An advanced simulation model for membrane bioreactors: development, calibration and validation

Membrane wastewater treatment plants (WWTPs) have several advantages compared with conventionally designed WWTPs with classical purification techniques. The filtration process is the key to their commercial success in Germany with respect to energy consumption and effectiveness, enabled by the optimization of filtration using a dynamic simulation model. This work is focused on the development of a robust, flexible and practically applicable membrane simulation model for submerged hollow-fibre and flat-sheet membrane modules. The model is based on standard parameters usually measured on membrane WWTPs. The performance of the model is demonstrated by successful calibration and validation for three different full-scale membrane WWTPs achieving good results. Furthermore, the model is combinable with Activated Sludge Models.     

Tertiary treatment of biologically treated piggery wastewater using vibratory shear-enhanced RO membrane.

This study presents a good example for the tertiary treatment of biologically treated piggery wastewater using vibratory shear enhanced RO membrane (VSEP RO). Through a simple process combination, utilizing Bioceramic SBR(BCS) and VSEP RO, at Gimhae plant livestock wastewater is treated excellently to meet the strict effluent standards. Application of RO membrane directly to the biologically treated effluent has been successful without any pretreatment to reduce high suspended solids. The combination of VESP UF followed by RO filtration processes produced a higher recovery rate in the 3-week pilot test.     

基于BioWin的MBR工艺模拟

以实际运行污水处理厂MBR工艺为研究对象,利用BioWinTM软件平台及其内嵌的通用活性污泥模型和厌氧消化模型(ASDM),建立了工艺模拟模型并进行初步模拟及校正,利用校正的模型对MBR工艺的运行参数进行了模拟分析,得到出水水质对工艺参数的敏感度,从而总结出了部分运行指南。     

Calibration and simulation of two large wastewater treatment plants operated for nutrient removal.

Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.     

Membrane bioreactor aeration: investigation of the velocity flow pattern.

Results of investigations concerning membrane bioreactor aeration are presented which were carried out at the Institute of Environmental Engineering of RWTH Aachen University (ISA) in cooperation with the Department of Chemical Engineering of the Technische Universit?t Berlin. In the field of industrial and municipal wastewater treatment the use of membrane bioreactors (MBR) is of increasing interest especially due to the high requirements on effluent quality nowadays. The design of aeration systems is a very important aspect of MBR development because it influences both cost of operation and filtration flux. The ISA has carried out tests concerning the velocity flow pattern in flat sheet membrane modules (developed by the A3 Water Solutions GmbH) to identify the effects of different aeration systems, aeration intensities and module constructions. The Department of Chemical Engineering is currently using the results obtained from the ADV to calibrate a numerical model which simulates two phase water and gas flow within an aerated membrane module. Optical investigations concerning the bubble distribution give a better understanding of the flow conditions in MBR. Developing a numerical tool for membrane module optimization concerning the hydrodynamics is the aim of the investigation of membrane bioreactor aeration.     

ASM1 dynamic calibration and long-term validation for an intermittently aerated WWTP.

Activated sludge models, and ASM1 in particular, are well recognised and useful mathematical representations of the macroscopic processes involved in the biological degradation of the pollution carried by wastewater. Nevertheless, the use of these models through simulation software requires a careful methodology for their calibration (determination of the model parameters' values) and the validation step (verification with an independent data set). This paper presents the methodology and the results of dynamic calibration and validation tasks as a prior work to a modelling project for defining a reference guideline destined to French designers and operators. To reach these goals, a biological nutrient removal (BNR) wastewater treatment plant (WWTP) with intermittent aeration was selected and monitored for 2 years. Two sets of calibrated parameters are given and discussed. The results of the long-term validation task are presented through a 2-month simulation with lots of operation changes. Finally, it is concluded that, even if calibrating ASM1 with a high degree of confidence with a single set of parameters was not possible, the results of the calibration are sufficient to obtain satisfactory results over long-term dynamic simulation. However, simulating long periods reveals specific calibration issues such as the variation of the nitrification capacity due to external events.     

Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression

The reservoir optimal operation depends on not only specific characteristics of reservoirs and hydropower stations but also stochastic inflows. The key issue of actual hydropower operation is to make an approximate optimal decision triggered by limited inflow forecasts. To implement actual optimal operation of hydropower system with limited inflows forecast, this paper makes use of Support Vector Regression (SVR) to derive optimal operating rules. To improve the performance of SVR, parameters in SVR model are calibrated with grid search and cross validation techniques. The trained SVR model describes the complex nonlinear relationships between reservoir operation decisions and factors by considering both generalization and regression performance, which overcomes local optimization and over fitting deficits. Hybrid programming platform is further developed to implement system simulation. This SVR model along with simulation platform is applied to the largest hydropower base in China – Jinsha system. Three scenarios are developed for comparison: deterministic optimal operation, SVR based simulation with calibrated parameters, SVR based simulation with default parameters. Comprehensive evaluation indicates that, operating rules derived from SVR presents a reliable performance in system power generation and output processes with respect to ideal deterministic results, especially when the parameters are calibrated. Hybrid programming technique provides a feasible and compatible platform for future research.     

NUMERICAL MODELING OF WASTEWATER TRANSPORT AND DEGRADATION IN SOIL AQUIFER

1. INTRODUCTION The wastewater soil treatment system is an ecological treatment system where a self-adjustingand purification mechanism involving land soil– microorganism–plant ecology is formed to effectively treat the wastewater, meanwhile the nutrien…     

Towards a generalized physicochemical framework

Process models used for activated sludge, anaerobic digestion and in general wastewater treatment plant process design and optimization have traditionally focused on important biokinetic conversions. There is a growing realization that abiotic processes occurring in the wastewater (i.e. 'solvent') have a fundamental effect on plant performance. These processes include weak acid-base reactions (ionization), spontaneous or chemical dose-induced precipitate formation and chemical redox conversions, which influence pH, gas transfer, and directly or indirectly the biokinetic processes themselves. There is a large amount of fundamental information available (from chemical and other disciplines), which, due to its complexity and its diverse sources (originating from many different water and process environments), cannot be readily used in wastewater process design as yet. This position paper outlines the need, the methods, available knowledge and the fundamental approaches that would help to focus the effort of research groups to develop a physicochemical framework specifically in support of whole-plant process modeling. The findings are that, in general, existing models such as produced by the International Water Association for biological processes are limited by omission of key corrections such as non-ideal acid-base behavior, as well as major processes (e.g., ion precipitation). While the underlying chemistry is well understood, its applicability to wastewater applications is less well known. This justifies important further research, with both experimental and model development activities to clarify an approach to modeling of physicochemical processes.     

Application of immersed MF (IMF) followed by reverse osmosis (RO) membrane for wastewater reclamation: A case study in Malaysia.

A pilot scale membrane plant was constructed and monitored in Shah Alam, Malaysia for municipal wastewater reclamation for industrial application purposes. The aim of this study was to verify its suitability under the local conditions and environmental constraints for secondary wastewater reclamation. Immersed-type crossflow microfiltration (IMF) was selected as the pretreatment step before reverse osmosis filtration. Secondary wastewater after chlorine contact tank was selected as feed water. The results indicated that the membrane system is capable of producing a filtrate meeting the requirements of both WHO drinking water standards and Malaysian Effluent Standard A. With the application of an automatic backwash process, IMF performed well in hydraulic performance with low fouling rate being achieved. The investigations showed also that chemical cleaning is still needed because of some irreversible fouling by microorganisms always remains. RO treatment with IMF pretreatment process was significantly applicable for wastewater reuse purposes and promised good hydraulic performance.     

The role of physical-chemical treatment in wastewater reclamation and reuse

Amid the heightened public health concerns for emerging microorganisms such as cryptosporidium and enteropathogenic E. coli in the water environment, there have been many instances where optimization of chemical coagulation-flocculation processes and filtration of wastewater was not achieved in practice, resulting in waste of coagulant chemicals and breach of the multiple barriers to pathogen removal and inactivation; thus, unnecessarily endangering public health. In addition, lack of information on the optimization of these processes has hampered the establishment of alternative and more cost-effective wastewater reclamation methods for tertiary and advanced wastewater treatment.Thus, the purpose of this paper is to evaluate the basic factors affecting the optimization of chemical coagulation-flocculation and filtration processes in municipal wastewater reclamation and reuse, based on the theoretical developments and practical applications. Reference is also made to the wastewater treatment processes and operations that can produce reclaimed water with an extremely small probability of enteric virus contamination.     

Membrane filtration and sonication for industrial wastewater reuse

This paper presents an experimental study aimed at estimating the efficiency of the innovative process of ultrafiltration (UF) combined with sonication (Son.) for the refinement of treated effluent to be reused in wet textile processes. Such a novel approach, which has not yet been employed on a full industrial scale, has been experienced at pilot scale on the secondary effluent of the Baciacavallo wastewater treatment plant (WWTP), which treats part of the effluent from one of the largest textile industry districts in Italy. The combined treatment efficiency was assessed both on ozonated and non-ozonated Baciacavallo secondary effluent. The membrane filtration process was optimized in terms of running time, backwash, chemical addition and cleaning procedures. The sonication treatment was optimized on laboratory-scale with synthetic solutions (demineralized water added with dyestuffs) in terms of hydroxyl radicals formation rate, frequency, acoustic power, hydrogen peroxide addition, contact time and pH. The optimal conditions have been applied on the pilot-scale sonicator which was used in combination with the UF treatment. According to the experimental results, the best configuration within the Baciacavallo WWTP was the sonication of non-ozonated wastewater followed by the UF. The combined treatment guaranteed the compliance with the target values for wastewater reuse in wet textile industries. This study is part of the Research Project PURIFAST (Purification of industrial and mixed wastewater by combined membrane filtration and sonochemical technologies) LIFE + ENV/IT/000439.     

State estimation for anaerobic digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.     

An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management

Water quality management is complicated with a variety of uncertainties and nonlinearities. This leads to difficulties in formulating and solving the resulting inexact nonlinear optimization problems. In this study, an inexact chance-constrained quadratic programming (ICCQP) model was developed for stream water quality management. A multi-segment stream water quality (MSWQ) simulation model was provided for establishing the relationship between environmental responses and pollution-control actions. The relationship was described by transformation matrices and vectors that could be used directly in a multi-point-source waste reduction (MWR) optimization model as water-quality constraints. The interval quadratic polynomials were employed to reflect the nonlinearities and uncertainties associated with wastewater treatment costs. Uncertainties associated with the water-quality parameters were projected into the transformation matrices and vectors through Monte Carlo simulation. Uncertainties derived from water quality standards were characterized as random variables with normal probability distributions. The proposed ICCQP model was applied to a water quality management problem in the Changsha section of the Xiangjiang River in China. The results demonstrated that the proposed optimization model could effectively communicate uncertainties into the optimization process, and generate inexact solutions containing a spectrum of wastewater treatment options. Decision alternatives could then be obtained by adjusting different combinations of the decision variables within their solution intervals. Solutions from the ICCQP model could be used to analyze tradeoffs between the wastewater treatment cost and system-failure risk due to inherent uncertainties. The results are valuable for supporting decision makers in seeking cost-effective water management strategies.     

Optimal Management of Coastal Aquifers Using Linked Simulation Optimization Approach

Saltwater intrusion management models can be used to derive optimal and efficient management strategies for controlling saltwater intrusion in coastal aquifers. To obtain physically meaningful optimal management strategies, the physical processes involved need to be simulated while deriving the management strategies. The flow and transport processes involved in coastal aquifers are difficult to simulate especially when the density-dependent flow and transport processes need to be modeled. Incorporation of this simulation model within an optimization-based management model is very complex and difficult. However, as an alternative, it is possible to link a simulation model externally with an optimization-based management model. The GA-based optimization approach is especially suitable for externally linking the numerical simulation model within the optimization model. Further efficiency in computational procedure can be achieved for such a linked model, if the simulation process can be simplified by approximation, as very large number of iterations between the optimization and simulation model is generally necessary to evolve an optimal management strategy. A possible approach for approximating the simulation model is to use a trained Artificial Neural Network (ANN) as the approximate simulator. Therefore, an ANN model is trained as an approximator of the three dimensional density-dependent flow and transport processes in a coastal aquifer. A linked simulation – optimization model is then developed to link the trained ANN with the GA-based optimization model for solving saltwater management problems. The performance of the developed optimization model is evaluated using an illustrative study area. The evaluation results show the potential applicability of the developed methodology using a GA- and ANN-based linked optimization – simulation model for optimal management of coastal aquifer.     

Selection of operational strategies in activated sludge processes based on optimization algorithms

This paper presents a new optimization algorithm for the selection of design and operation parameters in complex Activated Sludge (AS) processes. The algorithm estimates automatically the dimensions and operating point of the plant that minimize a global penalty function combining effluent requirements and costs. The mathematical optimization is based on a direct search algorithm integrated in a previously developed simulation package.Some illustrative examples concerning the design and operation of the Alpha process have been included to show the potential of this kind of mathematical tool when the complexity of plant configuration increases. The results obtained by the optimization procedure generate useful guidelines for the design and operation and suggest a great potential in the application for solving more complex problems when additional objectives and costs are included.     

Three stages MBR (methanogenic, aerobic biofilm and membrane filtration) for the treatment of low-strength wastewaters

The use of a new three stages MBR process with a first methanogenic UASB stage, a second stage with aerobic biofilm growing on small carrier elements maintained in suspension and third stage with membrane filtration module is presented. The objective of the first methanogenic chamber is to diminish COD of the raw wastewater, producing a biogas rich in methane, and decrease the sludge production. In the second stage, the remaining soluble biodegradable COD is oxidized by heterotrophs. In the third stage, the membrane modules could be operated at higher fluxes than those reported for AnMBR systems, and similar to those obtained in aerobic MBRs. In this sense, the concept of these three stages MBR is to join the advantages of the methanogenic and aerobic membrane bioreactor processes, by reducing energy requirements for aeration, producing biogas with high methane percentage and a permeate with very low COD content. A synthetic wastewater was fed to the three stages MBR. COD in the influent was between 200 and 1,200 mg/L, ammonium ranged from 10 to 35 mg/L and phosphorous concentration was 8 mg/L. OLR in-between 1 and 3 kg COD/(m3 d) and a HRT of 13-21 h were applied. Temperature was between 17.5 and 23.2 degrees C. During the whole operating period the COD removal efficiencies were in the range of 90 and 96% of which in between 40 and 80% was removed in the first methanogenic chamber. Biogas production with methane content between 75 and 80% was observed. With regard to membrane operation, average permeabilities around 150 L/(m2 h bar) were achieved, operating with fluxes of 11-15 L/(m2 h).     

Model-based evaluation of nitrogen removal in a tannery wastewater treatment plant.

Computer modelling has been used in the last 15 years as a powerful tool for understanding the behaviour of activated sludge wastewater treatment systems. However, computer models are mainly applied for domestic wastewater treatment plants (WWTPs). Application of these types of models to industrial wastewater treatment plants requires a different model structure and an accurate estimation of the kinetics and stoichiometry of the model parameters, which may be different from the ones used for domestic wastewater. Most of these parameters are strongly dependent on the wastewater composition. In this study a modified version of the activated sludge model No. 1 (ASM 1) was used to describe a tannery WWTP. Several biological tests and complementary physical-chemical analyses were performed to characterise the wastewater and sludge composition in the context of activated sludge modelling. The proposed model was calibrated under steady-state conditions and validated under dynamic flow conditions. The model was successfully used to obtain insight into the existing plant performance, possible extension and options for process optimisation. The model illustrated the potential capacity of the plant to achieve full denitrification and to handle a higher hydraulic load. Moreover, the use of a mathematical model as an effective tool in decision making was demonstrated.     

Organic colloids and their influence on low-pressure membrane filtration.

Wastewater treatment by low-pressure membrane filtration (MF and UF) is affected to a large extent by macromolecules and colloids. In order to investigate the influence of organic colloids on the membrane filtration process, colloids were isolated from a wastewater treatment plant effluent using a rotary-evaporation pre-concentration step followed by dialysis. Stirred cell tests were carried out using redissolved colloids, with and without additional glass fiber filtration. After constant pressure membrane filtration of 190 L/m2, the initial flux had declined by 50% for colloids > 6-8 kD (glass fiber filtered) with a hydrophilic MF membrane and for colloids > 12-14 kD (glass fiber filtered) with a hydrophobic MF membrane. For the non-filtered colloidal solutions, the flux decline was even steeper with the flux being below 10% of the initial flux after 190 L/m2 were passed through the membranes. As with larger particles, colloids form a filtration cake layer on top of the membrane surface when used as isolates without prior filtration. This filtration cake is easily removed during backwashing. However, polysaccharides as a macromolecular component of the colloid isolate cause severe fouling by the formation of a gel layer on the membrane surface that is difficult to remove completely.     

Principles of an enhanced MBR-process with mechanical cleaning

Up to date, different physical and chemical cleaning protocols are necessary to limit membrane fouling in membrane bioreactors. This paper deals with a mechanical cleaning process, which aims at the avoidance of hypochlorite and other critical chemicals in MBR with submerged flat sheet modules. The process basically consists of the addition of plastic particles into the loop circulation within submerged membrane modules. Investigations of two pilot plants are presented: Pilot plant 1 is equipped with a 10 m(2) membrane module and operated with a translucent model suspension; pilot plant 2 is equipped with four 50 m(2) membrane modules and operated with pretreated sewage. Results of pilot plant 1 show that the establishment of a fluidised bed with regular particle distribution is possible for a variety of particles. Particles with maximum densities of 1.05 g/cm(3) and between 3 and 5 mm diameter form a stable fluidised bed almost regardless of activated sludge concentration, viscosity and reactor geometry. Particles with densities between 1.05 g/cm(3) and 1.2 g/cm(3) form a stable fluidised bed, if the velocity at the reactor bottom is sufficiently high. Activities within pilot plant 2 focused on plant optimisation and the development of an adequate particle retention system.