1. CDS
  2. All Volumes and Issues
  3. Volume 4, Number 1, 2022
  4. The use of cellular automata in the simulation of wood drying processes in a wood drying chamber of periodic action

The use of cellular automata in the simulation of wood drying processes in a wood drying chamber of periodic action

CDS.
2022;
Volume 4, Number 1
: pp. 17 - 31
https://doi.org/10.23939/cds2022.01.017
Authors:
  1. Ya. I. Sokolovskyy
  2. O. V. Sinkevych
1
Lviv Polytechnic National University, Lviv, Ukraine
2
National Forestry University of Ukraine, Lviv, Ukraine

In this work, research the essence of the wood drying process in a periodic wood drying chamber. This paper provides a mathematical model of a wood drying chamber, which describes the general essence of physical drying processes using the equipment available in the wood drying chamber. This approach allows to take into account the physical parameters of the necessary equipment, such as heaters, fans, humidifying nozzles or other. This approach also allows to ignore some design characteristics that may differ depending on the type of wood drying chamber. Considering this, the main task in this work is to determine the temperature and humidity of the drying agent and lumber in the stack, as well as the temperature of the main components of the wood drying chamber. Taking into account such a large number of input parameters and describing a complex non-stationary process of heat transfer, there is a need to create complicated mathematical models. The presence of such mathematical models greatly complicates their application and requires significant computer resources for their calculation. In this way, the mathematical description is reduced to the description of non-linear partial differential equations. To simplify and speed up the calculations of this mathematical model, the use of cellular automata is suggested. To do this, the 3D model of the wood drying chamber is represented as a cell-automatic field, which consists of cells of the same size but different types. As a result, neighboring cells contain local relationships that describe their general behavior. This behavior depends on the type of tangent cells and is described by transition rules based on a mathematical model. Through the use of the developed cell-automatic model and transition rules, it is possible to obtain the values of the temperature and moisture content of the wood in the stack, the drying agent in the chamber, as well as the temperature of the main components of the chamber. The work also shows the corresponding graphs of changes in temperature and moisture content. To check the adequacy and reliability, the obtained results were compared with the results of other authors' experiments. As a result of the verification, the values of the average absolute error aren't high, which confirms the adequacy of the mathematical model and the prospects of using the developed cell-automatic model.

mathematical model
Non-stationary process of heat and moisture transfer
3D model
Cellular-automata model
transition rules
  1. Volkhonov M., Jabbarov I., Soldatov V., & Smirnov I. (2018). Development of the method of exposure control of grain drying in high­temperature dryers. Eastern-European journal of enterprise technologies., 3, 22–29. https://doi.org/10.15587/1729-4061.2018.133607
  2. Ivanova D., Valov N., Valova I., & Stefanova D. (2017). Optimization of Convective Drying. Tem journal., 6.3, 572-577. https://doi.org/10.18421/TEM63-19
  3. Solomon A., Claudiu V., & Bogoi A. (2022). Some practical remarks in solving partial differential equations using reduced order schemes obtained through the POD method. Incas Bulletin., 14.1, 187-196.  https://doi.org/10.13111/2066-8201.2022.14.1.15
  4. Gibson, M. J., Keedwell, E. C., & Savi'c, D. A. (2015). An investigation of the efficient implementation of cellular automata on multi-core CPU and GPU hardware. Parallel Distrib. Comput., 77, 11–25.  https://doi.org/10.1016/j.jpdc.2014.10.011
  5. Sitko, M., Chao, Q., Wang, J., Perzynski, K., Muszka, K., & Madej, L. (2020). A parallel version of the cellular automata static recrystallization model dedicated for high performance computing platforms – Development         and         verification.         Comput.           Mater.         Sci.,          172,          109–283.https://doi.org/10.1016/j.commatsci.2019.109283
  6. Shumylyak, L., Zhikharevich, V., & Ostapov, S. (2016). Modeling of impurities segregation phenomenon in the melt crystallization process by the continuous cellular automata technique. Applied Mathematics and Computation, 290, 336–354. https://doi.org/10.1016/j.amc.2016.06.012
  7. Salehi, M. S., & Serajzadeh, S. (2012). Simulation of static recrystallization in non-isothermal annealing using a coupled cellular automata and finite element model. Comput. Mater. Sci., 53, 145–152.  https://doi.org/10.1016/j.commatsci.2011.09.026
  8. Zaitsev, D. A. (2018). Simulating Cellular Automata by Infinite Petri Nets. Journal of Cellular Automata, 13(1–2), 121–144.
  9. Bandini, S., & Magagnini, M. (2001). Parallel Processing Simulation of Dynamic Properties of Filled    Rubber    Compounds    Based    On    Cellular    Automata.    Parallel    Comput.,    27,    643–661.https://doi.org/10.1016/S0167-8191(00)00082-X
  10. Svyetlichnyy, D. S. (2010). Modeling of the microstructure: From classical cellular automata approach to the frontal one. Comput. Mater. Sci., 50, 92–97. https://doi.org/10.1016/j.commatsci.2010.07.011
  11. Sokolovskyy, Ya., Sinkevych, O., & Voliansky R. (2019). Software for Studying Wood Drying Chambers Based on SolidWorks Flow Simulation Experiment. Experience of Designing and Application of CAD Systems, 2019, 24-27. https://doi.org/10.1109/ACITT.2019.8780040
  12. Lee J.-Y., Seid E.R., & Majozi M. (2015). Heat Integration of Material Transfer Streams in Batch         Processing        Plants.         Chemical        engineering        transactions,         45,         127-132.https://doi.org/10.3303/CET1545022
  13. Benthien J.T., Riegler M., Engehausen N., & Nopens M. (2020). Specific Dimensional Change Behavior of Laminated Beech Veneer Lumber in Terms of Moisture Absorption and Desorption. Fibers, 8.47, 47.  https://doi.org/10.3390/fib8070047
  14. Sokolovskyy, Ya., Sinkevych, O., & Volianskyi, R. (2020). The study of cellular automata method when used in the problem of capillary-porous material thermal conductivity. Advances in Intelligent Systems and Computing V: Springer Computer Science, 1293, 714–729. https://doi.org/10.1007/978-3-030-  63270-0_49
  15. Faiza M., Kamilia A., Mohammed E., Rachid B., & Slimane G. (2017). Numerical analysis of heat,  air,  and  moisture  transfers  in  a  wooden  building  material.  Thermal  science,  21.2,  785-795.https://doi.org/10.2298/TSCI160421248M
  16. Sokolovskyy, Ya., & Sinkevych, O. (2021). The use of cellular automata in modeling the processes  of  wood  drying  in  a  stack.  Ukrainian  Journal  of  Information  Technology,  3.2,  39-44.https://doi.org/10.23939/ujit2021.02.039
  17. Sychevsky V.A., Chorny A.D., & Baranova T.A. (2016). Optimization of aerodynamic conditions of the chamber drier operation. Izvestiâ vysših učebnyh zavedenij i ènergetičeskih ob edinennij sng. Ènergetika, 59.3, 260-271. https://doi.org/10.21122/1029-7448-2016-59-3-260-271
  18. Sokolovskyy, Ya., & Sinkevych, O. (2018). Software and algorithmic support for represettation of 3D models in 2D von Neumann neighborhood. CEUR Workshop Proceedings, 2300, 215–218.  https://ceur-ws.org/Vol-2300/Paper52.pdf
  19. Sokolovskyy, Ya., Sinkevych, O., & Voliansky, R. (2019). Development the software for simulation of physical fields in wood drying chambers by using cellular automata. Materials of the XV International Conference CADSM'2019, 24–27. https://doi.org/10.1109/CADSM.2019.8779262
  20. Sokolovskyy, Ya., Shymanskyi, V., Levkovych, M., & Yarkun V. (2017). Mathematical and software providing of research of deformation and relaxation processes in environments with fractal structure. Computer Sciences and Information Technologies CSIT 2017, 24-27. https://doi.org/10.1109/STC-  CSIT.2017.8098728
  21. Sokolovskyy, Ya., & Shymanskyi, V. (2014). Mathematical Modelling of Non-Isothermal Moisture Transfer and Rheological Behavior in Cappilary-Porous Materials with Fractal Structure During Drying. Canadian Center of Science and Education, 7.4, 111-122. https://doi.org/10.5539/cis.v7n4p111
  22. Sokolovskyy, Ya., Shymanskyi, V., & Levkovych, M. (2016). Mathematical modeling of non- isothermal moisture transfer and visco-elastic deformation in the materials with fractal structure. Computer science and information technologies CSIT 2016, 91-95. https://doi.org/10.1109/STC-CSIT.2016.7589877