Search NASA⌕ Search

SEARCH · Search NASA

Results for “Height”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights

This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six tropical sites operated by the Atmospheric Radiation Measurement (ARM) user facility. LiNGAM effectively identifies causal directions among variables of interest, revealing robust relationships such as those among the lifting condensation level (LCL), level of free convection (LFC), and convective inhibition (CIN), aligning with prior knowledge. Relative humidity is shown to directly influence LMD; however, this relationship exhibits strong nonlinearity and becomes difficult to detect when the contrast between oceanic and continental environments is excluded from the analysis. This study highlights the importance of establishing causal relationships before performing statistical inference.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Effects of height acceleration on Geosat heights

A radar altimeter tracking loop, such as that utilized by Geosat, produces height errors in the presence of persistent height acceleration h(a). The correction factor for the height error is a function of both the loop feedback parameters and the height acceleration. The correction, in meters, to the sea-surface height (SSH) derived from Geosat is -0.16 h(a), where h(a) is in m/sec per sec. The errors induced by accelerations are produced primarily by changes in along-track geoid slopes. The nearly circular Geosat orbit and dynamic ocean topography produce small h(a) values. One area studied in detail encompasses the Marianas Trench and the Challenger Deep in the west central Pacific Ocean. Histograms of SSH corrections due to range accelerations have also been determined from 24-hour segments of Geosat global data. The findings are that 20 percent of the Geosat measurements have acceleration-induced errors of 2 cm or more, while 8 percent have errors of 3 cm or more.

Hancock, David W., III↗
NASA NTRS2011

MISR Interactive Explorer (MINX) : Production Digitizing to Retrieve Smoke Plume Heights and Validating Heights Against Lidar Data

The height at which smoke from a wildfire is injected into the atmosphere is an important parameter for climatology, because it determines how far the smoke can be transported. Using the MINX program to analyze MISR (Multi-angle Imaging Spectro-Radiometer) data, I digitized wildfire smoke plumes to add to an existing database of these heights for use by scientists studying smoke transport and plume dynamics. In addition to using MINX to do production digitizing of heights, I assisted in gathering lidar data for an ongoing validation of MINX and helped evaluate those data.

smoke plume↗
NASA NTRSDate not supplied

Assimilation of PBL Height Data from Multiple Observing Systems in the GEOS System for Global PBL Height Analysis and Monitoring System

The Goddard Earth Observing System (GEOS) developed by the NASA Global Modeling and Assimilation Office provides the critical capability to assimilate a wide range of observations in producing a comprehensive PBL estimate consistent with model physics and observations. To generate global Planetary Boundary Layer height (PBLH) analysis and monitor PBLH data online, we have developed strategy and infrastructure for PBLH data assimilation in the GEOS system and ingested PBLH data derived from multiple observing systems including radiosonde, space- and ground-based LiDAR, and GNSS RO, and implemented corresponding thinning and quality control procedures. The evaluation of departures of model PBLH simulations from PBLH data for the period of 9 days in Aug 2015 will be presented, and different features of space-based backscattered-based PBLHs will be discussed.

Eun-Gyeong Yang↗
NASA NTRSDate not supplied

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗
NASA NTRS2018

Multibaseline TanDEM-X Mangrove Height Estimation: The Selection of the Vertical Wavenumber

We generated a large-scale mangrove forest height map using multiple TanDEM-X (TDX) interferometric synthetic aperture radar (InSAR) acquisitions with various spatial baselines in order to improve the height estimation accuracy across a wide range of forest heights. The forest height inversion using InSAR data is strongly dependent upon the vertical wavenumber (i.e., perpendicular baseline). First, we investigated the role of the vertical wavenumber in forest height inversion from InSAR data using the sensitivity of the interferometric (volume) coherence to forest height. We used corrected but lower resolution and accuracy Shuttle Radar Topography Mission (SRTM) mangrove height maps as a priori information over Akanda and Pongara National Parks in Gabon to estimate lower and upper boundaries of the vertical wavenumber over test sites from the measured coherence-to-height sensitivity. Only TDX acquisitions within the boundaries of the vertical wavenumber were selected and combined for multibaseline mangrove height inversion. Mangrove forest height was obtained with multibaseline TDX acquisitions and was validated against the reference height derived from field measurement data providing improvements in multibaseline inversion over existing height estimates (i.e., SRTM height) and single-baseline inversions (multibaseline inversion: r(exp 2) = 0.98, root mean square error (RMSE) of 2.73 m; SRTM height: r(exp 2) = 0.86, RMSE = 7.21 m; single-baseline inversions: r(exp 2) = 0.08-0.97, RMSE = 3.86-11.10 m). As a result, to accurately estimate forest heights over a wide range (3-60 m), multibaseline InSAR acquisitions (at least three different baselines) are needed to exclude biases associated with the vertical wavenumber in forest height inversion.

vertical wavenumber.↗
NASA NTRS2011

The Effects of Microgravity on Seated Height (Spinal Elongation)

ABSTRACT Many physiological factors, such as spinal elongation, fluid shifts, bone atrophy, and muscle loss, occur during an exposure to a microgravity environment. Spinal elongation is just one of the factors that can also affect the safety and performance of a crewmember while in space. Spinal elongation occurs due to the lack of gravity/compression on the spinal column. This allows for the straightening of the natural spinal curve. There is a possible fluid shift in the inter-vertebral disks that may also result in changes in height. This study aims at collecting the overall change in seated height for crewmembers exposed to a microgravity environment. During previous Programs, Apollo-Soyuz Test Project (ASTP) and Skylab, spinal elongation data was collected from a small number of subjects in a standing posture but were limited in scope. Data from these studies indicated a quick increase in stature during the first few days of weightlessness, after which stature growth reached a plateau resulting in up to a 3% increase of the original measurement [1-5]. However, this data was collected only for crewmembers in standing posture and not in a seated posture. Seated height may have a different effect than standing height due to a change in posture as well as due to a compounded effect of wearing restraints and a potential compression of the gluteal area. Seated height was deemed as a critical measurement in the design of the Constellation Program s (CxP) Crew Exploration Vehicle (CEV), called Orion which is now the point-of-departure vehicle for the Multi-Purpose Crew Vehicle (MPCV) Program; therefore a better understanding of the effects of microgravity on seated height is necessary. Potential changes in seated height that may not have impacted crew accommodation in previous Programs will have significant effects on crew accommodation due to the layout of seats in the Orion.. The current and existing configuration is such that the four crewmembers are stacked two by two with the commander and pilot seats on the top and the two remaining seats underneath, thereby limiting the amount of clearance for the crewmembers seated in the bottom seat. The inner mold line of these types of vehicles are fixed due to other design constraints; therefore, it is essential that all seats incorporate additional clearance to account for adequate spinal growth thereby ensuring that the crew can safely ingress the seat and be strapped in prior to its return to earth. If there is not enough clearance to account for spinal growth deltas between seats then there is the potential that crewmembers will not be able to comfortably and safely fit into their seats. The crewmember in the bottom stacked seat may even have negative clearance with the seat above him or her which could lead to potential ingress/egress issues or potentially injury of the crewmember during landing. These impacts are specific to these types of vehicles with stacked seat configuration. Without proper knowledge of the amount of spinal elongation, or growth, which occurs due to microgravity and space flight, the design of future vehicle(s) or suits may cause injury, discomfort, and limit crew accommodation and crew complements. The experiment primarily aimed to collect seated height data for subjects exposed to microgravity environments, and feed new information regarding the effect of elongation of the spine forward into the design of the Orion. The data collected during the experiment included, two seated height measurement and two digital pictures of seated height pre-, in-, and post-flight. In addition to seated height, crewmembers had an optional task of collecting stature , standing height. Seated height data was obtained from 29 crewmembers that included 8 ISS increment crew (2 females and 6 males) and 21 Shuttle crew (1 female, 20 males), and whose mean age was 48 years ( 4 years). This study utilized the last six Shuttle flights, STS-128 to STS-134. The results show that partipating crewmembers experienced growth up to 6% in seated height and up to 3% in stature. Based on the worst case statistical analysis of the subject data, the recommended seated height growth of 6% will be provided to the designers as the necessary seated height adjustment.

Young, K. S.↗
NASA NTRS2025

Effect of Strict Head Down Tilt Bedrest on Pituitary Gland Height

BACKGROUND Pituitary gland deformity and loss of pituitary height have been identified in astronauts postflight, hypothesized to be related to increased intracranial pressure or intracranial pressure pulsatility exposure from prolonged weightlessness. Microgravity-induced chronic headward fluid shift has been suggested as a root cause of intracranial compliance changes leading to altered intracranial pressure dynamics. Elevated intracranial pressure or pressure pulsatility is theorized to promote the development of an arachnoid diverticulum, which herniates into the pituitary fossa via a defect in the diaphragma sellae compressing the pituitary gland. We aimed to determine if chronic headward fluid induced by strict head-down tilt bed rest (HDTBR) can cause similar quantitative changes in pituitary gland height. METHODS Control group data from two 6-degree HDTBR studies were analyzed (SANS CM and AGBRESA). The AGBRESA study collected MRI data at Baseline, 14 days into HDTBR (HDTBR-14), 52 days into HDTBR (HDTBR-52), and three days into Recovery (R+ 3) and included eight healthy adults (2 women), age = 33 ± 8 years. The SANS CM collected MRI data at Baseline, 15 days into HDTBR (HDTBR-15), 29 days into HDTBR (HDTBR-29), and 12 days into Recovery (R+12) and included twelve healthy adults (4 women), age = 34 ± 9 years. Pituitary gland height was evaluated using a sagittal, 3D T1-MPRAGE sequence obtained on a dedicated 3T Siemens Biograph MRI scanner using a 32-channel head coil. Following the reconstruction of a true orthogonal sagittal plane of the pituitary gland using a 3D multiplanar reconstruction tool (Horosproject.org), the anterior pituitary mid-gland height at the pituitary stalk level was quantified according to the methodology described by Kramer et al. . A paired t-test was used to evaluate changes from the baseline measurements. FINDINGS The mean height of the pituitary gland at baseline was 6.5 ± 1.7 mm (AGBRESA) and 5.7 ± 1.6 mm (SANS CM). From baseline measurements, the SANS CM STUDY data showed a decrease in mean pituitary height of 0.3 mm (p=.011) at HDTBR-15, 0.5 mm at HDTBR-29 (p<.001) and 0.2 mm at R+12 (p=.02). From baseline measurements, the AGBRESA data showed a decrease in mean pituitary height of 0.3 mm (p=.06) at HDTBR-14, 0.6 mm at HDTBR-52 (p<.002) and 0.2 mm at R+3 (p=.13). CONCLUSION HDTBR results in progressive loss of pituitary height, which is most severe with the longest HDTBR exposure. Early pituitary height loss was the same at HDTBR-14 (AGBRESA) and HDTBR-15 (SANS CM). Residual pituitary height loss was the same at R+12 and R+3 but only significant in the latter (SANS CM). The degree of pituitary height loss at HDTBR-52 replicates the 0.6 mm height loss found in long-duration astronauts after approximately six months of microgravity exposure (p<.01, preflight mean height=5.9 mm). The hormonal effects of pituitary height loss are unknown in astronauts and HDTBR subjects and should be investigated in future studies. Future work will examine the individual variability in the loss of pituitary gland height and whether those changes are associated with other SANS findings, such as optic disc edema.

L A Kramer↗
DOE OSTI2025

Five Year Comparison of Mixing Height Determinations at the Savannah River Site

Air quality dispersion modeling is performed for the Savannah River Site (SRS) to demonstrate compliance with applicable regulations. The AMS/EPA Regulatory Model (AERMOD) modeling system is an EPA recommended model for air quality applications with a data preprocessor (AERMET) to incorporate meteorological data collected on site. AERMET parameterizes or calculates meteorological variables that are not directly measured onsite. One of the parameters estimated by AERMET is the atmospheric mixing height. While the mixing height is not currently a measurement input into AERMET, SRS has the capability to measure the local mixing height. The Savannah River National Laboratory (SRNL) operates a Vaisala CL31 Lidar Ceilometer which estimates mixing height from aerosol backscatter. This study compares the parameterized mixing height from AERMET to the ceilometer estimated mixing height for the current regulatory period at SRS incorporating data from 2015-2019. Results from this study showed the average daily minimum values (morning) from AERMET were an order of magnitude lower than the commonly used Holzworth (1972) method and the ceilometer estimated mixing heights. Additionally, on average, the ceilometer exhibited a daily maximum mixing height value that occurred 1-3 hours later than the AERMET estimated maximum. This difference is likely due to the nighttime atmospheric mixing height assumptions and calculations used by AERMET. The AERMET algorithm cuts off mixing height growth at sunset while the ceilometer data show ongoing evening convection typical of the southeastern United States. These results suggest that the AERMET parametrization scheme assumptions may not be representative of a forested landscape and evening convection which could account for more mixing overnight. The results obtained in this study are significant for air dispersion modeling applications for regulatory purposes and worker safety. Mixing height can impact model estimated pollutant concentrations. A greater mixing height will provide more volume for pollutant dispersion. This report documents efforts to quantify the dependence of mixing height inputs toward a conservative estimated pollutant concentration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
NASA NTRS2011

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗
NASA NTRS1986

Vertical distribution of ozone and the variation of tropopause heights based on ozonesonde and satellite observations

The distribution of atmospheric ozone is nonuniform both in space and time. Local ozone concentration vary with altitude, latitude, longitude, and season. Two year ozonesonde data, January 1981 to December 1982, observed at four Canadian stations and 2.5 year backscattered ultraviolet experiment data on the Nimbus-4 satellite, April 1970 to August 1972, observed over five American stations were used to study the relationship between the total ozone, vertical height distribution of the ozone mixing ratio, vertical height distribution of half total ozone, and the local tropopause height. The results show that there is a postive correlation between total ozone in Dobson Units and the tropopause height in terms of atmospheric pressure. This result suggests that local intrusion of the statosphere into the troposphere, or the local decreasing of tropopause height could occur if there is a local increasing of total ozone. A comparison of the vertical height distribution of the ozone mixing ratio, the modified pressure height of half total ozone and the tropopause height shows that the pressure height of an ozone mixing ratio of 0.3 micrograms/g, and the modified pressure height of half total ozone are very well correlated with the tropopause pressure height.

Hung, R. J.↗
NASA NTRS2008

Vertical Jump Height is more Strongly Associated with Velocity and Work Performed Prior to Take-off

Vertical jump (VJ) height is commonly used as a measure of athletic capability in strength and power sports. Although VJ has been shown to be a predictor of athletic performance, it is not clear which kinetic ground reaction force (GRF) variables, such as peak force (PF), peak power (PP), peak velocity (PV), total work (TW) or impulse (Imp) are the best correlates. To determine which kinetic variables (PF, PP, PV, TW, and Imp) best correlate with VJ height. Twenty subjects (14 males, 6 females) performed three maximal countermovement VJs on a force platform (Advanced Mechanical Technology, Inc., Watertown, MA, USA). VJ jump height was calculated as the difference between standing reach and the highest reach point measured using a Vertec. PF, PP, PV, TW, and Imp were calculated using the vertical GRF data sampled at 1000 Hz from the lowest point in the countermovement through the concentric portion until take-off. GRF data were normalized to body mass measured using a standard scale (Detecto, Webb City, MO, USA). Correlation coefficients were computed between each GRF variable and VJ height using a Pearson correlation. VJ height (43.4 plus or minus 9.1 cm) was significantly correlated (p less than 0.001) with PF (998 plus or minus 321 N; r=0.51), PP (1997 plus or minus 772 W; r=0.69), PV (2.66 plus or minus 0.40 m (raised dot) s(sup -1); r=0.85), TW (259 plus or minus 93.0 kJ; r=0.82), and Imp (204 plus or minus 51.1 N(raised dot)s; r=0.67). Although all variables were correlated to VJ height, PV and TW were more strongly correlated to VJ height than PF, PP, and Imp. Therefore, since TW is equal to force times displacement, the relative displacement of the center of mass along with the forces applied during the upward movement of the jump are critical determinants of VJ height. PV and TW are key determinants of VJ height, and therefore successful training programs to increase VJ height should focus on rapid movement (PV) and TW by increasing power over time rather than focusing on PF alone.

Bentley, J. R.↗
NASA NTRS2011

The RHESSI Microflare Height Distribution

We present the first in-depth statistical survey of flare source heights observed by RHESSI. Flares were found using a flare-finding algorithm designed to search the 6-10 keV count-rate when RHESSI's full sensitivity was available in order to find the smallest events (Christe et al., 2008). Between March 2002 and March 2007, a total of 25,006 events were found. Source locations were determined in the 4-10 keV, 10-15 keV, and 15-30 keV energy ranges for each event. In order to extract the height distribution from the observed projected source positions, a forward-fit model was developed with an assumed source height distribution where height is measured from the photosphere. We find that the best flare height distribution is given by g (h) oc exp(-h/lambda) where lambda = 6.1 plus or minus 0.3 Mm is the scale height. A power law height distribution with a negative power law index, gamma = 3.1 plus or minus 0.3 is also consistent with the data. Interpreted as thermal loop top sources, these heights are compared to loops generated by a potential field model (PFSS). The measured flare heights distribution are found to be much steeper than the potential field loop height distribution which may be a signature of the flare energization process.

Christe, P.↗
NASA NTRS2015

The Effect of Backward-Facing Step Height on Instability Growth and Breakdown in Swept Wing Boundary-Layer Transition

A low-speed experiment was performed on a swept at plate model with an imposed pressure gradient to determine the effect of a backward-facing step on transition in a stationary-cross flow dominated flow. Detailed hot-wire boundary-layer measurements were performed for three backward-facing step heights of approximately 36, 45, and 49% of the boundary-layer thickness at the step. These step heights correspond to a subcritical, nearly-critical, and critical case. Three leading-edge roughness configurations were tested to determine the effect of stationary-cross flow amplitude on transition. The step caused a local increase in amplitude of the stationary cross flow for the two larger step height cases, but farther downstream the amplitude decreased and remained below the baseline amplitude. The smallest step caused a slight local decrease in amplitude of the primary stationary cross flow mode, but the amplitude collapsed back to the baseline case far downstream of the step. The effect of the step on the amplitude of the primary cross flow mode increased with step height, however, the stationary cross flow amplitudes remained low and thus, stationary cross flow was not solely responsible for transition. Unsteady disturbances were present downstream of the step for all three step heights, and the amplitudes increased with increasing step height. The only exception is that the lower frequency (traveling crossflow-like) disturbance was not present in the lowest step height case. Positive and negative spikes in instantaneous velocity began to occur for the two larger step height cases and then grew in number and amplitude downstream of reattachment, eventually leading to transition. The number and amplitude of spikes varied depending on the step height and cross flow amplitude. Despite the low amplitude of the disturbances in the intermediate step height case, breakdown began to occur intermittently and the flow underwent a long transition region.

Eppink, Jenna L.↗