Dynamic Reliability Evaluation by First-Order Reliability Method Integrated with Stochastic Pseudo Excitation Method

2020 ◽  
pp. 2150024
Author(s):  
Siyu Zhu ◽  
Tianyu Xiang
Keyword(s):  
Random Variable ◽  
Random Excitation ◽  
Pseudo Excitation Method ◽  
First Order Reliability Method ◽  
Dynamic Reliability ◽  
First Order ◽  
Reliability Method ◽  
Uncertain Structure ◽  
Pseudo Excitation ◽  
Excitation Method

The stochastic pseudo excitation method (SPEM), which is based on the principle of pseudo excitation method (PEM), is introduced to represent the randomness of dynamic input in which the amplitude of excitation is adopted as a random variable. Based on the mathematic definition of power spectral density, a physical interpolation of the SPEM is discussed. Even if one random variable is involved in calculation, the effects of the uncertainties are required to be investigated. The SPEM offers a simple but quite effective way to solve the dynamic reliability problem. Through integrating the new algorithm into first-order reliability method (FORM), the dynamic reliability of uncertain structure subjected to random excitation is studied. A linear oscillator with three types of white noise is adopted to verify the SPEM for dynamic reliability of linear random vibration analysis. Also, the accuracy and efficiency of SPEM to handle the multi-degree-of-freedom structure is investigated in this paper.

Random Characteristics of Vehicle-Bridge System Vibration by an Optimized Pseudo Excitation Method

2020 ◽  
Vol 20 (05) ◽  
pp. 2050069
Author(s):  
Siyu Zhu ◽  
Yongle Li
Keyword(s):  
Excitation Frequency ◽  
Time History ◽  
Harmonic Excitation ◽  
Random Excitation ◽  
Computational Effort ◽  
Cumulative Distribution ◽  
Pseudo Excitation Method ◽  
Rail Irregularities ◽  
Pseudo Excitation ◽  
Excitation Method

The pseudo excitation method (PEM) is improved for its efficiency by incorporating the self-adaptive Gauss integration (SGI) technology as a new combining integration. The PEM can transform the random rail irregularities into some pseudo harmonic excitation, which is a mature approach to deal with the random excitation for vehicle–bridge systems. The SGI was used to distinguish the significant from the insignificant parts of an integral section for the random excitation frequency on the stochastic response of the system, thereby reducing the computational effort required for the random vibration analysis of the system. Also, the SGI can intelligently handle the recognized integral section, by subdividing the important sections into several necessary frequency points, making rough decomposition, and allowing the unimportant regions to be eliminated. Based on selected frequency points, the deterministic pseudo harmonic excitations were generated, and then the standard deviation (SD) of the time history for the system was calculated by the PEM. The vehicle subsystem was simulated as a 23-degree of freedom model, and the bridge subsystem as a three-dimensional finite element model. The time-varying power spectral density (PSD) plots of the system were presented. Besides, the cumulative distribution function (CDF) of the response was calculated using Poisson’s crossing assumption. The random characteristics for the vehicle–bridge vibrations for different speeds and rail irregularities were calculated.

Structural Dynamic Reliability on Supercavity Vehicle

2011 ◽  
Vol 230-232 ◽  
pp. 362-366
Author(s):  
Ming Liu ◽  
Wei Guang An
Keyword(s):  
Efficient Method ◽  
Random Excitation ◽  
Thin Shells ◽  
Good Precision ◽  
Structural Dynamic ◽  
Shell Elements ◽  
Dynamic Reliability ◽  
Wave Passage ◽  
Pseudo Excitation ◽  
Excitation Method

Dynamic reliability of supercavity vehicle is investigated. The vehicle is modeled as thin shells, using eight-node super-parametric shell elements. To deal with the tail of supercavity vehicle structures subjected to stationary random excitations, and the wave passage effect must be considered, an efficient method, the Pseudo Excitation Method, is suggested. The stationary random excitation is transformed into a deterministic transient excitation. The response can be obtained by Newark method, at last dynamic reliability of supercavity vehicle can be got base on the rule of first excursion failure. Examples show that this method is simple, efficient and has good precision.

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

2019 ◽  
Vol 9 (13) ◽  
pp. 2742 ◽  
Author(s):  
Paweł Zabojszcza ◽  
Urszula Radoń
Keyword(s):  
Reliability Index ◽  
Single Layer ◽  
Random Variable ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
Node Location ◽  
Academy Of Sciences ◽  
The Impact ◽  
Layer Steel

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.

An accuracy analysis method for first-order reliability method

2018 ◽  
Vol 233 (12) ◽  
pp. 4319-4327 ◽  
Author(s):  
Zhenzhong Chen ◽  
Zihao Wu ◽  
Xiaoke Li ◽  
Ge Chen ◽  
Guangfeng Chen ◽  
...  
Keyword(s):  
Structural Reliability ◽  
Nonlinear Problems ◽  
Accuracy Analysis ◽  
Analysis Method ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Level ◽  
Reliability Method ◽  
Value Range ◽  
Crashworthiness Design

The first-order reliability method is widely used for structural reliability analysis; however, its accuracy would become worse for nonlinear problems. This paper proposes the accuracy analysis method of the first-order reliability method, which considers the worst cases when using the first-order reliability method and gives the possible value range of the probability of safety. The accuracy analysis method can evaluate the reliability level of the first-order reliability method when the failure surfaces are nonlinear. The calculation formula for the possible value range of the probability of safety is proposed, and its trend as the dimensions and reliability rise is also discussed in this paper. A numerical example and a honeycomb crashworthiness design are presented to validate the accuracy of the first-order reliability method, and the results show that they are located within the possible value range proposed in this paper.

Sensitivity of Vessel Responses to Environmental Contours of Extreme Sea States

2015 ◽  
Author(s):  
Curtis Armstrong ◽  
Christopher Chin ◽  
Irene Penesis ◽  
Yuriy Drobyshevski
Keyword(s):  
Case Studies ◽  
Return Period ◽  
Significant Wave Height ◽  
Peak Period ◽  
First Order Reliability Method ◽  
First Order ◽  
Long Wave ◽  
Contour Lines ◽  
Reliability Method ◽  
Extreme Responses

A comparative study of two methods for the generation of the environmental contours is presented investigating the sensitivity of the predicted extreme vessel responses to the type of the contour lines. Two approaches for the generation of environmental contours of the significant wave height and peak period are compared: the Inverse First Order Reliability Method (IFORM) and Constant Probability Density (CPD) approach. Case studies include several global responses of a ship-shaped weather-vaning vessel and a semisubmersible platform. The case studies reveal that the differences between the IFORM and CPD contours are more pronounced in the range of long wave periods. Vessel responses which are less sensitive to long wave periods exhibit less difference (less than 1.0%) in their maximum values between the two types of contours. In contrast, responses which are sensitive to long wave periods show significantly larger differences of up to 7.0%. Uncertainties also exist in the predicted extreme responses where the environmental contour and the response isoline behave tangentially. Differences between the extreme responses produced by the two contours generally decrease with an increase in return period; however exceptions exist due to the tangential behaviour. It is advised that these sensitivities should be taken into consideration when the environmental contours are used in the design.

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