General Information
    • ISSN: 1793-821X (Print)
    • Abbreviated Title: J. Clean Energy Technol.
    • Frequency: Quarterly
    • DOI: 10.18178/JOCET
    • Editor-in-Chief: Prof. Haider F. Abdul Amir
    • Executive Editor: Ms. Jennifer Zeng
    • Abstracting/ Indexing:  INSPEC (IET), Electronic Journals Library, Chemical Abstracts Services (CAS), Ulrich's Periodicals Directory, Google Scholar, ProQuest, CNKI.
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Universiti Malaysia Sabah, Malaysia.
I would like to express my appreciation to all the reviewers and editors, who have been working
very hard to ensure the quality of the journal. It's my honor to work with such a wonderful team.

JOCET 2014 Vol.2(3): 201-205 ISSN: 1793-821X
DOI: 10.7763/JOCET.2014.V2.123

Prediction of Biogas Generation Profiles in Wastewater Treatment Plants Using Neural Networks

Peiman Kianmehr, Wathiq Mansoor, and Fadi A. Kfoury
Abstract—The great potential of Waste Activated Sludge (WAS) to produce methane as renewable bio-resource energy has always been of engineers’ interest. The evaluation of the rate of methane generation and its ultimate value is a crucial step to predict the performance of anaerobic digesters degrading wide ranges of raw and pre-treated WAS. Biochemical methanogenic potential (BMP) test is known as the most common assay in this context. However, it is known as a time consuming, equipment-intensive and consequently expensive tool. The objectives of this research are to identify key WAS properties required to estimate biodegradability of raw and pretreated sludge and accordingly generate a proper model for predicting sludge biodegradability, utilizing Artificial Neural Networks (ANN). Earlier attempts to identify such key indicators and generating a proper model representing sludge biodegradability using typical mathematical approaches were unsuccessful. However, the results of this research proved ANN effective in modeling sludge biodegradability.

Index Terms—Sludge digestion, pre-treatment, solid residence time, artificial neural networks.

Peiman Kianmehr, Wathiq Mansoor, and Fadi A. Kfoury are with School of Engineering, American University in Dubai, United Arab Emirates (e-mail:


Cite:Peiman Kianmehr, Wathiq Mansoor, and Fadi A. Kfoury, "Prediction of Biogas Generation Profiles in Wastewater Treatment Plants Using Neural Networks," Journal of Clean Energy Technologies vol. 2, no. 3, pp. 201-205, 2014.

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