Rajan Aravind^1,2, Sundararajan Natarajan¹, Krishnankutty Jayakumar², Ratna Kumar Annabattula^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 997-1032, 2024, DOI:10.32604/cmes.2024.053047

Abstract Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications. This is all the more important when elements composed of brittle materials are exposed to dynamic environments, resulting in catastrophic fatigue failures. The authors propose the application of a non-intrusive polynomial chaos expansion method for probabilistic studies on brittle materials undergoing fatigue fracture when geometrical parameters and material properties are random independent variables. Understanding the probabilistic nature of fatigue fracture in brittle materials is crucial for ensuring the… 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 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)… More >

P. Gayathri¹, R. Ganguli^1,2

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 119-138, 2011, DOI:10.3970/sdhm.2011.007.119

Abstract The effect of random variation in composite material properties on the reliability of structural damage detection is addressed in this paper. A composite plate is considered as the structure and a finite element model is used for the simulation. Damage growth due to cyclic loading is addressed. Matrix crack induced delamination is emphasized in this paper. Thresholds for the damage accumulation are found using finite element simulations so that the structure can be subjected to inspections and removed from service safely. Uncertainty effects of composite material properties on the response of the structure are quantified More >