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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

Reducing costs of managing and accessing navigation and ancillary data by relying on the extensive capabilities of NASA's spice system

The SPICE system of navigation and ancillary data possesses a number of traits that make its use in modern space missions of all types highly cost efficient. The core of the system is a software library providing API interfaces for storing and retrieving such data as trajectories, orientations, time conversions, and instrument geometry parameters. Applications used at any stage of a mission life cycle can call SPICE APIs to access this data and compute geometric quantities required for observation planning, engineering assessment and science data analysis. SPICE is implemented in three different languages, supported on 20+ computer environments, and distributed with complete source code and documentation. It includes capabilities that are extensively tested by everyday use in many active projects and are applicable to all types of space missions - flyby, orbiters, observatories, landers and rovers. While a customer's initial SPICE adaptation for the first mission or experiment requires a modest effort, this initial effort pays off because adaptation for subsequent missions/experiments is just a small fraction of the initial investment, with the majority of tools based on SPICE requiring no or very minor changes.

ancillary data↗
NASA NTRSDate not supplied

Interactive Framework to Support Open Model-Data Validation Efforts at the CCMC

Validation of models using observation data has been a central activity at the Community Coordinated Modeling Center (CCMC) over more than a decade. The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework is a database-driven implementation of the interactive analysis of model-data comparisons that simultaneously provides a view across a multitude of locations and time periods. CAMEL thus extends the single-location or single-trajectory timeseries data comparison capabilities provided by the CCMC online visualization that formed the backbone of initial validation efforts. We demonstrate CAMEL capabilities for an example application to study Neutral Density in the upper atmosphere among comparisons in the heliosphere, the Earth’s radiation belt, magnetosphere, and ionosphere-thermosphere-mesosphere domains.

Lutz Rastaetter↗
NASA NTRS1966

Pioneer project support

Pioneer project support - Doppler tracking data analysis, trajectory dispersions and initial tracking station acquisition, and gas leak effect on orbit

PIONEER SPACE PROBE↗
NASA NTRS1984

Elliptical Orbit Performance Computer Program

Elliptical Orbit Performance (ELOPE) computer program for analyzing orbital performance of space boosters uses orbit insertion data obtained from trajectory simulation to generate parametric data on apogee and perigee altitudes as function of payload data. Data used to generate presentation plots that display elliptical orbit performance capability of space booster.

Myler, T.↗
NASA NTRS1992

Radiation safety in aircraft operations

Data from a 7-yr flight experiment program to measure the significant biological components (tissue ionization rates, neutron flux, and nuclear reaction star rates) as a function of solar cycle, altitude, latitude and longitude from which biological risk from radiation is estimated are used to evaluate radiation dose and dose equivalents along specific flight trajectories. The data base used and the corresponding time-dependent global model are described. Ionization rates in air measured by argon filled chambers at solar minimum and maximum, and radiation measurements of the Brookhaven National Laboratory instrument compared to the present model are illustrated in tabular form. The global pressure distribution for solstice conditions at 14 km is shown.

Wilson, J. W.↗
NASA NTRS2002

Benefits of Nuclear Electric Propulsion for Outer Planet Exploration

Nuclear electric propulsion (NEP) offers significant benefits to missions for outer planet exploration. Reaching outer planet destinations, especially beyond Jupiter, is a struggle against time and distance. For relatively near missions, such as a Europa lander, conventional chemical propulsion and NEP offer similar performance and capabilities. For challenging missions such as a Pluto orbiter, neither chemical nor solar electric propulsion are capable while NEP offers acceptable performance. Three missions are compared in this paper: Europa lander, Pluto orbiter, and Titan sample return, illustrating how performance of conventional and advanced propulsion systems vary with increasing difficulty. The paper presents parametric trajectory performance data for NEP. Preliminary mass/performance estimates are provided for a Europa lander and a Titan sample return system, to derive net payloads for NEP. The NEP system delivers payloads and ascent/descent spacecraft to orbit around the target body, and for sample return, delivers the sample carrier system from Titan orbit to an Earth transfer trajectory. A representative scientific payload 500 kg was assumed, typical for a robotic mission. The resulting NEP systems are 100-kWe class, with specific impulse from 6000 to 9000 seconds.

Kos, Larry↗
DOE OSTI2024

In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)

Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Status on the Recovery of Voyager Plasma Electron Observations at Jupiter

We give status report on the recovery of Voyager 1 and 2 plasma electron observations during their Jupiter flybys. The plan is to complete this analysis including new results never published before. The original summary data tapes and later datafiles were evidently permanently lost along with our past analysis results of the plasma electron observations except for that shown in previous publications. These summary data tapes included the plasma ion and electron raw datafiles, status words needed to convert data numbers to currents, SEDR data with trajectory and attitude information and magnetic field measurements. In addition to recovering the plasma electron plasma observations (electron intensities and fluid parameters of the thermal and suprathermal electron populations, respectively), the SEDR trajectory information during the out bound passes were lost but fortunately in the past the SEDR files were converted to Spice Kernals, so this unexpected problem was solved. In addition, we had to rewrite our read routines it looked like the previous read routines so the rest of the Fortran code could be used; the Fortran- code had to be modified to work with the latest compilers and computer platforms. We will report on the- status of our work- originally funded under the Planetary Data Archiving, Restoration, and Tools (PDART)program but now being funded by the Internal Scientist Funding Model (ISFM) Exosphere Ionosphere Magnetospheres Modeling (EIMM)program at NASA Goddard Space Flight Center.

E C Sittler Jr.↗
NASA NTRS2013

Analysis and Results from a Flush Airdata Sensing System in Close Proximity to Firing Rocket Nozzles

This paper presents information regarding the nosecap Flush Airdata Sensing (FADS) system on Orion’s Pad Abort 1 (PA-1) vehicle. The purpose of the nosecap FADS system was to test whether or not useful data could be obtained from a FADS system if it was placed in close proximity to firing rocket nozzles like the Attitude Control Motor (ACM) nozzles on the PA-1 Launch Abort System. The nosecap FADS system used pressure measurements from a series of pressure ports which were arranged in a cruciform pattern and flush with the surface of the vehicle to estimate values of angle of attack, angle of sideslip, Mach number, impact pressure, and freestream static pressure. This paper will present the algorithms employed by the FADS system along with the development of the calibration datasets and a comparison of the final results to the Best Estimated Trajectory (BET) data for PA-1. Also presented in this paper is a Computational Fluid Dynamics (CFD) study to explore the impact of the ACM on the nosecap FADS system. The comparison of the nosecap FADS system results to the BET and the CFD study showed that more investigation is needed to quantify the impact of the firing rocket motors on the FADS system.

Flush Air Data Sensing System↗
NASA NTRS1975

Data correlation and analysis of arc tunnel and wind tunnel tests of RSI joints and gaps, phase 2. Volume 1: Technical report

Heat transfer data measured in gaps representative of those being employed for joints in the space shuttle reusable surface insulation (RSI) thermal protection systems (TPS) were assimilated, analyzed, and correlated. Several types of gap were investigated with emphasis on simple butt joints. Gap widths ranged from 0.0 to 0.76 cm and depths ranged from 1 to 6 cm. Laminar, transitional, and turbulent boundary layer flows over the gap opening were investigated. The angle between gap axis and external flow was varied between 0 and pi/2 radians. The contoured cross section gap performed significantly better than all other wide gaps and slightly better than all other narrow gap geometries. Three dimensional heating variations were observed within gaps in the absence of external flow pressure gradients. Interactions between heating within gaps and heating of adjacent top tile surfaces were observed. Gaps aligned with the flow were observed to promote boundary layer transition. Heat transfer correlation equations were obtained for many of the tests. The TPS thickness requirements with and without gaps were computed for a current shuttle entry trajectory. Experimental data employed in the study are summarized. A description of each test facility, run schedule and test conditions, model descriptive information, and heat flux data are included.

Cristensen, H. E.↗
NASA NTRS2010

Multi Sector Planning Tools for Trajectory-Based Operations

This paper discusses a suite of multi sector planning tools for trajectory-based operations that were developed and evaluated in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. The toolset included tools for traffic load and complexity assessment as well as trajectory planning and coordination. The situation assessment tools included an integrated suite of interactive traffic displays, load tables, load graphs, and dynamic aircraft filters. The planning toolset allowed for single and multi aircraft trajectory planning and data communication-based coordination of trajectories between operators. Also newly introduced was a real-time computation of sector complexity into the toolset that operators could use in lieu of aircraft count to better estimate and manage sector workload, especially in situations with convective weather. The tools were used during a joint NASA/FAA multi sector planner simulation in the AOL in 2009 that had multiple objectives with the assessment of the effectiveness of the tools being one of them. Current air traffic control operators who were experienced as area supervisors and traffic management coordinators used the tools throughout the simulation and provided their usefulness and usability ratings in post simulation questionnaires. This paper presents these subjective assessments as well as the actual usage data that was collected during the simulation. The toolset was rated very useful and usable overall. Many elements received high scores by the operators and were used frequently and successfully. Other functions were not used at all, but various requests for new functions and capabilities were received that could be added to the toolset.

Prevot, Thomas↗
DOE OSTI2026

Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method

While recent advances in deep learning have shown promising efficiency gains in solving time-dependent partial differential equations (PDEs), matching the accuracy of conventional numerical solvers still remains a challenge. One strategy to improve the accuracy of deep learning-based solutions for time-dependent PDEs is to use the learned model as the coarse propagator in the Parareal method and a traditional numerical method as the fine solver. However, successful integration of deep learning into the Parareal method requires consistency between the coarse and fine solvers, particularly for PDEs exhibiting rapid changes such as sharp transitions. Here, to ensure this consistency, we propose using convolutional neural networks (CNNs) to learn the fully discrete time-stepping operator defined by the same numerical scheme employed as the fine solver. We demonstrate the effectiveness of the proposed method in solving the classical and mass-conservative Allen–Cahn (AC) equations. Through iterative updates in the Parareal algorithm, our approach achieves a significant computational speedup compared to traditional fine solvers while converging to high-accuracy solutions. Our results highlight that the proposed hybrid Parareal algorithm effectively accelerates simulations, particularly when implemented on multiple GPUs, and converges to the desired accuracy in only a few iterations. Another advantage of our method is that the CNN model is trained on trajectory-based data generated from random initial conditions, such that the trained model can be used to solve the AC equations with various initial conditions without retraining. This work demonstrates the potential of integrating neural network methods into parallel-in-time frameworks for efficient and accurate simulations of time-dependent PDEs.

97 MATHEMATICS AND COMPUTING↗