International Journal of Mechanics and Materials in Design最新文献

This research tries to render an unconventional model for thermoelastic dissipation or thermoelastic damping (TED) in circular microplates by accommodating small-scale effect into both structure and heat transfer fields. To accomplish this purpose, the modified couple stress theory (MCST) and Guyer−Krumhansl (GK) heat conduction model are utilized for providing the coupled thermoelastic equations of motion and heat conduction. The equation of heat conduction is then solved to acquire the closed-form of temperature profile in the circular microplate. By placing the extracted temperature profile in the equation of motion, the size-dependent frequency equation influenced by thermoelastic coupling is established. By conducting some mathematical manipulations, the real and imaginary parts of damped frequency are obtained. In the next stage, with the help of the description of TED based upon the complex frequency (CF) approach, an explicit single-term relation consisting of structural and thermal scale parameters is derived for making a size-dependent estimation of TED value in circular microplates. For evaluating the precision and veracity of the proposed model, the results obtained through the presented solution are compared with the ones available from the literature. In addition, by way of several examples, the pivotal role of length scale parameter of MCST and thermal nonlocal parameter of GK model in the magnitude of TED is assessed. Various numerical results are also given to place emphasis on the impact of some parameters such as boundary conditions, geometrical features, material and ambient temperature on TED value. The formulation and results provided in this study can be used as a benchmark for optimal design of microelectromechanical systems (MEMS).

There are many inevitable uncertain parameters in engineering systems, and the ignorance of these random factors results in a remarkable reduction in the dynamical system’s performance for the eigenvalue topology optimization problem. To address the problem, a reliability-based topology optimization (RBTO) model for lightweight design with frequency constraints is established, which aims to account the probabilistic behavior incurred by material properties and geometric dimensions. Then, the single loop approach is used to tackle the RBTO problem. The sensitivities of eigenvalues with respect to the design and random variables are also deduced, in which the simple and multiple eigenfrequencies are simultaneously considered. Moreover, the threshold projection approach is used to eliminate the checkerboard phenomena and grey elements for the eigenvalue topology optimization problem. Three examples are discussed to exhibit the validity of the proposed RBTO methodology.

In this study, an iterative design window (DW) search using nonlinear dynamic simulation was proposed for polymer micromachined flapping-wing nano air vehicles (FWNAVs) that can satisfy both nonlinear and unsteady design requirements, which are contradictory to each other. The DW is defined as an existing area of satisfactory solutions in the design parameter space. The present FWNAVs have a complete 2.5-dimensional structure such that they can be fabricated using polymer micromachining. The micro-wing of our FWNAVs has been designed using morphological and kinematic parameters of an actual dipteran insect. Finally, using our method, we found the DW that allowed miniaturization of the design down to 10 mm while satisfying all the design requirements. Our findings demonstrate the possibility of further miniaturizing FWNAVs down to the size of small flying insects.

The type and distribution of microstructure of metallic materials in laser additive manufacturing have an important influence on the overall mechanical properties, and how to control the location distribution of microstructure rationally through topology optimization to improve the mechanical properties of the part is one of the research focuses. In this paper, we propose a method of microstructure distribution and orientation-structure topology optimization (MDOSTO) for laser additive manufacturing. This method obtains the position distribution of the microstructure of columnar and equiaxed grains under a macroscopically optimised design. Based on the anisotropy of columnar crystals and the isotropy of equiaxed grains to obtain a microstructure with alternating grains distribution for optimal mechanical properties. The flexibility is compared with the structure of disordered grain distribution by two arithmetic examples (Miniature binding beam and Cantilever Beam), and the flexibility is reduced by 26.3% and 26.6%, respectively, which verifies the feasibility and effectiveness of the method. This method makes full use of the properties of different microstructures to improve the mechanical properties of the part.

In this work, novel four-unknown refined theories were used to evaluate the free vibration of rotating stiffened toroidal shell segments subjected to varying boundary conditions in thermal environments. The shell segments consist of a functionally graded graphene-platelet-reinforced composite (FG-GPLRC). The effective material properties of the composite were calculated using the modified Halpin–Tsai model and the mixture rule. The governing equations of motion for the shell were formulated within the novel four-unknown refined shell theory framework. The effects of centrifugal and Coriolis forces and the initial hoop tension resulting from rotation were all included. The Rayleigh–Ritz procedure and smeared stiffener technique were subsequently used to determine the natural frequencies of the shells with stiffeners. The advantages of the adopted shell theory result directly from the reduction of key unknowns without the need for the shear correction factor, and it can predict better results for FG-GPLRC structures. Finally, numerical examples were provided to validate the proposed solution and demonstrate the effects of four-unknown refined theories, material distribution patterns, boundary conditions, rotating speed, and temperature rise on the natural frequencies of toroidal shell segments.

The piezoelectric sensor in the structural health monitoring (SHM) system may be debonded due to complex service environment. However, there are little attention on the debonding behavior of piezoelectric element, which could affect the reliability of the monitoring network. This paper considers the effect of left and right debonding of sensor on receiving signal with different debonding length (2, 4, 6 and 8 mm, respectively) and debonding directions (which are 90°, 180° and 270°, respectively). A finite element model was established to simulate the interface debonding between piezo disc and Aluminium matrix, and both an experimental investigation using a real Aluminium plate is made to further comparison with the simulation results. The characteristic parameters including the amplitude and phase of time domain receiving Lamb wave signals were extracted. The simulation results show the voltage distributions of piezoelectric sensor under different debonding length and direction. In addition, receiving signal indicates that there is not a monotonic downward trend of signal amplitude with the increase of right debonding length of the sensor. And when the wave propagation direction is parallel to the sensor debonding direction (180°), the signal amplitude of the sensor is greater than that perpendicular to the debonding direction (90° and 270°).

It has a positive impact on the machining accuracy to predict precisely the thermal error caused by the temperature change for the high-speed spindle-bearing system. In this paper, the dual reciprocity method (DRM) based on compactly supported radial basis functions (CSRBFs) and the line integration boundary element method (LIM-BEM) are presented for the thermal-deformation coupling calculation. The essential idea of this method is building the thermal-deformation coupling model only by the boundary information and obtaining results by line integrals. In this process, the boundary element model discretized by the discontinuous iso-parametric quadratic boundary element is established. Then, the transient temperature is calculated by the CSRBFs-DRM, and the thermo-elastic deformation is done by the LIM-BEM, under the exact calculation of the heat generation and the thermal contact resistance. To validate the effectiveness, thermal-deformation coupling experiments are conducted. The proposed method is compared with experimental data and the finite element method. The result shows that the proposed model is more appropriate for the thermal-deformation coupling calculation for the satisfactory universality and accuracy.

As an essential step of product design, tolerance design plays a critical role in reducing manufacturing costs while ensuring mechanical assemblies’ quality and reliability. However, existing tolerance allocation approaches only are concentrated on design specification constraints during the design stage, although component degradation caused by environmental and operating conditions increases the probability of product failure during the service life. To deal with the degradation effect arising over the service life of mechanical assemblies, this paper proposes a reliability-based tolerance design approach to allocate optimal, reliable tolerances to mechanical systems. The proposed approach rewrites the tolerance allocation problem as a two-objective optimization problem with probabilistic constraints, where time-dependent reliability is incorporated to ensure the product’s reliable and consistent operation during the specified service life. Then, the proposed approach applies the non-dominated sorting genetic algorithm II and an entropy-based TOPSIS method to obtain the non-dominated optimal tolerances and the best solution, respectively. In addition, unlike previous methods, epistemic uncertainty effects are considered in this work. A modified linear degradation model is developed to include the epistemic uncertainty in the degradation model’s parameters and investigate the effects of uncertainties on reliability.Accordingly, the proposed approach employs a single-loop sampling procedure to incorporate the effects of epistemic uncertainty on the obtained optimal tolerances. Finally, to illustrate the capability of the proposed method, an industrial case study is considered, and the obtained results and performances are compared and discussed.

In this paper, the multi-objective optimization design of arc star honeycomb (ASH) and bi-directional reentrant honeycomb (BRH) is carried out by Python script to improve Young's modulus based on the lightweight of the honeycomb. A large number of models of different structural parameters are established by the Python script and analyzed by the finite element method, and then the response surface model (RSM) is established according to the results of finite element analysis. On this basis, the non-dominated sorting genetic algorithm (NSGA-II) and RSM are combined to perform multi-objective optimization of the 2D and 3D configurations of the two types of honeycomb, and the optimal set of parameters is selected by comparing the individual fitness values. The results show that after multi-objective optimization, Young's modulus of the ASH and BRH is enhanced in both 2D and 3D configurations with the smallest possible mass. In addition, the ASH has performance advantages over the BRH in 2D configuration, and BRH is better in 3D configuration. It can also be observed that the ASH and BRH have Poisson ratio adjustable properties. The results also show that this multi-objective optimization method can effectively save the analysis and calculation time. The lightweight, high-strength metamaterial is expected to be used in key fields such as aerospace.

This study focuses on the electromechanical study of functionally graded graphene reinforced piezoelectric composite (FG-GRPC) structures using the modified Halpin Tsai (MHT) micromechanics model. Two piezoelectric material matrices, namely PZT-5H and PVDF, are reinforced with GPLs, an ultralightweight and highly rigid carbonaceous nanofiller. The developed graphene reinforced piezoelectric composites (GRPC) vary in the thickness direction to form FG-GRPC, with GPLs evenly scattered throughout the material matrix. The MHT model and Rule of the mixture (ROM) are used to determine the effective modulus of elasticity, poisson’s ratio, density, and piezoelectric characteristics of the GRPC structure. The spatial variation in composition across the thickness of FG-GRPC structural tiles is determined by a simple power law distribution. The voltage and power metrics of a circuit are calculated using first order shear deformation theory and Hamilton's approach from the governing differential equations of motion. An exhaustive parametric study is undertaken with an emphasis on the effects of GPL weight percentage, material grading exponent, thickness ratio, and frequency on the circuit metrics of FG-GRPC structures. Our findings indicate that the material grading exponent and a limited number of GPLs considerably improve the circuit parameters of FG-GRPC tiles. This study will demonstrate the required physical insights for coupled modelling of microelectromechanical systems, with applications spanning pressure sensors, small ultrasonic motors, active controllers, and intelligent systems.