Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken us...Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken using component failure rate data to predict PTC for a full stroke test and a partial stroke test.Given the subjective and uncertain aspects of the FMEDA approach,specifically the selection of component failure rates and the determination of the probability of detecting failure modes,a Fuzzy Inference System(FIS)was proposed to manage the data,addressing the inherent uncertainties.Fuzzy inference systems have been used previously for various FMEA type assessments,but this is the first time an FIS has been employed for use with FMEDA.ESDV PTC values were generated from both the standard FMEDA and the fuzzy-FMEDA approaches using data provided by FMEDA experts.This work demonstrates that fuzzy inference systems can address the subjectivity inherent in FMEDA data,enabling reliable estimates of ESDV proof test coverage for both full and partial stroke tests.This facilitates optimized maintenance planning while ensuring safety is not compromised.展开更多
针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒...针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒绝采样算法和追踪机制设计了一种可追踪环签名方案,签名算法中使用递归算法压缩了承诺的大小,进一步降低了签名尺寸,在随机预言机模型下证明方案满足可链接性、匿名性和抗陷害性。性能分析表明,签名尺寸与环成员数量为对数大小关系,在环成员数量较多时,公钥的存储开销和签名的通信开销具有明显优势。展开更多
文摘Published proof test coverage(PTC)estimates for emergency shutdown valves(ESDVs)show only moderate agreement and are predominantly opinion-based.A Failure Modes,Effects,and Diagnostics Analysis(FMEDA)was undertaken using component failure rate data to predict PTC for a full stroke test and a partial stroke test.Given the subjective and uncertain aspects of the FMEDA approach,specifically the selection of component failure rates and the determination of the probability of detecting failure modes,a Fuzzy Inference System(FIS)was proposed to manage the data,addressing the inherent uncertainties.Fuzzy inference systems have been used previously for various FMEA type assessments,but this is the first time an FIS has been employed for use with FMEDA.ESDV PTC values were generated from both the standard FMEDA and the fuzzy-FMEDA approaches using data provided by FMEDA experts.This work demonstrates that fuzzy inference systems can address the subjectivity inherent in FMEDA data,enabling reliable estimates of ESDV proof test coverage for both full and partial stroke tests.This facilitates optimized maintenance planning while ensuring safety is not compromised.
文摘针对目前格上环签名方案在环成员数量较多的情况下,签名效率低下且签名尺寸和公钥尺寸过大的问题,基于零知识证明,使用E-MLWE(extended module learning with errors)和MSIS(module short interger solution)问题降低了公钥大小,结合拒绝采样算法和追踪机制设计了一种可追踪环签名方案,签名算法中使用递归算法压缩了承诺的大小,进一步降低了签名尺寸,在随机预言机模型下证明方案满足可链接性、匿名性和抗陷害性。性能分析表明,签名尺寸与环成员数量为对数大小关系,在环成员数量较多时,公钥的存储开销和签名的通信开销具有明显优势。
