Supersonic Aircraft Shape Design

Supersonic Aircraft Shape Design Powered by SU2 and Pointwise

Supersonic aircraft are poised for a comeback. Current regulations do not permit supersonic flight over land due to sonic boom noise. However, recent advances in simulation-based design are opening the door to new supersonic aircraft designs with reduced sonic boom impacts. The design of these aircraft requires accurate predictions of sonic boom on the ground and techniques for shaping the aircraft to achieve a desired boom signature while maintaining performance.

This webinar details how Pointwise and SU2 can be used to tackle supersonic aircraft design. Watertight surface and volume meshes for complex geometries can be quickly generated in Pointwise and exported to the native SU2 format. A properly constructed mesh aids in accurately predicting boom on the ground. Furthermore, a new script for Pointwise can help designers generate Free Form Deformation (FFD) boxes for geometry parameterization and shape design in SU2.

We will also demonstrate how to formulate and solve a shape design problem in SU2, using a continuous adjoint formulation to obtain the sensitivities for gradient-based optimization. This includes a discussion of proper settings for the flow and adjoint problems, objectives and constraints, FFD design variables, and mesh deformation. Finally, we will present optimal shape design results from SU2 for the Lockheed Martin 1021 aircraft.

Discover How To

Quickly generate a watertight unstructured surface and volume mesh suitable for Euler calculations.
Improve farfield shock capturing without the need for grid adaptation by assembling Mach aligned structured blocks.
Save time by creating FFD boxes for design optimization within Pointwise.
Easily configure SU² for solving the Euler and adjoint Euler equations and computing surface sensitivities for design.
Set up a shape design problem in SU², including formulating objectives and constraints, FFD design variables, and mesh deformation.
Perform optimal shape design of a supersonic aircraft for minimizing drag with constraints.

Lockheed Martin 1021

The Lockheed Martin 1021 is one of the test cases from the AIAA 1st Sonic Boom Prediction Workshop. At that website, you will find the technical paper Full Configuration Low Boom Model and Grids for 2014 Sonic Boom Prediction Workshop by J. M. Morgenstern, M. Buonanno, and F. Marconi (AIAA Paper 2013-0647).

Travis Carrigan

Travis Carrigan joined Pointwise as a senior engineer after completing his M.S. in aerospace engineering at The University of Texas at Arlington in May 2011 where his graduate research involved aerodynamic design optimization. Currently, as Manager of Technical Sales, Mr. Carrigan works with prospective customers and demonstrates how Pointwise software can be used to improve their CFD process. He also produces technical marketing content and works with customers and software partners to demonstrate best practices in grid generation, solver setup, and solution post-processing for a variety of industries.

Francisco Palacios

Dr. Francisco Palacios is an engineering research associate at the Department of Aeronautics and Astronautics at Stanford University. His main areas of expertise include optimal aerodynamic shape design, large-scale multi-physics CFD simulations, and numerical analysis. Prior to his arrival at Stanford University in 2011, Dr. Palacios was research lead for technological innovation at the Madrid Institute for Advanced Studies and coordinator of the Airbus program “Future Simulation Concepts”. From 2011 to 2013, Dr. Palacios was responsible for the development of the main RANS solver for the Stanford PSAAP center, and for the research in adjoint-based methodologies to manage the uncertainties that are present in hypersonic combustion environments. Currently, Dr. Palacios research is focused on supersonic aircraft design and the development of novel shape design techniques applied to multi-physics problems.

Trent Lukaczyk

SU2

Trent Lukaczyk is a Ph.D. candidate in the Aerospace Design Lab within the Department of Aeronautics & Astronautics at Stanford University. His core research interests are in aircraft design and optimization methods, and he is currently contributing to the design of NASA's next-generation supersonic passenger jet. This work depends on experience in various disciplines that he gained during several internships and his undergraduate education at Cornell University: developing meshing tools, simulating the aerodynamics of both aircraft and automobiles, testing those designs in the wind tunnel, and designing combustion engines.

Thomas D. Economon

SU2

Thomas D. Economon is currently a Ph.D. candidate in the Aerospace Design Lab within the Department of Aeronautics & Astronautics at Stanford University. His research focuses on the development of new design methodologies for aerospace systems, including high-fidelity, adjoint-based techniques for optimal shape design, as well as tools for design at the conceptual level. He has extensive experience with high performance computing and the development of CFD platforms, most notably as a member of the core development team for the open-source SU² software suite. He holds a B.S. in Aerospace Engineering from the University of Notre Dame (2008) and an M.S. in Aeronautics & Astronautics from Stanford University (2010).

See how automated meshing enables shape optimization with CFD.