Numerical modeling for embedding of fiber Bragg grating sensors within metallic structures using laser solid freeform fabrication

Abstract

This paper aims at numerical modeling of laser solid freeform fabrication (LSFF) process utilized in embedding of fiber Bragg grating (FBG) sensors inside metallic structures. This model is used in characterization of the process. Fiber Bragg grating sensors have the capability of being embedded inside structures for monitoring temperature, strain and pressure. Due to the sensitivity of the FBG sensors to high temperatures and stresses, the embedding process using LSFF is a challenging task. In the present paper, a finite element model is developed to predict the stress and temperature fields adjacent to the fiber optic sensor inside the metallic structure and maps them to the spectral response of the sensor. Using this method, the stress-strain and temperature conditions of the sensor during the embedding process can be monitored and the modeling data can be used for process control and characterization to minimize the effects of high temperatures and residual stresses having negative effects on sensor coherence with the surrounding media. Finally, the proposed model is validated with an existing analytical model predicting temperature field and melt pool geometry.This paper aims at numerical modeling of laser solid freeform fabrication (LSFF) process utilized in embedding of fiber Bragg grating (FBG) sensors inside metallic structures. This model is used in characterization of the process. Fiber Bragg grating sensors have the capability of being embedded inside structures for monitoring temperature, strain and pressure. Due to the sensitivity of the FBG sensors to high temperatures and stresses, the embedding process using LSFF is a challenging task. In the present paper, a finite element model is developed to predict the stress and temperature fields adjacent to the fiber optic sensor inside the metallic structure and maps them to the spectral response of the sensor. Using this method, the stress-strain and temperature conditions of the sensor during the embedding process can be monitored and the modeling data can be used for process control and characterization to minimize the effects of high temperatures and residual stresses having negative effects on sensor c...