contributor author | Sofi, Alba | |
contributor author | Muscolino, Giuseppe | |
contributor author | Elishakoff, Isaac | |
date accessioned | 2017-05-09T01:14:26Z | |
date available | 2017-05-09T01:14:26Z | |
date issued | 2015 | |
identifier issn | 2332-9017 | |
identifier other | RISK_1_3_030201.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/156874 | |
description abstract | Design processes involve several sources of uncertainties in loads and/or parameters that may seriously affect the estimates of performance and reliability of engineering systems. The selection of an appropriate mathematical representation of uncertainty that is based on available information is crucial to obtain realistic results. It is widely recognized that the credibility of traditional probabilistic methods is unquestionable when large data sets are available; when only limited data are available to define the probabilistic distribution of nondeterministic quantities, one may want to supplement probabilistic analysis by some other techniques. This consideration has aroused the evergrowing interest of researchers toward alternative uncertainty models based on nonprobabilistic concepts. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Special Section on Nonprobabilistic Approaches for Handling Uncertainty in Engineering | |
type | Journal Paper | |
journal volume | 1 | |
journal issue | 3 | |
journal title | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering | |
identifier doi | 10.1115/1.4030822 | |
journal fristpage | 30201 | |
journal lastpage | 30201 | |
tree | ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2015:;volume( 001 ):;issue: 003 | |
contenttype | Fulltext | |