Research Progress on the Application of Intelligent Infrared Drying Technology to Edible Kelp: Equipment Integration, Heat and Mass Transfer, Multiphysics Simulation, and Quality Control

Physics-informed modeling and optimization of heat and mass transfer in porous mineral raw materials during energy-efficient industrial drying

Industrial drying of porous mineral raw materials is one of the energy-intensive stages of mineral processing, especially when the material contains bound moisture, fine particles, and heterogeneous pore structures. Inefficient drying regimes may lead to excessive energy consumption, nonuniform temperature distribution, incomplete moisture removal, thermal degradation of material properties, and reduced technological performance in subsequent processing operations. This study proposes a physics-informed modeling approach to describe and optimize coupled heat and mass transfer processes in porous mineral raw materials during industrial drying. The proposed framework combines heat conduction, convective heat exchange, moisture diffusion, evaporation-driven mass transfer, and boundary-condition constraints within a unified model structure. The model represents temperature and moisture fields as time-dependent variables and incorporates conservation laws to improve the reliability of drying-process predictions. Special attention is given to the interactions among thermal gradients, internal moisture migration, surface evaporation, and drying-air parameters. The methodological approach includes formulating governing equations, specifying initial and boundary conditions, constructing a physics informed residual function, and interpreting drying efficiency indicators. The proposed model can be used to estimate temperature-moisture dynamics, identify zones of delayed moisture removal, and support the selection of energy-efficient drying regimes. The study contributes to the development of digital and physics-based decision-support tools for mineral processing systems by linking industrial drying technology with heat and mass transfer modeling.

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

The convective drying of agricultural materials is an energy-intensive process, and optimizing dryer design is critical for improving efficiency and product quality. This study presents a comprehensive heat and mass transfer model for the convective drying of alfalfa leaves in a rotary drum dryer. Freshly harvested leaves with an initial moisture content of approximately 70% (w.b.) were used as the test material. The proposed system features a simplified drum design aimed at enhancing process efficiency while reducing equipment complexity. The primary objective was to reduce the moisture content of alfalfa leaves to below 50% to ensure their quality during subsequent storage and transportation. To determine the optimal operating conditions, the kinematics of leaf motion inside the rotating drum and the associated heat and mass transfer phenomena were investigated through analytical modeling, numerical simulation, and experimental studies on a laboratory-scale physical model. An analytical model was developed to establish relationships between transverse kinematic characteristics (detachment condition, Froude number, drum inclination angle), average longitudinal velocity, and residence time. Numerical simulations based on the Navier–Stokes equations (continuity, momentum, and energy) provided detailed moisture content distributions within individual leaves under varying airflow orientations and drying durations. The novelty of this work lies in the integrated determination of optimized operating parameters through combined analytical, numerical, and experimental approaches. A regression model relating final moisture content to key process variables (air velocity, temperature of 60 °C, drum rotation frequency and mass of loaded material) was developed from experimental data, yielding practical recommendations for the design and operation of rotary drum dryers for alfalfa and similar agricultural materials.

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.

Comparative evaluation of three thermal conductivity model for AA7072-AA7075-ethylene glycol–water viscoelastic hybrid nanofluid with porous medium using Levenberg Marquardt technique

The purpose of this investigation is to assess the outcome of Soret and Dufour effects on viscoelastic hybrid nanofluid flow across a sheet with convective conditions. The Levenberg–Marquardt technique is notable for its novel approach and convergent stability in the field of artificial neural networks. Using regression plots, state transition measures, histogram representations, and mean squared errors, this proposed model generates a numerical approach. The thermal–solutal convective flow of viscoelastic hybrid nanofluid based on AA7072–AA7075-ethylene glycol–water that is appropriate for complex industrial heat transfer systems where simultaneous mass and heat transport is essential. Heat exchanger design and optimization, cooling systems for metallurgical and chemical processing facilities, polymer production, and energy systems needing improved thermal performance under intricate flow circumstances are all areas in which it is especially helpful. The model helps enhance thermal efficiency, regulate concentration gradients, and guarantee stable operation in high-performance industrial applications by taking into consideration Soret-Dufour effects in addition to viscoelastic behavior. This study investigates mass and heat transmission enhancement in a laminar, steady, and incompressible flow of AA7072–AA7075/EG–H₂O Boger hybrid nanofluid across a sheet. Dufour–Soret effects, convective boundary conditions, thermal radiation, magnetic fields, and Darcy–Forchheimer porous resistance all affect the flow.

Thermal and Drying Performance of a Double Pass Solar Air Heater Assisted by Graphene and Hexagonal Boron Nitride-Doped Eutectic Phase Change Material