When using the risk priority number method to perform a criticality analysis of the failure modes of mechanical products, different subjective factors exist on the part of experts regarding the severity level (S), occurrence probability level (O), and failure modes. The estimation of the detection difficulty level (D) is different, which causes the problem of inaccurate evaluation of the criticality of failure modes. This study proposes a harm analysis method that combines group decision-making and fuzzy comprehensive evaluation. The similarity and difference between an individual expert and the group are used in group decision-making to assign the weight of the expert, thus reducing the influence of subjective factors on the evaluation results. On the basis of the fuzzy comprehensive evaluation method, the weight of three risk elements (S, O, and D) is determined, and a hazard ranking of the interval obtained by group decision-making is performed. The CA (criticality analysis) improvement method is used to analyze the hazard posed by low-temperature shut-off valves. Results indicate that this method can effectively assess the weak links of the low-temperature shut-off valves and improve the accuracy of the hazard evaluation in comparison with the risk priority coefficient method.

In order to improve the prediction accuracy of cryogenic shut-off valve failures and quantitatively analyze the distribution law of cryogenic shut-off valve failures, this study establishes a solution model based on genetic algorithm and statistics of cryogenic shut-off valve operating data, which is combined with two Weibull segmented models. The research analyzed the characteristics of the failure rate curve using probability statistical mathematics methods, used the K-S test method to validate the obtained two-parameter Weibull model, and compared the fitting results with the Weibull probability plot. The results show that the genetic algorithm based on D-test has both higher accuracy of curve fitting and more accurate parameters, which overcomes the shortcomings of inaccurate fitting results of WPP graphs, and can be used as a basis for theoretical assessment of reliability levels.

BACKGROUND A large amount of research has improved electrochemical performance by strengthening the chemical affinity by using polar materials in lithium–sulfur batteries. However, only some of this research has focused on the relationship between structure and polysulfide adsorption ability. RESULTS In this work, a Ti3C2 nanosheet structure has been applied as sulfur host matrix to improve electrochemical performance. Due to the nanosheet structure, the polysulfide was able to diffuse between the Ti3C2 layers, therefore improving the catalytic effect of the polysulfide. Moreover, the space between the Ti3C2 layers can store the soluble polysulfide as an effective reservoir. As a result, the traditional shuttle effect of the polysulfide could be efficiently inhibited. CONCLUSION Therefore, the as‐prepared Ti3C2/S composites exhibited high specific capacity, high rate performance, and stable cycle performance. All these superior electrochemical performances are attributed to the presence of the Ti3C2 nanosheet. © 2022 Society of Chemical Industry (SCI).