1 / 7

Applications to Fluid Mechanics

Applications to Fluid Mechanics. ERIC WHITNEY (USYD) FELIPE GONZALEZ (USYD). @. Supervisor: K. Srinivas Dassault Aviation: J. Périaux . Inaugural Workshop for FluD Group : 28th Oct 2003. AMME Conference Room. Overview. Aim:

Olivia
Download Presentation

Applications to Fluid Mechanics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Applications to Fluid Mechanics ERIC WHITNEY (USYD) FELIPE GONZALEZ (USYD) @ Supervisor: K. Srinivas Dassault Aviation:J. Périaux Inaugural Workshop for FluD Group : 28th Oct 2003. AMME Conference Room

  2. Overview • Aim: Develop modern numerical and evolutionary optimisation techniques for number of problems in the field of Aerospace, Mechanical and Mechatronic Engineering. • In Fluid Mechanics we are particularly interested in optimising fluid flow around different aerodynamic shapes: • Single and multi-element aerofoils. • Wings in transonic flow. • Propeller blades. • Turbomachinery aerofoils. • Full aircraft configurations. • We use different structured and unstructured mesh generation and CFD codes in 2D and 3D ranging from full Navier Stokes to potential solvers .

  3. CFD codes • Developed at the school MSES/MSIS - Euler + boundary layer interactive flow solver. The external solver is based on a structural quadrilateral streamline mesh which is coupled to an integral boundary layer based on a multi layer velocity profile representation. • HDASS : A time marching technique using a CUSP scheme with an iterative solver. • Vortex lattice method • Propeller Design • Requested to the author • MSES/MSIS - Euler + boundary layer interactive flow solver. The external solver is based on a structural quadrilateral streamline mesh which is coupled to an integral boundary layer based on a multi layer velocity profile representation • ParNSS ( Parallel Navier--Stokes Solver) • FLO22 ( A three dimensional wing analysis in transonic flow suing sheared parabolic coordinates, Anthony Jameson) • MIFS (Multilock 2D, 3D Navier--Stokes Solver) • Free on the Web • nsc2kec : 2D and AXI Euler and Navier-stokes equations solver • vlmpc : Vortex lattice program

  4. Evolutionary Algorithms What are Evolutionary Algorithms? Evolution • Populations of individuals evolve and reproduce by means of mutation and crossover operators and compete in a set environment for survival of the fittest. Crossover Mutation Fittest • Computers can be adapted to perform this evolution process. • EAs are able to explore large search spaces and are robust towards noise and local minima, are easy to parallelise. • EAs are known to handle approximations and noise well. • EAs evaluate multiple populations of points. • EAs applied to sciences, arts and engineering.

  5. HIERARCHICAL ASYNCHRONOUS PARALLEL EVOLUTION ALGORITHMS (HAPEA) Evolution Algorithm Evaluator • We use a technique that finds optimum solutions by using many different models, that greatly accelerates the optimisation process. Interactions of the 3 layers: solutions go up and down the layers. • Time-consuming solvers only for the most promising solutions. • Parallel Computing-BORGS Model 1 precise model Exploitation Model 2 intermediate model Model 3 approximate model Exploration

  6. Current and Ongoing CFD Applications Problem Two Element Aerofoil Optimisation Problem Formula 3 Rear Wing Aerodynamics 2D Nozzle Inverse Optimisation Multi-Element High Lift Design Transonic Viscous Aerodynamic Design Transonic Wing Design Aircraft Design and Multidisciplinary Optimisation Propeller Design UAV Aerofoil Design

  7. Outcomes of the research • The new technique with multiple models: Lower the computational expense dilemma in an engineering environment (at least 3 times faster than similar approaches for EA) • The new technique is promising for direct and inverse design optimisation problems. • As developed, the evolution algorithm/solver coupling is easy to setup and requires only a few hours for the simplest cases. • A wide variety of optimisation problems including Multi-disciplinary Design Optimisation (MDO) problems could be solved. • The benefits of using parallel computing, hierarchical optimisation and evolution algorithms to provide solutions for multi-criteria problems has been demonstrated.

More Related