Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
Numerical estimation of nonlinear volumetric heat capacity and Laser Beam Welding (LBW) efficiency
Submission Author:
Ariel Flores Monteiro de Oliveira , SP
Co-Authors:
Ariel Flores Monteiro de Oliveira, Elisan dos Santos Magalhães, Kahl Zilnyk
Presenter: Ariel Flores Monteiro de Oliveira
doi://10.26678/ABCM.COBEM2023.COB2023-0699
Abstract
Several industrial processes are realized in high temperatures, i.e., temperatures close to the melting point, such as welding, additive manufacturing, and forging. In order to simulate these processes, besides selecting a precise thermal model, one must implement the proper material’s thermal properties. Regarding heat transfer simulations, it is usual to account for the thermal properties as temperature functions in order to consider the properties’ variations due to temperature effects. However, it is challenging to find particular properties, mainly for high-temperature conditions. Regarding metals, the variable compositions also hinder precise data being found. Hence, various numerical approaches have been propounded to estimate the material’s thermal properties. The Quadrilateral Optimization Method (QOM) was chosen for the estimations in this work. The method is based on a laser beam welding (LBW) heat transfer model that acquires the temperature distribution over an AISI 1020 sample. The algorithm written in CUDA-C language was modified to assess the steel’s process efficiency and volumetric heat capacity (ρcp). The efficiency is obtained by estimating the laser power that defines the heat input on the sample. The volumetric heat capacity is implemented in the code as an exponential function of temperature (T) with one independent parameter and one temperature-dependent parameter. Thus, the determination of ρcp(T) requires the definition of two parameters. Therefore, the QOM was configured to ascertain three variables simultaneously. The goal values for the function parameters are based on the fit of literature data for AISI 1020 steel, while the efficiency is based on the experimental setup. The QOM provides an objective function that must be minimized to improve the estimations. The function is subjected to a Time Traveling Regularization (TTR) to enhance its sensibility. As this regularization adds the time factor to the analysis, a suitable number of time steps must be accounted for. The optimum number is evaluated and applied in this work. The simulated temperature using reference and estimated values, considering an optimum number of time steps, were compared and showed no significant deviations. Consequently, the estimated parameters are accurate enough to represent the thermal cycle precisely. Moreover, the QOM is suitable for simultaneously estimating the volumetric heat capacity in function of temperature and the power directed to the sample.
Keywords
numerical estimation, Quadrilateral Optimization Method, temperature-dependent properties, GPU processing, laser beam welding
