کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5019583 | 1468212 | 2017 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Capturing cognitive causal paths in human reliability analysis with Bayesian network models
ترجمه فارسی عنوان
ضبط مسیرهای علمی شناختی در تحلیل قابلیت اطمینان انسانی با مدل های شبکه بیس
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کلمات کلیدی
CPTTHERPCFMPIFHEPPRAHRAHSIPMFHuman-system interfaceHFEATHEANANRCAcrSpsf - PSFProbability mass function - احتمال تابع تودهHuman Error Probability - احتمال خطای انسانیProbabilistic risk assessment - ارزیابی ریسک احتمالیHuman reliability assessment - ارزیابی قابلیت اطمینان انسانBayesian updating - به روز رسانی بیزیProbability density function - تابع چگالی احتمالConditional Probability Table - جدول احتمال احتمالیDecision tree - درخت تصمیمDAG - روزBayesian network - شبکه بیزی، شبکه بیزینBayesian networks - شبکهٔ بیزی یا «شبکه باور» یا «شبکه باور بیزی»Performance shaping factor - عامل شکل گیری عملکردCognitive factors - عوامل شناختیPdf - پی دی افNuclear Regulatory Commission - کمیسیون تنظیم مقررات هسته ایDirected acyclic graph - گراف خطی خطی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی مکانیک
چکیده انگلیسی
reIn the last decade, Bayesian networks (BNs) have been identified as a powerful tool for human reliability analysis (HRA), with multiple advantages over traditional HRA methods. In this paper we illustrate how BNs can be used to include additional, qualitative causal paths to provide traceability. The proposed framework provides the foundation to resolve several needs frequently expressed by the HRA community. First, the developed extended BN structure reflects the causal paths found in cognitive psychology literature, thereby addressing the need for causal traceability and strong scientific basis in HRA. Secondly, the use of node reduction algorithms allows the BN to be condensed to a level of detail at which quantification is as straightforward as the techniques used in existing HRA. We illustrate the framework by developing a BN version of the critical data misperceived crew failure mode in the IDHEAS HRA method, which is currently under development at the US NRC [45]. We illustrate how the model could be quantified with a combination of expert-probabilities and information from operator performance databases such as SACADA. This paper lays the foundations necessary to expand the cognitive and quantitative foundations of HRA.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 158, February 2017, Pages 117-129
Journal: Reliability Engineering & System Safety - Volume 158, February 2017, Pages 117-129
نویسندگان
Kilian Zwirglmaier, Daniel Straub, Katrina M. Groth,