5,596 research outputs found

    MatSWMM - An open-source toolbox for designing real-time control of urban drainage systems

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    This manuscript describes the MatSWMM toolbox, an open-source Matlab, Python, and LabVIEW-based software package for the analysis and design of real-time control (RTC) strategies in urban drainage systems (UDS). MatSWMM includes control-oriented models of UDS, and the storm water management model (SWMM) of the US Environmental Protection Agency (EPA), as well as systematic-system edition functionalities. Furthermore, MatSWMM is also provided with a population-dynamics-based controller for UDS with three of the fundamental dynamics, i.e., the Smith, projection, and replicator dynamics. The simulation algorithm, and a detailed description of the features of MatSWMM are presented in this manuscript in order to illustrate the capabilities that the tool has for educational and research purposes.Peer ReviewedPostprint (author's final draft

    Optimizing intermittent water supply in urban pipe distribution networks

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    In many urban areas of the developing world, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. Here, we develop a computational model of transition, transient pipe flow in a network, accounting for a wide variety of realistic boundary conditions. We validate the model against several published data sets, and demonstrate its use on a real pipe network. The model is extended to consider several optimization problems motivated by realistic scenarios. We demonstrate how to infer water flow in a small pipe network from a single pressure sensor, and show how to control water inflow to minimize damaging pressure gradients

    Genetic algorithm design of neural network and fuzzy logic controllers

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    Genetic algorithm design of neural network and fuzzy logic controller

    Modelling sewer discharge via displacement of manhole covers during flood events using 1D/2D SIPSON/P-DWave dual drainage simulations

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    This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recordIn urban areas, overloaded sewers may result in surcharge that causes surface flooding. The overflow from sewer systems mainly starts at the inlets until the pressure head in the manhole is high enough to lift up its cover, at which stage the surcharged flow may be discharged via the gap between the bottom of the manhole cover and the ground surface. In this paper, we propose a new approach to simulate such a dynamic between the sewer and the surface flow in coupled surface and sewer flow modelling. Two case studies are employed to demonstrate the differences between the new linking model and the traditional model that simplifies the process. The results show that the new approach is capable of describing the physical phenomena when manhole covers restrict the drainage flow from the surface to the sewer network and reduce the surcharge flow and vice versa.DFG (Deutsche Forschungsgemeinschaft

    Doctor of Philosophy

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    dissertationControlling combined sewer overflows (CSOs) is one of the greatest urban drainage challenges in more than 700 communities in the United States. Traditional drainage design typically leads to centralized, costly and energy-intensive infrastructure solutions. Recently, however, application of decentralized techniques to reduce the costs and environmental impacts is gaining popularity. Rainwater harvesting (RWH) is a decentralized technique being used more often today, but its sustainability evaluation has been limited to a building scale, without considering hydrologic implications at the watershed scale. Therefore, the goal of this research is to study watershed-scale life cycle effects of RWH on controlling CSOs. To achieve this goal, (i) the life cycle costs (LCC) and long-term hydrologic performance are combined to evaluate the cost-effectiveness of control plans, (ii) the life cycle assessment (LCA) and hydrologic analysis were integrated into a framework to evaluate environmental sustainability of control plans, and (iii) the major sources of uncertainty in the integrated framework with relative impacts were identified and quantified, respectively. A case study of the City of Toledo, Ohio serves as the platform to investigate these approaches and to compare RWH with centralized infrastructure strategies. LCC evaluation shows that incorporating RWH into centralized control plans could noticeably improve the cost-effectiveness over the life cycle of drainage infrastructure. According to the results of the integrated framework, incorporating RWH could reduce Eco-toxicity Water (ETW) impacts, but caused an increase in the Global Warming Potential (GWP). In fact, incorporating RWH contributes to avoidance of untreated discharges into water bodies (thus reducing ETW) and additional combined sewage delivered to treatment facilities (thus increasing GWP). The uncertainty analysis suggests that rainfall data (as a hydrologic parameter) could be a significant source of the uncertainty in outputs of the integrated framework. Conversely, parameters of LCIA (life cycle impact assessment) could have trivial impacts on the outputs. This supports the need for robust hydrologic data and associated analyses to increase the reliability of LCA-based urban drainage design. In addition, results suggest that such an uncertainty analysis is capable of rendering optimal RWH system capacity as a function of annual rainfall depth to lead to minimized life cycle impacts. Capacities smaller than the optimal size would likely result in loss of RWH potable water savings and CSO control benefits, while capacities larger than optimal would probably incur excessive wastewater treatment burden and construction phase impacts

    Report and papers with guidelines on calibration of urban flood models

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    Computer modelling offers a sound scientific framework for well-structured analysis and management of urban drainage systems and flooding. Computer models are tools that are expected to simulate the behaviour of the modelled real system with a reasonable level of accuracy. Assurance of accurate representation of reality by a model is obtained through the model calibration. Model calibration is an essential step in modelling. This report present concepts and procedures for calibration and verification of urban flood models. The various stages in the calibration process are presented sequentially. For each stage, a discussion of general concepts is followed by descriptions of process elements. Finally, examples and experiences regarding application of the procedures in the CORFU Barcelona Case Study are presented. Calibration involves not only the adjustment of model parameters but also other activities such as model structural and functional validation, data checking and preparation, sensitivity analysis and model verification, that support and fortify the calibration process as a whole. The objective in calibration is the minimization of differences between model simulated results and observed measurements. This is normally achieved through a manual iterative parameter adjustment process but automatic calibration routines are also available, and combination parameter adjustment methods also exist. The focus of a model calibration exercise is not the same for all types of models. But regardless of the model type, good modelling practice should involve thorough model verification before application. A well-calibrated model can give the assurance that, at least for a range of tested conditions, the model behaves like the real system, and that the model is an accurate and reliable tool that may be used for further analysis. However, calibration could also reveal that the model cannot be calibrated and that the correctness of the model and its suitability as a tool for analysis and management of real-world systems could not be proven. The conceptualisation and simplification of real-world systems and associated processes in modelling inevitably lead to errors and uncertainty. Various modelling components introduce errors such as the input parameters, the model concept, scheme and corresponding model output, and the observed response measurements. Ultimately, the quality of the model as quantified by how much it deviates from reality is an aggregate of the errors that have been brought into it during the modelling process. Thus, it is important to identify the different error sources in a model and also account for and quantify them as part of the modelling.The work described in this publication was supported by the European Community’s Seventh Framework Programme through the grant to the budget of CORFU Collaborative Research on Flood Resilience in Urban Areas, Contract 244047

    Coupled, Data-Driven, and Real-Time Modeling and Control of Sewer Systems and Water Resource Recovery Facilities

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    Within the urban water cycle, the challenges posed in the operation of combined sewer systems include changing storms, evolving regulations, and impacts to environmental health. While building bigger infrastructure is one way to solve issues such as sewer overflows, budgetary constraints and increasing stresses to the system, such as climate change, limit the feasibility of this option for many communities and utilities. One alternative is posed by an increasing availability of sensors and data algorithms. Rather than building bigger, the use of real-time data and remote actuation provides a new avenue to autonomously adapt performance of the entire existing system. While promising, there are outstanding knowledge gaps that must be closed to bring the idea of smart wastewater systems to fruition. 1.) Sewer systems are highly dynamic and spatially heterogeneous. Thus a static, one-size-fits-all modeling approach will not accurately reflect the real-world system. This dissertation addresses this by presenting a data-driven toolchain that learns from historical sensor measurements to estimate current and future combined sewer conditions. By evaluating this toolchain on sensor data collected across the Detroit combined sewer network, it is discovered that wastewater and stormwater flow components exhibit distinct spatial and temporal variation, underscoring the importance of flexible re-calibration using the most relevant window of data. 2.) The efficacy and feasibility of real-time control across the sewershed poses a number of challenges. In particular, objectives for control across the scale of a city often force trade-offs between flood reduction and water quality; without informing control decisions based on these trade-offs, unintended consequences will affect performance across the system. To address this challenge, this dissertation introduces a real-time control algorithm to balance loads across distributed sewer assets and equalize combined sewer flow. The algorithm is evaluated in a simulated subsection of the Detroit combined sewer network. Trade-offs between flow and water quality objectives are evaluated to inform algorithm parameterization and considerations toward implementation. 3.) While the individual control of either sewer networks or water resource recovery facilities (WRRFs) has been explored separately, the opportunity to link these system components must consider the impact that sewer control has on WRRF operation and performance. By focusing on chemical phosphorus treatment, this dissertation quantifies the impact that WRRF influent dynamics and chemical addition has on treatment efficacy and efficiency. Namely, leveraging these two strategies together, phosphorus treatment is maintained or even improved, while chemical consumption is reduced. These findings exemplify benefits that can be accomplished by coupling the control and operation of system-wide assets.PHDEnvironmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163069/1/stroutm_1.pd

    An Introduction to Sewer Network Design Using SWMM

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    This is a basic manual for the calculation of sewage networks using the Storm Water Managemen Model (SWMM) software. This work consists of two files: one contains the introductory manual (pdf); the other complements the manual, and is a compressed file with the necessary resources to develop the models described in section 6 (p. 52). To use this data, it is recommended to copy the “SWMM Manual“ folder from the compressed file to the root directory of the hard drive (C:/SWMM Manual).Este é un manual básico para o cálculo de redes de saneamento utilizando o software Storm Water Management Model (SWMM). A obra componse de dous ficheiros: un contén o manual introdutorio (pdf); o outro complementa o manual, e é un ficheiro comprimido cos recursos necesarios para desenvolver os modelos que se describen no seu apartado 6 (p. 52). Para usar estes datos, recoméndase copiar a carpeta “SWMM Manual” do ficheiro comprimido ao directorio raíz do disco duro (C:/SWMM Manual).Este es un manual básico para el cálculo de redes de saneamiento utilizando el software Storm Water Management Model (SWMM). La obra se compone de dos archivos: uno contiene el manual introductorio (pdf); el otro complementa el manual, y es un archivo comprimido con los recursos necesarios para desarrollar los modelos que se describen en su apartado 6 (p. 52). Para usar estos datos, se recomienda copiar la carpeta “SWMM Manual” del archivo comprimido al directorio raíz del disco duro (C:/SWMM Manual).Spanish version available on / version en castelán accessible en: Anta, Jose; Naves, Acacia; Naves, Juan. (2019). Introducción al cálculo de redes de saneamiento con SWMM. A Coruña. Universidade da Coruña, Servizo de Publicacións. ISBN 978-84-9749-733-6. DOI: https://doi.org/10.17979/spudc.978849749733
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