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DOE OSTI2020

Production Operations Management System (POMS) for Fermilab Experiments

The Production Operations Management System (POMS) software allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs, and currently manages the majority of production computing of experiments at Fermilab.POMS provides a web service interface that enables automated job submission on distributed resources according to customers’ requests, as well as subsequent monitoring of those submissions as well as recovery of failed submissions, debugging and record keeping.POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub (for job submission), SAM (for data management), and Landscape (for monitoring), and in combination with them handles the creation of intermediate datasets of files for multistage campaigns.POMS visualizes these campaigns with an interactive GUI interface. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign.This paper will discuss the current usage, history, and some technical details of POMS, as well as planned future extensions, particularly interfacing with Rucio as well as SAM for file movement.

Mengel, Marc↗

NASA NTRS2006

Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

Hurricane Katrina inflicted widespread damage to vegetation in southwestern coastal Mississippi upon landfall on August 29, 2005. Storm damage to surface vegetation types at the NASA John C. Stennis Space Center (SSC) was mapped and quantified using IKONOS data originally acquired on September 2, 2005, and later obtained via a Department of Defense ClearView contract. NASA SSC management required an assessment of the hurricane s impact to the 125,000-acre buffer zone used to mitigate rocket engine testing noise and vibration impacts and to manage forestry and fire risk. This study employed ERDAS IMAGINE software to apply traditional classification techniques to the IKONOS data. Spectral signatures were collected from multiple ISODATA classifications of subset areas across the entire region and then appended to a master file representative of major targeted cover type conditions. The master file was subsequently used with the IKONOS data and with a maximum likelihood algorithm to produce a supervised classification later refined using GIS-based editing. The final results enabled mapped, quantitative areal estimates of hurricane-induced damage according to general surface cover type. The IKONOS classification accuracy was assessed using higher resolution aerial imagery and field survey data. In-situ data and GIS analysis indicate that the results compare well to FEMA maps of flooding extent. The IKONOS classification also mapped open areas with woody storm debris. The detection of such storm damage categories is potentially useful for government officials responsible for hurricane disaster mitigation.

Spruce, Joseph P.↗

DOE OSTI2017

Washington Geothermal Play Fairway Analysis Heat, Permeability, and Fracture Model Data

This submission contains raster and vector data for the entire state of Washington, with specific emphasis on the three geothermal play fairway sites: Mount St. Helens seismic zone (MSHSZ), Wind River valley (WRV), and Mount Baker (MB). Data are provided for 3 major geothermal models: heat, permeability, and fluid-filled fractures, and an additional infrastructure model. Both of the permeability and fluid-filled-fracture models are produced at 200 m and at 2 km depths; the heat model is only produced at the 200 m depth. Values are provided for both model favorability and model confidence. A combined model at 200m and 2 km depths is provided for favorability, confidence, and exploration risk. Raster data are provided in GeoTiff format and have a statewide coverage. Cell size is 104.355 ft; file type is unsigned 8-bit integer (0-255); 0 represents no favorability or confidence; 255 represents maximum favorability or confidence. The NAD83(HARN)/Washington South (ftUS) projection is used (EPSG:2927). Vector data are provided in shapefile or comma-delimited text file formats. Geographic coordinates, where provided, are in WGS84. A readme file accompanies each folder and provides an overview and description of the enclosed data. The heat model combines 5 intermediate raster layers (which are included in the download package): temperature gradient wells, young volcanic vents, hot springs, young intrusive volcanic rocks, and geothermometry. The permeability model combines 8 intermediate raster layers: density of mapped faults, 2D dilation tendency of mapped faults, 2D slip tendency of mapped faults, seismicity, 3D dilation tendency, 3D slip tendency, 3D maximum coulomb shear stress, and 3D slip gradients. The fluid-filled fracture model combines up to 4 intermediate rasters: resistivity from magneto-telluric 3D inversions, seismicity, Vp/Vs anomalies from passive seismic tomography, and Vs anomalies from ambient-noise tomography. A statewide infrastructure model is also provided that formalizes land-use constraints and restrictions relevant for geothermal prospecting and development. This model combines 10 intermediate rasters: areas off limits to drilling, existing or proposed geothermal leases, DNR-owned land, land-use restrictions along the Columbia River Gorge, areas inundated by water, availability of potential process water, proximity to existing roads, proximity to transmission lines, distance from urban areas, and snow-related elevation restrictions. Supporting vector data for the development of each raster layer is provided. For details on the areas of interest and modeling process please see the 'WA_State_Play_Fairway_Phase_2_Technical_Report' in the download package.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Kilauea Magnetotelluric Dataset

In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kilauea and the East and Southwest Rift zones, which has implications for understanding Kilaueas plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone (ERZ), where electrical contact resistances are on the order of 100 kOhm. This data supports the continuing efforts to increase geothermal power on the island of Hawaii. Each of the 70 EDI files are the MT impedance tensors for 1 site. There is also a description of the processing of the data and a site map showing the locations of each site.

15 GEOTHERMAL ENERGY↗

NASA NTRS1991

Users manual for the IMA program

The Impulsive Mission Analysis (IMA) computer program provides a user-friendly means of designing a complete Earth-orbital mission profile using an 80386-based microcomputer. The IMA program produces a trajectory summary, an output file for use by the new Simplex Computation of Optimum Orbital Trajectories (SCOOT) program, and several graphics, including ground tracks on a world map, altitude profiles, relative motion plots, and sunlight/communication timelines. The user can design missions using any combination of three basic types of mission segments: double co-eliptic rendezvous, payload delivery, and payload de-orbit/spacecraft recovery. Each mission segment is divided into one or more transfers, and each transfer is divided into one or more legs, each leg consisting of a coast arc followed by a burn arc.

Williams, D. F.↗

DOE OSTI2021

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

NASA NTRS1994

Measurements of striae in CR+ doped YAG laser crystals

Striations in Czochralski (CZ) grown crystals have been observed in materials such as GaAs, silicon, photorefractive crystals used for data storage, potassium titanyl phosphate crystals and LiNbO3. Several techniques have been used for investigating these defects including electron microscopy, laser scanning tomography, selective photoetching, X-ray diffuse scattering, interference orthoscopy, laser interferometry and micro-Fourier transform infrared spectroscopy mapping. A 2mm thick sample of the material to be investigated is illuminated with light that is absorbed and non-absorbed by the ion concentration to be observed. The back surface of the sample is focused onto a solid-state image detector and images of the input beam and absorbed (and diffracted) beams are captured at two wavelengths. The variation of the coefficient of absorption asa function of distance on the sample can be derived from these measurements. A Big Sky Software Beamcode system is used to capture and display images. Software has been written to convert the Beamcode data files to a format that can be imported into a spreadsheet program such as Quatro Pro. The spreadsheet is then used to manipulate and display data. A model of the intensity map of the striae collected by the imaging system has been proposed and a data analysis procedure derived. From this, the variability of the attenuation coefficient alpha can be generated. Preliminary results show that alpha may vary by a factor of four or five over distances of 100 mu m. Potential errors and problems have been discovered and additional experiments and improvements to the experimental setup are in progress and we must now show that the measurement techniques and data analysis procedures provide 'real' information. Striae are clearly visible at all wavelengths including white light. Their basic spatial frequency does not change radically, at least when changing from blue to green to white light. Further experimental and theoretical work can be done to improve the data collection techniques and to verify the data analysis procedures.

Cady, Fredrick M.↗

DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗

DOE OSTI2015

SU-C-213-03: Custom 3D Printed Boluses for Radiation Therapy

Purpose: To develop a clinical workflow and to commission the process of creating custom 3d printed boluses for radiation therapy. Methods: We designed a workflow to create custom boluses using a commercial 3D printer. Contours of several patients were deformably mapped to phantoms where the test bolus contours were designed. Treatment plans were created on the phantoms following our institutional planning guideline. The DICOM file of the bolus contours were then converted to stereoLithography (stl) file for the 3d printer. The boluses were printed on a commercial 3D printer using polylactic acid (PLA) material. Custom printing parameters were optimized in order to meet the requirement of bolus composition. The workflow was tested on multiple anatomical sites such as skull, nose and chest wall. The size of boluses varies from 6×9cm2 to 12×25cm2. To commission the process, basic CT and dose properties of the printing materials were measured in photon and electron beams and compared against water and soft superflab bolus. Phantoms were then scanned to confirm the placement of custom boluses. Finally dose distributions with rescanned CTs were compared with those computer-generated boluses. Results: The relative electron density(1.08±0.006) of the printed boluses resemble those of liquid tap water(1.04±0.004). The dosimetric properties resemble those of liquid tap water(1.04±0.004). The dosimetric properties were measured at dmax with an ion chamber in electron and photon open beams. Compared with solid water and soft bolus, the output difference was within 1% for the 3D printer material. The printed boluses fit well to the phantom surfaces on CT scans. The dose distribution and DVH based on the printed boluses match well with those based on TPS generated boluses. Conclusion: 3d printing provides a cost effective and convenient solution for patient-specific boluses in radiation therapy.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1975

Remote sensing applications for urban planning - The LUMIS project

The Santa Monica mountains of Los Angeles consist primarily of complexly folded sedimentary marine strata with igneous and metamorphic rocks at the eastern end of the mountains. With the increased development of the Santa Monicas, a study was conducted to determine the critical land use data items in the mountains. Two information systems developed in parallel are described. One capitalizes on the City's present computer line printer system, and the second utilizes map overlay techniques on an interactive computer terminal. Results concerning population, housing, and land improvement illustrate the successful linking of ordinal and nominal data files in the interactive system.-

Paul, C. K.↗

DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

DOE OSTI2018

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗

DOE OSTI2014

MO-G-BRE-04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image-Guided Treatment Machine

Purpose: Two aims of this work were to develop a method to automatically verify treatment delivery accuracy immediately after patient treatment and to develop a comprehensive daily treatment report to provide all required information for daily MR-IGRT review. Methods: After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a novel MR-IGRT treatment machine, we designed a method to use 1) treatment plan files, 2) delivery log files, and 3) dosimetric calibration information to verify the accuracy and completeness of daily treatment deliveries. The method verifies the correctness of delivered treatment plans and beams, beam segments, and for each segment, the beam-on time and MLC leaf positions. Composite primary fluence maps are calculated from the MLC leaf positions and the beam-on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. We also designed the daily treatment delivery report by including all required information for MR-IGRT and physics weekly review - the plan and treatment fraction information, dose verification information, daily patient setup screen captures, and the treatment delivery verification results. Results: The parameters in the log files (e.g. MLC positions) were independently verified and deemed accurate and trustable. A computer program was developed to implement the automatic delivery verification and daily report generation. The program was tested and clinically commissioned with sufficient IMRT and 3D treatment delivery data. The final version has been integrated into a commercial MR-IGRT treatment delivery system. Conclusion: A method was developed to automatically verify MR-IGRT treatment deliveries and generate daily treatment reports. Already in clinical use since December 2013, the system is able to facilitate delivery error detection, and expedite physician daily IGRT review and physicist weekly chart review.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Planck intermediate results

We present the NPIPE processing pipeline, which produces calibrated frequency maps in temperature and polarization from data from the Planck Low Frequency Instrument (LFI) and High Frequency Instrument (HFI) using high-performance computers. NPIPE represents a natural evolution of previous Planck analysis efforts, and combines some of the most powerful features of the separate LFI and HFI analysis pipelines. For example, following the LFI 2018 processing procedure, NPIPE uses foreground polarization priors during the calibration stage in order to break scanning-induced degeneracies. Similarly, NPIPE employs the HFI 2018 time-domain processing methodology to correct for bandpass mismatch at all frequencies. In addition, NPIPE introduces several improvements, including, but not limited to: inclusion of the 8% of data collected during repointing manoeuvres; smoothing of the LFI reference load data streams; in-flight estimation of detector polarization parameters; and construction of maximally independent detector-set split maps. For component-separation purposes, important improvements include: maps that retain the CMB Solar dipole, allowing for high-precision relative calibration in higher-level analyses; well-defined single-detector maps, allowing for robust CO extraction; and HFI temperature maps between 217 and 857 GHz that are binned into 0'.9 pixels (Nside = 4096), ensuring that the full angular information in the data is represented in the maps even at the highest Planck resolutions. The net effect of these improvements is lower levels of noise and systematics in both frequency and component maps at essentially all angular scales, as well as notably improved internal consistency between the various frequency channels. Based on the NPIPE maps, we present the first estimate of the Solar dipole determined through component separation across all nine Planck frequencies. The amplitude is (3366.6 ± 2.7) μK, consistent with, albeit slightly higher than, earlier estimates. From the large-scale polarization data, we derive an updated estimate of the optical depth of reionization of τ = 0.051 ± 0.006, which appears robust with respect to data and sky cuts. There are 600 complete signal, noise and systematics simulations of the full-frequency and detector-set maps. As a Planck first, these simulations include full time-domain processing of the beam-convolved CMB anisotropies. The release of NPIPE maps and simulations is accompanied with a complete suite of raw and processed time-ordered data and the software, scripts, auxiliary data, and parameter files needed to improve further on the analysis and to run matching simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

PRESSURE-FILM OPEN SOURCE SCANNING AND MAPPING

SF-22-099 Pressure-film Open Source Scanning and Mapping (POSSM) is software that analyses images of pressure-film (scans or photographs). POSSM collects data from that analysis in order to produce a number of visual aides, including pressure maps, histograms, and 3d surface plots. POSSM is designed to be able to analyze an entire folder full of images, exporting numeric data as .csv files and visual graphics as .png files.

Grider, Patrick↗

DOE OSTI2021

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. The paper summary follows: We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2-5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ~22 degrees to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity. Reference: Zhang, H. and K. L. Pankow (2021). High-resolution Bayesian spatial auto-correlation (SPAC) pseudo-3D Vs model of Utah FORGE site with a dense geophone array, Geophys. Res. Int, https://doi.org/10.1093/gji/ggab049

15 GEOTHERMAL ENERGY↗

DOE OSTI2013

A Python Object Oriented & Data Driven Testing Infrastructure for an Environmental Information Management System

Software systems such as TEIMS, the Taurus Environmental Information Management System evolve in size and complexity making manual testing no longer sufficient or feasible, becoming a performance and quality risk. TEIMS is a system of systems comprised of dynamic, data-driven web-based applications that support planning, operational monitoring, data collection, sample management, reporting and, scientific findings for LLNL’s Environmental Restoration Department (ERD). Selenium’s Integrated Development Environment (IDE) was previously used to support TEIMS testing. An approach with limited flexibility for future software development. As a student intern I was assigned the task to develop an object oriented testing infrastructure for TEIMS. A critical resource in this approach is the development of a catalogue of page elements. To accomplish this I created a comma separated value file, which is comprised of key identifiers based on page elements. Using the Python language and the Selenium Web driver I then developed the object mapping structure, which serves as a wrapper for exposure of each element allowing interaction with the tests and test suites. A master driver “Module” allowed the web driver to be shared among the objects and tests. I then developed a web-based graphical user interface (GUI) for test history, metrics and searching. This data driven approach provides flexibility and extensibility, allowing changes to the structure to be performed in a single place. The result is an object oriented/data driven infrastructure that allows tests to be simpler, flexible, and maintainable, with searchable results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Final Report UCLA-Thermochemical Storage with Anhydrous Ammonia

In ammonia-based thermochemical energy storage (TCES), ammonia is dissociated endothermically as it absorbs solar energy during the daytime. When energy is required, the reverse reaction releases energy to heat a working fluid such as steam, to produce electricity. Ammonia-based TCES has great advantages of simplicity, low cost reactants, and a strong industrial base in the conventional ammonia industry. The concept has been demonstrated over three decades of research at Australian National University, achieving a 24-hour demonstration of a complete system. At the start of this project, three challenges were identified that would have to be addressed to show that the system is technically and economically viable for incorporation into a CSP plant with an advanced, high temperature power block. All three of these challenges have now been addressed: 1. The ammonia synthesis reaction had not, to our knowledge, been carried out at temperatures consistent with modern power blocks (i.e., ~650°C). The technical feasibility of operating a reactor under high-temperature, near-equilibrium conditions was an unknown, and was therefore a technical risk. The project has successfully demonstrated steam heating to 650°C and energy recovery to steam at the 5 kWt level. 2. The ammonia system has a relatively low enthalpy of reaction combined with gas phase reactants. This is not a direct disadvantage since the reactants themselves are low cost. The challenge lies in storing the required volume of reactants cost effectively. Therefore, a second key goal was to show, through techno-economic analysis, that underground storage technologies can be used to store the energy-rich gas at a cost that is consistent with the SunShot cost goal. We have identified two promising technologies for gas storage: storage in salt caverns has an estimated cost of 1(USD)/kWht and storage in drilled shafts could be on the order of 7(USD)/kWht. Together these two options answer the technical challenge associated with storage of gas phase components. 3. While this project is primarily concerned with high-temperature heat recovery and methods to store the gaseous components, it is also important to consider the feasibility of the entire system. Consequently, an additional goal was to perform analysis to show the feasibility of integrating endothermic reactors within a tower receiver. A conceptual design of an ammonia dissociation receiver/reactor has been developed that fits into the same size cylindrical envelope as the molten salt receiver in SAM, and has the same design thermal capacity. The calculated thermal efficiency of this receiver is 94.6%. Thus, this investigation has established the technical feasibility of a surround field tower system using ammonia dissociation. With these challenges addressed, we proceeded to design a full-scale synthesis and heat recovery system. A model was developed and validated by comparison with our experimental data. A parametric study showed, among other things, the importance of using small tube diameters and spacing to enhance heat transfer. Multi-parameter optimization was used to find a design that minimizes the wall material volume. Finally, cost estimation shows that the ammonia system has good prospects of meeting the Sunshot 15(USD)/kWht target: estimated costs of the entire synthesis system for the 220 MWt plant with 6 hours of storage are 13(USD)/kWht using salt cavern storage and 18(USD)/kWht using shaft drilling. Costs per kWht are even lower with more hours of storage. With the established technology of ammonia synthesis as a starting point, the successes of the project have mitigated technical risks associated with high-temperature synthesis reaction, underground storage, and tower receiver design. Estimated costs are less than 15(USD)/kWht with salt cavern storage. It is now possible to map a time line to commercial deployment that is likely to be shorter and less risky than other thermochemical cycles under active investigation. UCLA has filed a patent that protects the new ideas developed during this project. Discussions are ongoing with potential investors with the aim of partnering for further work. As well as immediate improvements and extra work with the existing experimental system, a key goal is to extend it to a small solar-driven project at an early opportunity.

14 SOLAR ENERGY↗