50 research outputs found

    OpenSDM - An Open Sensor Data Management Tool

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    Exchange of scientific data and metadata between single users or organizations is a challenging task due to differences in data formats, the genesis of data collection, ontologies and prior knowledge of the users. Different data storage requirements, mostly defined by the structure, size and access scenarios, require also different data storage solutions, since there is no and there cannot be a data format which is suitable for all tasks and needs that occur especially in a scientific workflow. Besides data, the generation and handling of additional corresponding metadata leads us to the additional challenge of defining the meaning of data, which should be formulated in a way that it can be commonly understood to get out a maximum of expected and shareable information of the observed processes. In our domain we are able to take advantage of standards defined by the Open Geospatial Consortium, namely the standards defined by the Sensor Web Enablement, WaterML and CF-NetCDF working groups. Even though these standards are freely available and some of them are commonly used in specialized software packages, the adaption in widespread end-user software solutions still seems to be in its beginnings. This contribution describes a software solution developed at Graz University of Technology, which targets the storage and exchange of measurement data with a special focus on meteorological, water quantity and water quality observation data collected within the last three decades. The solution was planned on basis of long-term experience in sewer monitoring and was built on top of open-source software only. It allows high-performance storage of time series and associated metadata, access-controlled web services for programmatic access, validation tasks, event detection, automated alerting and notification. An additional web-based graphical user interface was created which gives full control to end-users. The OpenSDM software approach makes it easier for measurement station operators, maintainers and end-users to take advantage of the standards of the Open Geospatial Consortium, which usage should be promoted in the water related communities

    Optimisation of water resources systems using evolutionary algorithms

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    Evolutionäre multikriterielle Optimierung komplexer wasserwirtschaftlicher Systeme

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    Optimization Potential of Sewage Systems

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    Optimization of Water Resources Systems using Multi-Objective Evolution Strategies

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    This paper deals with the development of a new multi-objective evolution strategy in combination with an integrated pollution-load and water-quality model. The optimization algorithm combines the advantages of the Non-Dominated Sorting Genetic Algorithm and Self-Adaptive Evolution Strategies. The identification of a good spread of solutions on the pareto-optimum front and the optimization of a large number of decision variables equally demands numerous simulation runs. In addition, statements with regard to the frequency of critical concentrations and peak discharges require continuous long-term simulations. Therefore, a fast operating integrated simulation model is needed providing the required precision of the results. For this purpose, a hydrological deterministic pollution-load model has been coupled with a river water-quality and a rainfall-runoff model. Wastewater treatment plants are simulated in a simplified way. The functionality of the optimization and simulation tool has been validated by analyzing a real catchment area including sewer system, WWTP, water body and natural river basin. For the optimization/rehabilitation of the urban drainage system, both innovative and approved measures have been examined and used as decision variables. As objective functions, investment costs and river water quality criteria have been used

    Optimization of integrated urban wastewater systems using multi-objective evolution strategies

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    This paper deals with the development of a new multi-objective evolution strategy in combination with an integrated pollution-load and water-quality model to optimize the performance of an urban wastewater system. The optimization algorithm combines the advantages of the Non-Dominated Sorting Genetic Algorithm and Self-Adaptive Evolution Strategies and contains further development improving convergence and diversity. The identification of a good spread of solutions on the Pareto-optimum front and the optimization of a large number of decision variables equally demands numerous simulation runs. In addition, evaluation of criteria with regard to the frequency of critical concentrations in the river and peak discharges to the receiving water requires continuous long-term simulations. Therefore, a fast operating integrated simulation model is needed providing the required precision of results. For this purpose, a hydrological deterministic pollution-load model has been coupled with a river water-quality and a rainfall-runoff model. Wastewater treatment plants (WWTP) are simulated in a simplified way. The integrated simulation model and the multi-objective optimization algorithm were implemented in a modular common software shell. The functionality of the optimization and simulation tool has been validated by analyzing a real catchment area including sewer system, WWTP, water body and natural river basin. For the optimization/rehabilitation of the urban drainage system, both innovative and approved measures have been examined and used as decision variables. As objective functions, investment costs and river water quality criteria have been used

    Optimisation of Combined Sewer Systems using Evolution Strategies

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