Variation Of Material Parameters Research Articles

Chaos and resonance of nonlinear FG shallow shells reinforced by oblique stiffeners

This paper presents an analysis of the nonlinear dynamics of functionally graded (FG) shallow shells that are simply supported, reinforced with oblique stiffeners, and subjected to external excitation. The properties of these oblique stiffened functionally graded (OSFG) shallow shells vary across their thickness, following a power law distribution based on the volume fractions. Employing the first-order shear deformation theory (FSDT) coupled with the von Kármán nonlinear strain-displacement relations, the derivation of the nonlinear equations of motion is accomplished through the application of Hamilton's principle. The model of FG shallow shells reinforced with oblique two-series stiffeners is developed, allowing for the angles of the two stiffeners to be similar or different from each other. In this context, the employment of the first-order shear deformation theory (FSDT) results in the enhancement of the complexity in modeling the oblique stiffeners. Galerkin's method is applied to discretize the given equations, converting them into a nonlinear dynamical system with two degrees of freedom. This system incorporates both quadratic and cubic nonlinearities and considers the effects of external excitation. The analysis of this research particularly focuses on the resonant scenario involving principal resonance and 1:1 internal resonance. Through the asymptotic perturbation method, a four-dimensional nonlinear averaged equation is obtained. For the first time, a numerical investigation of the research reveals critical insights into the behavior of the system, such as waveforms, phase diagrams, and Poincaré maps, highlighting the effects of different angles of the stiffeners and variations of material parameters on the nonlinear dynamics of these shells.

Numerical Evaluation of Hydroformed Tubular Adhesive Joints under Tensile Loads

Adhesive joints are widespread in the aerospace, aeronautics, and automotive industries. When compared to conventional mechanical joints, adhesive joints involve a smaller number of components, reduce the final weight of the structure, enable joining dissimilar materials, and resist the applied loadings with a more uniform stress state distribution compared to conventional joining methods. Hydroformed tubular adhesive joints are a suitable solution to join tubes with identical cross-sections, i.e., tubes with the same dimensions, although this solution is seldom addressed in the literature regarding implementation feasibility. This work aims to numerically analyze, by cohesive zone modelling (CZM), hydroformed tubular adhesive joints between aluminum adherends subjected to tensile loads, considering the variation of material parameters (type of adhesive) and geometrical parameters. Initially, a validation of the proposed CZM approach is carried out against experimental data. Next, the aim is to numerically evaluate the tensile characteristics of the joints, measured by the maximum load (Pm) and energy of rupture (ER), considering the main geometrical parameters (outer tube diameter of the non-hydroformed adherend or dENHA, overlap length or LO, tube thickness or tAd, and joggle angle or q). CZM validation was successfully performed. The numerical study determined that the optimal geometry uses the adhesive Araldite® AV138, higher dENHA and LO highly benefit the joint behavior, tAd has a moderate effect, and q has negligible influence on the results.

Comprehensive investigation on modelling of low-velocity impact damage response of composite laminates − Experimental correlation and assessment

Low velocity impact (LVI) experiments are performed to provide correlations with the simulation results based on numerical modeling of the intralaminar matrix damage and interlaminar delamination damage of composite laminates. The good agreement between the numerical simulation and experimental results provided validation of the numerical modeling approach. The validated numerical modeling is then used in the parametrical assessment of the influence of material properties and model- related parameters on the global LVI deformation responses and the evolution characteristics of the intralaminar and interlaminar damage. It is observed that the element deletion method is not suitable to resolve the element distortion problem induced by the progressive damage. The numerical convergence problem caused by element distortion can be resolved with appropriate selection of threshold value of the critical damage parameter without element deletion. The parametrical numerical investigations showed that the variations of material properties and parameters related to interlaminar damage exhibited significant influence on the LVI global deformation responses and progressive damage evolutions. Meanwhile, insignificant influence of the material properties related to the intralaminar damage was observed for the normal variations within material scatters.

Implications of using simplified finite element meshes to identify material parameters of articular cartilage

The objective of this work was to determine the effects of using simplified finite element (FE) mesh geometry in the process of performing reverse iterative fitting to estimate cartilage material parameters from in situ indentation testing. Six bovine tibial osteochondral explants were indented with sequential 5 % step-strains followed by a 600 s hold while relaxation force was measured. Three sets of porous viscohyperelastic material parameters were estimated for each specimen using reverse iterative fitting of the indentation test with (1) 2D axisymmetric, (2) 3D idealized, and (3) 3D specimen-specific FE meshes. Variable material parameters were identified using the three different meshes, and there were no systematic differences, correlation to basic geometric features, nor distinct patterns of variation based on the type of mesh used. Implementing the three material parameter sets in a separate 3D FE model of 40 % compressive strain produced differences in von Mises stresses and pore pressures up to 25 % and 50 %, respectively. Accurate material parameters are crucial in any FE model, and parameter differences influenced by idealized assumptions in initial material property determination have the potential to alter subsequent FE models in unpredictable ways and hinder the interpretation of their results.

Erratum: Effect of continuously variable material parameters on dynamic stability of viscoelastic dielectric elastomers

Abstract Original article: EPL, 141 (2023) 16003.

CCZM‐based fatigue analysis and reliability assessment for wind turbine blade adhesive joints considering parameter uncertainties

AbstractWind turbine blades are complex structures composed of multiple bonded components. The fatigue performance of these adhesive joints is crucial for ensuring operational safety over the blade's lifespan. Traditional structural fatigue analysis methods are inadequate for evaluating the fatigue properties of these joints due to the unique characteristics of adhesive materials. Variations in material and dimensional parameters, as well as fluctuating operational loads, further complicate the fatigue analysis of adhesive joints in wind turbine blades. To tackle this issue, this study introduces a fatigue analysis and reliability assessment method for the adhesive joints of wind turbine blades, employing the Cyclic Cohesive Zone Model (CCZM) and accounting for parameter uncertainties. Specifically, a novel methodology for fatigue analysis based on the CCZM is presented. The methodology is programmatically implemented to obtain a fatigue life dataset through multiple simulations, considering uncertainties in material parameters, adhesive dimensions, and loads. Subsequently, a fatigue reliability model is formulated to evaluate the fatigue reliability of adhesive joints in wind turbine blades under different parameter conditions, and the sensitivity of fatigue reliability to each parameter is investigated. The findings offer valuable insights for improving the safety and reliability of adhesive structures in wind turbine blades.

Investigation of Temperature Impact on Friction Conditions in Running Production of Automotive Body Components

During the running production of automotive body components drifts in the process window is seen causing problems with non-conforming parts. Up until now, these drifts have been counter-acted based on the knowledge and experience of the press line operators. This experience-based process control will however become more troublesome in the future as recycled material grades will undoubtedly present larger in-coil variations in material parameters and effect also the friction conditions from component to component.The following study will present two cases from production of the Volvo XC60. For the two cases, the initial simulations made for the components showed a safe part, but during running production failure occurred suspected to be due to temperature effects in the tribology system. The study will furthermore present updated simulations considering developing thermal effects to replicate the failures, as well as present both standard and thermal simulations of the adjustments made in production.

Creating a Virtual Shadow of the Manufacturing of Automotive Components

Within the automotive industry, there is an increasing demand for a paradigm shift in terms of which materials are used for the manufacturing of the automotive body. Global climate goals are forcing a rapid adaption of new, advanced, sustainable material grades such as the fossil free steels and materials containing higher scrap content. With the introduction of these new and untested materials, methods for accounting for variation in material properties are needed directly in the press lines.The following study will focus on creating an initial virtual shadow of the manufacturing of a Volvo XC90 inner door panel through the application of Artificial Neural Networks (ANN). The virtual shadow differs from the concept of the digital twin by only being a virtual representation of the production line, with training data generated exclusively by numerical simulations, and having no automated communication with the physical press line control system. The virtual shadow can be used as an assistance to the press line operators to see how different press line settings and material parameter variations will impact the quality of the stamped component. The study aims to validate the virtual shadow through accurate predictions of the material draw-in measured in the physical press line.

Study on the Equivalent Stiffness of a Local Resonance Metamaterial Concrete Unit Cell

This paper addresses the pressing scientific problem of accurately predicting the equivalent stiffness of local resonance metamaterial concrete unit cells. Existing theoretical models often fail to capture the nuanced dynamics of these complex systems, resulting in suboptimal predictions and hindering advancements in engineering applications. To address this deficit, this paper proposes a novel two-dimensional theoretical vibration model that incorporates shear stiffness, a crucial yet often overlooked parameter in previous formulations. Motivated by the need for improved predictive accuracy, this paper rigorously validates a new theoretical model through numerical simulations, considering variations in material parameters and geometric dimensions. The analysis reveals several key findings: firstly, the equivalent stiffness increases with elastic modulus while the error rate decreases, holding geometric parameters and Poisson’s ratio constant. Secondly, under fixed geometric parameters and coating elastic modulus, the equivalent stiffness rises with an increasing Poisson’s ratio, accompanied by a decrease in error rate. Importantly, this paper demonstrates that the proposed model exhibits the lowest error rate across all parameter conditions, facilitating superior prediction of equivalent stiffness. This advancement holds significant implications for the design and optimization of metamaterial structures in various engineering applications for vibration isolation, with promising enhancements of performance and efficiency.

Towards design of a gradient locally resonant acoustic metasurface for negative reflection

Gradient acoustic metasurfaces are a class of subwavelength metamaterials that provide unprecedented opportunities to control the direction of reflected and refracted waves, including negative angles in accordance with the diffraction theory and generalized law of reflection. This opens new possibilities in designing metasurfaces for many practical applications in wave engineering. In this work, locally resonant acoustic metamaterials are considered as the building units of the metasurface, which owe their favorable properties to local resonances at the microstructural level. Non-trivial reflection angles are realized by introducing suitable phase modulations along the wave path. The required phase shift is achieved through the variation of geometrical and material parameters of the metamaterial unit cells. The negative reflection of ultrasound waves is demonstrated numerically by means of a finite-element analysis of a fluid-metasurface-solid structure. The results of this study provide new insights and detailed guidelines for designing metasurfaces for controllable acoustic wave reflection.

Probability distribution of write failure in a memory cell array consisting of magnetic tunnel junction elements with distributed write error rates

Write failure (WF) is a major reliability issue for applications of magnetoresistive random access memory (MRAM), and much effort has been devoted to reducing the write error rate (WER), which is the probability of write failures of a memory cell. Recently, it was shown that the WER of MRAM obeys a skewed probability distribution even though the variation in material parameters obeys a normal distribution. However, little is known about the effect of WER distribution on WF in a memory cell array. Here, we study WF in a memory cell array consisting of magnetic tunnel junction elements with distributed WERs based on numerical simulations. We simulated Bernoulli trials of writing, assuming that the WER obeys a beta distribution. The results show that for typical writing patterns, WF in a memory cell array obeys a binomial distribution, with the mean of the WER as the probability of success. The statistical properties of WF in a memory cell array are not affected by the variance and skewness of the WER. The results provide a basic understanding of the statistical properties of WF in a memory cell array and will be useful for the development of computing systems that exploit erroneous memories.

Optimal modeling of perovskite solar cell with graphene oxide as hole transport layer using L32 (28) Taguchi design

Material parameter variations are one of the main contributors affecting the performance of solar cell devices, thus, Taguchi design is employed to optimize the material parameters in attaining maximum power conversion efficiency (PCE). This paper discusses the optimal modeling of the Perovskite solar cell (PSC) with graphene oxide (GO) hole transport layer (HTL) using L32 (28) Taguchi design. The device simulation is conducted using a solar cell capacitance simulator (SCAP), whereas the L32 (28) Taguchi design is used for device optimization. The final results reveal that the L32 (28) Taguchi design has significantly optimized the device parameters in which FTO thickness, FTO donor concentration, TiO2 thickness, TiO2 donor concentration, CH3NH3PbI3-xClx thickness, CH3NH3PbI3-xClx donor concentration, GO thickness and GO acceptor concentration are predictively set to 0.1 µm, 1 x 1020 cm-3, 0.03 µm, 1 x 1020 cm-3, 0.9 µm, 1 x 1020 cm-3, 0.03 µm and 1 x 1020 cm-3 correspondingly. Analysis of variance (ANOVA) reveals that the CH3NH3PbI3-XClX thickness is the most dominant input parameter affecting the PCE of the device. The optimized input parameters yield the maximum attainable PCE of 35.91% with a signal-to-noise ratio (SNR) of 31.11 dB.

Simulation workflow for fault detection and localization in sandwich panels

Sandwich panels in civil engineering have the advantage of a high flexural strength and thermal insulation while providing a very low density. They are made of two steel sheets and a core of polyurethane or polyisocyanurate foam. Due to the manufacturing process, the panels occasionally have defects, that are not visible from the outside. These may cause visible damages after installation in building facades. This paper presents a workflow for the detection and localization of the defects exploiting their influence on the response to a dynamic excitation. It uses an experimentally validated finite element model, feature engineering, and a neural network. The workflow initiates with the development and validation of a mechanical finite element model using experimental data. The model serves as the foundation for a simulation campaign, examining both defect-free and models with defects. The simulation process incorporates variations in material parameters based on experimentally obtained standard deviations, ensuring a robust representation of real-world uncertainties. The resultant simulation dataset is subjected to a feature engineering process encompassing time and frequency domain features. This multi-domain feature extraction enhances the dataset’s informativeness. The feature dataset is employed to train a neural network for two primary use cases: Firstly, to differentiate between faulty and fault-free models, providing an accurate fault detection mechanism. And secondly, to localize faults within the model. The effectiveness of this approach is demonstrated using various testing datasets. The proposed methodology represents a combination of a synthetically created database from a validated finite element model, multi-domain feature engineering, and neural network capabilities. It offers a methodology for fault detection and localization in sandwich panels. Using a dataset of several hundred samples, a detection rate of 94.8 % and a localization rate of 81.3 % are achieved in this work. In practical use, this approach can lead to significant reduction of customer complaints, and savings in replacement costs and hence carbon footprint.

Nonlinear forced vibrations of functionally graded three-phase composite cylindrical shell subjected to aerodynamic forces, external excitations and hygrothermal environment

In this paper, the new functionally graded three-phase composite cylindrical shell is assumed as a common structure in the carrier rocket in the future, and we creatively study the nonlinear forced vibration of this cylindrical shell considering the interaction of different factors in the complex operating environment, including the aerodynamic forces, external excitations, and hygrothermal environment. Based on the first-order shear deformation theory, Von-Karman geometric nonlinear theory, and Hamilton's principle, we derive the nonlinear partial differential equations of motion of the functionally graded three-phase composite cylindrical shell. Considering the axisymmetry of the perfect circular shell, there is a 1:1 internal resonance between the conjugate modes of this cylindrical shell. On this basis, the nonlinear forced vibration of the cylindrical shell is investigated by a combination of Galerkin's method and the pseudo-arc length continuation method. Matcont toolbox can directly solve the ordinary differential equations to obtain the nonlinear frequency response curves. The method can effectively obtain both stable and unstable solutions, avoiding the mathematical difficulties encountered in the formulation process, and facilitating the study of the effects of parametric variables on the resonance response in complex environments. The results show that the variation of material parameters and the complex environment have important effects on the nonlinear resonance response of functionally graded three-phase composite cylindrical shell.

Cause–effect relationship between model parameters and damping performance of hydraulic shock absorbers

Despite long-term research and development of modern shock absorbers, the effect of variations of several crucial material and model parameters still remains dubious. The goal of this work is therefore a study of the changes of shock absorber dynamics with respect to typical parameter ranges in a realistic model. We study the impact of shim properties, as well as geometric features such as discharge coefficients and bleed orifice cross section. We derive cause–effect relationships by nonlinear parameter fitting of the differential equations of the model and show digressive and progressive quadratic damping curves for shim number and thickness, sharp exponential curves for discharge coefficients, and leakage width, as well as a linear decrease of damping properties with bleed orifice area. Temperature increase affecting material properties, such as density and viscosity of the mineral oil, is found to have a mostly linear relationship with damping and pressure losses. Our results are not only significant for the general understanding of shock absorber dynamics, but also serve as a guidance for the development of specific models by following the proposed methodology.

Movement tracking using asymmetric impedance meta-surface based on Helmholtz resonator

Acoustic sensors are one of the most commonly used sensors for detecting obstacles in mobile robots and vehicles by providing distance information of the obstacles in their path. However, although a single sensor can determine an object's distance, two or more sensors must be used to detect the movement of an object. Here, we propose a method to determine the distance and direction of an object traveling to a single sensor using an asymmetrically formed acoustic field. The acoustic field is formed by impedance-varying acoustic meta-surface using an asymmetric Helmholtz resonator array. We present multi-physics simulations using COMSOL and experimental results which show the movement of an acoustic source using a single microphone. Also, we present, explicitly, the effective material parameter variation made by the meta-surface with varying degrees of internal neck lengths.

Stochastic modeling of spatially-dependent elastoplastic parameters in 316L stainless steel produced by direct energy deposition

The stochastic modeling and calibration of an anisotropic elasto-plastic model for additive manufacturing materials are addressed in this work. We specifically focus on 316L stainless steel, produced by directed energy deposition. Tensile specimens machined from two additive manufactured (AM) box-structures were used to characterize material anisotropy and random spatial variations in elasticity and plasticity material parameters. Tensile specimens were cut parallel (horizontal) and perpendicular (vertical) to the AM deposition plane and were indexed by location. These results show substantial variability in both regimes, with fluctuation levels that differ between specimens loaded in the parallel and perpendicular build directions. Stochastic representations for the stiffness and Hill’s criterion coefficients random fields are presented next. Information-theoretic models are derived within the class of translation random fields, with the aim of promoting identifiability with limited data. The approach allows for the constitutive models to be generated on arbitrary geometries, using the so-called stochastic partial differential approach (to sampling). These representations are then partially calibrated using the aforementioned experimental results, hence enabling subsequent propagation analyses. Sampling is finally exemplified on the considered structure.

Residual Stress Testing and Simulation Analysis of Crystal Structures of Electronic Device Materials

In this paper, we analyze the residual stress of different components of the crystal structures of electronic device materials following exposure to elevated temperatures using a combination of experimental tests and finite element simulations. X-ray diffraction (XRD) and LXRD micro-area residual stress analyzer were employed to determine the residual strain and stress of the CBGA sample encapsulation cover and solder joints. Subsequently, the experimental data were utilized to verify the accuracy of the simulation. The discrepancy between experimental measurements and simulation outcomes of the residual stress following reflow soldering of CBGA-assembled micro-solder joints is below 14%. The analysis also included thermal warping deformation of the CBGA encapsulation cover and how the residual stress was influenced by the diameter, spacing, and height of the solder joints. The study reveals that the residual stress following reflow soldering of BGA solder joints is non-uniformly distributed within the array. Within a single solder joint, residual stress gradually increases in distribution from its middle to the point where it make contact with the PCB and chip, with the highest level of residual stress observed where the solder joint contacts the chip. The variation in material parameters, such as the coefficient of thermal expansion, is the primary cause of thermal warping deformation on the surface of CBGA encapsulation covers. Three primary factors significantly impact the residual stress on BGA solder joints: solder joint diameter, spacing, and height. The maximum value is inversely proportional to the height of the solder joints and the residual stress. Conversely, the diameter and spacing of the joints are positively proportional to the highest value. When the diameter of the solder joint is increased from 0.55 mm to 0.75 mm, the maximum residual stress in the BGA solder joint increases from 37.243 MPa to 36.835 MPa. Conversely, increasing the height of the solder joint from 0.36 mm to 0.44 mm reduces the stress from 39.776 MPa to 36.835 MPa.

Design and simulation of a highly efficient CuBi2O4 thin-film solar cell with hole transport layer

The advancement of thin-film photovoltaic technologies is increasing extensively in today’s world owing to their outstanding optical properties, simple fabrication process, and low-cost. In this work, a solar cell capacitance simulator in one-dimension (SCAPS-1D) has been used to evaluate the output parameters of the heterojunction CuBi2O4-based solar cells with various hole transport layers (HTLs). It is revealed that a p-type cuprous oxide (Cu2O) semiconductor as an HTL ensures proper band alignment at Cu2O/CuBi2O4 interface. The recombination due to minority electrons at the rear side of the CuBi2O4 solar structure with Cu2O HTL can be diminished notably than the device with other HTLs, thus improving the overall outputs of the suggested Cu2O/CuBi2O4/CdS/FTO heterostructure. To realize the behaviors of the proposed PV cell, the thickness and carrier concentration of various films, bulk defects, interface defects, cell resistances, and rear electrode work function of the anticipated CuBi2O4 thin-film photovoltaic device have been optimized. The recombination rates at the interfaces in the proposed heterostructure are also calculated. Moreover, to outline the effects of device input parameters of various materials on vital PV output parameters, adaptable machine learning algorithms have been used to train, test, and calculate the output datasets. High accuracy and low error metrics are confirmed for both the train and test datasets. With 1.0 μm absorber thickness, the efficiency of 29.2% with open-circuit voltage (Voc) of 1.02 V, short-circuit current density (Jsc) of 32.49 mA/cm2, and fill factor (FF) of 87.91% is found for the anticipated solar cell. This investigation suggests that the Cu2O can be effectively employed to scheme a highly efficient, stable, and economical CuBi2O4 solar device.

Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties

Fibril-reinforced poroviscoelastic material models are considered state-of-the-art in modeling articular cartilage biomechanics. Yet, cartilage material parameters are often based on bovine tissue properties in computational knee joint models, although bovine properties are distinctly different from those of humans. Thus, we aimed to investigate how cartilage mechanical responses are affected in the knee joint model during walking when fibril-reinforced poroviscoelastic properties of cartilage are based on human data instead of bovine. We constructed a finite element knee joint model in which tibial and femoral cartilages were modeled as fibril-reinforced poroviscoelastic material using either human or bovine data. Joint loading was based on subject-specific gait data. The resulting mechanical responses of knee cartilage were compared between the knee joint models with human or bovine fibril-reinforced poroviscoelastic cartilage properties. Furthermore, we conducted a sensitivity analysis to determine which fibril-reinforced poroviscoelastic material parameters have the greatest impact on cartilage mechanical responses in the knee joint during walking. In general, bovine cartilage properties yielded greater maximum principal stresses and fluid pressures (both up to 30%) when compared to the human cartilage properties during the loading response in both femoral and tibial cartilage sites. Cartilage mechanical responses were very sensitive to the collagen fibril-related material parameter variations during walking while they were unresponsive to proteoglycan matrix or fluid flow-related material parameter variations. Taken together, human cartilage material properties should be accounted for when the goal is to compare absolute mechanical responses of knee joint cartilage as bovine material parameters lead to substantially different cartilage mechanical responses.