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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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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Progress of Tripwire: Multi-modal Distributed Sensing for Repository Verification

This project is developing and demonstrating a multi-modal sensor system, TRIPWIRE, for containment verification in inaccessible radiological and nuclear waste repositories. The TRIPWIRE system will continuously monitor ionizing radiation and electromagnetic fields in the vicinity of emplaced nuclear materials buried in a repository, reporting on disturbances with a real-time alarm control station. The system will use long-length scintillating fiber bundles (SFBs) to perform area radiation monitoring; these will be coupled to kilometer-scale multimodal optical communication fibers – all light sensors and electronic components used with this system will be located above ground. Electromagnetic fields, and changes in local dielectric conditions caused by intrusion and soil movement, will be monitored using commercial grade, ported "leaky" coaxial cables (PCCs), with control electronics also located above ground. This paper documents the results of the simulations and modeling efforts that have helped identify the optimal placement of the SFBs. Additionally, the paper includes the current progress on the multi-modal SFB-PCC system, including the fabrication of long-length (>3-m) fibers and their coupling to optical fibers.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2021

Effects of multiple simultaneous faults on characteristic fault detection features of a heat pump in cooling mode

Faults in air-cooled vapor compression air-conditioning systems are known to reduce performance, including efficiency, capacity, and lifespan. Their effects have been studied, and fault detection and diagnostic (FDD) methods have been developed as tools for field technicians to install or repair systems, or for monitoring to alert operators to the fault’s presence. Most of this work has focused on faults that occur singly. It is likely that in some systems, multiple faults occur simultaneously, but it is uncertain what effects this may have on diagnostics. Here, this paper describes a laboratory study of a split system air source heat pump in which combinations of two, three, and four simultaneous faults occur. The study includes all combinations of: improper evaporator airflow; overcharge or undercharge of refrigerant; liquid line restrictions; and non-condensable gas in the refrigerant, each at multiple fault intensities. Fault features – those characteristics that can be determined from measurements, for use in diagnostics – are analyzed, and the key fault features are presented. A robust existing method for determining refrigerant charge, the virtual refrigerant charge sensor (VRC) is tested using the multiple fault data, in order to understand how its performance is impacted by the combined faults. The VRC performs well, typically able to correctly determine whether a system is undercharged or overcharged, but the magnitude estimates are impacted. The results suggest that simple subcooling-based methods of charging a system are likely to provide unsatisfactory results when other faults are present.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A systematic study and framework of fringe projection profilometry with improved measurement performance for in-situ LPBF process monitoring

Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. Here, in this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM.

42 ENGINEERING↗
DOE OSTI2021

Polyethylene Glycol Crowder’s Effect on Enzyme Aggregation, Thermal Stability, and Residual Catalytic Activity

Protein stability and performance in various natural and artificial systems incorporating many other macromolecules for therapeutic, diagnostic, sensor, and biotechnological applications attract increasing interest with the expansion of these technologies. Here we address the catalytic activity of lysozyme protein (LYZ) in the presence of a polyethylene glycol (PEG) crowder in a broad range of concentrations and temperatures in aqueous solutions of two different molecular mass PEG samples (Mw = 3350 and 10000 g/mol). The phase behavior of PEG–protein solutions is examined by using dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS), while the enzyme denaturing is monitored by using an activity assay (AS) and circular dichroism (CD) spectroscopy. Molecular dynamic (MD) simulations are used to illustrate the effect of PEG concentration on protein stability at high temperatures. The results demonstrate that LYZ residual activity after 1 h incubation at 80 °C is improved from 15% up to 55% with the addition of PEG. The improvement is attributed to two underlying mechanisms. (i) Primarily, the stabilizing effect is due to the suppression of the enzyme aggregation because of the stronger PEG–protein interactions caused by the increased hydrophobicity of PEG and lysozyme at elevated temperatures. (ii) The MD simulations showed that the addition of PEG to some degree stabilizes the secondary structures of the enzyme by delaying unfolding at elevated temperatures. The more pronounced effect is observed with an increase in PEG concentration. This trend is consistent with CD and AS experimental results, where the thermal stability is strengthened with increasing of PEG concentration and molecular mass. Overall, the results show that the highest stabilizing effect is approached at the critical overlap concentration of PEG.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Spectral Data Fusion From Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) Analyzers for Improved Detection of Cerium in a Simulated Dispersal Accident

Here, this work implements a mid-level data fusion methodology on spectral data from handheld X-ray fluorescence and laser-induced breakdown spectroscopy analyzers to quantify plutonium surrogate (CeO 2 ) contamination in soil samples for the first time. Spectral data from each analyzer were used independently to train supervised machine learning regressions to predict Ce concentration. Fused features from both data sets were then used to train the same models, comparing prediction performance by evaluating model precision and sensitivity. Fusing principal component scores from the two sensors yielded an order of magnitude improvement in precision and sensitivity of predictions made with an artificial neural network, compared to predictions made by models trained on independent sensor data. As a result, a boosted ensemble trained on the fused spectral features yielded an ideal predictor with root-mean-squared error on the order of 10 –6 and calculated limit of detection order 10 –5 wt %.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Mutual Inductance Level Sensor for Use in Liquid Metals

Electromagnetic instrumentation capable of measuring the level of liquid metal has been developed at Argonne National Laboratory’s (ANL) Mechanisms Engineering Test Loop (METL). The mutual inductance level sensor (MILS) utilizes the electromagnetic coupling between two coil conductors and a surrounding liquid metal to determine the level of the liquid metal. Mineral insulated cables wrapped on a stainless steel core provide a durable sensor construction. The use of a sealed stainless steel thimble isolates the sensor from the high-temperature liquid metal, allowing for easy sensor maintenance. Modern digital electronics allow for reliable and accurate operation of the sensor. Two sensor variations have been designed and fabricated, and the first variation has seen extensive testing in a non-sodium testing stand as well as in the high-temperature sodium environment of METL. Electromagnetic finite-element analysis studies have been performed using the COMSOL Magnetic Fields Solver. Regular operation of the MILS will commence following in-situ calibration of the sensors in the METL environment.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Journey Over Destination: Differentiable Sensor Placement Enhances Generalization [Poster]

The challenge of reconstructing spatial fields that change over time from limited sensor data has been a focal point for many research studies. Various machine learning methods have been used in attempts to address this complex issue, including convolutional neural networks. All of the proposed methods share a common requirement that the user needs to manually determine the sensor positions. This requirement remains a limiting factor in the ongoing quest for efficient learning and accurate field reconstruction. This study aims to present a method that enables a model to optimize sensor positions via backpropagation, thereby facilitating the model’s exploration of the spatial domain and enhancing sensor positioning effectively. Indexing naturally incorporates discrete decisions. This operation is nondifferentiable which is a requirement for the application of gradient-based optimization methods. We showcased its effectiveness by training an attention-based neural network, which achieved top-tier performance on two separate datasets. To our knowledge, this represents the first fully end-to-end differentiable workflow for enhancing sensor placement within a neural network model.

58 GEOSCIENCES↗
DOE OSTI2024

Development of Readily Available & Robust High Heat Flux Gardon Gauges

Concentrated solar power (CSP) technologies deliver concentrated solar energy as a heat source to industrial processes, power generation cycles, and chemical cycles. CSP systems require accurate and reliable high flux measurements, and next generation CSP systems will require flux measurement up to 1000 W/cm2. Existing flux measurement devices do not comprehensively meet the flux rating, cycle life, cost, and lead-time needs of stakeholders, necessitating the development of an improved flux sensor. In this study, Sandia National Laboratories (SNL) partnered with Hukseflux Thermal Sensors to develop a low-cost, short lead-time, and robust flux sensor rated to 250 W/cm2. Three prototype circular foil gauge designs were assessed for performance at the National Solar Thermal Test Facility (NSTTF) at SNL. Each gauge design measured flux up to 250 W/cm2 with <5% measurement error. Following baseline error quantification, gauges were exposed to flux above 500 W/cm2 to assess gauge failure mechanisms. Gauges physically survived >500 W/cm2 flux exposure, but measurement error was found to increase after foil coatings reached 400 °C. The results of this study suggest that coating optical properties change at excessive temperatures and that foil coating temperature, rather than heat flux level, dictates the acceptable gauge measurement range.

McLaughlin, Luke (ORCID:0000000303711310)↗
DOE OSTI2023

A Comprehensive Analysis of Real-World Accelerometer Data Quality in a Global Smartphone-based Seismic Network

The proliferation of low-cost sensors in smartphones has facilitated numerous applications; however, large-scale deployments often encounter performance issues. Sensing heterogeneity, which refers to varying data quality due to factors such as device differences and user behaviors, presents a significant challenge. In this research, we perform an extensive analysis of 3-axis accelerometer data from the MyShake system, a global seismic network utilizing smartphones. We systematically evaluate the quality of approximately 22 million 3-axis acceleration waveforms from over 81 thousand smartphone devices worldwide, using metrics that represent sampling rate and noise level. We explore a broad range of factors influencing accelerometer data quality, including smartphone and accelerometer manufacturers, phone specifications (release year, RAM, battery), geolocation, and time. Our findings indicate that multiple factors affect data quality, with accelerometer model and smartphone specifications being the most critical. In addition, we examine the influence of data quality on earthquake parameter estimation and show that removing low-quality accelerometer data enhances the accuracy of earthquake magnitude estimation.

58 GEOSCIENCES↗
DOE OSTI2020

Machine Vision-based Robot Manipulators for Nuclear Applications - 20370

Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Hunting Sub-GeV Dark Matter with Diamonds and Magnetic Microcalorimeters Principle

This project is to study feasibility of a new concept for the sub-GeV dark matter (DM) detection using diamond crystals and magnetic microcalorimeters (MMCs). Diamond crystals are made of low mass carbon constituent that maximize kinetic energy of nuclear recoils from sub-GeV DM scattering due to their relatively similar masses. MMC is employed as a sensitive phonon sensor to measure athermal phonons that are produced by DM scattering in diamond crystals with 100 ns timing resolution and ~10 eV energy resolution. MMC’s fast timing resolution allows high precision phonon pulse shape analysis to separate out unwanted background or noise signals in the low energy region at E < 1 keV. Especially, the low energy excess (LEE) problems have been reported in the dark matter detection community and the proposed diamond-MMC detector might be able to provide important information to understand the origins of LEE signals in DM detectors. In this project a diamond-MMC detector has been built for proof-of-concept experiments and athermal phonon collection efficiencies have been investigated for single crystal and poly-crystal chemical-vapour-diamonds (SC and PC CVDs) as well as reference sapphire crystals are tested in the same geometries to quatify athermal phonon propagation and their collection to the MMC phonon sensors. Athermal phonon collection efficiencies and their lifetime in the diamond and sapphire crystals are successfully measured in the same geometry and experimental setup for comparison. SC CVD crystals exhibit poorer performance than the sapphire reference crystals in athermal phonon collection, while the PC CVD crystal exhibit better result than the sapphire. PC CVD with MMC phonon sensors would be feasible for sub GeV DM detection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Aerosol-Jet Printed Sensors for Environmental, Safety, and Health Monitoring: A Review

An emergent direct-write approach, aerosol-jet printing (AJP), is gaining attention for the deployment of rapid and affordable microadditively manufactured energy-efficient sensors and printed electronics. AJP enables a broad range of ink viscosities (0.001–1 Pa s) for printing diverse materials ranging from ceramics and metals to polymers and biological matter. Reproducible, high-spatial-resolution features (≈10 µm), and wide standoff distances (1–11 mm) between the nozzle and the substrate facilitate conformal printing of complex geometrical designs on nonplanar—e.g., stepped or curved—surfaces. Here this paper aims to provide a comprehensive overview of state-of-the-art AJP-based sensors (e.g., strain and temperature gauges, biosensors, photosensors, humidity and surface acoustic wave sensors, dielectric elastomer actuators, and motion, smoke, and hazardous gas detectors) and to discuss prospective applications. The drive toward cost-effective devices that are smaller, lighter, and better-performing remains a frontier challenge in the field of printed electronics. Consequently, as AJP becomes increasingly utilized in the high-volume manufacturing of miniaturized active and passive sensors, it opens a pathway for facile large-scale fabrication of devices for a wide range of consumer and industrial applications, including transportation, agriculture, infrastructure, aerospace, national defense, and healthcare.

3-dimensional↗
DOE OSTI2025

Structural response reconstruction using a system-equivalent singular vector basis

Here, this paper develops a novel method for reconstructing the full-field response of structural dynamic systems using sparse measurements. The singular value decomposition is applied to a frequency response matrix relating the structural response to physical loads, base motion, or modal loads. The left singular vectors form a non-physical reduced basis that can be used for response reconstruction with far fewer sensors than existing methods. The contributions of the singular vectors to measured response are termed singular-vector loads (SVLs) and are used in a regularized Bayesian framework to generate full-field response estimates and confidence intervals. The reconstruction framework is applicable to the estimation of single data records and power spectral densities from multiple records. Reconstruction is successfully performed in configurations where the number of SVLs to identify is less than, equal to, and greater than the number of sensors used for reconstruction. In a simulation featuring a seismically excited shear structure, SVL reconstruction significantly outperforms modal FRF-based reconstruction and successfully estimates full-field responses with as few as two uniaxial accelerometers. SVL reconstruction is further verified in a simulation featuring an acoustically excited cylinder. Finally, response reconstruction and uncertainty quantification are performed on an experimental structure with three shaker inputs and 27 triaxial accelerometer outputs.

42 ENGINEERING↗
DOE OSTI2024

Design and evaluation of a low-cost sensor node for near-background methane measurement

Abstract. We developed a low-cost methane sensing node incorporating two metal oxide (MOx) sensors (Figaro Engineering TGS2611-E00 and TGS2600), humidity and temperature sensing, data storage, and telemetry. We deployed the prototype sensor alongside a reference methane analyzer at two sites: one outdoors and one indoors. We collected data at each site for several months across a range of environmental conditions (particularly temperature and humidity) and methane levels. We explored calibration models to investigate the performance of our system and its suitability for methane background monitoring and enhancement detection, first selecting a linear regression to fit a sensor baseline response and then fitting methane response by the sensor deviation from baseline. We achieved moderate accuracy in a 2 to 10 ppm methane range compared to data from the reference analyzer (RMSE < 0.6 ppm), but we found that the sensor response varied over time, possibly as a result of changes in non-targeted gas concentrations. We suggest that this cross sensitivity may be responsible for mixed results in previous studies. We discuss the implications of our results for the use of these and similar inexpensive MOx sensors for methane monitoring in the 2 to 10 ppm range.

Furuta, Daniel↗
DOE OSTI2020

Small-Scale Drying: FY2020 Interim Report

This report documents the interim experimental status of small-scale drying tests currently being performed at Pacific Northwest National Laboratory. These small-scale drying tests are to develop the technical bases for sensors, techniques, and approaches that will be used to address the challenges faced when determining moisture content from gas samples taken at the North Anna Nuclear Generating Station for the High Burnup Demonstration Project. Specifically, the purpose of these tests is to support Sandia National Laboratories gas sample methods and analyses through a series of small-scale experiments. Key focus areas include performing tests to: • Correlate sample bottle measurements to in-cask conditions • Estimate the amount of trapped and absorbed water on cask features and surfaces that can contribute to water vapor • Assess the accuracy of the hygrometer used in the measurements under similar conditions • Identify additional methods for measuring humidity in casks easily and accurately using lessons-learned from Sandia National Laboratories, including direct gravimetric and isotopic tracer techniques. To address these topics this report outlines a series of five tests and any data collected to date that were planned for FY 2020 that include 1) humidity measurement method development, 2) gas bottle sampling tests, 3) surface drying tests on cladding, 4) small-scale drying of cladding, and 5) small-scale drying of guide-tube/dashpots. This interim report documents the experimental background, design and progress of these small-scale drying tests. Further data gathered will be summarized in the FY 2021 report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Characterization of Soil and Rock Magnetic Properties along Multiple Hillslope Transects at Teller Road Site, Seward Peninsula, Alaska, 2018 and 2023

The magnetometer data was collected in multiple directions across the watershed hillslope at the NGEE Arctic Teller Road site at mile marker 27 (TL_MM27) on the Seward Peninsula, Alaska over multiple years in March 2018 and April 2023. The magnetic data were collected using a Geometrics Inc. G-858 gradiometer and G-857 base station in 2018 and the G-864 gradiometer and G857 base station in 2023. The data was collected (in all instances) by towing the gradiometer behind a snow machine around the watershed with the two sensors in a vertical profile with constant spacing during the continuous survey in that specific year. Magnetic total field measurements were collected by gradiometer and base station, and the data processing was performed in Geometrics MagMap2000 software. The processing steps were limited to removal of data spikes (despiking), reading dropouts, and correction/removal of bad GPS points. All offsets between sensors and GPS are stated within the data files and metadata, alongwith the processed and raw data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).In this data submission there are two sets of raw magnetic data (.bin and .stn for 2018 and base for 2023; raw rover mag for 2023 is in .csv) inside two .zip files that identify the year the mag data was collected. The data are proprietary format to Geometrics and can be opened and processed with MagMap2000 which can be downloaded for free at Geometrics website. There are also two processed data files *.csv for each year and two metadata files *.csv.

54 ENVIRONMENTAL SCIENCES↗