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Computational Tools and Methods

Description:

Scope Title:

A Framework for Wall-Modeled Large Eddy Simulation (WMLES) Solution Sensitivity Analysis

Scope Description:

Computational fluid dynamics (CFD) plays an important role in the design and development of a vast array of aerospace vehicles, from commercial transports to space systems. With the ever-increasing computational power, usage of higher fidelity, fast CFD tools and processes will significantly improve the aerodynamic performance of airframe and propulsion systems, as well as greatly reduce nonrecurring costs associated with ground-based and flight testing. Historically, the growth of CFD accuracy has allowed NASA and other organizations, including commercial companies, to reduce wind tunnel and single engine component tests. Going forward, increased CFD fidelity for complete vehicle or engine configurations holds the promise of significantly reducing development costs, by enabling certification by analysis (CbA).  Confidence in fast, accurate CFD and multidisciplinary analysis tools allow engineers to reach out of their existing design space and accelerate technology maturation schedules. Uncertainty quantification is a key technology in enhancing confidence in the prediction capability of the computational tools. NASA’s CFD Vision 2030 Study [Ref. 1] highlighted the many shortcomings in the existing computational technologies used for conducting high-fidelity simulations, including multidisciplinary analysis and optimization, and made specific recommendations for investments necessary to overcome these challenges. A more recent study provided a long-term vision and a technology development roadmap to enable CbA for aircraft and engine certification [see Ref. 2]. For aircraft certification, prediction of maximum lift was considered one of the needed critical technologies highlighted in the study. A grand challenge problem in this technical area was defined in Reference 3, where technology gaps and potential areas of research are highlighted. Another grand challenge problem in the area of propulsion was developed in Reference 4. Solution of these challenge problems requires availability of robust, cost effective, and accurate eddy resolving computational tools.

 

Research to date has indicated that WMLES technology provides a good compromise between solution accuracy and computational cost for predicting complex turbulent flows, where the traditional Reynolds-Averaged Navier-Stokes (RANS) codes fall short. WMLES has been applied to various problems such as high-lift, turbomachinery, and surface heat transfer. However, grid point requirement estimates and the rate of solution convergence continue to remain significant challenges. There is a need to develop a rigorous framework to understand solution sensitivity with respect to computational grids for high-lift and other turbulent flow applications where scale-resolving simulations are needed to capture necessary physics. This framework must consider all the important geometric and flow parameters (e.g., surface curvature, pressure gradients, Reynolds number, and heat transfer). It is important to have the capability of automatically generating a minimal, but optimal, grid that yields aerodynamic quantities of interest within the required engineering accuracy. It is also important to consider the role and interplay of flow physics modeling (wall model and subgrid-scale model) and numerical discretization. The ultimate objective of this research is that the developed framework allows WMLES results to be obtained using minimal computational resources and human interaction, while accounting for all the important parameters that influence the outcome. Proposals are solicited for the development and demonstration of such a framework for WMLES. The developed technology must be demonstrated on one or more of the challenge or subchallenge problems cited above. It is important to note that the solicitation is not aimed at developing a new grid generation method, but to provide a framework that accounts for all the parameters that influence an optimal WMLES grid and then yields that grid for a given geometry and flow conditions. 

Expected TRL or TRL Range at completion of the Project: 2 to 6

Primary Technology Taxonomy:

  • Level 1 15 Flight Vehicle Systems
  • Level 2 15.1 Aerosciences

Desired Deliverables of Phase I and Phase II:

  • Software
  • Research
  • Analysis

Desired Deliverables Description:

Phase I:

  1. Formulate and develop the required framework.
  2. Demonstrate the capability for one or two selected applications.
  3. Write a report that describes the formulation and the results for the selected WMLES applications.

 

Phase II:

  1. Complete development of the framework by including all the important parameters that influence the outcome of WMLES for a range of applications, not limited to high-lift.
  2. Demonstrate the capability for a range of complex applications, including computational cost and accuracy.
  3. Write a comprehensive final report to include (a) formulation of the framework, (b) software development, and (c) results of WMLES applications.
  4. Deliver the developed software to NASA for its internal use.

State of the Art and Critical Gaps:

NASA's CFD Vision 2030 Study identified several impediments in computational technologies, and this solicitation addresses one of those related to application of scale-resolving simulations needed for expanding the scope of application of CFD across the aircraft flight envelope, particularly in the prediction of maximum lift.  WMLES technology demonstrated significant potential in accurate prediction of maximum lift prediction/stall in the recently held American Institute of Aeronautics and Astronautics (AIAA) High-Lift Prediction Workshop - 4. WMLES has been implemented in two NASA codes (LAVA and FUN3D), but automatic mesh generation that allows solution to be obtained with a minimum number of cells, which generates aerodynamic quantities of interest within required engineering quantities, remains a challenge. This solicitation addresses this significant technology gap in the existing computational tools capability.

Relevance / Science Traceability:

Various programs and projects of NASA missions use CFD for advanced aircraft concepts, launch vehicle design, and planetary entry vehicles. The developed technology will enable design decisions by Aeronautics Research Mission Directorate (ARMD), Exploration Systems Development Mission Directorate (ESDMD), and Space Operations Mission Directorate (SOMD). WMLES capability has been implemented in NASA's unstructured-grid CFD code FUN3D, but the construction of an optimal grid remains a challenge and requires extensive human intervention. Having a framework that enables automation of unstructured grid generation for a given geometry and flow conditions would be hugely enabling. If Phase II is successful in automating the process, then there is significant potential of post Phase II funding from NASA, because the industrial scale-resolving simulation capability is the next big step in CFD. 

References:

  1. NASA’s CFD Vision 2030 Study: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20140003093.pdf
  2. NASA's A Guide for Aircraft Certification by Analysis Study: https://ntrs.nasa.gov/citations/20210015404
  3. Slotnick, J. P. and Mavriplis, D. J., “A grand challenge for the advancement of numerical prediction of high-lift aerodynamics,” AIAA Paper 2021-0955.
  4. Anand, M. S. et al., “Vision 2030 aircraft propulsion grand challenge problem: Full-engine CFD simulations with high geometric fidelity and physics accuracy,” AIAA Paper 2021-0956.
  5. Advanced Air Vehicles Program: https://www.nasa.gov/aeroresearch/programs/aavp
  6. Transformative Aeronuatics Concepts Program: https://www.nasa.gov/aeroresearch/programs/tacp

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