Probability distribution model of stress impact factor for corrosion pits of high-strength prestressing wires

2021 ◽  
Vol 230 ◽  
pp. 111686
Author(s):  
Xiguang Liu ◽  
Weiping Zhang ◽  
Xianglin Gu ◽  
Zhiwen Ye
Keyword(s):  
Probability Distribution ◽  
Impact Factor ◽  
High Strength ◽  
Distribution Model ◽  
Corrosion Pits

A new probability distribution model of turbulent irradiance based on Born perturbation theory

2010 ◽  
Vol 53 (10) ◽  
pp. 1811-1818
Author(s):  
HongXing Wang ◽  
Min Liu ◽  
Hao Hu ◽  
Qian Wang ◽  
XiGuo Liu
Keyword(s):  
Perturbation Theory ◽  
Probability Distribution ◽  
Distribution Model

The Strength Evaluation and Reliability Analysis of Periodic Symmetric Struts Support

2011 ◽  
Vol 462-463 ◽  
pp. 1164-1169
Author(s):  
Jing Xiang Yang ◽  
Ya Xin Zhang ◽  
Mamtimin Gheni ◽  
Ping Ping Chang ◽  
Kai Yin Chen ◽  
...  
Keyword(s):  
Distribution Function ◽  
Probability Distribution ◽  
Stress Distribution ◽  
Least Squares ◽  
Reliability Analysis ◽  
Least Squares Method ◽  
Nonlinear Least Squares ◽  
Distribution Model ◽  
Different Types ◽  
Nonlinear Least Squares Method

In this paper, strength evaluations and reliability analysis are conducted for different types of PSSS(Periodically Symmetric Struts Supports) based on the FEA(Finite Element Analysis). The numerical models are established at first, and the PMA(Prestressed Modal Analysis) is conducted. The nodal stress value of all of the gauss points in elements are extracted out and the stress distributions are evaluated for each type of PSSS. Then using nonlinear least squares method, curve fitting is carried out, and the stress probability distribution function is obtained. The results show that although using different number of struts, the stress distribution function obeys the exponential distribution. By using nonlinear least squares method again for the distribution parameters a and b of different exponential functions, the relationship between number of struts and distribution function is obtained, and the mathematical models of the stress probability distribution functions for different supports are established. Finally, the new stress distribution model is introduced by considering the DSSI(Damaged Stress-Strength Interference), and the reliability evaluation for different types of periodically symmetric struts supports is carried out.

Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills

2013 ◽  
Vol 2 (4) ◽  
pp. 61-78 ◽  
Author(s):  
Roy L. Nersesian ◽  
Kenneth David Strang
Keyword(s):  
Probability Distribution ◽  
Probability Distributions ◽  
Low Cost ◽  
Discrete Distribution ◽  
Distribution Model ◽  
Distribution Analysis ◽  
Distribution Models ◽  
Discrete Probability ◽  
Nonparametric Statistical ◽  
Spreadsheet Software

This study discussed the theoretical literature related to developing and probability distributions for estimating uncertainty. A theoretically selected ten-year empirical sample was collected and evaluated for the Albany NY area (N=942). A discrete probability distribution model was developed and applied for part of the sample, to illustrate the likelihood of petroleum spills by industry and day of week. The benefit of this paper for the community of practice was to demonstrate how to select, develop, test and apply a probability distribution to analyze the patterns in disaster events, using inferential parametric and nonparametric statistical techniques. The method, not the model, was intended to be generalized to other researchers and populations. An interesting side benefit from this study was that it revealed significant findings about where and when most of the human-attributed petroleum leaks had occurred in the Albany NY area over the last ten years (ending in 2013). The researchers demonstrated how to develop and apply distribution models in low cost spreadsheet software (Excel).

Applicable Probability Distribution Model of Refracted Star Number in Field of View of Indirectly Sensing Horizon Star Sensor

2013 ◽  
Vol 33 (12) ◽  
pp. 1201002
Author(s):  
王海涌 Wang Haiyong ◽  
金光瑞 Jin Guangrui ◽  
赵彦武 Zhao Yanwu
Keyword(s):  
Probability Distribution ◽  
Field Of View ◽  
Distribution Model ◽  
Star Sensor

Clustering-based probability distribution model for monthly residential building electricity consumption analysis

2020 ◽  
Vol 14 (1) ◽  
pp. 149-164
Author(s):  
Jieyan Xu ◽  
Xuyuan Kang ◽  
Zheng Chen ◽  
Da Yan ◽  
Siyue Guo ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Electricity Consumption ◽  
Residential Building ◽  
Distribution Model

Modeling the Influence of Microstructure on Stress Distributions and Concentrations in Pitting Corrosion

2018 ◽  
Author(s):  
Patrick Brewick ◽  
Andrew Geltmacher ◽  
Siddiq M. Qidwai
Keyword(s):  
Stainless Steel ◽  
Pitting Corrosion ◽  
Mechanical Load ◽  
High Strength ◽  
Geometrical Shape ◽  
Stress Distributions ◽  
Concentration Factors ◽  
Corrosion Pit ◽  
Stress Concentration Factors ◽  
Corrosion Pits

Despite the many advances made in material science, stainless steel and aluminum remain the structural materials best-suited for the naval fleet. While these metallic materials offer many benefits, such as high strength and good toughness, their persistent exposure to the maritime environment inevitably leads to issues with corrosion. Among the various manifestations of corrosion, pitting corrosion is of particular concern because the transition of corrosion pits to stress-corrosion cracks can lead to catastrophic failures. Traditional pitting corrosion analyses treat the pit shape as a semi-circle or ellipse and typically assume a growth pattern that maintains the original geometrical shape. However, when the underlying microstructure is incorporated into the model, pit growth is related to the grains surrounding the pit perimeter and the growth rate is proportional to crystallographic orientation. Since each grain has a potentially different orientation, pit growth happens at non-uniform rates leading to irregular geometries, i.e., non-circular and non-elliptical. These irregular pit geometries can further lead to higher stresses. This work presents a detailed look at corrosion pit growth coupled with mechanical load through a numerical model of a two-dimensional stable corrosion pit. Real microstructural information from a sample of 316 stainless steel is incorporated into the model to analyze microstructural effects on pit growth. Through this work, stress distributions and stress concentration factors are examined for a variety of pit geometries, including comparisons of their range of values to a typical, semi-circular pit. The consequences of these stress distributions and concentration factors are discussed.

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