Determination of the Neutral Temperature of Slender Beams by Using Nonlinear Solitary Waves

Abstract

Slender columns subjected to compressive stress are common in many civil structures. The rapid in situ measurement of this stress may prevent structural buckling. In this study, the authors applied an artificial neural network (ANN) to process numerical data that describe the coupling mechanism between highly nonlinear solitary waves (HNSWs) propagating along a granular system and a beam in contact with the granular medium. The aim is to evaluate the ability of HNSWs to measure stress in thermally loaded structures and to estimate the neutral temperature, i.e., the temperature at which the stress is null. Nonlinear solitary waves are compact nondispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles, where they are conventionally generated by the mechanical impact of a striker. The authors numerically investigated a straight chain of spherical particles in contact with a prismatic beam subjected to thermal stress. The effect of the neutral temperature on certain features of the waves was examined. These features then were fed into an ANN with the aim of estimating the neutral temperature. In the future, the findings presented in this paper may be used to develop a novel sensing system for the nondestructive prediction of neutral temperature and thermal buckling.