Ozonation and Biodegradation in Environmental Engineering: Dynamic Neural Network Approach

Modeling and Control of Ozonation and Biodegradation in Engineering gives a unified point of view on the application of Dynamic Neural Networks (DNN) to estimate and control the application of ozonation and biodegradation in chemical and environmental engineering. This book deals with modelling and control design of chemical processes oriented to environmental and chemical engineering problems. DNN enables plant engineers to obtain accurate processes analysis and realize effective control without requiring exact knowledge of real physical and chemical models. Linear Matrix Inequalities (LMI’s) are the main mathematical tools used to justify the workability of both the sensor and the neural controller. Solutions to problems are given using MATLAB.

Organic contaminants elimination in liquid, solid and gaseous phases are all covered in this book. Several processes of laboratory scale are evaluated with software sensors and controllers based on DNN technique. They are: removal of contaminants in residual water, remediation of contaminated soil, purification of contaminated air, biological degradation of contaminants in wastewater, bio-filtering treatment of volatile organic compounds, and bio-remediation of contaminated soils. The authors also look at combined treatment using both ozonation and biodegradation to test the sensor and controller.

Presents the DNN technique as an efficient method to identify and design controllers for a wide class of chemical and environmental engineering processes and introduces a unified mathematical approach that can be easily understood and applied by plant engineers, researchers and postgraduate studentsDefines a novel researching trend in environmental engineering processes dealing with incomplete mathematical model description and other non-measurable parameters and variables. Offers both significant new theoretical challenges and an examination of real-world problem-solvingHelps students or practitioners learn and implement DNN inexpensively using commercially available, PC-based software tools

I Chemical Processes in Environmental Engineering and Dynamic Neural Networks 1. Ozonation as main method for organic contaminants degradation in three different phases: liquid, solid and gaseous 2. Modelling of Ozonation Processes 3. Background on Dynamic Neural Networks 4. Motivation of Differential Neural Networks Application to Environment Problems 5. Neural observer application for phenols conventional ozonation in water to its simulation and kinetic parameters identification at different pHs

II Ozonation as a Principal Treatment Method for Organic Contaminants Elimination in Liquid Phase 6. Automatic control of ozonation systems 7. Catalytic ozonation for Recalcitrant Contaminants Removal 101 8. Photocatalytic Ozonation for Complex Organics 9. Physicochemical and Ozonation Mixed TreatmentMethods 10. Continuous Ozonation Treatment

III Remediation of Contaminated Soil 11. Conventional Ozonation and Mass Transfer Effects in Solid Phase

IV Purification of Contaminated Air 12. Ozonation of Gaseous Samples

V Sequential Treatment by Biodegradation and Ozonation 13. Biodegradation