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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
NASA NTRS1999

An Assessment of Magnetic Conditions for Strong Coronal Heating in Solar Active Regions by Comparing Observed Loops with Computed Potential Field Lines

We report further results on the magnetic origins of coronal heating found from registering coronal images with photospheric vector magnetograms. For two complementary active regions, we use computed potential field lines to examine the global non-potentiality of bright extended coronal loops and the three-dimensional structure of the magnetic field at their feet, and assess the role of these magnetic conditions in the strong coronal heating in these loops. The two active regions are complementary, in that one is globally potential and the other is globally nonpotential, while each is predominantly bipolar, and each has an island of included polarity in its trailing polarity domain. We find the following: (1) The brightest main-arch loops of the globally potential active region are brighter than the brightest main- arch loops of the globally strongly nonpotential active region. (2) In each active region, only a few of the mainarch magnetic loops are strongly heated, and these are all rooted near the island. (3) The end of each main-arch bright loop apparently bifurcates above the island, so that it embraces the island and the magnetic null above the island. (4) At any one time, there are other main-arch magnetic loops that embrace the island in the same manner as do the bright loops but that are not selected for strong coronal heating. (5) There is continual microflaring in sheared core fields around the island, but the main-arch bright loops show little response to these microflares. From these observational and modeling results we draw the following conclusions: (1) The heating of the main-arch bright loops arises mainly from conditions at the island end of these loops and not from their global non-potentiality. (2) There is, at most, only a loose coupling between the coronal heating in the bright loops of the main arch and the coronal heating in the sheared core fields at their feet, although in both the heating is driven by conditions/events in and around the island. (3) The main-arch bright loops are likely to be heated via reconnection driven at the magnetic null over the island. The details of how and where (along the null line) the reconnection is driven determine which of the split-end loops are selected for strong heating. (4) The null does not appear to be directly involved in the heating of the sheared core fields or in the heating of an extended loop rooted in the island. Rather, these all appear to be heated by microflares in the sheared core field.

Gary, G. A.↗
NASA NTRS2006

Small Body GN&C Research Report: A G-Guidance Enhancement to Increase Mission Functionality

G-Guidance is a robust G&C (guidance and control) algorithm developed under the small-body GN&C task. The G-Guidance scheme utilizes a model predictive control approach, along with a convexification of the governing dynamics, control constraints, and trajectory/state constraints. This report details an enhancement to the FY2005 G-Guidance algorithm; the addition of a fire-second approach helps to nullify velocity errors and hit desired final velocities much more precisely than the original Fire-first scheme developed in FY2005. The enhancement preserves the primary benefit of the algorithm, which is to ensure required thruster silent times during trajectory maneuvers. The fire-second scheme increases the versatility of the algorithm for missions employing G-Guidance. For instance, a landing sequence could employ the fire-second scheme to ensure a null final velocity at landing, whereas an ascent sequence could utilize a fire-first scheme to ensure there is no drift of the spacecraft toward the ground at the beginning of the maneuver. Examples are provided within to demonstrate a fire-first versus fire-second guidance scheme. As in the existing G-Guidance algorithm, the examples and schemes incorporate gravity models and thruster firing times into discrete dynamics that are solved as a optimal control problem to minimize fuel consumption or thruster energy expenditure.

velocity errors↗
DOE OSTI2021

River sinuosity describes a continuum between randomness and ordered growth

River channels are among the most common landscape features on Earth. An essential characteristic of channels is sinuosity: their tendency to take a circuitous path, which is quantified as along-stream length divided by straight-line length. River sinuosity is interpreted as a characteristic that either forms randomly at channel inception or develops over time as meander bends migrate. Studies tend to assume the latter and thus have used river sinuosity as a proxy for both modern and ancient environmental factors including climate, tectonics, vegetation, and geologic structure. But no quantitative criterion for planform expression has distinguished between random, initial sinuosity and that developed by ordered growth through channel migration. This ambiguity calls into question the utility of river sinuosity for understanding Earth’s history. We propose a quantitative framework to reconcile these competing explanations for river sinuosity. Using a coupled analysis of modeled and natural channels, we show that while a majority of observed sinuosity is consistent with randomness and limited channel migration, rivers with sinuosity ≥1.5 likely formed their geometry through sustained, ordered growth due to channel migration. This criterion frames a null hypothesis for river sinuosity that can be applied to evaluate the significance of environmental interpretations in landscapes shaped by rivers. The quantitative link between sinuosity and channel migration further informs strategies for preservation and restoration of riparian habitat and guides predictions of fluvial deposits in the rock record and in remotely sensed environments from the seafloor to planetary surfaces.

58 GEOSCIENCES↗
DOE OSTI2023

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a collection of objects stored within an RDate file, stateWaterRightsHarmonized.RData. Each object either describes how one should interact with the other objects, or contains the harmonized water rights data. Here is each object described in detail: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. The column headers for each data frame are: waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. basinNum - The alpha-numeric identifier of the WMA the record belongs to. priorityDate - The priority date associated with the right. allocatedFlow - The maximum flow of the allocation in cubic feet per second (ft3s-1). source - Whether the right is for surface water or groundwater. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. rightsByState_surface: A list of the cleaned surface water rights collected from each state. See rightsByState_ground for more details on how the data is formatted. fullRightsRecs: A list of the combined groundwater and surface water records for each state. Essentially, these lists are the merging of rightsByState_ground and rightsByState_surface by state. See rightsByState_ground for more details on how the data is formatted. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page.

Economics↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to included within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state.

Economics↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two-digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use(s) from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to include within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state. For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. This object holds the the data that is exported to created the xxGroundwaterHarmonizedRights.csv files. rightsByState_surface: A list of data frames with the cleaned surface water rights collected from each state. This object holds the the data that is exported to created the xxSurfaceWaterHarmonizedRights.csv files. fullRightsRecs: A list of the combined groundwater and surface water records for each state. This object holds the the data that is exported to created the xxFullHarmonizedRights.csv files. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page. The code related to the creation of this dataset can be viewed within HarDWR GitHub Repository/dataHarmonization.

Economics↗
NASA NTRS1992

Scattering effects of solar panel on Space Station Space-To-Ground (SGS) antenna performance

The purpose of this study is to characterize the scattering effects of a solar panel on the Space Station Space-to-Ground Subsystem reflector antenna when the antenna is operated in the RF tracking (difference) mode. This analysis is based on a combination of geometrical theory of diffraction and aperture integration techniques. The advantage of this combination method is its capability in predicting reflector antenna patterns not only in the forward region but also in the far-out sidelobes and backlobes. To verify the analytical model, measurements were performed on the Johnson Space Center far-field antenna test facility. Good agreement between computed and measured results was obtained. It was shown from computation and experiment that the solar panel scattering interference causes a shift in null position, a decrease in the depth of the null, as well as a decrease in the gain on the antenna difference mode patterns.

Hwu, Shian U.↗
DOE OSTI2022

Evidence of underdeveloped torus and broad-line region of weak emission line quasars based on their spectral energy distribution

To unravel the dominant cause of the weak emission line in a subset of optically selected radio-quiet ‘weak emission line quasars’ (WLQs), we have investigated the possibility of an underdeveloped broad line region (BLR). For this, we have modelled spectral energy distributions (SED) of 61 WLQs by using their optical and infrared (IR) photometric observations from Sloan Digital Sky Survey (SDSS) and WISE, respectively. SED fit consists of various emission components, including the luminosity from the dusty torus (L tor ). For comparison with the normal quasar, we have used a control sample of 55 Quasi-Stellar Objects (QSOs) for each WLQ matching in emission redshift and SDSS r-band. Based on our measurement of L tor , we found a decrement of 42 ± 2 per cent in IR luminosity in WLQs with respect to the control sample of normal QSOs. Using L tor /L bol as the measure of torus covering factor (CF tor ), we found a similar decrement in WLQ covering factor, with their CF tor distribution being significantly different with respect to the normal QSOs with a KS test P null of 4.27 × 10 −14 . As dusty torus and BLR covering factors are expected to be of a similar order in active galactic nucleus (AGN), our results suggest that the BLR in the WLQs is underdeveloped and could be a dominant cause of the weakness of their emission line. As a result, our analysis gives support to the models of WLQs based on the evolution scenario being in an early stage of AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

EIT Crinkles as Evidence for the Breakout Model of Solar Eruptions

We present observations of two homologous flares in NOAA active region 8210 occurring on 1998 May 1 and May 2, using EUV data from the Extreme Ultraviolet Radiation Imaging Telescope (EIT) on the Solar and Heliospheric Observatory (SOHO), high-resolution and high-time cadence images from the soft X-ray telescope (SXT) on Yohkoh, images or fluxes from the hard X-ray telescope (HXT) on Yohkoh and the BATSE experiment on the Compton Gamma Ray Observatory (CGRO), and Ca xix soft X-ray spectra from the Bragg crystal spectrometer (BCS) on Yohkoh. Magnetograms indicate that the flares occurred in a complex magnetic topology, consisting of an emerging flux region (EFR) sandwiched between a sunspot to the west and a coronal hole to the east. In an earlier study we found that in EIT images, both flaring episodes showed the formation of a crinkle-like pattern of emission ("EIT crinkles") occurring in the coronal hole vicinity, well away from a central "core field" area near the EFR-sunspot boundary. With our expanded data set, here we find that most of the energetic activity occurs in the core region in both events, with some portions of the core brightening shortly after the onset of the EIT crinkles, and other regions of the core brightening several minutes later, coincident with a burst of hard X-rays: there are no obvious core brightenings prior to the onset of the EIT crinkles. These timings are consistent with the "breakout model" of solar eruptions, whereby the emerging flux is initially constrained by a system of overlying magnetic field lines, and is able to erupt only after an opening develops in the overlying fields as a consequence of magnetic reconnection at a magnetic null point. In our case, the EIT crinkles would be a signature of this pre-impulsive-phase magnetic reconnection, and brightening of the core only occurs after the core fields begin to escape through the newly-created opening in the overlying fields. Morphology in soft X-ray images and properties in hard X-rays differ between the two events, with complexities that preclude a simple determination of the dynamics in the core at the times of eruption. From the BCS spectra, we find that the core region expends energy at a rate of approx. 10(exp 26) erg per second during the time of the growth of the EIT crinkles; this rate is an upper limit to energy expended in the reconnections opening the overlying fields. Energy losses occur at an order-of-magnitude higher rate near the time of the peak of the events. There is little evidence of asymmetry in the spectra, consistent with the majority of the mass flows occurring normal to the line-of-sight. Both events have similar electron temperature dependencies on time.

Sterling, Alphonse C.↗
NASA NTRS2001

EIT Crinkles as Evidence for the Breakout Model of Solar Eruptions

We present observations of two homologous flares in NOAA Active Region 8210 occurring on 1998 May 1 and 2, using EUV data from the EUV Imaging Telescope (EIT) on board the Solar and Heliospheric Observatory, high-resolution and high-time cadence images from the soft X-ray telescope on Yohkoh, images or fluxes from the hard X-ray telescope on Yohkoh and the BATSE experiment on board the Compton Gamma Ray Observatory, and Ca(XIX) soft X-ray spectra from the Bragg crystal spectrometer (BCS) on Yohkoh. Magnetograms indicate that the flares occurred in a complex magnetic topology, consisting of an emerging flux region (EFR) sandwiched between a sunspot to the west and a coronal hole to the east. In an earlier study we found that in EIT images, both flaring episodes showed the formation of a crinkle-like pattern of emission (EIT crinkles) occurring in the coronal hole vicinity, well away from a central 'core field' area near the EFR-sunspot boundary. With our expanded data set, here we find that most of the energetic activity occurs in the core region in both events, with some portions of the core brightening shortly after the onset of the EIT crinkles, and other regions of the core brightening several minutes later, coincident with a burst of hard X-rays; there are no obvious core brightenings prior to the onset of the EIT crinkles. These timings are consistent with the 'breakout model' of solar eruptions, whereby the emerging flux is initially constrained by a system of overlying magnetic field lines, and is able to erupt only after an opening develops in the overlying fields as a consequence of magnetic reconnection at a magnetic null point. In our case, the EIT crinkles would be a signature of this pre-impulsive phase magnetic reconnection, and brightening of the core only occurs after the core fields begin to escape through the newly created opening in the overlying fields. Morphology in soft X-ray images and properties in hard X-rays differ between the two events, with complexities that preclude a simple determination of the dynamics in the core at the times of eruption. From the BCS spectra, we find that the core region expends energy at a rate of approximately 10(exp 26) ergs/s during the time of the growth of the EIT crinkles; this rate is an upper limit to energy expended in the reconnections opening the overlying fields. Energy losses occur at an order of magnitude higher rate near the time of the peak of the events. There is little evidence of asymmetry in the spectra, consistent with the majority of the mass flows occurring normal to the line of sight. Both events have similar electron temperature dependencies on time.

Sterling, Alphonse C.↗
NASA NTRS2000

Progesterone facilitates chromosome instability (aneuploidy) in p53 null normal mammary epithelial cells

Mammary epithelial cells from p53 null mice have been shown recently to exhibit an increased risk for tumor development. Hormonal stimulation markedly increased tumor development in p53 null mammary cells. Here we demonstrate that mammary tumors arising in p53 null mammary cells are highly aneuploid, with greater than 70% of the tumor cells containing altered chromosome number and a mean chromosome number of 56. Normal mammary cells of p53 null genotype and aged less than 14 wk do not exhibit aneuploidy in primary cell culture. Significantly, the hormone progesterone, but not estrogen, increases the incidence of aneuploidy in morphologically normal p53 null mammary epithelial cells. Such cells exhibited 40% aneuploidy and a mean chromosome number of 54. The increase in aneuploidy measured in p53 null tumor cells or hormonally stimulated normal p53 null cells was not accompanied by centrosome amplification. These results suggest that normal levels of progesterone can facilitate chromosomal instability in the absence of the tumor suppressor gene, p53. The results support the emerging hypothesis based both on human epidemiological and animal model studies that progesterone markedly enhances mammary tumorigenesis.

NASA Discipline Radiation Health↗
NASA NTRS2016

Flow Characterization Studies of the 10-MW TP3 Arc-Jet Facility: Probe Sweeps

This paper reports computational simulations and analysis in support of calibration and flow characterization tests in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted in the NASA Ames 10-MW TP3 facility using flat-faced stagnation calorimeters at six conditions corresponding to the steps of a simulated flight heating profile. Data were obtained using a conical nozzle test configuration in which the models were placed in a free jet downstream of the nozzle. Experimental surveys of arc-jet test flow with pitot pressure and heat flux probes were also performed at these arc-heater conditions, providing assessment of the flow uniformity and valuable data for the flow characterization. Two different sets of pitot pressure and heat probes were used: 9.1-mm sphere-cone probes (nose radius of 4.57 mm or 0.18 in) with null-point heat flux gages, and 15.9-mm (0.625 in) diameter hemisphere probes with Gardon gages. The probe survey data clearly show that the test flow in the TP3 facility is not uniform at most conditions (not even axisymmetric at some conditions), and the extent of non-uniformity is highly dependent on various arc-jet parameters such as arc current, mass flow rate, and the amount of cold-gas injection at the arc-heater plenum. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested. Comparisons of computations with the experimental measurements show reasonably good agreement except at the extreme low pressure conditions of the facility envelope.

Goekcen, Tahir↗
NASA NTRS2016

Flow Characterization Studies of the 10-MW TP3 Arc-Jet Facility: Probe Sweeps

This paper reports computational simulations and analysis in support of calibration and flow characterization tests in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted in the NASA Ames 10-MW TP3 facility using flat-faced stagnation calorimeters at six conditions corresponding to the steps of a simulated flight heating profile. Data were obtained using a conical nozzle test configuration in which the models were placed in a free jet downstream of the nozzle. Experimental surveys of arc-jet test flow with pitot pressure and heat flux probes were also performed at these arc-heater conditions, providing assessment of the flow uniformity and valuable data for the flow characterization. Two different sets of pitot pressure and heat probes were used: 9.1-mm sphere-cone probes (nose radius of 4.57 mm or 0.18 in) with null-point heat flux gages, and 15.9-mm (0.625 in) diameter hemisphere probes with Gardon gages. The probe survey data clearly show that the test flow in the TP3 facility is not uniform at most conditions (not even axisymmetric at some conditions), and the extent of non-uniformity is highly dependent on various arc-jet parameters such as arc current, mass flow rate, and the amount of cold-gas injection at the arc-heater plenum. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested. Comparisons of computations with the experimental measurements show reasonably good agreement except at the extreme low pressure conditions of the facility envelope.

CFD↗
DOE OSTI2021

The H I absorption zoo: JVLA extension to z ~ 0.4

Here, we present an H I 21 cm absorption study of a sample of 26 radio-loud active galactic nuclei (AGN) at 0.25 < z < 0.4 carried out with the Karl G. Jansky Very Large Array. Our aim was to study the rate of incidence of H I in different classes of radio AGN, the morphology and kinematics of the detected H I, and the nature of the interaction between the H I and the radio source at these redshifts. Our sample consists of 14 sources with sizes of up to tens of kpc and 12 compact sources (< a few kpc) in the radio-power range 10 25.7 W Hz –1 –10 26.5 W Hz –1 . We detect H I in five sources, corresponding to a detection rate of ~19%. Within the error bars, this agrees with the detection rate found at lower redshifts. We find that the rest-frame UV luminosities of most of the sources in the sample, including all the detections, are below the proposed threshold above which the H I is supposed to have been ionised. An analysis of the optical emission-line spectra of the sources shows that despite their high radio powers, about one-third of the sample, including two detections, are low-ionisation sources. The radio continuum emission from the sources detected in H I is unresolved at ~5 to 10 kpc scales in our observations, but shows extended structure on parsec scales. We analysed the H I 21 cm absorption spectra of the detections to understand the morphology and kinematics of H I. The absorption profiles are mostly complex with widths between the nulls ranging from ~60 km s –1 to 700 km s –1 . These detections also exhibit remarkably high H I column densities in the range ~10 21 cm –2 –10 22 cm –2 for T spin = 100 K and unit covering factor. Our modelling of the H I 21 cm absorption profiles suggests that in two sources the gas appears to be disturbed, and in three cases, including one with disturbed H I, the majority of the absorption is consistent with it arising from an H I disc. Despite the high radio power of our sources, we do not detect fast outflows. However, the optical emission lines in these detections show the presence of significantly disturbed gas in the nuclear regions in the form of very wide and highly blueshifted emission-line components. Since some of our detections are also low-ionisation AGN, it is quite possible that this disturbance is caused by the radio jets. Overall, our findings point towards a continuation of the low-z trends in the H I detection rate and the incidence of H I in radio AGN up to z ~ 0.4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

Abstract Background Prescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients’ hospital utilization. Methods We used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients’ primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI). Results Associations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies. Conclusions Area-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Raab, Henry↗
NASA NTRS2002

Optical Testing of Diamond Machined, Aspheric Mirrors for Groundbased, Near-IR Astronomy

The Infrared Multi-Object Spectrometer (IRMOS) is a facility-class instrument for the Kitt Peak National Observatory 4 and 2.1 meter telescopes. IRMOS is a near-IR (0.8-2.5 micron) spectrometer and operates at approximately 80 K. The 6061-T651 aluminum bench and mirrors constitute an athermal design. The instrument produces simultaneous spectra at low- to mid-resolving power (R=lambda/delta lambda= 300-3000) of approximately 100 objects in its 2.8 x 2.0 arcmin field. We describe ambient and cryogenic optical testing of the IRMOS mirrors across a broad range in spatial frequency (figure error, mid-frequency error, and microroughness). The mirrors include three rotationally symmetric, off-axis conic sections, one off-axis biconic, and several flat fold mirrors. The symmetric mirrors include convex and concave prolate and oblate ellipsoids. They range in aperture from 94x86 mm to 286x269 mm and in f-number from 0.9 to 2.4. The biconic mirror is concave and has a 94x76 mm aperture, R(sub x)=377 mm, k(sub x)=0.0778, R(sub y)=407 mm, and k(sub y)=0.1265 and is decentered by -2 mm in X and 227 mm in Y. All of the mirrors have an aspect ratio of approximately 6:1. The surface error fabrication tolerances are less than 10 nm RMS microroughness, 'best effort' for mid-frequency error, and less than 63.3 nm RMS figure error. Ambient temperature (approximately 293 K) testing is performed for each of the three surface error regimes, and figure testing is also performed at approximately 80 K. Operation of the ADE Phaseshift MicroXAM white light interferometer (micro-roughness) and the Bauer Model 200 profilometer (mid-frequency error) is described. Both the sag and conic values of the aspheric mirrors make these tests challenging. Figure testing is performed using a Zygo GPI interferometer, custom computer generated holograms (CGH), and optomechanical alignment fiducials. Cryogenic CGH null testing is discussed in detail. We discuss complications such as the change in prescription with temperature and thermal gradients. Correction for the effect of the dewar window is also covered. We discuss the error budget for the optical test and alignment procedure. Data reduction is accomplished using commercial optical design and data analysis software packages. Results from CGH testing at cryogenic temperatures are encouraging thus far.

Chambers, V. John↗
NASA NTRSDate not supplied

Humans to Mars, but How Many? Using Training Requirements Modeling to Inform Crew Size

Missions to Mars will differ from previous human spaceflight missions in that the onboard crew of astronauts will be required to operate in an Earth-independent manner due to the long communication delays. Without a systematic, repeatable process to determine the number and composition of crew necessary to successfully accomplish these missions, NASA increases the risk that crew sizes may be too small to meet primary mission objectives under nominal conditions and, more consequentially, that crewmembers may not have the expertise needed to successfully respond to unforeseen failures without the real-time expertise of the Mission Control Central (MCC) team NASA currently relies upon. The NASA Engineering and Safety Center (NESC) is developing a methodology for assessing the trade space of factors that affect the number of crew for future missions. This methodology includes the consideration of results from three human performance models developed using the Improved Performance Research and Integration Tool (IMPRINT) modeling platform as well as a custom-built model on expertise trained within the crew. The IMPRINT results will be presented in the modeling and simulation sub-tag. Here we present results of a model based on NASA’s crew qualification and responsibility matrix (CQRM), a tool used to identify the crew qualifications for each area of responsibility (operation, system, and payload) for a mission. The model outputs an optimized allocation of training assignments along with a flight-assigned CQRM that can be used to consider the expertise that can be trained within a crew of a given size. We discuss the CQRM model result implications on the trade space for Mars mission crew size.

Mars↗
DOE OSTI2026

Divertor detachment characterization in negative triangularity discharges in DIII-D via 2D edge-plasma transport modeling

Edge fluid modeling of the first divertor-plasma detachment experiments in negative triangularity (NT) discharges in the DIII-D tokamak is presented using the 2D multifluid edge transport code UEDGE, including cross-field particle drifts. Experiments were performed where the lower single-null magnetic equilibrium had a strong NT (δ≈−0.5), that is, where the magnetic X-point is at a larger major radius than the core magnetic axis. Divertor-plasma detachment was induced by increasing the core plasma density in DIII-D via intrinsic gas puffing. Here density scans are performed with UEDGE to reach a detached plasma and to quantitatively recover the experimental rollover of the ion saturation current on the outer divertor target plate. The simulations cover experiments with both signs of the toroidal magnetic field, B T , where the ion magnetic Grad-B drifts are directed into (forward B T ) and out of (reverse B T ) the divertor region. Consistent with experiments with neutral beam power injection, the NT simulations reproduce: 40% higher density is needed to reach detachment onset with forward B T compared with reverse B T , and the absence of deep detachment is found with reverse B T . Similarly, comparison between Ohmic discharges in NT and positive triangularity (PT) shaping confirms that a substantially higher density is needed to achieve detachment in NT than in PT, with NT requiring an line-average density of at least the Greenwald density or higher. Simulation results suggest that higher densities are needed to reach detachment in negative compared to PT because these discharges have a shorter midplane-to-target distance along the total magnetic field B, a shorter outer divertor poloidal leg length (0.06 m vs 0.2 m), and reduced radial transport [near-scrape-off layer (SOL) D ⊥ /χ ⊥ =0.3/0.5 vs D ⊥ /χ ⊥ =1.0/1.0, all in (m 2 /s)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗