Showing papers on "Monte Carlo method published in 2024"
TL;DR: In this paper , a general framework of using sequential Monte Carlo (SMC) for constrained sampling problems based on forward and backward pilot resampling strategies is proposed, where all information observed or imposed on the underlying system can be viewed as constraints.
Abstract: Sequential Monte Carlo (SMC) methods are a class of Monte Carlo methods that are used to obtain random samples of a high dimensional random variable in a sequential fashion. Many problems encountered in applications often involve different types of constraints. These constraints can make the problem much more challenging. In this paper, we formulate a general framework of using SMC for constrained sampling problems based on forward and backward pilot resampling strategies. We review some existing methods under the framework and develop several new algorithms. It is noted that all information observed or imposed on the underlying system can be viewed as constraints. Hence the approach outlined in this paper can be useful in many applications.
2 citations
TL;DR: In this article , the reliability of reinforced concrete columns in a fire situation is investigated by combining the General, Equilibrium, and Isotherm at 500 ° C Methods, and the well-known Monte Carlo (MC) and the First Order Reliability Method (FORM) are used in a parametric study for the column's safety.
Abstract: Abstract The reliability of reinforced concrete (RC) columns in a fire situation is investigated in this paper by combining the General, Equilibrium, and Isotherm at 500 ° C Methods. The well-known Monte Carlo (MC) and the First Order Reliability Method (FORM) are used in a parametric study for the column’s safety. The columns, in a biaxial bending-compression situations, are analyzed by an algorithm that takes into consideration physical and geometric nonlinearities. The dead and live load actions, steel and concrete material strengths, section geometry, model error, and temperature are among the random variables taken into consideration. The findings indicate that increasing the cover can dramatically reduce the probability of failure.