广东核电站的人可靠性分析

人的可靠性分析是广东核电站PSA研究中的一个重要部分,其目的是研究电站中人的行为对反应堆堆芯熔化频率的影响,文章对广东核电站事故序列中可能出现的人误进行了定性和定量化分析,给出了PSA研究中需要的人误概率值。详细的人因分析将在以后的工作中进行。

APPLICATION OF HUMAN COGNITIVE MODEL FOR TIME DEPENDENT OPERATOR BEHAVIOR IN CHINESE NPP

This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.

Research on Oil/Gas In-pipe Inspection Robot

A new type of in-pipe mobile robot was designed and developed on the basis of w heel in-pipe robot and crawler in-pipe robot. The three sets of driving wheels circumferentially 120° apart in the cross section, both front and rear driving wheels are distributed on the same parallelogram mechanis m. The driving motor drives the three sets of driving wheels by worm couple, the regulating motor makes the three sets of driving wheels push against the pipe inwall with stable and adequate pressing force by the ball screw pair and p ressure sensor, so the in-pipe robot can provide adequate and stable traction force. The robot mechanism is simple and sm all in size and work reliably . It is particularly suitable to the pipe with diameter 400～650 mm.

Quantitative Human Reliability Analysis for Crew During Shipping Operation

A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.

A Multi-homed VPN Architecture Based on Extended SOCKS+TLS Protocols

A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmission connections can switch smoothly among the multiple proxies by maint aining a coherent connection context.The mechanism is transparent to application programs and can support th e building of VPN.With the cooperation of some other security components,the mechanism guarantees the reso urce availability and reliability of the end system against some attacks to the specific ports or hosts.

A Statistical Analysis of Reliability of Audit Opinions as Bankruptcy Predictors

This research measures the reliability of audit firms in predicting bankruptcy for United States （US） listed financial institutions. The object of analysis is the going concern opinion （GCO）, widely considered as a bankruptcy warning signal to stakeholders. The sample is composed of 42 US listed financial companies that filed for Chapter 11 between 1998 and 2011. To highlight the differences between bankrupting and healthy firms, a matching sample composed of 42 randomly picked healthy US listed financial companies is collected. We concentrate on financial institutions, whereas the existing literature pays considerably greater attention to the industrial sector. This research imbalance is remarkable and particularly unexpected in the wake of recent financial scandals. Literature points out two main approaches on bankruptcy prediction： （1） purely mathematical; and （2） approaches based on a combination of auditor knowledge, expertise, and experience. The use of data mining techniques allows us to benefit from the best features of both approaches. Statistical tools used in the analysis are： Logit regression, support vector machines （SVMs）, and an AdaBoost meta-algorithm. Findings show a quite low reliability of GCOs in predicting bankruptcy. It is likely that auditors consider further information in supporting their audit opinions, aside from financial-economic ratios. The scant predictive ability of auditors might be due to critical relationships with distressed clients, as suggested by recent literature.

A Factor Analysis of the Tourism in the Mexican Province of Michoacan

The tourism is a key branch in the world wide economy nowadays, and revenues account for one third of total income in the world. Many nations are trying to improve their tourism sector attracting more tourists every year in order to impact social welfare. This study addresses two research questions： （1） What are the factors that impact on tourism sector？ and （2） Does the tourism really impact on social welfare of the communities？ The objectives of this work are to analyze the variables that impact on the tourism in the Mexican providence of Michoacan and also to find out if the tourism sector is impacting on social welfare of the province, with the propose of answering this questions 41 variables were selected being 63 municipalities of Michoacan province in the case of study. Analysis Factorial of Correspondences （AFC） through the analysis of principal components methodology is employed in this article. The analysis is divided into five phases： （1） reliability testing; （2） the calculation of a matrix that expresses the joint variability of the variables; （3） extraction of the optimal number of factors; （4） the rotation of solutions for the ease of interpretation; and （5） the estimation of the scores graphically. The results showed that the variables that impact on tourism are several the most representative tourism infrastructure and complementary services restaurants, lodging with category five- and four- star travel, visitors foreign share of the Economic Active Population （EAP） in the tertiary sector, percentage of EAP women, percentage of economically active men and Gross Domestic Product （GDP） per capita among others. However the analysis of the Human Development Index （HDI） is not associated with the tourism variables

Human Reliability Analysis Method on Armored Vehicle System Considering Error Correction

Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability statistics in order to analyze, predict, reduce and prevent human errors. Firstly, the quantitative analysis model of HRA is proposed based on Markov process theory by using human error probability(HEP) and error correction cycle(ECC) as parameters. And human reliability evaluation criterion is built. Then, the HRA process considering error correction is proposed based on cognitive reliability and error analysis method(CREAM). Finally, according to the characteristics of armored vehicle system, common performance condition(CPC) in CREAM is improved.A reliability impact index is characterized by the overall contexts of tasks. Human reliability evaluation criterion of armored vehicle system is formulated. And the result of HRA is obtained based on the method presented in this paper. In addition, the relative weights are estimated by combining scale of 10/10—18/2 and analytical hierarchy process(AHP), and the triangular fuzzy number considering confidence factor and optimism index is adopted in order to reduce the subjectivity. The analysis results show that the method presented in this paper is reasonable and feasible. Meantime, the method can provide guidance for human reliability analysis of other weapon systems.

A robust and efficient structural reliability method combining radial-based importance sampling and Kriging

Simulation based structural reliability analysis suffers from a heavy computational burden, as each sample needs to be evaluated on the performance function, where structural analysis is performed. To alleviate the computational burden, related research focuses mainly on reduction of samples and application of surrogate model, which substitutes the performance function. However,the reduction of samples is achieved commonly at the expense of loss of robustness, and the construction of surrogate model is computationally expensive. In view of this, this paper presents a robust and efficient method in the same direction. The present method uses radial-based importance sampling (RBIS) to reduce samples without loss of robustness. Importantly, Kriging is fully used to efficiently implement RBIS. It not only serves as a surrogate to classify samples as we all know, but also guides the procedure to determine the optimal radius, with which RBIS would reduce samples to the highest degree. When used as a surrogate, Kriging is established through active learning, where the previously evaluated points to determine the optimal radius are reused. The robustness and efficiency of the present method are validated by five representative examples, where the present method is compared mainly with two fundamental reliability methods based on active learning Kriging.