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DOE OSTI2022

Hawaii Wave Surge Energy Converter (HAWSEC) OSU O.H. Hinsdale Basin

The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

iButton snow-ground interface temperature measurements in Los Alamos, New Mexico from 2023-2024

Snow/ground interface temperature measurements were collected at two sites in Los Alamos, New Mexico. Data were collected from November 29, 2023 to April 8, 2024 using iButton Link DS1921G-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g). These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 3 hours from a total of 19 iButtons. iButtons were placed in pairs, with one iButton placed at the ground surface and another buried 1 - 5 cm below the ground surface. One buried iButton did not successfully collect data, and therefore was excluded from this dataset. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Specifically, this dataset was used as a validation source for a novel machine learning approach to estimating snow depth (see related publication). Sensors were placed in areas with bare ground or minimal grass coverage, located away from any large vegetation. At Site A (TA51), manual snow depths were collected as validation data. These measurements were taken next to iButtons periodically throughout the winter, and notes on other precipitation types were also recorded. At Site B (TA6 Meteorological Station), a nearby sensor collected snow depths throughout the winter. This dataset contains one *.csv file of snow/ground interface temperatures at two sites, one *.csv file of manually collected snow depths, and one *.kml file of sensor locations. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) 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).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Increased range and contrast in fog with circularly polarized imaging

Fogs, low lying clouds, and other highly scattering environments pose a challenge for many commercial and national security sensing systems. Current autonomous systems rely on optical sensors for navigation whose performance is degraded by highly scattering environments. In our previous simulation work, we have shown that polarized light can penetrate through a scattering environment such as fog. We have demonstrated that circularly polarized light maintains its initial polarization state better than linearly polarized light, even through large numbers of scattering events and thus ranges. This has recently been experimentally verified by other researchers. In this work, we present the design, construction, and testing of active polarization imagers at short-wave infrared and visible wavelengths. We explore multiple polarimetric configurations for the imagers, focusing on linear and circular polarization states. The polarized imagers were tested at the Sandia National Laboratories Fog Chamber under realistic fog conditions. Here, we show that active circular polarization imagers can increase range and contrast in fog better than linear polarization imagers. We show that when imaging typical road sign and safety retro-reflective films, circularly polarized imaging has enhanced contrast throughout most fog densities/ranges compared to linearly polarized imaging and can penetrate over 15 to 25 m into the fog beyond the range limit of linearly polarized imaging, with a strong dependence on the interaction of the polarization state with the target materials.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Tardigrade (NA-22 Quarterly Report)

Tardigrade is an effort to create tunable thermal expansion materials for use in a ruggedized lens housing. This requires new computational algorithms to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. The project is 24 months into the 36-month plan. We are continuing effort on 3 main technical thrusts: material design algorithm development (transitioning into full 3D design), multi-material additive manufacturing process exploration, and sensor/optics design and engineering. In the last quarter, we have focused on developing the code for 3D Topology Optimization, building data sets for 2D autoencoder training, and finishing lens housing engineering for the microbolometer based test sensor. We are exploring 2 potential multi-material AM technologies, a polymer-based technique in development at LLNL and a metal SLS system produced by Aconity, called the AeroSint deposition head.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Tardigrade (Quarterly Report Q1 FY2022)

Tardigrade is an effort to create tunable thermal expansion materials for use in a ruggedized lens housing. This requires new computational algorithms to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. The project is 27 months into the 36-month plan. We are continuing effort on 3 main technical thrusts: material design algorithm development (transitioning into full 3D design), multi-material additive manufacturing process exploration, and sensor/optics design and engineering. In the last quarter, we have focused on developing the code for 3D Topology Optimization, building data sets for 2D autoencoder training, and finishing lens housing engineering for the microbolometer based test sensor. We are exploring 2 potential multi-material AM technologies, a polymer-based technique in development at LLNL and a metal SLS system produced by Aconity, called the AeroSint deposition head.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Fault isolation and fault-tolerant control for Takagi-Sugeno fuzzy time-varying delay stochastic distribution systems

A fault isolation, estimation, and fault-tolerant control (FTC) scheme for nonlinear time-varying delay stochastic distribution control systems was presented in this paper. The Takagi-Sugeno fuzzy model was adopted to approach the nonlinear dynamics of time-varying delay systems. According to the output equivalence principle and Laplace transformation, an augmented state vector was given to solve the time-varying delay problem. When multiple actuator faults and interference occur simultaneously, fault detection, isolation and fault estimation was designed to obtained the fault information. To decouple faults and obtain the value and location information of the fault, the system was separated into two parts through the designed multiple conversion matrices, in which one subsystem was only affected by one actuator fault. This has simplified the design of fault isolation and estimation. A adaptive observer for fault estimation was given. Then, fault information such as the time, location, and size was determined. The observer gain matrices were calculated using linear matrix inequality (LMI). When a fault was detected and diagnosed, a FTC algorithm was devised using the proportional-integral control scheme to compensate the fault as much as possible. It has been shown that even if multiple faults actuator occurred simultaneously, the FTC controller still ensured the output probability density function of the system traced the desired probability density function when a fault occurred. Finally, the expected results were obtained through the simulation example, which confirmed the effectiveness of the method.

42 ENGINEERING↗

DOE OSTI2020

Machine learning control of an elliptically bent hard x-ray mirror

This article showcases the high-resolution control of an elliptically bent hard X-ray mirror optics at the Advanced Photon Source. The mirror uses a compact laminar flexure bending mechanism to achieve elliptical shapes covering a large range of focal distances. An array of capacitive sensors are used as a surface profiler for in-situ monitoring of the mirror shape. Machine learning and control techniques were used to change the mirror shape and focus the incident X-ray at predefined focal planes. The mirror surface shape error can be controlled to be within 40 nm rms with high repeatability. This technique gives the capability to focus incident X-ray beam within a range of focal distances corresponding to shape deformation range of a mirror optics. This work would be beneficial for controlling similar adaptive optics for multiple adaptive optics systems.

adaptive optics↗

DOE OSTI2024

Ocean surface radiation measurement best practices

Ocean surface radiation measurement best practices have been developed as a first step to support the interoperability of radiation measurements across multiple ocean platforms and between land and ocean networks. This document describes the consensus by a working group of radiation measurement experts from land, ocean, and aircraft communities. The scope was limited to broadband shortwave (solar) and longwave (terrestrial infrared) surface irradiance measurements for quantification of the surface radiation budget. Best practices for spectral measurements for biological purposes like photosynthetically active radiation and ocean color are only mentioned briefly to motivate future interactions between the physical surface flux and biological radiation measurement communities. Topics discussed in these best practices include instrument selection, handling of sensors and installation, data quality monitoring, data processing, and calibration. It is recognized that platform and resource limitations may prohibit incorporating all best practices into all measurements and that spatial coverage is also an important motivator for expanding current networks. Thus, one of the key recommendations is to perform interoperability experiments that can help quantify the uncertainty of different practices and lay the groundwork for a multi-tiered global network with a mix of high-accuracy reference stations and lower-cost platforms and practices that can fill in spatial gaps.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Terrestrial laser scanning data (Levels 0 and 1) for Pasoh, Malaysia, Sep 2024

This data package contains data from terrestrial laser scanning (TLS) at the Pasoh Forest Reserve, Malaysia. The Pasoh Forest Reserve is a facility of the Forest Research Institute Malaysia, and contains evergreen lowland dipterocarp forest. The Next-Generation Ecosystem Experiments Tropics (NGEE-Tropics) study areas at Pasoh were established to study how different species respond to climatic variation and soil water availability. Two study areas were chosen representing different topography and species. The TLS data archived here were collected to provide detailed, three-dimensional information about forest structure. Specifically, data were collected to allow tree-level characterization of woody structure and leaf area for 12 focal trees with FloraPulse and sap flux sensors, facilitating estimation of woody biomass and leaf area to allow upscaling of water content and transpiration data to the tree-level. Scan positions were not selected to provide consistent data for non-focal trees with the study areas. This data package contains the following data: - High-level files document further details of the campaign and data package: 1_CampaignSummary.csv provides details about the campaign and study site, 2_ScanAreasDetail.csv provides details about each separate scan area (groups of scans post-processed into a single point cloud), 3_TerrestrialLidarSensor.csv provides further technical details about the Riegl VZ-400i TLS sensor, TLS_CSV_dd.csv is a CSV Data Dictionary providing information about the fields in CSV files following the ESS-DIVE CSV File Formatting Guidelines Reporting Format, TLS_flmd.csv is a File Level Metadata file providing information about each file in the data package following the ESS-DIVE File Level Metadata Reporting Format, and README.txt is a text file describing the overall project and file structure. - Level 0 data are the raw data (.PROJ folders) as recorded by the Riegl VZ-400i TLS instrument before scan co-registration and post-processing with the Riegl's proprietary RiSCAN PRO software, which requires a license. - Level 1 data contain post-processed, co-registered data from each scan area. The "PointClouds" folder for each scan area contains a .las file with 1 cm resolution point cloud data exported from RiSCAN PRO. These are the main files likely to be of interest to most users and can be further processed with any software capable of manipulating .las files (e.g. Python, R CloudCompare). The "Project Information" folder contains log files from post-processing in RiSCAN PRO that may be of interest to users who want to see detailed records of post-processing, including all PDF reports generated by RiSCAN PRO. The "ScanPositions" folder contains information about the final position of all TLS scans, after post-processing, in multiple formats. The file ScanPositions_*.csv provides final geo-referenced scan positions, and the file SOP_backup_*.csv can be used in RiSCAN PRO to restore the co-registered scan positions if users wish to re-process raw data (Level 0 .PROJ folders) with RiSCAN PRO software (e.g., subsample to a different resolution, exclude a certain scan position, or apply different filters on reflectance or deviation values) without redoing time-consuming co-registration steps.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The 先生 (SENSEI†) Experiment: sub-GeV dark matter searches with skipper-CCD

Skipper-CCDs are pixeled Silicon-based detectors that can perform multiple non-disruptive measurements of the same charge package. Their sub-electron resolution allows the detection of eV energy transfers, such as that expected from ultra-light dark matter interacting with electrons in a Silicon target. SENSEI (Sub-Electron Noise Skipper Experimental Instrument) is the first experiment to use Skipper-CCD for this purpose and to publish world-leading results using this technology. In this talk, we present an overview of the SENSEI experiment and the current status after the successful commissioning of the second batch of science-grade sensors at SNOLAB. We will also discuss the prospects in rare-events searches with skipper-CCDs: from SENSEI’s 100 g detector to OSCURA’s 10 kg array, and more.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

The SENSEI Experiment: sub-GeV dark matter searches with skipper-CCDs

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Measurement of Photons Emitted by High-Energy Charged Particles as Background in Single-Photon Resolving Image Sensors

This work introduces an advanced technique optimized for detecting photons generated by charged particles, leveraging Skipper charge coupled device (Skipper-CCD) image sensors. By analyzing background sources and detection efficiencies, the technique achieves strong agreement between experimental results and Cherenkov-based simulations. It also provides a robust framework for investigating secondary photon production in environments with high fluxes of ionizing particles, such as those anticipated in space-based astronomical instruments. These secondary photons present a critical challenge as background noise for next-generation single-photon resolving imagers used to study faint celestial objects. Furthermore, the method exhibits significant potential for broader applications, including exploring photon generation in various substrate materials and examining their transport through multiple interfaces.

Fernandez Moroni, Guillermo [Fermilab; Chicago U.,↗

DOE OSTI2023

Measurement of needle and armature dynamics in a gasoline direct injector by high-speed neutron imaging

In modern spark ignition engines, precise delivery of fuel with gasoline direct injection has become increasingly important in the effort to meet ever stricter efficiency and emissions regulations. Use of multiple small close-coupled injections has become more common in attempt to precisely control fuel distribution in the cylinder, but these strategies are hindered by nonlinear injection effects due to operation in the ballistic region of the solenoid-operated valve and due to armature bounce at the end of injection. Understanding the internal dynamics of the injector is crucial to minimizing and controlling non-linearity and shot-to-shot variation, but the experimental techniques available to date are capable only of tracking the position of either the top of the needle (via laser sensors or by monitoring current and voltage in the solenoid coil) or the bottom of the needle (via transparent nozzles or high-speed x-ray imaging). Furthermore, a complete picture of the axial and radial motion of valve needle has until now remained elusive. In this work, we present high-speed ensemble neutron transmission imaging of an entire 8-hole gasoline direct injector operating at 200 bar, allowing for both visualization and quantification of the actuation dynamics including lift and wobble of the valve ball, oscillation and bending of the valve needle, lift, rocking, and bounce of the armature, compression of the springs, and radial swelling of the solenoid during energization. Because neutrons offer high penetration through the metal injector while also being sensitive to the 1 H nuclei in fuel molecules, it is also possible to simultaneously see the fluid dynamics of the injection process, including filling of the sac volume, emanation of the spray through the nozzle holes and into the downstream gas, and the formation and evolution of fuel films on the tip of the injector and the walls of the spray container.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Continuous snow depth, ground interface temperature and shallow soil temperature measurements from 2021-10-1 to 2022-6-14, Seward Peninsula, Alaska

The dataset contains co-located snow depth, ground interface temperature, and shallow soil temperature measured at 98 discrete locations in a watershed located along the Nome-Teller road at mile marker 27 (referred to as T27), and at 53 discrete locations on a hillslope located along the Kougarok road at mile marker 64 (referred to as K64), in Seward Peninsula, Alaska. The dataset aims to understand the local heterogeneity of snow depth, snow temperature, and soil temperature dynamics and their interactions in a discontinuous permafrost region. The dataset is also valuable to train and evaluate machine learning and physical models to predict snow depth or the impact of snow depth on ground surface temperature. At each location, temperatures above and below the ground surface were measured by a pair of vertically deployed distributed temperature profiling probes designed based on Dafflon et al (2022). The probes have high precision temperature sensors spaced at 5 or 10 cm. The mean daily snow depth was estimated by identifying the pair of consecutive sensors with maximum drop of daily temperature high-frequency fluctuations. The ground interface temperature was measured by the sensor located 1-5 cm above the ground surface at 15-minute intervals. The shallow soil temperature was measured by the sensor located 1-5 cm below the ground surface at 15-minute intervals. The dataset includes a description of the probe locations in the "Probe_locations_*.csv" file and the 3 data files (Snow_depths_*.csv, Ground_interface_temperatures_*.csv, Shallow_soil_temperatures_*.csv). * is either T27 or K64, which are the two study sites. In each data file, each column corresponds to a measurement location. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv. A more detailed description of data processing, along with an updated dataset incorporating multiple seasons and improved snow depth estimation is available at https://doi.org/10.15485/2480365 (Wang et al., 2025a, Wang et al., 2025b).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).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. 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).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Laser ultrasonic imaging of subsurface defects with the linear sampling method

Laser ultrasonics is a remote nondestructive evaluation technique suitable for real-time monitoring of fabrication processes in semiconductor metrology, advanced manufacturing, and other applications where non-contact, high fidelity measurements are required. Here we investigate laser ultrasonic data processing approaches to reconstruct images of subsurface side drilled holes in aluminum alloy specimens. We demonstrate through simulation that the model-based linear sampling method (LSM) can perform accurate shape reconstruction of single and multiple holes and produce images with well-defined boundaries. We experimentally confirm that LSM produces images that represent the internal geometric features of an object, some of which may be missed by conventional imaging.

42 ENGINEERING↗

DOE OSTI2021

Multi-energy reconstructions, central electron temperature measurements, and early detection of the birth and growth of runaway electrons using a versatile soft x-ray pinhole camera at MST

A multi-energy soft x-ray pinhole camera has been designed, built, and deployed at the Madison Symmetric Torus to aid the study of particle and thermal transport, as well as MHD stability physics. This novel imaging diagnostic technique employs a pixelated x-ray detector in which the lower energy threshold for photon detection can be adjusted independently on each pixel. The detector of choice is a PILATUS3 100 K with a 450 μm thick silicon sensor and nearly 100 000 pixels sensitive to photon energies between 1.6 and 30 keV. An ensemble of cubic spline smoothing functions has been applied to the line-integrated data for each time-frame and energy-range, obtaining a reduced standard-deviation when compared to that dominated by photon-noise. The multi-energy local emissivity profiles are obtained from a 1D matrix-based Abel-inversion procedure. Central values of Te can be obtained by modeling the slope of the continuum radiation from ratios of the inverted radial emissivity profiles over multiple energy ranges with no a priori assumptions of plasma profiles, magnetic field reconstruction constraints, high-density limitations, or need of shot-to-shot reproducibility. In tokamak plasmas, a novel application has recently been tested for early detection, 1D imaging, and study of the birth, exponential growth, and saturation of runaway electrons at energies comparable to 100 × Te,0; thus, early results are also presented.

Delgado-Aparicio, L. F. (ORCID:0000000167394380)↗

DOE OSTI2023

A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature: Supporting Data

This dataset was used to assess the potential of a Distributed Temperature Profiling System developed and presented in the article named "A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature" and submitted to Cryosphere. There are three comma-delimited data files (.csv). Each of them contains snow or soil temperature with times (UTC) in the first column and temperature at various vertical distance from the ground surface (positive means in air/snow) or below the ground surface (negative means in soil). The measurements were acquired every 15 minutes. Data collected at the East River, Colorado site with two probes: 1) measuring air/snow temperature from 1.1 m above the ground surface to the ground surface (with 5 or 10 cm spacing between sensors) and 2) measuring soil temperature from the ground surface to 0.7 m depth (with 5 or 10 cm spacing between sensors). Data collected at the Teller road (mile 27) site near Nome, Alaska with one probe: measuring soil temperature from 5 cm above the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors). Additional metadata included in *.csv and *.pdf files. NGEE Arctic Project Summary: 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).

54 ENVIRONMENTAL SCIENCES↗