Nilay Papila

Shape optimization of supersonic turbines using global approximation methods

There is growing interest to adopt supersonic turbines for rocket propulsion. However, this technology has not been actively investigated in the United States for the last three decades. To aid design improvement, a global optimization framework combining the radial-basis neural network (NN) and the polynomial response surface (RS) method is constructed for shape optimization of a two-stage supersonic turbine, involving O(10) design variables. The design of the experiment approach is adopted to reduce the data size needed by the optimization task. The combined NN and RS techniques are employed. A major merit of the RS approach is that it enables one to revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a predefined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials consideration.

Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods

Turbine performance directly affects engine specific impulse, thrust-to-weight ratio, and cost in a rocket propulsion system. A global optimization framework combining the radial basis neural network (RBNN) and the polynomial-based response surface method (RSM) is constructed for shape optimization of a supersonic turbine. Based on the optimized preliminary design, shape optimization is performed for the first vane and blade of a 2-stage supersonic turbine, involving O(10) design variables. The design of experiment approach is adopted to reduce the data size needed by the optimization task. It is demonstrated that a major merit of the global optimization approach is that it enables one to adaptively revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a pre-defined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials considerations.

Assessment of Neural Net and Polynomial-Based Techniques for Aerodynamic Applications

Neural network and polynomial-based techniques are applied to. process aerodynamic data obtained fi-om computational simulations for flows around a generic threedimensional wing/blade and a twodimensional airfoil. The main purpose of this study is to offer insight into developing appropriate techniques for supporting engineering design and op-on by considering small data sets (between 9 to 25 simulations) and a larger data set (up to 765 simulations). Relative performances of radial-basis and back-propagation networks, and polynomial-based iechaiw are Compared. For moderate data sizes, both the neural network and the polynomial-based techniques yi

Computational-Fluid-Dynamics-Based Design Optimization for Single-Element Rocket Injector

d comparable prfomances ths? improve as the data size increases. For large data sets, a two-layer radialbasis network is effective for data analysis provided thatappropriatecan be developed to guide the s&&ion of model para&ters.

Detailed Aerodynamic Design Optimization of an RLV Turbine

A computational-fluid-dynamics-based design optimization approach, utilizing the response surface method, has been proposed for a single-element rocket injector. The overall goal of the effort is to demonstrate the integration of a set of computational and optimization tools to enable the injector designer to objectively determine the trades between performance and life during the design cycle. Using design of experiment techniques, 54 cases are selected, and computational solutions based on the Navier‐Stokes equations, finite rate chemistry, and the k‐e turbulence closure are obtained. The response surface methodology is employed as the optimization tool. Four independent design variables are selected, namely, H2 flow angle, H2 and O2 flow areas with fixed flow rates, and O2 posttip thickness. Design optimization is guided by four design objectives. The maximum temperature on the injector element oxidizer posttip, the maximum temperature on the injector face, and a combustion chamber wall temperature are chosen as life indicators. The length of the combustion zone is selected as an indicator of mixing and performance. In the context of this effort, the design optimization tools performed efficiently and reliably. In addition to establishing optimum designs by varying emphasis on the individual objectives, better insight into the interplay between design variables and their impact on the design objectives is gained. The need to include environmental design objectives early in the design phase is clearly established.

ASSESSMENT OF RESPONSE SURFACE-BASED OPTIMIZATION TECHNIQUES FOR UNSTEADY FLOW AROUND BLUFF BODIES

A task was developed at NASA/Marshall Space Flight Center (MSFC) to improve turbine aerodynamic performance through the application of advanced design and analysis tools. There are four major objectives of this task: 1) to develop, enhance, and integrate advanced turbine aerodynamic design and analysis tools; 2) to develop the methodology for application of the analytical techniques; 3) to demonstrate the benefits of the advanced turbine design procedure through its application to a relevant turbine design point; and 4) to verify the optimized design and analysis with testing. The turbine chosen on which to demonstrate the procedure was a supersonic design suitable for a reusable launch vehicle (RLV). The hot gas path and blading were redesigned to obtain an increased efficiency over the baseline. Both preliminary and detailed designs were considered. The subject of the current paper is the optimization of the blading. To generate an optimum detailed design, computational fluid dynamics (CFD), response surface Copyright 2001 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free liscense to exercise all rights under the copyright claimed herein for Governmental Purposes. All other rights are reserved by thecopyright owner methodology (RSM), and neural nets (NN) were used. The goal of the demonstration was to increase the total-tostatic efficiency, tit-s, of the turbine by eight points over the baseline design. The predicted rv-s of the optimized design was 10 points higher than the baseline.

CFD-Based Design Optimization for Single Element Rocket Injector

Shape of a trapezoidal obstacle immersed in a twodimensional unsteady, viscous flow is optimized by response surface (RS) techniques based on combined criteria of minimum total drag and maximum mixing efficacy. Time dependent Navier-Stokes computations are conducted to supply the database. In order to address the issues related with the noise, an outlier analysis based on iteratively re weighted least square (IRLS) method is applied. The results indicate that the optimum designs having a low mean drag coefficient tend to be square-shaped, while the designs having a large value of the mixing effectiveness are more trapezoidal-shaped. Both RS and IRLS models yield consistent designs, indicating that the present task is well handled by the techniques employed. In addition, the RS methodology is used to identify domains within the design space within which all designs are, for practical purpose, acceptable.

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

To develop future Reusable Launch Vehicle concepts, we have conducted design optimization for a single element rocket injector, with overall goals of improving reliability and performance while reducing cost. Computational solutions based on the Navier-Stokes equations, finite rate chemistry, and the k-E turbulence closure are generated with design of experiment techniques, and the response surface method is employed as the optimization tool. The design considerations are guided by four design objectives motivated by the consideration in both performance and life, namely, the maximum temperature on the oxidizer post tip, the maximum temperature on the injector face, the adiabatic wall temperature, and the length of the combustion zone. Four design variables are selected, namely, H2 flow angle, H2 and O2 flow areas with fixed flow rates, and O2 post tip thickness. In addition to establishing optimum designs by varying emphasis on the individual objectives, better insight into the interplay between design variables and their impact on the design objectives is gained. The investigation indicates that improvement in performance or life comes at the cost of the other. Best compromise is obtained when improvements in both performance and life are given equal importance.