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ANNs for Identifying Shock Loads in Continuously Operated Biofilters: Application to Biological Waste Gas Treatment
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Author(s): Eldon R. Rene (University of La Coruña, Spain), M. Estefanía López (University of La Coruña, Spain), Hung Suck Park (University of Ulsan, South Korea), D. V. S. Murthy (Broward College, USA)and T. Swaminathan (Indian Institute of Technology, India)
Copyright: 2012
Pages: 32
Source title:
Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and Solutions
Source Author(s)/Editor(s): Mohammad Ayoub Khan (Centre for Development of Advanced Computing, India)and Abdul Quaiyum Ansari (Jamia Millia Islamia, India)
DOI: 10.4018/978-1-4666-0294-6.ch004
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Abstract
Among the different waste gas treatment techniques developed to eliminate odorous and toxic pollutants from air, biological techniques have emerged as an effective, reliable, eco-friendly, simple, and economical option. Biological waste gas treatment systems such as biofilters are commonly used in industrial complexes to handle emissions at high gas flow rates and low pollutant concentrations (<5 g/m3). However, from a practical view-point, variation in concentrations and gas flow rates are common to any industrial emission, and it is a pre-requisite to simulate these conditions (shock loads) at the laboratory scale. This chapter provides sufficient theoretical background information on the different waste gas treatment systems, literature review on shock loads in biofilters, and the different steady and transient state models developed in the field of biofiltration. A fundamental overview of artificial neural networks and the different steps of the modeling process are also presented.
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