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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

STOP Modeling for the JWST: Techniques, Results, and Sensitivities

The James Web Space Telescope (JWST) is a large, infrared-optimized, space telescope scheduled for launch to L2 in 2011. It must meet rigorous thermal stability requirements, almost all of which will be verified through analysis. Terrestrial testing will be performed but even that will require significant analytical interpretation of results. Preliminary analysis indicates that traditional second-order effects could cause the telescope to exceed established performance requirements. This leads to very large detailed models, primarily since composite tubes are being modeled using solid elements. To minimize differences between the current baseline and the model the project is using a number of rapid analysis cycles. The large size of the telescope models and the short cycle time creates a demanding multidisciplinary analysis environment.

John D. Johnston↗
NASA NTRS2006

Development Tests of a Cryogenic Filter Wheel Assembly for the NIRCam Instrument

The James Webb Space Telescope is an infrared-optimized space telescope scheduled for launch in 201 3. Its 6.5-m diameter primary mirror will collect light from some of the first galaxies formed after the big bang. The Near Infrared camera (NIRCam) will detect the first light from these galaxies, provide the necessary tools for studying the formation of stars, aid in discovering planets around other stars, and adjust the wave front error on the primary mirror (Fig. 1). The instrument and its complement of mechanisms and optics will operate at a cryogenic temperature of 35 K. This paper describes tests and test results of the NIRCam Filter Wheel assembly prototype.

McCully, Sean↗
NASA NTRS2007

New Frontiers for Massive Star Winds: Imaging and Spectroscopy with the James Webb Space Telescope

The James Webb Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2013. JWST will find the first stars and galaxies that formed in the early universe, connecting the Big Bang to our own Milky Way galaxy. JWST will peer through dusty clouds to see stars forming planetary systems, connecting the Milky Way to our own Solar System. JWST's instruments are designed to work primarily in the infrared range of 1 - 28 microns, with some capability in the visible range. JWST will have a large mirror, 6.5 meters in diameter, and will be diffraction-limited at 2 microns (0.1 arcsec resolution). JWST will be placed in an L2 orbit about 1.5 million km from the Earth. The instruments will provide imaging, coronography, and multi-object and integral-field spectroscopy across the full 1 - 28 micron wavelength range. The breakthrough capabilities of JWST will enable new studies of massive star winds from the Milky Way to the early universe.

Sonneborn, George↗
NASA NTRS2007

Imaging and Spectroscopy with the James Webb Space Telescope

The James Webb Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2013. JWST will find the first stars and galaxies that formed in the early universe, connecting the Big Bang to our own Milky Way galaxy. JWST will peer through dusty clouds to see stars forming planetary systems, connecting the Milky Way to our own Solar System. JWST's instruments are designed to work primarily in the infrared range of 1 - 28 microns, with some capability in the visible range. JWST will have a large mirror, 6.5 meters in diameter, and will be diffraction-limited at 2 microns (0.1 arcsec resolution). JWST will be placed in an L2 orbit about 1.5 million km from the Earth. The instruments will provide imaging, coronography, and multi-object and integral-field spectroscopy across the full 1 - 28 micron wavelength range. The breakthrough capabilities of JWST will enable new studies of star formation and evolution in the Milky Way, nearby galaxies, and the early universe.

Sonneborn, George↗
NASA NTRS2009

Physical Principle for Generation of Randomness

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Zak, Michail↗
NASA NTRS2010

An Update on the Role of Systems Modeling in the Design and Verification of the James Webb Space Telescope

The James Web Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2014. System-level verification of critical performance requirements will rely on integrated observatory models that predict the wavefront error accurately enough to verify that allocated top-level wavefront error of 150 nm root-mean-squared (rms) through to the wave-front sensor focal plane is met. The assembled models themselves are complex and require the insight of technical experts to assess their ability to meet their objectives. This paper describes the systems engineering and modeling approach used on the JWST through the detailed design phase.

Muheim, Danniella↗
NASA NTRS2010

Systems Engineering on the James Webb Space Telescope

The James Web Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2014. System-level verification of critical performance requirements will rely on integrated observatory models that predict the wavefront error accurately enough to verify that allocated top-level wavefront error of 150 nm root-mean-squared (rms) through to the wave-front sensor focal plane is met. This paper describes the systems engineering approach used on the JWST through the detailed design phase.

Menzel, Michael T.↗
NASA NTRS2012

Initial Investigations of Controller Tools and Procedures for Schedule-Based Arrival Operations with Mixed Flight-Deck Interval Management Equipage

NASA's Air Traffic Management Demonstration-1 (ATD-1) is a multi-year effort to demonstrate high-throughput, fuel-efficient arrivals at a major U.S. airport using NASA-developed scheduling automation, controller decision-support tools, and ADS-B-enabled Flight-Deck Interval Management (FIM) avionics. First-year accomplishments include the development of a concept of operations for managing scheduled arrivals flying Optimized Profile Descents with equipped aircraft conducting FIM operations, and the integration of laboratory prototypes of the core ATD-1 technologies. Following each integration phase, a human-in-the-loop simulation was conducted to evaluate and refine controller tools, procedures, and clearance phraseology. From a ground-side perspective, the results indicate the concept is viable and the operations are safe and acceptable. Additional training is required for smooth operations that yield notable benefits, particularly in the areas of FIM operations and clearance phraseology.

Callantine, Todd J.↗
NASA NTRS2023

An Analysis of Barriers Preventing the Widespread Adoption of Predictive and Prescriptive Maintenance in Aviation

The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.

Christopher Teubert↗
NASA NTRSDate not supplied

Cloud-Based Demodulation and Data Distribution of a Satellite Downlink

Ground station networks connected to the cloud allow space missions to have global communications coverage without operating their own infrastructure. In this work, we describe the communications architecture for the TechEdSat-13 mission, which performed the first in-space characterization of a neuromorphic processor. The mission utilizes a commercial provider for S-band downlinks. A suite of cloud services and open-source software such as GNU Radio are leveraged to demodulate signals received by an AWS ground station during passes with TechEdSat-13 and store recovered data. Once a pass is scheduled, the entire process takes place without human intervention. On-orbit results the past year of operations are presented, demonstrating the advantages of this approach over traditional operator-owned ground stations. Use of software-defined radio makes possible custom signal processing. The homogeneity of apertures and their interfaces to the cloud simplifies scaling across many sites. This abundance of candidate links lays the groundwork for intelligent scheduling agents to optimize pass selection across several factors, automatically recover from failed contacts, and gather metrics to learn from past performance.

cloud demodulation↗
NASA NTRS2011

Runway Scheduling Using Generalized Dynamic Programming

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

optmization↗
NASA NTRS1991

AI techniques for a space application scheduling problem

Scheduling is a very complex optimization problem which can be categorized as an NP-complete problem. NP-complete problems are quite diverse, as are the algorithms used in searching for an optimal solution. In most cases, the best solutions that can be derived for these combinatorial explosive problems are near-optimal solutions. Due to the complexity of the scheduling problem, artificial intelligence (AI) can aid in solving these types of problems. Some of the factors are examined which make space application scheduling problems difficult and presents a fairly new AI-based technique called tabu search as applied to a real scheduling application. the specific problem is concerned with scheduling application. The specific problem is concerned with scheduling solar and stellar observations for the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) instrument in a constrained environment which produces minimum impact on the other instruments and maximizes target observation times. The SOLSTICE instrument will gly on-board the Upper Atmosphere Research Satellite (UARS) in 1991, and a similar instrument will fly on the earth observing system (Eos).

Thalman, N.↗
NASA NTRS1996

Dataflow Design Tool: User's Manual

The Dataflow Design Tool is a software tool for selecting a multiprocessor scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. The software tool implements graph-search algorithms and analysis techniques based on the dataflow paradigm. Dataflow analyses provided by the software are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool provides performance optimization through the inclusion of artificial precedence constraints among the schedulable tasks. The user interface and tool capabilities are described. Examples are provided to demonstrate the analysis, scheduling, and optimization functions facilitated by the tool.

Jones, Robert L., III↗
NASA NTRS1998

Deterministic Reconfigurable Control Design for the X-33 Vehicle

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. Four reconfigurable control design methods were investigated for the X-33 vehicle: Redistributed Pseudo-Inverse, General Constrained Optimization, Automated Failure Dependent Gain Schedule, and an Off-line Nonlinear General Constrained Optimization. The Off-line Nonlinear General Constrained Optimization approach was chosen for implementation on the X-33. Two example failures are shown, a right outboard elevon jam at 25 deg. at a Mach 3 entry condition, and a left rudder jam at 30 degrees. Note however, that reconfigurable control laws have been designed for the entire flight envelope. Comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

Wagner, Elaine A.↗
NASA NTRS2020

Scheduling NASA's Deep Space Network: Priorities, Preferences, and Optimization

NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40\% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process --- oversubsubscription and how to "fairly'" reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗
NASA NTRSDate not supplied

Traffic Flow Analysis for Package Delivery Drones using a Queueing Model

A key component of the small unmanned aircraft systems traffic management ecosystem is the design of scalable algorithms for strategic deconfliction of drones prior to takeoff. In this work, we focus on efficient flow management of drones on a network of intersecting edges subject to two kinds of spacing constraints: 1) between any two adjacent vehicles on an edge and 2) between any two vehicles on two different edges arriving one after the other at an intersection. The spacing is designed to enable non-intersection of operational volumes corresponding to two different vehicles thereby properly separating the vehicles inside each volume. For simplicity, we assume a constant ground speed for the drones and fixed dimensions for the operational volume blocks. The deconfliction is managed by adjusting the takeoff time of the drones, thereby regulating their arrival time at various crossing waypoints in the network. This framework allows us to study the maximum flow (throughput) of vehicles on a network of edges connecting depots to drop off sites subject to the temporal spacing constraints. The departure scheduling of individual drones results in a combinatorial optimization problem. To alleviate this, we solve a max-flow formulation and use queueing theory to simplify the analysis and provide upper bounds to the underlying optimization problem for individual drone departure scheduling. Our results indicate that throughput drops rapidly after the density of drones in the network passes the max-flow limits.

Alexey A Munishkin↗
NASA NTRS1972

Load relief and gust alleviation control study

The results of a study are presented in which a computerized optimal control techique was applied to the synthesis of a load relief control system for an advanced Saturn 5 derivative launch vehicle. This technique included selection of a load relief control law and computerized optimization of the controller gain schedules for a set of preselected adverse synthetic wind speed profiles. The gain optimization was effected using a hybrid optimizer program to minimize (optimize) a direct performance functional which specified the design goal (load relief) in engineering terms (explicit representation of maximum bending moments).

Vieweg, R. R.↗