PhD Fellowship in Reduced Order Models for Aerodynamic Applications
Faculty of Information Technology and Electrical Engineering
Department of Mathematical Sciences (IMF)
About the research project
Wind energy projects are today developed mainly as large wind farms or clusters of wind farms, e.g. Dogger Bank (UK) is being planned with four projects each rated 1200 MW offshore, and Fosen Wind (NO) is being constructed with six land based wind farms totalling 1000 MW. Attention is on reducing costs and increasing profitability. This can be achieved through design optimization, but also by optimizing the operation and maintenance (O&M) of the wind power plant (WPP). The KPN-project OPWIND (cofunded by the Research Council of Norway and industrial partners) will develop knowledge and tools for O&M optimization, in particular focusing on optimizing the operational control of WPPs.
Such optimization using state-of-the-art high fidelity simulation tools is not convenient and efficient. There has also been an increasing demand of computationally efficient real-time simulation tools. To this end part of the current project focuses on developing Reduced Order Models (ROMs) for aerodynamic applications. The ROMs is expected to bridge the gap between high fidelity numerical simulations and industrial needs of computationally efficient tools. A ROMs approach consists of using results from high fidelity numerical simulations to construct what are called "Reduced Bases" which are used in an online simulation to solve similar problem with much fewer degrees of freedom. However, the success of such models depends on some questions which the PhD candidate along with experts in Computational Mathematics and Offshore Wind Technology will answer in the project. These questions are: How do we choose the simulation set-up for high fidelity simulations so that we span the solution space in an optimal way? Which method should be utilized to construct the reduced order basis for the flow dynamics, from which we can reconstruct the solution for a new scenario, based on available input conditions? What are relevant quality criteria for the ROM in the context of aerodynamics of wind turbines, and how can the approximation properties of the ROM be optimized?
We seek a highly motivated individual with good analytical and communication skills holding a Master’s degree in applied/numerical mathematics or corresponding education with a solid background in finite element analysis. Familiarity with atmospheric flow and fluid mechanics is an advantage. Applicants must have significant programming experience ideally in C, C++ and/or Python. Applicants are required to justify their candidateship by explicitly explaining their personal motivation and academic aptitude for pursuing a doctoral degree within this research field. Applicants that expect to complete their Master’s degree by fall 2017 can apply.
Academic results, publications, relevant specialization, work or research experience, personal qualifications, and motivation will be considered when evaluating the applicants.
The applicants who do not master a Scandinavian language must document a thorough knowledge of English (equivalent to a TOEFL score of 600 or more).
Applicants must have a Master’s degree in computational/numerical mathematics or corresponding education, and must also satisfy the requirement for entering the PhD programme at NTNU; please see http://www.ntnu.edu/ime/research/phd for information about the PhD programme at NTNU.
The regulations for PhD programmes at NTNU state that a Master’s degree or equivalent with at least five years of studies and an average grade of A or B within a scale of A-E for passing grades (A best) for the last two years of the MSc is required, and C or higher for the BSc.
Terms of employment
The PhD fellow will be part of the Department of Mathematical Sciences at NTNU and will have her/his workplace there. See http://www.ntnu.no/imf. The Department currently has around 60 PhD fellows. The successful candidate will be offered a three-year position. The Department may offer a six to twelve month extension as a teaching assistant.
The PhD fellowship is placed in salary code 1017, with a gross salary of NOK 436 500 per year before tax. A pension contribution of 2% of the salary will be deducted as an obligatory premium to the Norwegian Public Service Pension Fund.
The appointment of the PhD fellow will be made according to Norwegian guidelines for universities and university colleges and to the general regulations regarding university employees. Applicants must agree to participate in organized doctoral study programs within the period of the appointment and have to be qualified for the PhD-study.(see http://www.ntnu.edu/ime/research/phd).
The successful candidate will be required to enroll in a PhD programme within the period of employment, and must sign a contract regulating the starting date and duration of employment as well as the required duties.
The position adheres to the Norwegian Government’s policy of balanced ethnicity, age and gender. NTNU wishes to increase the number of women in its workforce, and female candidates are therefore encouraged to apply.
For further information, please contact:
Professor Trond Kvamsdal, Trond.Kvamsdal@ntnu.no , phone (+47) 9358702
Research Manager Adil Rasheed, Adil.Rasheed@sintef.no
Professor Harald van Brummelen, email@example.com
Applications are to be submitted electronically through this page. Preferably, the attachments should be submitted as a single file. The application must include:
Information about educational background and work experience.
Relevant publications. Joint work will be considered provided that a short summary outlining the applicant's contributions is attached.
Certified copies of relevant transcripts and diplomas. Candidates from universities outside Norway are kindly requested to send a Diploma Supplement or similar documentation, which describes in detail the programme of study, the grading system, and the rights to further studies associated with the degree obtained.
Contact information for two references
Closing date: 10.12.2017.