Adaptive importance sampling based neural network framework for reliability and sensitivity prediction for variable stiffness composite laminates with hybrid uncertainties
نویسندگان
چکیده
منابع مشابه
AN ADAPTIVE IMPORTANCE SAMPLING-BASED ALGORITHM USING THE FIRST-ORDER METHOD FOR STRUCTURAL RELIABILITY
Monte Carlo simulation (MCS) is a useful tool for computation of probability of failure in reliability analysis. However, the large number of samples, often required for acceptable accuracy, makes it time-consuming. Importance sampling is a method on the basis of MCS which has been proposed to reduce the computational time of MCS. In this paper, a new adaptive importance sampling-based algorith...
متن کاملFree Vibration Analysis of Variable Stiffness Composite Laminates with Flat and Folded Shapes
In this article, free vibration analysis of variable stiffness composite laminate (VSCL) plates with flat and folded shapes is studied. In order to consider the concept of variable stiffness, in each layer of these composite laminated plates, the curvilinear fibers are used instead of straight fibers. The analysis is based on a semi-analytical finite strip method which follows classical laminat...
متن کاملMeta-model-based importance sampling for reliability sensitivity analysis
Reliability sensitivity analysis aims at studying the influence of the parameters in the probabilistic model onto the probability of failure of a given system. Such an influence may either be quantified on a given range of values of the parameters of interest using a parametric analysis, or only locally by means of its partial derivatives. This paper is concerned with the latter approach when t...
متن کاملSensitivity Analysis of Spatial Sampling Designs for Optimal Prediction
In spatial statistic, the data analyzed which is correlated and this correlation is due to their locations in the studied region. Such correlation that is related to distance between observations is called spatial correlation. Usually in spatial data analysis, the prediction of the amount of uncertain quantity in arbitrary 4locations of the area is considered according to attained observations ...
متن کاملAdaptive importance sampling for network growth models
Network Growth Models such as Preferential Attachment and Duplication/Divergence are popular generative models with which to study complex networks in biology, sociology, and computer science. However, analyzing them within the framework of model selection and statistical inference is often complicated and computationally difficult, particularly when comparing models that are not directly relat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Composite Structures
سال: 2020
ISSN: 0263-8223
DOI: 10.1016/j.compstruct.2020.112344