Evolution of the distribution function of the composition of oxide inclusions for the growth model of a disperse system formed during deoxidation

1991 ◽  
Vol 62 (4) ◽  
pp. 157-163
Author(s):  
Zofia Kalicka
Keyword(s):  
Distribution Function ◽  
Growth Model ◽  
Disperse System ◽  
Oxide Inclusions

Formulation of a Polynomial Stochastic Fatigue Crack Growth Model

2014 ◽  
Vol 909 ◽  
pp. 467-471 ◽  
Author(s):  
C.C. Ni
Keyword(s):  
Distribution Function ◽  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Growth Model ◽  
Analytical Solutions ◽  
Growth Function ◽  
Crack Size ◽  
Model Parameters ◽  
Crack Growth Model

The study is focused on the formulation of a proposed polynomial stochastic fatigue crack growth model. Assuming the fatigue crack growth rate equal to a deterministic polynomial function in terms of fatigue crack size multiplied by a stationary lognormal random factor accounting for the statistical scatter of the fatigue crack growth, the analytical solutions of fatigue crack growth function and median crack growth function in term of model parameters were derived. Two extreme cases, lognormal random variable and lognormal white noise, of the proposed model were also investigated, and the analytical solutions of the distribution function of the random crack size at any service time and distribution function of random time to reach a specified crack size were obtained.

Developing a hybrid software reliability growth model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Avinash Kumar Shrivastava ◽  
Ruchi Sharma
Keyword(s):  
Distribution Function ◽  
Growth Model ◽  
Software Reliability ◽  
Change Point ◽  
Distribution Functions ◽  
Reliability Growth ◽  
Software Reliability Growth Model ◽  
Content Type ◽  
Before And After ◽  
Software Reliability Growth

PurposeThe purpose of this paper is to develop a new software reliability growth model considering different fault distribution function before and after the change point.Design/methodology/approachIn this paper, the authors have developed a framework to incorporate change-point in developing a hybrid software reliability growth model by considering different distribution functions before and after the change point.FindingsNumerical illustration suggests that the proposed model gives better results in comparison to the existing models.Originality/valueThe existing literature on change point-based software reliability growth model assumes that the fault correction trend before and after the change is governed by the same distribution. This seems impractical as after the change in the testing environment, the trend of fault detection or correction may not follow the same trend; hence, the assumption of same distribution function may fail to predict the potential number of faults. The modelling framework assumes different distributions before and after change point in developing a software reliability growth model.

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