Efficient Method for Reliability Assessment Under High-Cycle Fatigue

Norouzi, Mahdi; Nikolaidis, Efstratios

doi:10.1142/s0218539312500222

Cited by 9 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(17) yields, (20) Because the integral in Eq. (20) is non-negative, f(t) has the following lower bound (21) If we continue the process of using Equations (17) and (19) to derive Eq. (20), the following Rice's inclusion-exclusion series [4,19] can be obtained (22) where (23) The PDF f(t) is then used in Eq.…”

Section: Approach 2: Statistically Dependent Up-crossingsmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Method to Calculate the Failure Rate of Dynamic Systems with Random Parameters Using the Total Probability Theorem

Majcher

Mourelatos

Geroulas

et al. 2015

SAE Int. J. Mater. Manf.

View full text Add to dashboard Cite

Using the total probability theorem, we propose a method to calculate the failure rate of a linear vibratory system with random parameters excited by stationary Gaussian processes. The response of such a system is non-stationary because of the randomness of the input parameters. A space-filling design, such as optimal symmetric Latin hypercube sampling or maximin, is first used to sample the input parameter space. For each design point, the output process is stationary and Gaussian. We present two approaches to calculate the corresponding conditional probability of failure. A Kriging metamodel is then created between the input parameters and the output conditional probabilities allowing us to estimate the conditional probabilities for any set of input parameters. The total probability theorem is finally applied to calculate the time-dependent probability of failure and the failure rate of the dynamic system. The proposed method is demonstrated using a vibratory system. Our approach can be easily extended to non-stationary Gaussian input processes.

show abstract

Section: Approach 2: Statistically Dependent Up-crossingsmentioning

confidence: 99%

“…We demonstrate the proposed approach using the single degree of freedom system of Figure 2 adopted from [21]. A concentrated mass M is placed at the mid-span of a massless beam of length L = 4m.…”

Section: Vibratory Beam Examplementioning

confidence: 99%

An Efficient Method to Calculate the Failure Rate of Dynamic Systems with Random Parameters Using the Total Probability Theorem

Majcher

Mourelatos

Geroulas

et al. 2015

SAE Int. J. Mater. Manf.

View full text Add to dashboard Cite

show abstract

“…The phase angles φ i are uniformly drawn from the range 0 to 2π. Norouzi and Nikolaidis (2012) showed that equation (3) can estimate the probability of failure for several PSD functions provided that results of MCs of a sampling spectrum are available.…”

Section: Probabilistic Re-analysis (Prra)mentioning

confidence: 99%

“…The selection of an appropriate sampling spectrum is critical in the application of PRRA (Norouzi and Nikolaidis, 2012). A suitable sampling spectrum should cause many failures with high likelihood.…”

Section: Probabilistic Re-analysis (Prra)mentioning

confidence: 99%

“…These methods have been applied to static problems where uncertainty is represented by random variables (Fonseca et al, 2007;Farizal and Nikolaidis, 2007;Li et al, 2011). Norouzi and Nikolaidis (2012) extended the applicability of the above method to the fatigue reliability assessment in random vibration when the excitation is represented by a Power Spectral Density function (PSD). The method estimates the probability of fatigue failure of a dynamic system for many PSD functions that are consistent with the available information by performing one MCs for a sampling PSD.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic re-analysis of nonlinear systems when energy of excitation changes

Norouzi

Nikolaidis

2015

IJRS

Self Cite

View full text Add to dashboard Cite

A reliability study of nonlinear mechanical systems under random dynamic loads often requires Monte Carlo simulation in the time domain with hundreds of thousands of replications. The uncertainties involved in design make such analyses necessary for various admissible loads, which can be impractical. The authors have already developed a methodology that reduces the computational cost of Monte Carlo simulation when the load is represented by a Power Spectral Density (PSD) function. This method is based on a probabilistic re-analysis, which uses results from a simulation for a single PSD to estimate the reliability for other admissible PSDs. However, the methodology was limited to PSDs with the same energy content. This paper proposes an approach to extend the applicability of the above method to cases in which the energy content of the PSD functions changes.Keywords: Monte Carlo simulation; probabilistic re-analysis; random vibration; power spectral density function; probability of first-passage.Reference to this paper should be made as follows: Norouzi, M. and Nikolaidis, E. (2015) 'Probabilistic re-analysis of nonlinear systems when energy of excitation changes', Int. . Since 1980, he has studied reliability design of aircraft, turbines and ocean structures. His research focuses on the decision-based design of engineering systems when there is limited Probabilistic re-analysis of nonlinear systems 37 information. He has published three books and more than 100 papers. He is a fellow member of the ASME and chairs the quality, reliability and robust design committee of the Society of Automotive Engineers. This paper is a revised and expanded version of a paper entitled 'Efficient sensitivity analysis of reliability of nonlinear dynamic systems considering change in energy content of excitation' presented at the '

show abstract

Integrating subset simulation with probabilistic re-analysis to estimate reliability of dynamic systems

Norouzi

Nikolaidis

2013

Struct Multidisc Optim

View full text Add to dashboard Cite

Efficient Method for Reliability Assessment Under High-Cycle Fatigue

Cited by 9 publications

References 11 publications

An Efficient Method to Calculate the Failure Rate of Dynamic Systems with Random Parameters Using the Total Probability Theorem

An Efficient Method to Calculate the Failure Rate of Dynamic Systems with Random Parameters Using the Total Probability Theorem

Probabilistic re-analysis of nonlinear systems when energy of excitation changes

Integrating subset simulation with probabilistic re-analysis to estimate reliability of dynamic systems

Contact Info

Product

Resources

About