Modelling and control of ozonation and biodegradation in environmental engineering : dynamic neural networks approach / / Tatyana Poznyak, Isaac Chairez, Alex Poznyak

• Autore: Poznyak Tatyana
• Pubblicazione: Amsterdam, Netherlands : , : Elsevier, , 2019
• Descrizione fisica: 1 online resource (548 pages) : illustrations
• Disciplina: 363.735
• Soggetto topico: Pollution - Technological innovations; Ozonization
• Persona (resp. second.): ChairezIsaac; PoznyakAlex
• Nota di contenuto: Front Cover -- Ozonation and Biodegradation in Environmental Engineering -- Copyright -- Contents -- List of gures -- List of tables -- Preface -- Notation and symbols -- Mathematical notations and symbols -- Part 1 Environmental Engineering and Dynamic Neural Networks -- 1 Ozonation as main method for organic contaminants degradation in three different phases: liquid, solid, and gaseous -- 1.1 Ozonation of organic contaminants in liquid phase -- 1.1.1 Basic reaction principles in liquid phase ozonation -- 1.1.2 Ozonation procedure in liquid phase -- 1.2 Ozonation of organic contaminants in the solid phase -- 1.2.1 Basic reaction principles in solid phase ozonation -- 1.2.2 Ozonation procedure in solid phase -- 1.3 Ozonation of volatile organic contaminants in the gaseous phase -- 1.4 Technological aspects of ozonation -- 1.4.1 Ozone sensors -- 1.4.2 Ozonation reactions -- 1.4.3 Ozone generators -- 1.5 Control of corona-discharge generator -- 1.5.1 State-space model -- 1.5.2 Numerical simulations -- 1.6 Conclusions -- 2 Modeling of ozonation -- 2.1 Chemical basis of ozonation modeling in the liquid phase -- 2.2 Mathematical model of ozonation in liquid phase -- 2.2.1 Estimation of the saturation constant ksat -- 2.2.2 Evaluation of the mathematical model by the simulation of ozonation of unsaturated hydrocarbon pollutants -- 2.3 Ozonation model of several contaminants in liquid phase -- 2.3.1 Model description -- 2.3.2 Abstract format of the model -- 2.3.3 Numerical illustration of the ozonation model -- 2.4 Application of a simple ozonation model to organic contaminants degradation in water -- 2.4.1 Studied compounds -- 2.4.2 Experimental conditions of ozonation -- 2.4.3 Analytical methods -- 2.4.4 Effect of the pH on the ozone decomposition in a liquid phase -- 2.4.5 Degradation by ozone of Ph, 4-CPh, and 2,4-DCPh, and their mixtures. ; 2.5 Mathematical model taking into account the pH effect -- 2.5.1 Modi ed mathematical model including the pH effect -- 2.5.2 Numerical illustration of the ozonation model with pH effect -- 2.5.3 pH effect without the presence of contaminants -- 2.5.4 Modeling of the pH effect in the presence of contaminants -- 2.6 Effect of intermediate and nal products on the ozonation reaction -- 2.7 Estimation of reaction constants -- 2.7.1 Estimation of the reaction rate constants in the case of the direct mechanism -- 2.7.2 Estimation of the reaction rate constants considering the pH effect -- 2.7.3 Differential form for constants estimates -- 2.8 Conclusions -- 3 Background on dynamic neural networks -- 3.1 Classes of arti cial neural networks -- 3.1.1 Arti cial neural networks -- 3.1.2 Feedforward neural network -- 3.1.3 Recurrent neural network -- 3.1.4 Learning ability and reinforcement learning -- 3.1.5 Why DNNs are much more preferable compared to FFNNs when the modeling of some dynamic process is required -- 3.1.6 Some limitations of ANNs -- 3.2 Neural observer as a universal software sensor -- 3.2.1 Plant and the observer structures -- 3.2.2 Main assumptions -- 3.2.3 Quasi-linear format of the model -- 3.2.4 Universal neuro-observer structure -- 3.2.5 Learning law for weights adaptation -- 3.3 How to estimate the quality of applied DNNs -- 3.3.1 Attractive ellipsoid method -- 3.3.2 How can we characterize an attractive ellipsoid? -- 3.3.3 Numerical quality estimation of state observation process using DNN -- 3.3.4 The best parameters nding using MATLAB toolboxes -- 3.4 Adaptive controllers based on DNN estimates -- 3.5 Conclusions -- 4 Neural observer application for conventional ozonation in water -- 4.1 State estimation methods -- 4.1.1 State estimation: a brief survey -- 4.2 Software sensors based on DNNO. ; 4.3 DNNO with discontinuous and time derivative terms -- 4.3.1 Training of DNNO -- 4.4 Application of DNNO to reconstruct the contaminant dynamics in ozonation -- 4.5 Estimation of the simulated ozonation variables using DNNO -- 4.5.1 Estimation of the reaction rate constants of phenols -- 4.6 Reconstruction of phenols behavior as well as their intermediates and nal products using DNNO -- 4.6.1 Ozonation procedure -- 4.6.2 Fundamentals of the phenols behavior reconstruction -- 4.6.2.1 Reconstruction of phenol and its byproducts pro les in ozonation -- 4.6.2.2 Reconstruction of 4-chlorophenol and its byproducts -- 4.6.2.3 Reconstruction of 2,4-dichlorophenol and byproducts -- 4.7 Limits of the proposed reconstruction method -- 4.8 Conclusions -- Part 2 Ozonation as a Principal Treatment Method for Organic Contaminants Elimination in Liquid Phase -- 5 Catalytic ozonation -- 5.1 Catalytic ozonation in the water treatment aimed at removing recalcitrant contaminants -- 5.2 Ozone decomposition in water in the presence of AC -- 5.3 Catalytic ozonation with activated carbon for the PAHs decomposition in water in the presence of methanol -- 5.3.1 Effect of the pH and AC on the decomposition of the PAHs in the presence of methanol -- 5.3.1.1 Anthracene decomposition -- 5.3.1.2 Fluorene decomposition -- 5.3.1.3 Phenanthrene decomposition -- 5.3.2 Estimation of the reaction rate constants -- 5.4 Catalytic ozonation with the metal oxides -- 5.4.1 Catalytic ozonation (NiO) of the benzoic and phthalic acids -- 5.4.1.1 Simple kinetic model -- 5.4.1.2 Degradation and mineralization of the benzoic acid and the phthalic acid by the conventional and catalytic ozonation -- 5.4.1.3 Effect of the catalyst concentration -- 5.4.1.4 Effect of the hydroxyl radical scavenger -- 5.4.1.5 XPS of the fresh and ozonated NiO. ; 5.4.2 Combination of conventional and catalytic ozonation -- 5.4.2.1 XPS study of the NiO surphase after ozonation of phenol, 4-phenolsulfonic and 2-naphthalenesulfonic acids -- 5.5 Catalytic ozonation of the naproxen with NiO in the presence of ethanol -- 5.5.1 Experimental -- 5.5.1.1 Materials -- 5.5.2 Adsorption studies -- 5.5.3 Analytical methods -- 5.5.4 Mathematical model of naproxen ozonation -- 5.5.5 Results and discussion -- 5.5.5.1 Naproxen adsorption -- 5.5.5.2 UV-Vis analysis -- 5.5.5.3 Naproxen decomposition -- 5.5.5.4 Intermediates obtained in ozonation of the naproxen -- 5.5.5.5 XPS spectrum of the catalyst -- 5.6 The nominal model of catalytic ozonation -- 5.6.1 Estimation of reaction rate constants based on the nominal mathematical model -- 5.6.1.1 Kinetics of the naproxen decomposition and the intermediates formation-decomposition -- 5.7 Numerical evaluation of the DNN observer -- 5.8 Conclusions -- 6 Photocatalytic ozonation -- 6.1 Effect of UV-ALEDs on terephthalic acid decomposition by photocatalytic ozonation with VxOy/ZnO and VxOy/TiO2 -- 6.1.1 Catalyst preparation -- 6.1.2 Photolysis and photocatalysis -- 6.1.3 Conventional, catalytic, and photocatalytic ozonations -- 6.1.4 Analytic methods -- 6.1.5 Catalyst characterization -- 6.2 Results and discussion -- 6.2.1 VxOy/TiO2 and VxOy/ZnO characterization -- 6.2.1.1 Diffuse re ectance UV-Vis spectroscopy -- 6.2.2 X-ray diffraction -- 6.2.3 Surface area -- 6.2.4 Surface electron microscopy -- 6.2.5 X-ray photoelectron spectroscopy (XPS) -- 6.2.5.1 Ozone decomposition -- 6.2.5.2 Photolysis and photocatalysis -- 6.2.5.3 Decomposition of the terephthalic acid by the conventional, catalytic and photocatalytic ozonation -- 6.2.5.3.1 Conventional ozonation -- 6.2.5.3.2 Catalytic ozonation -- 6.2.5.3.3 Photocatalytic ozonation -- 6.2.5.3.4 Oxalic acid characterization. ; 6.2.6 Simple kinetics -- 6.3 Mathematical model of the photocatalytic ozonation -- 6.3.1 Parameter estimation -- 6.4 Numerical evaluation of the DNNO with discontinuous learning law -- 6.5 Conclusions -- 7 Combination of physical-chemical methods and ozonation -- 7.1 Combination of chemical sedimentation and ozonation for the lignin elimination -- 7.1.1 Main contaminants formed in pulp and paper industry -- 7.1.2 Materials and methods -- 7.1.2.1 Chemical precipitation of lignin by sulfuric acid -- 7.1.2.2 Ozonation procedure -- 7.1.2.3 Samples analysis -- 7.1.3 Results and discussion -- 7.1.3.1 Effect of sulfuric acid dose on the lignin precipitation ef ciency -- 7.1.3.2 Comparison of the sludge structure -- 7.1.3.3 Ozonation of residual water at different pH values after the precipitation stage -- 7.1.4 Identi cation of the products formed in ozonation -- 7.1.5 Estimation of lignin decoloration constants -- 7.2 Coagulation and ozonation of land ll leachate -- 7.2.1 Land ll leachate contamination -- 7.2.2 Materials and methods -- 7.2.2.1 Description of the site and the characterization of the waste -- 7.2.2.2 Coagulation -- 7.2.2.3 Analytical methods -- 7.2.2.4 Ozonation kinetics -- 7.2.3 Results and discussion -- 7.2.3.1 HPLC analysis -- 7.2.3.2 Partial identi cation of same organics with GC/FID and GC/MS -- 7.2.4 Decomposition of different groups of organics after the coagulation -- 7.2.5 Estimation of the reaction rate constants -- 7.3 Flocculation-coagulation with biopolymer and ozonation -- 7.3.1 Contamination of municipal waste waters -- 7.3.2 Materials and methods -- 7.3.2.1 Characterization of the MWW -- 7.3.2.2 Experimental methodology of the MWW samples treatment -- 7.3.2.3 Determination of sludge volume and Z-potential -- 7.3.2.4 Coliforms quanti cation method -- 7.3.2.5 HE quanti cation -- 7.3.2.6 UV-spectrophotometry. ; 7.3.3 Results and discussions.
• Titolo autorizzato: Modelling and control of ozonation and biodegradation in environmental engineering
• ISBN: 0-12-812848-8; 0-12-812847-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910583467803321
• Lo trovi qui: Univ. Federico II