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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

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NASA NTRS1988

Thermal cycling of tungsten-fibre-reinforced superalloy composites

The thermal cycling of a tungsten-fiber-reinforced superalloy (TFRS) composite is typical of its application in high-temperature engine environments. The mismatch in thermal expansion coefficients between fiber and matrix causes substantial longitudinal (0 deg) stresses in the composite, which can produce inelastic damage-producing matrix strains. The case of thermal fatigue is explored as a "worst case" of the possible matrix damage, in comparison with specimens which are also mechanically loaded in tension. The thermally generated cyclic stresses and the attendant matrix plasticity may be estimated using a nonlinear finite-element program, by proposing a physical analog to the micromechanics equations. A damage metric for the matrix is proposed using the Coffin-Manson criterion, which metric can facilitate comparisons of damage among different candidate materials, and also comparisons for a given material subjected to different temperature cycles. An experimental program was carried out for thermal cycling of a 37 vol pct TFRS composite to different maximum temperatures. The results confirm the prediction that thermal cycling produces matrix degradation and composite strength reduction, which become more pronounced with increasing maximum cyclic temperature. The strength of the fiber is shown to be identical for the as-fabricated and thermally cycled specimens, suggesting that the reduction in composite strength is due to the loss of matrix contribution and also to notching effects of the matrix voids on the fiber.

Wetherhold, Robert C.↗

NASA NTRS2002

NASA Scientific Data Purchase Project: From Collection to User

NASA's Scientific Data Purchase (SDP) project is currently a $70 million operation managed by the Earth Science Applications Directorate at Stennis Space Center. The SDP project was developed in 1997 to purchase scientific data from commercial sources for distribution to NASA Earth science researchers. Our current data holdings include 8TB of remote sensing imagery consisting of 18 products from 4 companies. Our anticipated data volume is 60 TB by 2004, and we will be receiving new data products from several additional companies. Our current system capacity is 24 TB, expandable to 89 TB. Operations include tasking of new data collections, archive ordering, shipment verification, data validation, distribution, metrics, finances, customer feedback, and technical support. The program has been included in the Stennis Space Center Commercial Remote Sensing ISO 9001 registration since its inception. Our operational system includes automatic quality control checks on data received (with MatLab analysis); internally developed, custom Web-based interfaces that tie into commercial-off-the-shelf software; and an integrated relational database that links and tracks all data through operations. We've distributed nearly 1500 datasets, and almost 18,000 data files have been downloaded from our public web site; on a 10-point scale, our customer satisfaction index is 8.32 at a 23% response level. More information about the SDP is available on our Web site.

Nicholson, Lamar↗

NASA NTRS1997

A Disturbance Rejection Approach to Actuator and Sensor Placement

For various reasons as discussed for instance in, the selection of actuator and sensor positions is still ad hoc. This is especially true for flexible structures where many candidate configurations can exist. This study is an attempt to make the selection process more methodical. One approach to actuator and sensor placement is to optimize a closed loop performance metric directly by selecting the actuators, sensors, and controller gains simultaneously. This direct approach makes sense if the desired closed loop performance is well defined. Since the individual actuator and sensor contributions to the closed loop performance metric is complex, the solution strategy usually employs non linear programming with many design and numerical iterations. A second approach is to select actuators and/or sensors based on open loop properties so that closed loop performance is indirectly optimized. Since the individual sensor and actuator contributions to the open loop metric is simple, nonlinear optimization is usually not needed. This approach will suggest efficient actuator and sensor configurations for any type of control law. The method suggested in this study falls into the latter class of approaches.

Lim, K. B.↗

NASA NTRS2009

Thoughts on Earned Value Assessments

This slide presentation reviews the concepts of Earned Value reporting and Earned Value Metrics (EVM) and the implementation for the Constellation Program. EVM is used to manage both the contract and civil service workforce, and used as a measure of contractor costs and performance. The Program EVM is not as useful for Level of Effort tasking, for either contractor, or civil service employees. Some issues and concerns in reference to EVM and the process for the use of EVM for Mission assurance are reviewed,

Pido, Kelle↗

NASA NTRS2012

Preliminary Assessment of Suomi-NPP VIIRS On-orbit Radiometric Performance

The Visible-Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft that was launched on October 28th 2011. VIIRS was designed to provide moderate and imaging resolution of most of the globe twice daily. It is a wide-swath (3,040 km) cross-track scanning radiometer with spatial resolutions of 370.and 740 m at nadir for imaging and moderate bands, respectively. It has 22 spectral bands covering the spectrum between 0.412 11m and 12.01 11m, including 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and 1 day-night band (ON B). VIIRS observations are used to generate 22 environmental data products (EORs). This paper will briefly describe NPP VIIRS calibration strategies performed by the independent government team, for the initial on-orbit Intensive Calibration and Validation (ICV) activities. In addition, this paper will provide an early assessment of the sensor on-orbit radiometric performance, such as the sensor signal to noise ratios (SNRs), dual gain transition verification, dynamic range and linearity, reflective bands calibration based on the solar diffuser (SO) and solar diffuser stability monitor (SOSM), and emissive bands calibration based on the on-board blackbody calibration (OBC). A comprehensive set of performance metrics generated during the pre-launch testing program will be compared to VIIRS on-orbit early performance, and a plan for future cal/val activities and performance enhancements will be presented.

Oudrari, Hassan↗

NASA NTRS2016

JPSS-1 VIIRS Radiometric Characterization and Calibration Based on Pre-Launch Testing

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the first Joint Polar Satellite System (JPSS) completed its sensor level testing on December 2014. The JPSS-1 (J1) mission is scheduled to launch in December 2016, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 m. It is a cross-track scanning radiometer capable of providing global measurements twice daily, through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging and moderate bands, respectively. This paper will briefly describe J1 VIIRS characterization and calibration performance and methodologies executed during the pre-launch testing phases by the government independent team to generate the at-launch baseline radiometric performance and the metrics needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). This paper will also provide an assessment of the sensor pre-launch radiometric performance, such as the sensor signal to noise ratios (SNRs), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response-vs-scan (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the VIIRS sensor specification and the SNPP VIIRS pre-launch performance.

VIIRS↗

NASA NTRS2015

JPSS-1 VIIRS Pre-Launch Radiometric Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the first Joint Polar Satellite System (JPSS) completed its sensor level testing on December 2014. The JPSS-1 (J1) mission is scheduled to launch in December 2016, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. VIIRS instrument was designed to provide measurements of the globe twice daily. It is a wide-swath (3,040 kilometers) cross-track scanning radiometer with spatial resolutions of 370 and 740 meters at nadir for imaging and moderate bands, respectively. It covers the wavelength spectrum from reflective to long-wave infrared through 22 spectral bands [0.412 microns to 12.01 microns]. VIIRS observations are used to generate 22 environmental data products (EDRs). This paper will briefly describe J1 VIIRS characterization and calibration performance and methodologies executed during the pre-launch testing phases by the independent government team, to generate the at-launch baseline radiometric performance, and the metrics needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). This paper will also provide an assessment of the sensor pre-launch radiometric performance, such as the sensor signal to noise ratios (SNRs), dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, bands spectral performance, response-vs-scan (RVS), near field and stray light responses. A set of performance metrics generated during the pre-launch testing program will be compared to the SNPP VIIRS pre-launch performance.

RSB↗

NASA NTRS2016

Techniques for Liquid Rocket Combustion Spontaneous Stability and Rough Combustion Assessments

This work presents techniques for liquid rocket engine combustion stability assessments with respect to spontaneous stability and rough combustion. Techniques covering empirical parameter extraction, which were established in prior works, are applied for three additional programs: the F-1 Gas Generator (F1GG) component test program, the RS-84 preburner component test program, and the Marshall Integrated Test Rig (MITR) program. Stability assessment parameters from these programs are compared against prior established spontaneous stability metrics and updates are identified. Also, a procedure for comparing measured with predicted mode shapes is presented, based on an extension of the Modal Assurance Criterion (MAC).

Kenny, R. J.↗

NASA NTRS2015

JPSS-1 VIIRS Pre-Launch Radiometric Performance

The first Joint Polar Satellite System (JPSS-1 or J1) mission is scheduled to launch in January 2017, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the J1 spacecraft completed its sensor level performance testing in December 2014. VIIRS instrument is expected to provide valuable information about the Earth environment and properties on a daily basis, using a wide-swath (3,040 km) cross-track scanning radiometer. The design covers the wavelength spectrum from reflective to long-wave infrared through 22 spectral bands, from 0.412 m to 12.01 m, and has spatial resolutions of 370 m and 740 m at nadir for imaging and moderate bands, respectively. This paper will provide an overview of pre-launch J1 VIIRS performance testing and methodologies, describing the at-launch baseline radiometric performance as well as the metrics needed to calibrate the instrument once on orbit. Key sensor performance metrics include the sensor signal to noise ratios (SNRs), dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, bands spectral performance, response-vs-scan (RVS), near field response, and stray light rejection. A set of performance metrics generated during the pre-launch testing program will be compared to the sensor requirements and to SNPP VIIRS pre-launch performance.

Oudrari, Hassan↗

NASA NTRS2018

An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-Launch Testing

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022 and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011 and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB) and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Our analysis results confirmed the good performance of J2 VIIRS, in general as good as previous VIIRS instruments and all non-compliances are expected to have low impact on data quality. Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS) and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

Oudrari, Hassan↗

NASA NTRS2019

Qualification of a Hybrid Propulsion System for the Mars Ascent Vehicle

Technology for a hybrid based propulsion system is being developed to support a potential Mars Sample Return campaign. A Mars Ascent Vehicle (MAV) concept for launching samples off of Mars, and delivering them to orbit for further transport to Earth may utilize hybrid propulsion due to the predicted favorable low temperature characteristics and high performance of this option. However, the hybrid option is still undergoing technology development to demonstrate these capabilities. Once development of a capable hybrid propulsion system is proven, further work will be required. This will include environmental testing relative to the mission, and integration with the vehicle reaction control systems and payload. Qualification of such a system will be a significant effort. It will require specialized procurements for the propellants and environments involved, and further testing of the more specialized designs. This paper details an estimate of the tasks required to complete development efforts from Technical Readiness Level 5 (TRL5) through qualification. A success based program was formulated to reach the required performance metrics sufficient for a standard Preliminary Design Review (PDR). Using task level inputs from team members cost and schedule were conceived for continued progress to Critical Design Review (CDR), then through Qualification.

Prince, Andrew↗

NASA NTRS1994

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗

DOE OSTI2024

Exploring Enhanced Dominant Resource Fairness Using Linear Programming Calculated Weights

Maintaining resource fairness while achieving optimization for various performance metrics such as resource utilization, turnaround time and job latency is a well-known resource scheduling challenge in cloud computing. Despite the significant progress made with the introduction of dominant resource fairness by Ghodsi et al., which ensures major allocation properties such as sharing incentive, strategy-proofness, envy-freeness and Pareto efficiency to be achieved

Yan, Bo [Binghamton University]↗

DOE OSTI2024

Metric Learning to Accelerate Convergence of Operator Splitting Methods

Recent developments in machine learning have led to promising advances in accelerating the solution of constrained optimization problems. Increasing demand for real-time decision-making capabilities in applications such as artificial intelligence and optimal control has led to a variety of proposed strategies for learning to produce fast solutions to optimization problems. For example, recent works have shown that it is possible to accelerate the convergence of optimization algorithms by learning to select their parameters, such as gradient descent stepsizes. This work proposes a new approach, in which the underlying metric spaces of proximal operator splitting algorithms are learned to maximize convergence rate. While prior works in optimization theory have derived optimal metrics in simple cases, no such result exists for many practical problem forms including general Quadratic Programming (QP). This paper shows how differentiable optimization can enable the end-to-end learning of proximal metrics, enhancing the convergence of proximal algorithms for QP problems beyond what is possible based on known theory. Additionally, the results illustrate a strong connection between the learned proximal metrics and active constraints at the optima, leading to an interpretation in which the predicted proximal metrics can be viewed as a form of active set prediction.

King, Ethan [BATTELLE (PACIFIC NW LAB)]↗

NASA NTRS2014

NASA's Space Launch System: An Enabling Capability for Discovery

The National Aeronautics and Space Administration's (NASA's) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for human spaceflight and scientific missions beyond Earth orbit. Developed with the goals of safety, affordability, and sustainability in mind, the SLS rocket will launch the Orion Multi-Purpose Crew Vehicle (MPCV), equipment, supplies, and major science missions for exploration and discovery. Making its first uncrewed test flight in 2017 and its first crewed flight in 2021, the SLS will evolve into the most powerful launch vehicle ever flown, capable of supporting human missions into deep space and to Mars. This paper will summarize the planned capabilities of the vehicle, the progress the SLS Program has made in the years since the Agency formally announced its architecture in September 2011, and the path the program is following to reach the launch pad in 2017 and then to evolve the 70 metric ton (t) initial lift capability to 130 t lift capability. The paper will outline the milestones the program has already reached, from developmental milestones such as the manufacture of the first flight hardware and recordbreaking engine testing, to life-cycle milestones such as the vehicle's Preliminary Design Review in the summer of 2013. The paper will also discuss the remaining challenges in both delivering the 70 t vehicle and in evolving its capabilities to the 130 t vehicle, and how the program plans to accomplish these goals. In addition, this paper will demonstrate how the Space Launch System is being designed to enable or enhance not only human exploration missions, but robotic scientific missions as well. Because of its unique launch capabilities, SLS will support simplifying spacecraft complexity, provide improved mass margins and radiation mitigation, and reduce mission durations. These capabilities offer attractive advantages for ambitious science missions by reducing infrastructure requirements, cost, and schedule. A traditional baseline approach for a mission to investigate the Jovian system would require a complicated trajectory with several gravity-assist planetary fly-bys to achieve the necessary outbound velocity. The SLS rocket, offering significantly higher C3 energies, can more quickly and effectively take the mission directly to its destination, providing scientific results sooner and at lower operational cost. The SLS rocket will launch payloads of unprecedented mass and volume, such as "monolithic" telescopes and in-space infrastructure, and will revolutionize science mission planning and design for years to come. As this paper will explain, SLS is making measurable progress toward becoming a global infrastructure asset for robotic and human scouts of all nations by harnessing business and technological innovations to deliver sustainable solutions for space exploration.

Creech, Stephen D.↗

NASA NTRS2014

NASA's Space Launch System: An Enabling Capability for Discovery

Creech, Stephen D.↗

NASA NTRS2011

Source Lines Counter (SLiC) Version 4.0

Source Lines Counter (SLiC) is a software utility designed to measure software source code size using logical source statements and other common measures for 22 of the programming languages commonly used at NASA and the aerospace industry. Such metrics can be used in a wide variety of applications, from parametric cost estimation to software defect analysis. SLiC has a variety of unique features such as automatic code search, automatic file detection, hierarchical directory totals, and spreadsheet-compatible output. SLiC was written for extensibility; new programming language support can be added with minimal effort in a short amount of time. SLiC runs on a variety of platforms including UNIX, Windows, and Mac OSX. Its straightforward command-line interface allows for customization and incorporation into the software build process for tracking development metrics. T

Monson, Erik W.↗

NASA NTRS2012

A Change Impact Analysis to Characterize Evolving Program Behaviors

Change impact analysis techniques estimate the potential effects of changes made to software. Directed Incremental Symbolic Execution (DiSE) is an intraprocedural technique for characterizing the impact of software changes on program behaviors. DiSE first estimates the impact of the changes on the source code using program slicing techniques, and then uses the impact sets to guide symbolic execution to generate path conditions that characterize impacted program behaviors. DiSE, however, cannot reason about the flow of impact between methods and will fail to generate path conditions for certain impacted program behaviors. In this work, we present iDiSE, an extension to DiSE that performs an interprocedural analysis. iDiSE combines static and dynamic calling context information to efficiently generate impacted program behaviors across calling contexts. Information about impacted program behaviors is useful for testing, verification, and debugging of evolving programs. We present a case-study of our implementation of the iDiSE algorithm to demonstrate its efficiency at computing impacted program behaviors. Traditional notions of coverage are insufficient for characterizing the testing efforts used to validate evolving program behaviors because they do not take into account the impact of changes to the code. In this work we present novel definitions of impacted coverage metrics that are useful for evaluating the testing effort required to test evolving programs. We then describe how the notions of impacted coverage can be used to configure techniques such as DiSE and iDiSE in order to support regression testing related tasks. We also discuss how DiSE and iDiSE can be configured for debugging finding the root cause of errors introduced by changes made to the code. In our empirical evaluation we demonstrate that the configurations of DiSE and iDiSE can be used to support various software maintenance tasks

Rungta, Neha Shyam↗