An Application of Ultrasonic Waves in the Pretreatment of Biological Sludge in Urban Sewage and Proposing an Artificial Neural Network Predictive Model of Concentration

Atef El Jery, Houman Kosarirad, Nedasadat Taheri, Maryam Bagheri, Moutaz Aldrdery, Abubakr Elkhaleefa, Chongqing Wang () and Saad Sh. Sammen ()
Additional contact information
Atef El Jery: Department of Chemical Engineering, College of Engineering, King Khalid University, Abha 61411, Saudi Arabia
Houman Kosarirad: Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, 122 NH, Lincoln, NE 68588, USA
Nedasadat Taheri: School of Computing, University of Nebraska–Lincoln, Lincoln, NE 68588, USA
Maryam Bagheri: Department of Mechanical Engineering, University of Houston, Houston, TX 77004, USA
Moutaz Aldrdery: Department of Chemical Engineering, College of Engineering, King Khalid University, Abha 61411, Saudi Arabia
Abubakr Elkhaleefa: Department of Chemical Engineering, College of Engineering, King Khalid University, Abha 61411, Saudi Arabia
Chongqing Wang: School of Chemical Engineering, Zhengzhou University, Zhengzhou 450001, China
Saad Sh. Sammen: Department of Civil Engineering, College of Engineering, University of Diyala, Baqubah 10047, Iraq

Sustainability, 2023, vol. 15, issue 17, 1-16

Abstract: This research examines whether ultrasonic waves can enhance the hydrolysis, stability, and dewatering of activated sludge from raw urban wastewater. Sampling and physical examination of the activated sludge that was returned to the aeration pond were carried out using ultrasonic waves that were guided at frequencies of 30 and 50 kHz for periods of 0.5, 1, 3, 5, 10, 15, and 30 min. Various tests, including volatile suspended solids, inorganic solids, volatile solids, sludge resistant time, capillary suction time, total suspended solids, total solids, and volatile soluble solids, were carried out to advance further the processes of hydrolysis, stabilization, and dehydration of samples. According to the observations, the volatile soluble solids at a frequency of 30 kHz and t = 15 min were raised by 72%. The capillary suction time of 30 and 50 kHz in 1 min demonstrated a drop of 29 and 22%, respectively. It is crucial to consider that, at 10 min and the frequency of 50 kHz, the greatest efficiency was found. The 30 kHz and 1 min yielded the optimum sludge dewatering conditions. Finally, artificial neural networks (ANN) are utilized to propose predictive models for concentration, and the results were also very accurate ( M A E = 1.37 % ). Regarding the computational costs, the ANN took approximately 5% of the time spent on experiments.

Keywords: wastewater treatment; ultrasonic; sludge treatment; artificial neural network; dewatering (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/17/12875/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/17/12875/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:17:p:12875-:d:1225268

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().