An efficient method to estimate sorption isotherm curve coefficients. Issue 6 (3rd June 2019)

• Record Type: Journal Article
• Authors: Berger, Julien; Busser, Thomas; Dutykh, Denys; Mendes, Nathan
• Is Part Of: Inverse problems in science and engineering. Volume 27:Issue 6(2019)
• Page Start: 735
• Page End: 772
• Publication Date: 2019-06-03
• Subjects: Optimal Experiment Design (OED) -- parameter estimation problem -- convective moisture transfer -- sensitivity functions -- sorption moisture coefficients -- hysteresis; 65N21 -- 80A23 -- 35K55; Engineering mathematics -- Periodicals; Inverse problems (Differential equations) -- Periodicals; 620.001515357
• DOI: 10.1080/17415977.2018.1495720
• Languages: English
• ISSNs: 1741-5977

Abstract

ABSTRACT: This paper aims at estimating the sorption isotherm coefficients of a wood fiber material using experimental data. First, the mathematical model, based on convective transport of moisture, the Optimal Experiment Design (OED) and the experimental set-up are presented. Then, measurements of relative humidity within the material are carried out, after searching the OED using the computation of the sensitivity functions and a priori values of the unknown parameters. It enables to plan the experimental conditions in terms of sensor positioning and boundary conditions out of 20 possible designs, ensuring the best accuracy for the identification method and, thus, for the estimated parameter. After the measurements, the parameter estimation problem is solved. The determined sorption isotherm coefficients calibrate the numerical model to fit better the experimental data. However, some discrepancies still appear since the hysteresis effects on the sorption capacity are not included in the model. Therefore, the latter is improved proposing an additional differential equation for the sorption capacity to consider the hysteresis effects. The OED approach is developed for the estimation of five of the coefficients involved in the hysteresis model. To conclude, the prediction of the model with hysteresis have better reliability when compared to the experimental observations.