International Journal of Mechanics and Materials in Design最新文献

The present study focuses on the numerical and experimental investigation of a hat-stiffened composite inverted conical structure to identify its strength and stability under axial compressive loading conditions. A new design for the 3rd stage adapter with few changes in the present polar satellite launch vehicles launch vehicle is considered. An inverted conical structure with a hat-stiffened type of construction is used to obtain the higher bending stiffness. Both high-modulus and low-modulus uni-directional carbon prepreg are considered for the inverted conical structure. The experimental and numerical study is carried out on a hat-stiffened panel with a low-modulus carbon fiber prepreg material. Using the commercial software CATIA^®, the geometry of the inverted conical structure and hat-stiffened panel is generated. The structural analysis is carried out using MSC NASTRAN/PATRAN^® to determine the maximum load-carrying capacity, maximum stress and displacement values. It was observed that the strain obtained experimentally on the surface of the stiffened panel at twenty-six points using the 26-strain gauges shows good correlations with those obtained numerically.

Thermal protection system (TPS) of spacecraft requires enhanced impact resistance and thermal insulation capability while pursuing higher stiffness. Considering this, a topology optimization method of periodic microstructures with negative Poisson’s ratio and insulation performance is proposed for the filling material design of the core layer in TPS, in which homogenization approach is adopted in calculating properties of microstructures and multi-objective optimization is used for balancing the mechanical and thermal properties of the optimized microstructures. Considering the optimization design of impact-resistant structures with negative Poisson’s ratio, a novel objective function is proposed to reduce the influence of iteration steps on the optimization results. For the topology optimization of insulation structures, a suitable objective function is selected by comparing the optimization results of two existing objectives. Based on the weighted linear combination, a multi-objective microstructural topology optimization method is proposed, simultaneously incorporating negative Poisson’s ratio and insulation performance. By adjusting the weighting coefficient of the objective functions, the microstructure of the materials can be designed according to different performance requirements. Several 2D and 3D optimized microstructures with both better impact resistance and insulation performance of TPS are successfully designed. In addition, the 2D optimized microstructures under different weights are assembled into sandwich structures, and the compression and heat conduction are simulated to further illustrates the validity and flexibility of the proposed method considering requirements of both impact-resistant and thermal insulation performances of sandwich structures.

Variance global sensitivity (VGS) is defined by the mean square difference between output expectation and conditional one on input realization, and it can calculate the mean contribution of the input within its distribution region and guide the effective modulation of output variance. The Monte Carlo simulation (MCS) and quasi MCS are commonly used to estimate VGS, but they are time-consuming respectively due to double-loop framework and computation related to input dimension. Thus, a novel method is proposed to estimate VGS by elaborately using Bayesian updating. In the proposed algorithm, the input realizations are firstly treated as observations to construct a likelihood function. Then by Bayesian updating, all conditional output expectations on different input realizations, which are required in estimating VGS and most time-consuming, can be obtained as the posterior and estimated by the sample of simulating the output expectation. The proposed algorithm shares the sample of solving output expectation to obtain all conditional ones required for solving VGS, which makes the computational effort of estimating VGS equivalent to that of estimating output expectation, thus improving the efficiency of estimating VGS. Numerical and engineering examples fully substantiate the novelty and effectiveness of this algorithm.

The topology optimization methodology is widely utilized in industrial engineering for designing lightweight and efficient components. In this framework, considering natural frequencies is crucial for adequately designing components and structures exposed to dynamic loads, as in aerospace or automotive applications. The scientific community has shown the efficiency of Bi-directional Evolutionary Structural Optimization (BESO), showcasing its ability to converge towards optimal solid-void or bi-material solutions for a wide range of frequency optimization problems in continuum structures. However, these methods show limits when the complexity of the domain volume increases; thus, they are well-suited for academic case studies but may fail when dealing with industrial applications that require more complex shapes. The connectivity of the structures resulting from the optimization also plays a fundamental role in choosing the best optimization approach, as some available commercial and open-source codes nowadays return unfeasible sparse structures. An improved voxel-based BESO algorithm has been developed in this work to cope with current limits in lightweight structure optimization. A significant case study has been developed to evaluate the performances of the new methodology and compare it with existing algorithms. In contrast to previous studies, the method we developed guarantees that the final structure respects constraints on the initial design volume and that the structure’s connection is preserved, thus enabling the manufacturing of the component with Additive Manufacturing technologies. The proposed approach can be complemented by smoothing algorithms to obtain a structure with externally appealing surfaces.

A multi-objective topological optimization model is proposed for anisotropic multi-material microstructures with negative Poisson’s ratio (NPR) and high thermal conductivity using isogeometric analysis (IGA) approach and alternating active phases algorithm. The effective elasticity matrix and heat conductivity matrix are calculated to represent the metamaterial and thermal conduction properties of the microstructures, respectively. The weighting factor is defined to adjust the proportion of NPR and heat transfer performance in the optimization objective. The validity of the proposed model is confirmed by structural performance analysis. Additionally, the IGA-based optimal topological structures, which have continuous boundary and low intermediate density without sensitivity filtering, have been produced using 3D printing. The effects of weighting factor, the number of material types, and anisotropic parameters on the optimal topological structures and properties are investigated. Either increasing the weighting factor or upgrading to more materials with superior properties can boost the thermal conductivity of the microstructure. Compared to isotropic multi-material microstructures, it is recommended that the range for Poisson’s ratio factor, heat conductivity factor be 1–1.5 and 1.25–1.5 to enhance the performance of microstructures, respectively.

This study explores the nonlinear free vibration of a nanobeam within the framework of nonlocal elasticity theory. It incorporates the materials nonlinear behavior, von Kármán strains, and surface elasticity theory. The stress–strain relationship in this study includes the quadratic material nonlinearity, which is typically ignored in previous research. The governing equations are derived through the application of Hamiltons principle. Using Galerkins method on the partial differential equations, the nonlinear differential equation governing the system is derived. The cubic nonlinearity in this equation arises from geometrical effects, while the quantic nonlinearity is attributed to material nonlinearity. The derived nonlinear differential equation is addressed utilizing the modified Homotopy Perturbation method. This approach yields the nonlinear time response and nonlinear frequency of the nanobeam, taking into account the effects of material nonlinearity and surface phenomena. The findings demonstrated the combined impact of surface effects and nonlinear material behavior on the nonlinear time response and frequency of the nanobeam. The natural frequency of the nanobeam was analyzed using the Elman neural network. Various inputs were fed into the network, and its output was compared with the exact solution for the natural frequency to assess accuracy. Additionally, the influence of material nonlinearity and surface effects on the phase trajectories of the nanobeam is examined. For validation purposes, the results are compared with those obtained using the fourth-order Runge–Kutta numerical method and previous studies.

The performances of a hydrostatic bearing using the tapered-spool restrictors with appropriate design parameters is superior to other types of pressure compensation, that is the largest stiffness obtained under the lowest power consumption of supplying lubricant. However, the determination of design parameters is difficult, moreover, the simplification of the calculation formula will cause errors. Therefore, this study presents a method for identifying actual design parameters of the single‐action tapered-spool restrictor for actant values. Also, the influences of design parameters on the relationships between flow rate and pressure drop of this type restrictors are studied by both theoretical and experimental analyses. There are three design parameters that affect the characteristics of the tapered-spool restrictor, namely restriction parameter, compliance parameter, and restriction length ratio. Since both compliance parameter and restriction length ratio are functions of supply pressure, design parameters of a restrictor are determined simultaneously by solving a set of identification equations individually for the nominal value of each supply pressure. These identification equations are obtained by minimizing the sum of squared errors between the actual flow rate measured from experimental data and the flow rate calculated from the identification equations. Additionally, the advantages of the tapered-spool restrictors compared with other pressure compensation methods as well as the difficulties and errors in calculating design parameters are further elaborated in this study. Therefore, in order to design the appropriate parameters to match the hydrostatic bearing, the design parameters need to be identified when designing and calibrating such restrictors.

In this paper, a method to directly determine explicit expressions of the exact general solutions for isotropic rectangular beam is provided. If the spanwise variation of the bending moment is smooth, the exact solution of the stress function can be expressed in the form of infinite series, whose each term is the product of the bending moment or its higher derivatives and polynomial involving only the longitudinal coordinates, while the polynomials are independent of the distributed loads. First, the explicit exact expression of the stress function is derived by solving recurrence formulae. Then, the convergence and accuracy of the formulae is estimated by retaining different terms. Finally, formulae of the stress and displacement fields are applied to some classical examples with the cases distributed loads in simple polynomials and sine form, and the results obtained are in perfect agreement with the existing exact theory.