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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

The space shuttle ascent vehicle aerodynamic challenges configuration design and data base development

The phase B Space Shuttle systems definition studies resulted in a generic configuration consisting of a delta wing orbiter, and two solid rocket boosters (SRB) attached to an external fuel tank (ET). The initial challenge facing the aerodynamic community was aerodynamically optimizing, within limits, this configuration. As the Shuttle program developed and the sensitivities of the vehicle to aerodynamics were better understood the requirements of the aerodynamic data base grew. Adequately characterizing the vehicle to support the various design studies exploded the size of the data base to proportions that created a data modeling/management challenge for the aerodynamicist. The ascent aerodynamic data base originated primarily from wind tunnel test results. The complexity of the configuration rendered conventional analytic methods of little use. Initial wind tunnel tests provided results which included undesirable effects from model support tructure, inadequate element proximity, and inadequate plume simulation. The challenge to improve the quality of test results by determining the extent of these undesirable effects and subsequently develop testing techniques to eliminate them was imposed on the aerodynamic community. The challenges to the ascent aerodynamics community documented are unique due to the aerodynamic complexity of the Shuttle launch. Never before was such a complex vehicle aerodynamically characterized. The challenges were met with innovative engineering analyses/methodology development and wind tunnel testing techniques.

Dill, C. C.↗
NASA NTRS2000

Multidisciplinary High-Fidelity Analysis and Optimization of Aerospace Vehicles: Preliminary Results - Part 2

An objective of the High Performance Computing and Communication Program at the NASA Langley Research Center is to demonstrate multidisciplinary shape and sizing optimization of a complete aerospace vehicle configuration by using high-fidelity finite-element structural analysis and computational fluid dynamics aerodynamic analysis in a distributed, heterogeneous computing environment that includes high performance parallel computing. A software system has been designed and implemented to integrate a set of existing discipline analysis codes, some of them computationally intensive, into a distributed computational environment for the design of a high-speed civil transport configuration. The paper describes both the preliminary results from implementing and validating the multidisciplinary analysis and the results from an aerodynamic optimization. The discipline codes are integrated by using the Java programming language and a Common Object Request Broker Architecture compliant software product. A companion paper describes the formulation of the multidisciplinary analysis and optimization system.

Walsh, J. L.↗
NASA NTRS2005

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

Source record↗
NASA NTRS1995

Wing-section optimization for supersonic viscous flow

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗
NASA NTRS2024

Experimental Results for Mars Rotorcraft Airfoils (roamx-0201 and clf5605) at Low Reynolds Number and Compressible Flow in a Mars Wind Tunnel

Experimental results are obtained for a roamx-0201 type airfoil and the clf5605 airfoil at highsubsonic, low Reynolds number conditions using the Tohoku University Mars Wind Tunnel, Japan. The tests are conducted at a Mach number of M = 0.60, and a Reynolds number of Re = 20,000 to reflect representative aerodynamics of a rotor blade for Mars exploration. The angle of attack is varied between α = −2.0 deg and α = 6.0 deg. The roamx-0201 type airfoil is an unconventional airfoil optimized for the chosen tunnel operating conditions using the Evolutionary aLgorithm for Iterative Studies of Aeromechanics (ELISA), developed under the Rotor Optimization for the Advancement of Mars eXploration (ROAMX) project. ELISA is utilized here to optimize aerodynamic airfoil performance using a Genetic Algorithm and two-dimensional high-fidelity CFD simulations, ultimately resulting in a Pareto-optimal airfoil set. The clf5605 airfoil is the outboard airfoil used on the Ingenuity Mars Helicopter and provides a baseline against which the roamx-0201, as well as possible future airfoil profiles for the compressible low Reynolds number regime, can be compared against. Lift and drag data are recorded using a balance, pressure distributions are obtained using Pressure Sensitive Paint (PSP) application, and Schlieren images are obtained to visualize the flowfield. The data is tabulated to aid future research.

Roamx↗
NASA NTRS1999

Aero-Structural Optimization of HSCT Configurations in Transonic and Supersonic Flow

This document outlines the progress made under NASA Cooperative Research Agreement NCC2- 5226 for the period 10/01/97-09/30/98. The work statement originally proposed was meant to extend over the period of two complete years of which only one was funded. Consequently, only a portion of the goals were achieved. Similar work will continue in our group under different sponsorship and will be available in the form of conference and journal publications. The following sections summarize the technical accomplishments obtained during the last year. Details of these accomplishments can be found in the accompanying paper that was presented at the AIAA 37th Aerospace Sciences and Exhibit Meeting which was held in Reno, NV in January of this year. The original proposal outlined a research program meant to lay down the foundation for the development of high-fidelity, fully-coupled aerodynamic/structural optimization methods applicable to a variety of aerospace applications including the design optimization of High Speed Civil Transport (HSCT) configurations. The necessary research and development work was divided into two main efforts which addressed the necessities of the long term goal. Initially, our experience in the simulation of unsteady aeroelastic flows was directly applied to existing aerodynamic optimization techniques in order to provide insight into the effects of aeroelastic deformations on the performance of aircraft which have been designed based on purely aerodynamic cost functions. The intention was to follow up this work with a detailed investigation into the basic research work that has to be completed for the development of an optimization framework which efficiently allows the truly coupled design of aero-structural systems. This follow-up effort was not funded. The outcome of our efforts during the past year was the development of a coupled aero-structural analysis and design environment that was applied to the design of a complete aircraft configuration.

Alonso, Juan J.↗
NASA NTRS1993

Grid and aerodynamic sensitivity analyses of airplane components

An algorithm is developed to obtain the grid sensitivity with respect to design parameters for aerodynamic optimization. The procedure is advocating a novel (geometrical) parameterization using spline functions such as NURBS (Non-Uniform Rational B-Splines) for defining the wing-section geometry. An interactive algebraic grid generation technique, known as Two-Boundary Grid Generation (TBGG) is employed to generate C-type grids around wing-sections. The grid sensitivity of the domain with respect to geometric design parameters has been obtained by direct differentiation of the grid equations. A hybrid approach is proposed for more geometrically complex configurations such as a wing or fuselage. The aerodynamic sensitivity coefficients are obtained by direct differentiation of the compressible two-dimensional thin-layer Navier-Stokes equations. An optimization package has been introduced into the algorithm in order to optimize the wing-section surface. Results demonstrate a substantially improved design due to maximized lift/drag ratio of the wing-section.

Sadrehaghighi, Ideen↗
NASA NTRS2004

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗
NASA NTRS1989

Vortical sources of aerodynamic force and moment

It is shown that the aerodynamic force and moment can be expressed in terms of vorticity distribution (and entropy variation for compressible flow) on near wake plane, or in terms of boundary vorticity flux on the body surface. Thus the vortical sources of lift and drag are clearly identified, which is the real physical basis of optimal aerodynamic design. Moreover, these sources are highly compact, hence allowing one to concentrate on key local regions of the configuration, which have dominating effect to the lift and drag. A detail knowledge of the vortical low requires measuring or calculating the vorticity and dilatation field, which is however still a challenging task. Nevertheless, this type of formulation has some unique advantages; and how to set up a well-posed problem, in particular how to establish vorticity-dilatation boundary conditions, is addressed.

Wu, J. Z.↗
DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
NASA NTRS2000

First-Order Model Management With Variable-Fidelity Physics Applied to Multi-Element Airfoil Optimization

First-order approximation and model management is a methodology for a systematic use of variable-fidelity models or approximations in optimization. The intent of model management is to attain convergence to high-fidelity solutions with minimal expense in high-fidelity computations. The savings in terms of computationally intensive evaluations depends on the ability of the available lower-fidelity model or a suite of models to predict the improvement trends for the high-fidelity problem, Variable-fidelity models can be represented by data-fitting approximations, variable-resolution models. variable-convergence models. or variable physical fidelity models. The present work considers the use of variable-fidelity physics models. We demonstrate the performance of model management on an aerodynamic optimization of a multi-element airfoil designed to operate in the transonic regime. Reynolds-averaged Navier-Stokes equations represent the high-fidelity model, while the Euler equations represent the low-fidelity model. An unstructured mesh-based analysis code FUN2D evaluates functions and sensitivity derivatives for both models. Model management for the present demonstration problem yields fivefold savings in terms of high-fidelity evaluations compared to optimization done with high-fidelity computations alone.

Alexandrov, N. M.↗
DOE OSTI2021

On the scaling of wind turbine rotors

This paper formulates laws for scaling wind turbine rotors. Although the analysis is general, the article primarily focuses on the subscaling problem, i.e., on the design of a smaller-sized model that mimics a full-scale machine. The present study considers both the steady-state and transient response cases, including the effects of aerodynamic, elastic, inertial, and gravitational forces. The analysis reveals the changes to physical characteristics induced by a generic change of scale, indicates which characteristics can be matched faithfully by a subscaled model, and states the conditions that must be fulfilled for desired matchings to hold. Based on the scaling laws formulated here, the article continues by considering the problem of designing scaled rotors that match desired indicators of a full-scale reference. To better illustrate the challenges implicit in scaling and the necessary tradeoffs and approximations, two different approaches are contrasted. The first consists in a straightforward geometric zooming. An analysis of the consequences of zooming reveals that, although apparently simple, this method is often not applicable in practice, because of physical and manufacturing limitations. This motivates the formulation of scaling as a constrained optimal aerodynamic and structural matching problem of wide applicability. Practical illustrations are given considering the scaling of a large reference 10 MW wind turbine of about 180 m in diameter down to three different sizes of 54, 27, and 2.8 m. Results indicate that, with the proper choices, even models characterized by very significant scaling factors can accurately match several key performance indicators. Additionally, when an exact match is not possible, relevant trends can at least be captured.

17 WIND ENERGY↗
NASA NTRS1993

Formulation for Simultaneous Aerodynamic Analysis and Design Optimization

An efficient approach for simultaneous aerodynamic analysis and design optimization is presented. This approach does not require the performance of many flow analyses at each design optimization step, which can be an expensive procedure. Thus, this approach brings us one step closer to meeting the challenge of incorporating computational fluid dynamic codes into gradient-based optimization techniques for aerodynamic design. An adjoint-variable method is introduced to nullify the effect of the increased number of design variables in the problem formulation. The method has been successfully tested on one-dimensional nozzle flow problems, including a sample problem with a normal shock. Implementations of the above algorithm are also presented that incorporate Newton iterations to secure a high-quality flow solution at the end of the design process. Implementations with iterative flow solvers are possible and will be required for large, multidimensional flow problems.

Hou, G. W.↗
NASA NTRS2018

Application of a Knowledge-Based Optimization Method for Aerodynamic Design

The current research is investigating the application of an optimization technique to an existing knowledge-based design tool. The optimization method, referred to as CODISC, helps improve the results from a knowledge-based design by eliminating the required advanced design knowledge, or help fine-tune a well-performing vehicle. Three CODISC designs are presented using a generic transonic transport, the Common Research Model (CRM). One design optimizes the baseline CRM to demonstrate the ability to improve a well-performing vehicle. Another design is performed from the CRM with camber and twist removed, which highlights the ability to use CODISC in the conceptual design phase. The final design implements laminar flow on the CRM, showing how CODISC can optimize the extent of laminar flow to find the best aerodynamic performance. All three CODISC designs reduced the vehicle drag compared to the baseline CRM, and highlight the new optimization technique’s versatility in the aircraft design industry.

CODISC↗
NASA NTRS1977

Ramjet propulsion for single-stage-to-orbit vehicles

The concept of single stage earth-to-orbit transportation is studied with respect to existing and projected ramjet technology. Four types of ramjet are analyzed: fan ejector, fan ramjet, supersonic combustion ramjet, and fan ramjet with turbojet boosters. A fan ramjet with a removable fan, with separate rockets for the non-air-breathing flight phase, is considered superior to an ejector ramjet, for both ease of orbit insertion and payload boost capability. Vehicle design is also discussed in terms of trajectory integration and optimization, aerodynamic trim and stability, and complete mass estimation. Graphs are presented showing Mach number for air-breathing and non-air-breathing flight, specific impulse from various ramjet engines, and orbital-insertion parameters.

Martin, J. A.↗
NASA NTRS1992

Practical considerations in waverider applications

This paper proposes a practical perspective for waverider shapes with respect to their use in the commercial and military aerospace industry. Also, integration problems that must be considered when deriving these shapes for operational aircraft are discussed and general approaches to solving them are suggested. The inverse design methodology that is used to generate waverider geometries is discussed as a potentially powerful tool for the aerospace industry in the design of practical operational high-speed (Mach 4 to 25) aircraft. Further, it is suggested that unless this methodology proves to be a valuable tool in the near future, it will not likely find a customer in the aerospace industry and may become no more than an interesting academic study in aerodynamic optimization.

Stevens, Daniel R.↗
NASA NTRS1994

Preconditioned domain decomposition scheme for three-dimensional aerodynamic sensitivity analysis

A discrete sensitivity analysis algorithm had previously been developed and applied to two-dimensional aerodynamic optimization problems, where the computational domains were discretized by using single grids. The sparse, unsymmetric systems of linear equations resulting from this algorithm were solved by a direct matrix inversion matrix. However, for large two-dimensional problems and, practically, all three-dimensional problems, direct inversion methods become inapplicable, primarily due to the prohibitive computer storage needed. In an attempt to alleviate such hindrances, the sensitivity analysis with domain decomposition (SADD) scheme was developed. This scheme divides the computational domain into smaller and nonoverlapping subdomains (multiblock grids) that are solved separately. Then, the final solution is constructed from the subdomain solutions. As the number of grid points in the interface boundaries of the subdomains becomes large, the computer memory required to store the effective coefficient matrix of these interface points starts to increase. Presented in this Technical Note is a preconditioned iterative procedure to overcome this particular problem.

Eleshaky, Mohamed E.↗
NASA NTRS1995

Parallel CFD design on network-based computer

Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

Cheung, Samson↗