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Multi-objective optimization of heat pump drying process using NSGA-II and response surface methodology: a case study of sludge

Zhaofan Wu, Yongcun Li, Wentao Zhou, Qiang Fu

2025Case Studies in Thermal Engineering9 citationsDOIOpen Access PDF

Abstract

Deep drying is essential for the resource utilization of sludge, with the heat pump drying process currently being an energy-saving solution. A heat pump staged drying experimental device is built, and the drying process is set to three stages: low temperature (30°C), medium temperature (40°C), and high temperature (50°C). To achieve multiple objectives of sufficient sludge drying effect, high energy efficiency, and short total drying time, this paper proposes an optimization method combining NSGA-II with response surface methodology. First, the efficacy coefficients of different objectives are determined for standardized evaluation. Then, the response model of each objective is obtained by response surface methodology, and the influence of the duration of each stage on the response is explored. Finally, the optimal process conditions are determined through the optimization of NSGA-II. The durations of the low, medium, and high temperature stages are 2.4897 h, 2.4878 h, and 1.5879 h, respectively. The corresponding energy efficiency score, drying effect, and total drying time are 0.8998, 0.8836, and 6.5654 h, respectively. Compared with constant medium temperature drying, the energy efficiency score increases by 4.3%, the drying effect increases by 5.4%, and the total drying time is reduced by 17.9%.

Topics & Concepts

Response surface methodologyHeat pumpProcess (computing)Process engineeringMaterials scienceEnvironmental scienceProcess optimizationComputer scienceThermodynamicsEnvironmental engineeringHeat exchangerPhysicsEngineeringOperating systemMachine learningHeat Transfer and OptimizationAdvanced Multi-Objective Optimization AlgorithmsBuilding Energy and Comfort Optimization
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