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At least 19 records

Crew optimized Shuttle/experiment pointing

The extensive participation of the Shuttle crewmembers (Commander, Pilot, Mission Specialist, and Payload Specialist) in Shuttle/experiment pointing is required to accomplish and enhance payload pointing operations and to optimize associated data collection. For payloads requiring extensive pointing operations, the degree of mission success which can be achieved by the involvement of the crew can not be matched by a combination of remote ground operations and automation. The importance of the use of the crew's manipulative skills, scientific judgment, and flexibility in the alteration of preplanned time lines was clearly demonstrated during the Skylab Apollo Telescope Mount solar experiment operations. The payload pointing operations associated with the Spacelab Instrument Pointing System and the Annular Suspension and Pointing System Gimbal System will also extensively use these crew capabilities. Crew operations will also play a potentially important role in the use of advanced pointing systems to accurately point experiments which have an extensive interaction with the surrounding environment, such as laser experiments.

Holt, A. C.↗

Free-form Airfoil Shape Optimization Under Uncertainty Using Maximum Expected Value and Second-order Second-moment Strategies

Free-form shape optimization of airfoils poses unexpected difficulties. Practical experience has indicated that a deterministic optimization for discrete operating conditions can result in dramatically inferior performance when the actual operating conditions are different from the - somewhat arbitrary - design values used for the optimization. Extensions to multi-point optimization have proven unable to adequately remedy this problem of "localized optimization" near the sampled operating conditions. This paper presents an intrinsically statistical approach and demonstrates how the shortcomings of multi-point optimization with respect to "localized optimization" can be overcome. The practical examples also reveal how the relative likelihood of each of the operating conditions is automatically taken into consideration during the optimization process. This is a key advantage over the use of multipoint methods.

Huyse, Luc↗

Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range

We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler flow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.

Li, Wu↗

Estimation of the global average temperature with optimally weighted point gauges

This paper considers the minimum mean squared error (MSE) incurred in estimating an idealized Earth's global average temperature with a finite network of point gauges located over the globe. We follow the spectral MSE formalism given by North et al. (1992) and derive the optimal weights for N gauges in the problem of estimating the Earth's global average temperature. Our results suggest that for commonly used configurations the variance of the estimate due to sampling error can be reduced by as much as 50%.

Hardin, James W.↗

A transmittance-optimized, point-focus Fresnel lens solar concentrator

The development of a point-focus Fresnel lens solar concentrator for high-temperature solar thermal energy system applications is discussed. The concentrator utilizes a transmittance-optimized, short-focal-length, dome-shaped refractive Fresnel lens as the optical element. This concentrator combines both good optical performance and a large tolerance for manufacturing, deflection, and tracking errors. The conceptual design of an 11-meter diameter concentrator which should provide an overall collector efficiency of about 70% at an 815 C (1500 F) receiver operating temperature and a 1500X geometric concentration ratio (lens aperture area/receiver aperture area) was completed. Results of optical and thermal analyses of the collector, a discussion of manufacturing methods for making the large lens, and an update on the current status and future plans of the development program are included.

Oneill, M. J.↗

A Transmittance-optimized, Point-focus Fresnel Lens Solar Concentrator

The development of a point-focus Fresnel lens solar concentrator for high-temperature solar thermal energy system applications is discussed. The concentrator utilizes a transmittance-optimized, short-focal-length, dome-shaped refractive Fresnel lens as the optical element. This concentrator combines both good optical performance and a large tolerance for manufacturing, deflection, and tracking errors. The conceptual design of an 11-meter diameter concentrator which should provide an overall collector efficiency of about 70% at an 815 C (1500 F) receiver operating temperature and a 1500X geometric concentration ratio (lens aperture area/receiver aperture area) was completed. Results of optical and thermal analyses of the collector, a discussion of manufacturing methods for making the large lens, and an update on the current status and future plans of the development program are included.

Oneill, M. J.↗

Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

Mehr, Ali Farhang↗

Experimental Investigation of a Point Design Optimized Arrow Wing HSCT Configuration

The M2.4-7A Arrow Wing HSCT configuration was optimized for straight and level cruise at a Mach number of 2.4 and a lift coefficient of 0.10. A quasi-Newton optimization scheme maximized the lift-to-drag ratio (by minimizing drag-to-lift) using Euler solutions from FL067 to estimate the lift and drag forces. A 1.675% wind-tunnel model of the Opt5 HSCT configuration was built to validate the design methodology. Experimental data gathered at the NASA Langley Unitary Plan Wind Tunnel (UPWT) section #2 facility verified CFL3D Euler and Navier-Stokes predictions of the Opt5 performance at the design point. In turn, CFL3D confirmed the improvement in the lift-to-drag ratio obtained during the optimization, thus validating the design procedure. A data base at off-design conditions was obtained during three wind-tunnel tests. The entry into NASA Langley UPWT section #2 obtained data at a free stream Mach number, M(sub infinity), of 2.55 as well as the design Mach number, M(sub infinity)=2.4. Data from a Mach number range of 1.8 to 2.4 was taken at UPWT section #1. Transonic and low supersonic Mach numbers, M(sub infinity)=0.6 to 1.2, was gathered at the NASA Langley 16 ft. Transonic Wind Tunnel (TWT). In addition to good agreement between CFD and experimental data, highlights from the wind-tunnel tests include a trip dot study suggesting a linear relationship between trip dot drag and Mach number, an aeroelastic study that measured the outboard wing deflection and twist, and a flap scheduling study that identifies the possibility of only one leading-edge and trailing-edge flap setting for transonic cruise and another for low supersonic acceleration.

Narducci, Robert P.↗

Applying Dynamical Systems Theory to Optimize Libration Point Orbit Stationkeeping Maneuvers for WIND

NASA's WIND mission has been operating in a large amplitude Lissajous orbit in the vicinity of the interior libration point of the Sun-Earth/Moon system since 2004. Regular stationkeeping maneuvers are required to maintain the orbit due to the instability around the collinear libration points. Historically these stationkeeping maneuvers have been performed by applying an incremental change in velocity, or (delta)v along the spacecraft-Sun vector as projected into the ecliptic plane. Previous studies have shown that the magnitude of libration point stationkeeping maneuvers can be minimized by applying the (delta)v in the direction of the local stable manifold found using dynamical systems theory. This paper presents the analysis of this new maneuver strategy which shows that the magnitude of stationkeeping maneuvers can be decreased by 5 to 25 percent, depending on the location in the orbit where the maneuver is performed. The implementation of the optimized maneuver method into operations is discussed and results are presented for the first two optimized stationkeeping maneuvers executed by WIND.

WIND↗

Optimal fine pointing control of a large space telescope using an Annular Momentum Control Device

This paper discusses the application of an Annular Momentum Control Device (AMCD) to fine pointing control of a large space telescope (LST). The AMCD represents a new development in the field of momentum storage devices. A linearized mathematical model is developed for the AMCD/LST system, including the magnetic suspension actuators. Two approaches to control system design are considered. The first approach uses a stochastic linear-quadratic Gaussian controller which utilizes feedback of all states. The second approach considers a more practical control system design in which the axial and radial loops are designed independently.

Nadkarni, A. A.↗

Optimal nodal point distribution for improved accuracy in computational fluid dynamics

In applying finite-difference techniques to flow field problems, the accuracy attained for a fixed number of node points can be improved using unequally-spaced node points. The distribution of these node points is chosen here by minimizing a measure of local truncation error with respect to the parameters which define a transformation between the computational space of equally-spaced node points and the physical space of unequally-spaced node points. The problem then becomes a nonlinear programming problem. Numerical results are presented for two one-dimensional test problems: the Blasius boundary layer problem and the inviscid Burgers' equation.

Pierson, B. L.↗

Defining optimal point-to-point transfer surfaces for orbital path-constrained rendezvous

Many scenarios for future orbital operations involve maneuvering in proximity to such large space structures as the Space Station Freedom; in most cases, the accidental contact of a vehicle with such a structure will be dangerous and must be avoided. Classical rendezvous targeting is inadequate for this purpose, because it recognizes no restraint on the path between the point of departure and the desired point of arrival. A computer program has been devised to minimize this susceptibility. Surfaces are found to exist whose penalty is less than that of a sphere, though not markedly less.

Soileau, Kerry M.↗

Options for Robust Airfoil Optimization under Uncertainty

A robust optimization method is developed to overcome point-optimization at the sampled design points. This method combines the best features from several preliminary methods proposed by the authors and their colleagues. The robust airfoil shape optimization is a direct method for drag reduction over a given range of operating conditions and has three advantages: (1) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (2) it uses a large number of spline control points as design variables yet the resulting airfoil shape does not need to be smoothed, and (3) it allows the user to make a tradeoff between the level of optimization and the amount of computing time consumed. For illustration purposes, the robust optimization method is used to solve a lift-constrained drag minimization problem for a two-dimensional (2-D) airfoil in Euler flow with 20 geometric design variables.

Padula, Sharon L.↗

Flight Planning

Seagull Technology, Inc., Sunnyvale, CA, produced a computer program under a Langley Research Center Small Business Innovation Research (SBIR) grant called STAFPLAN (Seagull Technology Advanced Flight Plan) that plans optimal trajectory routes for small to medium sized airlines to minimize direct operating costs while complying with various airline operating constraints. STAFPLAN incorporates four input databases, weather, route data, aircraft performance, and flight-specific information (times, payload, crew, fuel cost) to provide the correct amount of fuel optimal cruise altitude, climb and descent points, optimal cruise speed, and flight path.

Source record↗

Optimization on a Network-based Parallel Computer System for Supersonic Laminar Wing Design

A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.

Garcia, Joseph A.↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗