dopant concentration, absorber defect density, and ETL dopant concentration, on PCE. We generate a dataset of 20,480 samples to train classical and neural network-based machine learning models to predict performance parameters of PSCs, including short-circuit current density (JSC), open-circuit voltage (VOC), fill factor (FF), and PCE (η). The current density vs. voltage (J-V) characteristics curve is well-fitted by the predicted JSC, VOC, and FF, as evidenced by an average root mean squared error (RMSE) of 0.03 and a goodness of fit (R2) value of 0.99. The fully connected artificial neural network performs best, with RMSE of 0.05% and R2 of 0.99998 for predicting PCE. Genetic algorithm is used to optimize PCE, yielding a maximum PCE of 20.92%. Furthermore, an analysis of feature dimension and dataset size on prediction performance guides future modeling approaches.

Coupled Effects of High Temperature and Steel Fiber Content on Energy Absorption Properties of Concrete.

The associated effects of temperature and steel fiber content on the energy absorption properties of concrete were examined using quasi-static uniaxial compression tests of concrete materials with varied steel fiber contents (0%, 0.5%, 1%, and 1.5%) at various temperatures (20 °C, 200 °C, 400 °C, and 520 °C). The experimental findings demonstrate that steel fibers can greatly boost concrete's ability to absorb energy and that the toughness index rises with steel fiber concentration. The energy absorption capacity of concrete under high-temperature conditions also significantly decreases as temperature rises, and the energy absorption ability of steel fiber concrete under the same temperature is superior to that of plain concrete. The coupled influence factor K of temperature-steel fiber percentage characterizing the energy-absorbing ability of concrete was determined, and the coupled influence law of temperature and steel fiber content on the energy-absorbing capacity of concrete materials was summarized and analyzed on the basis of the experimental data of high-temperature compression. Equivalent equations for steel fiber reinforcing and temperature weakening effects when they are comparable (K = 1) are developed and equivalent parameters for concrete materials are given.

Modeling and experimental characterization of two-wave mixing in Yb-doped fiber amplifiers

Two-wave mixing between forward- and backward-propagating signal light has recently been observed in frequency-modulated single-frequency fiber laser systems. The phenomenon is a potential limiting factor for power scaling of such frequency-tunable lasers. In this contribution, we derive a perturbative coupled-mode theory for two signals that counter-propagate in an Yb-doped fiber with a constant frequency detuning. We apply the theory to analyze experimental results dedicated to extracting the central material parameter that relates the Yb inversion to a (real) refractive-index change. The perturbative theory is derived to all orders, and argued to be convergent. The experimental results and our analysis support previous estimates of the ratio between changes in the gain coefficient and the refractive index.

Versatile data-adaptive hyperelastic energy functions for soft materials

Applications of soft materials are customarily linked to complex deformation scenarios and material nonlinearities. In the bioengineering field, soft materials typically mimic the low stiffness of biological matter subjected to extreme deformations. Computational frameworks surge as a versatile tool to assist the design of functional applications. The constitutive model lies at the core of such frameworks. In this regard, the customary extreme non-linear behavior of elastomers poses an additional challenge to thoroughly capture the material behavior. Here, data-driven methodologies hold considerable promise for enhancing constitutive modeling when contrasted with phenomenological approaches. In this investigation, we introduce a versatile data-adaptive method tailored to the modeling of hyperelastic soft materials at finite strains. Specifically, our method substitutes an a priori chosen model for the strain energy function by a flexible interpolant defined on a discretized invariant space. Within this framework, the interpolation values assume the role of material parameters and are determined through finite element model updating to conform to measured experimental data — comprising full-field displacements coming from Digital-Image-Correlation and global reaction forces. We validate the method on uniaxial experimental tests of soft elastomers, encompassing ELASTOSILTM, DOWSILTM, and V HBTM. Overall, we aim to establish a new route for the construction of hyperelastic energy functions, untethered from any predefined existing models or assumptions regarding the shape of the energy.

Traction-separation law parameters for the description of age-related changes in the delamination strength of the human descending thoracic aorta.

Aortic dissection is a life-threatening disease that consists in the development of a tear in the wall of the aorta. The initial tear propagates as a discontinuity leading to separation within the aortic wall, which can result in the creation of a so-called false lumen. A fatal threat occurs if the rupture extends through the whole thickness of the aortic wall, as blood may then leak. It is generally accepted that the dissection, which can sometime extend along the entire length of the aorta, propagates via a delamination mechanism. The aim of the present paper is to provide experimentally validated parameters of a mathematical model for the description of the wall's cohesion. A model of the peeling experiment was built in Abaqus. The delamination interface was described by a piecewise linear traction-separation law. The bulk behavior of the aorta was assumed to be nonlinearly elastic, anisotropic, and incompressible. Our simulations resulted in estimates of the material parameters for the traction-separation law of the human descending thoracic aorta, which were obtained by minimizing the differences between the FEM predictions and the delamination force given by the regression of the peeling experiments. The results show that the stress at damage initiation, Tc, should be understood as an age-dependent quantity, and under the assumptions of our model this dependence can be expressed by linear regression as Tc = - 13.03·10-4·Age + 0.2485 if the crack front advances in the axial direction, and Tc = - 7.58·10-4·Age + 0.1897 if the crack front advances in the direction of the aortic circumference (Tc [MPa], Age [years]). Other model parameters were the stiffness K and the separation at failure, δf-δc (K = 0.5MPa/mm, δf-δc = 0.1mm). The material parameters provided by our study can be used in numerical simulations of the biomechanics of dissection propagation through the aorta especially when age-associated phenomena are studied.

Сравнительный прочностной анализ алмазных сегментов канатных камнерезных станков

The paper discusses the different shapes of diamond segments for stone cutting machines. The purpose of this research is to find ways to improve the abrasion resistance of the diamond segments, reduce the vibration load and increase the cutting efficiency. The operating conditions of stone-cutting machines are analysed, as well as the ways of increasing the efficiency of diamond segments by changing their shape. A calculation of the loads arising during operation of the diamond segments is made, and the results are verified using an experimental setup. The initial shape is analysed and the stresses that exceed the material parameters are found. In order to reduce the stresses, a diamond segment with rounded edges is simulated. Segments with bevelled edges and conical shape are also considered. Based on the experimental results, it is found that one of the promising shapes is that with rounded edges.

Сравнительный прочностной анализ алмазных сегментов канатных камнерезных станков

The paper discusses the different shapes of diamond segments for stone cutting machines. The purpose of this research is to find ways to improve the abrasion resistance of the diamond segments, reduce the vibration load and increase the cutting efficiency. The operating conditions of stone-cutting machines are analysed, as well as the ways of increasing the efficiency of diamond segments by changing their shape. A calculation of the loads arising during operation of the diamond segments is made, and the results are verified using an experimental setup. The initial shape is analysed and the stresses that exceed the material parameters are found. In order to reduce the stresses, a diamond segment with rounded edges is simulated. Segments with bevelled edges and conical shape are also considered. Based on the experimental results, it is found that one of the promising shapes is that with rounded edges.

Finite Element Analysis of the Mechanical Response for Cylindrical Lithium-Ion Batteries with the Double-Layer Windings

The plastic properties for the jellyroll of lithium-ion batteries showed different behavior in tension and compression, showing the yield strength in compression being several times higher than in tension. The crushable foam models were widely used to predict the mechanical responses to compressive loadings. However, since the compressive characteristic is dominant in this model, it is difficult to identify distributions of the yield strength in tension. In this study, a simplified jellyroll model consisting of double-layer windings was devised to reflect different plastic characteristics of a jellyroll, and the proposed model was applied to an 18650 cylindrical battery under compressive loading conditions. One winding adopted the crushable foam model for representing the compressive plastic behavior, and the other winding adopted the elastoplastic models for tracking the tensile plastic behavior. The material parameters in the crushable foam model were calibrated by comparing the simulated force–displacement curve with the experimental one for the case where the cell was crushed between two plates when the punch was displaced by 7 mm. A specific cut-off value (10 MPa) was assigned to a yield stress limit in the elastoplastic model. Further, the computational model was validated with two more loading cases, a cylindrical rod indentation and a spherical punch indentation, as the punch was displaced by 6.3 mm and 6.5 mm, respectively. For three loading cases, deformed configurations and plastic strain distributions were investigated by finite element analysis. It was found that the proposed model clearly provides the plastic behavior both in compression and tension. For the crush simulation, the maximum compressive stress approached 222 MPa in the middle of the jellyroll, and the maximum effective plastic strain approached 60% in the middle of the layered roll. For indentation with the cylindrical and the spherical punch, the maximum effective plastic strain approached 52% and 277% in the layered roll, respectively. The local crack or location of a short circuit could be predicted from the maximum effective plastic strain.

Crystal Plasticity Parameter Optimization in Cyclically Deformed Electrodeposited Copper—A Machine Learning Approach

This paper describes an application of a machine learning approach for parameter optimization. The method is demonstrated for the elasto-viscoplastic model with both isotropic and kinematic hardening. It is shown that the proposed method based on long short-term memory networks allowed a reasonable agreement of stress–strain curves to be obtained for cyclic deformation in a low-cycle fatigue regime. The main advantage of the proposed approach over traditional optimization schemes lies in the possibility of obtaining parameters for a new material without the necessity of conducting any further optimizations. As the power and robustness of the developed method was demonstrated for very challenging problems (cyclic deformation, crystal plasticity, self-consistent model and isotropic and kinematic hardening), it is directly applicable to other experiments and models.

Crystal Plasticity Parameter Optimization in Cyclically Deformed Electrodeposited Copper-A Machine Learning Approach.

This paper describes an application of a machine learning approach for parameter optimization. The method is demonstrated for the elasto-viscoplastic model with both isotropic and kinematic hardening. It is shown that the proposed method based on long short-term memory networks allowed a reasonable agreement of stress-strain curves to be obtained for cyclic deformation in a low-cycle fatigue regime. The main advantage of the proposed approach over traditional optimization schemes lies in the possibility of obtaining parameters for a new material without the necessity of conducting any further optimizations. As the power and robustness of the developed method was demonstrated for very challenging problems (cyclic deformation, crystal plasticity, self-consistent model and isotropic and kinematic hardening), it is directly applicable to other experiments and models.

Analytical Study on the Load-Bearing Performance of RC Beams Subjected to ASR Expansion

The alkali–silica reaction (ASR), a major cause of cracks in concrete, is a critical issue in the maintenance of social infrastructure. In this study, a concrete mesoscale model was meticulously developed, and a coupled stress–moisture model was also developed to reproduce ASR degradation. The aim was to investigate the effect of ASR degradation on the bending load-carrying capacity of RC beams. The concrete mesoscale model, specifically designed to reproduce ASR degradation, was modeled from three phases: coarse aggregate, mortar, and ITZ (interfacial transition zone). ASR was considered as the expansion of the coarse aggregate, and the objective was to reproduce expansion cracks with numerical analysis using the mesoscale model. Uniaxial compression tests were carried out on cylindrical specimens with ASR-accelerated deterioration to clarify the relationship between ASR deterioration and compressive properties, and the experimental results were used to identify material parameters in the mesoscale analysis model. The results showed that the model proposed in this study can reproduce the change in compressive properties due to expansion cracking. Finally, RC beams were constructed using the mesoscale model, and the effect of ASR degradation on the bending load-carrying capacity of the RC beams was investigated. The results showed that the presence of expansion cracks caused the initial stiffness of the load-displacement curves to decrease, but the bearing capacity tended to increase. This suggests that factors other than cracks, such as chemical prestress and boundary conditions in this model, have a strong influence on the load-bearing capacity of deteriorated RC beams.

An Optimized Strain-Compensated Arrhenius Constitutive Model of GH4169 Superalloy Based on Hot Compression.

A precise constitutive model is essential for capturing the deformation characteristics of the GH4169 superalloy in numerical simulations of thermal plastic forming processes. Hence, the aim of this study was to develop a precise modified constitutive model to describe the hot deformation behavior exhibited by the GH4169 superalloy. The isothermal cylindrical uniaxial compression tests of the GH4169 superalloy were carried out at temperatures of 950~1100 °C and strain rates of 0.01~10 s-1 using a Thermecmastor-200KN thermal-mechanical simulator. The original strain-stress curves were corrected by minimizing the effects of plastic heat and interfacial friction. Based on the true stress-strain curves, the original strain-compensated Arrhenius constitutive model was constructed using polynomial orders of 3, 5, and 10, respectively. The results showed that once the polynomial order exceeds the 5th, further increasing the order has little contribution to the accuracy of the model. To improve prediction ability, a higher precision Arrhenius constitutive model was established by extending a series of material parameters as functions that depend on temperature, strain, and strain rate, in which the error can be reduced from 4.767% to 0.901% compared with the classic strain-compensated Arrhenius constitutive model.

Sensitivity analysis of fibrous thick-walled tubes with mechano-sensitive remodeling fibers in homeostasis

AbstractIn this article, we apply the sensitivity analysis method to capture the influence of various parameters on the inflation pressure, axial force, and the deformation for an inflated and axially stretched cylinder. The material consists of an isotropic ground substance material reinforced with fibers that undergo a continuous and mechano-sensitive remodeling process. The input parameters of the mechanical system are assumed to be distributed according to the uniform probability distribution function. In the sensitivity analysis, we apply the Sobol method to determine how the variations of input parameters affect the inflation as well as the axial force in the cylinder. Special attention is given to the fiber remodeling process associated with a homeostatic balance between the constant fiber creation process and the strain-stabilized fiber dissolution. The results may help to understand the importance of the effect of material parameter changes, for example, due to remodeling processes in the context of diseases or recovering processes, on the overall tissue behavior.