Search results

The purpose of this paper is to accelerate the time‐consuming task of assembling the impedance matrix resulting from the discretization of integral equations by the moment method, accelerated using massively parallel processing scheme.

This paper provides several approaches for the implementation of moment method on compute unified device architecture (CUDA) capable general purpose video cards, as well as giving general implementation design patterns and a good overview on the topic.

The proposed method seems to be efficient in the light of the presented numerical results.

The subject of the paper is an evolving, considerably new aspect among computation techniques which could be of high interest for the scientific community.

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

THE most difficult problem in an analysis of a split axle type of undercarriage is the proper division of the moments which must be carried by the axle and radius rod. These moments are due to wheel overhang and braking torque. It has been found that most of the methods so far devised have resulted cither in a mass of very ponderous calculations based on strain‐energy or, owing to simplifying assumptions, in an erroneous answer. The correct and probably the easiest way is to resolve these external moments into and normal to the plane of the axle, radius rod, and hinge line (hereafter called the plane of the “vee structure”). In order to avoid finding the complicated and numerous equations of a line normal to this plane, and of lines in this plane normal and parallel to the hinge line, as well as equations of the resultant loads and moments required for resolution, the method of rabattément has been developed.

The purpose of this paper is to find the best solver for parallelizing particle methods based on solving Pressure Poisson Equation (PPE) by taking Moving Particle Semi-Implicit (MPS) method as an example because the solution for PPE is usually the most time-consuming part difficult to parallelize.

To find the best solver, the authors compare six Krylov solvers, namely, Conjugate Gradient method (CG), Scaled Conjugate Gradient method (SCG), Bi-Conjugate Gradient Stabilized (BiCGStab) method, Conjugate Gradient Squared (CGS) method with Symmetric Lanczos Algorithm (SLA) method and Incomplete Cholesky Conjugate Gradient method (ICCG) in terms of convergence, time consumption, parallel efficiency and memory consumption for the semi-implicit particle method. The MPS method is parallelized by the hybrid Open Multi-Processing (OpenMP)/Message Passing Interface (MPI) model. The dam-break flow and channel flow simulations are used to evaluate the performance of different solvers.

It is found that CG converges stably, runs fastest in the serial way, uses the least memory and has highest OpenMP parallel efficiency, but its MPI parallel efficiency is lower than SLA because SLA requires less synchronization than CG.

With all these criteria considered and weighed, the recommended parallel solver for the MPS method is CG.

The paper attempts to establish the connection between structural reliability and structural optimization for the particular case of plastic structures. Along this line, the paper outlines a reliability‐based optimization approach to design plastic structures with uncertain interdependent strengths and acted on by random interdependent loads. The importance of such interdependencies, and of some of the other statistical parameters used as input data in probabilistic computations, is demonstrated by several examples of sensitivity studies on both the probability of collapse failure as well as the reliability‐based optimum solution.

THE general theorems given in Sections 4 and 6 include, from the fundamental point of view, all that is required for the analysis of redundant structures. However, to facilitate practical calculations it is helpful to develop more explicit methods and formulae. To find these is the purpose of this Section.

The purpose of this study is to develop a modified parameter identification method and a novel measurement method to calibrate a 3 degrees-of-freedom (3-DOF) parallel tool head. This parallel tool head is a parallel mechanism module in a five-axes hybrid machine tool. The proposed parameter identification method is named as the Modified Singular Value Decomposition (MSVD) method. It aims to overcome the difficulty of choosing the algorithm parameter in the regularization identification method. The novel measurement method is named as the vector projection (VP) method which is developed to expand the measurement range of self-made measurement implements.

Newton Iterative Algorithm based on Least Square Method is analyzed by using the Singular Value Decomposition method. Based on the analysis result, the MSVD method is proposed. The VP method transforms the angle measurement into the displacement measurement by taking full advantage of the ability that the 3-DOF parallel tool head can move in the X – Y plane.

The kinematic calibration approach is verified by calibration simulations, a Rotation Tool Center Point accuracy test and an experiment of machining an “S”-shaped test specimen.

The kinematic calibration approach with the MSVD method and VP method could be successfully applied to the 3-DOF parallel tool head and other 3-DOF parallel mechanisms.

MOST previous methods for predicting moments of resistance of beams subjected to pure bending beyond the limit of proportionality involve somewhat complicated and cumbersome calculations and are usually confined to specific materials and cross‐sections.

This paper aims to develop a method for evaluating the failure probability and global sensitivity of multiple failure modes based on convex-probability hybrid uncertainty.

The uncertainty information of the input variable is considered as convex-probability hybrid uncertainty. Moment-independent variable global sensitivity index based on the system failure probability is proposed to quantify the effect of the input variable on the system failure probability. Two-mode sensitivity indices are adopted to characterize the effect of each failure mode on the system failure probability. The method based on active learning Kriging (ALK) model with a truncated candidate regions (TCR) is adopted to evaluate the systems failure probability, as well as sensitivity index and this method is termed as ALK-TCR.

The results of five examples demonstrate the effectiveness of the sensitivity index and the efficiency of the ALK-TCR method in solving the problem of multiple failure modes based on the convex-probability hybrid uncertainty.

Convex-probability hybrid uncertainty is considered on system reliability analysis. Moment-independent variable sensitivity index based on the system failure probability is proposed. Mode sensitivity indices are extended to hybrid uncertain reliability model. An effective global sensitivity analysis approach is developed for the multiple failure modes based on convex-probability hybrid uncertainty.

PROBLEMS relating to built‐in or rigid‐end members under transverse loading are frequently encountered by the aircraft engineer. In the following paper discussion of relevant theorems leads to the development of Clapeyron's Theorem of Three Moments. The latter is particularly valuable in, for example, estimating the crankshaft bearing loads in a non‐radial engine. Attention is also drawn to Wilson's method of solving continuous beam problems. This simple method produces results identical with those given by the Theorem of Three Moments and deserves wider recognition.