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At least 1,675 records · Page 93

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Phenomenological models of two-particle correlation distributions on transverse momentum in relativistic heavy-ion collisions

Two-particle, pair-number correlation distributions on two-dimensional transverse momentum (p t1 , p t2 ) constructed from the particle production in relativistic heavy-ion collisions allow access to dynamical processes in these systems beyond what can be studied with angular correlations alone. Only a few measurements of this type have been reported in the literature, and phenomenological models, which facilitate physical interpretation of the correlation structures, are nonexistent. Ongoing efforts at the Relativistic Heavy-Ion Collider (RHIC) will provide a significant volume of these correlation measurements in the future. In anticipation of these new data, two phenomenological models are developed which describe two-dimensional (2D) correlation distributions on transverse momentum. One model is based on a collision event-by-event fluctuating blast wave. The other is based on event-by-event fluctuations in fragmenting color-flux tubes and in jets. Both models are shown to be capable of accurately describing the measured single-particle p t distributions for minimum-bias Au+Au collisions at √s NN = 200 GeV. Both models are then applied to preliminary, charged-particle correlation measurements on 2D transverse momentum. Here, the capabilities of the two models for describing the overall structure of these correlations, the stability of the fitting results with respect to collision centrality, and the resulting trends of the dynamical fluctuations are evaluated. In general, both phenomenological models are capable of qualitatively describing the major correlation structures on transverse momentum and can be used to establish the required magnitudes and centrality trends of the fluctuations. Both models will be useful for interpreting the forthcoming correlation data from the RHIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Effect of centrality bin width corrections on two-particle number and transverse momentum differential correlation functions

Two-particle number and transverse momentum differential correlation functions are powerful tools for unveiling the detailed dynamics and particle production mechanisms involved in relativistic heavy-ion collisions. Measurements of transverse momentum correlators P 2 and G 2 , in particular, provide added information not readily accessible with better known number correlation functions R 2 . However, it is found that the R 2 and G 2 correlators are somewhat sensitive to the details of the experimental procedure used to measure them. They exhibit, in particular, a dependence on the collision centrality bin width, which may have a rather detrimental impact on their physical interpretation. A technique to correct these correlators for collision centrality bin-width averaging is presented. The technique is based on the hypothesis that the shape of single- and pair-probability densities vary slower with collision centrality than the corresponding integrated yields. In conclusion, the technique is tested with Pb-Pb simulations based on the HIJING and ultrarelativistic quantum molecular dynamics models and shown to enable a precision better than 1% for particles in the kinematic range 0.2 ≤ p T ≤ 2.0 GeV/c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

The NASA ACTIVATE Mission

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol–cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020–22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration N d , including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scavenging, and mesoscale organization. Remote sensing advances range from new retrieval methods for N d , cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technological advances along with efforts in outreach and open data science.

aerosol indirect effect↗

DOE OSTI2021

Comparison of pyrometry and thermography for thermal analysis of thermite reactions

This article examines the thermal behavior of a laser ignited thermite composed of aluminum and bismuth trioxide. Temperature data were collected during the reaction using a four-color pyrometer and a high-speed color camera modified for thermography. The two diagnostics were arranged to collect data simultaneously, with similar fields of view and with similar data acquisition rates, so that the two techniques could be directly compared. Results show that at initial and final stages of the reaction, a lower signal-to-noise ratio affects the accuracy of the measured temperatures. Both diagnostics captured the same trends in transient thermal behavior, but the average temperatures measured with thermography were about 750 K higher than those from the pyrometer. This difference was attributed to the lower dynamic range of the thermography camera’s image sensor, which was unable to resolve cooler temperatures in the field of view as well as the photomultiplier tube sensors in the pyrometer. Overall, while the camera could not accurately capture the average temperature of a scene, its ability to capture peak temperatures and spatial data make it the preferred method for tracking thermal behavior in thermite reactions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

High-dimensional and high-resolution x-ray tomography for energy materials science

At the forefront of developments in synchrotron x-ray microscopy, we report nanoscale-resolution high-dimensional spectrotomography under controlled sample environments has been demonstrated. Such cutting-edge experimental capability has been broadly applied to scientific studies in the field of energy materials science, where the dynamically evolving structural and chemical defects play a vital role in the functionality. In this article, we review novel developments of this technique from both experimental and data/information mining perspectives. Using studies on lithium-ion battery electrode materials as examples, we highlight the rich information in the high-dimensional and high-resolution x-ray tomographic data, which can be used to interpret the complicated thermal-electro-chemo-mechanical interplay that occurs under the operating conditions and collectively determines battery performance. We also discuss the frontier challenges in this field and our perspectives of the future directions in the context of projected major developments in the landscape of largescale x-ray facilities across the globe.

36 MATERIALS SCIENCE↗

NASA NTRS1984

Development of dynamic simulation of TF34-GE-100 turbofan engine with post-stall capability

This paper describes the development of a hybrid computer simulation of a TF34-GE-100 turbofan engine with post-stall capability. The simulation operates in real-time and will be used to test and evaluate stall recovery control modes for this engine. The simulation calculations are performed by an analog computer with a peripheral multivariable function generation unit used for computing bivariate functions. Tabular listings of simulation variables are obtained by interfacing to a digital computer and using a custom software package for data collection and display.

Krosel, S. M.↗

NASA NTRS1986

Effects of salinity on the microwave emission of soils

Controlled plot experiments were conducted to collect L and C band passive microwave data concurrent with ground observations of salinity and soil moisture. Two dielectric mixing models were used with an emission model to predict the emissivity from a bare smooth uniform profile. The models produce nearly identical results when near zero salinity is involved and reproduce the observed data at L band extremely well. Discrepancies at C band are attributed to sampling depth problems. Comparisons of predicted emissivities at various salinities with observed values indicate that the dynamic range of the emissivities can be explained using either of the dielectric mixing models. Evaluation of the entire data set, which included four salinity levels, indicates that for general application the effects of soil salinity can be ignored in interpreting microwave data for estimating soil moisture under most agricultural conditions.

Jackson, T. J.↗

NASA NTRS1987

Salinity effects on the microwave emission of soils

Jackson, Thomas J.↗

NASA NTRS1991

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Clukey, Steven J.↗

NASA NTRS1995

Interactions in Undersaturated and Supersaturated Lysozyme Solutions: Static and Dynamic Light Scattering Results

We have performed multiangle static and dynamic light scattering studies of lysozyme solutions at pH=4.7. The Rayleigh ratio R(sub g) and the collective diffusion coefficient D(sub c) were determined as function of both protein concentration c(sub p) and salt concentration c(sub s) with two different salts. At low salt concentrations, the scattering ratio K(sub c)(sub p)/R(sub theta) and diffusivity increased with protein concentration above the values for a monomeric, ideal solution. With increasing salt concentration this trend was eventually reversed. The hydrodynamic interactions of lysozyme in solution, extracted from the combination of static and dynamic scattering data, decreased significantly with increasing salt concentration. These observations reflect changes in protein interactions, in response to increased salt screening, from net repulsion to net attraction. Both salts had the same qualitative effect, but the quantitative behavior did not scale with the ionic strength of the solution. This indicates the presence of salt specific effects. At low protein concentrations, the slopes of K(sub c)(sub p)/R(sub theta) and D(sub c) vs c(sub p) were obtained. The dependence of the slopes on ionic strength was modeled using a DLVO potential for colloidal interactions of two spheres, with the net protein charge Z(sub e) and Hamaker constant A(sub H) as fitting parameters. The model reproduces the observed variations with ionic strength quite well. Independent fits to the static and dynamic data, however, led to different values of the fitting parameters. These and other shortcomings suggest that colloidal interaction models alone are insufficient to explain protein interactions in solutions.

Muschol, Martin↗

NASA NTRS2004

CFD Approaches for Simulation of Wing-Body Stage Separation

A collection of computational fluid dynamics tools and techniques are being developed and tested for application to stage separation and abort simulation for next-generation launch vehicles. In this work, an overset grid Navier-Stokes flow solver has been enhanced and demonstrated on a matrix of proximity cases and on a dynamic separation simulation of a belly-to-belly wing-body configuration. Steady cases show excellent agreement between Navier-Stokes results, Cartesian grid Euler solutions, and wind tunnel data at Mach 3. Good agreement has been obtained between Navier-Stokes, Euler, and wind tunnel results at Mach 6. An analysis of a dynamic separation at Mach 3 demonstrates that unsteady aerodynamic effects are not important for this scenario. Results provide an illustration of the relative applicability of Euler and Navier-Stokes methods to these types of problems.

Buning, Pieter G.↗

NASA NTRS2011

Evaluating Cloud Computing in the Proposed NASA DESDynI Ground Data System

The proposed NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission would be a first-of-breed endeavor that would fundamentally change the paradigm by which Earth Science data systems at NASA are built. DESDynI is evaluating a distributed architecture where expert science nodes around the country all engage in some form of mission processing and data archiving. This is compared to the traditional NASA Earth Science missions where the science processing is typically centralized. What's more, DESDynI is poised to profoundly increase the amount of data collection and processing well into the 5 terabyte/day and tens of thousands of job range, both of which comprise a tremendous challenge to DESDynI's proposed distributed data system architecture. In this paper, we report on a set of architectural trade studies and benchmarks meant to inform the DESDynI mission and the broader community of the impacts of these unprecedented requirements. In particular, we evaluate the benefits of cloud computing and its integration with our existing NASA ground data system software called Apache Object Oriented Data Technology (OODT). The preliminary conclusions of our study suggest that the use of the cloud and OODT together synergistically form an effective, efficient and extensible combination that could meet the challenges of NASA science missions requiring DESDynI-like data collection and processing volumes at reduced costs.

Benchmark↗

NASA NTRSDate not supplied

Enhancing Autonomous Satellite Communication Systems with Weather-Aware Scheduling and Reconfiguration

NASA currently provides communication support to over 100 satellite missions, and the agency is driving developments in Ka-band communications and network management automation to support additional future missions. At Ka-band frequencies, rain can degrade a communication link by more than 10 dB, which may be mitigated by agile scheduling and data rate control. We present a weather forecasting module for Ka-band communications that is intended to be used in an autonomous network management service that employs machine-to-machine scheduling systems for dynamic user access opportunities. Our forecasting module (NIMBUS) runs on AWS Cloud, consumes the freely and publicly available NOAA MRMS precipitation rate dataset (1km x 1km x 2-min), produces 30-minute Nowcasts using the pySTEPS algorithm, and publishes high level ground station specific link quality predictions. We evaluate two potential NIMBUS outputs, a binary classifier that predicts rain attenuation greater than 3 dB and a rain attenuation estimator, and we backtest these outputs using one year of power measurement data collected from observations of the geostationary ANIK F2 satellite’s Ka-band beacon. We report, with a 30-minute lead time, a binary classifier accuracy of 84% and an estimator RMSE of 1.67 dB. Additionally, we discuss how the NIMBUS module could be incorporated into a user-initiated service framework to enable weather-aware scheduling and reconfiguration. Operating a static link budget with minimal link margin can increase network operation costs by creating additional scheduling tasks due to failed packets, which may require human intervention and/or lead to inefficient asset utilization. The proposed system aims to increase throughput by reducing link margin, while mitigating increases in network operations costs by leveraging autonomous machine-to-machine scheduling, shortened prediction lead times, and advances in precipitation Nowcasting.

satellite communications↗

DOE OSTI2020

Robust Assessment of Real-World Adversarial Examples

We explore rigorous, systematic, and controlled experimental evaluation of adversarial examples in the real world and propose a testing regimen for evaluation of real world adversarial objects. We show that for small scene/ environmental perturbations, large adversarial performance differences exist. Current state of adversarial reporting exists largely as a frequency count over a dynamic collections of scenes. Our work underscores the need for either a more complete report or a score that incorporates scene changes and baseline performance for models and environments tested by adversarial developers. We put forth a score that attempts to address the above issues in a straight-forward exemplar application for multiple generated adversary examples. We contribute the following: 1. a testbed for adversarial assessment, 2. a score for adversarial examples, and 3. a collection of additional evaluations on testbed data.

deep learning, adversarial machine learning, machi↗

DOE OSTI2021

Measurement of N* Cross-Sections from Single-Pion Electroproduction at low Q 2

Measurements of nucleon electroexcitation resonance cross-sections give unique insight into the dynamics of the strong interaction and our knowledge of Quantum Chromodynamics (QCD). The analysis of exclusive electroproduction data is an important tool in understanding the structure of the nucleon and its excited states. Exclusive channels give a clear way to extract the desired resonant contributions from non-resonant contributions. A gap in the helicity amplitudes extracted from single-pion cross-section data exists for virtual photon momentum transfers (Q 2 ) in the range of 1- 2 GeV 2 . Using data collected by the CEBAF Large Acceptance Spectrometer (CLAS) detector with a beam energy of 4.8 GeV, the reaction channel y*r → nπ + is used in this study to investigate the kinematic region covering W=[1.1,1.82)GeV and Q 2 = [1.1,3.5)GeV 2 . This work expands on the previous kinematic coverage for charged single-pion electroproduction and increases the angular coverage of previously extracted kinematic bins.

Tyler, Nicholas↗

DOE OSTI2021

Persistent, “Mysterious” Seismoacoustic Signals Reported in Oklahoma State during 2019

Here, we report on the source of seismoacoustic pulses that were observed across the state of Oklahoma (OK) during summer of 2019, and the subject of national media coverage and speculation. Seismic network data collected across four U.S. states and interviews with witnesses to the pulse’s effect on residential structures demonstrate that they were triggered by routine ammunition disposal operations conducted by McAlester Army Ammunition Plant (McAAP). During these operations, conventional explosives destroy obsolete munitions stored in pits through a controlled sequence of electronically timed shots that occur over tens of minutes. Despite noise-abatement efforts that reduce coupling of acoustic energy with air, some lower frequency, subaudible (infrasonic) sound radiates from these shots as discrete pulses. We use nine months of blast log documents, seismic network records, analyst picks, and physical modeling to demonstrate that seismic stations as far as 640 km from McAAP sample these pulses, which record seasonal patterns in stratospheric and tropospheric winds, as well as the dynamic formation of waveguides and shadow zones. Digital short-term average to long-term average detectors that we augment with dynamic thresholds and time-binning operations identify these pulses with a fair probability, when compared with visual observations. Our analyses thereby provide estimates of observation rates for both partial and full sequences of these pulses, as well as single shots. We suggest that disposal operations can exploit existing, composite seismic networks to predict where residents are likely to witness blasting. Crucially, our data also show that dense seismic networks can record multiscale atmospheric processes in the absence of infrasound arrays.

58 GEOSCIENCES↗

NASA NTRS1984

Development of dynamic simulation of TF34-GE-100 turbofan engine with post-stall capability

This paper describes the development of a hybrid computer simulation of a TF34-GE-100 turbofan engine with post-stall capability. The simulation operates in real-time and will be used to test and evaluate stall recovery control modes for this engine. The simulation calculations are performed by an analog computer with a peripheral multivariable function generation unit used for computing bivariate functions. Tabular listings of a simulation variables are obtained by interfacing to a digital computer and using a custom software package for data collection and display.

Krosel, S. M.↗

DOE OSTI2026

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗