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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Three-dimensional migration behavior of juvenile salmonids in reservoirs and near dams

To acquire 3-D tracking data on juvenile salmonids, Juvenile Salmon Acoustic Telemetry System (JSATS) cabled hydrophone arrays were deployed in the forebays of two dams on the Snake River and at a mid-reach reservoir between the dams. The depth distributions of fish were estimated by statistical analyses performed on large 3-D tracking data sets from ~33,500 individual acoustic tagged yearling and subyearling Chinook salmon and juvenile steelhead at the two dams in 2012 and subyearling Chinook salmon at the two dams and the mid-reach reservoir in 2013. This research investigated the correlation between vertical migration behavior and passage routes. The depth distributions of fish within the forebays of the dams were significantly different from fish passing the mid-reach reservoir. Fish residing deeper in the forebay tended to pass the dam using deeper powerhouse routes. This difference in depth distributions indicated that the depth distribution of fish at the mid-reach reservoir was not related to behaviors of fish passing through certain routes of the adjacent dams. For fish that were detected deeper than 17.5 m in the forebays, the probability of powerhouse passage (i.e., turbine) increased significantly. Another important finding was the variation in depth distributions during dam passage associated with the diel period, especially the crepuscular periods.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Mars Global Reference Atmospheric Model (Mars-GRAM) and Database for Mission Design

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model, while above 80 km it is based on Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter. Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science and Thermal Emission Spectrometer data. RS data from 2480 profiles were used, covering latitudes 75 deg S to 72 deg N, surface to approximately 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160 deg and 265-310 deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, RS density varied by about a factor of 2.5 over ranges of latitudes and Ls values observed. Evaluated at matching positions and times, these figures show average RSMars-GRAM density ratios were generally 1+/-)0.05, except at heights above approximately 25 km and latitudes above approximately 50 deg N. Average standard deviation of RSMars-GRAM density ratio was 6%. TES data were used covering surface to approximately 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). Depending on season, TES data covered latitudes 85 deg S to 85 deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (greater than 45 deg N), or at most altitudes in the southern hemisphere at Ls approximately 90 and 180 deg. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approximately 2.5% for all data, or approximately 1-4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C. G.↗
DOE OSTI2017

Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data

Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

Abstract Background Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. Results We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. Conclusions Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

GoAmazon 2014/15 Particle Sampling Field Campaign Report

As a part of the GoAmazon 2014/15 field deployments, samples of atmospheric particles were collected at the T3 field site (3° 12' 46.70" S, 60° 35' 53.0, Manacapuru, Brazil) established in the Amazonian region. The site was located downwind from Manaus and therefore, experienced clean conditions when winds were from northwest and polluted conditions when winds were from Manaus. During the second intensive operational period of GoAmazon 2014/15 (09/06/2014-10/02/2014), multiple samples of particles were collected using a cascade Multi-Orifice Uniform Deposition Impactor (MOUDI-110). Size-resolved samples by MOUDI (0.056-0.1, 0.1-0.18, 0.18-0.32, 0.32-0.56, 0.56-1.0, 1.0-1.8 μm) were collected for 6-12 hours. A variety of substrates, compatible with different spectro-microscopy methods of analysis, were arranged on the impactor stages. Collected aerosol samples are now stored pending laboratory analysis using multi-modal methods of chemical imaging. Our approach is to analyze only the samples of specific interest. We use the field campaign records and data on meteorology, as well as in situ measurements of gases and aerosols, to select the subset of samples for the in-depth laboratory analysis for selected episodes where changes in chemical composition of particles can be correlated with other data recorded at the site. Hence, we do not expect to perform detailed measurements on all samples—rather, only those samples with the greatest potential to provide scientific insight into aerosol chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network

As the disparity between compute and I/O on high-performance computing systems has continued to widen, it has become increasingly difficult to perform post-hoc data analytics on full-resolution scientific simulation data due to the high I/O cost. Error-bounded data decomposition and progressive data retrieval framework has recently been developed to address such a challenge by performing data decomposition before storage and reading only part of the decomposed data when necessary. However, the performance of the progressive retrieval framework has been suffering from the over-pessimistic error control theory, such that the achieved maximum error of recomposed data is significantly lower than the required error. Therefore, more data than required is fetched for recomposition, incurring additional I/O overhead. In order to tackle this issue, we propose a DNN-based progressive retrieval framework that can better identify the minimum amount of data to be retrieved. Our contributions are as follows: 1) We provide an in-depth investigation of the recently developed progressive retrieval framework; 2) We propose two designs of prediction models (named D-MGARD and E-MGARD) to estimate the amount of retrieved data size based on error bounds. 3) We evaluate our proposed solutions using scientific datasets generated by real-world simulations from two domains. Evaluation results demonstrate the effectiveness of our solution in accurately predicting the amount of retrieval data size, as well as the advantages of our solution over the traditional approach to reducing the I/O overhead. Based on our evaluation, our solution is shown to read significantly less data (5% - 40% with D-MGARD, 20% - 80% with E-MGARD).

Wang, Jinzhen↗
DOE OSTI2016

Rising plant-mediated methane emissions from arctic wetlands

Plant-mediated CH 4 flux is an important pathway for land–atmosphere CH 4 emissions, but the magnitude, timing, and environmental controls, spanning scales of space and time, remain poorly understood in arctic tundra wetlands, particularly under the long-term effects of climate change. CH 4 fluxes were measured in situ during peak growing season for the dominant aquatic emergent plants in the Alaskan arctic coastal plain, Carex aquatilis and Arctophila fulva, to assess the magnitude and species-specific controls on CH 4 flux. Plant biomass was a strong predictor of A. fulva CH 4 flux while water depth and thaw depth were copredictors for C. aquatilis CH 4 flux. Here, we used plant and environmental data from 1971 to 1972 from the historic International Biological Program (IBP) research site near Barrow, Alaska, which we resampled in 2010–2013, to quantify changes in plant biomass and thaw depth, and used these to estimate species-specific decadal-scale changes in CH 4 fluxes. A ~60% increase in CH 4 flux was estimated from the observed plant biomass and thaw depth increases in tundra ponds over the past 40 years. In spite of our covering only ~5% of the landscape, we estimate that aquatic C. aquatilis and A. fulva account for two-thirds of the total regional CH 4 flux of the Barrow Peninsula. The regionally observed increases in plant biomass and active layer thickening over the past 40 years not only have major implications for energy and water balance, but also have significantly altered land–atmosphere CH 4 emissions for this region, potentially acting as a positive feedback to climate warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

GeoXO Atmospheric Composition Instrument (AC) Measurements Conditions Assessment

NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecraft at GOES-Central position, that will carry an Atmospheric Composition Instrument (ACX) among its payloads; the requirement on the ACX is to scan its region of interest in one hour. An assessment of ACX observational conditions is presented, based on view geometry and solar angle range over the year. The availability for observations of each pixel is estimated per day of the year, as function of the geometric air mass factor (AMF), which can be related to signal to noise ratio using a model of the ACX instrument performance, and ultimately to expected column error for specific atmospheric species. In addition, cloud climatology – based on statistics derived from GOES-16 ABI cloud product data – is considered to determine typical fractions of cloud-free ACX observations and typical cloud optical depths, for each pixel as function of time of day and season. The results of such assessments can be used to prepare for GeoXO ACX data and further the understanding and development of the future instrument operations.

Boryana Efremova↗
NASA NTRS1994

Comparison of plate and asthenospheric flow models for the thermal evolution of oceanic lithosphere

Although seafloor depth and heat flow for young oceanic lithosphere can be descibed by modeling the lithosphere as the boundary layer of a cooling halfspace, a long standing question has been why data at older ages deviate from those expected for a halfspace. Two classes of models have been proposed for these deviations. In one, heat added from below 'flattens' depth and heat flow. In the other, asthenospheric flow beneath the lithosphere perturbs the depths. We compare recent versions of the model classes: the GDH1 thin-lithosphere plate model (Stein and Stein, 1992) and an asthenospehric flow model (Phipps Morgan and Smith, 1992). The plate model fits heat flow data better than the flow model for all cases considered, and topographic data in all but one case. The flow model significantly overpredicts depths for the North Atlantic, because the assumed asthenospheric flow in the plate motion direction would yield deepening for old ages rather than the observed flattening. Overall, the GDH1 global average model does better than this flow model, whose parameters were fit to specific plates. Moreover, the plate models fit to specific plates do better than the flow model. Plate models thus appear more useful than this flow model, suggesting that deviations from a cooling halfspace are largely thermal in origin.

Stein, Carol A.↗
NASA NTRS2014

The Asteroid Impact and Deflection Assessment Mission and its Potential Contributions to Human Exploration of Asteroids

The joint ESA and NASA Asteroid Impact and Deflection Assessment (AIDA) mission will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission, involves sending astronauts to study and sample a near-Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. AIDA's primary objective is to demonstrate a kinetic impact deflection and characterize the binary NEA Didymos. The science and technical data obtained from AIDA will aid in the planning of future human exploration missions to NEAs and other small bodies. The dual robotic missions of AIDA, ESA's Asteroid Impact Monitor (AIM) and NASA's Double Asteroid Redirection Test (DART), will provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while conducting in-depth scientific examinations of the binary target Didymos both prior to and after the kinetic impact demonstration. The knowledge gained from this mission will help identify asteroidal physical properties in order to maximize operational efficiency and reduce mission risk for future small body missions. The AIDA data will help fill crucial strategic knowledge gaps concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations.

Abell, Paul A.↗
NASA NTRS2017

Pyroclastics Northeast of Gassendi Crater: Discovery/Characteristics/Implications

In our ongoing effort to better understand lunar volcanism on the Moon, we are investigating pyroclastic deposits in the Gassendi region. Interest in pyroclastics has remained high due to the availability of high-resolution data (LRO, Kaguya), which is used to build on previous remote sensing studies [e.g., 1, 2, 3] and also extensive studies of lunar pyroclastic glasses [4, 5]. Analyses conducted in the laboratory of pyroclastic spheres from several deposits show that this volcanic material had a greater depth of origin and lesser fractional crystallization than mare basalts [e.g., 4, 6]. Data indicates that pyroclastic glasses are the best examples of primitive materials on the Moon, and they are important for both characterizing the lunar interior and as a starting place for under-standing the origin and evolution of lunar basaltic magmatism [2].

Giguere, T. A.↗
NASA NTRS2000

Coupling Satellite and Ground-Based Instruments to Map Climate Forcing by Anthropogenic Aerosols

Climate forcing by anthropogenic aerosols is a significant but highly uncertain factor in global climate change. Only satellites can offer the global coverage essential to reducing this uncertainty; however, satellite measurements must be coupled with correlative, in situ measurements both to constrain the aerosol optical properties required in satellite retrieval algorithms and to provide chemical identification of aerosol sources. This grant funded the first two years of a three-year project which seeks to develop methodologies for combining spaceborne lidar with in-situ aerosol data sets to improve estimates of direct aerosol climate forcing. Progress under this two-year grant consisted in the development and deployment of a new in-situ capability for measuring aerosol 180' backscatter and the extinction-to-backscatter ratio. This new measurement capacity allows definitive lidar/in-situ comparisons and improves our ability to interpret lidar data in terms of climatically relevant quantities such as the extinction coefficient and optical depth. Measurements were made along the coast of Washington State, in Central Illinois, over the Indian Ocean, and in the Central Pacific. Thus, this research, combined with previous measurements by others, is rapidly building toward a global data set of extinction-to-backscatter ratio for key aerosol types. Such information will be critical to interpreting lidar data from the upcoming PICASSO-CENA, or P-C, satellite mission. Another aspect of this project is to investigate innovative ways to couple the lidar-satellite signal with targeted in-situ measurements toward a direct determination of aerosol forcing. This aspect is progressing in collaboration with NASA Langley's P-C lidar simulator and radiative transfer modeling by the University of Lille, France.

Charlson, Robert J.↗
DOE OSTI2017

Evaluating Corrosion in SAVY Containers using Non-Destructive Techniques

Powerpoint presentation on Ultrasonic and Eddy Current NDT; UT Theory; Eddy current (ECA): How it works; Controlled Corrosion at NM Tech; Results – HCl Corrosion; Waveform Data for 10M HCl; Accuracy Statistics; Results – FeCl 3 Pitting; Waveforms for Anhydrous FeCl 3 ; Analyzing Corroded Stainless Steel 316L Plates; 316L Plate to Imitate Pitting; ECA Pit Depth Calibration Curve; C Scan Imaging; UT Pit Detection; SST Containers: Ultrasonic (UT) vs. CMM; UT Data Analysis; UT Conclusions and Observations; ECA Conclusions; Automated System Vision.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Apparent Minimum Free Energy Requirements for Methanogenic Archaea and Sulfate-Reducing Bacteria in an Anoxic Marine Sediment

Among the most fundamental constraints governing the distribution of microorganisms in the environment is the availability of chemical energy at biologically useful levels. To assess the minimum free energy yield that can support microbial metabolism in situ, we examined the thermodynamics of H2-consuming processes in anoxic sediments from Cape Lookout Bight, NC, USA. Depth distributions of H2 partial pressure, along with a suite of relevant concentration data, were determined in sediment cores collected in November (at 14.5 C) and August (at 27 C) and used to calculate free energy yields for methanogenesis and sulfate reduction. At both times of year, and for both processes, free energy yields gradually decreased (became less negative) with depth before reaching an apparent asymptote. Sulfate reducing bacteria exhibited an asymptote of -19.1 +/- 1.7 kj(mol SO4(2-)(sup -1) while methanogenic archaea were apparently supported by energy yields as small as -10.6 +/- 0.7 kj(mol CH4)(sup -1).

Hoehler, Tori M.↗
NASA NTRS2002

Mars-Gram Validation with Mars Global Surveyor Data

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many b4ars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science (RS) and Thermal Emission Spectrometer (TES) data. RS data from 2480 profiles were used, covering latitudes 75deg S to 72deg N, surface to approx. 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160deg and 265-310deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, measured RS density varied by about a factor of 2.5 over the range of latitudes and Ls values observed. Evaluated at matching positions and times, average RS/Mars-GRAM density ratios were generally lf0.05, except at heights above approx. 25 km and latitudes above approx.50deg N. Average standard deviation of RS/Mars-GRAM density ratio was 6%. TES data were used covering surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of Mars global dust storm). Depending on season, TES data covered latitudes 85deg S to 85deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 6.5-10.5% (varying with height) for all data, or approx. 5- 12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for 1o:al time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C. G.↗
DOE OSTI2020

Square Kilometre Array Science Data Challenge 1: analysis and results

ABSTRACT As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality data sets for testing and evaluating new techniques. In this paper, we present a description and results from the first such Science Data Challenge 1 (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560, 1400, and 9200 MHz) at three depths (8, 100, and 1000 h), SDC1 asked participants to apply source detection, characterization, and classification methods to simulated data. The challenge opened in 2018 November, with nine teams submitting results by the deadline of 2019 April. In this work, we analyse the results for eight of those teams, showcasing the variety of approaches that can be successfully used to find, characterize, and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

Bonaldi, A.↗
DOE OSTI2015

A physical approach to the identification of high-Z mergers: Morphological classification in the stellar mass domain

At z ≳ 1, the distinction between merging and “normal” star-forming galaxies based on single band morphology is often hampered by the presence of large clumps which result in a disturbed, merger-like appearance even in rotationally supported disks. In this paper we discuss how a classification based on canonical, non-parametric structural indices measured on resolved stellar mass maps, rather than on single-band images, reduces the misclassification of clumpy but not merging galaxies. We calibrate the mass-based selection of mergers using the MIRAGE hydrodynamical numerical simulations of isolated and merging galaxies which span a stellar mass range of 10{sup 9.8}–10{sup 10.6} M{sub ⊙} and merger ratios between 1:1–1:6.3. These simulations are processed to reproduce the typical depth and spatial resolution of observed Hubble Ultra Deep Field (HUDF) data. We test our approach on a sample of real z≃2 galaxies with kinematic classification into disks or mergers and on ∼100 galaxies in the HUDF field with photometric/spectroscopic redshift between 1.5 ≤ z ≤ 3 and M > 10{sup 9.4} M{sub ⊙}. We find that a combination of the asymmetry A{sub MASS} and M{sub 20, MASS} indices measured on the stellar mass maps can efficiently identify real (major) mergers with ≲20% contamination from clumpy disks in the merger sample. This mass-based classification cannot be reproduced in star-forming galaxies by H-band measurements alone, which instead result in a contamination from clumpy galaxies which can be as high as 50%. Moreover, we find that the mass-based classification always results in a lower contamination from clumpy galaxies than an H-band classification, regardless of the depth of the imaging used (e.g., CANDELS versus HUDF).

79 ASTRONOMY AND ASTROPHYSICS↗