Finite Element Model Fractional Steps Updating Strategy for Spatial Lattice Structures Based on Generalized Regression Neural Network

Caiwei Liu,Jijun Miao,Changyong Zhao

doi:10.1155/2016/5845326

Abstract

In order to get a more accurate finite element model of a spatial lattice structure with bolt-ball joints for health monitoring, a method of modifying the bolt-ball joint stiffness coefficient was proposed. Firstly, the beam element with adjustable stiffness was used in the joint zone in this paper to reveal the semirigid characteristic of the joint. Secondly, the value of stiffness reduction factor (ar) was limited in the range of[0.2,0.8]and the reference value (ar0) of it was suggested to be 0.5 based on referenced literatures. Finally, the finite element model fractional steps updating strategy based on neural network technique was applied and the limited measuring point information was used to form the network input parameter. A single-layer latticed cylindrical shell model with 157 joints and 414 tubes was used in a shaking TABLE test. Based on the measured modal data, the presented method was verified. The results show that this model updating technique can reflect the true dynamic characters of the shell structure better. Moreover, the neural network can be simplified considerably by using this algorithm. The method can be used for model updating of a latticed shell with bolt-ball joints and has great value in engineering practice.

Highlights

Structural health monitoring is becoming increasingly important, in the prevention of catastrophic failures, and in improving maintainability of aerospace, civil, and mechanical infrastructure
The results show that this model updating technique can reflect the true dynamic characters of the shell structure better
The corresponding stiffness reduction factor is ar1, the step of training samples is set to b2 within the variation range of [−R1, R1] (R1 < R0), and c2 is the number of steps. ar1×(1−(c2/2)b2)EIr, . . . , ar1×(1−b2)EIr, ar1 × 1.0EIr, and ar1 × (1 + b2)EIr, . . . , ar1 × (1 + (c2/2)b2)EIr are put into the semirigid model of the spatial lattice structure

Summary

Introduction

Structural health monitoring is becoming increasingly important, in the prevention of catastrophic failures, and in improving maintainability of aerospace, civil, and mechanical infrastructure. When the friction coefficient and contact parameters were determined according to the results of repeated trials, the stiffness reduction factors of the four types of bolt-ball joints were obtained (i.e., 0.524, 0.466, 0.317, and 0.122). By using these factors, sound model updating results could be determined. In order to get a more accurate finite element model of a spatial lattice structure with bolt-ball joints for health monitoring, a new method that is suitable for the spatial lattice structure was proposed in this paper and was used to analyze experimental results of a singlelayer latticed cylindrical shell model with 157 joints and 414 tubes tested using a shaking TABLE. The method can be used for model updating of a latticed shell with bolt-ball joints and has great value in engineering practice

Construction of Semirigid Model

Updating Strategy Basing on GRNN

Finite Element Model Updating of SingleLayer Lattice Cylindrical Shell

Findings

Conclusions