International Journal of Mechanics and Materials in Design最新文献

Nowadays, research on the application of new materials with interesting electrical properties, such as high dielectric constant, on electrostatically-actuated microstructures has become one of the prominent research fields worldwide. One of the main disadvantages of these structures is the high required voltage. The main purpose of this paper is to demonstrate the ability of dielectric materials to reduce the required voltage of capacitive MEMS and also to intensify their softening behavior. So, a nonlinear model for a capacitive microstructure has been presented and HfO₂ has been selected as the substrate material of the capacitor whose package is filled with high pressure & dielectric constant gas. It has been shown that both of these changed options together (or each of them) can significantly reduce the required actuating voltage. The physically gradient-descent-based learning method has been used to solve the governing nonlinear equation, allowing to obtain the primary and secondary resonances in the first harmony, as well as in higher harmonies of the response. It has been shown that, growing the thickness of the dielectric layer, as well as using a high coefficient dielectric gas in the package, intensifies the softening behavior.

The aim of this paper is to investigate the nonlinear static stability of nanocomposite multilayer organic solar cells (NMOSC) on elastic foundations under axial compressive loading in thermal environment. In the previous literatures, the NMOSC consists of five isotropic layers including Al, P3HT:PCBM, PEDOT:PSS, ITO and glass. However, the disadvantages of ITO are high cost, scarcity and low chemical stability. Therefore, the graphene material is chosen to replace the ITO layer in this study. The material properties of graphene layer are assumed to depend on temperature while the elastic moduli of four remaining isotropic layers are constants. For methodology, the geometrical compatibility and nonlinear equilibrium equations are derived based on the Hamilton’s principle and classical plate theory. These equations are solved by using the Galerkin method in order to obtain the expression of critical buckling load and compressive loading – deflection amplitude curves. For geometric optimization problem, three optimization algorithms including social group optimization, basic differential evolution and enhanced colliding bodies optimization algorithms are applied to find the maximum value of the critical buckling loading of NMOSC depending on four geometrical and material variables. Parametric studies are conducted to indicate the influences of temperature increment, geometrical parameters, initial imperfection and elastic foundations on the static stability characteristics of the NMOSC.

Exact solutions for the electro-elastic static response of simply supported doubly curved (DC) shell piezoelectric bimorph energy harvesters composed of laminated cross-ply or antisymmetric angle-ply composite substrate shell subjected to distributed mechanical loads have been derived. Both series and parallel connections of the piezoelectric layers of the bimorphs are considered for deriving the exact solutions. Derivation of such exact solutions is found to be possible when the piezoelectric layers are orthotropic and generally orthotropic. All linear theories of elasticity and piezoelectricity are used in orthogonal curvilinear coordinate system and a variational principle is employed to determine the boundary conditions associated with the governing equations. The electro-elastic governing equations are solved exactly to obtain the static responses of the harvesters for different shell configurations. The effects of curvature, stacking sequence of the substrate layers and connections of the piezoelectric layers on the harvesting capability of the laminated composite DC shell bimorph harvesters are investigated. It is explored from the exact solutions that the energy harvesting capability of hyperboloid DC Shell piezoelectric bimorph is maximum among the spherical, paraboloid and hyperboloid DC laminated piezoelectric shell harvesters. The expressions of the exact solutions for the DC laminated shell type piezoelectric energy harvesters derived in this paper may be treated as the benchmark solutions for verifying numerical and experimental results.

This work is focused on developing a stochastic model to study the effect of randomness in material properties of functionally graded material, of shell structure under the effect of thermal shock. A modified and more general form of power law is utilized to functionally grade the shells along their thickness. Upon consideration of the uncertainty in the constituent properties of functionally graded material the transient temperature distribution and therefore the development of the thermal stresses in the shells are obtained and analysed. The conventionally used Monte Carlo simulation is performed for validating computationally efficient Response Surface Method based Perturbation technique, which is subsequently applied to perform stochastic analysis of thermal stresses. For various distribution patterns of the constituent materials in the functionally graded material, the randomness of thermal stresses across the thickness of the shell structure due to uncertainty in input properties is analysed. Moreover with different level of uncertainty the maximum stochasticity of thermal stresses is predicted and plotted.

Among various types of auxetic metamaterials, the perforated materials with peanut-shaped pores exhibit numerous advantages such as simple fabrication, high load-bearing capability, low stress-concentration level and flexibly tunable mechanical properties, and thus they have received much attention recently. However, one challenging is to make a high-efficient and reversible design of such metamaterials to meet diverse auxetic requirements, without the need to model them through conventional physics- or rule-based methods in time-consuming and case-by-case manner. In this study, a data-driven countermeasure is introduced by coupling back-propagation neural network (BPNN) and genetic algorithm (GA). Firstly, a dataset including microstructure-property pairs is prepared to train BPNN to determine the hidden logic mapping relationship from microstructural parameters to Poisson ratio. Then, GA is employed to optimize the mapping relationship to find the corresponding optimal solutions of microstructural parameters meeting the target Poisson’s ratio. The efficiency and accuracy of specific optimal designs is verified by the tensile experiment and finite element simulation. Subsequently, more optimal solutions corresponding to positive, zero or negative Poisson’s ratios are achieved under constrained/unconstrained conditions to accelerate the design of auxetic metamaterials by this interdisciplinary tool in which the auxetic characteristics and artificial intelligence are interconnected mutually.

Low frequency vibration assisted forming characterized with high excitation force can reduce the forming load and improve the surface quality, and has been proven to have a promising application in forming processes of high-strength metals. In this work, the plastic deformation behavior of 7075 aluminum alloy sheets under low frequency vibration was studied. The low frequency vibration assisted tension (LFVT) tests were performed on 7075-WT and 7075-T6 sheets. The obvious stress oscillation (called the stress superposition effect) and stress softening/hardening effect were observed in the experimental stress–strain relation under LFVT. After explaining the effects with the thermal activation theory, a physical constitutive model was developed by introducing the mechanical work done by low frequency vibration, a critical vibration energy value, and Hooke’s law into the thermal activation framework. The VUHARD user-subroutine was used to embed the developed model into ABAQUS/Explicit to perform the finite element (FE) analysis of the LFVT tests. The comparison of the predicted load through the FE simulation with the experimental one demonstrated the developed model could precisely describe the stress–strain relation under LFVT. The simulation result with different vibration modes also showed that the vibration softening effect gradually increased as the amplitude or frequency increased. The influence of the amplitude on vibration softening stress was much greater than that of the frequency.

High electromagnetic interference (EMI) shielding but relatively low cost is highly desired due to the severe electromagnetic pollution and cost restriction. However, no existing research can provide the optimal microstructure to these competing goals in nanocomposite foams. The present paper concentrates on the multi-objective optimization of high-efficient EMI shielding in porous graphene-reinforced nanocomposites. First, a two-scale electromagnetic constitutive model of EMI shielding effectiveness (SE) and cost is established through the effective-medium approximation with tunneling and Maxwell–Wagner-Sillars polarization effects. Then, a NSGA-II-based multi-objective optimization is developed for high EMI SE and low cost with the assistance of crowding distance and elite strategy. Compared to the experimental data of graphene/PDMS nanocomposite foam, the effective EMI SE of Pareto-optimal solutions increases by 78% while maintaining the identical cost. On the contrary, the optimal cost decreases by 76% while achieving the same EMI SE. The optimal EMI SE per unit cost is demonstrated to enhance by 405% with the experiment. The significant promotion of Pareto-optimal solutions in EMI shielding performance and efficiency is ascribed to the appropriate choice of microstructural parameters based on the multi-objective optimization. This research provides accurate instructions for the multi-objective optimal design in porous graphene-reinforced nanocomposites.

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The aim of this paper is to propose a novel computational technique of applying reliability-based design to thermoelastic structural topology optimization. Therefore, the optimization of thermoelastic structures' topology based on reliability-based design is considered by utilizing geometrical nonlinearity analysis. For purposes of introducing reliability-based optimization, the volume fraction parameter is viewed as a random variable with a normal distribution having a mean value and standard deviation. The Monte Carlo simulation approach for probabilistic designs is used to calculate the reliability index, which is used as a constraint related to the volume fraction constraint of the deterministic problem. A new bi-directional evolutionary structural optimization scheme is developed, in which a geometrically nonlinear thermoelastic model is applied in the sensitivity analysis. The impact of changing the constraint of a defined volume of the required design in deterministic problems is examined. Additionally, the impact of altering the reliability index in probabilistic problems is investigated. The effectiveness of the suggested approach is shown using a benchmark problem. Additionally, this research takes into account probabilistic thermoelastic topology optimization for a 2D L-shaped beam problem.

Topology optimization of multi-material structures under dynamic loads is implemented to minimizing compliance on polygonal finite element meshes with multiple volume constraints. A multiresolution scheme is introduced to obtain high resolution de-signs for structural dynamics problems with less computational burden. This multiresolution scheme employs a coarse finite element mesh to fulfil the dynamic analysis, a refined density variable mesh for optimization and a density variable mesh overlapping with the density variable mesh for design configuration representation. To obtain the dynamic response, the HHT-α method is employed. A ZPR (Zhang-Paulino-Ramos Jr.) update scheme is used to update the design variables in association to multiple volume constraints by a sensitivity separation technique. Several numerical examples are presented to demonstrate the effectiveness of the method to solve the topology optimization problems for mul-ti-material structures under dynamic loads.

Compliant mechanisms have increasing popularity. However, very few studies are available on transmission characteristics of compliant mechanisms in the literature. For conventional rigid-body mechanisms, the transmission angle is used to define motion quality. On contrary, the classic transmission angle formula cannot easily be employed for compliant mechanisms, unlike rigid-body mechanisms. This paper, a generalized equation that defines the transmission angle of all types of compliant four-bar mechanisms is introduced. For all configurations of partially compliant four-bar mechanisms, the formula is altered. Four theorems in some special cases are devised. Deviation of the transmission angle of a fully compliant four-bar mechanism from its rigid-body counterpart is discussed. Finally, a prototype is built and the theoretical approaches are compared with experimental results. To the best of our knowledge, this is the first study on the transmission angle of a compliant four-bar mechanism.