Surrogate-based optimization of thermal damage to living biological tissues by laser irradiation

TL;DR

This paper presents a surrogate-based optimization approach using Latin Hypercube Sampling and Response Surface Models to analyze and optimize thermal damage in biological tissues caused by laser irradiation.

Contribution

It introduces a novel surrogate-based framework combining LHS and RSM for optimizing thermal damage in tissues with a dual phase lag model.

Findings

Quadratic response of maximum temperature to input variables.

Thermal damage response also exhibits quadratic behavior.

Comparison shows the effectiveness of the surrogate model with different sample sizes.

Abstract

The surrogate-based analysis and optimization of thermal damage in living biological tissue by laser irradiation are discussed in this paper. Latin Hypercube Sampling (LHS) and Response Surface Model (RSM) are applied to study surrogate-based optimization of thermal damage in tissue using a generalized dual phase lag model. Response value of high temperature as a function of input variables and relationship of maximum temperature and thermal damage as a function of input variables are investigated. Comparison of SBO model and simulation results for different sample sizes are examined. The results show that every input variable individually has quadratic response of maximum temperature and maximum thermal damage in highly absorbing tissues.