Studying the Kinetics of the Autothermal Thermophilic Aerobic Digestion: Application of AI-based modeling
Publish Year: 1402
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IRCCE12_023
تاریخ نمایه سازی: 2 مرداد 1403
Abstract:
Autothermal Thermophilic Aerobic Digestion, a widely used wastewater treatment method, uses heat-loving microbes to efficiently break down organic matter in sludge without external heating. While complex, understanding the intricate kinetics of this process is crucial for optimization. This study proposes an Artificial Neural Network model, trained on real data, to predict predicting the kinetic rate constant (KATAD). The model, enhanced through Genetic Algorithm optimization, demonstrates exceptional accuracy (more than ۹۹%). Evaluation reveals temperature as the most influential parameter (CI = ۱.۲۳), followed by the primary to secondary sludge ratio (CI = -۰.۴۷), and concentration with the least impact on KATAD (CI = ۰.۱۹).
Keywords:
Artificial Neural Network , Autothermal Thermophilic Aerobic Digestion , Biodegradation Kinetics , Genetic Algorithm , Rate Constant
Authors
Kourosh Fakhari
Biotechnology Group, Chemical Engineering Department, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran
Armin Rahimieh
Biotechnology Group, Chemical Engineering Department, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran
Mohsen Nosrati
Biotechnology Group, Chemical Engineering Department, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran