<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This article demonstrates that it is possible to optimize the drying process for pine wood in two independent ways. Those ways involve either the use of the critical diffusion coefficient (DC) which is determined by the experiment shown below, and/or the drying air moistening impulse in the second drying phase. When processing data which has been gained from the pine wood drying experiment, both coincidences and differences were found when compared to the results from a simulation of the drying process which was carried out using the same drying schedule. There is a relatively good level of agreement between the drying experiment and the simulation results of TORKSIM v5.11 simulation program in the case of the simulated and experimentally determined drying curves. The magnitude of numerical values for the DC agrees with this finding, as do the wood's moisture profile in the final phase of the drying experiment at 142 hours, the simulated and measured wood surface temperatures from the beginning of drying to a point at 60 hours into the process, and the simulated wood stresses when compared with the maximum values for the electrical surface-core ratio (ESCR) graph, as determined by the experiment. It was found that the DC's numerical value decreases sharply by about 1.5 times after transitioning from the first drying phase to the second drying phase.</p>
</abstract>

This article demonstrates that it is possible to optimize the drying process for pine wood in two independent ways. Those ways involve either the use of the critical diffusion coefficient (DC) which is determined by the experiment shown below, and/or the drying air moistening impulse in the second drying phase. When processing data which has been gained from the pine wood drying experiment, both coincidences and differences were found when compared to the results from a simulation of the drying process which was carried out using the same drying schedule. There is a relatively good level of agreement between the drying experiment and the simulation results of TORKSIM v5.11 simulation program in the case of the simulated and experimentally determined drying curves. The magnitude of numerical values for the DC agrees with this finding, as do the wood's moisture profile in the final phase of the drying experiment at 142 hours, the simulated and measured wood surface temperatures from the beginning of drying to a point at 60 hours into the process, and the simulated wood stresses when compared with the maximum values for the electrical surface-core ratio (ESCR) graph, as determined by the experiment. It was found that the DC's numerical value decreases sharply by about 1.5 times after transitioning from the first drying phase to the second drying phase.

Optimizing the pine wood drying process using a critical diffusion coefficient and a timed moistening impulse

Institute of Forestry and Rural Engineering

Forestry Studies

This work is licensed under the Creative Commons Attribution 4.0 International License.

Männipuidu kuivatuse protsessi optimeerimine, kasutades kriitilist difusiooni konstanti ja ajastatud niisutusimpulssi

This article demonstrates that it is possible to optimize the drying process for pine wood in two independent ways. Those ways involve either the use of the...

Optimizing the pine wood drying process using a critical diffusion coefficient and a timed moistening impulse

Article Category: Research paper

Pubblicato online: 04 giu 2022

Pagine: 150 - 165

Ricevuto: 17 nov 2021

Accettato: 31 dic 2021

DOI: https://doi.org/10.2478/fsmu-2021-0017

Parole chiave
critical diffusion coefficient, moistening impulse, optimization, wood drying

© 2021 Hannes Tamme et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Optimizing the pine wood drying process using a critical diffusion coefficient and a timed moistening impulse

Article Category: Research paper

Pubblicato online: 04 giu 2022

Pagine: 150 - 165

Ricevuto: 17 nov 2021

Accettato: 31 dic 2021

DOI: https://doi.org/10.2478/fsmu-2021-0017

Parole chiavecritical diffusion coefficient, moistening impulse, optimization, wood drying

© 2021 Hannes Tamme et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
critical diffusion coefficient, moistening impulse, optimization, wood drying