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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Design and Stability of an On-Orbit Attitude Control System Using Reaction Control Thrusters

Principles for the design and stability of a spacecraft on-orbit attitude control system employing on-off Reaction Control System (RCS) thrusters is presented. Both the vehicle dynamics and the control system actuators are inherently nonlinear, hence traditional linear control system design approaches are not directly applicable. This paper has three main aspects: It summarizes key RCS control System design principles from the Space Shuttle and Space Station programs, it demonstrates a new approach to develop a linear model of a phase plane control system using describing functions, and applies each of these to the initial development of the NASA's next generation of upper stage vehicles. Topics addressed include thruster hardware specifications, phase plane design and stability, jet selection approaches, filter design metrics, and automaneuver logic.

Hall, Robert A.↗
NASA NTRS1991

NASA Goddard Space Flight Center Robotic Processing System Program Automation Systems, volume 2

Topics related to robot operated materials processing in space (RoMPS) are presented in view graph form. Some of the areas covered include: (1) mission requirements; (2) automation management system; (3) Space Transportation System (STS) Hitchhicker Payload; (4) Spacecraft Command Language (SCL) scripts; (5) SCL software components; (6) RoMPS EasyLab Command & Variable summary for rack stations and annealer module; (7) support electronics assembly; (8) SCL uplink packet definition; (9) SC-4 EasyLab System Memory Map; (10) Servo Axis Control Logic Suppliers; and (11) annealing oven control subsystem.

Dobbs, M. E.↗
NASA NTRS2008

Scripting Module for the Satellite Orbit Analysis Program (SOAP)

This add-on module to the SOAP software can perform changes to simulation objects based on the occurrence of specific conditions. This allows the software to encompass simulation response of scheduled or physical events. Users can manipulate objects in the simulation environment under programmatic control. Inputs to the scripting module are Actions, Conditions, and the Script. Actions are arbitrary modifications to constructs such as Platform Objects (i.e. satellites), Sensor Objects (representing instruments or communication links), or Analysis Objects (user-defined logical or numeric variables). Examples of actions include changes to a satellite orbit ( v), changing a sensor-pointing direction, and the manipulation of a numerical expression. Conditions represent the circumstances under which Actions are performed and can be couched in If-Then-Else logic, like performing v at specific times or adding to the spacecraft power only when it is being illuminated by the Sun. The SOAP script represents the entire set of conditions being considered over a specific time interval. The output of the scripting module is a series of events, which are changes to objects at specific times. As the SOAP simulation clock runs forward, the scheduled events are performed. If the user sets the clock back in time, the events within that interval are automatically undone. This script offers an interface for defining scripts where the user does not have to remember the vocabulary of various keywords. Actions can be captured by employing the same user interface that is used to define the objects themselves. Conditions can be set to invoke Actions by selecting them from pull-down lists. Users define the script by selecting from the pool of defined conditions. Many space systems have to react to arbitrary events that can occur from scheduling or from the environment. For example, an instrument may cease to draw power when the area that it is tasked to observe is not in view. The contingency of the planetary body blocking the line of sight is a condition upon which the power being drawn is set to zero. It remains at zero until the observation objective is again in view. Computing the total power drawn by the instrument over a period of days or weeks can now take such factors into consideration. What makes the architecture especially powerful is that the scripting module can look ahead and behind in simulation time, and this temporal versatility can be leveraged in displays such as x-y plots. For example, a plot of a satellite s altitude as a function of time can take changes to the orbit into account.

Carnright, Robert↗
NASA NTRS1976

Architecture and data processing alternatives for the TSE computer. Volume 3: Execution of a parallel counting algorithm using array logic (Tse) devices

A parallel algorithm for counting the number of logic-l elements in a binary array or image developed during preliminary investigation of the Tse concept is described. The counting algorithm is implemented using a basic combinational structure. Modifications which improve the efficiency of the basic structure are also presented. A programmable Tse computer structure is proposed, along with a hardware control unit, Tse instruction set, and software program for execution of the counting algorithm. Finally, a comparison is made between the different structures in terms of their more important characteristics.

Metcalfe, A. G.↗
NASA NTRS2003

Results of the Workshop on Two-Phase Flow, Fluid Stability and Dynamics: Issues in Power, Propulsion, and Advanced Life Support Systems

The Two-phase Flow, Fluid Stability and Dynamics Workshop was held on May 15, 2003 in Cleveland, Ohio to define a coherent scientific research plan and roadmap that addresses the multiphase fluid problems associated with NASA s technology development program. The workshop participants, from academia, industry and government, prioritized various multiphase issues and generated a research plan and roadmap to resolve them. This report presents a prioritization of the various multiphase flow and fluid stability phenomena related primarily to power, propulsion, fluid and thermal management and advanced life support; and a plan to address these issues in a logical and timely fashion using analysis, ground-based and space-flight experiments.

McQuillen, John↗
NASA NTRS2019

Citizen Science Data Quality: The GLOBE Program

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international program that provides a way for students and the public to contribute Earth system observations. Currently 122 countries, more than 40,000 schools, and 200,000 citizen scientists are participating in GLOBE. Since 1995, participants have contributed 195 million observations. Modes of data collection and data entry have evolved with technology over the lifetime of the program, including the launch of the GLOBE Observer mobile app in 2016 to broaden access and public participation in data collection. GLOBE must meet the data needs of a diverse range of stakeholders, from elementary school classrooms to scientists across the globe, including NASA scientists. Operational quality assurance measures include participant training, adherence to standardized data collection protocols, range and logic checks, and an approval process for photos submitted with an observation. In this presentation, we will discuss the current state of operational data QA/QC, as well as additional QA/QC processes recently explored and future directions.

Amos, Helen↗
NASA NTRSDate not supplied

QuantifyML: How good is my machine learning model?

This paper presents an approach, QuantifyML, which employs model counting to assess the learnability and robustness of machine learning models. Typically the efficacy of machine learning models is determined by computing their accuracy statistically on test data sets. However, this may be misleading, if the test data is not representative of the problem that is being studied. Further, two different models may have the same accuracy on a given data set, measured statistically, but may be very different in their behavior on unseen data. Also, models with high accuracy could have poor adversarial robustness. In QuantifyML, our goal is to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into a C program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise counts w.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, expressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the robustness of trained models around given inputs. Our evaluation demonstrates these applications of QuantifyML on decision trees and neural networks trained to learn relational properties of graphs, for which we know the ground truth, and to perform image classification, for which we do not have the ground truth, but we can quantify local robustness.

Deep Neural Networks↗
NASA NTRS1973

Ballistic mode Mercury orbiter missions.

The MVM'73 Mercury flyby mission will initiate exploration of this unique planet. No firm plans for follow-on investigations have materialized due to the difficult performance requirements of the next logical step, an orbiter mission. Previous investigations of ballistic mode flight opportunities have indicated requirements for a Saturn V class launch vehicle. Consequently, most recent effort has been oriented to use of solar electric propulsion. More comprehensive study of the ballistic flight mode utilizing Venus gravity-assist has resulted in identification of timely high-performance mission opportunities compatible with programmed launch vehicles and conventional spacecraft propulsion technologies. A likely candidate for an initial orbiter mission is a 1980 opportunity which offers net orbiter spacecraft mass of about 435 kg with the Titan IIIE/Centaur launch vehicle and single stage solid propulsion for orbit insertion.

Hollenbeck, G. R.↗
NASA NTRS1979

Multivariable control altitude demonstration on the F100 turbofan engine

The F100 Multivariable control synthesis (MVCS) program, was aimed at demonstrating the benefits of LGR synthesis theory in the design of a multivariable engine control system for operation throughout the flight envelope. The advantages of such procedures include: (1) enhanced performance from cross-coupled controls, (2) maximum use of engine variable geometry, and (3) a systematic design procedure that can be applied efficiently to new engine systems. The control system designed, under the MVCS program, for the Pratt & Whitney F100 turbofan engine is described. Basic components of the control include: (1) a reference value generator for deriving a desired equilibrium state and an approximate control vector, (2) a transition model to produce compatible reference point trajectories during gross transients, (3) gain schedules for producing feedback terms appropriate to the flight condition, and (4) integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance.

Lehtinen, B.↗
NASA NTRS1984

Uprated orbital maneuvering engine

The baseline orbital maneuvering system (OMS) of the Space Shuttle has the potential for significant performance uprating, leading to increased Shuttle payload capability. The baseline OMS, its requirements, and its operational characteristics are described. Potential uprating approaches are discussed and the logic for selection of a higher performance engine is presented. It is shown that a higher performance engine essentially means an engine operating at higher pressures and that a pump-fed engine is necessary for the higher pressure operation. A description of the uprated OMS engine, including requirements, baseline engine characteristics, and significant engine issues, is presented. Discussion of the program underway at the NASA Lyndon B. Johnson Space Center to attain additional insight into these issues, through the performance of a component demonstration program, includes the technical objectives, approach, and program schedule. The plans for further development are presented, culminating in the plans for integration with the Orbiter and the Shuttle system.

Hooper, J. C.↗
NASA NTRS2005

Model Checking Real Time Java Using Java PathFinder

The Real Time Specification for Java (RTSJ) is an augmentation of Java for real time applications of various degrees of hardness. The central features of RTSJ are real time threads; user defined schedulers; asynchronous events, handlers, and control transfers; a priority inheritance based default scheduler; non-heap memory areas such as immortal and scoped, and non-heap real time threads whose execution is not impeded by garbage collection. The Robust Software Systems group at NASA Ames Research Center has JAVA PATHFINDER (JPF) under development, a Java model checker. JPF at its core is a state exploring JVM which can examine alternative paths in a Java program (e.g., via backtracking) by trying all nondeterministic choices, including thread scheduling order. This paper describes our implementation of an RTSJ profile (subset) in JPF, including requirements, design decisions, and current implementation status. Two examples are analyzed: jobs on a multiprogramming operating system, and a complex resource contention example involving autonomous vehicles crossing an intersection. The utility of JPF in finding logic and timing errors is illustrated, and the remaining challenges in supporting all of RTSJ are assessed.

Lindstrom, Gary↗
NASA NTRSDate not supplied

QuantifyML: How Good is My Machine Learning Model?

We present QuantifyML, which applies model counting to assess the learn ability, safety, and robustness of machine learning models. Typically, the efficacy of machine learning models is determined by computing their accuracy statistically on test datasets. However, this may be misleading, if the test data is not representative of the problem that is being studied. With QuantifyML we aim to precisely quantify the extent to which machine learning models have learned and generalized from the given data. In QuantifyML, a trained model is translated into aC program, which is fed to the CBMC model checking tool to produce a formula in Conjunctive Normal Form (CNF), which in turn is analyzed with state-of-the-art model counters to efficiently obtain precise countsw.r.t different outputs. QuantifyML enables i) evaluating the learnability of models by comparing the counts for the outputs to ground truth, ex-pressed as logical predicates (if available), ii) comparing the performance of different models that may be built with different machine learning algorithms (e.g., decision-trees vs. neural networks), and iii) quantifying the safety and robustness of trained models.

Deep Neural Networks↗
NASA NTRS1974

Application of IPAD to missile design

The application of an integrated program for aerospace-vehicle design (IPAD) to the design of a tactical missile is examined. The feasibility of modifying a proposed IPAD system for aircraft design work for use in missile design is evaluated. The tasks, cost, and schedule for the modification are presented. The basic engineering design process is described, explaining how missile design is achieved through iteration of six logical problem solving functions throughout the system studies, preliminary design, and detailed design phases of a new product. Existing computer codes used in various engineering disciplines are evaluated for their applicability to IPAD in missile design.

Santa, J. E.↗
NASA NTRS1982

Program for Analysis and Resizing of Structures

Program for Analysis and Resizing of Structures (PARS) determines optimum resizing of structures subject to stress, displacement, and flutter constraints. Is an efficient code for sizing large- or small-scale finite-element models in presence of strength, thermal, and aeroelastic constraints with minimum and maximum bounds on structural dimensions. PARS is composed of individual processors that are executed in a logical sequence to perform analysis or synthesis.

Haftka, R. T.↗
NASA NTRS1993

MIRAGE: The data acquisition, analysis, and display system

Developed for the NASA Johnson Space Center and Life Sciences Directorate by GE Government Services, the Microcomputer Integrated Real-time Acquisition Ground Equipment (MIRAGE) system is a portable ground support system for Spacelab life sciences experiments. The MIRAGE system can acquire digital or analog data. Digital data may be NRZ-formatted telemetry packets of packets from a network interface. Analog signal are digitized and stored in experimental packet format. Data packets from any acquisition source are archived to a disk as they are received. Meta-parameters are generated from the data packet parameters by applying mathematical and logical operators. Parameters are displayed in text and graphical form or output to analog devices. Experiment data packets may be retransmitted through the network interface. Data stream definition, experiment parameter format, parameter displays, and other variables are configured using spreadsheet database. A database can be developed to support virtually any data packet format. The user interface provides menu- and icon-driven program control. The MIRAGE system can be integrated with other workstations to perform a variety of functions. The generic capabilities, adaptability and ease of use make the MIRAGE a cost-effective solution to many experimental data processing requirements.

Rosser, Robert S.↗
NASA NTRS1989

A programmable CCD driver circuit for multiphase CCD operation

A programmable CCD (charge-coupled device) driver circuit was designed to drive CCDs in multiphased modes. The purpose of the drive electronics is to operate developmental CCD imaging arrays for NASA's tiltable moderate resolution imaging spectrometer (MODIS-T). Five objectives for the driver were considered during its design: (1) the circuit drives CCD electrode voltages between 0 V and +30 V to produce reasonable potential wells, (2) the driving sequence is started with one input signal, (3) the driving sequence is started with one input signal, (4) the circuit allows programming of frame sequences required by arrays of any size, (5) it produces interfacing signals for the CCD and the DTF (detector test facility). Simulation of the driver verified its function with the master clock running up to 10 MHz. This suggests a maximum rate of 400,000 pixels/s. Timing and packaging parameters were verified. The design uses 54 TTL (transistor-transistor logic) chips. Two versions of hardware were fabricated: wirewrap and printed circuit board. Both were verified functionally with a logic analyzer.

Ewin, Audrey J.↗
NASA NTRS2003

Independent Review of the Failure Modes of F-1 Engine and Propellants System

The F-1 is the powerful engine, that hurdled the Saturn V launch vehicle from the Earth to the moon on July 16,1969. The force that lifted the rocket overcoming the gravitational force during the first stage of the flight was provided by a cluster of five F-1 rocket engines, each of them developing over 1.5 million pounds of thrust (MSFC-MAN-507). The F-1 Rocket engine used RP-1 (Rocket Propellant-1, commercially known as Kerosene), as fuel with lox (liquid Oxygen) as oxidizer. NASA terminated Saturn V activity and has focused on Space Shuttle since 1972. The interest in rocket system has been revived to meet the National Launch System (NLS) program and a directive from the President to return to the Moon and exploration of the space including Mars. The new program Space Launch Initiative (SLI) is directed to drastically reduce the cost of flight for payloads, and adopt a reusable launch vehicle (RLV). To achieve this goal it is essential to have the ability of lifting huge payloads into low earth orbit. Probably requiring powerful boosters as strap-ons to a core vehicle, as was done for the Saturn launch vehicle. The logic in favor of adopting Saturn system, a proven technology, to meet the SLI challenge is very strong. The F-1 engine was the largest and most powerful liquid rocket engine ever built, and had exceptional performance. This study reviews the failure modes of the F-1 engine and propellant system.

Ray, Paul↗
NASA NTRS2008

Algorithm-Based Fault Tolerance Integrated with Replication

In a proposed approach to programming and utilization of commercial off-the-shelf computing equipment, a combination of algorithm-based fault tolerance (ABFT) and replication would be utilized to obtain high degrees of fault tolerance without incurring excessive costs. The basic idea of the proposed approach is to integrate ABFT with replication such that the algorithmic portions of computations would be protected by ABFT, and the logical portions by replication. ABFT is an extremely efficient, inexpensive, high-coverage technique for detecting and mitigating faults in computer systems used for algorithmic computations, but does not protect against errors in logical operations surrounding algorithms.

Some, Raphael↗