Ofertas de empleo en HOVEDSTADEN (Dinamarca) de Profesores de universidades y de la enseñanza superior
Phd Scholarship In Hydraulic Modelling And Data Assimilation For Deep Urban Tunnel Systems
Clasificación del trabajo:Profesionales científicos e intelectuales : Profesionales de la enseñanza : Profesores de universidades y de la enseñanza superior : Profesores de universidades y de la enseñanza superior. Arbejde, der forudsætter viden på højeste niveau inden for pågældende område : Undervisning og pædagogisk arbejde : Undervisning og forskning ved universiteter og højere læreranstalter : Undervisning og forskning på universiteter og højere læreranstalter.
Descripción de la oferta de trabajo:
DTU Environment invites for applications for a 3-year PhD scholarship within the field of hydraulic modelling and data assimilation for deep urban tunnel systems. The research project is part of a strategic partnership between DTU and Nanyang Technological University (NTU). The PhD student will work closely with our research partners at NTU and other DTU departments on a joint research effort in Smart Cities. The student will spend a minimum of one year at NTU in Singapore throughout the project, as well as become part of the joint degree PhD agreement between NTU and DTU. The PhD Student will be placed in the Urban Water Systems Section. This section has 30 scientific employees focusing on sustainable management of the urban water cycle with respect to its quantity and quality dealing with processes and technologies across the continuum from raw water, to potable water, to wastewater, to storm water. In all cases, collection, treatment, use, and reuse are considered. Both computational and experimental studies are conducted and research is done at the lab, pilot, full, or city scale, and in collaboration with other research institutes, stakeholders, and end-users. Project description Large underground tunnel systems are becoming a widespread tool to assist in solving various problems in urban water management due to their ability to convey and store large volumes of water. The most advanced and ambitious of its kind is currently the Deep Tunnel Sewerage System (DTSS) in Singapore that enable the centralised collection of used water (wastewater) for water reclamation. Also in Copenhagen tunnels are part of the modern wastewater infrastructure adapted to projected future climate changes, by storing and transporting combined sewage and stormwater to treatment facilities in order to minimize sewage overflows and treatment plant bypasses and thus protect local harbor areas and coastal zones used for bathing in summer. Tunnels make it possible to improve the operation of urban wastewater systems, for example by holding back water during peak hours until later when electricity is cheap, which can lead to significant economic savings in the purification of wastewater and to evening out the daily fluctuations of a city’s electricity consumption. The operation of urban tunnel systems has so far generally not included advanced control algorithms for optimizing e.g. energy consumption or self-cleansing. In order to do this without compromising the main purpose of the tunnels – transporting wastewater, it is of paramount importance to always know the state of the system, i.e. how much water is everywhere in the tunnels at all times, and to be able to make reliable forecasts of the system state to test the consequence of a given control decision. Observations from the system can provide pointwise information about water levels, flows and water quality while models can be used to estimate and forecast the entire system state. Observations in tunnel systems are, however, very scarce, uncertain and error prone due to the hostile environment, and model based forecasts of the future are only useful if the starting point of the models are close to reality. The overall objectives of the PhD project are to: •Use modern data assimilation (DA) methods to update the states of detailed hydraulic models of urban tunnel systems in real time to get good system-wide estimates of water levels, flows and relevant water quality parameters. •Develop tuning methods for the DA scheme that are suitable for hydraulic pipe/tunnel models, and develop methods to make model based sensor validation using modern DA methods and hydraulic models. •Use the updated models as starting point for forecasting water levels, flows and water quality throughout the systems – for a range of operational purposes. Qualifications Candidates should have a master's degree in Engineering or a similar degree with an academic level equivalent to the master's degree in Engineeri
Servicio de empleo de origen:AMS, Servicios Públicos de Empleo, Dinamarca.