Results 301 to 310 of about 28,090,256 (352)
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Reliability Engineering & System Safety, 2019
Owing to its time-consuming computation of complex structural responses, structural reliability analysis is still one of the challenging tasks. In this work, based on the FORM, the structural reliability analysis problem is transformed into a sequential ...
Zhao Jing, Jianqiao Chen, Xu Li
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Owing to its time-consuming computation of complex structural responses, structural reliability analysis is still one of the challenging tasks. In this work, based on the FORM, the structural reliability analysis problem is transformed into a sequential ...
Zhao Jing, Jianqiao Chen, Xu Li
semanticscholar +1 more source
Machine learning-based methods in structural reliability analysis: A review
Reliability Engineering & System Safety, 2021Sajad Saraygord Afshari +3 more
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Reliability Engineering & System Safety, 2018
With the increasing complexity and size of modern advanced engineering systems, the traditional reliability theory cannot characterize and quantify the complex characteristics of complex systems, such as multi-state properties, epistemic uncertainties ...
J. Mi +3 more
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With the increasing complexity and size of modern advanced engineering systems, the traditional reliability theory cannot characterize and quantify the complex characteristics of complex systems, such as multi-state properties, epistemic uncertainties ...
J. Mi +3 more
semanticscholar +1 more source
Time-variant reliability analysis using the parallel subset simulation
Reliability Engineering & System Safety, 2019Time-variant reliability problems commonly occur in practical engineering applications due to deterioration in material properties, dynamic load and other causes.
Weiqi Du, Yuanxin Luo, Yongqin Wang
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A review and assessment of importance sampling methods for reliability analysis
Structural Safety, 2022Armin Tabandeh, G. Jia, P. Gardoni
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A Reliability Analysis of a Deep Neural Network
Latin American Test Symposium, 2019Deep Learning, and in particular its implementation using Convolutional Neural Networks (CNNs), is currently one of the most intensively and widely used predictive models for safety-critical applications like autonomous driving assistance on pedestrian ...
A. Bosio +3 more
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ITER guide for reliability analysis
IEEE Thirteenth Symposium on Fusion Engineering, 2003Demanding reliability and availability (R&A) goals have been established for the International Thermonuclear Experimental Reactor (ITER). The possibility of achieving such goals depends on implementing a dedicated R&A assurance program from the outset of the design efforts. A guide for ITER reliability analyses has been prepared and preliminary results
Buende, R., Ollivier, G., Flanagan, C.
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Design tools for reliability analysis
Proceedings of the 43rd annual conference on Design automation - DAC '06, 2006Recent progress in EDA tools allows IC designs to be accurately verified with consequent improvements in yield and performance through reduced guard bands. This paper will present a tools perspective, including the primary effects such as HCI, NBTI and EM for which EDA tools are available, types of tools (dynamic simulation vs.
Zhihong Liu, Bruce McGaughy, James Z. Ma
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Reliability Engineering & System Safety, 2019
Reliability evaluation of manufacturing system always takes machine performance and product quality as two key factors. But the imperfect inspection usually leads to unreliable quality judgments, cause the propagation of unqualified products, and ...
Zhenggeng Ye +4 more
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Reliability evaluation of manufacturing system always takes machine performance and product quality as two key factors. But the imperfect inspection usually leads to unreliable quality judgments, cause the propagation of unqualified products, and ...
Zhenggeng Ye +4 more
semanticscholar +1 more source
A Reliability Simulation Language for Reliability Analysis
1986Much attention is being directed towards the development of reliability assessment tools. Common to all techniques is the requirement for a systematic description of the reliability problem.
N. D. Deans, A. J. Miller, D. P. Mann
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