An efficient design of primary sedimentation tanks using a combination of the response surface, metaheuristic, and scenario building methods

Abstract

Solid particle sedimentation is assumed as a complex procedure in both water and wastewater treatment plants. There is a great deal of interest in applying and developing different simulation and optimization methods to design a primary sedimentation tanks (PSTs). In traditional techniques, mechanical and physical parameters are set by sequential error loops. To eliminate the disadvantage of existing techniques, this study proposes a hybrid method based on the response surface methodology, efficient metaheuristics and scenario building methods using different experimental methods. This novel framework creates a robust and sustainable design for the PSTs. First of all, the parameters of the considered PST based on the economic, improve process and tank efficiency scenarios are tuned and optimized by the Central Composition Design (CCD) and Response Surface Methodology (RSM). To forecast an efficient response value for these scenarios, different metaheuristic algorithms including the Genetic Algorithm (GA), Pattern Search Algorithm (PSA) and Simulate Annealing Algorithm (SAA) are applied. Results demonstrated that PSA, GA and PSA with 0.02, 0.032 and 0.063 in comparison with experimental practices have the best calibration for prediction of response in economic, improve process and tank efficiency scenarios, correspondingly. Finally, experimental tests have proven that the optimum Retention Time (RT) is equal to 2 hours based on the biological oxygen demand and the total suspended solids eliminations in the lab-scale setup.

A hybrid approach for low-carbon transportation system analysis: integrating CRITIC-DEMATEL and deep learning features

“…The proposed deep learning method can be hybridized with recent and powerful metaheuristics to better optimize the errors (Tian et al 2022b , 2023c ). Many factors related to the environmental systems to optimize the energy consumption and fuel of vehicles can also be studied in future works (Zamanikherad et al 2022 ). Finally, future research should shift the low-carbon transportation assessment to a sustainable transportation assessment, considering different social criteria such as job opportunities and lost workdays in addition to environmental criteria.…”

Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks

“…In this regard, the consideration of urban traffic before and during the COVID-19 pandemic is another future research recommendation. Finally, a combination of our prediction model with novel heuristics, metaheuristics, and exact reformulations can be considered for our future work [38][39][40][41].…”