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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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At least 127 records · Page 7

Procedures for shape optimization of gas turbine disks

Two procedures, the feasible direction method and sequential linear programming, for shape optimization of gas turbine disks are presented. The objective of these procedures is to obtain optimal designs of turbine disks with geometric and stress constraints. The coordinates of the selected points on the disk contours are used as the design variables. Structural weight, stress and their derivatives with respect to the design variables are calculated by an efficient finite element method for design senitivity analysis. Numerical examples of the optimal designs of a disk subjected to thermo-mechanical loadings are presented to illustrate and compare the effectiveness of these two procedures.

Cheu, Tsu-Chien↗

Electromagnetic analysis for large reflector antennas

A comparison is made between the measured E and H plane patterns of the 35 GHz offset paraboloidal reflector and the calculated patterns for the same reflector using the 200 points to describe the surface. The accuracy of the computer prediction is quite good considering that the only description of the surface was the coordinates of a finite number of points on the reflector. The results indicate the possibility of acceptable accuracy in the prediction of electromagnetic performance for arbitrarily distorted reflectors using the coordinates of a practical number of measured points. An optimization of the number and distribution of points, and experimental verification for a distorted reflector are planned.

Bailey, M. C.↗

Logistics and operations integration requirements to support Space Station servicing of free flying spacecraft - OMV flight operation

The logistics of OMV free-flyer servicing are examined, with emphasis on integrating the OMV operations into the overall STS-Space Station system. The depletion rate of consumables and lifetimes of free-flyer components are known quantities, which permits definition of a predictable maintenance schedule. Servicing with an OMV will depend on the position and capabilities of the OMV, Shuttle and Station when free-flyer maintenance is needed. Optimized orbital servicing of free-flyers will involve coordination of and resolution of schedule conflicts among STS, the OMV and the Station. The scheduled availability of any of the three components will be predicted in terms of probabilities that any one of the components will not be needed for another mission while performing the mission they are on.

Bell, Jerome A.↗

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

Telban, Robert J.↗

Efficient Trajectory Propagation for Orbit Determination Problems

Regularized formulations of orbital motion apply a series of techniques to improve the numerical integration of the orbit. Despite their advantages and potential applications little attention has been paid to the propagation of the partial derivatives of the corresponding set of elements or coordinates, required in many orbit-determination scenarios and optimization problems. This paper fills this gap by presenting the general procedure for integrating the state-transition matrix of the system together with the nominal trajectory using regularized formulations and different sets of elements. The main difficulty comes from introducing an independent variable different from time, because the solution needs to be synchronized. The correction of the time delay is treated from a generic perspective not focused on any particular formulation. The synchronization using time-elements is also discussed. Numerical examples include strongly-perturbed orbits in the Pluto system, motivated by the recent flyby of the New Horizons spacecraft, together with a geocentric flyby of the NEAR spacecraft.

numerical methods↗

Sequential filtering applied to the determination of tracking station locations

The extended sequential filter has been applied to the problem of dynamically determining the geocentric coordinates of two laser satellite tracking stations. This filter provides significant advantages over the classical batch methods through (1) fewer iterations required for convergence, (2) wider radius of convergence, and (3) availability of the parameter estimate evolution. Processing the data sequentially readily identifies the data arcs required to minimize the effects of geopotential model errors. By means of the Smithsonian standard earth 2 and the Goddard earth model 1 geopotentials to reduce laser range observations of the Beacon Explorer-C satellite, it is demonstrated that a two-pass arc is optimal for estimating the height of one station and all coordinates of the second station while minimizing the effect of geopotential model error. These two-pass estimates are in good agreement with other determinations that utilize considerably more data as well as different satellites.

Schutz, B. E.↗

New Approaches to Multidisciplinary Design and Optimization

Research under the subject grant is being carried out in a jointly coordinated effort within three laboratories in the School of Aerospace Engineering and the George Woodruff School of Mechanical Engineering. The objectives and results for Year 2 of the research program are summarized. The "Objectives" and "Expected Significance" are taken directly from the Year 2 Proposal presented in October 1994, and "Results" summarize the what has been accomplished this year. A discussion of these results is provided in the following sections. A listing of papers, presentations and reports that acknowledge grant support, either in part or in whole, and that were prepared during this period is provided in an attachment.

Schrage, D. P.↗

Optimal detumbling of a large manned spacecraft using an internal moving mass

This investigation deals with the use of a movable mass control system to stabilize a tumbling asymmetric spacecraft about the maximum inertia axis. A first-order gradient optimization technique is used to minimize angular velocity components along the intermediate and minimum inertia axes, thus, permitting a wide range of initial guesses for mass position history. Motion of the control mass is along a linear track fixed in the vehicle. The control variable is taken as mass acceleration with respect to body coordinates. Motion is limited to defined quantities and a penalty function is used to insure a given range of positions. Numerical solutions of the optimization equations verify that minimum time detumbling is achieved with the largest permissible movable mass, length of linear track, and positions of the mass on the two coordinates perpendicular to the linear motion. The optimal method permits detumbling in about one-fourth the time when compared to a force control law formulation available in the literature.

Kunciw, B. G.↗

Psychophysiological Monitoring of Aerospace Crew State

As next-generation space exploration missions necessitate increasingly autonomous systems, there is a critical need to better detect and anticipate crewmember interactions with these systems. The success of present and future autonomous technology in exploration spaceflight is ultimately dependent upon safe and efficient interaction with the human operator. Optimal interaction is particularly important for surface missions during highly coordinated extravehicular activity (EVA), which consists of high physical and cognitive demands with limited ground support. Crew functional state may be affected by a number of variables including workload, stress, and motivation. Real-time assessments of crew state that do not require a crewmember’s time and attention to complete will be especially important to assess operational performance and behavioral health during flight. In response to the need for objective, passive assessment of crew state, the aim of this work is to develop an accurate and precise prediction model of human functional state for surface EVA using multi-modal psychophysiological sensing. The psychophysiological monitoring approach relies on extracting a set of features from physiological signals and using these features to classify an operator’s cognitive state. This work aims to compile a non-invasive sensor suite to collect physiological data in real-time. Training data during cognitive and more complex functional tasks will be used to develop a classifier to discriminate high and low cognitive workload crew states. The classifier will then be tested in an operationally relevant EVA simulation to predict cognitive workload over time. Once a crew state is determined, further research into specific countermeasures, such as decision support systems, would be necessary to optimize the automation and improve crew state and operational performance.

Wusk, Grace C.↗

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management, FPM, AOP, UAM, deconflicti↗

Initial Design Guidelines for Onboard Automation of Flight Path Management

Achieving the National Academy of Science’s vision of advanced aerial mobility will depend on significant developments in automation to achieve safe and efficient operations. Flight path management (FPM), a major category of automation functionality needed to achieve this vision, will provide dynamic management of an aircraft’s flight path, ensuring that it remains feasible to fly to mission completion, deconflicted from hazards, coordinated with other traffic, flexible to accommodate future disturbances, and optimized to meet business objectives. While efforts are underway to advance FPM technology for the Urban Air Mobility application, initial design guidelines are presented for FPM automation capabilities to achieve each of these objectives based on 15+ years of prior FPM automation research and development. Methods to efficiently account for uncertainty in the prediction of trajectories are described, as are additional considerations for prioritizing safety in the design of FPM automation capabilities and interactions between aircraft. Recommendations are supported by extensive experience gained via previous work with the FPM reference automation system, Autonomous Operations Planner, developed by NASA. By employing capable FPM automation supported by cooperative operational flight rules and information sharing, future aircraft operators will benefit from an increased ability to plan and execute safe and efficient flights and to achieve mission success in a dynamic airspace.

Flight Path Management↗

An Intelligent Propulsion Control Architecture to Enable More Autonomous Vehicle Operation

This paper describes an intelligent propulsion control architecture that coordinates with the flight control to reduce the amount of pilot intervention required to operate the vehicle. Objectives of the architecture include the ability to: automatically recognize the aircraft operating state and flight phase; configure engine control to optimize performance with knowledge of engine condition and capability; enhance aircraft performance by coordinating propulsion control with flight control; and recognize off-nominal propulsion situations and to respond to them autonomously. The hierarchical intelligent propulsion system control can be decomposed into a propulsion system level and an individual engine level. The architecture is designed to be flexible to accommodate evolving requirements, adapt to technology improvements, and maintain safety.

autonomy↗

An Intelligent Propulsion Control Architecture to Enable More Autonomous Vehicle Operation

This paper describes an intelligent propulsion control architecture that coordinates with the flight control to reduce the amount of pilot intervention required to operate the vehicle. Objectives of the architecture include the ability to: automatically recognize the aircraft operating state and flight phase; configure engine control to optimize performance with knowledge of engine condition and capability; enhance aircraft performance by coordinating propulsion control with flight control; and recognize off-nominal propulsion situations and to respond to them autonomously. The hierarchical intelligent propulsion system control can be decomposed into a propulsion system level and an individual engine level. The architecture is designed to be flexible to accommodate evolving requirements, adapt to technology improvements, and maintain safety.

autonomy↗

Optimal Experimental Design With Fast Neural Network Surrogate Models

Designing optimal experiments minimizes the uncertainty of results and maximizes the efficient use of resources. Herein, machine learning surrogate models and the approximate coordinate exchange (ACE) algorithm are used to determine optimum experimental designs over large or arbitrarily restrictive design spaces. Optimal experimental design is particularly salient in materials science where experiments are expensive and material properties must often be inferred indirectly. The proposed framework is demonstrated by finding optimal experiments with which the hidden constituent properties of composite materials can be most efficiently inferred from observable experimental outcomes. The optimum experimental design is given by an information-theoretic criteria, which maximizes the conditional mutual information between the hidden properties and the expected experimental outcomes. To perform tractable optimization a neural network is trained as a surrogate model to mimic a physics based simulation, which can calculate the expected experimental outcome based on a candidate experimental design and sampled constituent properties. The ACE algorithm is used to optimize over large design spaces with many tests and controlled parameters where an exhaustive search would be intractable even with the surrogate model. Using this approach, optimal experimental designs that are consistent with those produced by heuristic knowledge and established best practices are found; then optimal designs in larger design spaces where heuristic knowledge is unavailable are examined.

machine learning↗

Personality factors in flight operations. Volume 1: Leader characteristics and crew performance in a full-mission air transport simulation

Crew effectiveness is a joint product of the piloting skills, attitudes, and personality characteristics of team members. As obvious as this point might seem, both traditional approaches to optimizing crew performance and more recent training development highlighting crew coordination have emphasized only the skill and attitudinal dimensions. This volume is the first in a series of papers on this simulation. A subsequent volume will focus on patterns of communication within crews. The results of a full-mission simulation research study assessing the impact of individual personality on crew performance is reported. Using a selection algorithm described in previous research, captains were classified as fitting one of three profiles along a battery of personality assessment scales. The performances of 23 crews led by captains fitting each profile were contrasted over a one-and-one-half-day simulated trip. Crews led by captains fitting a positive Instrumental-Expressive profile (high achievement motivation and interpersonal skill) were consistently effective and made fewer errors. Crews led by captains fitting a Negative Expressive profile (below average achievement motivation, negative expressive style, such as complaining) were consistently less effective and made more errors. Crews led by captains fitting a Negative Instrumental profile (high levels of competitiveness, verbal aggressiveness, and impatience and irritability) were less effective on the first day but equal to the best on the second day. These results underscore the importance of stable personality variables as predictors of team coordination and performance.

Chidester, Thomas R.↗

Flexible space structure model reduction by modal cost analysis

It is noted that reduced models and reduced controllers for flexible space structures are obtained by retaining those modes which make the greatest contribution to quadratic control objectives. Attention is given to the relative importance of damping, frequency and mode shapes in the mode truncation decisions for the following control objectives: attitude control, vibration suppression and figure control. It is also shown that using Modal Cost Analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop coordinates which are most critical to the quadratic control performance criterion. In this manner, the modes which need to be controlled are deduced from truncations of the optimal controller.

Skelton, R. E.↗

The IMS Satellite Situation Center

Following a brief historical review of the SSC (Satellite Situation Center), created by the U.S. for the IMS (International Magnetospheric Study), its main functions are discussed. The services of the SSC include the accurate orbit determination of the satellites, 12-18 months in advance and the coordination of simultaneous observations by a multispacecraft system, which are essential for the optimization of the scientific gains from experiments conducted with limited resources. For 1976 SSC generated plots of the satellites Vela 5B, Vela 6A, Vela 6B, Hawkeye 1, Imp H (7), Imp J (8) by computing certain projections of the solar ecliptic, solar magnetospheric, and solar magnetic coordinate systems. The SSC system was automated by the addition of a computer system capable of interactive graphics. The SSC can also provide the ground-based campaigns with a graphical or tabular information about the position low-altitude satellites in any coordinate system. The possible participation of the SSC in future Electrodynamics Explorer mission, Space Shuttle programs is also being explored.

Sugiura, M.↗