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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Flight duration, airspeed practices and altitude management of airplanes involved in the NASA VGH General Aviation Program

Flight duration, airspeed, and altitude information obtained from NASA velocity gravity height (VGH) recorders is presented for each of 95 general aviation airplanes flown in twin- and single-engine executive, personal, instructional, commercial survey, aerial application, aerobatic, commuter, and float operations. These data complement normal acceleration data obtained from the same airplanes and reported in NASA-TM-84660, and together they provide a data base for the design and analysis of general aviation airplane operations.

Jewel, Joseph W., Jr.↗
NASA NTRS1999

Improvement of Space Shuttle Main Engine Low Frequency Acceleration Measurements

The noise floor of low frequency acceleration data acquired on the Space Shuttle Main Engines is higher than desirable. Difficulties of acquiring high quality acceleration data on this engine are discussed. The approach presented in this paper for reducing the acceleration noise floor focuses on a search for an accelerometer more capable of measuring low frequency accelerations. An overview is given of the current measurement system used to acquire engine vibratory data. The severity of vibration, temperature, and moisture environments are considered. Vibratory measurements from both laboratory and rocket engine tests are presented.

Stec, Robert C.↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗
NASA NTRS2002

Monitoring the Microgravity Environment Quality On-board the International Space Station Using Soft Computing Techniques: Preliminary System Performance Results - Part 2

This paper presents the preliminary performance results of the artificial intelligence monitoring system in full operational mode using near real time acceleration data downlinked from the International Space Station. Preliminary microgravity environment characterization analysis result for the International Space Station (Increment-2), using the monitoring system is presented. Also, comparison between the system predicted performance based on ground test data for the US laboratory "Destiny" module and actual on-orbit performance, using measured acceleration data from the U.S. laboratory module of the International Space Station is presented. Finally, preliminary on-orbit disturbance magnitude levels are presented for the Experiment of Physics of Colloids in Space, which are compared with on ground test data. The ground test data for the Experiment of Physics of Colloids in Space were acquired from the Microgravity Emission Laboratory, located at the NASA Glenn Research Center, Cleveland, Ohio. The artificial intelligence was developed by the NASA Glenn Principal Investigator Microgravity Services Project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment of time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a dynamic graphical display, implemented in Java, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, structural modes, etc., and decide whether or not to run their experiments, whenever that is an option, based on the acceleration magnitude and frequency sensitivity associated with that experiment. This monitoring system detects primarily the vibratory disturbance sources. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗
NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗
NASA NTRS2006

Vehicle Transponder for Preemption of Traffic Lights

The purpose of this article is to describe, in more detail, the transponder installed in each vehicle that participates in the emergency traffic-light-preemption system described in the immediately preceding article. The transponder (see figure) is a fully autonomous data--collection, data-processing, information-display, and communication subsystem that performs robustly in preemption of traffic lights and monitoring of the statuses of street intersections. This transponder monitors the condition of the emergency vehicle in which it is installed and determines when the vehicle has been placed in an emergency-response condition with its siren and/or warning lights activated. Upon detection of such a condition, the transponder collects real-time velocity and acceleration data from the onboard diagnostic (OBD) computer of the vehicle. For this purpose, the transponder contains an OBD interface circuit, including a microprocessor that determines the manufacturer and model of the vehicle and then sends the appropriate commands to the OBD computer requesting the speed and acceleration data. At the same time, data from an onboard navigation system are collected to determine the location and the heading of the vehicle. Then acceleration, speed, position, and heading data are processed and combined with a vehicle-identification number and the resulting set of data is transmitted to monitoring and control units located at all intersections within communication range. When the unit at an intersection determines that this vehicle is approaching and has priority to preempt the intersection, it transmits a signal declaring the priority and the preemption to all participating vehicles (including this one) in the vicinity. If the unit at the intersection has determined that other participating vehicles are also approaching the intersection, then this unit also transmits, to the vehicle that has priority, a message that the other vehicles are approaching the same intersection. The texts of these messages, plus graphical symbols that show the directions and numbers of the approaching vehicles, are presented on the display panel of a computer that is part of the transponder.

Foster, Conrad↗
NASA NTRS2004

A status report on the characterization of the microgravity environment of the International Space Station

A primary objective of the International Space Station is to provide a long-term quiescent environment for the conduct of scientific research for a variety of microgravity science disciplines. Since continuous human presence on the space station began in November 2000 through the end of Increment-6, over 1260 hours of crew time have been allocated to research. However, far more research time has been accumulated by experiments controlled on the ground. By the end of the time period covered by this paper (end of Increment-6), the total experiment hours performed on the station are well over 100,000 hours (Expedition 6 Press Kit: Station Begins Third Year of Human Occupation, Boeing/USA/NASA, October 25, 2002). This paper presents the results of the on-going effort by the Principal Investigator Microgravity Services project, at NASA Glenn Research Center, in Cleveland, Ohio, to characterize the microgravity environment of the International Space Station in order to keep the microgravity scientific community apprised of the reduced gravity environment provided by the station for the performance of space experiments. This paper focuses on the station microgravity environment for Increments 5 and 6. During that period over 580 Gbytes of acceleration data were collected, out of which over 34,790 hours were analyzed. The results presented in this paper are divided into two sections: quasi-steady and vibratory. For the quasi-steady analysis, over 7794 hours of acceleration data were analyzed, while over 27,000 hours were analyzed for the vibratory analysis. The results of the data analysis are presented in this paper in the form of a grand summary for the period under consideration. For the quasi-steady acceleration response, results are presented in the form of a 95% confidence interval for the station during "normal microgravity mode operations" for the following three attitudes: local vertical local horizontal, X-axis perpendicular to the orbit plane and the Russian torque equilibrium attitude. The same analysis was performed for the station during "non-microgravity mode operations" to assess the station quasi-steady acceleration environment over a long period of time. The same type of analysis was performed for the vibratory, but a 95th percentile benchmark was used, which shows the overall acceleration magnitude during Increments 5 and 6. The results, for both quasi-steady and vibratory acceleration response, show that the station is not yet meeting the microgravity requirements during the microgravity mode operations. However, it should be stressed that the requirements apply only at assembly complete, whereas the results presented below apply up to the station's configuration at the end of Increment-6. c2004 Elsevier Ltd. All rights reserved.

ISS Project↗
NASA NTRS1994

Joint Launch + One Year Science Review of USML-1 and USMP-1 with the Microgravity Measurement Group

On September 22-24, 1993, investigators from the First United States Microgravity Laboratory (USML-1) and the First United States Microgravity Payload (USMP-1) Missions met with the Microgravity Measurement Group (MGMG) in Huntsville Alabama, to discuss science results and the microgravity environments from the respective missions. USML-1 was launched June 1992, and USMP-1 was launched October 1992. This document summarizes from the various investigations, the comprehensive results and highlights, and also serves as a combined mission report for the two missions. USML-1 was the first totally U.S.-sponsored mission dedicated to microgravity research and included 31 investigations in fluid dynamics, crystal growth, combustion, biotechnology, and technology demonstrations supported by 11 facilities. The papers in these proceedings attest to the wealth of information gleaned from the highly successful mission. On the USMP-1 mission, both the MEPHISTO and the Lambda Point experiments exceeded by over 100% their planned science objectives. The mission also marked the first time that acceleration data were down-linked and analyzed in real-time. The meeting, which concentrated on flight results, brought low-gravity investigators, accelerometer designers, and acceleration data analysis experts together. This format facilitated a tremendous amount of information exchange between these varied groups. Several of the experimenters showed results, some for the very first time, of the effects of residual accelerations on their experiment. The proceedings which are published in two volumes also contain transcriptions of the discussion periods following talks and also submittals from a simultaneous poster session.

Microgravity↗
NASA NTRS1994

Joint Launch + One Year Science Review of USML-1 and USMP-1 with the Microgravity Measurement Group

On September 22-24, 1993, investigators from the First United States Microgravity Laboratory (USML-1) and the First United States Microgravity Payload (USMP-1) Missions met with the Microgravity Measurement Group (MGMG) in Huntsville, Alabama, to discuss science results and the microgravity environments from the respective missions. USML-1 was launched June 1992, and USMP-1 was launched October 1992. This document summarizes from the various investigations, the comprehensive results and highlights, and also serves as a combined mission report for the two missions. USML-1 was the first totally U.S.-sponsored mission dedicated to microgravity research and included 31 investigations in fluid dynamics, crystal growth, combustion, biotechnology, and technology demonstrations supported by 11 facilities. The papers in these proceedings attest to the wealth of information gleaned from the highly successful mission. On the USMP-1 mission, both the MEPHISTO and the Lambda Point experiments exceeded by over 100% their planned science objectives. The mission also marked the first time that acceleration data were down-linked and analyzed in real-time. The meeting, which concentrated on flight results, brought low-gravity investigators, accelerometer designers, and acceleration data analysis experts together. This format facilitated a tremendous amount of information exchange between these varied groups. Several of the experimenters showed results, sane for the very first time, of the effects of residual accelerations on their experiment. The proceedings which are published in two volumes also contain transcriptions of the discussion periods following talks and also submittals from a simultaneous poster session.

Ramachandran, N.↗
NASA NTRS1994

Summary report of mission acceleration measurements for STS-60, SPACEHAB2, launched 11 February 1994

The STS-60 mission, which launched on 11 February 1994, carried seven accelerometer systems. This report describes the configuration of each of these systems, where they were located on the Orbiter and the name of a contact person for each system. The Space Acceleration Measurement System (SAMS) was one of the accelerometer systems on-board and this mission marked its eighth successful flight. Acceleration data are provided here for SAMS which flew under an agreement between the NASA Microgravity Science and Applications division and the NASA office of Advanced Concepts and Technology. Acceleration data for the other accelerometer systems are not presented here. SAMS was located in the commercial SPACEHAB laboratory, on its second flight. The SAMS system was configured with three triaxial sensor heads with filter cut-offs of 5, 10, and 50 Hz. The acceleration environment related to an experiment centrifuge, an experiment refrigerator freezer unit, a SAMS sensor head rotation, an Orbiter shudder, and payload deploy activities are discussed. In the Appendices, all of the data from SAMS Head B (10 Hz) are plotted to provide an overview of the environment during the majority of the STS-60 mission. An evaluation form is included at the end of the report to solicit users' comments about the usefulness of this series of reports.

Rogers, Melissa J. B.↗
NASA NTRS2006

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗
NASA NTRS1989

Measurement of hand dynamics in a microsurgery environment: Preliminary data in the design of a bimanual telemicro-operation test bed

Data describing the microsurgeon's hand dynamics was recorded and analyzed in order to provide an accurate model for the telemicrosurgery application of the Bimanual Telemicro-operation Test Bed. The model, in turn, will guide the development of algorithms for the control of robotic systems in bimanual telemicro-operation tasks. Measurements were made at the hand-tool interface and include position, acceleration and force between the tool-finger interface. Position information was captured using an orthogonal pulsed magnetic field positioning system resulting in measurements in all six degrees-of-freedom (DOF). Acceleration data at the hands was obtained using accelerometers positioned in a triaxial arrangement on the back of the hand allowing measurements in all three cartesian-coordinate axes. Force data was obtained by using miniature load cells positioned between the tool and the finger and included those forces experienced perpendicular to the tool shaft and those transferred from the tool-tissue site. Position data will provide a minimum/maximum reference frame for the robotic system's work space or envelope. Acceleration data will define the response times needed by the robotic system in order to emulate and subsequently outperform the human operator's tool movements. The force measurements will aid in designing a force-reflective, force-scaling system as well as defining the range of forces the robotic system will encounter. All analog data was acquired by a 16-channel analog-to-digital conversion system residing in a IBM PC/AT-compatible computer at the Center's laboratory. The same system was also used to analyze and present the data.

Charles, Steve↗
NASA NTRS1982

Development of a photovoltaic module qualification test based on combined-environment accelerated stress data

The U.S. Coast Guard has developed a qualification test to screen photovoltaic modules for utilization on marine aids to navigation. The test is based on a combined-environment of hot and cold saltwater immersion and air pressurization. The test has demonstrated a very high acceleration factor and excellent correlation of electrical failures with modules in a concurrent real-time marine exposure.

Trenchard, S. E.↗
DOE OSTI2025

First Joint Oscillation Analysis of Super-Kamiokande Atmospheric and T2K Accelerator Neutrino Data

The Super-Kamiokande and T2K Collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of 19.7⁢(16.3) × 10 20 protons on target in (anti)neutrino mode, the analysis finds a 1.9⁢𝜎 exclusion of 𝐶⁢𝑃 conservation (defined as 𝐽 𝐶⁢𝑃 = 0) and a 1.2⁢𝜎 exclusion of the inverted mass ordering.

Neutrino detection↗
DOE OSTI2021

Data-driven acceleration of thermal radiation transfer calculations with the dynamic mode decomposition and a sequential singular value decomposition

In this work, we present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem, a factor of several thousand on a cooling problem where the effective scattering ratio approaches unity, and a factor of 20 improvement in a realistic, multimaterial radiating shock problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗