(DEPSCOR - RESEARCH COLLABORATION - FY21) A NEW PARADIGM FOR TRANSCRITICAL INJECTION SIMULATIONS AND UNDERSTANDING

Abstract

Despite several recent activities in developing high fidelity models to study fuel injection and combustion dynamics, there is yet much to be done in making trans- and super-critical fluid calculations accurate and affordable. This is an important concern in rocket propulsion, and the proposed research addresses this at the foundational level. The proposal recognizes the high cost of real fluid models and has proposed an adaptive neural network based model to evaluate thermodynamic and transport properties, if successful this would offer a large savings in computational resources compared to traditional approaches.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 20, 2023
Source ID
FA95502210306

Entities

People

  • Daniel Banuti

Organizations

  • Air Force Office of Scientific Research
  • Office of the Secretary of Defense
  • University of New Mexico

Tags

Readers

  • Combustion and Flow Dynamics.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML