Limit and shakedown analysis with uncertain data. Heitzer, M. & Staat, M. In Stochastic Optimization Techniques, Numerical Methods and Technical Applications, volume 513, of Lecture Notes in Economics and Mathematical Systems, pages 253–267. Springer, Berlin, Heidelberg, 2002. ZSCC: NoCitationData[s0]
abstract   bibtex   
The structural reliability with respect to plastic collapse or to inadaptation is formulated on the basis of the lower bound limit and shakedown theorems. A direct definition of the limit state function is achieved. The suggested approach which combines the FE method with first order reliability methods (FORM) leads to a better understanding of the influences on the structural behaviour. The theorems are implemented into a general purpose FEM program in a way capable of large-scale analysis. The limit state function and its gradient are obtained from a mathematical optimization problem. This direct approach reduces considerably the necessary knowledge of uncertain technological input data, the computing time, and the numerical error, leading to highly effective and precise reliability analyses.
@incollection{heitzer_limit_2002,
	series = {Lecture {Notes} in {Economics} and {Mathematical} {Systems}},
	title = {Limit and shakedown analysis with uncertain data},
	volume = {513},
	copyright = {All rights reserved},
	isbn = {978-3-540-42889-3},
	abstract = {The structural reliability with respect to plastic collapse or to inadaptation is formulated on the basis of the lower bound limit and shakedown theorems. A direct definition of the limit state function is achieved. The suggested approach which combines the FE method with first order reliability methods (FORM) leads to a better understanding of the influences on the structural behaviour. The theorems are implemented into a general purpose FEM program in a way capable of large-scale analysis. The limit state function and its gradient are obtained from a mathematical optimization problem. This direct approach reduces considerably the necessary knowledge of uncertain technological input data, the computing time, and the numerical error, leading to highly effective and precise reliability analyses.},
	booktitle = {Stochastic {Optimization} {Techniques}, {Numerical} {Methods} and {Technical} {Applications}},
	publisher = {Springer, Berlin, Heidelberg},
	author = {Heitzer, Michael and Staat, Manfred},
	editor = {Marti, Kurt},
	year = {2002},
	note = {ZSCC: NoCitationData[s0]},
	pages = {253--267},
}

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