Shape optimization under uncertainty for rotor blades of horizontal axis wind turbines

Vahid Keshavarzzadeh, Roger G. Ghanem, Daniel A. Tortorelli

Research output: Contribution to journalArticlepeer-review


We present a computational framework for the shape optimization of a Horizontal-Axis Wind Turbine (HAWT) rotor blade under uncertainty. Our framework integrates aerodynamic simulations based on the blade element method which utilizes reduced order models of the blade structure and wind load with design sensitivity analysis and nonlinear programming. The wind velocity is modeled as a stochastic process to account for variations in time and space. An additional stochastic process accounts for uncertainties in the structural material properties. The uncertainty propagation is based on a non-intrusive polynomial chaos expansion that allows accurate estimation of stochastic performance metrics such as generated power and structural compliance. Sensitivities of cost and constraint functions with respect to shape parameters namely twist angles are computed with an efficient scheme to enable gradient based optimization. To demonstrate the effect of uncertainty, designs obtained from optimization under uncertainty are compared to those obtained from deterministic optimization.

Original languageEnglish (US)
Pages (from-to)271-306
Number of pages36
JournalComputer Methods in Applied Mechanics and Engineering
StatePublished - Sep 1 2019


  • Blade element method
  • Horizontal-axis wind turbine
  • Polynomial chaos expansion
  • Reduced order models
  • Shape optimization under uncertainty

ASJC Scopus subject areas

  • Computational Mechanics
  • Mechanics of Materials
  • Mechanical Engineering
  • General Physics and Astronomy
  • Computer Science Applications


Dive into the research topics of 'Shape optimization under uncertainty for rotor blades of horizontal axis wind turbines'. Together they form a unique fingerprint.

Cite this