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At least 523 records · Page 29

REopt Lite Geothermal Heat Pump Design Requirements

This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be revised, as required, throughout the development phase with consensus between the Department of Energy (DOE) Geothermal Technologies Office (GTO) and NREL. The GHP module will expand existing REopt Lite capabilities to include techno-economic optimization of GHP systems, either stand alone, or integrated with the other existing technology types, namely solar photovoltaics (PV), wind power, battery energy storage, thermal energy storage, combined hear and power (CHP), and absorption chiller. Included in this submission are links to the REopt Lite web tool and open-source Git-Hub page. The REopt Lite tool can also be accessed directly via the NREL Developer Network. A link is also provided for the REopt report that overviews the module's capabilities.

15 GEOTHERMAL ENERGY↗

HERO WEC 2024 Hydraulic Configuration Deployment Data

The following submission includes raw and processed data from the in water deployment of NREL's Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), in the form of parquet files, TDMS files, CSV files, bag files and MATLAB workspaces. This dataset was collected in March 2024 at the Jennette's pier test site in North Carolina. This submission includes the following: - Data description document (HERO WEC FY24 Hydraulic Deployment Data Descriptions.doc) - This document includes detailed descriptions of the type of data and how it was processed and/or calculated. - Processed MATLAB workspace - The processed data is provided in the form of a single MATLAB workspace containing data from the full deployment. This workspace contains data from all sensors down sampled to 10 Hz along with all array Value Added Products (VAPs). - MATLAB visualization scripts - The MATLAB workspaces can be visualized using the file "HERO_WEC_2024_Hydraulic_Config_Data_Viewer.m/mlx". The user simply needs to download the processed MATLAB workspaces, specify the desired start and end times and run this file. Both the .m and .mlx file format has been provided depending on the user's preference. - Summary Data - The fully processed data was used to create a summary data set with averages and important calculations performed on 30-minute intervals to align with the intervals of wave resource data reported from nearby CDIP ocean observing buoys located 20km East of Jennette's pier and 40km Northeast of Jennette's pier. The wave resource data provided in this data set is to be used for reference only due the difference in water depth and proximity to shore between the Jennette's pier test site and the locations of the ocean observing buoys. This data is provided in the Summary Data zip folder, which includes this data set in the form of a MATLAB workspace, parquet file, and excel spreadsheet. - Processed Parquet File - The processed data is provided in the form of a single parquet file containing data from all HERO WEC sensors collected during the full deployment. Data in these files has been down sampled to 10 Hz and all array VAPs are included. - Interim Filtered Data - Raw data from each sensor group partitioned into 30-minute parquet files. These files are outputs from an intermediate stage of data processing and contain the raw data with no Quality Control (QC) or calculations performed in a format that is easier to use than the raw data. - Raw Data - Raw, unprocessed data from this deployment can be found in the Raw Data zip folder. This data is provided in the form of TDMS, CSV, and bag files in the original format output by the MODAQ system. - Python Data Processing Script - This links to an NREL public github repository containing the python script used to go from raw data to fully processed parquet files. Additional documentation on how to use this script is included in the github repository. This data set has been developed by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗

RC-SFA Data Management Templates and Guidance for Standardized, Reusable AI-Ready Data Packages

This data package provides templates and supporting documentation developed by the River Corridor Science Focus Area (RC-SFA; https://www.pnnl.gov/projects/river-corridor) to communicate its approach to managing and publishing AI-ready data. The package is intended to help data users and data producers understand the structures, metadata practices, and quality-control approaches that support consistent, reusable, and machine-actionable data products across RC-SFA studies. Rather than focusing on a single experimental dataset, this package documents the data management framework used to make RC-SFA data easier to find, ingest, navigate, and interpret. The materials in this package reflect RC-SFA practices for standardized data package organization, including the use of a human- and machine-readable README, file-level metadata, data dictionaries, descriptive file naming, method identifiers, and automated and review-based quality assurance procedures. Together, these components illustrate how RC-SFA extends FAIR data principles toward AI-readiness by prioritizing deep metadata, consistency across data packages, and support for informed downstream reuse by both humans and computational tools. This dataset is comprised of (1) readme; (2) presentation slides with an overview of RC-SFA approach and guidance; (3) document of RC-SFA best practices; (4) data dictionary (dd); (5) file level metadata (flmd); and a subfolder containing templates for dd and flmd. All files are .csv and .pdf. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

AI-readiness↗

PARETO 0.8.0 Release

PARETO 0.8.0 Release. Highlights: Model Updates - Applied unified sets for pipeline and trucking arcs in strategic model - Apply unified sets for pipeline and trucking arcs in operational model - Added new config argument for removal efficiency calculation method - Standardized bidirectional capacity constraint - Added dependencies removed in IDAES 2.1 - Created bounding functions & utilities - Added Hydraulics module to the strategic model - Add additional arc types to strategic model Documentation and Tutorial Updates - Improved PARETO treatment document - Introduced general tutorial and treatment module Jupyter notebooks for Strategic Model - Update docs with correct support email list address - Consolidate and deduplicate Getting Started and resources for developers - Enable Black formatting for Jupyter notebooks - Add Binder configuration files and README Bug Fixes - Fix strategic model documentation typos - Removed duplicated units from output file header UI Updates - Added view for comparing different scenarios - Added functionality for manually overriding PARETO decisions

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗

CCSI Toolset 3.22 Release

CCSI Toolset 3.22 Release Highlights The Sequential Design of Experiments user interface was updated to resolve an issue where the results would fail to plot in some cases (e.g., Non-Uniform Space Filling designs). The Machine Learning/Artificial Intelligence module was updated to support Keras 3 and to reflect changes made to dependencies’ syntax. A check was added to ensure PSUADE is installed and available at FOQUS startup. If PSUADE is not installed, a link to the FOQUS documentation is displayed and FOQUS is closed. The copyright year was updated to include 2024 in places where it had not previously been updated. Typographical errors were corrected to improve clarity in variable names and documentation. The FOQUS documentation was updated to reflect the fact that ALAMO can have two executables and indicates the correct executable to add to the Settings path. SimSinter was updated to version 3.1.0. This version removed gPROMS support and included security updates.

AS↗

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗

GEOS: A performance portable multi-physics simulation framework for subsurface applications

GEOS is a simulation framework focused on solving tightly coupled multi-physics problems with an initial emphasis on subsurface reservoir applications. Currently, GEOS supports capabilities for studying carbon sequestration, geothermal energy, hydrogen storage, and related subsurface applications. The unique aspect of GEOS that differentiates it from existing reservoir simulators is the ability to simulate tightly coupled compositional flow, poromechanics, fault slip, fracture propagation, and thermal effects, etc. Extensive documentation is available on the GEOS documentation pages (GEOS Documentation, 2024). Note that GEOS, as presented here, is a complete rewrite of the previous incarnation of the GEOS referred to in (Settgast et al., 2017).

58 GEOSCIENCES↗

Protocol for Determining Actual Flow Rate in FTWC Duct Systems

This paper is intended to document the theory and methods to determine the actual flow rate in the exhaust system used to ventilate the Flanged Tritium Waste Containers based on realtime instrument readings. Section 1 provides introductory and background material; Section 2 details the various correction factors used to adjust flow readings for ambient air pressure and temperature and other operational parameters. Section 3 provides guidance on implementing this process during venting operations, and Section 4 provides supporting documentation and also a field checklist that can be used by personnel during venting. For Revision 1, a summary of editorial changes made to the paper was added as Section 4.4, as well as a section documenting peer review (Section 4.5).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

UTrain Manual for Training Administrators

This Institutional Training Administrative Procedure provides the business rules that must be followed when working in UTrain. As commercial off-the-shelf software with customizations, UTrain cannot address all the implementation business requirements, and thus, administrative business rules and processes were defined and documented. Many business rules were incorporated into the UTrain training materials. UTrain is the Laboratory’s official learning management system. UTrain is the system of record for all Laboratory training, qualification, certification, and worker authorization. All training at LANL must be documented in UTrain. The detailed steps of how to operate UTrain are contained in the UTrain courses and training manuals and in the UTrain job aids, not in this document.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume II: DUNE Physics

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume II of this TDR, DUNE Physics, describes the array of identified scientific opportunities and key goals. Crucially, we also report our best current understanding of the capability of DUNE to realize these goals, along with the detailed arguments and investigations on which this understanding is based. This TDR volume documents the scientific basis underlying the conception and design of the LBNF/DUNE experimental configurations. As a result, the description of DUNE's experimental capabilities constitutes the bulk of the document. Key linkages between requirements for successful execution of the physics program and primary specifications of the experimental configurations are drawn and summarized. This document also serves a wider purpose as a statement on the scientific potential of DUNE as a central component within a global program of frontier theoretical and experimental particle physics research. Thus, the presentation also aims to serve as a resource for the particle physics community at large.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison of Light-Weight Radioisotope Heater Unit (LWRHU) Historical Testing to Special Form Testing Requirements

This paper compares the Light-Weight Radioisotope Heater Unit (LWRHU) historical testing to Department of Transportation (DOT) Special Form criteria per 49 CFR Part 173, Shippers-General Requirements for Shipments and Packages, Section 469, Tests for special form Class 7 (radioactive) materials as specified in DOE-STD-1027, Hazard Categorization of DOE Nuclear Facilities. Compliance with the aforementioned criteria allows for the exclusion of radioactive sources from the facility’s nuclear material inventory. As part of a new program at Los Alamos National Laboratory (LANL), LWRHUs are planned to be moved into TA-55, PF-5 Power Source Assembly Area (PSAA) for assembly and testing activities. The PSAA Facility is categorized as a low hazard, non-nuclear facility per DOE STD-1027 and is described in TA55-PF-5-FHC-11-001, Facility Hazard Categorization of the PSAA at PF-5, TA-55. The Facility Hazard Categorization document states, there must be documentation that radioactive sources are engineered to pass the special form testing specified by DOT in 49 CFR 173.469, Tests for special form Class 7 (radioactive) materials or ANSI N43.6, Sealed Radioactive Sources - Classification. This paper documents the extensive historical environmental safety testing of the LWRHU and demonstrates its ability to survive potential launch safety accident scenarios. The testing results are used herein to demonstrate through a comparative analysis that the robust design of the LWRHU meets or exceeds the special form testing specifications in 49 CFR 173.469, enabling the LWRHU to be transported and handled in PF-5 in support of testing and assembly program.

07 ISOTOPE AND RADIATION SOURCES↗

Central Plateau Vadose Zone Geoframework

The objective of this environmental calculation file (ECF) is to document the revision of the three dimensional (3D) geoframework model (GFM) of the Central Plateau Vadose Zone (CPVZ) on the Hanford Site. CP-60925, Model Package Report: Central Plateau Vadose Zone Geoframework, documents the original version of the CPVZGFM (herein after called the CPVZ-Rev.0) and is the underlying basis for the CPVZ conceptual model. The CPVZ GFM provides a more detailed interpretation of the vadose zone hydrostratigraphic units (HSUs) in the Central Plateau area of the greater Hanford South geoframework model (HSGFM) (ECF-HANFORD-13-0029, Development of the Hanford South Geologic Framework Model, Hanford Site, Washington). The development of the CPVZ GFM provides a consistent vadose zone geologic framework that is needed to support the 3D, multiple-waste-site modeling approach proposed in CP-60405, Hanford Site Composite Analysis Technical Approach Description: Vadose Zone, while incorporating an appropriate level of geologic data and interpretations for the size of the model using current site-standard HSUs. Future more detailed site-specific investigations within the Central Plateau can then use the CPVZ GFM as a starting point instead of the larger scale HSGFM. This GFM was developed using the site standard and approved for use IHS Kingdom software. This ECF is a revision to the original model described in CP-60925, but the underlying assumptions and conceptual model are unchanged. Therefore, this revision is a new calculation of version 1.0 of the CPVZ GFM and not a new version of the GFM. Throughout this report, the original model documented in CP-60925 is called CPVZ-Rev.0and the calculation for this revision of the model is called CPVZ-Rev.1.

58 GEOSCIENCES↗

Sierra/SolidMechanics 4.56 Verification Tests Manual

Presented in this document is a small portion of the tests that exist in the Sierra / SolidMechanics (Sierra / SM) verication test suite. Most of these tests are run nightly with the Sierra / SM code suite, and the results of the test are checked versus the correct analytical result. For each of the tests presented in this document, the test setup, a description of the analytic solution, and comparison of the Sierra / SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This document can be used to conrm that a given code capability is veried or referenced as a compilation of example problems. Additional example problems are provided in the Sierra / SM Example Problems Manual. Note, many other verication tests exist in the Sierra / SM test suite, but have not yet been included in this manual.

97 MATHEMATICS AND COMPUTING↗

Sierra/SD - Verification Test Manual - 4.56

This document presents tests from the Sierra Structural Mechanics verification test suite. Each of these tests is run nightly with the Sierra/SD code suite and the results of the test checked versus the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra/SD code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

97 MATHEMATICS AND COMPUTING↗

Sierra/Aria 4.56 Verification Manual

Presented in this document is a portion of the tests that exist in the Sierra Thermal/Fluids verification test suite. Each of these tests is run nightly with the Sierra/TF code suite and the results of the test checked under mesh refinement against the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

97 MATHEMATICS AND COMPUTING↗

The MFiX Particle-in-Cell Method (MFiX-PIC) Theory Guide

MFiX (Multiphase Flow with Interphase eXchanges) is an open-source multiphase flow solver developed at the National Energy Technology Laboratory. Within the code, users have access to a single phase or interpenetrating continua-based multiphase two-fluid model (TFM), a discrete element model (DEM), and a particle-in-cell model (PIC). TFM, DEM, and PIC can all be used to create multiphase simulations that include hydrodynamics, chemical reactions, and heat transfer.

01 COAL, LIGNITE, AND PEAT↗

TRT Compton Scattering Data: Comparisons between LLNL and LANL: Multigroup

This memo is one of a pair of reports comparing Compton scattering data in the context of thermal radiation transport (TRT). This document focuses on Multigroup (MG) data while the other report focuses on Pointwise (PW) data. These complementary analyses, via PW comparisons, show if the same physics are used and if fundamental bugs are present, and, via MG comparisons, quantify macroscopic Compton effects such as mean amplification factors. No averaging of Compton data over photon energy is done for the PW comparisons, while lab-dependent numerical resolution choices become relevant for the MG comparisons. For this MG-comparison report, we make and document the numerical assumptions we use to convert LLNL PW data into MG data. This document plots and quantifies differences in Compton scattering data between MG LANL and LLNL for four disparate temperatures on a logarithmically-spaced photon-energy grid. In addition to LANL and LLNL data, we add a third and fourth independent vote from data generated by Brooks Kinch (LANL postdoc). For the purposes of these comparisons, we neglect induced scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗