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At least 109 records · Page 6

Optimal Control Design Using an H2 Method for the Glovebox Integrated Microgravity Isolation Technology (g-LIMIT)

The acceleration environment on the International Space Station (ISS) will likely exceed the requirements of many micro-gravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) is being built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for micro-gravity science experiments. G-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform for mounting science payloads from the nominal acceleration environment. The system utilizes payload acceleration, relative position, and relative orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current command to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. This paper presents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for both frequency-weighted H(sub 2) and H(sub infinity) norms. Comparison of the performance and robustness to plant uncertainty for these two optimal control design approaches are included in the discussion.

Calhoun, Phillip C.↗

Surrogate Modeling and Optimization of a Combustor with an Interdigitated Flushwall Injector

Design and Analysis of Computer Experiments (DACE) methods are applied and used to perform surrogate modeling and optimization of a simplified combustor flowpath with an interdigitated flushwall injector. The objectives of the optimization are the thrust potential and combustion efficiency, which are evaluated across a range of flight Mach numbers, duct heights, spanwise spacings, and injection angles. The focus of this work is to highlight the application of a sequential learning approach, in order to learn about the responses of the objective functions over the design space and to identify local regions of interest for further analysis. This approach is contrasted to a previous effort where only a single sampling set was used to fit surrogate models and perform optimization. The optimal solutions resulting from the previous and present approaches are different, due to surrogate model-guided local refinement of the design space allowed by the sequential learning method. The values of the global error estimates between the previous and present approaches are comparable, but the sequential method proved more computationally cost-effective. Further refinement in the optimal regions might be needed to improve predictive capability of surrogate models and to obtain the optimal solutions sets.

Rajiv R Shenoy↗

Optimal design of a thermally stable composite optical bench

The Lidar Atmospheric Sensing Experiment will be performed aboard an ER-2 aircraft; the lidar system used will be mounted on a lightweight, thermally stable graphite/epoxy optical bench whose design is presently subjected to analytical study and experimental validation. Attention is given to analytical methods for the selection of such expected laminate properties as the thermal expansion coefficient, the apparent in-plane moduli, and ultimate strength. For a symmetric laminate in which one of the lamina angles remains variable, an optimal lamina angle is selected to produce a design laminate with a near-zero coefficient of thermal expansion. Finite elements are used to model the structural concept of the design, with a view to the optical bench's thermal structural response as well as the determination of the degree of success in meeting the experiment's alignment tolerances.

Gray, C. E., Jr.↗

Optimal Control Design using an H(sub 2) Method for the Glovebox Integrated Microgravity Isolation Technology (G-Limit)

The acceleration environment on the International Space Station (ISS) will likely exceed the requirements of many micro-gravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) is being built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for microgravity science experiments. G-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform for mounting science payloads from the nominal acceleration environment. The system utilizes payload acceleration, relative position, and relative orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current commands to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. This paper presents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for frequency-weighted H(sub 2) norms. Comparison of the performance and robustness to plant uncertainty for this control design approach is included in the discussion.

Calhoun, Philip C.↗

Development of a digital adaptive optimal linear regulator flight controller

Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.

Berry, P.↗

The future United States space program; Proceedings of the Twenty-fifth Anniversary Conference, Houston, Tex., October 30-November 2, 1978. Parts 1 & 2

Space Shuttle guidance problems, solar power satellites, space law, satellite communications, space medicine, and engineering of large space systems are discussed. Topics of the papers include biological experiments designed for the Space Shuttle, an optimized guidance law for Space Shuttle re-entry, aircraft propulsion based on laser energy, industrial materials available in the lunar soil, health programs for a solar power satellite construction team, closed life support systems for large habitats in space, the advantages of a manned mission to Mars, the interpretation of radar imagery of Venus, a cost analysis for the satellite power system, and the geological history of Mars.

Johnston, R. S.↗

Fundamental results from microgravity cell experiments with possible commericial applications

Some of the major milestones are presented for studies in cell biology that were conducted by the Soviet Union and the United States in the upper layers of the atmosphere and in outer space for more than thirty-five years. The goals have changed as new knowledge is acquired and the priorities for the use of microgravity have shifted toward basic research and commercial applications. Certain details concerning the impact of microgravity on cell systems is presented. However, it needs to be emphasized that in planning and conducting microgravity experiments, there are some important prerequisites not normally taken into account. Apart from the required background knowledge of previous microgravity and ground-based experiments, the investigator should have the understanding of the hardware as a physical unit, the complete knowledge of its operation, the range of its capabilities and the anticipation of problems that may occur. Moreover, if the production of commercial products in space is to be manifested, data obtained from previous microgravity experiments must be used to optimize the design of flight hardware.

Winget, Charles M.↗

Inverse problems in the design, modeling and testing of engineering systems

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Alifanov, Oleg M.↗

On-orbit parametric identification methodology

On-orbit system identification (ID) of large space systems is essential for various reasons. For example, the complex composite structure of such systems cannot be ground-tested; their structural dynamic characteristics must be known accurately in order to accomplish active control. Furthermore, such capability can be used to characterize/identify various disturbances. The identification process is consisted of four principal elements: (1) modeling, (2) the estimation algorithm, (3) input system, and (4) measurement system. These elements are highly correlated and all togerher determine the success of the identification problem. Accurate modeling of large space systems is the most important element of the identification process. Large flexible structures are non-linear and infinite dimensional systems with highly coupled parameters and low frequency packed modes. In addition, these systems are subject to stochastic and time-varying disturbances, they have structural parameters which can vary due to on-orbit assembly deployment, and operations. These systems are generally; however, represented by constant coefficient, finite order differential equations. The non-linearities, coupling and noise effects are also often neglected. Moreover, identification experiment designs which lead to highly complex optimization problems usually require the simultaneous choice of ID algorithm, sensor, and actuator type and placement. On-orbit bandwidth and power restrictions on excitation, limited data window, and restrictions on sensor/actuator type, placement and number, has led to practical questions of implementations.

Hadaegh, Fred Y.↗

Recent Progress on the VASIMR

Experimental and theoretical studies on the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) have continued through a NASA led collaborative program involving several research groups. In the experimental area, performance characterization of the VASIMR helicon plasma source has been obtained over a portion of the parameter space, with helium and hydrogen propellant. Density (10(exp 18) - 10(exp 19)/ cubic meter) and temperature (5 eV) were measured at moderate degree of ionization in two separate experimental devices. Helicon design improvement and optimization will be discussed. Experiments with the ion cyclotron resonance heating (ICRH) subsection have begun and preliminary results will be discussed. Theoretical picture and integrated numerical simulation continue to be refined to account for the main physics elements of the VASIMR, including RF absorption and particle acceleration with subsequent detachment in the magnetic nozzle.

ChangDiaz, Franklin R.↗

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Shyy, Wei↗

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↗

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↗

Multidisciplinary Optimization Branch Experience Using iSIGHT Software

The Multidisciplinary Optimization (MDO) Branch at NASA Langley Research Center is investigating frameworks for supporting multidisciplinary analysis and optimization research. An optimization framework call improve the design process while reducing time and costs. A framework provides software and system services to integrate computational tasks and allows the researcher to concentrate more on the application and less on the programming details. A framework also provides a common working environment and a full range of optimization tools, and so increases the productivity of multidisciplinary research teams. Finally, a framework enables staff members to develop applications for use by disciplinary experts in other organizations. Since the release of version 4.0, the MDO Branch has gained experience with the iSIGHT framework developed by Engineous Software, Inc. This paper describes experiences with four aerospace applications: (1) reusable launch vehicle sizing, (2) aerospike nozzle design, (3) low-noise rotorcraft trajectories, and (4) acoustic liner design. All applications have been successfully tested using the iSIGHT framework, except for the aerospike nozzle problem, which is in progress. Brief overviews of each problem are provided. The problem descriptions include the number and type of disciplinary codes, as well as all estimate of the multidisciplinary analysis execution time. In addition, the optimization methods, objective functions, design variables, and design constraints are described for each problem. Discussions on the experience gained and lessons learned are provided for each problem. These discussions include the advantages and disadvantages of using the iSIGHT framework for each case as well as the ease of use of various advanced features. Potential areas of improvement are identified.

Padula, S. L.↗

Shape Memory Alloy Actuator Design: CASMART Collaborative Best Practices

Upon examination of shape memory alloy (SMA) actuation designs, there are many considerations and methodologies that are common to them all. A goal of CASMART's design working group is to compile the collective experiences of CASMART's member organizations into a single medium that engineers can then use to make the best decisions regarding SMA system design. In this paper, a review of recent work toward this goal is presented, spanning a wide range of design aspects including evaluation, properties, testing, modeling, alloy selection, fabrication, actuator processing, design optimization, controls, and system integration. We have documented each aspect, based on our collective experiences, so that the design engineer may access the tools and information needed to successfully design and develop SMA systems. Through comparison of several case studies, it is shown that there is not an obvious single, linear route a designer can adopt to navigate the path of concept to product. SMA engineering aspects will have different priorities and emphasis for different applications.

Benafan, Othmane↗

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 input design for aircraft instrumentation systematic error estimation

A new technique for designing optimal flight test inputs for accurate estimation of instrumentation systematic errors was developed and demonstrated. A simulation model of the F-18 High Angle of Attack Research Vehicle (HARV) aircraft was used to evaluate the effectiveness of the optimal input compared to input recorded during flight test. Instrumentation systematic error parameter estimates and their standard errors were compared. It was found that the optimal input design improved error parameter estimates and their accuracies for a fixed time input design. Pilot acceptability of the optimal input design was demonstrated using a six degree-of-freedom fixed base piloted simulation of the F-18 HARV. The technique described in this work provides a practical, optimal procedure for designing inputs for data compatibility experiments.

Morelli, Eugene A.↗