Reference number : GC-2017-Q1-03478, amendment number : , agreement type : G, recipient legal name : Zingg, David (University of Toronto), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Motivated by the need to reduce the drag of transport aircraft and as a result their CO2 emissions, the proposed research program comprises algorithm development for computational fluid dynamics, algorithm development for aerodynamic shape optimization, and application to drag reduction via unconventional aircraft configurations and active flow control. 
 The algorithm development for computational fluid dynamics is concentrated on promising higher-order operators having the generalized summation-by-parts property. This includes further development of tensor-product operators as well as novel multidimensional operators applicable to unstructured grids recently introduced by the applicant&rsquo;s group. These operators have similar properties to discontinuous Galerkin methods, but, as they do not rely on an explicit basis, they offer flexibility that hopefully can be exploited to improve efficiency on modern computer architectures. 
 The algorithm development for aerodynamic shape optimization concentrates on two areas. The first involves adaptive geometry control based on free-form deformation that enables the optimization algorithm to modify the design space in search of the optimal geometry. Since this enables the optimization to go in directions not anticipated by the designer, it opens up the possibility of discovering novel aerodynamic concepts through optimization. The research will also include the development of a reliable and efficient methodology for incorporating prediction of laminar-turbulent transition within the optimization framework, thus enabling the development of aircraft configurations exploiting significant regions of natural laminar flow. 
 The unconventional aircraft configurations under study include a variation of the blended wing-body developed in the applicant&rsquo;s group known as the lifting fuselage configuration, as well as the strut-braced wing and box-wing configurations. Emphasis will be on regional and single-aisle class aircraft, the former due to its relevance to Canada, the latter because it is the dominant class of aircraft globally. The three configurations will be optimized through aerodynamic shape optimization coupled with medium fidelity structural models and including trim and static margin constraints. A baseline conventional configuration will be optimized in an identical manner in order to provide a reference. The goal is to further advance these configurations and to identify which of the three is most promising for the regional and single aisle classes. 
 Finally, the high-order methods will be utilized in direct and large-eddy simulations of turbulent flows applied to the development of active flow control techniques for drag reduction. In particular, the focus will be on synthetic jet actuation to control large structures in the outer layer of the turbulent boundary layer., program purpose french : Motivated by the need to reduce the drag of transport aircraft and as a result their CO2 emissions, the proposed research program comprises algorithm development for computational fluid dynamics, algorithm development for aerodynamic shape optimization, and application to drag reduction via unconventional aircraft configurations and active flow control. 
 The algorithm development for computational fluid dynamics is concentrated on promising higher-order operators having the generalized summation-by-parts property. This includes further development of tensor-product operators as well as novel multidimensional operators applicable to unstructured grids recently introduced by the applicant&rsquo;s group. These operators have similar properties to discontinuous Galerkin methods, but, as they do not rely on an explicit basis, they offer flexibility that hopefully can be exploited to improve efficiency on modern computer architectures. 
 The algorithm development for aerodynamic shape optimization concentrates on two areas. The first involves adaptive geometry control based on free-form deformation that enables the optimization algorithm to modify the design space in search of the optimal geometry. Since this enables the optimization to go in directions not anticipated by the designer, it opens up the possibility of discovering novel aerodynamic concepts through optimization. The research will also include the development of a reliable and efficient methodology for incorporating prediction of laminar-turbulent transition within the optimization framework, thus enabling the development of aircraft configurations exploiting significant regions of natural laminar flow. 
 The unconventional aircraft configurations under study include a variation of the blended wing-body developed in the applicant&rsquo;s group known as the lifting fuselage configuration, as well as the strut-braced wing and box-wing configurations. Emphasis will be on regional and single-aisle class aircraft, the former due to its relevance to Canada, the latter because it is the dominant class of aircraft globally. The three configurations will be optimized through aerodynamic shape optimization coupled with medium fidelity structural models and including trim and static margin constraints. A baseline conventional configuration will be optimized in an identical manner in order to provide a reference. The goal is to further advance these configurations and to identify which of the three is most promising for the regional and single aisle classes. 
 Finally, the high-order methods will be utilized in direct and large-eddy simulations of turbulent flows applied to the development of active flow control techniques for drag reduction. In particular, the focus will be on synthetic jet actuation to control large structures in the outer layer of the turbulent boundary layer., agreement title english : Computational Aerodynamics for Aircraft Drag Reduction, agreement title french : Computational Aerodynamics for Aircraft Drag Reduction, agreement number : RGPIN, agreement value : 330000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada