Inverse Estimation of Effective Moisture Diffusivity in Lumber during Drying Using Genetic Algorithms

Abstract

This article presents a methodology based on genetic algorithms (GA) optimization with a three-dimensional numerical solution to the diffusion model obtained by using the finite volume method (FVM) for determining the effective moisture diffusivity in lumber. The objective or error function between measured and simulated drying curves was obtained, and the effective moisture diffusivity parameters with greatest correspondence between measured and estimated values were obtained. As a result, a new equation for effective moisture diffusivity was proposed, which depends on lumber moisture content and drying temperature. Effective moisture diffusivities ranged from 1.120 × 10-9 to 1.277 × 10-8 m2/s. Finally, the proposed coefficients were validated by experiments. The drying kinetics were successfully simulated with the optimized effective moisture diffusivity model.

Keywords

• Effective moisture diffusivity
• Inverse problem
• Genetic algorithms
• Optimization