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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
DOE OSTI2020

System and method for modeling and forecasting cyclical demand systems with dynamic controls and dynamic incentives

Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Analytical Functions for 200 West Pump-and-Treat SCADA Sensor Data

Historical operations at the U.S. Department of Energy’s Hanford Site included disposal of waste fluids to the subsurface in the 200 West Area on the Hanford Central Plateau. Subsequent infiltration of fluids has resulted in groundwater contamination with carbon tetrachloride, nitrate, uranium, technetium-99, and other contaminants. A pump-and-treat (P&T) system, with an extraction/injection well network and an aboveground treatment plant, was implemented as part of interim and final remedies in the 200 West area. The HYPATIA single-page web application (part of the SOCRATES suite) is being developed to provide access to and analysis of chemistry and treatment facility sensor data for this 200 West P&T system. For the web application, analytical algorithms were developed to perform summing, differencing, smoothing, outlier detection, change-point detection, mass flow rate, and injectivity calculations on the data. Candidate algorithms were identified and tested, with the best-performing algorithms then assembled for implementation in HYPATIA. Because HYPATIA is hosted on the Amazon Web Services (AWS) cloud computing platform, algorithms were implemented in a back-end AWS Lambda function that can be called by the HYPATIA front end. The Lambda function applies the requested data processing to specified data via functions written in R, Python, and JavaScript. Development, testing, and review of the data analysis algorithms was completed under an NQA-1 quality program. This new HYPATIA functionality will provide information to support site decisions regarding P&T system performance and optimization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Recognizing Unrecognized Sources of Uncertainty (USU) in Nuclear Data

Historically, time-of-flight (TOF) nuclear cross section measurements on different nuclides are assumed to be uncorrelated if they were recorded in different facilities with identical methods, identical facilities with different methods, and even identical facilities with identical methods. Ideally, measurements of different nuclides would truly be uncorrelated thus providing independent assessments of some cross section. In reality, correlations exist between measurements but are simply assumed to be unimportant. To eliminate these qualitative assumptions, in this paper we make a counter-intuitive suggestion to perform an intentionally correlated measurement of energy-differential fission and capture reactions for nuclides in a single criticality safety benchmark during a single experimental campaign. While this would introduce undesirable correlations, it would fully quantify correlations between datasets, rather than assume that the correlations do not exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2022

Projecting Power Converter Specific Power Through 2050 for Aerospace Applications

In order to analyze the potential fuel burn benefit from the electrification of aircraft powertrains, it is important to quantify the amount of weight that will be added to the aircraft for each additional component of the electric powertrain. This paper provides a projection of the specific power and efficiency of power converters, (AC-DC, DC-AC, or DC-DC), through the year 2050. Data was first collected on state of the art power converters in multiple application areas, creating a power converter database. Relevant specific powers were added to a set of historical data from 1976-2020, and then three different logistic curves were fit through the historical data to represent S-curve shaped growth through the year 2050. The three curves were differentiated by conservative, nominal, and aggressive assumptions for the year in which the logistic curve begins to bend down towards slower growth. With a 30% knockdown factor accounting for the additional weight required for a high altitude converter, projections range from the aggressive specific power projection of 52.9 kW/kg in 2050 to a much more conservative specific power of 12 kW/kg in which growth is limited due to certifiability concerns. Little historical data was found on converter efficiencies to project efficiency based on historical trends. Projections are based on expert opinion on yearly decreases in converter losses. 2050 projections range from 0.987 to 0.997.

fuel burn↗
DOE OSTI2025

Synthetic method of analogues for emerging infectious disease forecasting

The Method of Analogues (MOA) has gained popularity in the past decade for infectious disease forecasting due to its non-parametric nature. In MOA, the local behavior observed in a time series is matched to the local behaviors of several historical time series. The known values that directly follow the historical time series that best match the observed time series are used to calculate a forecast. This non-parametric approach leverages historical trends to produce forecasts without extensive parameterization, making it highly adaptable. However, MOA is limited in scenarios where historical data is sparse. This limitation was particularly evident during the early stages of the COVID-19 pandemic, where the emerging global epidemic had little-to-no historical data. In this work, we propose a new method inspired by MOA, called the Synthetic Method of Analogues (sMOA). sMOA replaces historical disease data with a library of synthetic data that describe a broad range of possible disease trends. This model circumvents the need to estimate explicit parameter values by instead matching segments of ongoing time series data to a comprehensive library of synthetically generated segments of time series data. We demonstrate that sMOA has competitive performance with state-of-the-art infectious disease forecasting models, out-performing 78% of models from the COVID-19 Forecasting Hub in terms of averaged Mean Absolute Error and 76% of models from the COVID-19 Forecasting Hub in terms of averaged Weighted Interval Score. Additionally, we introduce a novel uncertainty quantification methodology designed for the onset of emerging epidemics. Developing versatile approaches that do not rely on historical data and can maintain high accuracy in the face of novel pandemics is critical for enhancing public health decision-making and strengthening preparedness for future outbreaks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Trends in the Sea Ice Cover Using Enhanced and Compatible AMSR-E, SSM/I and SMMR Data

Arguably, the most remarkable manifestation of change in the polar regions is the rapid decline (of about -10 %/decade) in the Arctic perennial ice cover. Changes in the global sea ice cover, however, are more modest, being slightly positive in the Southern Hemisphere and slightly negative in the Northern Hemisphere, the significance of which has not been adequately assessed because of unknown errors in the satellite historical data. We take advantage of the recent and more accurate AMSR-E data to evaluate the true seasonal and interannual variability of the sea ice cover, assess the accuracy of historical data, and determine the real trend. Consistently derived ice concentrations from AMSR-E, SSM/I, and SMMR data were analyzed and a slight bias is observed between AMSR-E and SSM/I data mainly because of differences in resolution. Analysis of the combine SMMR, SSM/I and AMSR-E data set, with the bias corrected, shows that the trends in extent and area of sea ice in the Arctic region is -3.4 +/- 0.2 and -4.0 +/- 0.2 % per decade, respectively, while the corresponding values for the Antarctic region is 0.9 +/- 0.2 and 1.7 .+/- 0.3 % per decade. The higher resolution of the AMSR-E provides an improved determination of the location of the ice edge while the SSM/I data show an ice edge about 6 to 12 km further away from the ice pack. Although the current record of AMSR-E is less than 5 years, the data can be utilized in combination with historical data for more accurate determination of the variability and trends in the ice cover.

Comiso, Josefino C.↗
NASA NTRS1999

Review of historical monitoring data on Techa River contamination

The Mayak Production Association was the first Russian site for the production and separation of plutonium. The extensive increase in plutonium production during 1948-1955, as well as the absence of reliable waste-management technology, resulted in significant releases of liquid radioactive effluent into the rather small Techa River. This resulted in chronic external and internal exposure of about 30,000 residents of riverside communities; these residents form the cohort of an epidemiologic investigation. Analysis of the available historical monitoring data indicates that the following reliable data sets can be used for reconstruction of doses received during the early periods of operation of the Mayak Production Association: Temporal pattern of specific beta activity of river water for several sites in the upper Techa region since July 1951; average annual values of specific beta activity of river water and bottom sediments as a function of downstream distance for the whole river since 1951; external gamma-exposure rates near the shoreline as a function of downstream distance for the whole Techa River since 1952; and external gamma-exposure rate as a function of distance from the shoreline for several sites in the upper and middle Techa since 1951.

NASA Discipline Radiation Health↗
NASA NTRS1979

Performance deterioration based on in-service engine data: JT9D jet engine diagnostics program

Results of analyses of engine performance deterioration trends and levels with respect to service usage are presented. Thirty-two JT9D-7A engines were selected for this purpose. The selection of this engine fleet provided the opportunity of obtaining engine performance data starting before the first flight through initial service such that the trend and levels of engine deterioration related to both short and long term deterioration could be more carefully defined. The performance data collected and analyzed included in-flight, on wing (ground), and test stand prerepair and postrepair performance calibrations with expanded instrumentation where feasible. The results of the analyses of these data were used to: (1) close gaps in previously obtained historical data as well as augment the historical data with more carefully obtained data; (2) refine preliminary models of performance deterioration with respect to usage; (3) establish an understanding of the relationships between ground and altitude performance deterioration trends; (4) refine preliminary recommendations concerning means to reduce and control deterioration; and (5) identify areas where additional effort is required to develop an understanding of complex deterioration issues.

Sallee, G. P.↗
DOE OSTI2023

EAGLE-I Power Outage Data Information

This DOI contains information on the EAGLE-I power outage dataset and serves as a blanket DOI for all EAGLE-I historic data. Historic power outage data from specific years have been linked to this DOI.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
NASA NTRS2015

Appendix A: NAS-Wide Encounter Rate Evaluation Using Historical Radar Data and the Airspace Concept Evaluation System (ACES)

Regulations that establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall level of safety required to operate in the airspace. Several key gaps must be addressed in order to link equipment requirements to an airspace level of safety. Foremost among these is the calculation of the relative effectiveness of a particular system to mitigate violations of a separation standard with other aircraft, which is known as the systems risk ratio. The risk ratio is calculated as the probability of mid-air collision with a DAA system divided by the probability of mid-air collision without a DAA system. The risk ratio of a DAA system, in combination with the risk ratios of other collision avoidance mitigations, will determine the overall safety of the airspace measured in terms of the number of mid-air collisions per flight hour. Defining the required risk ratio that the DAA system needs to ensure the safety of the airspace requires an evaluation of the current airspace and a simulated evaluation that incorporates UAS aerodynamic performance and the mission characteristics of future UAS operations that are projected to be conducted in areas that interact with current operations. These evaluations will produce the frequency of encounters that currently exist in the airspace and those that could be generated with the introduction of UAS. Together, the frequency of encounters, an evaluation of unmitigated risk of collision, and a desired level of safety of the airspace will yield a required risk ratio of the DAA system. This study will focus on evaluating the encounter rates between aircraft based on historical radar data and encounter rates that could occur based on simulated UAS missions.

Unmanned Aircraft Systems↗
NASA NTRS2022

Specific Power and Efficiency Projections of Electric Machines and Circuit Protection Exploration for Aircraft Applications

The purpose of this paper is to generate specific power and efficiency projections through the year 2050 for electric machines for aircraft applications. A general literature review was performed to identify the types of electric machines that are commonly used and which types have the biggest potential for future aircraft applications due to their high specific power and efficiency. A database with historical data was built to include parameters such as weight [kg], rated power [kW], specific power [kW/kg], RPM, efficiency, year, motor cooling type, application type and motor type to allow for trend identification and accurate projections. Once the data was gathered, multiple curve fits on the historical data were generated and extrapolated to produce the projections for specific power according to conservative, nominal and aggressive projection scenarios. A different process was followed for the efficiency projections due to the scattered nature of the data. A state of the art (SoA) value for efficiency was identified through literature review and was used to create the conservative, nominal and aggressive projections for the time frames of 2030, 2040, and 2050. The efficiency and the specific power projections of EMs for 2050 are 0.989 and 50kW/kg respectively. This paper will also be examining circuit protection as it is an additional component of electric powertrains.

electric machines↗
NASA NTRS2010

GLGM-3: A Degree-ISO Lunar Gravity Model from the Historical Tracking Data of NASA Moon Orbiters

In preparation for the radio science experiment of the Lunar Reconnaissance Orbiter (LRO) mission, we analyzed the available radio tracking data of previous NASA lunar orbiters. Our goal was to use these historical observations in combination with the new low-altitude data to be obtained by LRO. We performed Precision Orbit Determination on trajectory arcs from Lunar Orbiter 1 in 1966 to Lunar Prospector in 1998, using the GEODYN II program developed at NASA Goddard Space Flight Center. We then created a set of normal equations and solved for the coefficients of a spherical harmonics expansion of the lunar gravity potential up to degree and order 150. The GLGM-3 solution obtained with a global Kaula constraint (2.5 x 10(exp -4)/sq l) shows good agreement with model LP150Q from the Jet Propulsion Laboratory, especially over the nearside. The levels of data fit with both gravity models are very similar (Doppler RMS of approx.0.2 and approx. 1-2 mm/s in the nominal and extended phases, respectiVely). Orbit overlaps and uncertainties estimated from the covariance matrix also agree well. GLGM-3 shows better correlation with lunar topography and admittance over the nearside at high degrees of expansion (l > 100), particularly near the poles. We also present three companion solutions, obtained with the same data set but using alternate inversion strategies that modify the power law constraint and expectation of the individual spherical harmonics coefficients. We give a detailed discussion of the performance of this family of gravity field solutions in terms of observation fit, orbit quality, and geophysical consistency.

Mazarico, E.↗
NASA NTRS2010

Validation of the Integrated Medical Model Using Historical Space Flight Data

The Integrated Medical Model (IMM) utilizes Monte Carlo methodologies to predict the occurrence of medical events, utilization of resources, and clinical outcomes during space flight. Real-world data may be used to demonstrate the accuracy of the model. For this analysis, IMM predictions were compared to data from historical shuttle missions, not yet included as model source input. Initial goodness of fit test-ing on International Space Station data suggests that the IMM may overestimate the number of occurrences for three of the 83 medical conditions in the model. The IMM did not underestimate the occurrence of any medical condition. Initial comparisons with shuttle data demonstrate the importance of understanding crew preference (i.e., preferred analgesic) for accurately predicting the utilization of re-sources. The initial analysis demonstrates the validity of the IMM for its intended use and highlights areas for improvement.

Kerstman, Eric L.↗
NASA NTRS1979

LACIE large area acreage estimation

A sample wheat acreage for a large area is obtained by multiplying its small grains acreage estimate as computed by the classification and mensuration subsystem by the best available ratio of wheat to small grains acreages obtained from historical data. In the United States, as in other countries with detailed historical data, an additional level of aggregation was required because sample allocation was made at the substratum level. The essential features of the estimation procedure for LACIE countries are included along with procedures for estimating wheat acreage in the United States.

Chhikara, R. S.↗
NASA NTRS1998

Technology Assessment of High Capacity Data Storage Systems: Can We Avoid a Data Survivability Crisis?

This technology assessment of long-term high capacity data storage systems identifies an emerging crisis of severe proportions related to preserving important historical data in science, healthcare, manufacturing, finance and other fields. For the last 50 years, the information revolution, which has engulfed all major institutions of modem society, centered itself on data-their collection, storage, retrieval, transmission, analysis and presentation. The transformation of long term historical data records into information concepts, according to Drucker, is the next stage in this revolution towards building the new information based scientific and business foundations. For this to occur, data survivability, reliability and evolvability of long term storage media and systems pose formidable technological challenges. Unlike the Y2K problem, where the clock is ticking and a crisis is set to go off at a specific time, large capacity data storage repositories face a crisis similar to the social security system in that the seriousness of the problem emerges after a decade or two. The essence of the storage crisis is as follows: since it could take a decade to migrate a peta-byte of data to a new media for preservation, and the life expectancy of the storage media itself is only a decade, then it may not be possible to complete the transfer before an irrecoverable data loss occurs. Over the last two decades, a number of anecdotal crises have occurred where vital scientific and business data were lost or would have been lost if not for major expenditures of resources and funds to save this data, much like what is happening today to solve the Y2K problem. A pr-ime example was the joint NASA/NSF/NOAA effort to rescue eight years worth of TOVS/AVHRR data from an obsolete system, which otherwise would have not resulted in the valuable 20-year long satellite record of global warming. Current storage systems solutions to long-term data survivability rest on scalable architectures having parallel paths for data migration.

Halem, M.↗
DOE OSTI2025

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗
DOE OSTI2025

Monitored Natural Attenuation (MNA) Assessment for the Chemicals, Metals, and Pesticides (CMP) Pits Operable Unit (OU) and the Pen Branch Wetland

In October 2024, Savannah River National Laboratory (SRNL) was tasked to conduct an independent review of groundwater data and assess the monitored natural attenuation (MNA) performance related to the Chemicals, Metals, and Pesticides (CMP) Pits Operable Unit (OU) located in the central portion of the Savannah River Site (SRS). The SRNL assessment of MNA entailed an independent analysis of groundwater concentration data, groundwater elevation data, available surface water concentration data, soil concentration data, and relevant historical geological characterization logs for the CMP Pits OU. Historical data tables and records were obtained from both the Savannah River Nuclear Solutions - Area Completion Projects (SRNSACP) team and South Carolina State University (SCSU) and condensed into new data sets by the SRNL project team for more targeted analysis of MNA performance characteristics. All data pertaining to groundwater concentration, surface water concentration, and groundwater elevation were restricted to collection dates after any known active remediation for the CMP OU.

54 ENVIRONMENTAL SCIENCES↗