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

Aug 2026 · Geotechnology, Mining and Rational Use of Natural Resources (GeoTech-VII 2026) · Vol 14297, pp. 142971S - 142971S-10 · 0 citations · 10 references
Engineering

Abstract

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.

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