Primodal Inc.

Hamilton, Canada

Primodal Inc.

Hamilton, Canada

Time filter

Source Type

Choubert J.-M.,IRSTEA | Rieger L.,EnviroSim Associates Ltd | Shaw A.,Black and Veatch Corporation | Copp J.,Primodal Inc. | And 7 more authors.
Water Science and Technology | Year: 2013

Increasingly stringent effluent limits and an expanding scope of model system boundaries beyond activated sludge has led to new modelling objectives and consequently to new and often more detailed modelling concepts. Nearly three decades after the publication of Activated Sludge Model No1 (ASM1), the authors believe it is time to re-evaluate wastewater characterisation procedures and targets. The present position paper gives a brief overview of state-of-the-art methods and discusses newly developed measurement techniques on a conceptual level. Potential future paths are presented including on-line instrumentation, promising measuring techniques, and mathematical solutions to fractionation problems. This is accompanied by a discussion on standardisation needs to increase modelling efficiency in our industry. © IWA Publishing 2013.


Olsson G.,Lund University | Carlsson B.,Uppsala University | Comas J.,University of Girona | Copp J.,Primodal Inc. | And 12 more authors.
Water Science and Technology | Year: 2014

Key developments of instrumentation, control and automation (ICA) applications in wastewater systems during the past 40 years are highlighted in this paper. From the first ICA conference in 1973 through to today there has been a tremendous increase in the understanding of the processes, instrumentation, computer systems and control theory. However, many developments have not been addressed here, such as sewer control, drinking water treatment and water distribution control. It is hoped that this review can stimulate new attempts to more effectively apply control and automation in water systems in the coming years. © IWA Publishing 2014.


Jeppsson U.,Lund University | Alex J.,Ifak e.V. Magdeburg | Batstone D.J.,University of Queensland | Benedetti L.,WaterWays | And 15 more authors.
Water Science and Technology | Year: 2013

As the work of the IWA Task Group on Benchmarking of Control Strategies for wastewater treatment plants (WWTPs) is coming to an end, it is essential to disseminate the knowledge gained. For this reason, all authors of the IWA Scientific and Technical Report on benchmarking have come together to provide their insights, highlighting areas where knowledge may still be deficient and where new opportunities are emerging, and to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The paper focuses on the topics of temporal and spatial extension, process modifications within the WWTP, the realism of models, control strategy extensions and the potential for new evaluation tools within the existing benchmark system. We find that there are major opportunities for application within all of these areas, either from existing work already being done within the context of the benchmarking simulation models (BSMs) or applicable work in the wider literature. Of key importance is increasing capability, usability and transparency of the BSM package while avoiding unnecessary complexity. © IWA Publishing 2013.


Nopens I.,Ghent University | Benedetti L.,Ghent University | Jeppsson U.,Lund University | Pons M.-N.,French National Center for Scientific Research | And 6 more authors.
Water Science and Technology | Year: 2010

The COST/IWA Benchmark Simulation Model No 1 (BSM1) has been available for almost a decade. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the research work related to the benchmark simulation models has resulted in more than 300 publications worldwide demonstrates the interest in and need of such tools within the research community. Recent efforts within the IWA Task Group on "Benchmarking of control strategies for WWTPs" have focused on an extension of the benchmark simulation model. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pretreatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In this paper, the finalised plant layout is summarised and, as was done for BSM1, a default control strategy is proposed. A demonstration of how BSM2 can be used to evaluate control strategies is also given. © IWA Publishing 2010.


Benedetti L.,WaterWays | Belia E.,Primodal Inc. | Cierkens K.,Ghent University | Flameling T.,Waterschap de Dommel | And 3 more authors.
Water Science and Technology | Year: 2013

This paper illustrates how a dynamic model can be used to evaluate a plant upgrade on the basis of post-upgrade performance data. The case study is that of the Eindhoven wastewater treatment plant upgrade completed in 2006. As a first step, the design process based on a static model was thoroughly analyzed and the choices regarding variability and uncertainty (i.e. safety factors) were made explicit. This involved the interpretation of the design guidelines and other assumptions made by the engineers. As a second step, a (calibrated) dynamic model of the plant was set up, able to reproduce the anticipated variability (duration and frequency). The third step was to define probability density functions for the parameters assumed to be uncertain, and propagate that uncertainty with the dynamic model by means of Monte Carlo simulations. The last step was the statistical evaluation and interpretation of the simulation results. This work should be regarded as a 'learning exercise' increasing the understanding of how and to what extent variability and uncertainty are currently incorporated in design guidelines used in practice and how model-based post-project appraisals could be performed. Copyright © IWA Publishing 2013 Water Science and Technology.


Copp J.B.,Primodal Inc. | Belia E.,Primodal U.S. Inc. | Hubner C.,Institute fur Automation und Kommunikation E.V. Magdeburg Ifak | Vanrolleghem P.,Laval University | Rieger L.,Laval University
2010 IEEE International Conference on Automation Science and Engineering, CASE 2010 | Year: 2010

The implementations of water quality monitoring networks have a number of inherent engineering challenges and the automation of the data collection and analysis only adds to that complexity. This paper has been written to discuss the challenges and solutions that have been developed within the framework of an industrial/academic partnership. Water quality monitoring stations are important tools in the area of environmental water science; however, traditional monitoring station installations and their maintenance tend to require more effort than desirable. Common sensors are not easily integrated into fieldbus systems and the lack of storable meta data (status, calibration information, location,...) available from sensor devices in this field, requires additional effort on the part of the owner if a fully utilizable database of meaningful values is to be constructed. An approach is proposed to automate this effort by providing an electronic catalog of predefined devices that can be input by the user during setup or read from the sensor in real-time. Automated data evaluation, alarm triggering and real-time data 'correction' are all being developed with an aim to create fully documented long-term databases of usable and meaningful water quality data. And finally, to initiate improvements in the area of monitoring automation, some thoughts on the future of advanced fieldbus systems are presented. © 2010 IEEE.


Talebizadeh M.,Laval University | Belia E.,Primodal Inc. | Vanrolleghem P.A.,Laval University
Environmental Modelling and Software | Year: 2016

The availability of influent wastewater time series is crucial when using models to assess the performance of a wastewater treatment plant (WWTP) under dynamic flow and loading conditions. Given the difficulty of collecting sufficient data, synthetic generation could be the only option. In this paper a hybrid of statistical (a Markov chain-gamma model for stochastic generation of rainfall and two different multivariate autoregressive models for stochastic generation of air temperature and influent time series in dry conditions) and conceptual modeling techniques is proposed for synthetic generation of influent time series. The time series of rainfall and influent in dry weather conditions are generated using two types of statistical models. These two time series serve as inputs to a conceptual sewer model for generation of influent time series. The application of the proposed influent generator to the Eindhoven WWTP shows that it is a powerful tool for realistic generation of influent time series and is well-suited for probabilistic design of WWTPs as it considers both the effect of input variability and total model uncertainty. © 2015 Elsevier Ltd.


Alferes J.,Laval University | Tik S.,Laval University | Copp J.,Primodal Inc. | Vanrolleghem P.A.,Laval University
Water Science and Technology | Year: 2013

In situ continuous monitoring at high frequency is used to collect water quality information about water bodies. However, it is crucial that the collected data be evaluated and validated for the appropriate interpretation of the data so as to ensure that the monitoring programme is effective. Software tools for data quality assessment with a practical orientation are proposed. As water quality data often contain redundant information, multivariate methods can be used to detect correlations, pertinent information among variables and to identify multiple sensor faults. While principal component analysis can be used to reduce the dimensionality of the original variable data set, monitoring of some statistical metrics and their violation of confidence limits can be used to detect faulty or abnormal data and can help the user apply corrective action(s). The developed algorithms are illustrated with automated monitoring systems installed in an urban river and at the inlet of a wastewater treatment plant. © 2013 IWA Publishing.


Talebizadeh M.,Laval University | Belia E.,Primodal Inc. | Vanrolleghem P.A.,Laval University
Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014 | Year: 2014

The primary goal of wastewater treatment plants (WWTPs) is to remove pollutants from wastewaters so as to reach a set of effluent standards under a set of environmental, cost, and regulatory constraints. To design a WWTP according to these criteria, design engineers usually make the initial sizing of the plant using design guidelines or a set of modeling tools under steady-state conditions. In these approaches the effect of different sources of uncertainties are taken into account in an implicit manner through the application of safety factors and/or selection of conservative design values for design inputs. In this study, the application of a set of statistical and process-based dynamic modeling tools is proposed to explicitly characterize the uncertainty/variability in the input time series and model parameters and propagate these into the uncertainty in the model outputs (i.e. effluent wastewater composition and costs). Depending on the effluent standards the probability of non-compliance (PONC) to the effluent standards can be calculated. The proposed probabilistic methodology provides the design engineers with a concerted framework to utilize and incorporate into the design of WWTPs the available and future information on the characteristics of the sewershed and the climate conditions, as well as the latest advances in dynamic modeling. Moreover, the calculated PONC can be used as an objective criterion for comparing different design alternatives and help designers avoid the application of overly-conservative safety factors.

Loading Primodal Inc. collaborators
Loading Primodal Inc. collaborators