General outlook of UNIPASS™ V5.0: A general-purpose probabilistic software system

Lin, Hong‐Zong; Khalessi, M.

doi:10.1016/j.strusafe.2005.03.009

Cited by 10 publications

(3 citation statements)

References 12 publications

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“…This program allows to perform a wide range of probabilistic function assessments, including finite element analysis in a graphical environment. UNIPASS is a probabilistic evaluation software that provides the ability to model uncertainty, define probability distribution variables, and probabilistic models and responses [ 37 ]. The use of reliability analysis and of the finite element method has been described by many researchers (Lee and Ang [ 38 ], Engelstad and Reddy [ 39 ], Mahadevan and Mehty [ 40 ], Zabojszcza and Radoń [ 41 , 42 ], Mochocki et al [ 43 ], Kubicka et al [ 44 ]).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Approach to Limit States of a Steel Dome

2021

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In this paper, Numpress Explore software, developed at the Institute of Fundamental Technological Research of the Polish Academy of Sciences (IPPT PAN), was used to conduct reliability analyses. For static-strength calculations, the MES3D module, designed by the authors, was employed. Ultimate limit state was defined as condition of non-exceedance of the capacity value, resulting from the stability criterion of the bent and compressed element. The serviceability limit state was defined as the condition of non-exceedance of allowable vertical displacement. The above conditions constitute implicit forms of random variable functions; therefore, it was necessary to build an interface between the Numpress Explore and MES3D programs. In the study, a comparative analysis of two cases was carried out. As regards the first case, all adopted random variables had a normal distribution. The second case involved a more accurate description of the quantities mentioned. A normal distribution can be adopted for the description of, e.g., the randomness in the location of the structure nodes, and also the randomness of the multiplier of permanent loads. In actual systems, the distribution of certain loads deviates substantially from the Gaussian distribution. Consequently, adopting the assumption that the loads have a normal distribution can lead to gross errors in the assessment of structural safety. The distribution of loads resulting from atmospheric conditions is decidedly non-Gaussian in character. The Gumbel distribution was used in this study to describe snow and wind loads. The modulus of elasticity and cross-sectional area were described by means of a log-normal distribution. The adopted random variables were independent. Additionally, based on an analysis of the elasticity index, the random variables most affect the failure probability in the ultimate limit state and serviceability limit state were estimated.

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Section: Introductionmentioning

confidence: 99%

Probabilistic Approach to Limit States of a Steel Dome

2021

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“…An overview and test of different discretization methods can be found in the works of Li and Der Kiureghian [17] and Matthies [18]. Popular reliability analysis codes, such as ANSYS PDS, DesignXplorer, CalREL/FERUM/OpenSees, COSSAN, NESSUS, PERMAS-RA/STRUREL, PHIMECA-SOFT, PROBAN, PROFES, and UNIPASS, are reviewed in [19][20][21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Node Location Imperfections on the Reliability of Single-Layer Steel Domes

Zabojszcza

Radoń

2019

Applied Sciences

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This study is an attempt to assess the effect of node location imperfections on the reliability dome. The analysis concerns a single-layer steel lattice dome that is very sensitive to node snap-through. The load-displacement path of the structure was determined using the program, Finite Element Method-Krata. To determine the failure probability, reliability index, and elasticity index, the first-order reliability method approximation method was employed. The reliability analysis was conducted with Numpress Explore software, developed at the Institute of Fundamental Technological Research of the Polish Academy of Sciences, Warsaw. In this paper, it is shown how large differences in the assessment of the safety of a structure can appear when we incorrectly estimate the standard deviation of the random variable responsible for the imperfections of node locations.

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“…Generally, the reliability sensitivity is defined as the partial derivative of the failure probability with respect to the distribution parameter of the basic random variable and it is coded in the software [1][2][3][4]. Most literature discussed the reliability sensitivity in the independent variable space, which is easy to be implemented.…”

Section: Introductionmentioning

confidence: 99%

Reliability sensitivity analysis involving correlated random variables by directional sampling

Song

Lü

Song

2011

2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering

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Directional sampling based reliability sensitivity analysis for independent normal variables problem is extended for the reliability sensitivity analysis involving correlated random variables. For the reliability and reliability sensitivity problem involving correlated random variables, independent normal transformation techniques, including Nataf transformation or Copula functions, are firstly employed before the implementation of directional sampling. And then the reliability and sensitivity are estimated by the directional sampling in the independent standard normal space. Employing the equivalently transformation techniques between correlated random variables and independent normal ones, the reliability sensitivity of failure probability with respect to the distribution parameters of correlated random variables can be estimated by the chain rule of derivative finally. After simple numerical example is used to demonstrate the validity and feasibility of the presented extended method, it is employed to analyze the reliability and reliability sensitivity for the aeroengine turbine blade with correlated random variables. From the results of examples, it is determined the important parameters with large influence on the reliability, and the presented method can significantly reduce the computational cost than that of classical Monte Carlo simulation. The Nataf transformation can give the equivalently transformation when the random variables are correlated normal distributed, and the Nataf transformation is a way to model the dependence structure of a random vector by a normal copula, parameterized by its correlation matrix.

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General outlook of UNIPASS™ V5.0: A general-purpose probabilistic software system

Cited by 10 publications

References 12 publications

Probabilistic Approach to Limit States of a Steel Dome

Probabilistic Approach to Limit States of a Steel Dome

The Impact of Node Location Imperfections on the Reliability of Single-Layer Steel Domes

Reliability sensitivity analysis involving correlated random variables by directional sampling

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