Safety Factors and Reliability: Friends or Foes?

Elishakoff, Isaac

doi:10.1007/978-1-4020-2131-2

Cited by 62 publications

(39 citation statements)

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“…Although his paper about safety was published in 1921 in Hungarian [9], Elishakoff, the world renowned expert of safety credited Kazinczy with first proposing the use of the theory of probability for defining the safety of structures [1].…”

Section: History Of His Lifementioning

confidence: 99%

“…This paper is dedicated to his memory. This text is based on the student research work of Lógó et al prepared in 2014 [22], and Kaliszky's former paper in 2007 [7] and his presentation at the Hungarian Academy of Sciences in 2014 1 . Kazinczy's achievements in plasticity and in reliability analysis in structural engineering are among the most important results in this field.…”

Section: Introductionmentioning

confidence: 99%

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Gábor Kazinczy and His Legacy in Structural Engineering

Kaliszky

Sajtos²,

Lógó³

et al. 2015

Period. Polytech. Civil Eng.

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Section: History Of His Lifementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Gábor Kazinczy and His Legacy in Structural Engineering

Kaliszky

Sajtos²,

Lógó³

et al. 2015

Period. Polytech. Civil Eng.

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“…In the literature several concepts of fuzzy as well possibilistic concepts for reliability and safety factors can be found [7,8,[21][22][23] A concept of possibility of failure Π (F) is used for this purpose to quantify the risk of mechanical response exceeding the state limit. This is defined as…”

Section: Fuzzy Safety Factorsmentioning

confidence: 99%

“…As this concept and meaning of fuzzy reliability based purely on the possibility theory is not fully developed, e.g. in standards, a fuzzy safety factor based on the interval safety factor [8] is used in addition. The following equation is used, here with stress σ and yield stress…”

Section: Fuzzy Safety Factorsmentioning

confidence: 99%

Fuzzy Modeling of Imprecise Material Parameters in the Analysis of Metal Matrix Composite Structures

Wehrle

Wedekind

Baier

2011

Volume 9: Transportation Systems; Safety Engineering, Risk Analysis and Reliability Methods; Applied Stochastic Optimization, U

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Engineering information is often uncertain, deviated, imperfect, erroneous, imprecise, etc. Fuzzy methods, based on possibility theory are well suited for describing epistemic uncertainty. Included in epistemic uncertainty are data sets where only few samples are available and are appropriately modeled with fuzzy methods. The resulting fuzzy parameters can then be used in structural analysis, allowing for nondeterministic consideration and, therefore, uncertainty assessment. In this study, different approaches to construct fuzzy membership functions are discussed and compared. Further, the influence of fuzzy modeling, or fuzzification, is evaluated within the framework of structural analysis and then in the safety factor assessment. The mechanical response was calculated using finite element analysis with uncertain material, evaluating stress and buckling load factor. Finally, the fuzzy safety factors were quantified for the different fuzzification methods, showing the importance of uncertainty consideration.

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“…This practice is common in structural analysis, where stress or strain values must not be underestimated in order to avoid failure. The choice of the constant is often based on previous knowledge of the problem [19][20][21]. However, for surrogate-based analysis, there is no established practice for choosing the safety margin.…”

mentioning

confidence: 99%

Using Cross Validation to Design Conservative Surrogates

2010

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The use of surrogates (also known as metamodels) for facilitating optimization and statistical analysis of computationally expensive simulations has become commonplace. Surrogate models are usually fit to be unbiased (i.e., the error expectation is zero). However, in certain applications, it might be important to safely estimate the response (e.g., in structural analysis, the maximum stress must not be underestimated in order to avoid failure). In this work we use safety margins to conservatively compensate for fitting errors associated with surrogates. We propose the use of cross validation for estimating the required safety margin for a desired level of conservativeness (percentage of safe predictions). The approach was tested on three algebraic examples for two basic surrogates: namely, kriging and polynomial response surface. For these examples we found that cross validation is effective for selecting the safety margin. We also applied the approach to the probabilistic design optimization of a composite laminate. This design under uncertainty example showed that the approach can be successfully used in engineering applications.

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Safety Factors and Reliability: Friends or Foes?

Cited by 62 publications

References 0 publications

Gábor Kazinczy and His Legacy in Structural Engineering

Gábor Kazinczy and His Legacy in Structural Engineering

Fuzzy Modeling of Imprecise Material Parameters in the Analysis of Metal Matrix Composite Structures

Using Cross Validation to Design Conservative Surrogates

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