1,720,978 research outputs found
Development of an Integrated System for the Optimization of Sequencing Batch Reactors
No full textThis paper presents a synthesis of the EOLI supervision system for optimizing both the biological reaction phases and the settling phase of Sequencing Batch Reactors (SBR) performing carbon and nitrogen removal from urban or industrial wastewaters; (ii) a summary of the integration capabilities of the integrated system developed by an industrial partner of the project to propose both the hardware and the software of the EOLI solution under a unified framework
Monitoring denitrification by means of pH and ORP in continuous-flow conventional activated sludge processes
No full textIndirect signal analysis (pH, ORP and DO) are often used in monitoring and control of SBRs (Sequencing Batch Reactors), where operating conditions can be clearly identified during the various cyclic phases. Only few studies applied this methodology to control continuous flow plants, as it is much more difficult to identify operating conditions because of continually variable inflow characteristics. This work applied indirect signal analysis to control pre-denitrification in continuous-flow activated sludge processes: (i) a laboratory-scale plant, fed with synthetic wastewater, simulating real municipal wastewater and (ii) a pilot-scale plant, fed with real sewage. Three different ranges of ORP values identify three operational conditions of the denitrification process. (1) ORP > 0 mV means that nitrates and/or nitrites are present, possibly due to a low C/N ratio. (2) –50 < ORP < –200 mV is typical of normal operating conditions, that is with a balanced C/N ratio. (3) ORP < –350 mV means that oxidized nitrogen load is too low or that C/N exceeds the stoichiometric ratio. The trend of pH, instead, points out if and how the process is evolving from one to another operating condition. The correlation between pH and ORP signals (as well as their derivatives) allows to restore normal operating conditions by acting on the internal recycle flow-rate. Improved denitrification process ensures lower effluent nitrate concentration, and reduce external carbon dosage to achieve stricter nitrogen limits. © 2017 Desalination Publications. All rights reserved
A hybrid, integrated IEDDS for the management of Sequencing Batch Reactors
No full textA Sequencing Batch Reactor (SBR) is a particular kind of wastewater treatment plant (WWTP), where all treatment processes take place in a single reactor tank, according to a fixed temporal sequence. SBR offers several advantages in terms of reduced costs, minor impact and greater flexibility with respect to traditional WWTPs. However, an optimal cost/performance ratio can only be achieved if the treatment processes are continuously monitored and controlled. In this paper, we present a hybrid, distributed, knowledge-based (Intelligent) Environmental Decision Support System (IEDSS) specifically dedicated to the management of SBRs. The IEDSS is responsible for verifying, ensuring and enforcing the compliance of the processes with the optimal operation policies and the current regulations. The core of the IEDSS is composed by a hybrid, declarative knowledge base that encodes the knowledge and best practices for the management of the plant. It relies on OWL ontologies to describe the plant and its hardware equipment, business processes to model the plants treatment cycles, business rules to encode decision-making policies, an improved variant of Event Calculus (EC) to manage the temporal aspects and a compliance mechanism based on extended Event-Condition-Action rules (ECA rule) to monitor and check the compliance of its evaluations and decisions. The system as a whole has been implemented using open source technologies and has been tested on data coming from a pilot plant fed with real urban wastewater
SBR on-line monitoring by set-point titration
No full textThe applicability of set-point titration for monitoring biological processes has been widely demonstrated in the literature. Based on published and on-going experiences, some operating procedures have been specifically developed to be applied to SBRs, so that real-time information about the process and/or the influent can be obtained. This, in turn, would allow plant operators to select the most appropriate actions properly and timely. Five operating modes are described for the monitoring of (1) influent toxicity, (2) influent N-content, (3) nitrification capacity, (4) end of the nitrification reaction, and (5) nitrate effluent concentration, and are currently tested on the on-line titrator TITAAN (TITrimetric Automated ANalyser) which is in operation on a pilot scale SBR
Formal Verification of Wastewater Treatment Processes Using Events Detected from Continuous Signals by Means of Artificial Neural Networks. Case Study: SBR Plant
No full textThis paper proposes a modular architecture for the analysis and the validation of wastewater treatment processes. An algorithm using neural networks is used to extract the relevant qualitative patterns, such as apexes, knees and steps, from the signals acquired in the reaction tanks. These patterns, which show changes in the signals trend, are mapped to events in the process and logged using an appropriate XML format. The logs, in turn, are considered traces of the execution of a manufacturing process and validated using tools commonly applied for the Verification of Business Processes. The system has been applied to the data collected from a Sequencing Batch Reactor (SBR) for municipal wastewater treatment, equipped with probes for the on-line acquisition of signals such as pH, oxidation--reduction potential (ORP) and dissolved oxygen (DO). A SBR has turned out to be a suitable case study since the commonly acknowledged criteria for monitoring the biological processes (nitrification and denitrification) can be expressed in the form or qualitative constraints, which are easily translated into formal rules. The process logs, hence, are matched against these rules, which act as filters and quality classifiers
An ontology-based approach for the instrumentation, control and automation infrastructure of a WWTP
No full textThe instrumentation, control and automation of wastewater treatment plants (WWTPs) is a key aspect to ensure good performance and lower operational costs. However, control systems are seldom interoperable and standard-compliant. In this paper, we propose a knowledge-based approach which decouples the description of the plants and their control strategies from their physical structure and instrumentation. In particular, we propose a semantic model based on ontologies, formalized using the W3C OWL2 standard. We have extended the Semantic Sensor Network and created a specialized representation of the WWTP domain, to provide a consistent description of instrumentation (sensors and probes), actuators and data acquisition systems. We show how this ontology can be used to model typical management actions, such as collecting samples or applying a control policy, and their outcomes
Application of image analysis in activated sludge to evaluate correlations between settleability and features of flocs and filamentous species
No full textBrevetto Enea "Gruppo per la gestione automatizzata di impianti per il trattamento biologico di acque reflue. Parte 1. Verifica del funzionamento in campo e rappresentazione della base di conoscenza del dominio
Get PDFIl presente rapporto tecnico introduce Constance - COntrollo iNtelligente e geSTione Automatizzata per il trattameNto di aCque rEflue, un sistema brevettato da ENEA per la gestione intelligente e il controllo automatizzato di impianti di depurazione di acque di scarico, con lo studio di fattibilità e le verifiche di funzionalità effettuate in occasione della sua prima installazione in campo su un impianto di depurazione reale. Principalmente, viene rappresentata la base di conoscenza del dominio operativo, costituita dall’insieme di tutti i segnali acquisiti in campo, le relazioni esistenti tra essi e le elaborazioni necessarie al completo controllo del sistema. Constance utilizza logiche di controllo e politiche di gestione basate su tecniche di machine learning e sistemi a regole, usando unicamente segnali indiretti, quali pH e potenziale redox, misurabili con sensori affidabili ed economici, riducendo i costi di realizzazione e aumentando la robustezza del sistema. Constance garantisce un importante incremento dell’efficienza energetica del sistema di aerazione di oltre il 50% rispetto ad impianti non controllati, mantenendo un’elevata efficienza dei processi biologici, garantendo basse concentrazioni degli inquinanti allo scarico
Feasibility evaluation of contaminated lagoon sediment bioremediation with SS-SBR
No full textThe aim of this study is to evaluate the feasibility of the application of an aerobic sediment slurry-sequencing batch reactor (SS-SBR) for the treatment of polyciclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) contaminated lagoon sediment. In this work, the application of aerobic processes to SS-SBR technologies is investigated. In the study the Venice lagoon sediment samples were characterised for PAH, PCB and heavy metal contents. The sampled sediment were used for the preparation of several slurries. Respirometric experiments were carried out to evaluate the biological and chemical oxygen uptake rate. Moreover, PAHs and nine selected PCB congeners were measured during the respirometric tests. The sediment shows high chemical oxygen demand (approximately 50% of the total oxygen demand). The chemical oxygen uptake is particularly large at the initial phase. The chemical oxidation seems to be considerably faster than the biological reaction. Aerobic biodegradation seems to occur only for low-molecular-weight PAHs (two-three rings) whereas high molecular PAHs are not degraded during the duration of the experiments carried out in this study (five days). The nine PCB congeners measured in this research show an average disappearance of about 25 per cent
Modelling Biological Leachate Treatment in a Sequencing Batch Reactor
No full textOld landfill leachates are characterised by a low content of biodegradable COD
when compared to TKN. Therefore, biological nitrogen removal can only be achieved if external
COD is added for denitrification. In this study leachate treatment in a lab-scale sequencing batch
reactor was modelled using the activated sludge model N. 1 with minor modifications. The
model was calibrated using experimental data of one cycle (about six hours) and validated over
one entire week of operation. The model was capable of simulating reasonably well the leachate
treatment processes. In particular, nitrite-built-up observed in the lab-scale reactor during
nitrification was as well simulated by the model. If compared with the experimental periods in
which complete nitrification was achieved, the nitrite accumulation diminished the external COD
that was necessary for denitrification. The nitrite built-up was monitored using dissolved oxygen
concentration behaviour in the reactor and, therefore, this signal could be used to develop a
control system for nitrogen removal optimisation
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