Multi-objective optimization of ultrasonic algae removal technology by using response surface method and non-dominated sorting genetic algorithm-II

Ultrasonic technology is an environment-friendly method in algae-laden water treatment with the advantages of wonderful efficiency and no chemical additions. However, ultrasonic technology is costly and can lead to the release of algae organic matter (AOM). Few studies considered algae removal efficiency, water safety, and economy. In this study, a Response Surface Methodology (RSM) and Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) integrated method was used to investigate the influence of ultrasound parameters on algal removal efficiency band AOM release and conduct the multi-objective optimization of ultrasonic technology for satisfactory algal removal, environment protection, and improved economy. The maximum algae removal rate (rho), minimal energy consumption, and minimal UV254 value of algal solution were calculated. Quadratic polynomial models were obtained to illustrate the relationship between ultrasonic parameters and the responses. Ultrasonic frequency was the most important factor affecting algal removal efficiency, and high frequency was beneficial for algal removal because of its contribution to the break of air bubbles. High power density significantly increased the UV254 value, and the concentration of soluble microbial metabolites and humic acid-like substances significantly increased after ultrasound. The optimization solutions calculated by NSGA-II showed low deviation from single-objective optimization solution by RSM, demonstrating that the multi-objective optimization results were reliable. This study presents a novel RSM and NSGA-II combined method in optimizing ultrasonic technology for effective, safe, and economic algal removal. The optimization results can provide references for ultrasonic parameters to be selected in practical applications.

Automated summary

This study presents a novel method of optimizing ultrasonic technology for effective, safe, and economic algal removal using Response Surface Methodology (RSM) and Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II). The relationship between ultrasonic parameters and the responses was illustrated using quadratic polynomial models. The study found that ultrasonic frequency was the most important factor affecting algal removal efficiency, and high frequency was beneficial for algal removal due to the break of air bubbles.