K. Umesh¹, R. Ganguli¹

CMC-Computers, Materials & Continua, Vol.41, No.3, pp. 215-240, 2014, DOI:10.3970/cmc.2014.041.215

Abstract Fractal dimension based damage detection method is investigated for a composite plate with random material properties. Composite material shows spatially varying random material properties because of complex manufacturing processes. Matrix cracks are considered as damage in the composite plate. Such cracks are often seen as the initial damage mechanism in composites under fatigue loading and also occur due to low velocity impact. Static deflection of the cantilevered composite plate with uniform loading is calculated using the finite element method. Damage detection is carried out based on sliding window fractal dimension operator using the static deflection. Two dimensional homogeneous Gaussian random… More >

L.B. Borkowski¹, K.C. Liu¹, A. Chattopadhyay¹

CMC-Computers, Materials & Continua, Vol.37, No.3, pp. 161-193, 2013, DOI:10.3970/cmc.2013.037.161

Abstract The microstructural variation in fiber-reinforced composites has a direct relationship with its local and global mechanical performance. When micromechanical modeling techniques for unidirectional composites assume a uniform and periodic arrangement of fibers, the bounds and validity of this assumption must be quantified. The goal of this research is to quantify the influence of microstructural randomness on effective homogeneous response and local inelastic behavior. The results indicate that microstructural progression from ordered to disordered decreases the tensile modulus by 5%, increases the shear modulus by 10%, and substantially increases the magnitude of local inelastic fields. The experimental and numerical analyses presented… More >

Leiting Dong^1,2, Salah H. Gamal³, Satya N. Atluri^2,4

CMC-Computers, Materials & Continua, Vol.37, No.1, pp. 1-21, 2013, DOI:10.3970/cmc.2013.037.001

Abstract In this paper, a simple and reliable procedure of stochastic computation is combined with the highly accurate and efficient Trefftz Computational Grains (TCG), for a direct numerical simulation (DNS) of heterogeneous materials with microscopic randomness. Material properties of each material phase, and geometrical properties such as particles sizes and distribution, are considered to be stochastic with either a uniform or normal probabilistic distributions. The objective here is to determine how this microscopic randomness propagates to the macroscopic scale, and affects the stochastic characteristics of macroscopic material properties. Four steps are included in this procedure: (1) using the Latin hypercube sampling,… More >

Fangyi Li¹, Guangyao Li^2,3, Guangyong Sun², Zhen Luo⁴, Zheng Zhang²

CMC-Computers, Materials & Continua, Vol.19, No.1, pp. 37-56, 2010, DOI:10.3970/cmc.2010.019.037

Abstract The focus of this paper is concentrated on multi-disciplinary and multi-objective optimization for thin walled beam systems considering safety, normal mode, static loading-bearing and weight, in which the uncertainties of the parameters are described via intervals. The size and shape of the cross-section are treated as design parameters during optimization. Considering the lightweight and safety, the design problem is formulated with two individual objectives to measure structural weight and maximum energy absorption, respectively, constrained by the average force, normal mode and maximum stress. The optimization problem with uncertainties is further transformed into a deterministic optimization based on interval number programming.… More >

C. Jiang¹, Y.C. Bai¹, X. Han^1,2, H.M. Ning¹

CMC-Computers, Materials & Continua, Vol.18, No.1, pp. 21-42, 2010, DOI:10.3970/cmc.2010.018.021

Abstract In this paper, an efficient interval optimization method based on a reliability-based possibility degree of interval (RPDI) is suggested for the design of uncertain structures. A general nonlinear interval optimization problem is studied in which the objective function and constraints are both nonlinear and uncertain. Through an interval order relation and a reliability-based possibility degree of interval, the uncertain optimization problem is transformed into a deterministic one. A sequence of approximate optimization problems are constructed based on the linear approximation technique. Each approximate optimization problem can be changed to a traditional linear programming problem, which can be easily solved by… More >

F.Y.Li^1,2, G.Y.Li¹

CMC-Computers, Materials & Continua, Vol.15, No.3, pp. 199-220, 2010, DOI:10.3970/cmc.2010.015.199

Abstract In this paper, an uncertain multi-objective optimization method is suggested to deal with crashworthiness design problem of vehicle, in which the uncertainties of the parameters are described by intervals. Considering both lightweight and safety performance, structural weight and peak acceleration are selected as objectives. The occupant distance is treated as constraint. Based on interval number programming method, the uncertain optimization problem is transformed into a deterministic optimization problem. The approximation models are constructed for objective functions and constraint based on Latin Hypercube Design (LHD). Thus, the interval number programming method is combined with the approximation model to solve the uncertain… More >

TakehikoNakama¹

CMC-Computers, Materials & Continua, Vol.14, No.1, pp. 35-60, 2009, DOI:10.3970/cmc.2009.014.035

Abstract Random noise perturbs objective functions in practical optimization problems, and genetic algorithms (GAs) have been proposed as an effective optimization tool for dealing with noisy objective functions. In this paper, we investigate GAs in a variety of noisy environments where fitness perturbation can occur in any form-for example, fitness evaluations can be concurrently disturbed by additive and multiplicative noise. We reveal the convergence properties of GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms in noisy environments. We compute the one-step transition probabilities of the Markov chain and show that the chain has… More >