Non-Intrusive Computational Method and Uncertainty Quantification Tool for Isolator Operability Calculations

Computational fluid dynamics (CFD) simulations are extensively used by NASA for hypersonic aerothermodynamics calculations. The physical models used in CFD codes and initial/boundary conditions for numerical simulations carry significant uncertainties. There are also inherent errors in experiments designed for model validation, and numerical discretization. Despite this knowledge, only a limited number of efforts have been undertaken to formally characterize these uncertainties and to evaluate their impact on the predictive capability of CFD tools for hypersonic applications such as isolator dynamics. Major challenges with uncertainty quantification for such simulations include lack of sufficient data to characterize the associated uncertainties in the isolator dynamics phenomena and the computational cost of the required large number of cases. CFDRC in partnership with Virginia Tech and UTSI proposes to directly address these issues and deliver an non-intrusive tool for uncertainty quantification that can be integrated with the state-of-the-art CFD tools currently utilized by NASA and its customers. During Phase I, this team will develop and demonstrate a dimensionally adaptive sparse grid approach for uncertainty quantification coupled with NASA LaRC VULCAN-CFD code. In phase I, the developed tool will be demonstrated on the test rig developed and characterized at the NASA-LaRC Isolator Dynamics Research Lab. Surrogate models including polynomial response surface and gradient-enhanced Kriging will be developed based upon the samples generated from the adaptively sparse grid algorithm, thereby providing a modeling tool to estimate the operability of isolator over the relevant flight regime and ultimately to optimize design of isolator to prevent scramjet unstart. In Phase II, the framework will be further developed to include uncommon probability density distributions of uncertain parameters, and will be validated and demonstrated on more complex problems.

Non-intrusive uncertainty quantification has been identified as an enabling technology to advance the role of computational fluid dynamics codes in the Design Development Research and Engineering community, ultimately leading to utilization for certification for flight. The proposed computational product offers a direct solution to link the various sources of uncertainties to predictions made by CFD tools, thereby enabling the usability of CFD tools for making risk-informed design decisions. The adaptive sparse grid method offers a significant advantage over other uncertainty quantification methods due to the ability to handle non-smooth system response with complex probability density distributions and much smaller number of required CFD simulations. This product can be a highly effective tool for wider applications requiring aerothermodynamics calculations where the lack of confidence in modeling parameters and predictive capability of the CFD codes has limited their impact.

The work established in this project can be transitioned to support a significant number of other applications where reacting CFD modeling tools are utilized. Energy and propulsion applications such as gas-turbine combustors, augmentors, rockets, and many others can benefit from the product developed in the proposed work.

This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.