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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Wind tunnel investigation of a large-scale upper surface blown-flap transport model having two engines

An investigation has been conducted to determine the aerodynamic characteristics of a large-scale subsonic jet transport model with an upper surface blowing flap system that would augment lift. The model had a 25 deg swept wing of aspect ratio 7.89 and two turbofan engines with the engine centerline located at 0.256 of the wing semispan. The lift of the flap system was augmented by turbofan exhaust impingement on the Coanda surface. Results were obtained for several flap deflections and engine nozzle configurations at jet momentum coefficients from 0 to 4.0. Three-component longitudinal data are presented with two engines operating. Limited longitudinal and lateral data are presented with an engine out. In addition, limited exhaust and flap pressure data are presented.

Aoyagi, K.↗
NASA NTRS2019

Directional limits on persistent gravitational waves using data from Advanced LIGO’s first two observing runs

We perform an unmodeled search for persistent, directional gravitational wave (GW) sources using data from the first and second observing runs of Advanced LIGO. We do not find evidence for any GW signals. We place limits on the broadband GW flux emitted at 25 Hz from point sources with a power law spectrum at F(α;Θ) < (0.05–25) × 10^(−8) erg/sq. cmsHz and the (normalized) energy density spectrum in GWs at 25 Hz from extended sources at Ω(α)(Θ) < (0.19–2.89) × 10^(−8) per sr where α is the spectral index of the energy density spectrum. These represent improvements of 2.5–3× over previous limits. We also consider point sources emitting GWs at a single frequency, targeting the directions of Sco X-1, SN 1987A, and the Galactic center. The best upper limits on the strain amplitude of a potential source in these three directions range from h(0) < (3.6–4.7) × 10^(−25), 1.5× better than previous limits set with the same analysis method. We also report on a marginally significant outlier at 36.06 Hz. This outlier is not consistent with a persistent gravitational-wave source as its significance diminishes when combining all of the available data.

B. P. Abbott↗
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↗
DOE OSTI2022

End-Use Load Profiles for the U.S. Building Stock: Practical Guidance on Accessing and Using the Data

This report describes example applications and considerations for using the National Renewable Energy Lab’s ResStock and ComStock end use load profiles (EULP). The report begins with an introduction to the three year project, and then provides instructions on accessing the EULP data and considerations for using the EULP and limitations of the data. The remainder of the report is on EULP use cases, including a variety of electricity planning use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

Solar activity and total atmospheric ozone

Analyses are presented of the association between two parameters of solar activity (Lyman-alpha and 10.7 cm flux) and global total ozone as determined from Nimbus observations for the period April-December 1970 (IRIS observations), and April 1970-April 1972 (BUV observations); and between Lyman-alpha and global total ozone as observed at ground stations and the ozone concentration in the lower and middle stratosphere in the subtropics for the period 1969-1972. It is shown that the high correlations discussed in other published studies between these solar paramters and nine months of IRIS data resulted from the use of a very limited, seasonally unfiltered data set.

London, J.↗
NASA NTRS1998

Vertical Profiles of Cloud Condensation Nuclei, Condensation Nuclei, Optical Aerosol, Aerosol Optical Properties, and Aerosol Volatility Measured from Balloons

Under the support of this grant a balloon-borne gondola containing a variety of aerosol instruments was developed and flown from Laramie, Wyoming, (41 deg N, 105 deg W) and from Lauder, New Zealand (45 deg S, 170 deg E). The gondola includes instruments to measure the concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), optically detectable aerosol (OA.) (r greater than or equal to 0.15 - 2.0 microns), and optical scattering properties using a nephelometer (lambda = 530 microns). All instruments sampled from a common inlet which was heated to 40 C on ascent and to 160 C on descent. Flights with the CN counter, OA counter, and nephelometer began in July 1994. The CCN counter was added in November 1994, and the engineering problems were solved by June 1995. Since then the flights have included all four instruments, and were completed in January 1998. Altogether there were 20 flights from Laramie, approximately 5 per year, and 2 from Lauder. Of these there were one or more engineering problems on 6 of the flights from Laramie, hence the data are somewhat limited on those 6 flights, while a complete data set was obtained from the other 14 flights. Good CCN data are available from 12 of the Laramie flights. The two flights from Lauder in January 1998 were successful for all measurements. The results from these flights, and the development of the balloon-bome CCN counter have formed the basis for five conference presentations. The heated and unheated CN and OA measurements have been used to estimate the mass fraction of the aerosol volatile, while comparisons of the nephelometer measurements were used to estimate the light scattering, associated with the volatile aerosol. These estimates were calculated for 0.5 km averages of the ascent and descent data between 2.5 km and the tropopause, near 11.5 km.

Deshler, T.↗
NASA NTRS1959

Wind-Tunnel Investigation at Subsonic and Supersonic Speeds of the Static and Dynamic Stability Derivatives of an Airplane Model with an Unswept Wing and a High Horizontal Tail

Results are presented of a wind-tunnel investigation to evaluate the static and dynamic stability derivatives of a model with a low-aspect-ratio unswept wing and a high horizontal tail. In addition to results for the complete model, results were also obtained of the body alone, body and wing, and body and tail. Data were obtained in the Mach number range from 0.65 to 2.2, at a Reynolds number of 2 million based on the wing mean aerodynamic chord. The angle-of-attack range for most of the data was -11.5 deg to 18 deg. A limited amount of data was obtained with fixed transition. A correspondence between the damping in pitch and the static stability, previously noted in other investigations, was also observed in the present results. The effect observed was that a decrease (or increase) in the static stability was accompanied by an increase (or decrease) in the damping in pitch. A similar correspondence was observed between the damping in yaw and the static-directional stability. Results from similar tests of the same model configuration in two other facilities over different speed ranges are presented for comparison. It was found that most of the results from the three investigations correlated reasonably well. Estimates of the rotary derivatives were made using available procedures. Comparison with the experimental results indicates the need for development of more precise estimation procedures.

Lessing, Henry C.↗
NASA NTRS2019

North American Extreme Precipitation Events and Related Large-Scale Meteorological Patterns: a Review of Statistical Methods, Dynamics, Modeling, and Trends

This paper surveys the current state of knowledge regarding Large-Scale Meteorological Patterns (LSMPs) associated with short-duration (less than one week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some 4 promising analysis techniques have been identified and the LSMP perspective is useful for evaluating model dynamics.

Mathew Barlow↗
DOE OSTI2023

Best-estimate Modeling of the High Temperature Test Facility with RELAP5-3D

Prismatic HTGRs are a concept of interest for near-term deployment. While plenty of validation data exist for standalone neutronics or multiphysics modeling, the availability of integral effects thermal hydraulics validation data is more limited. The High Temperature Test Facility provides such data and is used as the basis for the High-Temperature Gas-Cooled Reactor Thermal Hydraulics Benchmark. This presentation presents results of best-estimate modeling of HTTF experiments PG-27 and PG-29 using the RELAP5-3D ring model developed at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Data-driven organic solubility prediction at the limit of aleatoric uncertainty

Abstract Small molecule solubility is a critically important property which affects the efficiency, environmental impact, and phase behavior of synthetic processes. Experimental determination of solubility is a time- and resource-intensive process and existing methods for in silico estimation of solubility are limited by their generality, speed, and accuracy. This work presents two models derived from the FASTPROP and CHEMPROP architectures and trained on BigSolDB which are capable of predicting solubility at arbitrary temperatures for a wide range of small molecules in organic solvent. Both extrapolate to unseen solutes 2–3 times more accurately than the current state-of-the-art model and we demonstrate that they are approaching the aleatoric limit (0.5–1$$\log S$$ log S ) of available test data, suggesting that further improvements in prediction accuracy require more accurate datasets. The FASTPROP-derived model (called FASTSOLV) and the CHEMPROP-based model are open source, freely accessible via a Python package and web interface, highly reproducible, and up to 2 orders of magnitude faster than current alternatives.

Science & Technology - Other Topics↗
DOE OSTI2024

Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet

cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.

43 PARTICLE ACCELERATORS↗
NASA NTRS1993

Impeller flow field characterization with a laser two-focus velocimeter

Use of Computational Fluid Dynamics (CFD) codes, prevalent in the rocket engine turbomachinery industry, necessitates data of sufficient quality and quantity to benchmark computational codes. Existing data bases for typical rocket engine configurations, in particular impellers, are limited. In addition, traditional data acquisition methods have several limitations: typically transducer uncertainties are 0.5% of transducer full scale and traditional pressure probes are unable to provide flow characteristics in the circumferential (blade-to-blade) direction. Laser velocimetry circumvents these limitations by providing +0.5% uncertainty in flow velocity and +0.5% uncertainty in flow angle. The percent of uncertainty in flow velocity is based on the measured value, not full range capability. The laser electronics multiple partitioning capability allows data acquired between blades as the impeller rotates, to be analyzed separately, thus providing blade-to-blade flow characterization. Unlike some probes, the non-intrusive measurements made with the laser velocimeter does not disturb the flow. To this end,, and under Contract (NAS8-38864) to the National Aeronautics and Space Administration (NASA) at Marshall Space Flight Center (MSFC), an extensive test program was undertaken at Rocketdyne. Impellers from two different generic rocket engine pump configurations were examined. The impellers represent different spectrums of pump design: the Space Shuttle Main Engine (SSME) high pressure fuel turbopump (HPFTP) impeller was designed in the 1 1970's the Consortium for CFD application in Propulsion Technology Pump Stage Technology Team (Pump Consortium) optimized impeller was designed with the aid of modern computing techniques. The tester configuration for each of the impellers consisted of an axial inlet, an inducer, a diffuser, and a crossover discharge. While the tested configurations were carefully chosen to be representative of generic rocket engine pumps, several features of both testers were intentionally atypical. A crossover discharge, downstream of the impeller, rather than a volute discharge was used to minimize asymmetric flow conditions that might be reflected in the impeller discharge flow data. Impeller shroud wear ring radial clearances were purposely close to minimize leakage flow, thus increasing confidence in using the inlet data as an input to CFD programs. The empirical study extensively examined the flow fields of the two impellers via performance of laser two-focus velocimeter surveys in an axial plane upstream of the impellers and in multiple radial planes downstream of the impellers. Both studies were performed at the impeller design flow coefficients. Inlet laser surveys that provide CFD code inlet boundary conditions were performed in one axial plane, with ten radial locations surveyed. Three wall static pressures, positioned circumferentially around the impeller inlet, were used to identify asymmetrical pressure distributions in the inlet survey plane. The impeller discharge flow characterization consisted of three radial planes for the SSME HPFTP impeller and two radial planes for the Pump Consortium optimized impeller. Housing wall static pressures were placed to correspond to the radial locations surveyed with the laser velocimeter. Between five and thirteen axial stations across the discharge channel width were examined in each radial plane during the extensive flow mapping. The largely successful empirical flow characterization of two different impellers resulted in a substantial contribution to the limited existing data base, and yielded accurate data for CFD code benchmarking.

Brozowski, L. A.↗
NASA NTRS2003

On the Scaling Laws for Jet Noise in Subsonic and Supersonic Flow

The scaling laws for the simulation of noise from subsonic and ideally expanded supersonic jets are examined with regard to their applicability to deduce full scale conditions from small-scale model testing. Important parameters of scale model testing for the simulation of jet noise are identified, and the methods of estimating full-scale noise levels from simulated scale model data are addressed. The limitations of cold-jet data in estimating high-temperature supersonic jet noise levels are discussed. It is shown that the jet Mach number (jet exit velocity/sound speed at jet exit) is a more general and convenient parameter for noise scaling purposes than the ratio of jet exit velocity to ambient speed of sound. A similarity spectrum is also proposed, which accounts for jet Mach number, angle to the jet axis, and jet density ratio. The proposed spectrum reduces nearly to the well-known similarity spectra proposed by Tam for the large-scale and the fine-scale turbulence noise in the appropriate limit.

Vu, Bruce↗
NASA NTRSDate not supplied

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗
NASA NTRSDate not supplied

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗