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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 NTRS2015

KSC 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT) Report

This report documents analysis results of the Kennedy Space Center updated 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). This test was designed to demonstrate that the new DRWP operates in a similar manner to the previous DRWP for use as a situational awareness asset for mission operations at the Eastern Range to identify rapid changes in the wind environment that weather balloons cannot depict. Data examination and two analyses showed that the updated DRWP meets the specifications in the OAT test plan and performs at least as well as the previous DRWP. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 5,426 wind component reports from 49 concurrent DRWP and balloon profiles presented root mean square (RMS) wind component differences around 2.0 m/s. The DRWP's effective vertical resolution (EVR) was found to be 300 m for both the westerly and southerly wind component, which the best EVR possible given the DRWP's vertical sampling interval. A third analysis quantified the sensitivity to rejecting data that do not have adequate signal by assessing the number of first-guess propagations at each altitude. This report documents the data, quality control procedures, methodology, and results of each analysis. It also shows that analysis of the updated DRWP produced results that were at least as good as the previous DRWP with proper rationale. The report recommends acceptance of the updated DRWP for situational awareness usage as per the OAT's intent.

Profiler↗
DOE OSTI2022

Temporal Study 2021-2022: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected at weekly or bi-weekly intervals at six sites across the Yakima River Basin in Washington, USA. Related sensor data will be published separately and can be used to link sediment respiration rates to biogeochemical processing rates. The data package was originally published in November 2022. It was updated in November 2023 (v2; modified files) and April 2025 (new and modified files). See the change history section in readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), and ions; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol; (8) readme; (9) methods codes; (10) international generic sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected our data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2022 Meeting Notes and Information Request Status

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2023 (FY2023) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during these meetings benefit operating, new, and advanced reactors. Significant safety insights have been and are continuing to be obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional benefits to the operating fleet and new LWR and non-LWR designs. U.S. evaluations of obtained examination information and input regarding future Daiichi examinations are of interest to several organizations within Japan. Since its inception, the U.S. has provided consensus input for high priority time-sequenced examination tasks and supporting research activities. In their Mid-to-Long-term Examination Plan for 1F investigations, TEPCO included all remaining U.S. consensus information requests and additional information requests they identified. TEPCO periodically provides reports on the status of these requests (reflecting D&D priorities, new insights from investigations, and new technologies that become available). Hence, U.S. experts agreed that it was appropriate for TEPCO to track and prioritize these information requests as D&D progresses. U.S. experts will continue to review and comment on the information obtained from examinations and, as needed, provide additional details and relevant background material to support future examinations. As documented in this report, several other items, such as additional details on information requests pertaining to ex-vessel examinations, relevant references from prior research, additional documents to provide insights regarding recent investigation findings, and reviews of recently released documents, were agreed to during the FY2023 meeting.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1977

Computation of spacecraft signal raypath trajectories relative to the sun

A computer program (CTS 41B) used to determine the trajectory of a spacecraft signal raypath was updated to increase its usefulness during solar conjunctions (CTS 41C). The closest point of approach of the raypath to the sun is projected onto the surface and the solar latitude and longitude calculated. A sample computation and plots are given for the 1976 Viking solar conjunction. Eventually it may be possible to predict the communication link performance degradation in the near sun region due to solar activity.

Cannon, R.↗
NASA NTRS2009

Performance of the Extravehicular Mobility Unit (EMU): Airlock Coolant Loop Recovery (A/L CLR) Hardware - Phase II

An EMU water processing kit (Airlock Coolant Loop Recovery A/L CLR) was developed as a corrective action to Extravehicular Mobility Unit (EMU) coolant flow disruptions experienced on the International Space Station (ISS) in May of 2004 and thereafter. Conservative schedules for A/L CLR use and component life were initially developed and implemented based on prior analysis results and analytical modeling. The examination of postflight samples and EMU hardware in November of 2006 indicated that the A/L CLR kits were functioning well and had excess capacity that would allow a relaxation of the initially conservative schedules of use and component life. A relaxed use schedule and list of component lives was implemented thereafter. Since the adoption of the relaxed A/L CLR schedules of use and component lives, several A/L CLR kit components, transport loop water samples and sensitive EMU transport loop components have been examined to gage the impact of the relaxed requirements. The intent of this paper is to summarize the findings of that evaluation, and to outline updated schedules for A/L CLR use and component life.

Steele, John↗
NASA NTRSDate not supplied

NASA’s Orbital Debris Optical Program: ES-MCAT Nearing Full Operational Capability (FOC)

The NASA JAO/ES-MCAT (Eugene Stansbery Meter Class Autonomous Telescope) Facility is nearing Full Operational Capability, or FOC. ES-MCAT is now fully capable of autonomously running all observations, including: (a) monitoring weather and closing when conditions are not safe, as well as halting observations when conditions are not suitable (e.g. too cloudy) for operations, (b) start-up/shut-down nightly tasking, (c) collecting calibration data and survey or TLE-tracked data, and (d) processing all collected data, including on-chip photometry and astrometry calibrations using the GAIA star catalogue. The processed data are then further analyzed at NASA Johnson Space Center to correlate detections with known objects in the Space Surveillance Network (SSN) catalogue. MCAT can collect data of specific objects with known orbits or can search for objects with orbits similar to those of spacecraft or rocket bodies that have recently broken up. However, the primary goal for ES-MCAT is to survey the geosynchronous (GEO) belt to provide a statistical sample of the GEO debris environment for both engineering models for spacecraft designers and long-term environment evolutionary purposes. The approach for sweeping the sky to statistically survey GEO has been investigated and updated from past surveys taken by NASA and will be reported, herein referred to as the Candy Cane method. ES-MCAT’s optical performance and the limiting magnitude for the full optical system will be discussed. An analysis used to determine which filter to use for GEO surveys (SDSS r′) includes combining the reflectivity of the primary and secondary mirrors, transmission of the field corrector and CCD window, and the quantum efficiency of the CCD detector, resulting in throughput of the full optical path. This throughput is then combined with the expected typical transparency of the atmosphere at ES-MCAT’s altitude/location for the Sloan Digital Sky Survey (SDSS) g′r′i′z′ and Johnson/Kron-Cousins BVRI filters to yield expected relative throughput.

S. M. Lederer↗
DOE OSTI2024

Multi-Fidelity Modeling and Control for Building Temperature Control

The ability to control energy loads such as a building's heating, ventilation, and air conditioning (HVAC) system can help facilitate increased penetration of variable renewable energy sources into the electric grid. To be able to control these HVAC systems more effectively, detailed simulations of the corresponding building physics is becoming increasingly important. These detailed simulations can be complex, nonlinear, and can require immense computational power when used in an advanced control method such as model predictive control (MPC), prompting the need to explore less computationally intensive strategies. In this work, a multi-fidelity approach is proposed to combine samples from a complex, high-fidelity model with a simple, low-fidelity model within the MPC control loop. More specifically, the parameters of a reduced-order, linear building model are periodically updated with knowledge from its high-fidelity counterpart - an EnergyPlus model - in an online fashion using a Gaussian Process surrogate model. Hence, highly accurate predictions of current and future conditions in a building are maintained with a substantially reduced computational burden compared to using the high-fidelity models alone. In other words, this linear parameter varying model preserves the low computational requirements of a low-order linear model while accurately modeling a building's dynamics. This allows a building controller to take highly informed actions without requiring a large computational budget.

building modeling↗
NASA NTRS2009

Comet 81p/Wild 2: The Updated Stardust Coma Dust Fluence Measurement for Smaller (Sub 10-Micrometre) Particles

Micrometre and smaller scale dust within cometary comae can be observed by telescopic remote sensing spectroscopy [1] and the particle size and abundance can be measured by in situ spacecraft impact detectors [2]. Initial interpretation of the samples returned from comet 81P/Wild 2 by the Stardust spacecraft [3] appears to show that very fine dust contributes not only a small fraction of the solid mass, but is also relatively sparse [4], with a low negative power function describing grain size distribution, contrasting with an apparent abundance indicated by the on-board Dust Flux Monitor Instrument (DFMI) [5] operational during the encounter. For particles above 10 m diameter there is good correspondence between results from the DFMI and the particle size inferred from experimental calibration [6] of measured aerogel track and aluminium foil crater dimensions (as seen in Figure 4 of [4]). However, divergence between data-sets becomes apparent at smaller sizes, especially submicrometre, where the returned sample data are based upon location and measurement of tiny craters found by electron microscopy of Al foils. Here effects of detection efficiency tail-off at each search magnification can be seen in the down-scale flattening of each scale component, but are reliably compensated by sensible extrapolation between segments. There is also no evidence of malfunction in the operation of DFMI during passage through the coma (S. Green, personal comm.), so can the two data sets be reconciled?

Price, M. C.↗
DOE OSTI2023

Spatial Study 2022: Surface Water Samples, Cotton Strip Degradation, and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides data and photos generated from sample collection during the same one-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. The contents include surface water geochemistry data; river substrate grain size photos; stream depth data; manual chamber open channel respiration data; and field metadata (including qualitative information on instream and river corridor characteristics). Grain size photos can be used to improve estimates of channel substrate D50 data. The dataset also includes tensile strength and photos from cotton strip field degradation experiments; five-week sensor time series temperature, dissolved oxygen, pressure, pH, specific conductance, chlorophyll A, and turbidity data; plots of the sensor data; and R scripts used to generate the plots. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. SSS data published in the CM data package were not included in this data package. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Additionally, sensor data from a similar 2021 spatial study can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052 and 2021 sample data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1898914. The 2021 spatial study had some sites in common with this 2022 spatial study. This dataset is comprised of three photo folders and one main data folder with six subfolders. The photo folders contain photographs and videos of cotton strip retrieval and sediment quadrats. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) total suspended solids (TSS) data and cotton strip tensile strength data and averages; (5) field protocol; (6) readme; (7) methods codes; (8) international generic sample number (IGSN) mapping file; (9) sensor installation methods summary; (10) stream depth and averages; and (11) Ultrameter data and averages. The Sonar subfolder consists of Sonar time-series depth data and a processing script. The BarotrollAtm, DepthHOBO, MantaRiver, miniDOT, and miniDOTManualChamber subfolders contain time-series data, plots, and summary files. All files are .csv, .pdf, .txt, .R, .Rmd, .jpg, .jpeg, .AVI, .mp4, or .mov. The data package was originally published in April 2023. It was updated in August 2023 (v2; modified files) and September 2024 (v3; modified files). See the change history section in the readme for details. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CIRCLEZ : Reliable photometric redshifts for active galactic nuclei computed solely using photometry from Legacy Survey Imaging for DESI

Photometric redshifts for galaxies hosting an accreting supermassive black hole in their center, known as active galactic nuclei (AGNs), are notoriously challenging. At present, they are most optimally computed via spectral energy distribution (SED) fittings, assuming that deep photometry for many wavelengths is available. However, for AGNs detected from all-sky surveys, the photometry is limited and provided by a range of instruments and studies. This makes the task of homogenizing the data challenging, presenting a dramatic drawback for the millions of AGNs that wide surveys such as SRG/eROSITA are poised to detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGNs using only one dataset that covers a large area: the tenth data release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures over the footprint of the eROSITA-DE survey, which avoids issues related to the cross-calibration of surveys. We present the results from CIRCLEZ, a machine-learning algorithm based on a fully connected neural network. CIRCLEZ is built on a training sample of 14 000 X-ray-detected AGNs and utilizes multi-aperture photometry, mapping the light distribution of the sources. The accuracy (σNMAD) and the fraction of outliers (η) reached in a test sample of 2913 AGNs are equal to 0.067 and 11.6%, respectively. The results are comparable to (or even better than) what was previously obtained for the same field, but with much less effort in this instance. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching a comparable accuracy as in eFEDS when limiting the magnitude of the counterparts to the depth of LS10. The method can be applied to fainter samples of AGNs using deeper optical data from future surveys (for example, LSST, Euclid), granting LS10-like information on the light distribution beyond the morphological type. Along with this paper, we have released an updated version of the photometric redshifts (including errors and probability distribution functions) for eROSITA/eFEDS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Determination of the number of ψ(3686) events taken at BESIII*

Abstract The number ofψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×10 6 by counting inclusiveψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers ofψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×10 6 and (345.4±2.6)×10 6 , respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number ofψ(3686) events in the three data samples is (2712.4±14.3)×10 6 .

Physics↗
DOE OSTI2023

The profiles of bars in spiral galaxies

ABSTRACT We present an analysis of major-axis surface-brightness profiles of bars in a volume-limited sample of 182 barred spiral galaxies, using Spitzer 3.6 $\mu$m images. Unlike most previous studies, we use the entire bar profile, and we classify profiles into four categories. These are ‘Peak+Shoulders’ (P+Sh) – updating the classic ‘flat bar’ profile – and three subtypes of the classic ‘exponential’ profile: (true) Exponential, ‘Two-Slope’ (shallow inner slope + steeper outer slope), and ‘Flat-Top’ (constant inner region, steep outer slope). P+Sh profiles are preferentially found in galaxies with high stellar masses, early Hubble types, red colours, and low gas fractions; the most significant factor is stellar mass, and previous correlations with Hubble type can be explained by the tendency of higher-mass galaxies to have earlier Hubble types. The most common type of non-P+Sh profile is Exponential, followed by Flat-Top profiles; all non-P+Sh profiles appear to have similar distributions of stellar mass, Hubble type, colour, and gas fraction. We also morphologically classify the bars of an inclined subsample into those with and without boxy/peanut-shaped (B/P) bulges; as previously reported, the presence of a B/P bulge is very strong function of stellar mass. Essentially all bars with B/P bulges have P+Sh profiles; we associate the profile shoulders with the outer, vertically thin part of the bar. We find a small number of P+Sh profiles in bars without clear B/P bulges, which may indicate that P+Sh formation precedes the formation of B/P bulges.

Astronomy & Astrophysics↗
DOE OSTI2022

Update on NNL TSL Validation Efforts [Slides]

A new sub-thermal neutron transmission capability at RPI LINAC has been used to validate Be (metal). NNL transmission measurements validated NCSU Be and Be+Sd TSLs for ENDF/B-VIII.1 and showed improvements WRT ENDF/B-VII.1 and ENDF/B-VIII.0. Amplitude differences highlighted the importance of sample characterization. Additional measurement is in progress for CY2022. PNDA is being developed as an alternative to critical experiment validation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1981

High speed cylindrical roller bearing analysis. SKF computer program CYBEAN. Volume 2: User's manual

CYBEAN (CYlindrical BEaring ANalysis) was created to detail radially loaded, aligned and misaligned cylindrical roller bearing performance under a variety of operating conditions. Emphasis was placed on detailing the effects of high speed, preload and system thermal coupling. Roller tilt, skew, radial, circumferential and axial displacement as well as flange contact were considered. Variable housing and flexible out-of-round outer ring geometries, and both steady state and time transient temperature calculations were enabled. The complete range of elastohydrodynamic contact considerations, employing full and partial film conditions were treated in the computation of raceway and flange contacts. The practical and correct implementation of CYBEAN is discussed. The capability to execute the program at four different levels of complexity was included. In addition, the program was updated to properly direct roller-to-raceway contact load vectors automatically in those cases where roller or ring profiles have small radii of curvature. Input and output architectures containing guidelines for use and two sample executions are detailed.

Dyba, G. J.↗
NASA NTRS2001

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour: Output from Two Sample Cases - Volume 2

A closed-loop optimal neural-network controller technique was developed to optimize rotorcraft aeromechanical behaviour. This technique utilities a neural-network scheme to provide a general non-linear model of the rotorcraft. A modem constrained optimisation method is used to determine and update the constants in the neural-network plant model as well as to determine the optimal control vector. Current data is read, weighted, and added to a sliding data window. When the specified maximum number of data sets allowed in the data window is exceeded, the oldest data set is and the remaining data sets are re-weighted. This procedure provides at least four additional degrees-of-freedom in addition to the size and geometry of the neural-network itself with which to optimize the overall operation of the controller. These additional degrees-of-freedom are: 1. the maximum length of the sliding data window, 2. the frequency of neural-network updates, 3. the weighting of the individual data sets within the sliding window, and 4. the maximum number of optimisation iterations used for the neural-network updates.

Leyland, Jane Anne↗
NASA NTRS2010

Cognitive Assessment During Long-Duration Space Flight

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is a computer-based, self-administered battery of five cognitive assessment tests developed for medical operations at NASA's Johnson Space Center in Houston, Texas. WinSCAT is a medical requirement for U.S. long-duration astronauts and has been implemented with U.S. astronauts from one NASA/Mir mission (NASA-7 mission) and all expeditions to date on the International Space Station (ISS). Its purpose is to provide ISS crew surgeons with an objective clinical tool after an unexpected traumatic event, a medical condition, or the cumulative effects of space flight that could negatively affect an astronaut's cognitive status and threaten mission success. WinSCAT was recently updated to add network capability to support a 6-person crew on the station support computers. Additionally, WinSCAT Version 2.0.28 has increased difficulty of items in Mathematics, increased number of items in Match-to-Sample, incorporates a moving rather than a fixed baseline, and implements stricter interpretation rules. ISS performance data were assessed to compare initial to modified interpretation rules for detecting potential changes in cognitive functioning during space flight. WinSCAT tests are routinely taken monthly during an ISS mission. Performance data from these ISS missions do not indicate significant cognitive decrements due to microgravity/space flight alone but have shown decrements. Applying the newly derived rules to ISS data results in a number of off-nominal performances at various times during and after flight.. Correlation to actual events is needed, but possible explanations for off-nominal performances could include actual physical factors such as toxic exposure, medication effects, or fatigue; emotional factors including stress from the mission or life events; or failure to exert adequate effort on the tests.

Seaton, Kimberly↗
NASA NTRSDate not supplied

The Search for Extant Life on Mars: A Human Exploration Objective

A search for evidence of extant life on Mars should be conducted prior to and as part of human exploration missions. Potentially habitable environments for modern life occur on Mars. Despite a vigorous campaign of exploration of the surface over the last 3 decades, no mission has attempted to search for signatures of extant life since the Viking landers in 1976. Finding an example of extant life beyond Earth would be one of the greatest scientific discoveries of all time. This is especially important because (once discovered) the biochemistry and metabolism of the life form can be studied. Earth and Mars exchange materials over geologic time because impacts eject rock and crustal materials into space that are eventually deposited on other planets and moons [1]. Therefore, Earth and Mars could share life with a common origin and similar biochemistry; if this is the case, life on Mars likely experienced billions of years of evolution in isolation from Earth. Alternatively, Mars may host a distinct genesis of life which could be evident from its different biochemistry. Either discovery would change our understanding of life in the solar system and beyond. The Mars 2020/Perseverance sample collection mission is not optimized for finding extant life because the site for sample collection, Jezero Crater, was chosen for its ancient habitability and likelihood to host fossil evidence of life. Furthermore, the samples collected will not be returned for at least a decade. Within that period, technology development for human exploration will likely be underway and it is possible that humans will land on Mars without an updated knowledge of extant life on Mars, which may pose a risk both to those mission crews and to Earth when they return. Thus, it is important to perform a search for extant life on Mars prior to humans landing at a site where life may persist. Salts and shallow ground ice are particularly important environments to evaluate for extant life prior to human missions because they may be encountered and interacted with by human crews.

C.R. Stoker↗
DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

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