A simple model is proposed to analyze a rise in temperature of a gas and of tank material during filling a tank at high pressure. A numerical simulation has been done to compare the temperature change of the gas and material measured for actual tanks. It reveals that the estimated temperature is in good agreement with the measured temperature for an actual hydrogen tank.

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For elastic-plastic stress analyses, the stress-strain characteristic is one of the most fundamental properties of material. Though S-S curve expressed by multiple linear lines can be easily available for FEM codes, S-S curve expressed as an analytic function is more useful for theoretical analyses. However, formulation of S-S curve using few measured data may be not studied enough. For the Needleman S-S curve, an approximate estimation procedure, using Newton method solving two equations comprised by yield stress and tensile strength, is presented. And two application studies, plastic buckling stress of short column and collapse pressure in the elastic-plastic zone, are performed. The studies show that the estimate of S-S curve can be used for accurate calculation under both stress states, since the failure strengths calculated agree well with ones obtained by experiment.

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A new observation method was developed for evaluating precipitates distributions on the electropolished surface of the ferritic heat-resisting steel (9Cr-3W) , using field emission type-scanning electron microscopy (FE-SEM) . The FE-secondary and backscattered electron images of the electropolished surfaces visualize clearly fine precipitates, since the electropolishing surfaces are very flat and not influenced by martensite matrix surface unevenness.
The intergranular or transgranular precipitates distributions for each of the two types of chromium carbide and laves phase which were identified by backscattered electron images, were quantitatively evaluated, respectively, before and after the creep-fatigue testing.

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Fatigue crack propagation behavior in pure-aluminum under pull-push loading was investigated. Usually, fatigue crack propagate by mode I and fatigue crack propagation rate da⁄dN accelerate with crack growth in many metals under pull-push loading. However, results in pure-aluminum of present study showed that crack propagation mode was changed depending on testing conditions and mixed mode of crack propagation was observed. Also, even in the case of constant stress amplitude, retardation behavior of crack propagation was observed. Mixed mode crack propagation and retardation behavior of crack are discussed from the viewpoint of local crack propagation behavior, fracture surfaces'configuration and crack opening behavior.

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Since risk is defined as combination of the probability of failure and the consequence of failure, these two values should be evaluated for quantitative risk analyses. In this lecture, focus is centered on technique how to evaluate failure probabilities of structural components. The conventional reliability engineering approach, which is applicable when the life distribution or failure rate of the component is available through life tests or a reliability database, is firstly reviewed. Then, structural reliability engineering approach, in which the probability of failure is evaluated based on the failure mechanism and the statistical properties of loads and material strength, etc. , is reviewed. The essence of structural reliability engineering approach is the mathematical formulation of the failure probability using the uncertainty variables and the limit-state function. It is, however, difficult to directly calculate this formula since it is a multi-fold integral of a multi-dimensional joint distribution function. The first-order reliability method (FORM) is widely used technique to approximately calculate this probability integral. The Monte Carlo simulation, a numerical method to solve probabilistic problems, can be also applied to calculate this probability integral. However, the crude Monte Carlo simulation is not realistic because it takes too much time to calculate very low failure probabilities. To conquer this problem, more efficient Monte Carlo simulation technique like importance sampling and stratified sampling is employed. A brief review on technique to evaluate the failure probability of a structural system is also presented. An emphasis on the necessity of reliability data and the usage of Bayesian approach to evaluate failure probabilities of practical structures concludes this paper.

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