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 - 27 September 2024

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 >

Khaldoon M. Alhyasat^1,*, Kamarulzaman Ibrahim¹, Amer Al-Omari², Mohd Aftar Abu Bakar¹

Computer Systems Science and Engineering, Vol.39, No.1, pp. 55-67, 2021, DOI:10.32604/csse.2021.014909 - 10 June 2021

Abstract In this paper, the Rama distribution (RD) is considered, and a new model called extended Rama distribution (ERD) is suggested. The new model involves the sum of two independent Rama distributed random variables. The probability density function (pdf) and cumulative distribution function (cdf) are obtained and analyzed. It is found that the new model is skewed to the right. Several mathematical and statistical properties are derived and proved. The properties studied include moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis and moment generating function. Some simulations are undertaken to illustrate the behavior of More >

Hui Yin¹, Dejie Yu^1,2, Shengwen Yin¹, Baizhan Xia¹

CMES-Computer Modeling in Engineering & Sciences, Vol.109-110, No.3, pp. 221-246, 2015, DOI:10.3970/cmes.2015.109.221

Abstract This paper presents a new hybrid Chebyshev-perturbation method (HCPM) for the prediction of acoustic field with random and interval parameters. In HCPM, the perturbation method based on the first-order Taylor series that accounts for the random uncertainty is organically integrated with the first-order Chebyshev polynomials that deal with the interval uncertainty; specifically, a random interval function is firstly expanded with the first-order Taylor series by treating the interval variables as constants, and the expressions of the expectation and variance can be obtained by using the random moment method; then the expectation and variance of the More >

Zichun Yang^1,2,3, Kunfeng Li^1,4, Qi Cai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.95, No.2, pp. 143-171, 2013, DOI:10.3970/cmes.2013.095.143

Abstract The conventional probabilistic reliability model for structures is based on the “probability assumption” and “binary-state assumption”. These assumptions are often offset the reality of practical engineering and lead to a wrong conclusion. In fact, besides randomness, fuzziness which is different from randomness in nature is also a prevalent uncertainty factor and plays an important role in structural reliability assessment. In this paper, a novel structural reliability model with random variables and fuzzy variables is established by using the fuzzy set theory, possibility theory and probability measure for fuzzy events, based on the “mixed probability and More >