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Stochastic Control Part 13

Tham khảo tài liệu 'stochastic control part 13', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 472 Stochastic Control also with a complete set of numerical simulative methods such as Importance Sampling Adaptive Importance Sampling and others. The outputs it can give are such as the cumulative distribution function of the results the probability of failure or the performance level for a given probability of failure the probabilistic sensitivity factors and the confidence bounds of the requested result. One important feature of NESSUS is its capability to deal not only with components but also with systems via such methods as the Efficient Global Reliability Analysis and the Probabilistic Fault-Tree Analysis. STRUREL distributed by RCP is a complete package which is similar to NESSUS but has many more capabilities as it can deal for example with both time-invariant and timevariant problems. It is really much more difficult to be used but its advantages are quite evident for the expert user beside the capabilities we already quoted for the previous code it can carry out risk and cost analysis failure mode assessment reliability assessment for damaged structure development and optimisation of strategies for inspection and maintenance reliability oriented structural optimisation. It can also be interfaced with Permas FE code and with user-made Fortran routines in such a way as to make the user able to match with very general and complex problems a last but very important feature is the capability to carry out random vibration analysis with reference for example to wave wind and earthquake loading. The next two codes are of quite different nature as they are to be used when one is interested in optimisation and in the building of a robust design. The first one ST-Orm distributed by EASi Engineering uses the SDI technique to find the setting of the control variables of a design which ensures that the assigned target is reached with a given probability it uses M-C to obtain a cloud of results and then applying multilinear regressions and new M-C trials it generates