An Adaptive First-Order Reliability Analysis Method for Nonlinear Problems

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...

Adaptive High-Order Finite-Difference Method for Nonlinear Wave Problems

We discuss a scheme for the numerical solution of one-dimensional initial value problems exhibiting strongly localized solutions or finite-time singularities. To accurately and efficiently model such phenomena we present a full space-time adaptive scheme, based on a variable order spatial finite-difference scheme and a 4th order temporal integration with adaptively chosen time step. A wavelet a...

An Energy Based Adaptive Pushover Analysis for Nonlinear Static Procedures

Nonlinear static procedure (NSP) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. Therefore, the pushover analysis is an important part of each NSP. Accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...

An Adaptive Finite Element Method for Nonlinear Optimal Control Problems

An adaptive accelerated first-order method for convex optimization

In this paper, we present a new accelerated variant of Nesterov’s method for solving a class of convex optimization problems, in which certain acceleration parameters are adaptively (and aggressively) chosen so as to: preserve the theoretical iteration-complexity of the original method, and; substantially improve its practical performance in comparison to the other existing variants. Computatio...