Relevant bibliographies by topics / WASTEWATER TREATMENT MODELLING

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'WASTEWATER TREATMENT MODELLING'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "WASTEWATER TREATMENT MODELLING"

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Parashar, Varsha, Ashok K. Sharma, Sarita Sharma, and Sanjay Verma. "Mathematical Modelling of Uasb Reactor for Dairy Wastewater Treatment." International Journal of Scientific Research 3, no. 8 (June 1, 2012): 151–53. http://dx.doi.org/10.15373/22778179/august2014/43.

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Vanhooren, Henk, Jurgen Meirlaen, Youri Amerlinck, Filip Claeys, Hans Vangheluwe, and Peter A. Vanrolleghem. "WEST: modelling biological wastewater treatment." Journal of Hydroinformatics 5, no. 1 (January 1, 2003): 27–50. http://dx.doi.org/10.2166/hydro.2003.0003.

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Modelling is considered to be an inherent part of the design and operation of a wastewater treatment system. The models used in practice range from conceptual models and physical design models (laboratory-scale or pilot-scale reactors) to empirical or mechanistic mathematical models. These mathematical models can be used during the design, operation and optimisation of a wastewater treatment system. To do so, a good software tool is indispensable. WEST is a general modelling and simulation environment and can, together with a model base, be used for this task. The model base presented here is specific for biological wastewater treatment and is written in MSL-USER. In this high-level object-oriented language, the dynamics of systems can be represented along with symbolic information. In WEST's graphical modelling environment, the physical layout of the plant can be rebuilt, and each building block can be linked to a specific model from the model base. The graphical information is then combined with the information in the model base to produce MSL-EXEC code, which can be compiled with a C++ compiler. In the experimentation environment, the user can design different experiments, such as simulations and optimisations of, for instance, designs, controllers and model fits to data (calibration).
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Solon, Kimberly, Eveline I. P. Volcke, Mathieu Spérandio, and Mark C. M. van Loosdrecht. "Resource recovery and wastewater treatment modelling." Environmental Science: Water Research & Technology 5, no. 4 (2019): 631–42. http://dx.doi.org/10.1039/c8ew00765a.

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This paper discusses the extent to which new unit processes applied for resource recovery can be modelled with conventional ASMs, the additional modelling challenges being faced, while providing recommendations on how to address current modelling research gaps.
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Merayo, Noemi, Ana Balea, Javier Tejera, Amalio Garrido-Escudero, Carlos Negro, and Angeles Blanco. "Modelling the Mineralization of Formaldehyde by Treatment with Nitric Acid." Water 12, no. 6 (May 30, 2020): 1567. http://dx.doi.org/10.3390/w12061567.

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Formaldehyde is a recalcitrant pollutant, which is difficult to remove from wastewater using conventional and advanced treatments. The objective of this research was to remove the organic matter from formaldehyde from an industrial wastewater, achieving its total mineralization and allowing the reuse of the water. The treatment was based on the reaction of formaldehyde with nitric acid, which was first studied and modelled with synthetic waters. Results show that it was possible to almost completely mineralize the formaldehyde (>95% TOC removal) at the best conditions studied (1.72 M of nitric acid and 85 °C of temperature). The addition of NaNO2 accelerated this reaction; however, after 2 h of reaction time, its effect was negligible at the maximum concentration of HNO3 studied. The results obtained with industrial wastewater fit well with the model. It is concluded that formaldehyde in actual wastewaters can be successfully removed through direct mineralization with nitric acid, under selected conditions.
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Belia, E., Y. Amerlinck, L. Benedetti, B. Johnson, G. Sin, P. A. Vanrolleghem, K. V. Gernaey, et al. "Wastewater treatment modelling: dealing with uncertainties." Water Science and Technology 60, no. 8 (October 1, 2009): 1929–41. http://dx.doi.org/10.2166/wst.2009.225.

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This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model prediction accuracy and uncertainty issues. It also aims to identify future research needs. Ultimately the goal of such a discussion would be to generate transparent and objective methods of explicitly evaluating the reliability of model results, before they are implemented in an engineering decision-making context.
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Hernandez-Sancho, F., M. Molinos-Senante, and R. Sala-Garrido. "Cost modelling for wastewater treatment processes." Desalination 268, no. 1-3 (March 2011): 1–5. http://dx.doi.org/10.1016/j.desal.2010.09.042.

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Daigger, G. T. "A practitioner’s perspective on the uses and future developments for wastewater treatment modelling." Water Science and Technology 63, no. 3 (February 1, 2011): 516–26. http://dx.doi.org/10.2166/wst.2011.252.

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The modern age of wastewater treatment modelling began with publication of the International Water Association (IWA) Activated Sludge Model (ASM) No.1 and has advanced significantly since. Models are schematic representations of systems that are useful for analysis to support decision-making. The most appropriate model for a particular application often incorporates only those components essential for the particular analyses to be performed (i.e. the simplest model possible). Characteristics of effective models are presented, along with how wastewater modelling is integrated into the wastewater project life cycle. The desirable characteristics of wastewater treatment modelling platforms are then reviewed. Current developments of note in wastewater treatment modelling practice include estimates of greenhouse gas emissions, incorporating uncertainty into wastewater modelling and design practice, more fundamental modelling of process chemistry, and improved understanding of the degradability of wastewater constituents in different environments. Areas requiring greater emphasis include increased use of metabolic modelling, characterisation of the hydrodynamics of suspended and biofilm biological treatment processes, and the integration of biofilm and suspended growth process modelling. Wastewater treatment models must also interface with water and wastewater management software packages. While wastewater treatment modelling will continue to advance and make important contributions to practice, it must be remembered that these are complex systems which exhibit counter-intuitive behaviour (results differ from initial expectations) and multiple dynamic steady-states which can abruptly transition from one to another.
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Clouzot, Ludiwine, Jean-Marc Choubert, Frédéric Cloutier, Rajeev Goel, Nancy G. Love, Henryk Melcer, Christoph Ort, et al. "Perspectives on modelling micropollutants in wastewater treatment plants." Water Science and Technology 68, no. 2 (July 1, 2013): 448–61. http://dx.doi.org/10.2166/wst.2013.272.

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Models for predicting the fate of micropollutants (MPs) in wastewater treatment plants (WWTPs) have been developed to provide engineers and decision-makers with tools that they can use to improve their understanding of, and evaluate how to optimize, the removal of MPs and determine their impact on the receiving waters. This paper provides an overview of such models, and discusses the impact of regulation, engineering practice and research on model development. A review of the current status of MP models reveals that a single model cannot represent the wide range of MPs that are present in wastewaters today, and that it is important to start considering classes of MPs based on their chemical structure or ecotoxicological effect, rather than the individual molecules. This paper identifies potential future research areas that comprise (i) considering transformation products in MP removal analysis, (ii) addressing advancements in WWTP treatment technologies, (iii) making use of common approaches to data acquisition for model calibration and (iv) integrating ecotoxicological effects of MPs in receiving waters.
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Kamara, A., O. Bernard, A. Genovesi, D. Dochain, A. Benhammou, and J. P. Steyer. "Hybrid modelling of anaerobic wastewater treatment processes." Water Science and Technology 43, no. 1 (January 1, 2001): 43–50. http://dx.doi.org/10.2166/wst.2001.0011.

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This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feedforward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.
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Henze, M., M. C. M. van Loosdrecht, G. A. Ekama, and D. Brdjanovic. "Biological Wastewater Treatment: Principles, Modelling and Design." Water Intelligence Online 7 (December 30, 2015): 9781780401867. http://dx.doi.org/10.2166/9781780401867.

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Dissertations / Theses on the topic "WASTEWATER TREATMENT MODELLING"

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Thomas, David N. "Flocculation modelling in wastewater treatment." Thesis, Cranfield University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323835.

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Ghavipanjeh, Farideh. "Modelling and control of wastewater treatment." Thesis, Lancaster University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250027.

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Samsó, Campà Roger. "Numerical modelling of constructed wetlands for wastewater treatment." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144624.

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Constructed Wetlands (CWs) are a wastewater treatment technology that inherits the purification potential of natural wetlands and optimizes it to comply with regulations for treated discharges. CWs have become an equally performing alternative to conventional wastewater treatment technologies of communities up to 2000PE, with lower energy and maintenance costs. Despite their potential, CWs lack reliability, which holds back their full deployment in the territory. This fact results from the lack of understanding on their internal functioning and because they are prone to clogging. The enormous diversity of CWs typologies and operation strategies, and the fact that they operate at the mercy of the environmental conditions, makes each CW unique on its kind, and experimental studies are usually only representative of the studied system. This fact makes mathematical models essential to study their functioning. Several models for CWs have proliferated in the last dozen years to provide supporting tools for their design and operation as well as more insight into the treatment processes. However, compared to models utilized in similar disciplines, CWs models are still in an embrionary stage. Accordingly, the objectives of the current work were to develop a CWs model able to describe the most common processes taking place within CWs, and to use this model to shed light on the internal functioning of these systems in the long-term. The model, named BIO_PORE, was built in COMSOL Multiphysics and can simulate subsurface flow and pollutants transport in porous media. It also implements the biokinetic model Constructed Wetlands Model number 1 (CWM1) to describe the fate of organic matter, nitrogen and sulphur and the growth of the bacterial groups found in CWs. The model was calibrated with experimental data of a year of operation of a pilot system. Two empirical parameters (Mcap and Mbio_max ) were used to improve the description of bacterial growth obtained with CWM1 and to include the effects of solids accumulation on bacterial communities. The effect of these two parameters was evaluated using local sensitivity analysis. The model was later used to unveil the dynamics of bacterial communities within CWs. In addition, a theory was derived from simulation results, which aimed at describing the most basic functioning patterns of CWs based on the interaction between bacterial communities and accumulated solids. At the end of the document a mathematical formulation is presented to describe bioclogging and a numerical experiment is carried out to showcase its impact on simulation results. The main outcome of the current work was the BIO_PORE model. This model was able to reproduce effluent pollutant concentrations measured during an entire year of operation of the pilot system. Parameters Mcap and Mbio_max proved essential to prevent unlimited bacterial growth predicted by CWM1 near the inlet sections of CWs. These two parameters were also responsible for the good fitting with experimental data. This was confirmed with the sensitivity analysis, which demonstrated that they have a major impact on the model predictions for effluent COD and ammonia and ammonium nitrogen. The theory derived from simulation results indicated that bacteria move towards the outlet with time, following the accumulation of inert solids from inlet to outlet. This result may prove that CWs life-span is limited, corresponding to the time after which bacterial communities are pushed as much towards the outlet that their total biomass is not able to provide effluents with acceptable quality. The inclusion of bioclogging was a requisite to reproduce the bacterial distribution and fluid flow and pollutants transport within CWs. More work on the BIO_PORE model is required and more experimental data is necessary to calibrate and validate its results.
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Solimeno, Alessandro. "Numerical modelling of microalgae systems for wastewater treatment." Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/441737.

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Reactions and processes that occur in microalgae and bacteria systems are difficult to understand because most of them take place simultaneously and depend on many parameters such as temperature, solar radiation, nutrients availability (e.g. carbon and nitrogen) as well on certain inhibitory conditions (e.g excess of oxygen in the culture medium). In comparison with conventional wastewater treatment technologies, less is known about the physical, chemical and biochemical reactions and processes that occur in microalgae-bacteria treatment systems. The main outcome of the present PhD thesis was to develop a new integrated mechanistic model, named BIO_ALGAE, which includes crucial physical and biokinetic processes to simulate microalgae growth in different type of cultures, and most particularly in wastewater. The model was used to advance the understanding the inherent complexity of microalgae and bacteria interactions that occur in high rate algal ponds (HRAP) and photobioreactors.BIO_ALGAE model was mainly built by coupling the River Water Quality Model 1 (RWQM1) formulation and the modified ASM3 model, and was implemented in COMSOL MultiphysicsTM simulation platform. Inorganic carbon, as a limiting substrate for the growth of microalgae, is one of the major innovative features of BIO_ALGAE. Carbon is an essential resource for microalgae production. Moreover, temperature, photorespiration, pH dynamics, solar radiation, light attenuation and transfer of gases to the atmosphere are considered main limiting factors for microalgae growth. In a pragmatic approach to reduce the model¿s complexity in the initial stages of its development, it was decided to start by studying physical, chemical and biokinetic processes of microalgae alone, hence neglecting bacterial processes. Once calibrated the most uncertain parameters of the model, bacteria processes were added, and this gave place to the integral model BIO_ALGAE. This model was calibrated and validated with high quality experimental data from pilot raceway ponds over short-time scale and for long-term operation.The BIO_ALGAE model has proved to be an efficient tool to understand microalgae and bacteria interactions in wastewater treatment and to simulate the dynamics of different components in the ponds. The model was used to investigate the effect of environmental conditions and nutrients availability on microalgae growth and the different hydraulic retention time (HRT) operating strategies on the relative proportion of microalgae and bacteria and biomass production. Moreover, thanks to the model it was possible to optimize the performance of both HRAP and photobioreactor.
Las reacciones y los procesos que ocurren en sistemas mixtos de microalgas y bacterias son difíciles de entender ya que la mayoría de ellos tienen lugar simultáneamente y dependen de muchos parámetros tales como temperatura, radiación solar, disponibilidad de nutrientes (e.g. carbono y nitrógeno) así como ciertas condiciones inhibitorias (e.g. exceso de oxígeno en el medio de cultivo). En comparación con las tecnologías convencionales de tratamiento de aguas residuales, actualmente hay poco conocimiento de las reacciones físicas, químicas y bioquímicas y de los procesos que se producen en los sistemas de tratamiento de microalgas y bacterias. El objetivo principal de la presente tesis doctoral fue desarrollar un nuevo modelo mecanístico integrado, denominado BIO_ALGAE, que incluye procesos físicos y bioquinéticos cruciales para simular el crecimiento de microalgas en diferentes tipos de cultivos, principalmente en aguas residuales. El modelo se utilizó para comprender de una mejor forma las interacciones que se llevan a cabo entre microalgas y bacterias en lagunas de alta carga (LAC) y fotobiorreactores. El modelo BIO_ALGAE se construyó mediante el acoplamiento del River Water Quality Model 1 (RWQM1) y del modelo ASM3 modificado, y se implementó en la plataforma de simulación COMSOL MultiphysicsTM. El carbono inorgánico, utilizado como sustrato limitante para el crecimiento de microalgas, es una de las principales características innovadoras de BIO_ALGAE. Además, la temperatura, la fotorespiración, la dinámica del pH, la radiación solar, la atenuación de la luz y la transferencia de gases a la atmósfera se consideraron los principales factores limitantes del crecimiento de las microalgas. Para reducir la complejidad del modelo en las etapas iniciales de su desarrollo, se decidió empezar por estudiar los procesos físicos, químicos y bioquinéticos sólo de las microalgas, dejando de lado los procesos bacterianos. Una vez calibrados los parámetros más sensibles del modelo, se añadieron los procesos bacterianos, lo que dio lugar al modelo integral BIO_ALGAE. Este modelo fue calibrado y validado con datos experimentales de alta calidad procedentes de LAC operadas a corto y largo plazo. El modelo BIO_ALGAE ha demostrado ser una herramienta eficaz para entender las interacciones de microalgas y bacterias en el tratamiento de aguas residuales y simular la dinámica de diferentes componentes en las LAC. El modelo se utilizó para investigar el efecto de las condiciones ambientales y la disponibilidad de nutrientes en el crecimiento de microalgas. También se estudió el efecto del tiempo de retención hidráulica sobre la proporción relativa de microalgas-bacterias y la producción de biomasa. Gracias al modelo fue posible optimizar el rendimiento tanto de las lagunas de alta carga como del fotobiorreactor.
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Soteman, Sven Wilhelm. "Modelling material mass balances over wastewater treatment plants." Doctoral thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/14070.

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Includes bibliographical references.
The overall objective of whole wastewater treatment plant (WWTP)modelling is to develop a COD (electron), carbon (C), nitrogen (N), phosphorus (P), alkilinity (proton), calcium (Ca), magnesium (Mg) and inorganic suspended solids (ISS) concentrations mass balances models for unit operations in municipal WWTPs. The development of such a model, for both steady state and dynamic simulation conditions, is an objective greater that this thesis project, however, it makes a number of significant steps towards it.
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Mattei, Maria Rosaria. "Mathematical modelling of multispecies biofilms for wastewater treatment." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1182/document.

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Cette thèse s'intéresse à l'application d'un modèle mathématique unidimensionnel de formation et de croissance de biofilms multi-espèces. Le modèle se compose d'un système d'équations non linéaires aux dérivées partielles hyperboliques, décrivant la croissance d'espèces microbiennes dans le biofilm, et un système d'équations semi-linéaires aux dérivées partielles paraboliques, qui régit la diffusion de substrat de la phase aqueuse vers la matrice du biofilm. L'ensemble conduit à un problème de valeur limite libre, essentiellement hyperbolique. Dans une première étude, l'analyse et la simulation de la phase initiale de croissance du biofilm ont été examinées. Le problème mathématique résultant a été discuté en utilisant la méthode des caractéristiques et le théorème du point fixe a été utilisé pour déterminer l'existence et l'unicité des solutions mathématiques. Un deuxième aspect de la thèse porte sur l'analyse et la prévision de la dynamique des populations microbienne dans plusieurs types biofilms pour le traitement des eaux usées. Le modèle a été appliqué pour simuler la compétition bactérienne et évaluer l'influence de la diffusion du substrat sur la stratification microbienne des biofilms multi-espèces, en incluant les bactéries nitrifiantes, Anammox et bactéries sulfato-réductrices. Dans les deux cas, la méthode des caractéristiques a été utilisée à des fins numériques et l'équation de conservation de masse joue un rôle crucial pour vérifier l'exactitude des simulations. Les résultats des simulations montrent que le modèle est en mesure d'évaluer correctement les effets des conditions limites qui s'exercent sur la concurrence bactérienne. Enfin, ce modèle a été étendu pour inclure le phénomène de colonisation microbienne. Le nouveau modèle est capable de prendre en compte l'invasion de nouvelles espèces en se basant sur un ensemble d'équations non linéaires aux dérivées partielles hyperboliques pour ce qui concerne le processus de croissance. De plus, le processus d'invasion biologique d'espèces nouvelles dans le biofilm a été modélisé par un système d'équations non linéaires aux dérivées partielles paraboliques. Ce modèle d'invasion a été appliqué avec succès pour simuler l'invasion des bactéries hétérotrophes dans les biofilms autotrophes
This dissertation relates to the applications of a one-dimensional mathematical model for multispecies biofilm formation and growth. The model consists of a system of nonlinear hyperbolic partial differential equations, describing the growth of microbial species in biofilms, and a system of semilinear parabolic partial differential equations, which governs substrate diffusion from the surrounding aqueous phase into the biofilm. Overall, this leads to a free boundary value problem, essentially hyperbolic. In a first study, the analysis and simulations of the initial phase of biofilm growth have been addressed. The resulting mathematical problem has been discussed by using the method of characteristics and the fixed-point theorem has been used to obtain existence, uniqueness and properties of solutions. A second aspect of the thesis deals with the analysis and prediction of population dynamics in multispecies biofilms for wastewater treatment. The model has been applied to simulate the bacterial competition and to evaluate the influence of substrate diffusion on microbial stratification for a nitrifying multispecies biofilm including Anammox bacteria and a sulfate-reducing biofilm. In both cases, the method of characteristics has been used for numerical purposes and the mass conservation equation plays a crucial role in checking the accuracy of simulations. The simulation results reveal that the model is able to evaluate properly the effects that boundary conditions exert on bacterial competition. Finally, the biofilm model has been extended to include the colonization phenomenon. The new model is able to take into account the invasion of new species diffusing from bulk liquid to biofilm, still based on a set of nonlinear hyperbolic partial differential equations for what concerns growth process. Indeed, the biological invasion process of new species into the biofilm has been modeled by a system of nonlinear parabolic partial differential equations. The invasion model has been successfully applied to simulate the invasion of heterotrophic bacteria in a constituted autotrophic biofilm and viceversa
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Janus, Tomasz. "Modelling and simulation of membrane bioreactors for wastewater treatment." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/9507.

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The work presented in this thesis leads to the formulation of a dynamic mathematical model of an immersed membrane bioreactor (iMBR) for wastewater treatment. This thesis is organised into three parts, each one describing a different set of tasks associated with model development and simulation. In the first part, the Author qualitatively and quantitatively compares various published activated sludge models, i.e. models of biochemical processes associated with bacterial growth, decay, lysis and substrate utilisation in activated sludge systems. As the thesis is focused on modelling membrane bioreactors (MBRs) which are known to experience membrane fouling as a result of adsorption of biopolymers present in the bulk liquid onto and within the membrane, all activated sludge models considered in this thesis are able to predict, with various levels of accuracy, the concentrations of biopolymeric substances, namely soluble microbial products (SMP) and extracellular polymeric substances (EPS). Some of the published activated sludge models dedicated to modelling SMP and EPS kinetics in MBR systems were unable to predict the SMP and EPS concentrations with adequate levels of accuracy, without compromising the predictions of other sludge and wastewater constituents. In other cases, the model equations and the assumptions made by their authors were questionable. Hence, two new activated sludge models with SMP and EPS as additional components have been formulated, described, and simulated. The first model is based on the Activated Sludge Model No. 1 (ASM1) whereas the second model is based on the Activated Sludge Model No. 3 (ASM3). Both models are calibrated on two sets of data obtained from a laboratory-scale system and a full-scale system and prove to be in very good agreement with the measurements. The second part of this thesis explains the development of two membrane fouling models. These models are set to describe the loss of membrane permeability during filtration of various solutions and suspensions. The main emphasis is placed on filtration of activated sludge mixtures, however the models are designed to be as general as feasibly possible. As fouling is found to be caused by a large number of often very complex processes which occur at different spatial as well as temporal scales, the two fouling models developed here have to consider a number of significant simplifications and assumptions. These simplifications are required to balance the model's accuracy, generality and completeness with its usability in terms of execution times, identifiability of parameters and ease of implementation in general purpose simulators. These requirements are necessary to ascertain that long term simulations as well as optimisation and sensitivity studies performed in this thesis either individually on fouling models or on the complete model of a MBR can be carried out within realistic time-scales. The first fouling model is based on an idea that fouling can be subdivided into just two processes: short-term reversible fouling and long-term irreversible fouling. These two processes are described with two first order ordinary differential equations (ODEs). Whilst the first model characterises the membrane filtration process from an observer's input-output point of view without any rigorous deterministic description of the underlying mechanisms of membrane fouling, the second model provides a more theoretical and in-depth description of membrane fouling by incorporating and combining three classical macroscopic mechanistic fouling equations within a single simulation framework. Both models are calibrated on a number of experimental data and show good levels of accuracy for their designated applications and within the intended ranges of operating conditions. In the third part, the first developed biological model (CES-ASM1) is combined with the behavioural fouling model and the links between these two models are formulated to allow complete simulation of a hollow fibre (HF) immersed membrane bioreactor (iMBR). It is assumed that biological processes affect the membrane through production of mixed liquor suspended solids (MLSS), SMP and EPS which cause pore blockage, cake formation, pore diameter constriction, and affect the specific cake resistance (SCR). The membrane, on the other hand, has a direct effect on the bulk liquid SMP concentration due to its SMP rejection properties. SMP are assumed to be solely responsible for irreversible fouling, MLSS is directly linked to the amount of cake depositing on the membrane surface, whereas EPS content in activated sludge affects the cake's SCR. Other links provided in the integrated MBR model include the effects of air scouring on the rate of particle back-transport from the membrane surface and the effects of MLSS concentration on oxygen mass transfer. Although backwashing is not described in great detail, its effects are represented in the model by resetting the initial condition in the cake deposition equation after each backwash period. The MBR model was implemented in Simulink® using the plant layout adopted in the MBR benchmark model of Maere et al. [160]. The model was then simulated with the inputs and operational parameters defined in [36, 160]. The results were compared against the MBR benchmark model of Maere et al. [160] which, contrary to this work, does not take into account the production of biopolymers, the membrane fouling, nor any interactions between the biological and the membrane parts of an MBR system.
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Pereira, Sofia Filipe. "Modelling of a wastewater treatment plant using GPS-X." Master's thesis, Faculdade de Ciências e Tecnologia, 2014. http://hdl.handle.net/10362/13621.

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Dissertation to obtain the degree of Master in Chemical and Biochemical Engineering
The work present in this thesis was conducted in Portucel Soporcel mill, in the industrial complex of Setúbal, and had as main objective the modelling of the treatment process of the effluents from this industry, using for this purpose the software GPS-X. This program has a clear-cut graphical interface and uses a specialized translator that converts the graphical process into material balance equations, based on dynamic models. These models allow, besides the kinetic descripton of the treatment process carried out at the WWTP, to simulate new scenarios towards the study of critical parameters for the process as well as optimization and control of the WWTP. The effluent that arrives to Portucel’s WWTP, from the pulp and paper mills of the complex, is particularly rich on fibers (solids), lignin, chlorinated and sulphur compounds, resin acids, phenols and starch. It has a brown colour due to the presence of lignin and has a high oxygen chemical demand (about 1,095 g O2/m3). The WWTP uses the activated sludge process with extended aeration. This method allows an efficient removal of organics at the same time as it minimizes the sludge production. For the modelling of the process it was necessary to collect historical data related to the WWTP’s performance over the last 3 years. This data was used as input values for the influent characterisation and as output values to achieve the treated effluent characterisation. Since the first simulation did not lead to the desired output results, it was necessary to proceed to the model calibration, by means of a more detailed study concerning the nutrient and organic fractions of the influent. Once the model was calibrated, a study of the urea flowrate was conducted. The urea is added to the influent, before the beginning of the biological oxidation, as a way to satisfy the nitrogen requirements along the treatment process. However, this flowrate was never submitted to a study that evaluated, in a higher detail, the effective requirements of this nutrient. Thus, some simulations were done using the software, by decreasing successively the value of the urea flowrate and the results obtained were analyzed. Furthermore, these simulations were validated in the WWTP itself, at Portucel, through the decrease of the urea flowrate to half the normal value. Both the simulations and Portucel’s results showed that, actually, the addition of urea is not necessary because it does not affect the treatment process in a significant way, namely in terms of the removal of chemical oxygen demand. The simulations have also showed that the concentration of nitrogen in the final effluent diminishes significantly with the reduction of the urea flowrate, which could be advantageous in an environmental point of view.
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Pavasant, Prasert. "Modelling of the extractive membrane bioreactor process." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266478.

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Lumbers, Jeremy. "Rotating biological contactors : mechanisms, modelling and design." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/47161.

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Books on the topic "WASTEWATER TREATMENT MODELLING"

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Mannina, Giorgio, ed. Frontiers in Wastewater Treatment and Modelling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58421-8.

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Olsson, Gustaf. Wastewater treatment systems: Modelling, diagnosis and control. London: IWA Publishing, 1999.

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M, Henze, ed. Biological wastewater treatment: Principles, modelling and design. London: IWA Pub., 2008.

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Kiourtsidis, S. Advances in crossflow microfiltration process applied in wastewater treatment-modelling. Manchester: UMIST, 1994.

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Schütze, Manfred R. Modelling, simulation, and control of urban wastewater systems. London: Springer, 2002.

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M, Henze, and IAWPRC Specialised Seminar (1985 : Copenhagen, Denmark), eds. Modelling of biological wastewater treatment: Proceedings of an IAWPRC Specialised Seminar held in Copenhagen, Denmark, 28-30 August 1985. Oxford: Pergmaon, 1986.

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M, Henze, and International Association on Water Pollution Research and Control., eds. Modelling of biological wastewater treatment: Proceedings of an IAWPRC specialised seminar held in Copenhagen, Denmark 28-30 August 1985. Oxford: Pergamon, 1986.

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Laurent, Julien, Randal Samstag, Jim Wicks, and Ingmar Nopens, eds. CFD Modelling for Wastewater Treatment Processes. IWA Publishing, 2022. http://dx.doi.org/10.2166/9781780409030.

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Abstract:
Abstract This Scientific and Technical Report (STR) provides in-depth fundamentals and guidelines regarding Computational Fluid Dynamics (CFD) simulations of Water Resources Recovery Facilities (WRRFs) unit processes (e.g. headworks, aerobic and anaerobic biological reactors, settling tanks, disinfection). Each unit process is described with respect to: Literature review and process descriptionRelevant CFD concepts and modelling approachCase studiesFuture research needs CFD Modelling for Wastewater Treatment Processes also opens the discussion on two fundamental topics: experimental validation of CFD simulations, and the complementarity between CFD and Chemical Reaction Engineering approaches. This book is intended for undergraduate and graduate students majoring in fields related to wastewater treatment and/or fluid mechanics, as well as researchers and engineers who conduct research and practices in modelling such unit processes. Water resource recovery modelling is not just about lab-scale processes. Now and in the future it is about improving our understanding of (and designing better) full-scale facilities!
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Laurent, Julien, Ingmar Nopens, Jim Wicks, and Randal Samstag. CFD Modelling for Wastewater Treatment Processes. IWA Publishing, 2020.

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CFD Modelling for Wastewater Treatment Processes. IWA Publishing, 2020.

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Book chapters on the topic "WASTEWATER TREATMENT MODELLING"

1

Szetela, R. W. "Modelling Wastewater Treatment Plants." In Hydroinformatics Tools for Planning, Design, Operation and Rehabilitation of Sewer Systems, 335–55. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-017-1818-9_15.

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Gupta, A. K., and C. Sahoo. "Treatment of Industrial Wastewater." In Recent Trends in Modelling of Environmental Contaminants, 143–65. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1783-1_6.

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Boller, M., U. von Gunten, R. Pianta, and L. Solcà. "Modelling Full-Scale Advanced Micropollutant Oxidation." In Chemical Water and Wastewater Treatment VI, 125–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59791-6_12.

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Thomas, D. N., S. J. Judd, and N. Fawcett. "Flocculation Modelling of Primary Sewage Effluent." In Chemical Water and Wastewater Treatment V, 83–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72279-0_8.

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Drewnowski, J., and M. Zmarzły. "Mathematical Modelling in Diagnosis of Wastewater Treatment Plant." In Lecture Notes in Civil Engineering, 727–33. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58421-8_114.

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Mannina, Giorgio. "Erratum to: Frontiers in Wastewater Treatment and Modelling." In Lecture Notes in Civil Engineering, E1. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58421-8_116.

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Rizzo, Anacleto, Tamás Gábor Pálfy, and Nicolas Forquet. "Modelling Under Varying Flows." In Ecotechnologies for the Treatment of Variable Stormwater and Wastewater Flows, 111–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70013-7_7.

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Alcaraz-Gonzalez, Victor. "Modelling and Control of Wastewater Treatment Processes: An Overview and Recent Trends." In Water and Wastewater Management, 143–50. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95288-4_12.

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Džubur, Alma, Amra Serdarević, and Suvada Šuvalija. "Modelling Steps for Dynamic Simulation of Wastewater Treatment Processes." In Advanced Technologies, Systems, and Applications VII, 122–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17697-5_10.

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Santín, Ignacio, Carles Pedret, and Ramón Vilanova. "Process Modelling and Simulation Scenarios." In Control and Decision Strategies in Wastewater Treatment Plants for Operation Improvement, 5–15. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46367-4_2.

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Conference papers on the topic "WASTEWATER TREATMENT MODELLING"

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Gaya, Muhammad Sani, Norhaliza Abdul Wahab, Yahya Md Sam, Mashitah Che Razali, and S. I. Samsudin. "Neuro-fuzzy modelling of wastewater treatment system." In 2012 IEEE International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2012. http://dx.doi.org/10.1109/iccsce.2012.6487150.

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Zhen, Ran, Liang Wang, Xueli Wu, Chao Si, and Jianhua Zhang. "Adaptive neural network and its application in wastewater treatment." In 2015 7th International Conference on Modelling, Identification and Control (ICMIC). IEEE, 2015. http://dx.doi.org/10.1109/icmic.2015.7409460.

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Gasparovic, Claudia L. M., Eduardo Eyng, Laercio M. Frare, Larissa B. C. Sabbi, Michelle Budke Costa, and Fábio Orssatto. "Velocity Simulation of an Electrochemical Reactor for Textile Wastewater Treatment." In Modelling, Simulation and Identification / 841: Intelligent Systems and Control. Calgary,AB,Canada: ACTAPRESS, 2016. http://dx.doi.org/10.2316/p.2016.840-048.

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Ma, L., R. Duolikun, and X. Ma. "Hydraulic Mode of New Outside Cycle Anaerobic Reactor by Residence Time Distribution in Wastewater Treatment." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.699-023.

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Luca, Laurentiu, Marian Barbu, and Sergiu Caraman. "Modelling and performance analysis of an urban wastewater treatment plant." In 2014 18th International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2014. http://dx.doi.org/10.1109/icstcc.2014.6982430.

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Bernard, Olivier, Zacharia Hadj-Sadok, and Denis Dochain. "Dynamical modelling and state estimation of anaerobic wastewater treatment plants." In 1999 European Control Conference (ECC). IEEE, 1999. http://dx.doi.org/10.23919/ecc.1999.7099912.

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Pittol, José A., Yamitet Sánchez, Rosalba Lamanna, Silvana Revollar, and Pastora Vega. "A Fuzzy Virtual Sensor for Substrate Concentration in a Wastewater Treatment Plant." In Computational Intelligence and Bioinformatics / Modelling, Simulation, and Identification. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.755-058.

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Pittol, José A., Yamitet Sánchez, Rosalba Lamanna, Silvana Revollar, and Pastora Vega. "A Fuzzy Virtual Sensor for Substrate Concentration in a Wastewater Treatment Plant." In Computational Intelligence and Bioinformatics / Modelling, Simulation, and Identification. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.755-058.

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Birs, Isabela R., Ioana Nascu, Cosmin Darab, and Ioan Nascu. "Modelling and calibration of a conventional activated sludge wastewater treatment plant." In 2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR). IEEE, 2016. http://dx.doi.org/10.1109/aqtr.2016.7501327.

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Fang, Xusheng, Zhengang Zhai, Renhao Xiong, Li Zhang, and Bingtao Gao. "LSTM-based Modelling for Coagulant Dosage Prediction in Wastewater Treatment Plant." In AIEE 2022: 2022 The 3rd International Conference on Artificial Intelligence in Electronics Engineering. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3512826.3512847.

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