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Reference : UMR5560-PIEDUR-001
Workplace : TOULOUSE
Date of publication : Monday, April 26, 2021
Type of Contract : FTC Scientist
Contract Period : 12 months
Expected date of employment : 21 June 2021
Proportion of work : Full time
Remuneration : between 2 648 and 3 768 Euros as gross monthly salary (according to experience)
Desired level of education : PhD
Experience required : Indifferent
The hired post-doc will process and analyse meteorological and turbulence observations performed with an instrumented unmanned aerial vehicle (UAV) on a wind farm site. This work is embedded in the MOMENTA project, the aim of which is to study the characteristics of a wind-turbine wake, through field observations, wind tunnel tests and numerical simulations. A wind turbine harvests momentum from the atmospheric flow, and converts it into electricity. In the area downwind of the turbine and the blades the wind speed is thus reduced, but the turbulence is increased due to the blade rotation. These two effects are penalising for the downstream wind turbines, which motivates the development of models able to accurately represent the flow field in order to optimize wind-turbine farms layout.
The post-doc will work in the Laboratoire d'Aérologie (a Lab. from CNRS and University), under the scientific supervision of Pierre Durand (senior scientist at CNRS), within the AQUIET (Air Quality, Impacts, Energy Transition) team. The leader of UAV observations is Patrice Médina (chief-engineer at CNRS), with whom the data processing step will be done. The MOMENTA project is led by LHEEA (a Lab. From Ecole Centrale de Nantes and CNRS), and brings also together groups from IFPEN, PRISME (a Lab. From Université d'Orléans), Ecole de l'Air (Salon de Provence) as well as the companies Valemo et Valorem.
The Laboratoire d'Aérologie has developed, onboard a 20-kg unmanned aerial vehicle (UAV), an instrumental payload in order to measure meteorological parameters such as temperature, moisture wind and turbulence. In the framework of the Momenta project, this UAV is operated on a wind-farm site (situated in the so-called Vendée, France) during several field campaigns, in order to observe in situ the perturbed wake area of wind turbines. From these observations, the three components of the instantaneous wind along the UAV trajectory will be computed with a high resolution. However, to achieve this, a huge data processing and qualification step will have to be done, since turbulent wind estimate requires the fast and simultaneous acquisition of numerous parameters, each of them being to be accurately calibrated and qualified to obtain a valuable data set. The description of the wake will then be done through statistical parameters such as turbulence intensity and characteristic scales. Such observations remain original, and since they are done in a collaborative framework, the resulting scientific production is expected in a quite short term.
Expected qualification : PhD in meteorology and/or aerodynamics
Scientific skills: Boundary-layer meteorology, data processing of turbulence airborne observations
Techical skills: Acquisition systems, meteorological sensors, inertial platforms, signal processing, spectral analysis, data fusion
Computing and programming skills: Data processing software (Matlab), CFD (Fluent, ...)
Ability to write scientific papers for international Journals
Willingness to work in a team
The employing institution is CNRS (www.cnrs.fr). The Lab. (Laboratoire d'Aérologie, https://www.aero.obs-mip.fr) belongs to the Institut National des Sciences de l'Univers (INSU, www.insu.cnrs.fr). The Lab., situated in the Rangueil scientific campus, in Toulouse, France, is one of the six research Labs. of the Observatoire Midi-Pyrénées (http://www.obs-mip.fr). It is composed of around thirty permanent scientists, supported by technical staffs. The hired post-doc will belong to a small research team, working in close collaboration with a technical service in charge of the development, operation and data processing of unmanned aerial vehicles. The proposed job is a contribution to an ANR-funded project, through which the various expenses (travel, publication and conference fees, etc.) will be taken in charge. Large datasets will have be to processed, however this will be done on a standard computer since high computing performances will not be required.
Constraints and risks
Depending on the schedule of the observation campaigns, one or two one-week field trips could be requested.
Other travels will be planned in the context of the collaborative project, and in order to attend conferences, possibly abroad.
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