Moisture Content Distribution Research Articles

Moisture migration mechanism of round bamboo in the radial direction during drying

Round bamboo exhibits a hierarchical gradient wall structure and contains closed bamboo cavities, creating a complex pathway for radial moisture migration. In this project work, round bamboo was dried at different temperatures (60, 75 and 90 °C), and the radial moisture content distribution and moisture migration pathway in the drying process were elucidated using the X-ray method, micromorphology and theoretical calculations. The porosity and average aperture of the inner bamboo internode were 38.92 % and 14.98 nm respectively, which were higher than those of the outer (23.17 % and 13.83 nm). The moisture diffusion coefficient at the bamboo diaphragm was about 1/4 that of the bamboo internode. The radial moisture content distribution in fresh round bamboo exhibited an asymmetric distribution, with higher levels in the middle and lower levels on both sides. During the drying process, moisture primarily migrated through the outer surface under the moisture gradient, with a small amount entering the bamboo cavity through the inner surface by temperature action. The moisture entering the bamboo cavity eventually migrated slowly through the diaphragm.

Evaluating Moisture Content in Immersion Vacuum-Cooled Sausages with Citrus Peel Extracts Using Hyperspectral Imaging.

The moisture content of immersion vacuum-cooled sausages with modified casings containing citrus fruit extracts under different storage conditions was studied using hyperspectral imaging (HSI) associated with chemometrics. Different pre-processing combinations were applied to improve the robustness of the model. The partial least squares regression model, employing the full reflectance spectrum with pre-treatment of the standard normal variate, showed calibration coefficients of determination (Rc2) of 0.6160 and a root mean square error of calibration (RMSEC) of 2.8130%. For the first time, prediction maps developed via HSI visualized the distribution of moisture content in the immersion vacuum-cooled sausages with unique modified casings in response to fluctuating storage conditions. The prediction maps showed exact parts with high water content, which will help us to monitor and prevent mold growth. The combination of HSI with multivariate analysis not only quantifies changes in moisture content but also visually represents them in response to various casing treatments under different storage conditions, illustrating the significant potential for real-time inspection and early mold detection in sausages within the processed meat industry.

Laboratory exploration of a novel method to protect silicate relics against salt efflorescence by directional induction of water

Salt efflorescence is one of the critical problems for the preservation of immovable silicate relics. Salt efflorescence mainly comes from continuous cycles of crystallization/dissolution or hydration/dehydration of salts in confined pores in silicate relics. Many protocols have been developed in attempts to alleviate possible salt damages with minor success because of endless water and salt feed from underground. In this study, we propose and design a novel technique for salt damage prevention and protection of immovable relics. Materials with higher water-absorbing ability than matrix are applied to control the water and salt migration direction in simulated sand samples. The distribution of moisture content on the surface of sand is followed by hyperspectral imaging. It appears that water and salt molecules will preferentially transport towards positions containing higher water-absorbing material. Both organic and inorganic high water-absorbing materials show effective in controlling the water and salt migration direction, which provides a new approach for the prevention and protection of salt efflorescence in silicate cultural relics.

Estimating soil moisture content in citrus orchards using multi-temporal sentinel-1A data-based LSTM and PSO-LSTM models

Soil moisture content is a vital variable in agricultural, hydrological, ecological and climatological processes. However, susceptible to soil type, soil structure, topography, vegetation and human activities, soil moisture content exhibits strong spatial heterogeneity in spatial distribution, which makes it difficult to accurately estimate the soil moisture content distribution information at a large scale using conventional methods. To solve the problem, this study proposed a novel hybrid model (PSO-LSTM) based on the particle swarm optimization (PSO) and long short-term memory (LSTM) network model to accurately predict soil moisture content at a large scale. Five different input combinations were constructed based on the vertical polarization (VV) and cross-polarization (VH) of multi-phase Sentinel-1A data, and the soil moisture content at depths of 5 cm, 10 cm, 20 cm and 40 cm in citrus orchards were estimated using the standalone LSTM and hybrid PSO-LSTM models. The results showed that the estimation accuracy of the hybrid PSO-LSTM model was greater than that of the standalone LSTM model at different depths, with the normalized root mean square error (NRMSE) of 4.568–11.023 % and 18.056–30.156 %, respectively. With the VV polarization as the only inputs, the PSO-LSTM model obtained high prediction accuracy, with the normalized root mean square error (NRMSE) of 5.458–10.125 %, respectively. Therefore, the PSO-LSTM model with VV polarization input was recommended to estimate the soil moisture content at different depths in citrus orchards, which provides important data for decision-making on distributed precision irrigation at a large scale.

Wood sandwich softening behavior via coupling of moisture and heat

The controllability of the position and thickness of the compressed layer in the sandwich compression wood is primarily based on the yield stress distribution during a hydrothermal treatment. In this study, the variation law of the yield stress of poplar wood was analyzed in the moisture content (MC) range of absolute dryness to saturation and the temperature range of 30–210℃. A prediction model of wood yield stress response to MC and temperature was developed and the formation of sandwich compression was analyzed. The yield stress of the wood was influenced by the thermal effect and plasticizing effect. In the process of increasing temperature and MC, the yield stress decreased gradually. And the yield stress change rate was 0.29–0.46 MPa in the MC range of 5–10%. The prediction model of wood yield stress was developed by a multiple linear regression analysis. This example demonstrated that coupling distributions of MC and temperature were formed upon heating at 180℃, which led to a gradient distribution of the glass transition temperature and yield stress inside the wood. This phenomenon resulted in the sandwich softening behavior under the coupling of moisture and heat, which was the key formation mechanism of sandwich compressed wood.

Visualisation of moisture content distribution maps and classification of freshness level of loquats

Moisture content (MC) and freshness undergo evident changes during the storage of loquat fruits and thus are important indices of loquat fruit quality. Conventional methods for assessing MC and freshness are typically destructive and time-consuming, and cannot provide distribution maps of MC in the whole loquats. In this study, the use of hyperspectral imaging (HSI) was investigated for rapid and non-destructive prediction of MC in loquats, and for the visualisation of their MC distribution maps. Furthermore, freshness level discrimination models for loquats at different storage times were established using partial least squares discriminant analysis (PLS-DA), multinomial logistic regression (MLogR), and back-propagation neural network (BPNN) classification models. MC was well-predicted, with the best residual predictive deviation (RPD) of 2.40. Using the best prediction model, the distribution maps of MC in loquats were visualised. Additionally, the competitive adaptive reweighted sampling (CARS)-BPNN model obtained superior discrimination performance, with 95.56 % and 93.33 % accuracy for the calibration and prediction sets. Our results show that HSI is a promising fast and non-destructive method for determining MC and freshness of loquats.

A Practicable Guideline for Predicting the Thermal Conductivity of Unconsolidated Soils

For large infrastructure projects, such as high-voltage underground cables or for evaluating the very shallow geothermal potential (vSGP) of small-scale horizontal geothermal systems, large-scale geothermal collector systems (LSCs), and fifth generation low temperature district heating and cooling networks (5GDHC), the thermal conductivity (λ) of the subsurface is a decisive soil parameter in terms of dimensioning and design. In the planning phase, when direct measurements of the thermal conductivity are not yet available or possible, λ must therefore often be estimated. Various empirical literature models can be used for this purpose, based on the knowledge of bulk density, moisture content, and grain size distribution. In this study, selected models were validated using 59 series of thermal conductivity measurements performed on soil samples taken from different sites in Germany. By considering different soil texture and moisture categories, a practicable guideline in the form of a decision tree, employed by empirical models to calculate the thermal conductivity of unconsolidated soils, was developed. The Hu et al. (2001) model showed the smallest deviations from the measured values for clayey and silty soils, with an RMSE value of 0.20 W/(m∙K). The Markert et al. (2017) model was determined to be the best-fitting model for sandy soils, with an RMSE value of 0.29 W/(m∙K).

Prediction of CPTu static sounding parameters based on DPH dynamic probing heavy test on the example of “the Praski terrace” sands inWarsaw title

This paper attempts to relate the parameters obtained from CPTu static sounding and DPH dynamic test conducted in non-cohesive alluvial deposits of the Vistula River. The investigation was carried out in eight test stations located on the left bank of the Vistula River in Warsaw. The presented theses were based on the results of static CPTU and dynamic DPH tests obtained at 8 test stations. Additionally, in order to associate the obtained sounding results to the lithological type of the tested medium, drillings and grain size analyses were performed. The correlation of the different test methods stems from the need to identify and explain observed discrepancies against the background of different geological conditions, such as moisture content or grain size distribution. The comparative analysis of the parameters obtained from static and dynamic probing, is relevant to the alluvial sediments formed the lower over-flood terrace (called “the Praski terrace”) of Warsaw. Based on the comparison this paper proposes a correlation between the cone penetration resistance the sleeve friction and the number of blows, expressed by the functional relationship. Differences in the matching formulas were shown depending on the saturation of the tested sediments. Correlations were referred to a soil type, which enabled to specify the range of applicability of the proposed relationships. The results of the study were further used to show their diversity using statistical methods. This made it possible to assess the variability of the parameters of the non-cohesive soil, which forms a single lithogenetic unit.

Design and Optimization of a Mixed-Flow Drying Chamber for Tiger Nuts Based on CFD-DEM Heat and Mass Transfer Model

In order to solve the problem of inconsistent moisture content in particles during the drying process of tiger nuts (Cyperus esculentus) due to uneven air flow and temperature distribution in the drying chamber, an open-hole corner box was designed based on the principle of negative pressure micro-perforated air supply. Using computational fluid dynamics (CFD) and discrete element method (DEM) simulation, coupled with the basic theory of interphase heat and mass transfer, a mathematical model for interphase heat and moisture coupling transfer was established. The effects of different aperture rates of corner boxes in the drying chamber, spatial location arrangement, and other related variables on the airfield distribution, temperature field distribution, tiger nut temperature, and moisture content changes were investigated. The results show that the average air velocity below the air inlet gradually increases as the opening ratio increases. When the opening rate is 0.33%, the wind field uniformity is better, and the inhomogeneity of the drying chamber wind field is improved. As the lateral distance increases, the consistency of the moisture content distribution increases and then decreases, and the flow rate of the tiger nuts gradually increases when the grain is discharged. The rate of decrease in water content decreases gradually with the increase in longitudinal distance. When the wind speed reaches 4 m/s, the drying chamber wind field is more uniform, and the water vapor diffusion efficiency at the outlet is basically the same. Therefore, the appropriate corner box has a horizontal distance of 320 mm and a longitudinal distance of 420 mm, providing a basis for the design of tiger nut drying equipment.

Geographic Information System (GIS) Application in Soil Fertility Management: A Review

As the global population expected to reach 10 billion by 2050 and arable land decreases, innovative soil management strategies are required to maximize agricultural productivity while preserving natural resources. GIS, as a powerful technology, offers a comprehensive solution by enabling the collection, storage, analysis, and visualization of spatial data for agricultural purposes. By integrating GIS with sensors, communication technologies, and data analytics, precision agriculture is possible, allowing for efficient use of agricultural inputs and reduced environmental impact. GIS technology facilitates the simulation and modeling of biological ecosystems, providing valuable insights for sustainable soil management. It has diverse applications in agriculture, ranging from soil nutrient mapping to yield estimations and runoff detection. GIS works by overlaying various layers of information onto digital maps, allowing for the identification of relationships and patterns that are crucial for optimizing soil fertility. Detailed maps created through GIS highlight the distribution of soil nutrients, pH levels, and moisture content, enabling informed decision-making on fertilizer use, irrigation techniques, and land management practices. By harnessing the power of GIS, farmers and land managers can make data-driven decisions that maximize agricultural productivity, conserve resources, and protect soil health for future generations. The integration of GIS with other technologies further enhances its effectiveness in soil fertility management. Overall, GIS is a valuable tool for understanding and managing soil fertility, contributing to sustainable agriculture and food security.

Role of particle gradation of clay–sand mixtures on the interfacial adhesion performance of polymer coatings

Abstract The interface performance between clay–sand mixtures and concrete structures is governed by the mixture's composition and its physical properties. Moisture content and particle-size distribution play important roles in deciding the mixture's arrangement of soil particles, porosity, hydraulic conductivity and behaviour under various mechanical loadings. Application of a polymer interfacial coating can improve the bond performance between soils and concrete mainly via interfacial friction/mechanical interlocking. The present work analyses the development of interfacial strength between clay–sand mixtures and a polymer coating with changes in particle gradation. The multi-scale mechanisms at the interface are investigated, giving primary attention to soil porosity. A 50:50 clay–sand mixture exhibited a greater interfacial adhesive performance compared to other soil mixtures. In addition, the moisture-controlled pores and gradation-controlled pores demonstrated differences in macroscale interfacial strength. Both mercury intrusion porosimetry (MIP) and 129Xe nuclear magnetic resonance (NMR) were utilized to detect the pore structure of the mixtures. 129Xe-NMR revealed the pore distribution of the mixtures as ranging from macropores to nanopores, and MIP complemented the pore information by determining the critical pore entry diameter in the macropore regime. Mesopores dominated with increasing fine sand content until a threshold value was reached; thereafter, merging of pores occurred and macropores dominated.

Application of hyperspectral imaging and colorimetric sensor array coupled with multivariate analysis for quality detection during salted duck eggs processing

AbstractIn order to realize the evaluation of salted duck eggs quality, this study constructed salts‐sensitive colorimetric sensor array (CSA) based on silver nanoprisms (AgNPRs) etching principle and utilized hyperspectral imaging (HSI) system to capture the reflectance spectral of CSA and section of salted duck eggs. To minimize the noise in spectral signals, three preprocessing methods including Savitzky–Golay Smoothing (SG), standard normal variate (SNV) transformation, and multiplicative scatter correction were used. The competitive adaptive reweighted sampling and uninformative variables elimination were used to select the optimal wavelengths, and then partial least squares regression was used to predict moisture, lipid, and salt content (SC). Results demonstrated coefficients of determination of 0.8200, 0.8969, 0.8709, and 0.9239 for protein moisture, yolk moisture, yolk lipid, and protein SC. Visualization distribution maps successfully display the distribution of moisture and lipid content during salting periods. The results indicated that the CSA based on AgNPRs etching principle can be an effective tool in quantitative measurement of salt and HSI combining CSA can be applied to evaluate the quality of salted duck eggs comprehensively. The study offers a rapid detection method for the production and processing of salted duck eggs in the industry.Practical applicationA novel salts‐sensitive CSA was constructed to evaluate quality of salted duck eggs based on AgNPRs etching. This study designed and developed a portable sample collection device using 3D printing technology to acquire the information of samples and CSA at the same time. This study combined with HSI system and colorimetric sensor technology to evaluate the quality of salted duck eggs during the salting process.

Water, starch, and nuclear behavior in ray parenchyma during heartwood formation of Catalpa bungei ‘Jinsi’

Catalpa bungei ‘Jinsi’, a cultivar of C. bungei C. A. Mey., is valued for its heartwood with good overall mechanical properties, naturally durable and golden-yellow color. Little is known about heartwood formation in C. bungei ‘Jinsi’ trees. The behavior of starch, water, and nuclei was studied in the xylem tissue of C. bungei ‘Jinsi’ concerning aging in ray parenchyma cells. Blocks containing heartwood, golden zone, transition zone, and sapwood were collected from the stems of six C. bungei ‘Jinsi’ trees. The moisture content of the blocks was measured by oven drying. Changes in starch and nuclei in ray parenchyma were investigated in radial profiles from sapwood to heartwood blocks using microscopy and various staining techniques. The nuclear size and starch content gradually decreased to heartwood. While the horizontal distribution of moisture content of C. bungei ‘Jinsi’ was very varied, with the heartwood and golden zone being lower than sapwood but slightly higher than the transition zone. Starch grains were rare, but nuclei were still present in some ray parenchyma cells in the heartwood and golden zone. The nuclei showed irregular shape and elongation before disintegration. These results suggest that the most apparent change occurs in the transition zone, the critical location involved in forming C. bungei ‘Jinsi’ heartwood. Water and starch appear to be actively engaged in heartwood formation. The loss of function of ray parenchyma cells results from heartwood formation.

Characterizing the dynamic resilient modulus of subgrade soil treated by BT-SAP subjected to freeze-thaw cycles

Freeze-thaw (FT) cycles are regarded as a damage effect to the dynamic resilient modulus (MR) of subgrade soil in seasonal frozen regions and improving the resistance on freeze-thaw cycles must be concerned urgently. For this purpose, the bentonite superabsorbent polymer (BT-SAP) was developed as an available admixture to relieve the attenuation of MR of subgrade soil under FT cycles. In order to evaluate the improvement of resistance on FT cycles, a series of dynamic triaxial tests were conducted after various FT cycles. The main influences on MR were investigated including the numbers of freeze-thaw cycles, BT-SAP contents, deviator stress and confining stress. The experimental results indicate that the BT-SAP can delay the attenuation trend of MR that means the resistance on freeze-thaw cycles have been promoted. The ensuing discoveries are that with the increment of BT-SAP content, the sensitivity of the subgrade soil to FT cycles is gradually reduced. Nevertheless, results reveal that a proper content of BT-SAP is recommended as 0.5%, where if the BT-SAP content exceeds 0.5%, the improvement effect of resistance on FT cycles decreases. Moreover, the improved effect caused by BT-SAP can produce a coupling enhancement combining with confining stress, and it also can offset the softening effect due to the deviator stress. For better application and practicability, the high-accuracy empirical model for predicting MR is established and validated. Finally, based on the soil freezing temperature, unfrozen moisture content and moisture distribution characteristics, the mechanism of BT-SAP reducing the freeze-thaw cycle sensitivity is analyzed. The conclusions mentioned above show that employing BT-SAP material is acceptable and significant to improve resistance on freeze-thaw of subgrade soil.

Computational fluid dynamic simulation of packed bed drying process: impact of particle properties, drying conditions, and lateral edge heating modes on drying kinetics

In this work, a two-dimensional computational fluid dynamic (CFD) model is developed to describe the drying process of a packed bed made of spherical particles. The volumetrical evaporation rate inside the bed is computed from the pressure difference between the particle surface and the airflow. By using the thermal equilibrium assumption, the heat conservation equation is derived. The CFD model is solved in the COMSOL Multiphysics environment. The obtained results indicate remarkable maldistributions of temperature and moisture content. These maldistributions can be explained by the impact of lateral edges on thermo-hydraulic behavior. Additionally, the impact of particle diameter, air velocity, and bed width on the spatial-temporal moisture content and temperature distribution is investigated. It shows that the CFD model can be simplified to the receding front drying model for a bed made of small particles. Furthermore, by changing the thermal boundary conditions at the lateral edges, the influence of the heating mode at the lateral edges on the drying behavior is explored. The results indicate that contact heating at the bed wall can help to accelerate the drying process significantly.

Estimation of spatial distribution of soil moisture on steep hillslopes by state-space approach (SSA)

Soil moisture is a critical variable that quantifies precipitation, floods, droughts, irrigation, and other factors with regard to decision-making and risk evaluation. An accurate prediction of soil moisture dynamics is important for soil and environmental management. However, the complex topographic condition and land use in hilly and mountainous areas make it a challenge to monitor and predict soil moisture dynamics in these areas. In this study, the determinants of soil moisture variability were determined by structural equation modeling, and then an attempt was made to estimate the spatial distribution of soil moisture content on steep hillslope using the state-space method. Herein, soil moisture at different depths (0–10, 10–20, and 20–30 cm) was monitored by portable time-domain reflectometer (TDR) along this hillslope (100 m × 180 m). It showed that the spatial variability of soil moisture decreased with increasing soil wetness, primarily in the topsoil (0–10 cm). Soil moisture was correlated with elevation (r = 0.28, 0.50, and 0.28), capillary porosity (r = 0.06, 0.37, and 0.28), soil texture (r for Clay: 0.20, 0.24, and 0.16; r for Sand: −0.25, −0.18, and −0.28), organic carbon (r = −0.31, −0.08, and 0.10) and land use (r = −0.01, 0.28, and 0.24) under different conditions (dry, moderate, and wet). Among these determinants, elevation made direct contributions to soil moisture variation, especially under moderate conditions, while land use made its impacts by altering soil texture. It is encouraging that the state-space approach yielded precise and cost-effective predictions of soil moisture dynamics along this steep hillslope since it gives the minimum root-mean-square error (RMSE) and Akaike information criterion (AIC). Moreover, soil organic carbon (AIC = −4.497, RMSE = 0.104, R2 = 0.899), rock fragment contents (AIC = −4.366, RMSE = 0.111, R2 = 0.878), and elevation (AIC = −3.693, RMSE = 0.156, R2 = 0.629) effectively anticipated the spatial distribution of soil moisture under dry, moderate, and wet conditions, respectively. This study confirms the efficacy of the state-space approach as a valuable tool for soil moisture prediction in areas characterized by complex and spatially heterogeneous conditions.

Kiln-drying effectiveness as influenced by moisture content and density variation within a Scots pine timber batch

ABSTRACT Sorting of sawn timber batches is crucial for efficient kiln-drying. This study aimed to verify the hypothesis of different drying attributes of 25 mm thick sapwood and mixed Scots pine boards sawn from a group of butt, second, and top logs and assess the effects of kiln-drying. Three options dry-bulb temperature were taken into account. The drying results were evaluated based on the final moisture content distribution, changes in the cross-sectional dimensions of the sawn timber, drying time, and unit heat consumption. Correlations between sawn timber features, drying temperature, and drying results were analyzed using non-parametric statistical tests. The study proved the dependence of the initial moisture content and wood density variation of Scots pine sawn timber on the log type and the position on the round timber cross-section. The variation of drying attributes of the sapwood and mixed 25 mm Scots boards is insignificant in the final moisture content distribution and cross-sectional dimensions. However, green sorting may have only a beneficial effect on drying time and heat consumption.

Use of Artificial Intelligence Methods for Modelling of Drying Processes

In the course of drying process one of the main problems is to exactly determine the moisture content in the material bed. The measurement is an option, but its accuracy is not satisfactory. Another way to determine the moisture distribution is to use physically based or blackbox models. Physically based models give a moderately good result, but it normally takes a great effort to identify their parameters, and to solve the model itself. Derivation of the classical black-box models seems to be an uncomplicated approach. However, the application of such models is mainly limited mainly for process control. Therefore, this paper overviews the application opportunities of the use of artificial intelligence methods. Among those methods (neural network, Fuzzy modelling, genetic algorithm, etc) the main emphasize is given to the use of artificial neural network (ANN) modelling especially for grain drying as a widely applied dehydration technology. A methodology is given to the selection aspects of neural network structure and specifically to the main influencing model parameters as sampling time, randomised training, different training algorithms, number of hidden neurones, number of linked data series and type of validation data. Based on the recent study, it is concluded that the ANN can be used during effectively in case of post-harvest processes especially for estimation the temperature and moisture content distribution.

Spatially-temporal distribution of moisture content and dynamics of greenhouse gas emissions from upper soil horizons in floodplain fallow lands of Bashmakovsky district of Penza oblast

There are more than 1’300 thousand hectares of fallow lands potentially suitable for agricultural producers in the Penza region of Russia, which is 31% of the region total area. More than 300000 hectares of land have been abandoned for more than 20 years, and territory already became forest. Additionally soils under young forests – actively sequester carbon dioxide in soil. How much it makes sense to raise fallow land in terms of climate change and which areas produce the most carbon dioxide from the soil is a research question of great interest. In addition to vegetation, factors such as soil moisture and temperature influence the carbon dioxide emission from soil. As a result, the greenhouse gas fluxes monitoring, we can conclude that forest areas and natural ecosystems mostly deposit carbon dioxide, as the amount of available carbon increases due to a greater increase in biomass. Areas that are used in agriculture produce more nitrous oxide and methane, but less carbon dioxide, which is associated with the specifics of fertilization.

Software tools for calculating the main parameters of the drying process of anisotropic materials

Modern technologies for processing anisotropic materials require an integrated approach to controlling the drying process, which significantly affects the quality and properties of the material. This paper investigates the development of software tools for calculating the main parameters of the drying process of anisotropic materials. The use of cellular automata in this context allows modeling and controlling the distribution of temperature, moisture content, and stresses in the dried material. The work includes the development of a structural diagram and a modeling algorithm, in particular, taking into account the anisotropy of the physical and mechanical characteristics of wood. One of the key features of the work is the possibility of extending the existing transition rules for the cellular automaton model, which allows determining the initial moisture content in the cells based on its gradient at the boundaries and in the center of the wood. Software tools implemented in C++ programming language using the cross-platform environment "Code::Blocks" and the library "wxWidgets" provide the user with an intuitive and user-friendly graphical interface. The user can define input parameters, including geometric dimensions of the material, dryer characteristics, and other process parameters. An important function of the program is the output of results in the form of graphs illustrating the distribution of temperature, moisture content and stresses at different stages of drying. The user can also specify parameters for detailed analysis and export data for further research in Microsoft Excel. The study was conducted on pine wood material, taking into account various drying parameters. The modeling results demonstrate a significant effect of time and process parameters on the distribution of moisture and stresses in the material, which is in line with real-world conditions.