Eco-intelligent integrated pre-fenton and artificial neural network system for debottlenecking the efficiency of physico-chemical treatment in POP-B3 waste management
DOI:
https://doi.org/10.61511/hcr.v2i1.2043Keywords:
artificial neural network, hazardous waste (B3), persistent organic pollutants (pops), pid controller, prec-fentonAbstract
Background: Persistent Organic Pollutants (POPs) in hazardous waste (B3) continue to increase due to industrial activities and are difficult to degrade using conventional methods. POPs can accumulate in the environment and pose serious health risks, such as cancer and reproductive disorders. The PREC-Fenton system has been proposed to enhance the treatment efficiency of hazardous waste, particularly POPs, by combining chemical reactions with energy utilization from salinity gradient power. Methods: The research methodology comprises modeling approaches, research framework formulation, system definition, thermodynamic property regression, model construction, system simulation, financial feasibility study, and simulation result analysis. Findings: The research findings indicate that the PREC-Fenton system is capable of reducing POPs by up to 1,038.8 kg/h with an efficiency of 99%, while producing 176.24 kg/h of clean water and generating 300.17 kW of energy with a conversion efficiency of 40%. The energy efficiency of the ORC increased by 46.13%. System optimization using an Artificial Neural Network (ANN) with 13 neurons in a single hidden layer yielded the lowest RMSE values and high accuracy, with R² values exceeding 0.96 for the KP, KI, and KD parameters. The economic analysis showed a break-even point (BEP) at 44% capacity, a net present value (NPV) of USD 125,529, an internal rate of return (IRR) of 33.48%, a discounted payback period (DPP) of 5 years, and a return on investment (ROI) of 190.89% before tax and 114.60% after tax. These results confirm that the PREC-Fenton system is efficient, cost-effective, and environmentally friendly. Conclusion: This study successfully developed an efficient PREC-Fenton system for hazardous waste (B3) treatment, achieving up to 99.99% degradation efficiency of POPs, clean water production of 176.24 kg/h, and energy generation of 300.17 kW. Novelty/Originality of this article: This article presents an innovative integration of the PREC-Fenton system with an adaptive control approach based on Artificial Neural Networks (ANN) to optimize the real-time degradation of POP-B3 waste.
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