FReET: Software for the statistical and reliability analysis of engineering problems and FReET-D: Degradation module

Novák, Drahomı́r; Vořechovský, Miroslav; Teplý, Břetislav

doi:10.1016/j.advengsoft.2013.06.011

Cited by 85 publications

(44 citation statements)

References 38 publications

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“…complex finite element method (FEM) simulations -and this is the case of complex FEM modelling, especially in 3D. With respect to the small-sample simulation technique described above the straightforward and the simplest approach uses the non-parametric rank-order statistical correlation between the basic random variables and the structural response variable [16,17]. The sensitivity analysis is obtained as an additional result of LHS, and no additional computational effort is necessary.…”

Section: Simulation-based Sa: Non-parametric Rank-ordermentioning

confidence: 99%

See 1 more Smart Citation

Methods of Sensitivity Analyses and theirs Role in Engineering

Drahom¡r¹,

Lehký²,

Cao³

et al. 2018

Proceedings of the International Symposium on Mechanical Engineering and Material Science (ISMEMS 2017)

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Abstract-The paper describes selected efficient methods for sensitivity analysis of engineering problems: The non-parametric rank-order statistical correlation between the basic random variables and the structural response variable, neural network ensemble-based sensitivity analysis and sensitivity analysis in terms of coefficient of variation. All three methods were utilized and compared for practical engineering example.

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Section: Simulation-based Sa: Non-parametric Rank-ordermentioning

confidence: 99%

“…These types of SA are implemented in reliability software FReET [17,18], widely used in engineering.…”

Section: Simulation-based Sa: Non-parametric Rank-ordermentioning

confidence: 99%

Methods of Sensitivity Analyses and theirs Role in Engineering

Drahom¡r¹,

Lehký²,

Cao³

et al. 2018

Proceedings of the International Symposium on Mechanical Engineering and Material Science (ISMEMS 2017)

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“…Furthermore, while these random starting solutions will result in a different final result in every calculation run, the differences are found to be negligible. Note that the differences in optimization result can be avoided when using a modified Latin Hypercube Sample where the mid-node of every probability interval is taken, see (Novak et al, 2014) for an example of this type of modified LHS.…”

Section: Maximum Entropy Estimation Of the Pdfmentioning

confidence: 99%

Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire

Coile¹,

Balomenos²,

Pandey³

et al. 2016

Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure

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Concrete columns are critical for the stability of structures in case of fire. In order to allow for a true Performance Based Design, the design should be based on considerations of risk and reliability. Consequently, the probability density function (PDF) which describes the load-bearing capacity of concrete columns during fire exposure has to be assessed. As second order effects can be very significant for columns, traditional probabilistic methods to determine the PDF become very computationally expensive. More precisely, for most current numerical calculation tools (e.g. Finite Element), the computational requirements are so high that traditional Monte Carlo simulations become infeasible for any practical application. In order to tackle this, a computationally very efficient method is presented and applied in this paper. The method combines the Maximum Entropy Principle together with the Multiplicative Dimensional Reduction Method, and Gaussian Interpolation, resulting in an estimation of the full PDF requiring only a very limited number of numerical calculations. Although the result is necessarily an approximation, it gives very good assessment of the PDF and it is a significant step forward towards true risk-and reliability-based structural fire safety.

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“…by considering the individual quantities in equation (1) to (4) as random quantities with a known probability distribution (e.g. as occurred for tasks concerning the service life of concrete structures described in [8]), with the output being values of statistical parameters or the probability distribution of this quantity. This enables the acquisition of further information and the possibility of comparison, e.g.…”

Section: Definition Of Coefficientsmentioning

confidence: 99%

“…Likewise, sensitivity studies can be carried out when the probabilistic approach is used (see e.g. [8]). …”

Section: Definition Of Coefficientsmentioning

confidence: 99%

Methodology for the quantification of concrete sustainability

2018

Self Cite

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Abstract. Efficient sustainability management requires the use of tools which allow material, technological and construction variants to be quantified, measured or compared. These tools can be used as a powerful marketing aid and as support for the transition to "circular economy". Life Cycle Assessment (LCA) procedures are also used, aside from other approaches. LCA is a method that evaluates the life cycle of a structure from the point of view of its impact on the environment. Consideration is given also to energy and raw material costs, as well as to environmental impact throughout the life cycle -e.g. due to emissions. The paper focuses on the quantification of sustainability connected with the use of various types of concrete with regard to their resistance to degradation. Sustainability coefficients are determined using information regarding service life and "eco-costs". The aim is to propose a suitable methodology which can simplify decision-making in the design and choice of concrete mixes from a wider perspective, i.e. not only with regard to load-bearing capacity or durability.

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FReET: Software for the statistical and reliability analysis of engineering problems and FReET-D: Degradation module

Cited by 85 publications

References 38 publications

Methods of Sensitivity Analyses and theirs Role in Engineering

Methods of Sensitivity Analyses and theirs Role in Engineering

Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire

Methodology for the quantification of concrete sustainability

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