Development of an OpenSource Autonomous Computational Fluid Dynamics MetaModeling Environment for SmallScale Combustor Optimization

Abstract

This work presents an opensource autonomous computational fluid dynamics (CFD) metamodeling environment (OpenACME) for smallscale combustor design optimization in a deterministic and continuous design space. OpenACME couples several objectoriented programing opensource codes for conjugateheat transfer, steadystate, multiphase incompressible Reynolds averaged NavierStokes CFDassisted engineering design metamodeling. There are fifteen design variables. Nonparametric rank regression (NPRR), global sensitivity analyses (GSA), and singleobjective (SOO) optimization strategies are evaluated. The Euclidean distance (singleobjective criterion) between a design point and the utopic point is based on the multiobjective criteria: combustion efficiency (η) maximization and pattern factor (PF), critical liner area factor (Acritical ), and total pressure loss (TPL) minimization. The SOO approach conducts Latin hypercube sampling (LHS) for reacting flow CFD for subsequent local constraint optimization by linear interpolation. The local optimization successfully improves the initial design condition. The SOO approach is useful for guiding the design and development of future gas turbine combustors. NPRR and GSA indicate that there are no leadingorder design variables controlling η, pattern factor (PF), Acritical , and TPL. Therefore, interactions between design variables control these output metrics because the output design space is inherently nonsmooth and nonlinear. In summary, OpenACME is developed and demonstrated to be a viable tool for combustor design metamodeling and optimization studies.