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Integration of models, data management, interfaces and training support in a drinking water treatment plant simulator
Abstract
Water supply companies are gradually changing to a centralised, fully automated operation. The drivers for this change are the increase in efficiency and a better and more stable water quality. Fully automated treatment plants will require more sophisticated operator care than manually operated plants, so operation supervisors should periodically train in a drinking water treatment plant simulator. The successful first time setup of such a simulator is addressed in this paper. Environmental decision-support systems (EDSSs) were used as a blueprint for this simulator because the integration of different models is common in EDSSs. By applying a SCADA-like graphic user interface and several report options, even a group of end-users without specific modelling skills or knowledge can take advantage of the use of integrated hydraulic, water quality and process control models. The ‘Waterspot’ drinking water treatment plant simulator has been developed and applied to Dutch drinking water treatment plants. To demonstrate successful application, a case study is described for the drinking water treatment plant at Weesperkarspel.
... Data to be analyzed has to be entered through a graphic interface by means of property dialogs (Bartolín et al. 2008). EPA-NET is employed in various fields of research, where there is a need for continuous improvement (Ardeshir et al. 2006;Martinez et al. 2007;Worm et al. 2010;Guidolin et al. 2010;Yu et al. 2010;Ramesh et al. 2012;Padilla et al. 2013;Abdelbaki 2014). For example, in Algeria a methodology for implementation of GIS coupled with EPANET for the Chetouane water distribution network (WDN) has been developed to take advantage of a powerful modeling environment. ...
... EPANET (Rossman 2000) was chosen for the simulation of the distribution of velocities and pressures. In EPANET, supply networks are defined by elements, such as nodes, pipes, valves and tanks (Guidolin et al. 2010;Worm et al. 2010). ...
... The latter is free software which can convert all elements from GIS, such as lines and polylines in layers at DXF format, in a set of pipes and fittings in EPANET (Rossman 2000). Additional elements such as tanks, pumps and valves should be added manually to the model in EPANET (Worm et al. 2010). The conversion software can calculate the lengths of pipes; while other network data, such as elevations nodes, water need and pipe diameters must be modified using EPANET (Rossman 2000) after the converted file is loaded. ...
For more effective management of water distribution network in an arid region, Mapinfo GIS (8.0) software was coupled with a hydraulic model (EPANET 2.0) and applied to a case study region, Chetouane, situated in the north-west of Algeria. The area is characterized not only by water scarcity but also by poor water management practices. The results showed that a combination of GIS and modeling permits network operators to better analyze malfunctions with a resulting more rapid response as well as facilitating in an improved understanding of the work performed on the network. The grouping of GIS and modeling as an operating tool allows managers to diagnosis a network, to study solutions of problems and to predict future situations. The later can assist them in making informed decisions to ensure an acceptable performance level for optimal network operation.
... Robert Sitzenfrei et al., 2013 ont développé une nouvelle approche utilisée pour estimer les coûts de construction des réseaux d'AEP projetés visant à traiter la croissance de la population ou à des comparaisons de différentes stratégies d'expansion dans la croissance. Les travaux les plus récents dans le domaines des réseaux d'eau potable sont ceux de : G.I.M. Worm et al., 2010, Cheng-I Ho et al., 2010, Adel Gastli et al., 2010Mahmoud R. Halfawy (2010), Yong Ge, 2010, Weifeng Li et al., 2011, D.A. Sampson, 2011, Jiping Jianga et al., 2012, Robert Sitzenfrei et al., 2013, Holguin -Gonzalez et al., 2013, B. Coelho & A. Andrade-Campos, 2014, Javier E. Holguin, Bakhtiar Feizizadeh et al., 2014, A.T. Kulkarni, et al., 2014 Le SIG est principalement sollicité pour ses capacités d'analyse reliées à la manipulation des données d'entrée du modèle (changement de formats et de structures, interrogation de la base de données et pré-traitements) (CGDD, 2012). Nous prétendons que les capacités analytiques du SIG devraient davantage être mises à profit pour le traitement des données intermédiaires et de sorties des modèles mais également pour la formulation du modèle luimême. ...
... Certains livres ont également été destinés à ce thème (Fischer et Nijkamp, 1993;Fischer et al., 1996;Haines-Young et al., 1993;Singh et Fiorentino, 1996;Sample, 1994) in (Pouliot, 1999). Quelques exemples de couplage trouvés dans la littérature concernant les réseaux d'alimentation en eau potable sont cités dans les sections suivantes : Kleiner et al. (2001) Worm et al., 2010;Guidolin et al., 2010, Tian Yu Ma Liya et al., 2010M. Tabesh et al., 2011, Nianqing Zhou et al., 2011, I. E. Karadirek et al., 2012, Andrew S. Benson et al., 2012, Ramesh et al., 2012, M. Tabesh & H. Saber, 2012, Panagopoulos et al, 2012, Wojciech Kurek et Avi Ostfeld, 2013, Ni-Bin Chang et al., 2013, Robert Sitzenfrei et al., 2013, Abbas Roozbahani et al., 2013, Nilufar Islam et al, 2013, Robert Janke et al., 2013, M. Shafiqul Islam et al., 2013, G. Fattoruso et al., 2013, Lynn E. Johnson , 2013, W.R. Furnass et al., 2013,Padilla et al., 2013et Kegong Diao, et al, 2014, Taeho Choi & Jayong Koo (2014, Peter M. Bach et al., 2014 ...
... Il présente une convivialité au niveau de son interface qui permet de le rendre assez facilement accessible (Générale des eaux, 2003). Epanet (Rossman, 2000) est utilisé dans divers domaine de recherche, d'où une perpétuelle amélioration suivie d'extensions est développé, conjuguée aux SIG, les travaux les plus récents sont faits par : Stefan et al , 2000;Burrows et al., 2000;Bell et al., 2000;Bartolin et al., 2001;Bahadur et al, 2001;Brown et al., 2002;Daene et al., 2002, Gumbo et al., 2003Argent, 2004;Alonso et al., 2004;Biagioni., 2004;Ardeshir, et al., 2006;Tao Zhang, 2006;Zheng Yi Wu et al., 2006;Marunga et al., 2006 ;Martinez et al., 2007;Yong Liu et al., 2007;Vairavamoorthy et al., 2007;Haifeng et al., 2008;Jun et al., 2008;Bartolin et al., 2008;Tabesh et al., 2009;Torres et al., 2009;Kenneth et al., 2009, Tabesh et al., 2010Worm et al., 2010;Guidolin et al., 2010, Tian Yu Ma Liya et al., 2010Daoyi et al., 2010, Franchini et Alvisi, 2010Tabesh et al., 2011;Zhou et al., 2011;Karadirek et al., 2012;Benson et al., 2012;Ramesh et al., 2012;Tabesh et Saber, 2012;Panagopoulos et al., 2012;Kurek et Ostfeld, 2013;Ni-Bin Chang et al., 2013;Sitzenfrei et al., 2013;Roozbahani et al., 2013;Nilufar al., 2013;Janke et al., 2013 ;Shafiqul et al., 2013;Fattoruso et al., 2013;Lynn, 2013;Furnass et al., 2013;Padilla et al., 2013;Choi et Koo 2014, Bach et al., 2014et Diao et al., 2014. ...
Ce travail consiste à modéliser le réseau d’alimentation en eau potable du groupement urbain de la ville de Tlemcen (GUT), Algérie, et à rechercher une approche de gestion de ce dernier via des outils d’investigation puissants que sont les systèmes d’information géographique (SIG). Le manque d’eau que subit ce groupement est dû non seulement à la conséquence de la sécheresse qu’a connue la ville cette dernière décennie, mais aussi à une gestion délicate et difficile du fait de l’utilisation d’outils d’investigation archaïques (archivage manuel, plans…). La tension relative à l’alimentation en eau potable qui règne actuellement ne cesse de croître avec le développement socioéconomique, culturel et touristique du GUT, demandant une rationalisation de l’eau potable par crainte de voir s’instaurer un véritable souci pour son acquisition, si une politique d’anticipation, de planification et de contrôle ne suit pas. La croissance sociale dynamique conjuguée à la concentration de la population dans le centre urbain et à l’acuité des problèmes techniques liés à l’alimentation en eau confronte la maîtrise de la gestion du réseau et les interpelle pour une meilleure exploitation, voire pour une optimisation via l’acquisition et l’utilisation d’outils modernes que sont les SIG. Pour l’amélioration de la connaissance du réseau, la détection et la compréhension des désordres pouvant s’y produire, la simulation de son fonctionnement, le dimensionnement des extensions, la prévision des branchements particuliers, la décision sur le choix de l’emplacement et les situations futures, seule la gestion à l’aide d’un SIG pourra répondre à cette problématique. Dans un souci d’efficacité, une démarche méthodologique a été adoptée pour mettre en place le SIG de l’alimentation en eau potable du GUT, cette démarche est basée sur une approche systémique. Le SIG
mis en place est couplé au modèle de simulation d’écoulement dans les réseaux de distribution « Epanet ». Des sous programmes en langage MapBasic sont développés pour le couplage SIG - Epanet. Une enquête est ensuite menée, cette enquête a touché l’organisme gestionnaire du réseau de distribution d’eau potable et les abonnés du GUT. Les résultats sont prometteurs.
Mots clés : Approche systémique, Modélisation, SIG, Epanet, Réseau d’AEP, Gestion.
Abstract : This work aims to model a drinking water network and to seek a management approach for this latter for the Tlemcen city Urban Grouping (UGT), Algeria, using geographic information systems (GIS). Water shortages experienced by this grouping are not only a consequence of the drought which has occurred in the city over the last
decade, but also a delicate and difficult management issue due to the use of archaic investigative tools (manual archiving, plans…). The current pressure on water supply keeps on growing along with socio-economic, cultural and tourism development of UGT, requiring rationalization of drinking water for fear of seeing a genuine concern being
established regarding its availability, in the case where a policy of anticipation, planning and control did not follow. Due to the growth coupled with the social dynamics of population concentration in the urban centre, together with acute technical problems related to water supply, operators are faced with network management control and the
challenge of a better practice, or even optimization through the acquisition and use of modern tools such as GIS. To improve the knowledge of the network, as well as the detecting and understanding of disorders that occur there, the simulation of operations, the design of extensions, the prediction of private connections, the decision making related to the location choice and future situations, only management using a geographic information system (GIS) is able to address this issue. In the interests of efficiency, a geographical information system is developed and coupled with “Epanet” simulation model of flow in distribution networks. MapBasic language subroutines are developed for
coupling GIS-Epanet. A survey was conducted; this survey covered the organization managing of the water distribution network and subscribers of UGT. Results are promising.
Key words : Systemic approach, Modeling, GIS, Epanet, Water Distribution Network; Management
... A different simulator which simulates a drinking water treatment plant was illustrated in [8]. According to [8], operators at recent drinking water treatment plants were required to have more sophisticated knowledge and technology than ever because those plants are fully automated. ...
... A different simulator which simulates a drinking water treatment plant was illustrated in [8]. According to [8], operators at recent drinking water treatment plants were required to have more sophisticated knowledge and technology than ever because those plants are fully automated. They developed a simulator for Dutch drinking water treatment plants using Environmental decision-support systems (EDSSs). ...
... EPANET has been used in various fields of researchcombined with GIS. The most recent work has been reported by Stefan et al., 2000;Burrows et al., 2000;Bell et al., 2000;Bartolin et al., 2001;Bahadur et al, 2001;Brown et al., 2002;Daene et al., 2002 ;Gumbo et al., 2003;Alonso et al., 2004;Biagioni B., 2004;Ardeshir, et al., 2006;Marunga et al., 2006 ;Zhang Tao, 2006;Zheng Yi Wu et al., 2006;Martinez et al., 2007;Yong Liu et al., 2007;Vairavamoorthy et al., 2007;Haifeng et al., 2008;Jun et al., 2008;Bartolin et al., 2008;Tabesh et al., 2009;Kenneth et al., 2009;Torres et al., 2009 ;Daoyi et al., 2010 ;Franchini and Alvisi, 2010;Guidolin et al., 2010 ;Tabesh et al., 2010;Tian Yu Ma Liya et al., 2010;Worm et al., 2010;Tabesh et al., 2011;Zhou et al., 2011;Benson et al., 2012;Karadirek et al., 2012;Ramesh et al., 2012;Tabesh and Saber, 2012;Panagopoulos et al., 2012;Fattoruso et al., 2013;Furnass et al., 2013;Janke et al., 2013;Lynn, 2013;Kurek and Ostfeld, 2013 ;Nilufar al., 2013;Padilla et al., 2013;Roozbahani et al., 2013;Shafiqul et al., 2013;Sitzenfrei et al., 2013;Bach et al., 2014;Diao et al., 2014;Kanakoudis et al., 2014;Abdelbaki 2014;Choi andKoo 2015 andAbdelbaki et al., 2017. Coupling allows GIS to leverage the analytic capabilities of models with the models taking on the graphical and data management capabilities of GIS (Nyerges, 1992). ...
... It is a program that converts all line and polyline elements (in DXF format layers) into a set of pipes and fittings under EPANET (Rossman, 2000). Additional elements must be added manually to the model (Worm et al., 2010) such as tanks, pumps and valves.The conversion program can calculate pipe lengths. Other network data such as node elevations, pipe demands and pipe diameters must be manually entered into EPANET (Rossman, 2000) after the converted file is loaded (Figure 15). ...
Increases in the growth of urban regions along with climate change have contributed to a scarcity in water resources. For arid regions, this problem may be aggravated by inadequate management plans and a lack of proper data collection related to the geographical location of water distribution networks. A possible solution is the utilization of a geographical information system (GIS) as a tool in decision-making process in the field of water distribution management. Coupling external hydraulic calculation models with GIS can further enhance this management tool. The current study utilized these tools in assessing the performance of a drinking water distribution network of an urban cluster in Tlemcen, Algeria. A methodology was developed by coupling GIS to a hydraulic calculation model (EPANET). The results showed that it is possible to obtain an alphanumeric description of the pipes, tanks, and all the accessories constituting the network. Design irregularities in the Tlemcen urban cluster’s network were identified. The approach adopted in this chapter contributes effectively to the management of water distribution networks using GIS. This offers operators a management tool that allows for analysis of malfunctions with an instantaneous response, to study various solutions and to plan for future situations.
... Water supply companies are gradually shifting to centralised, fully-automated operations (Worm et al., 2010). The motivation for this change is the need for increased eciency and a better and more stable water quality. ...
... understanding the system behaviour to be achieved.Worm et al. (2010) discusses the successes in setting up this type of simulator for the rst time. The simulation in the study incorporates four simultaneous models: a water quality model, a hydraulic model, a process control model and a eld object model. In general, there is a need to develop plant-wide dynamic models able to describe start-up, shut-down, ...
One of the biggest operational risks to water companies arises from their ability to control the day-to-day management of their water treatment plants. With increasing pressures to remain competitive, companies are looking for solutions to be able to make predictions on how their treatment processes can be improved. This work focuses on mathematical modelling and optimisation of clean water treatment processes. The main motivation is to provide tools which water companies can use to predict the performance of their plants to enable better control of risks and uncertainties. Most modelling work within water operations has so far been based on empirical observations rather than on mathematically describable relationships of the process as will be considered in this work. Mathematical models are essential to describe, predict and control the complicated interactions between the different parts of the treatment process, a concept which is well understood within the process industry but not yet established within the water treatment industry. This work will also consider the level of modelling detail actually required to accurately represent a water treatment plant. This thesis develops the conceptual understanding of clean water treatment processes utilising first principles modelling techniques. The main objective of this work is the consideration of a complete mathematical model of an entire water treatment plant, which enables a wider view on how changes in one processing unit will affect the treatment process as a whole. The performance of the process models are first verified individually and are then combined to enable the simulation of a complete water treatment work. By using detailed modelling (especially gPROMS utilised in this work) requires specialist software knowledge. Without knowledge of advanced simulation tools or having a background in process modelling, the detailed models developed in this work would not be fully utilised if implemented in the water industry, if utilised at all. A systematic framework is presented for the development of simpler surrogate models that can be used to predict the effluent suspended solids concentration, for a given number of independent variables. This approach can provide valuable guidance in clean water treatment process design and operation, thus providing a tool to achieve better day-to-day performance management.
... In a shift from least-cost optimization PBMs, recent literature has explored scenario-based modeling for multiple objectives. Both Worm et al. 98 and Rietveld et al. 99 use scenario-based numerical models to inform operational decision-making. Furthermore, Ribera et al. 100 uses a scenariobased approach to perform a life cycle and human health risk assessment on nanofiltration alternatives. ...
... Moreover, Dharmappa et al. creates a practical framework for integrating data from bench-and pilot-scale studies into DSSs throughout the design process. Worm et al. 98 and Rietveld et al. 99 also provide good examples of practical DSS research. Their papers include discussions of the graphical user interface, a case study for DSS implementation, and additional features such as operator training support. ...
Water treatment plants (WTPs) are tasked with providing safe potable water to consumers. However, WTPs face numerous potential obstacles, including changes in source water quality and quantity, financial burdens related to operations and upgrades, and stringent water quality regulations. Moreover, these challenges may be exacerbated by climate change in the form of long-term climatic perturbations and the increasing frequency and intensity of extreme weather events. To help WTPs overcome these issues, decision support systems (DSSs), which are used to aid and enhance the quality and consistency of decision-making, have been developed. This paper reviews the scientific literature on the development and application of DSSs for water treatment, including physically-based models, statistical models, and artificial intelligence techniques, and suggests future directions in the field. We first set the context of how water quality is impacted by climate change and extreme weather events. We then provide a comprehensive review of DSSs and conclude by offering a series of recommendations for future DSS efforts for WTPs, suggesting that these tools should (1) more accurately reflect the practical needs of WTPs, (2) represent the tradeoffs between the multiple competing objectives inherent to water treatment, (3) explicitly handle uncertainty to better inform decision makers, (4) incorporate nonstationarity, especially with regard to extreme weather events and climate change for long-term planning, and (5) use standardized terminology to accelerate the dissemination of knowledge in the field.
... The Waterspot simulator combines a graphical user interface (GUI) with four models: a process model for water quality, a process model for hydraulics, a control model and an object model [22]. An overview of the simulator's software structure is shown in Fig. 1. ...
... Simulator software's structure[22]. ...
The usefulness of a human-in-the-loop drinking-water-treatment-plant simulator was investigated for training and assessment. An in-simulator transfer of training experiment was conducted with three groups training with accelerated simulation, experienced operators (EO), inexperienced operators (IO), and laymen (L60x) and a group of laymen training at real-time speed (L1x). Participants learned how to improve water quality during training. Upon transfer, when confronted with a different process disturbance than during training, L60x performed significantly poorer than EO and IO combined. No difference was found between EO and IO, and during transfer, L60x outperformed L1x. These results indicate that learning to control slow and complex processes may improve by training with a realistic simulation running at accelerated speed.
... Farmers usually do not react well when delivered large amounts of redundant, complicated information, some of which they do not even need (Ascough et al., 2010). Worm et al. (2010) showed that the acceptance of a DT increases with its improved "look and feel". Historically, many DTs reported outputs in quantitative terms, which growers find difficult to interpret: based a number, a grower still has a decision to make. ...
Agriculture needs to reduce its current dependence toward pesticides while reducing crop losses caused by pests and ensuring food security; Integrated Pest Management (IPM) is considered the most appropriate approach to achieve the goal. More specifically, growers should use tools that enable informed decisions on whether and when crop protection is needed, and which methods should be used. These tools include risk algorithms, decision rules, intervention thresholds, and decision support systems (DSSs), collectively named decision tools (DTs). A large number of DTs have been developed and made available to advisors and farmers, mainly through Internet-based systems. The adoption rate of these systems, however, has been low because of technical limitations and farmer perceptions. Fragmentation of the DTs offered, poor local implementation, and restriction to particular users are among the causes for low adoption. If properly mobilised, the use and effects of DTs could substantially be increased. Sharing of IPM DTs has a strong potential for providing wider access to the existing knowledge, for fostering IPM implementation, and for supporting plant health policies. In this article, we outline an overall approach to develop a web-based platform, in which DTs are shared and made widely available. Such a platform can include a range of ready-to-use DTs, i.e. DTs which are currently available, that have been field-validated, and which are already being used in some agricultural contexts. The platform also provides open, full documentation of DTs, makes DTs available for validation and adaptation in different agricultural contexts, and makes DTs easily available for multiple kinds of end-users involved in IPM (farmers, IPM experts, public and private information and service providers, and policy makers). We also consider how DT sharing can reduce both the technological and behavioural limitations of existing plant health management systems.
... User-friendly hardware-software interfaces and usability are important factors that affect DSS usage (Naura, 2011). How data and information are presented to farmers can influence their perception and adoption of DSS (Rossi et al., 2012;Worm et al., 2010). Farmers desire a direct, clear, and unambiguous pathway for information that can guide their farming decisions (Rossi et al., 2012). ...
The use of intelligent decision support systems (DSS) in precision farming provides an opportunity to improve agricultural recommendations and reduce the impacts of agriculture on the environment. Despite the benefits offered by DDS, many farmers remain skeptical of using these hardware and software tools, and their adoption rates have remained low. A survey of 312 South Dakota farmers examined the barriers and opportunities for their engagement with DSS. Exploratory factor analysis was used to analyze 13 Likert scale survey items that probed farmers’ concerns about DSS. Factor loadings indicated that farmers’ concerns are related to high cost, insufficient knowledge, lack of confidence, and cyber security and privacy. A latent profile analysis (LPA) method was used to classify respondents into profiles or groups based on their dimensions of concerns (cost, knowledge, confidence, and security). Results of the LPA revealed that the sample of farmers could be grouped into four distinct profiles that ranged from low to high confidence in the use of DSS for agronomic decision‐making. Giving attention to farmer comfort/concern profiles allows for a more inclusive and better targeted engagement with farmers and potentially increase the adoption of PA. This knowledge can be vital for technology developers, policymakers, and extension services who are keen to promote PA usage among large‐, medium‐, and small‐scale farmers in the United States.
... Additionally, the management of water treatment will be enhanced by any improvement in consistent function of treatment processes. As the demand for increasingly refined operational management of drinking water plants grows, the potential of increasing the amount of data used in the operation system is being investigated to increase energy saving and reduce the consumption of chemical agents, increasing the quality and efficiency of the production process (Eggimann et al. 2017;Li et al. 2021a;Worm et al. 2010). Many water treatment plants still require the development of a dosing system to meet the effluent quality requirements, and excessive manual dosing is frequently used (Zhang 2005). ...
The increasing quantities of polluted waters are calling for advanced purification methods. Flocculation is an essential component of the water purification process, yet flocculation is commonly not optimal due to our poor understanding of the flocculation process. In particular, there is little knowledge on the mechanisms ruling the migration of pollutants during treatment. Here we have created the first tensor diagram, a mathematical framework for the flocculation process, analyzed its properties with a deep learning model, and developed a classification scheme for its relationship with pollutants. The tensor was constructed by combining pixel matrices from a variety of floc images, each with a particular flocculation period. Changing the factors used to make flocs images, such as coagulant dose and pH, resulted in tensors, which were used to generate matrices, that is the tensor diagram. Our deep learning algorithm employed a tensor diagram to identify pollution levels. Results show tensor map attributes with over 98% of sample images correctly classified. This approach offers potential to reduce the time delay of feedback from the flocculation process with deep learning categorization based on its clustering capabilities. The advantage of the tensor data from the flocculation process improves the efficiency and speed of response for commercial water treatment.
... Accessibility of the end-product is also highly dependent on the use of an enticing graphic user interface. Indeed, Worm et al. (2010) highlight that, when models are applied in a DSS, the distance between the models and the end-user increases. Therefore, the users will increasingly judge the system the more complex it is and base their appreciation on the quality of the user interface. ...
This PhD thesis aims consolidating, developing, and applying our knowledge on composting modelling, with the goal of providing accessible and usable information, tools, and perspectives for researchers and decision-makers alike. The hope is that the work developed throughout this dissertation can help in optimizing composting, notably by reducing greenhouse gas (GHG) emissions and improving nutrient recycling. As such, the thesis is divided into three phases: (1) phase 1 is a consolidation and development of the fundamentals of composting modelling, (2) followed by phase 2, where the modelling of nutrient loss and GHG emissions is investigated, (3) with phase 3 focusing on how to ensure that this work can be used by decision-makers.
In the first phase, a comprehensive and systematic review of the entirety of the literature on composting modelling was undertaken (chapter 2), seeking to provide a better understanding on the work that has been done and guidance on where future work should focus and how it should be approached. This review then raised some interesting questions regarding modelling approaches, notably regarding modelling of composting kinetics, which was studied in detail through the evaluation of current modelling approaches (chapter 3). Phase 2 then focused on the specific notions relating to GHG emissions and nutrient loss during composting, and how to model these phenomena. This section starts with a presentation of the experimental reactors and plan designed to monitor and evaluate the composting process (chapter 4), followed by the comprehensive composting model developed to accurately predict emissions and nutrient transformation during composting (chapter 5). Finally, phase 3 aimed to make this information easily and widely usable, especially for decision-makers. This started with a review on the best practices to develop models and decision support systems for environmental decision-making (chapter 6), followed by the development of novel simple kinetic modelling approaches (chapter 7), culminating with the development, calibration, and validation of a parsimonious composting model (chapter 8).
Through this work, a consolidated basis of the current state on composting modelling has been developed, followed-up by the exploration and development of both fundamental and applicable knowledge and tools.
... In addition to The Beer Game, there are more management games in the economic context in which researchers analyze the behavior of a group of people, as well as the participants learn from the experience [59][60][61][62][63][64][65]. Besides, the use of this type of simulations as a learning tool is usual in other contexts such as politics [49,66] and environmental care [67][68][69][70]. All these applications focus on management learning for general situations, and new concepts acquired by participants can be applied at any time in the real processes. ...
This paper presents the development of the first Management Flight Simulator of an Intensive Care Unit (ICU). It allows analyzing the physician decision-making related to the admission and discharge of patients and it can be used as a learning–training tool. The discrete event simulation model developed mimics real admission and discharge processes in ICUs, and it recreates the health status of the patients by using real clinical data (instead of using a single value for the length of stay). This flexible tool, which allows recreating ICUs with different characteristics (number of beds, type of patients that arrive, congestion level...), has been used and validated by ICU physicians and nurses of four hospitals. We show through preliminary results the variability among physicians in the decision-making concerning the dilemma of the last bed, which is dealt in a broad sense: it is not only about how the last available ICU bed is assigned but also about how the physician makes decisions about the admission and discharge of patients as the ICU is getting full. The simulator is freely available on the internet to be used by any interested user (https://emi-sstcdapp.unavarra.es/ICU-simulator).
... Indeed, Worm et al. (2010) highlight that, when models are applied in a DSS, the distance between the models and the end-user increases. Therefore, the users will increasingly judge the system the more complex it is and base their appreciation on the quality of the user interface. ...
Environmental decision support systems (EDSSs), or DSS applied in the environmental field, have been developed for over 40 years now. However, most of these tools fail to find use or fall out of use extremely quickly. In the aim of aiding in the conception and development of practical and successful decision support systems, i.e. systems that can lead to positive outcomes, this review looks over the existing literature, both EDSS-centric and from broader decision-related fields, to highlight some of the most important challenges influencing the success and usability of these systems. In all, 13 major challenges facing EDSS development were identified and over 60 recommendations and best practices were provided to address these challenges. Though this paper is mainly focused on environmental decision support systems, most of the highlighted information and conclusions are applicable to the development of decision support systems in any field.
... The goal of such quantification is to create a suite of realistic water quality scenarios that a treatment plant may experience. To estimate the performance of operating alternatives during such scenarios, several simulation models have been developed (Baxter et al. 1999;Harrington et al. 1992;Maier et al. 2004;Rietveld et al. 2010;Worm et al. 2010). Water managers, consultants, or operators can use simulation to test a range of plausible influent water quality scenarios and estimate which operating policies yield the best performance. ...
Understanding influent water quality variability is essential for the long-term planning of potable water systems. To quantify variability and generate realistic influent scenarios, we propose a nonparametric time series approach based on k-nearest neighbor (k-NN) bootstrap resampling. The k-NN approach resamples historical data conditioned on a “feature vector” at a given time to generate values at subsequent times. We modified this algorithm by adding random perturbations to the resampled values to generate realistic extremes unobserved in the historical record. k-NN is widely used in stochastic hydrology and hydroclimatology; however, it is adapted here for the multivariate, data-limited context of water treatment. To examine the performance of the algorithm, we applied it to an eleven-year, monthly water quality dataset of alkalinity, temperature, total organic carbon, and pH from the Cache la Poudre River in Colorado. We found that the k-NN simulations captured the relevant distributional statistics of the historical record, which suggests that the algorithm produces realistic and varied scenarios. When used in conjunction with modeling and optimization, these scenarios have the potential to improve the sustainability, resilience, and efficiency of potable water systems.
... Furthermore, the information provided should not be redundant, difficult to read, or irrelevant to the end-user. Regarding this, Worm and colleagues [122] investigated the direct link between the rate of acceptance of a DT and the overall design of the system. For example, presenting the outputs of a DT in quantitative terms, might lead to difficulties in the interpretation of the information. ...
The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.
... This way, the problems involved in the design of water distribution networks have different dimensions. The economic dimension of water distribution networks has been addressed considering aspects as cost of treatment intended for human consumption [11] or for sanitary use [12], cost of pipelines [13], maintenance of the network [14], pumping [15], efficiency in energy consumption [16], cost of utilities [17] and cost of extraction [18]. The environmental dimension has considered the life cycle assessment analysis [19], emissions generated by system [20] and reducing water losses [21]. ...
This paper presents a systematic approach to synthesize optimal water distribution networks (WDN) taking into account the water requirement of consumers based on a multi-stakeholder approach. A structural representation is developed to satisfy the water requirements of all users without taking into account water concessions in the region, but considering the depletion of groundwater and surface water, to generate an integral water distribution network. A rigorous mathematical formulation is developed as a mixed-integer linear programming model to transform the water distribution problem into an optimization task that seeks to minimize the overall cost of the water supply network. The proposed optimization model was applied to the Sonoran water scarcity problem from Mexico, where the optimal water distribution network was obtained, based on a multi-criteria approach taking into account the industrial, domestic and agricultural users. The obtained results show that the proposed model can satisfy economic, environmental and social aspects, where the distribution of water is equal for all users without affecting natural resources. Also, the results show economic advantages due to the sales of water.
... This way, the problems involved in the design of water distribution networks have different dimensions. The economic dimension of water distribution networks has been addressed considering aspects as cost of treatment intended for human consumption [11] or for sanitary use [12], cost of pipelines [13], maintenance of the network [14], pumping [15], efficiency in energy consumption [16], cost of utilities [17] and cost of extraction [18]. The environmental dimension has considered the life cycle assessment analysis [19], emissions generated by system [20] and reducing water losses [21]. ...
This paper presents an approach for designing power and water distribution networks involving the sizing, geographic location, as well as the economic, environmental and social impacts, and taking into account the multiplicity of criteria for the stakeholders involved in the development of operational policies and new facilities. In this paper is presented a method for defining solutions concerning to the design of power and water distribution networks based on a multi-stakeholder environment. A multi-objective model, considering economic, environmental and social factors, is used for illustrating how the different criteria, about priorities of the stakeholders, affect the design of the system and how to propose a solution for achieving a tradeoff between the multiple stakeholders. The proposed method was applied to an electric and water stressed scheme in the north of Mexico, the results show that the minimization of the dissatisfaction of the involved systems can provide an optimal solution that meets the objectives of all stakeholders.
... Le fonctionnement actuel traduit plusieurs déficiences : discontinuité de l'alimentation, taux de fuites important (60 %), vétusté des conduites… Epanet [19] est un modèle de calcul développé par l'Agence américaine de protection de l'environnement , il est choisi pour la simulation et la répar tition des vitesses et des pressions. Dans Epanet, les réseaux de distribution sont définis par des éléments tels que les noeuds, les conduites, les vannes et les réservoirs, etc. [20] [21]. Le réseau d'AEP du groupement urbain de Tlemcen a été modélisé dans sa totalité et un calage a été fait. ...
Ce travail consiste à modéliser le réseau d’alimentation en eau potable du groupement urbain de la ville de Tlemcen (GUT), Algérie, et à rechercher une approche de gestion de ce dernier via des outils d’investigation puissants que sont les systèmes d’information géographique (SIG). Le manque d’eau que subit ce groupement est dû non seulement à la conséquence de la sécheresse qu’a connue la ville cette dernière décennie, mais aussi à une gestion délicate et difficile du fait de l’utilisation d’outils d’investigation archaïques (archivage manuel, plans…). La tension relative à l’alimentation en eau potable qui règne actuellement ne cesse de croître avec le développement socio-économique, culturel et touristique du GUT, demandant une rationalisation de l’eau potable par crainte de voir s’instaurer un véritable souci pour son acquisition, si une politique d’anticipation, de planification et de contrôle ne suit pas. La croissance sociale dynamique conjuguée à la concentration de la population dans le centre urbain et à l’acuité des problèmes techniques liés à l’alimentation en eau confronte les gestionnaires avec la maîtrise de la gestion du réseau et les interpelle pour une meilleure exploitation, voire pour une optimisation via l’acquisition et l’utilisation d’outils modernes que sont les SIG. Pour l’amélioration de la connaissance du réseau, la détection et la compréhension des désordres pouvant s’y produire, la simulation de son fonctionnement, le dimensionnement des extensions, la prévision des branchements particuliers, la décision sur le choix de l’emplacement et les situations futures, seule la gestion à l’aide d’un système d’information géographique (SIG) pourra répondre à cette problématique. Dans un souci d’efficacité, un système d’information géographique est mis en place et couplé au modèle de simulation d’écou lement dans les réseaux de distribution « Epanet ». Des sous-programmes en langage MapBasic sont développés pour le couplage SIGEpanet. Les résultats sont prometteurs.
This work aims to model a drinking water network and to seek a management approach for this latter for the Tlemcen city Urban Grouping (UGT), Algeria, using geographic information systems (GIS). Water shortages experienced by this grouping are not only a consequence of the drought which has occurred in the city over the last decade, but also a delicate and difficult management issue due to the use of archaic investigative tools (manual archiving, plans…). The current pressure on water supply keeps on growing along with socio-economic, cultural and tourism development of UGT, requiring rationalization of drinking water for fear of seeing a genuine concern being established regarding its availability, in the case where a policy of anticipation, planning and control did not follow. Due to the growth coupled with the social dynamics of population concentration in the urban centre, together with acute technical problems related to water supply, operators are faced with network management control and the challenge of a better practice, or even optimization through the acquisition and use of modern tools such as GIS. To improve the knowledge of the network, as well as the detecting and understanding of disorders that occur there, the simulation of operations, the design of extensions, the prediction of private connections, the decisionmaking related to the location choice and future situations, only management using a geographic information system (GIS) is able to address this issue. In the interests of efficiency, a geographical information system is developed and coupled with “Epanet” simulation model of flow in distribution networks. MapBasic language subroutines are developed for coupling GIS-Epanet. Results are promising.
... This simple and robust automation is sub-optimal with respect to the performance of the treatment plant and energy efficiency (Bakker et al. 2003). In the meantime, there is an on-going trend towards the fully automated (centralized) operation of water supply systems (PWN 2006;Worm et al. 2010). When utilities implement modern centralized automatic control, they aim at reducing costs and, at the same time, improving the quality of the operations. ...
Conventional automatic production flow control and pump pressure control of water supply systems are robust and simple: production flow is controlled based on the level in the clear water reservoir and pump pressure is controlled on a static set-point. Recently, more advanced computer-based control methods were developed in which production flow is controlled by using a short-term water demand forecasting model and pressure is controlled by a dynamic pressure control module. To assess the differences between conventional and advanced control, we examined operational data of water treatment plantGruszczyn that supplies drinking water to a part of the city of Poznan, Poland. We compared two periods of three weeks of conventional and advanced control. The comparison showed that with advanced control the variation in the production flow was 83% lower, and the pump pressure of the clear water pumps was 29% lower. The lower pressure resulted in 20% less background leakage and the overall system's energy costs were 11.5% lower.
... Farmers generally require clear and concise information, and usually react unfavourably to the delivery of large amounts of redundant information (i.e., information not directly relevant to the producer decision-making process) (BCPC, 2000;Ascough et al., 2010). Worm et al. (2010) showed that the acceptance and appreciation of a DSS increases in accordance to the "look and feel" of the system. Historically, many DSSs have presented their outputs in quantitative terms, which growers find difficult to interpret. ...
The European Community Directive 128/2009 on the Sustainable Use of Pesticides establishes a strat-egy for the use of plant protection products (PPPs) in the European Community so as to reduce risks to human health and the environment. Integrated Pest Management (IPM) is a key component of this strategy, which will become mandatory in 2014. IPM is based on dynamic processes and requires decision-making at strategic, tactical, and operational levels. Relative to decision makers in conventional agricultural systems, decision makers in IPM systems require more knowledge and must deal with greater complexity. Different tools have been developed for supporting decision-making in plant disease control and include warning services, on-site devices, and decision support systems (DSSs). These decision-support tools operate at different spatial and time scales, are provided to users both by public and private sources, focus on different communication modes, and can support multiple op-tions for delivering information to farmers. Characteristics, weaknesses, and strengths of these tools are described in this review. Also described are recently developed DSSs, which are characterised by: i) holistic treatment of crop management problems (including pests, diseases, fertilisation, canopy management and irrigation); ii) conversion of complex decision processes into simple and easy-to-understand 'decision supports'; iii) easy and rapid access through the Internet; and iv) two-way communication between users and providers that make it possible to con-sider context-specific information. These DSSs are easy-to-use tools that perform complex tasks efficiently and effectively. The delivery of these DSSs via the Internet increases user accessibility, allows the DSSs to be updated easily and continuously (so that new knowledge can be rapidly and efficiently provided to farmers), and allows users to maintain close contact with providers.
... The hydraulic model included in the WaterSPOT simulator [4], [5] includes a full model of the treatment plant. The control of this model is done by the emulator. ...
In the drinking water industry process automation is commonly used, but the use of virtual commissioning (VC) has been low so far. Virtual commissioning has a beneficial effect by minimizing errors before and during implementing control in the actual plant. At PWN Watersupply Company North-Holland classic VC has been applied since 2010, yielding new control of a drinking water treatment plant. The new control is tested in a virtual environment before upload to the real plant's controllers. In this research the WaterSPOT simulator was used to connect a hydraulic model with the emulated process automation software. Relevant process values such as valve openings and pump speeds were transferred to the hydraulic model in the WaterSPOT simulator. Calculation results will be sent back to the process automation software. Advanced VC allows the testing of new control to be full-circle, i.e. simulation to the detail of the hydraulics of the plant. As a result time is saved during the SAT, less process disturbances occur and less failures are expected since more extreme situations can be tested using VC. Advanced VC at drinking water treatment plants is an industry first.
... There is an on-going trend towards the fully automated centralized operation of water supply systems (Worm et al., 2010;PWN, 2006). When utilities implement centralized automatic control, they aim to reduce costs and at the same time improve the quality of the operations or at least keep the same quality of operations executed by motivated operators. ...
Literature shows that water demand forecasting models which use water demand as single input, are capable of generating a fairly accurate forecast. However, at changing weather conditions the forecasting errors are quite large. In this paper three different forecasting models are studied: an Adaptive Heuristic model, a Transfer/-noise model, and a Multiple Linear Regression model. The performance of the models was studied both with and without using weather input, in order to assess the possible performance improvement due to using weather input. Simulations with the models showed that when using weather input the largest forecasting errors can be reduced by 11%, and the average errors by 7%. This reduction is important for the application of the forecasting model for the control of water supply systems and for anomaly detection.
... a Stimela water quality model and an EPANET hydraulic model Worm et al. (2010) 18 Release of toluene from a pipe -Discussed the potential and advantages of adopting a well-defined philosophy for the simulation of accidents in chemical plants. ...
An inevitable need for the skilled operators to increase the safety and productivity is not new to the chemical industry. Consequently, the training of operators is considered as a very important activity in the chemical industry. Conventional training methodologies are ineffective in training the operators for seldom-occurring perilous situations. The operator training simulator (OTS) is an alternative to train operators without actually endangering the plant and personnel. This contribution covers and discusses the need for OTS, applications of OTS in the chemical industry, issues related to OTS, salient features of a good OTS, commercial software packages used to build OTS, and training configurations. In this article, applications of OTS in the chemical industry reported in the open literature from 1990 to mid-2013 are also reviewed briefly. The review shows that OTS has been successfully used in many chemical industries. Finally, this article concludes by outlining the future directions. Overall, it provides a deeper understanding of many issues about the OTS to interested researchers, vendors, modeling engineers, and application engineers aiming to stimulate further developments in this area leading to improved OTS and their increased usage in the chemical industry.
... In order to increase the efficiency and stable water quality, Water supply companies are gradually changing to an advance centralized, fully automated operation [13],[14].The increasing demand of water treatment plants to require more efficient use of water resources, both in urban and rural environment [15]. The Nantong Penyao project was aimed to develop the conceptual design of an effective and economically responsible water purification plant for the municipality of Nantong [16]. ...
This paper presents technical communication of automation industry which describes the technical issues of
automation control system in operation development, improving management level and high efficiency process in water treatment system. Today’s water treatment plants are applied for water conservancy projects, emerged by the technology of automation control system is to ensure safe, continues, high quality water supply to municipal and for multi-purpose usage. Along with automation technology, computer technology, network communication development, advanced water treatment monitoring system is realized in Nantong pengyoa water purification plant. The Nantong pengyoa water purification plant has an important beneficial industry relationship to People’s Republic of China improving living status and environment condition mainly expounds the water supply, to build well-off society, comparatively improving the labor production growth & level of implementation of targets as well as high water quality requirements. In this paper, it develops the task and tells the technical solutions of water treatment plant which has been centralized in fully automated operation in some developed industries since many years. And also append short description of its current practices such as networking, and real-time monitoring control, composition & structure, process flow and automatic process control which are performed in water treatment plants to achieve high efficiency in quality of productivity.
... Hence, the Web-based platform with extendible real-time functions is quite eligible to provide online risk information management for decision support and hazard alert. Many approaches of integrated system were developed with computation tools to simulate the hydrological models and analyses for environmental monitoring (Foran et al. 2000; Causapé 2009; Xing et al. 2009; Worm et al. 2010). Furthermore, a flexible and expandable framework with Web interface would be more competitive to incorporate heterogeneous data. ...
... A clear and well constructed Graphical User Interface (GUI) that allows endusers without specific modelling skills or knowledge of the modelling system to take advantage of the DSS is likely to yield higher interest and usage among the farming community than a complex DSS that is essentially inaccessible to user groups. This has been effectively demonstrated for data management interfaces in the drinking water treatment sector (Worm et al., 2010) who noted that the acceptance and appreciation of a DSS is increasingly determined by the 'look and feel' of the system. The Taw study was not able to develop a GUI in the project timeframe but additional funds are being targeted specifically for this purpose. ...
Engagement with farmers and landowners is often undertaken by the research community to obtain information relating to typical land, livestock and enterprise management and generally centres on responses to questionnaire surveys. Farmers and land managers are constituted as expert observers of ground-level processes and provide diverse information on farming practices, enterprise economics and underpinning attitudes towards risk. Research projects designed to inform policy and practice may rely on such data to understand better on-the-ground decisions that can impact on environmental quality and the rural economy. Such approaches to eliciting local-level expert knowledge can generate large quantities of data from which to formulate rules relating to farm enterprise types. In turn, this can help to inform the structure of Decision Support Systems (DSS) and risk-based tools to determine farming practices likely to impact on environmental quality. However, in this paper we advocate the need for integrated farmer participation throughout the whole research process – from project inception through to community qualitative validation and legitimation - and thus not just for the elicitation of questionnaire responses. With farm questionnaire surveys being adopted widely by the research community, it is an opportune time to highlight a recent case study of the Taw catchment, Devon, UK. This serves as an example of co-construction of a DSS via a co-ordinated and integrated approach to expert elicitation with a farmer questionnaire survey as a central methodology. The aim of the paper is to detail the core aspects of an iterative cycle of participatory environmental management and DSS development for water quality protection and consider the multiple benefits of co-ordinated programmes of engagement with the farming community in this process.
... Hence, the Web-based platform with extendible real-time functions is quite eligible to provide online risk information management for decision support and hazard alert. Many approaches of integrated system were developed with computation tools to simulate the hydrological models and analyses for environmental monitoring (Foran et al. 2000; Causapé 2009; Xing et al. 2009; Worm et al. 2010). Furthermore, a flexible and expandable framework with Web interface would be more competitive to incorporate heterogeneous data. ...
The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.
In this study, an autoencoder-based molecular structure embedding model was developed to predict treatability of micropollutant in a drinking water treatment plant (DWTP) by machine learning using 69 micropollutants monitoring data at 18 DWTPs for three years. The molecular structure, which contains physicochemical characteristics, was embedded as a fixed-length vector that is advantageous for data-driven analysis and machine learning. First, the molecular structure of the micropollutants was converted to a sequence of tokens using the simplified molecular-input line-entry system (SMILES) pair encoding tokenizer, a frequency-based tokenization method. It was then compressed into fixed-length vectors using an autoencoder trained on various molecular structures within the Chemical Entities of Biological Interest. To validate the proposed models, a binary classification of micropollutant treatability was performed using the embedded molecular structure of micropollutants with various external features, such as concentration, season, and the presence of specific drinking water treatment processes by machine learning. The accuracy of the developed model for the 69 micropollutants in this study was 0.86, and the molecular structure was determined to be the most important feature. Furthermore, an accuracy of 0.71 was obtained in external validation for pharmaceuticals and personal care products that were not used for training. This shows that the proposed embedding vector can be generalized to unseen molecules during the training process, which means that it reflects the characteristics of the molecular structures.
Drinking Water Treatment Plants (DWTPs) face changes in raw water quality and treatment needs to be adjusted to produce the best water quality at the minimum environmental cost. An environmental decision support system (EDSS) was developed for aiding DWTP operators in choosing the adequate permanganate dosing rate in the pre-oxidation step. To this end, multiple linear regression (MLR) and multi-layer perceptron (MLP) models are compared for choosing the best predictive model. Besides, a case-based reasoning (CBR) model was approached to provide the user with a distribution of solutions given similar operating conditions in the past. The predictive model consisted of an MLP and has been validated against historical data with sufficient good accuracy for the utility needs (R2 = 0.76 and RSE = 0.13 mg·L−1). The integration of the predictive and the CBR models in an EDSS gives the user an augmented decision-making capacity of the process and has great potential for both assisting experienced users and for training new personnel in deciding the operational set-point of the process.
The relative accuracy of static and dynamic water treatment works (WTWs) models was examined. Case study data from an operational works were used to calibrate and verify these models. It was found that dynamic clarification, filtration and disinfection models were more accurate than static models at predicting the final water quality of an operational site but that the root mean square errors of the models were within 5% of each other for key performance criteria. A range of abstraction rates at which the WTWs was predicted to operate adequately were identified using both types of models for varying raw water qualities. Static clarification, filtration and disinfection models were identified as being more suitable for whole works optimisation than dynamic models based on their relative accuracy, simplicity and computational demands.
The scarcity of potable water increasing day by day. Rivers are the main source of land water for industry and agricultural activity. Unexpected transforms in river low reasoned by imminent tremendous events may enforce grave dilapidation on river water quality and significant impacts on ecosystems. The aim of these lessons is to determine the quality category of water in river and to help extract the key features and problems with the existing systems for water treatment. A number of quantitative models based on system, neural network, fuzzy logic, genetic algorithms, integrated models. Hybrid and many other feature selection techniques are being used in water analysis and treatment by decision-makers in WWTP (waste water treatment plants). It includes twenty five water quality parameters. Water quality is categorized into five levels based on the values of water quality index as Poor (WQI= 0 to 44, Marginal (WQI = 45 to 64), Fair (WQI = 65 to 79), Good (WQI = 80 to 94), and Excellent (WQI= 95 to100). The sensitivity The comparison of the various systems is done on the basis of datasets used for filtration the methodology applied and the platform on which the system is implemented. Thus this report reviews the various expert systems from 1995 to 2015 used for river water quality analysis and treatment.
This work aims to model a drinking water network and to seek a management approach for this latter for the Tlemcen city Urban Grouping (UGT), Algeria, using geographic information systems (GIS). Water shortages experienced by this grouping are not only a consequence of the drought which has occurred in the city over the last decade, but also a delicate and difficult management issue due to the use of archaic investigative tools Imanual archiving, plans⋯). The current pressure on water supply keeps on growing along with socio-economic, cultural and tourism development of UGT, requiring rationalization of drinking water for fear of seeing a genuine concern being established regarding its availability, in the case where a policy of anticipation, planning and control did not follow. Due to the growth coupled with the social dynamics of population concentration in the urban centre, together with acute technical problems related to water supply, operators are faced with network management control and the challenge of a better practice, or even optimization through the acquisition and use of modern tools such as GIS. To improve the knowledge of the network, as well as the detecting and understanding of disorders that occur there, the simulation of operations, the design of extensions, the prediction of private connections, the decisionmaking related to the location choice and future situations, only management using a geographic information system (GIS) is able to address this issue. In the interests of efficiency, a geographical information system is developed and coupled with "Epanet" simulation model of flow in distribution networks. MapBasic language subroutines are developed for coupling GIS-Epanet. Results are promising.
This research deals with the contribution of process simulation models to the factory acceptance test (FAT) of process automation (PA) software of drinking water treatment plants. Two test teams tested the same piece of modified PA-software. One team used an advanced virtual commissioning (AVC) system consisting of PA-emulation and integrated process simulation models. The other team used the same PA-emulation but basic parameter relations instead of the process simulation models, the virtual commissioning (VC) system. Each test team found one (different) error of the 13 errors put into the software prior to the experiment; most of the errors were found prior to the functional test. The team using the AVC-system found three errors, the team using the VC-system found four, but the AVC-team judged 1% of the test items 'not possible', the VC-team 17%. It was concluded that the hypothesis that with AVC more errors could be found than with VC could not be accepted. So, for the FAT of PA-software of drinking water treatment plants, the addition of basic parameter relations to PA-emulation was sufficient. It was not the exact process behavior that helped to find errors, but the passing of process thresholds.
Waterspot is a plant-wide drinking water treatment simulator that has been developed in a 3 year research project. The incorporation of real-time and historical data of on-line water quality measurements, flow measurements, process data and water quality laboratory measurements in the simulator improves the acceptance of model output by technologists, ensures a more realistic training of operators and shows the potential of detecting deviations from the expected water quality and control of the plant. The optimal position of the simulator in the automation architecture was found to be on the process information management system (PIMS) network.
Pipe bursts in a drinking water distribution system lead to water losses, interruption of supply, and damage to streets and houses due to the uncontrolled water flow. To minimize the negative consequences of pipe bursts, an early detection is necessary. This paper describes a heuristic burst detection method, which continuously compares measured and expected values of water demands and pressures. The expected values of the water demand are generated by an adaptive water demand forecasting model, and the expected values of the pressures are generated by a dynamic pressure drop - demand relation estimator. The method was tested off-line on a historic dataset of 5 years of water flow and pressure data in three supply areas (with 650, 11,180 and 130,920 connections) in the western part of the Netherlands. In the period 274 bursts were reported of which, based on the definition we propose in this paper, 38 were considered as relatively larger bursts. The method was able to detect 50, 25.9 and 7.8% in the considered areas related to all bursts, and around 80% in all three areas related to the subset of relatively larger bursts. The method generated false alarms on 3% of the evaluated days on average.
This research aims at developing anoperator training simulator (OTS) using AspenOTS Frameworkfor fatty acid methyl ester (FAME) production plant. All over the world, there is an increasing interest towards the use of vegetable oils in much desired eco-friendly biodiesel production. In view of environmental concerns due to high polluting nature of fossil fuels and also because of the limited availability of non-renewable energy sources e.g. fossil fuels, biodiesel is seen as a future fuel alternative. In order to improve the process efficiency and hence the profitability with the satisfaction of environmental concerns, in-depth analysis of process is inevitable. Simulation provides a platform to study and analyse the process in detail. In addition, safety and productivity in the plant is mainly dependant on the ability of the operators to deal with emergency situations in the running plant. Therefore, the training of operators is a tremendously important activity in the chemical industry to avoid accidental hazards in the plant. In present contribution, a steady state and dynamic simulator has been developed using Aspen Plus7.3 and Aspen Plus Dynamics 7.3. Subsequently, a high fidelity operator training simulator that can be used to explore normal and emergency conditions, is developed using Aspen OTS Framework.
Water treatment plants are in general robust and designs are based on the performance of individual processes with pre-set boundary conditions. It is assumed that an integral approach of the entire treatment plant can lead to more efficient operation. Taking into account the developments in sensoring, automation and computation, it is a challenge to improve quality and reliability of the treatment plants and to make maximal use of the installed infrastructure, postponing new investments.
At Amsterdam Water Supply (AWS), the first steps have been taken to come to an integral dynamic model of the total water treatment plant and the use of this model as an instrument for integral control. The parameters influencing the performance of the water treatment process will be incorporated in an overall model evaluating the goal factors quality (good, constant and reliable), quantity, costs, environmental impact (low residuals level), redundancy and flexibility. For several individual processes at AWS models have already been developed during the last few years, like models for the ozone process, biological activated carbon filtration and pellet softening. For the final calibration and validation pilot reactors are automated and on-line data are collected. Criteria for evaluation are developed to realise an optimal control of the individual processes in interaction with the goal factors of the total treatment process.
To extend two previous surveys of specific decision support system (DSS) applications over the period (January 1971-December 1994), we have conducted a follow-up survey covering the period between 1995 and 2001. A total of 210 published applications are identified. To examine the development pattern of a specific DSS over time, we analysed and summarized the survey results according to (1) the area of application, (2) the year of publication in each area of application, (3) the distribution of underlying tools in DSSs, (4) a classification based on Alter's taxonomy, and (5) the management level (operational, tactical, or strategic) for which the DSS was designed.Journal of the Operational Research Society (2006) 57, 1264-1278. doi:10.1057/palgrave.jors.2602140 Published online 28 December 2005
Development of environmental decision support systems (EDSS) is rapidly progressing. The sustainable management of natural resources has a growing research focus as the awareness of the complexity of interactions between socio-cultural, economical and biophysical system components is increasingly acknowledged. As better data and methods become available, the complexity of the system representation is augmenting. At the same time realism and relevance are increasing and allowing direct support for management and policy development. This article gives the background of recent developments in EDSS and summarises a selected set of papers that were presented at the 2nd Biennial Conference of the International Society of Environmental Modelling and Software (IEMSS 2004). Recent developments show a continuum between integrated assessment modelling and EDSS with varying levels of stakeholder participation in both EDSS development and application. There is a general tendency towards better utilisation of interdisciplinary data, integration and visualisation of temporal and spatial results. Future developments appear directed towards better representation of reality in models, improving user-friendliness and use in a negotiation or group discussion context.
The flow through a unit of a drinking water treatment plant is one of the most important parameters in terms of a unit's effectiveness. In the present paper, a new EPAnet library is presented with the typical hydraulic elements for drinking water treatment processes well abstraction, rapid sand filtration and cascade and tower aeration. Using this treatment step library, a hydraulic model was set up, calibrated and validated for the drinking water treatment plant Harderbroek. With the actual valve position and pump speeds, the flows were calculated through the several treatment steps. A case shows the use of the model to calculate the new setpoints for the current frequency converters of the effluent pumps during a filter backwash.
Major emphasis must be laid on guaranteeing high standards in drinking water quality. This can only be achieved when the drinking water treatment plant operates optimally. In this paper a treatment plant, consisting of ozonation with low dosage of ozone, pellet softening, pH correction and activated carbon filtration, treating lake water with high content of natural organic matter is analysed. Models are developed to describe the processes under changing conditions. For integrated modelling interaction of the treatment steps is considered to take place through the water stream. Water quality parameters are influenced by preceding treatment steps and they determine the performance of the following treatment steps. Assuming that disinfection is sufficient in the treatment plant and suspended and colloidal solids are sufficiently removed in preceding steps, the main controlled parameters for a treatment plant are chemical stability (saturation index SI), biological stability (assimilable organic carbon AOC), disinfection by-products (bromate) and organic micro-pollutants (pesticides). It is concluded that with good use of the by-pass of a pellet softening reactor and with optimised operation of the fluidised bed, the dosage of chemicals can be minimised, resulting in reduction of costs, environmental emissions and maintenance. Ozonation has a key role in the biostability and the toxicity of the drinking water. When ozone is only applied for oxidation (low dosages) some organic micro-pollutants are reduced and the run-time of the activated carbon filters is prolonged. However, ozonation decreases the bio-stability of the drinking water and enhances bromate formation. Therefore, the quality benefits related to oxidation of organic micro-pollutants should be weighted against the formation of bromate and AOC. The increase of AOC concentrations should be compensated by longer contact times in the biological filters.
Towards the twenty-first century, there will be more changes in water treatment practice than that which have occurred during the entire twentieth century. The change will be likely driven by continuing development of technology, public concern, and tougher regulations.
Management issues in many sectors of society demand integrated analysis that can be supported by integrated modelling. Since all-inclusive modelling software is difficult to achieve, and possibly even undesirable, integrated modelling requires the linkage of individual models or model components that address specific domains. Emerging from the water sector the OpenMI has, been developed with the purpose of being the glue that can link together model components from various origins. The OPenMI Provides a standardized interface to define, describe and transfer data on a time basis between software components that run simultaneously, thus supporting systems where feedback between the modelled processes is necessary in order to achieve physically sound results. The OpenMI allows the linking of models with different spatial and temporal representations: for example, linking river models and groundwater models, where the river model typically uses a one-dimensional grid and a short timestep and the groundwater model uses a two- or three-dimensional grid and a longer timestep. The OpenMI is designed to accommodate the easy migration of existing modelling systems, since their re-implementation may not be economically feasible due to the large investments that have been put into the development and testing of these systems.
Experimental research was carried out for calibration and validation of a model describing ozone decay and ozone exposure (CT), decrease in UV absorbance at 254 nm (UVA254), increase in assimilable organic carbon concentration and bromate formation. The model proved to be able to predict these parameters on the basis of the applied ozone dosage. The experimental ozone dosages ranged from 0.4 mg-O3/L to 0.9 mg-O3/L for natural water with a dissolved organic carbon concentration of 2.4 mg-C/L. The UVA254 was found to be an effective parameter for estimation of rapid ozone decay for natural water under experimental conditions tested. The experimental setup consisted of a bench-scale plug flow reactor (approximately 100 L/h) with dissolved ozone dosing.
Multiple fluidised bed reactors for water softening (crystallisation of calcium carbonate) have been in operation at drinking water treatment plants since the late 1980s. Research on the operation of these pellet reactors has been focussed on investigating crystallisation under constant fluidised bed composition. However, in practice the bed composition varies frequently, despite large effort of plant operators. An improvement in the control of the fluidised bed can be achieved by using model-based multivariable control. Due to the nonlinear behaviour of the reactor, caused by water temperature variation during the year, a nonlinear control approach is used. A particle filter, based on a first-principles model, estimates the state of the softening reactor and a nonlinear model-predictive controller determines the values of the manipulated variables. We show in a simulation experiment, that it is possible to keep the reactor at desired operational parameters (pellet size and bed height) under varying operational conditions. In this way, the cost of pellet softening can be reduced and irregularities prevented.
Drinking water production plants (in The Netherlands) are normally controlled by effluent quality. When the effluent quality does not meet the guidelines, the treatment process is manipulated. This is mainly done using the experience of the operators. Water quality models can be used to support the operators' task by off-line process evaluation and model predictive control (MPC).
Stimela is a modelling environment that is developed by DHV Water BV and the Delft University of Technology. It is especially designed for water quality modelling. An example of off-line use of Stimela for operation and design is given by a model of a counter-current packed tower aerator.
In the near future Stimela will be used for MPC. Therefore DHV Water BV and the Delft University of Technology are starting a project with water companies in which MPC with Stimela will be applied. In this project internet technology will be used to access water quality data from online measurements and form the model calculations. The data can be used by operators when they are at other locations, by drinking water technologists at the office to analyse specific problems, and by the management for weekly, monthly and yearly reports. In this way all the data are available for everyone in the organisation, from the operator to the managing director.
In Norway one of the largest Liquid Natural Gas (LNG) plants worldwide is under construction (Hammerfest, Natural gas field Snøhvit). The control and automation of the plant is done with the digital control system (DCS) "800xA Extended Automation" manufactured by ABB. The complexity of the plant is very high and additionally some processes were newly introduced. That is why it was decided to perform the testing, training and virtual commissioning with a high fidelity simulator. The simulator used consists of a process simulator manufactured by Kongsberg Process Simulation, Sandvika (formerly Fantoft) and an emulator of the AC 870P/Melody system which is the active control part of 800xA. The original human system interface is used so that an overall test of the complete system is achieved. One of the various challenges of this project is that the engineering, testing (virtual commissioning) and operator training is done simultaneously in different places in Norway: the engineering is done in the facilities in Bergen, testing is done in Oslo, training is performed in Hammerfest. Measures had to be taken to ensure the integrity of the data involved.
This paper presents the mathematical basis and some illustrative examples of a model-based decision-making method for the automatic calculation of optimum design parameters in modern Wastewater Treatment Plants (WWTP). The starting point of the proposed methodology is the mathematical modelling of the main processes inside a plant's units. The procedure for the automatic calculation of the design parameters is then based on expressing the optimum WWTP design problem as a Mathematical Programming (Optimisation) Problem that can be solved using a non-linear optimisation algorithm (GRG2). The paper shows how the proposed methodology is able to achieve optimum WWTP design using either a steady-state or dynamic mathematical model of the plant and a set of constraints associated with the permitted operational ranges and the required water quality in the effluent. As an illustrative example to show the usefulness of the proposed methodology, the optimum design of the Step-Feed process for nitrogen removal (Alpha) has been analysed by considering two different problems: the optimum plant dimensions, estimated at critical temperature for effluent requirements (Problem 1), and the optimum selection of facultative volumes, fractions of the influent flow-rate and the values of oxygen set-points for long-term plant operation (Problem 2). The proposed decision-making method is intended to facilitate the task of the engineers involved in the design of new WWTP, especially when the complexity of the plant requires a systematic procedure for the selection of the main design parameters.
In recent years, pressure has increased on environmental scientist/modellers to both undertake good science in an efficient and timely manner, under increasing resource constraints, and also to ensure that the science being performed is immediately relevant to a particular environmental management context. At the same time, environmental management is changing, with increasing requirements for multi-scale and multi-objective assessment and decision making that considers economic and social systems, as well as the ecosystem. Integration of management activities, and also of the modelling undertaken to support management, has become a high priority. To solve the problems of application and integration, knowledge encapsulation in models is being undertaken in a way that both meets the needs for good science, and also provides the conceptual and technical structures required for broader and more integrated application of that knowledge by managers. To support this modelling, tools and technologies from computer science and software engineering are being transferred to applied environmental science fields, and a range of new modelling and software development approaches are being pursued. The papers in this Special Issue provide examples of the integrated modelling concepts and applications that have been, or are being, developed. These include the use of object-oriented concepts, component-based modelling techniques and modelling frameworks, as well as the emerging use of integrated modelling platforms and metadata support for modelling semantics. This paper provides an overview of the science and management imperatives underlying recent developments, discusses the technological and conceptual developments that have taken place, and highlights some of the semantic, operational and process requirements that need to be addressed now that the technological aspects of integrated modelling are well advanced.
Planners, policy-makers and their technicians have the difficult task to intervene in complex human-natural systems. It is not enough for them to focus on individual processes; rather it is necessary to address the system as a complex integral whole. In the given circumstances, integrated models as part of Policy Support Systems (PSS) can provide support. The MedAction PSS incorporates socio-economic and physical processes in a strongly coupled manner. It is implemented with the GEONAMICA® application framework and is intended to support planning and policy making in the fields of land degradation, desertification, water management and sustainable farming. The objective of this paper is to provide some insight in the individual models, the model integration achieved, as well as the actual use of the MedAction PSS. For the latter an application example is developed. The paper also argues that technical and scientific aspects of Policy Support Systems are not the sole elements deciding on their use in practice and concludes with some lessons learned during the development and use of the MedAction PSS and similar systems.
Simulation for virtual commissioning
- R Schumann
- M Hoyer
- G C Premier
Schumann, R., Hoyer, M., Premier, G.C., 2007. Simulation for virtual commissioning. Eurosim conference, Ljubljana, Slovenia.