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Operation of a 25 KWth Calcium Looping Pilot-plant with High Oxygen Concentrations in the Calciner
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Multiparameter analysis and operating cost optimization for NO removal using active coke.

Wen Liu1, Huawei Liu1, Weiliang Cheng1

  • 1Key Laboratory of Power Station Energy Transfer Conversion and System of MOE, School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing, China.

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|November 6, 2025
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Summary
This summary is machine-generated.

This study optimizes active coke denitrification by simulating operating parameters. Key factors like temperature and pipe length were adjusted to reduce costs by 25% while maintaining high nitrogen oxide (NOx) removal efficiency.

Keywords:
NO removalactive cokeeconomic optimizationgenetic algorithm optimizationmachine learning

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Area of Science:

  • Environmental Engineering
  • Chemical Engineering
  • Catalysis

Background:

  • Limited research exists on optimizing operating parameters for nitrogen oxide (NOx) removal using active coke.
  • Active coke is a promising material for catalytic denitrification processes in industrial emissions.

Purpose of the Study:

  • To investigate the impact of operating parameters on NOx removal efficiency and cost-effectiveness using active coke.
  • To develop and apply simulation and optimization models for enhancing denitrification processes.

Main Methods:

  • A COMSOL simulation model was developed to analyze the denitrification process in an active coke-packed pipe.
  • The effects of temperature, flow velocity, pipe length, inlet NOx concentration, and pipe diameter were simulated.
  • A neural network predictive model and a genetic algorithm were used for optimization.

Main Results:

  • Temperature, flow velocity, and pipe length significantly influenced denitrification efficiency (up to 43.6%).
  • Increasing pipe diameter negligibly affected efficiency but increased flue gas processing capacity.
  • Optimization reduced operating costs by up to 25% while meeting denitrification standards.

Conclusions:

  • Operating parameters critically affect active coke denitrification performance and cost.
  • Simulation and AI-driven optimization can significantly improve the efficiency and economic viability of NOx removal.
  • This study provides a framework for optimizing industrial denitrification processes.