Experimental Investigation and CFD Modeling of Heat and Mass Transfer During Drying of Alfalfa Leaf Fraction in a Rotary Drum Dryer

Modeling and Experimental Analysis of a Dual-collector Indirect Solar Dryer for Intermittent and Continuous Drying of Bioproducts

This study presents the development and experimental validation of a coupled heat and mass transfer model for a dual-collector indirect solar dryer based on the energy balance of a representative section of the system. The governing equations describe the simultaneous evolution of collector temperature, drying air temperature and product moisture content while accounting for solar irradiance variations of up to 1050 W m⁻², convective heat transfer and both continuous and intermittent drying modes. Experimental tests were conducted on banana (Musa paradisiaca) and sweet potato (Ipomoea batatas), with a loading capacity of 1.5 kg for each product and an intermittency ratio of α = 0.5 under a controlled drying temperature below 60 °C. Temperature profiles, dry-basis moisture content and drying rates were determined and analysed for both operating configurations. The results showed favourable thermal conditions for drying, characterised by a gradual increase in temperature and enhanced mass transfer during the initial drying stage. Moisture content decreased from approximately 1.4 to 1.2 kg water kg⁻¹ dry matter for banana and from 3.0 to 2.6 kg water kg⁻¹ dry matter for sweet potato, indicating rapid evaporation of free water. Maximum drying rates of 5.6 and 6.3 kg water kg⁻¹ dry matter min⁻¹ were recorded for banana and sweet potato, respectively, demonstrating the intensity of heat and mass transfer at the beginning of the process. Comparison of continuous and intermittent drying modes showed that intermittency reduced the overall drying rate while stabilising thermal and moisture gradients. Numerical predictions were in good agreement with experimental observations, confirming the reliability of the proposed model. The observed discrepancies were mainly attributed to climatic fluctuations and simplifying assumptions adopted in the model.

Computational Fluid Dynamics-Based Characterization of Heat Transfer and Airflow in an Indirect Solar Fish Dryer Under Tropical Conditions

Indirect solar drying is a widely adopted fish preservation technique in tropical regions, valued for its low energy requirement and capacity to enhance product quality. However, non-uniform airflow and temperature distribution within drying chambers remain persistent design challenges that compromise drying efficiency and product consistency. This study investigated the airflow characteristics and convective heat transfer performance of an indirect solar fish dryer through computational fluid dynamics (CFD) simulation and experimental validation. A three-dimensional CFD model was developed to simulate temperature distribution and airflow patterns under forced convection, with an inlet air velocity of 1.2 m·s⁻¹ and an inlet air temperature of 60 °C. Experimental air temperatures were recorded inside the drying chamber during actual drying operations and compared with simulated values using linear regression and root-mean-square error (RMSE). The regression analysis yielded a strong linear relationship between simulated and experimental temperatures (R² = 0.9413), with an RMSE of 3.41 °C, indicating reasonable agreement in absolute temperature prediction. These results confirm that the CFD model accurately represents the thermal behavior and convective heat transfer characteristics of the dryer. The validated CFD framework provides a reliable, cost-effective tool for evaluating and optimizing the design and operational performance of indirect solar fish dryers under tropical conditions, thereby reducing reliance on iterative physical prototyping.

Numerical investigation of coupled heat and mass transfer in deformable granular beds during humid-air and superheated-steam drying

Integrated CFD simulation and thermal imaging for monitoring convective drying of tomato wedges

The overarching aim of this study was to develop and validate a computational fluid dynamics (CFD) model to predict heat and mass transfer processes during the convective drying of tomato wedges. Experimental drying trials were conducted at three air temperatures (60, 70, and 80 °C) to evaluate model performance by monitoring drying kinetics under controlled conditions. During the drying process, the moisture content of tomato wedges was reduced from an initial value of 15.67 kg water/kg dry matter to a final value of 0.17 kg water/kg dry matter, requiring 21, 13, and 11 h at 60, 70, and 80 °C, respectively. Spatiotemporal surface temperature distributions were continuously obtained from radiometric infrared thermography recorded by a highly sensitive thermal camera and was used for monitoring of temperature changes and for CFD model validation. The results revealed that a close correspondence was observed between experimental data and simulated results across all operating drying temperatures, with improved predictive accuracy observed at lower temperatures. The model also demonstrated good predictive performance for moisture content during drying, with root-mean-square error (RMSE), and chi-square (χ2) values of 0.812 and 0.313, respectively. Additionally, color change, lycopene content, antioxidant activity, and total phenols were determined to evaluate the impact of drying temperatures on tomato quality. Drying air temperature of 70 °C resulted in the highest lycopene retention and lower color change, while a higher temperature of 80 °C showed lower degradation of antioxidant activity and phenols, indicating that drying temperature not only affects drying rate but also influences the nutritional and quality values. Overall, the developed CFD model can serve as a robust tool for analyzing and predicting the drying behavior of tomato wedges, improving process optimization, quality preservation, and enhanced control of drying operations.

Modeling and experimental validation of an indirect active hybrid solar dryer for mint leaves: Coupled thermal and moisture-transfer analysis

A mathematical model was developed and experimentally validated to predict the thermal performance and drying behavior of an indirect active solar dryer (IAHSD) for mint leaves. The distinctive contribution of the proposed approach is its integration of solar-energy input, auxiliary gas heating, controlled fresh–recirculated air mixing, ambient-humidity effects, chamber heat losses, and mint-leaf moisture removal within a computationally accessible model suitable for operational assessment and control-oriented applications. The model describes coupled heat and mass transfer processes while considering key operating parameters, including drying air temperature (50–60°C), air recirculation ratio (70–90%), and ambient relative humidity (20–80%). Simulation results showed that increasing drying air temperature and recirculation ratio enhanced the drying chamber temperature, whereas higher ambient humidity reduced the thermal level and slowed moisture removal. Predicted chamber temperatures ranged from 37.83°C to 67.31°C depending on the inlet air temperature, while experimental values followed similar trends but were slightly lower due to environmental variations. Maximum temperatures occurred near midday, highlighting the influence of solar radiation on system performance. The model also captured moisture removal dynamics, indicating that higher drying temperatures accelerated drying rates, while elevated humidity reduced evaporation efficiency. Under low temperature and high humidity conditions, temporary moisture absorption was observed due to reversed vapor pressure gradients. Model validation showed strong agreement between predicted and measured data, with coefficients of determination (R 2 ) ranging from 0.85 to 0.96, confirming the reliability of the proposed model.

Applicable methodologies for modelling of heat and mass transfer phenomena in tumble dryers: A review

Tumble dryers are convenient but energy-intensive, and their performance depends on coupled heat and mass transfer within the drum and air circuit. This review evaluates mathematical modeling approaches for these processes, spanning 0-D lumped-parameter models, 1-D heat and moisture transfer models, and kinematic and image-processing methods, across vented, condenser, and heat-pump dryer types. Literature was drawn from peer-reviewed sources published roughly since the 1990s. The Chilton–Colburn analogy remains the dominant framework for evaporation-rate modeling, but its reliance on constant transfer coefficients, uniform textile temperature, and saturated surface assumptions limits its accuracy during the falling-rate drying period, when evaporation slows and a larger fraction of supplied energy may be diverted to heating the textiles and drum rather than moisture removal. This review’s contribution lies in systematically comparing classical models (Lambert, Deans) against newer 1-D, regression-based, kinematic, and image-processing strategies, clarifying the assumptions, applicability boundaries, and engineering trade-offs of each. The findings point toward hybrid, uncertainty-aware models that couple energy-balance formulations with variable transfer coefficients, textile-motion data, and data-driven tools as the most promising path forward for energy-efficient dryer design and control.