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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
NASA NTRS1933

Drop and Flight Tests on NY-2 Landing Gears Including Measurements of Vertical Velocities at Landing

This investigation was conducted to obtain quantitative information on the effectiveness of three landing gears for the NY-2 (consolidated training) airplane. The investigation consisted of static, drop, and flight tests on landing gears of the oleo-rubber-disk and the mercury rubber-chord types, and flight tests only on a landing gear of the conventional split-axle rubber-cord type. The results show that the oleo gear is the most effective of the three landing gears in minimizing impact forces and in dissipating the energy taken.

Peck, W D↗
NASA NTRS1979

Height dependence of spread F bubble drift velocities

Vertical bubble velocities in equatorial spread F have been investigated analytically by Ott (1978), Osakow and Chaturvedi (1978), all of whom found a proportionality of the vertical velocity to bubble depletion density. The paper presents radar data from two equatorial sites which support theoretical predictions that vertical drift velocities of spread F bubbles increase with height on the bottomside of the F layer. This increase is shown to result from the proportionality of bubble drift velocity to density depletion amplitude, which itself increases with height. The measured rate of increase is found to be dU/dh equals about 2 m/s km. It is concluded that this is consistent with numerical simulation results within a factor of 2.

Hudson, M. K.↗
DOE OSTI2025

Ensemble‐Based, Large‐Eddy Reconstruction of Wind Turbine Inflow in a Near‐Stationary Atmospheric Boundary Layer Through Generative Artificial Intelligence

ABSTRACT To validate the second‐by‐second dynamics of turbines in field experiments, it is necessary to accurately reconstruct the winds going into the turbine. Current time‐resolved inflow reconstruction techniques estimate wind behavior in unobserved regions using relatively simple spectral‐based models of the atmosphere. Here, we develop a technique for time‐resolved inflow reconstruction that is rooted in a large‐eddy simulation model of the atmosphere. Our “large‐eddy reconstruction” technique blends observations and atmospheric model information through a diffusion model machine learning algorithm, allowing us to generate probabilistic ensembles of reconstructions for a single 10‐min observational period. Our generated inflows can be used directly by aeroelastic codes or as inflow boundary conditions in a large‐eddy simulation. We verify the second‐by‐second reconstruction capability of our technique in three synthetic field campaigns, finding positive Pearson correlation coefficient values () between ground‐truth and reconstructed streamwise velocity, as well as smaller positive correlation coefficient values for unobserved fields (spanwise velocity, vertical velocity, and temperature). We validate our technique in three real‐world case studies by driving large‐eddy simulations with reconstructed inflows and comparing to independent inflow measurements. The reconstructions are visually similar to measurements, follow desired power spectra properties, and track second‐by‐second behavior ().

17 WIND ENERGY↗
NASA NTRS1986

Use of the Sun to determine pointing of ST radar beams

Verification of the beam pointing direction for ST (stratosphere troposphere) radars is a technically difficult problem. Consequently it is not usually done. For measurement of horizontal wind, the lack of precise knowledge of the beam pointing direction is usually of little consequence as any errors cause only a small uncertainty in the measured velocity. However, instantaneous vertical velocities are typically more than an order of magnitude less than horizontal velocities and average vertical velocities are more than two orders of magnitude less than average horizontal velocities. Hence small pointing errors for vertical beams can result in large errors due to contamination by horizontal winds. Experimental confirmation of pointing accuracy using the measured winds is difficult but has been achieved where horizontal and vertical winds are measured at the same site. Using the techniques described by Balsley and Riddle, 1984 and Riddle and Balsley, 1985, pointing accuracy was measured at Ponape, Federated States of Micronesia. The experiment is described in detail.

Riddle, A. C.↗
NASA NTRS1984

Frequency and site selection criteria for MST radars, part 5.1A

The majority of mesosphere-stratosphere-troposphere (MST) and ST radars are located in or near mountainous terrain. When measuring horizontal velocities, the terrain is a small factor, but when measuring vertical velocities, the meteorological noise induced by rough terrain can severely limit the usefulness of the observations. When the variance of the vertical velocity is too large, it is not possible to suitably filter the data to detect the small synoptic-scale signal with reasonable statistical confidence. The variance of vertical velocity at all tropospheric levels is directly related to the low level wind speed during flow over rough terrain. It is suggested that the synoptic-scale vertical velocity can be measured by ST radars where the terrain is smooth. The large-scale vertical velocity cannot always be reliably determined from MST radar data when the underlying terrain is rough. The vertical velocity is potentially on of future radar site selections, taking into account the desired meteorological applications of the data and engineering design factors. If the synoptic-scale vertical velocity is a desired variable, the radar should not be located near mountains.

Nastrom, G. D.↗
DOE OSTI2023

TRACER CLAMPS1 Doppler Lidar Vertical Stare Data

These files contain 24 hour periods of data collected from the CLAMPS1 Halo Streamline Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER CLAMPS2 Doppler Lidar Vertical Stare Data

These files contain 24 hour periods of data collected from the CLAMPS2 Halo Streamline XR+ Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Vertical wind velocities from superpressure balloons - A case study using Eole data

A method for determining vertical wind velocities using the pressure- and temperature-change data from superpressure (constant-density) balloons was proposed in an earlier paper (1975). In this paper, we present a case study using actual balloon data to test the method. Data from the Eole balloon experiment were used to estimate the sign of vertical wind velocities, as well as the horizontal velocity field, near 200 mb over Australia. The resulting patterns of vertical velocity compare favorably with satellite pictures and with current models of flow near jet-stream maxima. Additionally, this study provides evidence that areas of vertical motion in the troposphere extend upward into the lower stratosphere without changing sign.

Banta, R. M.↗
NASA NTRS2001

Toward a Unified Parameterization of the Boundary Layer and Moist Convection: A New Type of Mass-Flux Model - Part 1

Higher-order closure (HOC) models have been proposed for parameterization of the turbulent planetary boundary layer (PBL). HOC models must include closures for higher-order moments (e.g., fourth moments in third-order closure models), for pressure terms, and for dissipation terms. Mass-flux closure (MFC) models have been proposed for parameterization of cumulus convection and, more recently, the convective PBL. MFC models include closures for lateral mass exchanges and for pressure terms (which are usually ignored). The authors developed a new kind of model that combines HOC and MFC, which they hope will be useful for the parameterization of both the PBL and cumulus convection, in a unified framework. Such a model is particularly well suited to regimes in which the PBL turbulence and the cumulus convection are not well separated, for example, the broken stratocumulus and shallow cumulus regimes. The model makes use of an assumed joint probability distribution for the variables of interest, and the equations typically used in HOC models can be derived by integrating over the distribution. Accordingly, the model is called Assumed-Distribution Higher-Order Closure (ADHOC). The prognostic variables of ADHOC are the mean state, the second and third moments of the vertical velocity, and the vertical fluxes of other quantities of interest. All of the parameters of the distribution can be determined from the predicted moments, thereafter the joint distribution is effectively known, and so any and all moments can be constructed as needed. In this way, the usual closure problem of "higher moments" is avoided. The pressure-term parameterizations previously developed for HOC models are used to predict the convective fluxes and the moments of the vertical velocity. In companion papers, parameterizations of lateral mass exchanges and subplume-scale fluxes are presented, and then ADHOC is applied to several observationally based tropical, subtropical, and dry convective boundary layers.

Lappen, Cara-Lyn↗
NASA NTRS1976

Equations and approximations involved in computing vertical wind velocities from superpressure balloon data

Superpressure, or constant-level, balloons have long been used to obtain horizontal wind velocities in the atmosphere. This paper presents equations which can be used to evaluate omega, the vertical wind component in pressure coordinates, from on-board pressure and temperature sensors. These equations take into account the short-term displacements of a balloon from its equilibrium density level, and thus they do not assume that the balloon precisely maintains constant density. The longer-term and larger-amplitude diurnal oscillations in balloon level, and also an approximation used in deriving the vertical velocity equations, are both discussed in some detail. These equations can be used to obtain quantitative estimates of omega if reasonable estimates of the ambient lapse rate could be obtained.

Banta, R. M.↗
DOE OSTI2021

Factors Affecting Entrainment Rate in Deep Convective Clouds and Parameterizations

The parameterization of cloud entrainment rates has been problematic for many years, hindering the accurate representation of convective processes in large-scale models. Here, we extend our previous work on individual shallow convection to ensemble deep convection. Entrainment rates are estimated based on three-dimensional convective clouds from August 19-20 of 1999, during the Kwajalein Experiment, simulated using a high-resolution cloud-resolving model. They are found to be negatively correlated with both vertical velocity and buoyancy, and positively correlated with the vertical divergence of the vertical velocity and with the reciprocal of cloud radii. The physical mechanisms underlying these relationships are interpreted. It is found that the parameterizations with multiple properties perform better than those with a single property. Entrainment rates and relative humidity of entrained air are positively correlated at temperature higher than 0°C, but negatively correlated at temperature lower than 0°C. Relative humidity is also included in the parameterization of entrainment rates, which differs from our previous work on shallow cumulus clouds and other studies. Finally, two forms of parameterization for entrainment rate are recommended. The first treats the entrainment rate as a function of the vertical velocity and buoyancy for temperature higher than 0°C, but as a function of relative humidity and buoyancy for temperature lower than 0°C. The second involves an equation that relates entrainment rates to vertical velocity and buoyancy regardless of temperature.

54 ENVIRONMENTAL SCIENCES↗