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At least 73 records · Page 4

System Synthesis in Preliminary Aircraft Design Using Statistical Methods

This paper documents an approach to conceptual and early preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically Design of Experiments (DOE) and Response Surface Methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an Overall Evaluation Criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in an innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting in solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a High Speed Civil Transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabilistic designs (and eventually robust ones).

DeLaurentis, Daniel↗

Transonic Dynamics Tunnel Force and Pressure Data Acquired on the HSR Rigid Semispan Model

This report describes the aerodynamic data acquired on the High Speed Research Rigid Semispan Model (HSR-RSM) during NASA Langley Transonic Dynamics Tunnel (TDT) Test 520 conducted from 18 March to 4 April, 1996. The purpose of this test was to assess the aerodynamic character of a rigid high speed civil transport wing. The wing was fitted with a single trailing edge control surface which was both steadily deflected and oscillated during the test to investigate the response of the aerodynamic data to steady and unsteady control motion. Angle-of-attack and control surface deflection polars at subsonic, transonic and low-supersonic Mach numbers were obtained in the tunnel?s heavy gas configuration. Unsteady pressure and steady loads data were acquired on the wing, while steady pressures were measured on the fuselage. These data were reduced using a variety of methods, programs and computer systems. The reduced data was ultimately compiled onto a CD-ROM volume which was distributed to HSR industry team members in July, 1996. This report documents the methods used to acquire and reduce the data, and provides an assessment of the quality, repeatability, and overall character of the aerodynamic data measured during this test.

Schuster, David M.↗

Integration of the Response Surface Methodology with the Compromise Decision Support Problem in Developing a General Robust Design Procedure

In this paper we introduce a comprehensive and rigorous robust design procedure to overcome some limitations of the current approaches. A comprehensive approach is general enough to model the two major types of robust design applications, namely, robust design associated with the minimization of the deviation of performance caused by the deviation of noise factors (uncontrollable parameters), and robust design due to the minimization of the deviation of performance caused by the deviation of control factors (design variables). We achieve mathematical rigor by using, as a foundation, principles from the design of experiments and optimization. Specifically, we integrate the Response Surface Method (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example. Our focus in this paper is on illustrating our approach rather than on the results per se.

Chen, Wei↗

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Vaidyanathan, Rajkumar↗

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.

Papila, Nilay↗

Global Optimization Techniques for Fluid Flow and Propulsion Devices

This viewgraph presentation gives an overview of global optimization techniques for fluid flow and propulsion devices. Details are given on the need, characteristics, and techniques for global optimization. The techniques include response surface methodology (RSM), neural networks and back-propagation neural networks, design of experiments, face centered composite design (FCCD), orthogonal arrays, outlier analysis, and design optimization.

Shyy, Wei↗

Characterization of Truncated Tumor-Associated NADH Oxidase (ttNOX)

Bacterial, plant and animal cells possess novel surface proteins that exhibit both NADH oxidation (NOX) or hydroquinone and protein disulfide-thiol interchange. These enzymatic activities alternate to yield oscillating patterns wjth period lengths of approximately 24 minutes. The catalytic period of NOX proteins are temperature compensated and gravity responsive. We report the cloning, expression and characterization of truncated tumor-associated NADH oxidase (ttNOX), in which the membrane spanning region has been deleted. The cDNA (originated from HeLa cells) was cloned into pET-34b and pET-14b (Novagen) vectors for E. coli expression. Optimized expression and purification protocols yielded greater than 300mg per liter of culture with greater than 95% purity. Circular dichroism data was collected from a 2.7mg/ml solution in a 0.1mm cuvette with variable scanning using an Olis RSM CD spectrophotometer. The ellipticity values were scanned from 190 to 260nm. The spectra recorded have characteristics for alpha proteins with band maxima at 216nm and a possible shoulder at 212nm at 12OC and 250 C. Protein crystal screens are in progress and, to date, only small crystals have been observed. The regular periodic oscillatory change in the ttNOX protein is indicative of a possible time-keeping functional role. A single protein possessing alternating catalytic activities, with a potential biological clock function, is unprecedented and structural determination is paramount to understanding this role.

Karr, Laurel J.↗

Management of Total Pressure Recovery, Distortion and High Cycle Fatigue in Compact Air Vehicle Inlets

It is the purpose of this study to demonstrate the viability and economy of Response Surface Methods (RSM) and Robustness Design Concepts (RDC) to arrive at micro-secondary flow control installation designs that maintain optimal inlet performance over a range of the mission variables. These statistical design concepts were used to investigate the robustness properties of 'low unit strength' micro-effector installations. 'Low unit strength' micro-effectors are micro-vanes set at very low angles-of-incidence with very long chord lengths. They were designed to influence the near wall inlet flow over an extended streamwise distance, and their advantage lies in low total pressure loss and high effectiveness in managing engine face distortion.

Anderson, Bernhard H.↗

Design-of-experiments to Reduce Life-cycle Costs in Combat Aircraft Inlets

It is the purpose of this study to demonstrate the viability and economy of Design- of-Experiments (DOE), to arrive at micro-secondary flow control installation designs that achieve optimal inlet performance for different mission strategies. These statistical design concepts were used to investigate the properties of "low unit strength" micro-effector installation. "Low unit strength" micro-effectors are micro-vanes, set a very low angle-of incidence, with very long chord lengths. They are designed to influence the neat wall inlet flow over an extended streamwise distance. In this study, however, the long chord lengths were replicated by a series of short chord length effectors arranged in series over multiple bands of effectors. In order to properly evaluate the performance differences between the single band extended chord length installation designs and the segmented multiband short chord length designs, both sets of installations must be optimal. Critical to achieving optimal micro-secondary flow control installation designs is the understanding of the factor interactions that occur between the multiple bands of micro-scale vane effectors. These factor interactions are best understood and brought together in an optimal manner through a structured DOE process, or more specifically Response Surface Methods (RSM).

Anderson, Bernhard H.↗

Design and Analysis of Turbines for Space Applications

In order to mitigate the risk of rocket propulsion development, efficient, accurate, detailed fluid dynamics analysis of the turbomachinery is necessary. This analysis is used for component development, design parametrics, performance prediction, and environment definition. To support this requirement, a task was developed at NASAh4arshall 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. The redesign of the turbine was conducted with a consideration of system requirements, realizing that a highly efficient turbine that, for example, significantly increases engine weight, is of limited benefit. Both preliminary and detailed designs were considered. To generate an improved design, one-dimensional (1D) design and analysis tools, computational fluid dynamics (CFD), response surface methodology (RSM), and neural nets (NN) were used.

Griffin, Lisa W.↗

Method for Constructing Composite Response Surfaces by Combining Neural Networks with other Interpolation or Estimation Techniques

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

Rai, Man Mohan↗

Optimal Micro-Jet Flow Control for Compact Air Vehicle Inlets

The purpose of this study on micro-jet secondary flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to optimally design micro-jet secondary flow control arrays, and to establish that the aeromechanical effects of engine face distortion can also be included in the design and optimization process. These statistical design concepts were used to investigate the design characteristics of "low mass" micro-jet array designs. The term "low mass" micro-jet may refers to fluidic jets with total (integrated) mass flow ratios between 0.10 and 1.0 percent of the engine face mass flow. Therefore, this report examines optimal micro-jet array designs for compact inlets through a Response Surface Methodology.

Anderson, Bernhard H.↗

Optimal Micro-Vane Flow Control for Compact Air Vehicle Inlets

The purpose of this study on micro-vane secondary flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to optimally design micro-vane secondary flow control arrays, and to establish that the aeromechanical effects of engine face distortion can also be included in the design and optimization process. These statistical design concepts were used to investigate the design characteristics of "low unit strength" micro-effector arrays. "Low unit strength" micro-effectors are micro-vanes set at very low angles-of-incidence with very long chord lengths. They were designed to influence the near wall inlet flow over an extended streamwise distance, and their advantage lies in low total pressure loss and high effectiveness in managing engine face distortion. Therefore, this report examines optimal micro-vane secondary flow control array designs for compact inlets through a Response Surface Methodology.

Anderson, Bernhard H.↗

Identification of Experimental Unsteady Aerodynamic Impulse Responses

The identification of experimental unsteady aerodynamic impulse responses using the Oscillating Turntable (OTT) at NASA Langley's Transonic Dynamics Tunnel (TDT) is described. Results are presented for two configurations: a Rigid Semispan Model (RSM) and a rectangular wing with a supercritical airfoil section. Both models were used to acquire unsteady pressure data due to pitching oscillations on the OTT. A deconvolution scheme involving a step input in pitch and the resultant step response in pressure, for several pressure transducers, is used to identify the pressure impulse responses. The identified impulse responses are then used to predict the pressure response due to pitching oscillations at several frequencies. Comparisons with the experimental data are presented.

Silva, Walter A.↗

Black Box Testing: Experiments with Runway Incursion Advisory Alerting System

This report summarizes our research findings on the Black box testing of Runway Incursion Advisory Alerting System (RIAAS) and Runway Safety Monitor (RSM) system. Developing automated testing software for such systems has been a problem because of the extensive information that has to be processed. Customized software solutions have been proposed. However, they are time consuming to develop. Here, we present a less expensive, and a more general test platform that is capable of performing complete black box testing. The technique is based on the classification of the anomalies that arise during Monte Carlo simulations. In addition, we also discuss a generalized testing tool (prototype) that we have developed.

Mukkamala, Ravi↗

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

Optimal Control of Shock Wave Turbulent Boundary Layer Interactions Using Micro-Array Actuation

The intent of this study on micro-array flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to determine optimal designs of micro-array actuation for controlling the shock wave turbulent boundary layer interactions within supersonic inlets and compare these concepts to conventional bleed performance. The term micro-array refers to micro-actuator arrays which have heights of 25 to 40 percent of the undisturbed supersonic boundary layer thickness. This study covers optimal control of shock wave turbulent boundary layer interactions using standard micro-vane, tapered micro-vane, and standard micro-ramp arrays at a free stream Mach number of 2.0. The effectiveness of the three micro-array devices was tested using a shock pressure rise induced by the 10 shock generator, which was sufficiently strong as to separate the turbulent supersonic boundary layer. The overall design purpose of the micro-arrays was to alter the properties of the supersonic boundary layer by introducing a cascade of counter-rotating micro-vortices in the near wall region. In this manner, the impact of the shock wave boundary layer (SWBL) interaction on the main flow field was minimized without boundary bleed.

Anderson, Bernhard H.↗

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

Rai, Man Mohan↗