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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Estimation of peak winds from hourly observations

Two closely related methods to obtain estimates of the hourly peak wind at Cape Kennedy were compared by statistical tests. The methods evaluated the Monin-Obukhov stability length and the standard deviation of the hourly observed wind speed, so as to augment the latter quantity by F standard deviations. F is an optimized factor. A third method utilizing an optimized gust factor was also applied to the hourly wind. The latter procedure estimated 2952 peak winds with an rms error of 2.81 knots, an accuracy which was not surpassed by the other methods. Peak ground wind speed data were developed for use in space shuttle design operation analyses.

Graves, M. E.↗
DOE OSTI2025

Brillouin Sensing with PCA, and PCA-Based Neural Networks for Efficient Temperature Monitoring

This work explores peak estimation techniques in Brillouin Optical Time Domain Analysis (BOTDA), emphasizing both accuracy and efficiency. Euclidean distance measurement method is applied to principal components derived from Brillouin Gain Spectrum data. It offers a major speed advantage being 180 170 times faster than traditional curve fitting methods such as Lorentzian curve fitting, while maintaining similar accuracy. Additionally, a PCA- based neural network model shows significant reduction of peak estimation time compared to Lorentzian fitting. Results show Brillouin frequency shift errors lie under 0.75 MHz in both Euclidean distance-based and neural network-based methods, both of which utilize PCA components. For large data sets and long length fibers, PCA- assisted neural network for peak estimation would be an efficient solution.

Distributed optical fiber sensing↗
NASA NTRS1993

Two-dimensional velocity, optical risetime, and peak current estimates for natural positive lightning return strokes

Velocities, optical risetimes, and transmission line model peak currents for seven natural positive return strokes are reported. The average 2D positive return stroke velocity for channel segments of less than 500 m in length starting near the base of the channel is 0.8 +/- 0.3 x 10 exp 8 m/s, which is slower than the present corresponding average velocity for natural negative first return strokes of 1.7 +/- 0.7 x 10 exp 8/s. It is inferred that positive stroke peak currents in the literature, which assume the same velocity as negative strokes, are low by a factor of 2. The average 2D positive return stroke velocity for channel segments of greater than 500 m starting near the base of the channel is 0.9 +/- 0.4 x 10 exp 8 m/s. The corresponding average velocity for the present natural negative first strokes is 1.2 +/- 0.6 x 10 exp 8 m/s. No significant velocity change with height is found for positive return strokes.

Mach, Douglas M.↗
NASA NTRS1989

Photoelectric return-stroke velocity and peak current estimates in natural and triggered lightning

Two-dimensional photoelectric return stroke velocities from 130 strokes are presented, including 86 negative natural, 41 negative triggered, one positive triggered, and two positive natural return strokes. For strokes starting near the ground and exceeding 500 m in length, the average velocity is 1.3 + or - 0.3 X 10 to the 8th m/s for natural return strokes and 1.2 + or - 0.3 X 10 to the 8th m/s for triggered return strokes. For strokes with lengths less than 500 m, the average velocities are slightly higher. Using the transmission line model (TLM), the shortest segment one-dimensional return stroke velocity, and either the maximum or plateau electric field, it is shown that natural strokes have a peak current distribution that is lognormal with a median value of 16 kA (maximum E) or 12 kA (plateau E). Triggered lightning has a medium peak current value of 21 kA (maximum E) or 15 kA (plateau E). Correlations are found between TLM peak currents and velocities for triggered and natural subsequent return strokes, but not between TLM peak currents and natural first return stroke velocities.

Mach, Douglas M.↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗
NASA NTRS2016

Recurrence Rate and Magma Effusion Rate for the Latest Volcanism on Arsia Mons, Mars

Magmatism and volcanism have evolved the Martian lithosphere, surface, and climate throughout the history of Mars. Constraining the rates of magma generation and timing of volcanism on the surface clarifies the ways in which magma and volcanic activity have shaped these Martian systems. The ages of lava flows on other planets are often estimated using impact crater counts, assuming that the number and size-distribution of impact craters per unit area reflect the time the lava flow has been on the surface and exposed to potential impacts. Here we show that impact crater age model uncertainty is reduced by adding stratigraphic information observed at locations where neighboring lavas abut each other, and demonstrate the significance of this reduction in age uncertainty for understanding the history of a volcanic field comprising 29 vents in the 110-kilometer-diameter caldera of Arsia Mons, Mars. Each vent within this caldera produced lava flows several to tens of kilometers in length; these vents are likely among the youngest on Mars, since no impact craters in their lava flows are larger than 1 kilometer in diameter. First, we modeled the age of each vent with impact crater counts performed on their corresponding lava flows and found very large age uncertainties for the ages of individual vents, often spanning the estimated age for the entire volcanic field. The age model derived from impact crater counts alone is broad and unimodal, with estimated peak activity in the field around 130Ma (megaannum, 1 million years). Next we applied our volcano event age model (VEAM), which uses a directed graph of stratigraphic relationships and random sampling of the impact crater age determinations to create alternative age models. Monte Carlo simulation was used to create 10,000 possible vent age sets. The recurrence rate of volcanism is calculated for each possible age set, and these rates are combined to calculate the median recurrence rate of all simulations. Applying this approach to the 29 volcanic vents, volcanism likely began around 200-300Ma then first peaked around 150Ma, with an average production rate of 0.4 vents per Myr (million years). The recurrence rate estimated including stratigraphic data is distinctly bimodal, with a second, lower peak in activity around 100Ma. Volcanism then waned until the final vents were produced 10-90Ma. Based on this model, volume flux is also bimodal, reached a peak rate of 1-8 cubic kilometers per million years by 150Ma and remained above half this rate until about 90Ma, after which the volume flux diminished greatly. The onset of effusive volcanism from 200-150Ma might be due to a transition of volcanic style away from explosive volcanism that emplaced tephra on the western flank of Arsia Mons, while the waning of volcanism after the 150Ma peak might represent a larger-scale diminishing of volcanic activity at Arsia Mons related to the emplacement of flank apron lavas.

Richardson, Jacob A.↗
NASA NTRS2021

Center of Gravity Quasi-Static Load Estimate Using Random Vibration Responses

The quasi-static load (QSL) is often levied on flight hardware structural designers as a requirement. This requirement is verified either by test or analysis with engineers using different approaches to meet this requirement. A commonly used approach is to consider the rms acceleration Center of Gravity (CG) responses of test articles undergoing random vibration tests. The differences between structural engineers and/or test conductors within the space industry exist on how the data obtained from flight hardware random vibration tests are used to estimate QSLs. In this paper, a method to accurately estimate the CG grms from the acceleration power spectral densities with an appropriate sigma value to estimate peak CG accelerations is discussed. Recommendations are made to ensure that the community follows consistent QSL estimation from random vibration test data. The method of estimating the CG acceleration responses may also be used to response limit if the flight hardware responses exceed flight limit loads with margins.

Kolaini, Ali↗
NASA NTRS1991

Dust and molecular properties of the low-opacity cloud Lynds 1563

Optical, molecular, and far-infrared data are analyzed for L1563, estimated peak Ab 2.5 mag. The cloud is detected by IRAS at 12, 25, 60, and 100 microns, and with CO, (C-13)O, and H2CO molecules. A column density comparison yields an estimate of the temperature of the classical dust grains of 15.6 + or - 1 K, while the color temperature derived from the ratio I(60)/I(100) is 26 K. Both dust and color temperatures decrease toward the cloud center.

Clark, Frank O.↗
NASA NTRS2007

Comparison of the KSC-ER Cloud-to-Ground Lightning Surveillance System (CGLSS) and the U.S. National Lightning Detection Network(TradeMark)(NLDN)

The NASA Kennedy Space Center (KSC) and Air Force Eastern Range (ER) use data from two cloud-to-ground lightning detection networks, CGLSS and NLDN, during ground and launch operations at the KSC-ER. For these applications, it is very important to understand the location accuracy and detection efficiency of each network near the KSC-ER. If a cloud-to-ground (CG) lightning strike is missed or mis-located by even a small amount, the result could have significant safety implications, require expensive retests, or create unnecessary delays or scrubs in launches. Therefore, it is important to understand the performance of each lightning detection system in considerable detail. To evaluate recent upgrades in the CGLSS sensors in 2000 and the entire NLDN in 2002- 2003, we have compared. measurements provided by these independent networks in the summers of 2005 and 2006. Our analyses have focused on the fraction of first strokes reported individually and in-common by each network (flash detection efficiency), the spatial separation between the strike points reported by both networks (relative location accuracy), and the values of the estimated peak current, Ip, reported by each network. The results within 100 km of the KSC-ER show that the networks produce very similar values of Ip (except for a small scaling difference) and that the relative location accuracy is consistent with model estimates that give median values of 200-300m for the CGLSS and 600-700m for the NLDN in the region of the KSC-ER. Because of differences in the network geometries and sensor gains, the NLDN does not report 10-20% of the flashes that have a low Ip (2 kA < |Ip| < 16 kA), both networks report 99 % of the flashes that have intermediate values of Ip (16< |Ip| < 50 kA), and the CGLSS fails to report 20-30% of the high-current events (|Ip| >=0 kA).

Ward, Jennifer G.↗
NASA NTRS1988

Return stroke velocities and currents using a solid state silicon detector system

A small, portable device has been developed to measure return stroke velocities. With the device, velocities from 135 strokes that consist of 92 natural return strokes and 43 triggered return strokes have been analyzed. The average return stroke velocity for longer channels, greater than 500 meters, is 1.2 + or - 0.3 x 10 to the 8th m/s for both natural and triggered return strokes. For shorter channel lengths, less than 500 m, natural lightning has a statistically higher average return stroke velocity of 1.9 + or - 0.7 x 10 to the 8th m/s than triggered lightning with an average return stroke velocity of 1.4 + or - 0.4 x 10 to the 8th m/s. Using the transmission line model of the return stroke, natural lightning has a peak current distribution that is log-normal with a median value of 19 kA. Return stroke velocities and currents were determined for two distant single stroke natural positive cloud-to-ground flashes. The velocities were 1.0 and 1.7 x 10 to the 8th ms/s while the estimated peak current for each positive flash was over 125 kA.

Mach, Douglas M.↗
NASA NTRS1996

Intramuscular Pressure Measurement During Locomotion in Humans

To assess the usefulness of intramuscular pressure (IMP) measurement for studying muscle function during gait, IMP was recorded in the soleus and tibialis anterior muscles of ten volunteers during, treadmill walking, and running using transducer-tipped catheters. Soleus IMP exhibited single peaks during late-stance phase of walking (181 +/- 69 mmHg, mean +/- S.E.) and running (269 +/- 95 mmHg). Tibialis anterior IMP showed a biphasic response, with the largest peak (90 +/- 15 mmHg during walking and 151 +/- 25 mmHg during running) occurring shortly after heel strike. IMP magnitude increased with gait speed in both muscles. Linear regression of soleus IMP against ankle joint torque obtained by a dynamometer in two subjects produced linear relationships (r = 0.97). Application of these relationships to IMP data yielded estimated peak soleus moment contributions of 0.95-165 Nm/Kg during walking, and 1.43-2.70 Nm/Kg during running. IMP results from local muscle tissue deformations caused by muscle force development and thus, provides a direct, practical index of muscle function during locomotion in humans.

Ballard, Ricard E.↗
NASA NTRS1998

Leg intramuscular pressures during locomotion in humans

To assess the usefulness of intramuscular pressure (IMP) measurement for studying muscle function during gait, IMP was recorded in the soleus and tibialis anterior muscles of 10 volunteers during treadmill walking and running by using transducer-tipped catheters. Soleus IMP exhibited single peaks during late-stance phase of walking [181 +/- 69 (SE) mmHg] and running (269 +/- 95 mmHg). Tibialis anterior IMP showed a biphasic response, with the largest peak (90 +/- 15 mmHg during walking and 151 +/- 25 mmHg during running) occurring shortly after heel strike. IMP magnitude increased with gait speed in both muscles. Linear regression of soleus IMP against ankle joint torque obtained by a dynamometer produced linear relationships (n = 2, r = 0.97 for both). Application of these relationships to IMP data yielded estimated peak soleus moment contributions of 0.95-1.65 N . m/kg during walking, and 1.43-2.70 N . m/kg during running. Phasic elevations of IMP during exercise are probably generated by local muscle tissue deformations due to muscle force development. Thus profiles of IMP provide a direct, reproducible index of muscle function during locomotion in humans.

Clinical Trial↗
NASA NTRS2008

Classification of Small Negative Lightning Reports at the KSC-ER

The NASA Kennedy Space Center (KSC) and Air Force Eastern Range (ER) operate an extensive suite of lightning sensors because Florida experiences the highest area density of ground strikes in the United States, with area densities approaching 16 fl/sq km/yr when accumulated in 10x10 km (100 sq km) grids. The KSC-ER use data derived from two cloud-to-ground (CG) lightning detection networks, the "Cloud-to-Ground Lightning Surveillance System" (CGLSS) and the U.S. National Lightning Detection Network (TradeMark) (NLDN) plus a 3-dimensional lightning mapping system, the Lightning Detection and Ranging (LDAR) system, to provide warnings for ground operations and to insure mission safety during space launches. For operational applications at the KSC-ER it is important to understand the performance of each lightning detection system in considerable detail. In this work we examine a specific subset of the CGLSS stroke reports that have low values of the negative inferred peak current, Ip, i.e. values between 0 and -7 kA, and were thought to produce a new ground contact (NGC). When possible, the NLDN and LDAR systems were used to validate the CGLSS classification and to determine how many of these reported strokes were first strokes, subsequent strokes in a pre-existing channel (PEC), or cloud pulses that the CGLSS misclassified as CG strokes. It is scientifically important to determine the smallest current that can reach the ground either in the form of a first stroke or by way of a subsequent stroke that creates a new ground contact. In Biagi et al (2007), 52 low amplitude, negative return strokes ([Ip] < or = 10 kA) were evaluated in southern Arizona, northern Texas, and southern Oklahoma. The authors found that 50-87% of the small NLDN reports could be classified as CG (either first or subsequent strokes) on the basis of video and waveform recordings. Low amplitude return strokes are interesting because they are usually difficult to detect, and they are thought to bypass conventional lightning protection that relies on a sufficient attractive radius to prevent "shielding failure" (Golde, 1977). They also have larger location errors compared to the larger current events. In this study, we use the estimated peak current provided by the CGLSS and the results of our classification to determine the minimum Ip for each category of CG stroke and its probability of occurrence. Where possible, these results are compared to the findings in the literature.

Ward, Jennifer G.↗
DOE OSTI2024

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗
NASA NTRS1977

The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

Castruccio, P. A.↗
NASA NTRS1984

Federal photovoltaic utilization program status report

This paper is a partial status report of the Federal Photovoltaic Utilization Program. Selected photovoltaic systems, already installed or being installed by 24 federal agencies under the sponsorship of the Department of Energy, are described with both text and illustrations. More than 1,000 DOE-funded photovoltaic systems now are in operation providing an estimated peak power output of 410 kWp.

Lawson, A. C.↗
NASA NTRS1994

Case study of a low-reflectivity pulsating microburst: Numerical simulation of the Denver, 8 July 1989, storm

On 8 July 1989, a very strong microburst was detected by the Low-Level Windshear Alert system (LLWAS), within the approach corridor just north of Denver Stapleton Airport. The microburst was encountered by a Boeing 737-200 in a 'go-around' configuration which was reported to have lost considerable air speed and altitude during penetration. Data from LLWAS revealed a pulsating microburst with an estimated peak velocity change of 48 m/s. Wilson et al. reported that the microburst was accompanied by no apparent visible clues such as rain or virga, although blowing dust was present. Weather service hourly reports indicated virga in all quadrants near the time of the event. A National Center for Atmospheric Research (NCAR) research Doppler radar was operating; but according to Wilson et al., meaningful velocity could not be measured within the microburst due to low radar-reflectivity factor and poor siting for windshear detection at Stapleton. This paper presents results from the three-dimensional numerical simulation of this event, using the Terminal Area Simulation System (TASS) model. The TASS model is a three-dimensional nonhydrostatic cloud model that includes parameterizations for both liquid and ice phase microphysics, and has been used in investigations of both wet and dry microburst case studies. The focus of this paper is the pulsating characteristic and the very-low radar reflectivity of this event. Most of the surface outflow contained no precipitation. Such an event may be difficult to detect by radar.

Proctor, Fred H.↗