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At least 253 records · Page 14

Measurement Capabilities of Planar Doppler Velocimetry in Large-Scale Wind Tunnels

Over the past few years, Planar Doppler Velocimetry (PDT) has been shown by several laboratories to offer an attractive means for measuring three-dimensional velocity vectors everywhere in a light sheet placed in a flow. Unlike some other optical means of measuring flow velocities, PDT is particularly attractive for use in large wind tunnels where distances to the sample region may be several meters, because it does not require the spatial resolution and tracking of individual scattering particles or the alignment of crossed beams at large distances. To date, demonstrations of PDT (also called Doppler Global Velocimetry by some authors) have been made either in low speed flows without quantitative comparison to other measurements, or in supersonic flows where the Doppler shift is large and its measurement is relatively insensitive to instrumental errors. Moreover, most reported applications have relied on the use of continuous-wave lasers, which limit the measurement to time-averaged velocity fields. This work summarizes the results of two previous studies of PDT in which the use of pulsed lasers to obtain instantaneous velocity vector fields is evaluated. The objective has been to quantitatively define and demonstrate PDT capabilities for applications in large-scale wind tunnels that are intended primarily for the testing of rotorcraft and subsonic aircraft at speeds typically less than 100 m/s. For such applications, the adequate resolution of low-speed flow fields requires accurate measurements of small Doppler shifts that are obtained at distances of several meters from the sample region and with a field of view that is sufficient to encompass the entire region of interest. The use of pulsed lasers provides the unique capability to obtain not only time-averaged fields, but also their statistical fluctuation amplitudes and the spatial excursions of unsteady flow regions such as wakes, separations, and rotor-tip vortices. To accomplish the objectives of these studies, the PDT measurement process was first modeled and its performance evaluated computationally. The noise sources considered included those related to the optical and electronic properties of Charge-Coupled Device (CCD) arrays and to speckle effects associated with the coherent illumination of aerosols from pulsed lasers. The signal noise estimates were incorporated into the PDT signal analysis process and combined with computed scattering signals using a Mae scattering theory for a distributed range of aerosol particle sizes. The results are used to define the necessary instrument configuration, to show that the expected signal levels from a practical PDT system are sufficiently large to allow its useful application in large facilities, and to show that the expected velocity measurement uncertainties are small compared to the mean velocities of interest for most subsonic, large-scale wind tunnel testing, Experimental studies using several bench-top setups are then described that validate the physics of the PDT model and demonstrate the ability to obtain accurate PDT measurements using procedures that are compatible with large-scale wind tunnel operations. The PDT measurement capabilities found in this study lead to the conclusion that PDT offers significant advantages compared to other means of measuring velocity fields in large-scale wind tunnels, including those operating at low speeds.

McKenzie, Robert L.↗

How “hot” are hotspots: Statistically localizing the high-activity areas on soil and rhizosphere images

The topic of microbial hotspots in soil requires not only visualizing their spatial distribution and biochemical analyses, but also statistical approaches to identify these hotspots and separate them from the surrounding activities (background). We hypothesized that each hotspot type (e.g. enzyme activities in the rhizosphere, root exudation, localization of herbicide accumulation) is a result of local process driven by biotic and/or abiotic factors, and the process rates in the hotspots are much faster than those in the soil background. We further hypothesized that the background and hotspot activities in soil belong to different statistical distributions. Consequently, hotspot determination should be based on statistical separation of activities significantly higher than the background. We analyzed for the statistical distributions of grey values on three groups of published images: 1) 14 C images of carbon input by roots into the rhizosphere, 2) 14 C glyphosate accumulation in the plant, and 3) zymogram of leucine aminopeptidase activity in rooted soil. The two Gaussian distributions were fit (the first representing the background, the second the hotspots) to the distribution of grey values in the images, the parameters (means and standard deviations, SD) of the fitted distributions were calculated, and the background was removed. Thus, we identified hotspots as areas outside of the Mean+2SD image intensity (corresponding to the upper ~ 2.5% of activity, being over 97.5% of background values) and finally, visualized images of solely hotspot locations. Finally, these results were compared with previously used decisions on hotspot intensity thresholding (i.e. Top-25% and 17 standard thresholding approaches in ImageJ) and discussed the advantages of the Mean+2SD as well as Mean+3SD approaches. These advantages include: i) simple unification of the thresholding approach for several imaging methods with various principles of activity distribution, ii) identification of hotspots with various activity levels, iii) analysis of “time-specific” hotspots in temporal sequences of images. Compared with 17 standard thresholding methods, we concluded that objectively elucidating and separating the hotspots should be based on statistical distribution analysis, e.g. using the Mean+2SD or Mean+3SD approaches. Furthermore, this simple Mean+2SD approach delivered suitable results for three groups of images and so, helps to understand the processes responsible for the highest activities and elucidate hotspots.

59 BASIC BIOLOGICAL SCIENCES↗

Statistics and dynamics of persistent anomalies

Persistent anomalies with recurrent spatial patterns play an important role in the atmosphere's low-frequency variability. A connection between statistical and dynamical methods of description and prediction of persistent anomalies is established by computing and analyzing the empirical orthogonal functions (EOFs) in a simple deterministic model, on the one hand, and in Southern Hemisphere geopotential heights, on the other. The dynamical model is governed by the fully nonlinear, equivalent-barotropic vorticity equation on the sphere, with simplified forcing, dissipation and topography. The Southern Hemisphere data consist in gridded daily maps of 500 mb heights from June 1972 to July 1983. Two types of persistent anomalies appear in this time series, both having a strong wavenumber-three component; they differ by the value of the constant phase of this wave and by the strength of the wavenumber-one component. The first two EOFs bear a striking resemblance to these two patterns. It is concluded that the dynamical interpretation of EOFs is their pointing from the time mean to the most populated regions of the system's phase space. Pursuing this interpretation, a Markov-chain formulation of transitions from one persistent anomaly regime to another is introduced, and the implications for long-range forecasting are discussed.

Mo, Kingtse C.↗

Exploiting stochastic locality in lattice QCD: hadronic observables and their uncertainties

Abstract Because of the mass gap, lattice QCD simulations exhibit stochastic locality: distant regions of the lattice fluctuate independently. There is a long history of exploiting this to increase statistics by obtaining multiple spatially-separated samples from each gauge field; in the extreme case, we arrive at the master-field approach in which a single gauge field is used. Here we develop techniques for studying hadronic observables using position-space correlators, which are more localized, and compare with the standard time-momentum representation. We also adapt methods for estimating the variance of an observable from autocorrelated Monte Carlo samples to the case of correlated spatially-separated samples.

Physics↗

A practical guide to characterizing irradiated nuclear fuels using FIB tomography

We report focused ion beam (FIB) tomography with combined electron backscatter diffraction (EBSD) and energy dispersive x-ray spectroscopy (EDS) is a technique capable of statistically characterizing the microstructure and spatial compositional variation of nuclear fuel in three-dimensions (3D). The 3D visualization from FIB tomography provides a comprehensive picture of the interconnected microstructural and compositional features that can impact fuel performance. While these features are often characterized with surface examination, the complexity and relationship of fission products and grain boundary networks may not fully be captured by these 2D methods. This work presents a practical guide to FIB tomography that is tailored to nuclear fuel characterization. The steps used to collect and process the data are provided along with the scripts used to process the data. Additionally, suggestions for future characterization efforts utilizing this approach are given.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland

Abstract Quantification of methane (CH 4 ) gas emission from peat is critical to understand CH 4 budget from natural wetlands under a climate warming scenario. Previous studies have focused on prediction and mapping of CH 4 emission flux using process‐based models, while application of statistical‐empirical models for upscaling spatially sparse in situ measurements is scarce. In this study, we developed an empirical remote sensing upscaling approach to estimate CH 4 emission flux in the Everglades using limited in situ point‐based CH 4 emission flux measurements and Landsat data during 2013–2018. We spatially and temporally linked in situ data with Landsat surface reflectance based on temporally composite data sets and developed an object‐based machine learning framework to model and map CH 4 emission flux. An ensemble analysis of two machine learning models, k ‐Nearest Neighbor ( k ‐NN) and Support Vector Machine (SVM), shows that the upscaling approach is promising for predicting CH 4 emission flux with a R 2 of 0.65 and 0.87 based on a fivefold cross‐validation for a dry season and wet season estimation, respectively. We generated emission flux map products that successfully revealed the spatial and temporal heterogeneity of CH 4 emission within the dominant freshwater marsh ecosystem in the Everglades. We conclude that Landsat is promising for upscaling and monitoring CH 4 emission flux and reducing the uncertainty in emission estimates from wetlands.

Zhang, Caiyun↗

pnnl/frequency_sensitivity

This research code base includes functions to compute statistics of image distributions in (spatial DFT) frequency space, train deep learning image classifiers on these distributions with variable depth and weight decay, and finally measure the sensitivity of the trained models to perturbations along (spatial DFT) frequency components.

Central, PNNL Developer↗

The BIRDIES Experiment: Measuring Beryllium Isotopes to Resolve Dynamics in the Stratosphere

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.

58 GEOSCIENCES↗

PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data

Abstract. Geological records of past environmental change provide crucial insights into long-term climate variability, trends, non-stationarity, and nonlinear feedback mechanisms. However, reconstructing spatiotemporal fields from these records is statistically challenging due to their sparse, indirect, and noisy nature. Here, we present PaleoSTeHM, a scalable and modern framework for spatiotemporal hierarchical modeling of paleo-environmental data. This framework enables the implementation of flexible statistical models that rigorously quantify spatial and temporal variability from geological data while clearly distinguishing measurement and inferential uncertainty from process variability. We illustrate its application by reconstructing temporal and spatiotemporal paleo-sea-level changes across multiple locations. Using various modeling and analysis choices, PaleoSTeHM demonstrates the impact of different methods on inference results and computational efficiency. Our results highlight the critical role of model selection in addressing specific paleo-environmental questions, showcasing the PaleoSTeHM framework's potential to enhance the robustness and transparency of paleo-environmental reconstructions.

58 GEOSCIENCES↗

Astrodynamics 1975; Conference, Nassau, Bahamas, July 28-30, 1975, Technical Papers

Articles are grouped under four headings: (1) dynamics and control of satellites; (2) satellite mission analysis; (3) Aeros-B and Symphonie satellite engineering problems; (4) optimization and control techniques applied to solar space heating and cooling of buildings. Topics covered include: communications and earth survey satellite systems, a system of two counter-orbiting satellites measuring GRT-predicted nodal drag, statistical mechanics studies of the spatial density function of orbiting space junk, attitude control of satellites, nutation dampers, low thrust inertial guidance and ascent inertial guidance, a shuttle-launched multi-comet intercept mission, preflight and in-flight analysis of the Atmosphere Explorer (AE-C) satellite, and launch-encounter strategy for the Mariner 1977 Jupiter-Saturn mission. Individual items are announced in this issue.

Powers, W. F.↗

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Ruedger, W. H.↗

Statistics of cold cumulonimbus anvils based on enhanced infrared photographs

Infrared photographs from the Atlantic Geosynchronous Satellite, enhanced to resolve cold anvil temperatures of tropical clouds, are analyzed statistically to determine their spatial-temporal variability during the NASA-U2 Flight Experiment of 1980. Diurnal dependence varies regionally, indicating topographic control via low level convergence and release of convective instability. Anvil growth rates, area covered and duration are discussed for individual and merging anvil systems. Gradients of anvil temperatures implied by infrared photographs are shown to be caused, in part, by radial decrease in anvil depth, i.e., to emissivities less than 1. An error in cloud top temperature of 10C is caused by 10% reduction in emissivity. Errors are near zero in dense, actively growing portions of the anvil.

Danielsen, E. F.↗

Biasing errors and corrections

The dependence of laser velocimeter measurement rate on flow velocity is discussed. Investigations outlining that any dependence is purely statistical, and is nonstationary both spatially and temporally, are described. Main conclusions drawn are that the times between successive particle arrivals should be routinely measured and the calculation of the velocity data rate correlation coefficient should be performed to determine if a dependency exists. If none is found, accept the data ensemble as an independent sample of the flow. If a dependency is found, the data should be modified to obtain an independent sample. Universal correcting procedures should never be applied because their underlying assumptions are not valid.

Meyers, James F.↗

Design and analysis of numerical experiments

Methods for the design and analysis of numerical experiments that are especially useful and efficient in multidimensional parameter spaces are presented. The analysis method, which is similar to kriging in the spatial analysis literature, fits a statistical model to the output of the numerical model. The method is applied to a fully nonlinear, global, equivalent-barotropic dynamical model. The statistical model also provides estimates for the uncertainty of predicted numerical model output, which can provide guidance on where in the parameter space to conduct further experiments, if necessary. The method can provide significant improvements in the efficiency with which numerical sensitivity experiments are conducted.

Bowman, Kenneth P.↗

Effects of location uncertainties on the observed distribution of gamma-ray bursts detected by BATSE

The Burst and Transient Source Experiment (BATSE) on NASA's Compton Gamma-Ray Observatory has shown that the sources of gamma-ray bursts have an angular distribution consistent with isotropy, yet the bursts are spatially inhomogeneous. Detection of a statistically significant deviation from isotropy in the burst distribution would provide a clue to the distance of the burst sources. BATSE's ability to detect slight deviations of the angular distribution from isotropy is, in part, dependent on the accuracy of the computed burst locations. Using bursts whose locations have been determined accurately and independently, we estimate BATSE's location uncertainties and incorporate them into 3D Monte Carlo simulations of the burst distributions to show that, despite individual burst location uncertainties of about 5 deg, the ability of BATSE to place stringent limits on the anisotropy present in the angular distribution of the gamma-ray bursts is not significantly degraded. Observational effects of possible galactic halo distributions of the burst sources are noted.

Horack, J. M.↗

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Lee, J.↗

Monitoring and Assimilation of MIPAS and SCIAMACHY Ozone Data

Preliminary results are presented from experiments that integrate ozone observations from two ENVISAT-borne instruments with the ozone data assimilation system developed at NASA's Data Assimilation Office (DAO). The data used are ozone total column provided by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and stratospheric profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. The DAO's existing system sequentially assimilates the Solar Backscatter Ultraviolet/2 total and partial ozone column data. Incorporation of SCIAMACHY and MIPAS data is done in two stages. First, the observations are monitored. The monitoring consists of computing the differences between Envisat observations and the ozone system forecast, i.e. observed-minus-forecast (O-F) residuals. The O-F residuals are then analyzed using simple statistical methods to examine the spatial distribution of differences, which are large for SCIAMACHY near the terminator. In the second stage, the MIPAS data will be actively assimilated along with the SBW/2 observations; any preliminary results of note will be discussed.

Wargan, K.↗

Validation of Methods to Predict Vibration of a Panel in the Near Field of a Hot Supersonic Rocket Plume

This paper describes the measurement and analysis of surface fluctuating pressure level (FPL) data and vibration data from a plume impingement aero-acoustic and vibration (PIAAV) test to validate NASA s physics-based modeling methods for prediction of panel vibration in the near field of a hot supersonic rocket plume. For this test - reported more fully in a companion paper by Osterholt & Knox at 26th Aerospace Testing Seminar, 2011 - the flexible panel was located 2.4 nozzle diameters from the plume centerline and 4.3 nozzle diameters downstream from the nozzle exit. The FPL loading is analyzed in terms of its auto spectrum, its cross spectrum, its spatial correlation parameters and its statistical properties. The panel vibration data is used to estimate the in-situ damping under plume FPL loading conditions and to validate both finite element analysis (FEA) and statistical energy analysis (SEA) methods for prediction of panel response. An assessment is also made of the effects of non-linearity in the panel elasticity.

Bremner, P. G.↗