“Uncertainties modeling of environmental noise predictions – Application to wind turbine noise”

PhD three-year fixed-term contract

Deadline for applying: April 8, 2016

PhD starting: Autumn, 2016

Description of the PhD project

The French legislation (Noise Law 1992) requires the realization of noise assessment studies and of noise maps. Nowadays that implies to use numerical simulations, but very little information or methodologies are available to assess the uncertainties associated with these simulations. Without this information, it is very difficult to estimate the degree of confidence that can be placed on a sound prediction, or the risk that real noise levels exceed the calculated sound levels. Nowadays, an engineering company on sound, an industry, or a government office are not able to assess the risk of noise annoyance satisfactorily. This is particularly the case for the prediction of wind turbine noise. Uncertainties of sound simulations have two main sources. The first comes from the lack of precision of models or of prediction methods used, especially when several models are linked or coupled together (e.g. transmission / propagation, micrometeorology / acoustic, etc.). The second comes from the uncertainty of the input parameters of a model, which can be related to the experimental method used to characterize these parameters, or to spatial or temporal variability of these parameters (soil, wind …). While acoustic modeling tools have been greatly improved in recent years, few studies have focused on the estimation of uncertainties associated with the chaining of models and their numerous input parameters. Existing work only treat a few special cases and does not take into account the specificity of wind turbine (significant height of sources, movement of blades…). But today there is a major challenge to estimate the accuracy and representativeness (spatial and temporal) of environmental sound level. This thesis therefore appears to be both innovative in the community of environmental acoustics, and as needed on the control of environmental impacts by humans.

The prediction of variability (deterministic and random) of predicted sound levels require (i) to refine the models, (ii) to estimate the fluctuations of all input data, (iii) to achieve an optimized digital experience plan and (iv) to use advanced modeling for the propagation of uncertainty and sensitivity analysis techniques for complex systems (metamodel, Kriging, screening, etc.). The ultimate goal is to achieve a method by which an acoustician could assess more accurately the uncertainties of the entire modeling chain due to deterministic and random variability uncertainties influential parameters: wind farm operating modes, micrometeorological characteristics (stability and atmospheric turbulence), ground acoustic properties (acoustic impedance), digital terrain model, surface roughness (spatial spectrum), etc. The thesis will allow both a better understanding of the relative influence of environmental parameters and their impact on the noise levels close to a wind farm neighborhood. It will also The French Institute of Science and Technology for Transport, Development and Networks Centre for expertise and engineering on risks, urban and country planning, environnement and mobility provide a method for estimating the uncertainties due to the spatial and temporal variability of these parameters on an acoustic prediction. It will allow a better estimate of the risk of noise to which a population can be exposed. The thesis will also improve outdoor sound propagation models. Uncertainty propagation methods and chaining of models are problems present in many areas of science; the methods used and the results obtained will then have a broader scope than that of the noise impact of wind farms. For example, the methods and tools developed as part of this thesis will be used for the validation and development of future digital engineering models for the prediction of environmental noise (urban noise, transport, industry, etc.). These methods and tools will also contribute to provide useful information for standardization working groups in environmental acoustics.

Desired skills

The candidate have strong acoustic skills and bases in numerical simulation. Skills in programming skills or in statistics would be a plus.

Oral and written fluency English is required. Oral and written fluency in French is a plus.

PhD information

  • Employee : Cerema or Ifsttar1 , three-year fixed-term contract from autumn 2016 to autumn 2019.
  • Remuneration : 1420€ the first two years (increased the 3rd year).
  • Doctoral school : SPIGA (ED498)
  • Hosting research teams : the PhD student will work at the Environmental Acoustic Lab. of Ifsttar in Nantes, and at the research team in acoustics of Cerema in Strasbourg, according to terms that will be defined before the beginning of the PhD

PhD supervisors

  • PhD director: Benoit Gauvreau (CR-HDR), Ifsttar, Laboratoire d’Acoustique Environnementale (benoit.gauvreau@ifsttar.fr, tel 33 (0)2 40 84 58 98)
  • PhD co-director: David Ecotière (ITPE-Cesaar), Cerema, Acoustic team of the Cerema laboratory of Strasbourg (david.ecotiere@cerema.fr, tel 33 (0)3 88 77 79 33).

To apply for this position

People who want to apply for this PhD are requested to contact PhD supervisors and to send by email before April 8, 2016 the following documents:

  • Curriculum Vitae
  • Copy of passport
  • Copy of last completed degree (and transcript)
  • Letter of motivation
  • Letter of recommendation

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