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All sourcesNASA NTRSDOE OSTI
DOE OSTI1989

Nuclear Safety [Vol. 30, No. 3, July-September 1989]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 325 Safety of Framatome Advanced Nuclear Steam Supply Systems Designs by J. A. Charles and D. Lange, 333 Book Review of Nuclear Accidents: Intervention Levels for the Protection of the Public by H. B. Piper; ACCIDENT ANALYSIS: 335 Living PRA Computer Systems by S. C. Dinsmore and H.-P. Balfanz, 343 Summary of ICAP Assessments of RELAP5/MOD2 by W. E. Driskell and R. G. Hanson; CONTROL AND INSTRUMENTATION: 352 Thermal Performance Monitoring System at Maanshan Nuclear Power Plant by H.-J. Chao, Y.-P. Lin, G.-H. Jou, L.-Y. Liao, and Y.-B. Chen; DESIGN FEATURES: 358 Warning Systems for Nuclear Power Plant Emergencies by J. H. Sorensen and D. S. Mileti; WASTE AND SPENT FUEL MANAGEMENT: 371 Activities Related to Waste Management Compiled by E G. Silver; OPERATING EXPERIENCES: 382 Steam Generator Tube Performance: Experience with Water-Cooled Nuclear Power Reactors During 1985 by O. S. Tatone and R. L. Tapping, 400 Systems Interaction Analyses: Concepts and Techniques (Part II) by M. D. Muhlheim and G. A. Murphy, 413 Reactor Shutdown Experience Compiled by J. W. Cletcher, 416 Operating U.S. Power Reactors Compiled by E G. Silver; RECENT DEVELOPMENTS: 440 General Administrative Activities Compiled by E G. Silver, 460 Reports, Standards, and Safety Guides by D. S. Queener, 466 Status of Power-Reactor Licensing Activities Compiled by E G. Silver, 470 Proposed Rule Changes as of Mar. 31, 1989; ANNOUNCEMENTS: 334 Proceedings Published, 351 CEC Seminar on Methods and Codes for Assessing the Off-Site Consequences of Nuclear Accidents, 357 Short Course on Multiphase Flow and Heat Transfer: Bases and Applications in A: The Nuclear Power Industry B: The Process Industries, 357 International Conference on Probabilistic Safety Assessment and Management, 478 International Topical Meeting on the Safety, Status, and Future of Non-Commercial Reactors and Irradiation Facilities, 475 The Authors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

PSIP For HDF5 Pilot Project (Final Report)

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, incremental and iterative approach (much in the same spirit as Agile methodologies) for making routine software process improvements in software projects. It is designed to be easily applied in existing development workflows. Quoting from a November 2019 workshop paper describing PSIP. PSIP breaks from classic software process improvement approaches such as CMM(I), SPICE, ISO 9000 or Six Sigma, in that it trades comprehensive standards and certification-driven assessment for self-defined, internally driven goals. It does, however, carry forward such ideas as having staged models of improvement (like CMM(I)) in the form of progress tracking cards. Additionally, PSIP is more aligned with lean and agile methods; it adopts their emphasis on iterative improvement and continuous learning. At its core, PSIP is an instantiation of the Plan-Do-Check-Act management cycle (PDCA, also known as Plan-Do-Study-Adjust) which provides the foundation for much of the modern software process improvement literature. This situates PSIP within a constellation of bottom-up, inductive software process improvement methods. PSIP is designed around the notion that already overburdened teams can define and carry out a series of small, incremental steps of progression towards improvement goals without significant (there will be some, but the goal is to avoid significant) disruption to ongoing development activities. A key enabling tool in PSIP is the use of Progress Tracking Cards (PTCs) which define the steps of progression towards a given improvement goal. This is the theory of PSIP. The PSIP for HDF5 project was aimed at putting PSIP into practice with the purpose of evaluating its effectiveness in planning and facilitating quality and process improvements in a scientific software project as well as its associated artifacts. The HDF5 project was chosen as a use case to evaluate PSIP for several reasons. First, NNSA labs and LLNL in particular have a keen interest in how HDF5 quality impacts its uptake and sustainability as a community adopted and supported code. Next, HDF5 is a foundational library, a key substrate in the HPC/CSE software stack, and any improvements there realized through this contract will have benefits to many DOE applications depending on it. HDF5 also represents an older, legacy code with technical debts to pay down. These characteristics are similar to many NNSA and even some ECP code projects. But, because HDF5 is an I/O library, it represents a simpler use case within which to study PSIP than a full-fledged and significantly more complex PDE simulation code. We believe these attributes make HDF5 an ideal use case for evaluating PSIP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Emerging Pathways to Upgrade the US Housing Stock: A Review of the Home Energy Upgrade Literature

The residential buildings sector is responsible for about 20% of total US energy use. In order to achieve climate goals, we need ways to reduce carbon emissions and energy use in this sector. In addition, resiliency, electric grid stability, emergency survivability and other energy and building-related issues are becoming increasingly important challenges. New homes in most of the US meet various energy codes and are reasonably energy efficient. However, the vast majority of energy use is from existing homes that were not required to conform to energy performance requirements. It is becoming imperative to reach as many of these existing homes as possible and find ways to improve their energy-related performance. This must be done in such a way that it meets the needs and desires of homeowners and building occupants, as well as those of the contractors and design professionals engaged in doing the upgrades themselves. Energy retrofits of homes started in the 1970’s in response to the energy crisis, however, these retrofits were very limited in scope and relatively few homes were upgraded. Those homes that have been upgraded generally still have much scope for improvement. A huge effort is needed to get to scale to address the energy use in housing. The target population is effectively every home in the country, whether a large suburban single-family home, or a small downtown apartment. In order to provide a framework for analysis and the basis for plans to get to large-scale retrofits of homes, this literature review summarizes the state-of-the art in the US buildings industry. It identifies where more research, engineering, or technology is needed, as well as relevant industry trends, such as electrification, one-stop shop program design and others. It also examines other key topics, such as availability of financing, minimizing household disruption, and engaging home owners and occupants. This literature review builds on a similar review from several years ago (Less and Walker, 2014). The current review focuses on efforts in the intervening years. This literature review is part of a larger DOE study of deep energy upgrades that includes industry surveys and development of cost-stack analyses. For this review, we gathered data not just from the published literature, but also from practitioners in conjunction with other aspects of the larger DOE study. In some cases, we refer to comments from specific individuals or companies, or refer to specific products by name. This is not intended as an endorsement, but rather to provide clarity on sources of information and examples of relevant technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

14 Steps to Creating Value in Cost and Schedule Resources for Nuclear Waste Management - 20188

While Waste Management budgets are shrinking, DOE required cost and schedule controls are becoming increasingly stringent. At the same time, there is a scarcity of adept, qualified, and competent projects controls staff who both understand nuclear waste management and are capable of addressing today's cost and schedule challenges. In response, we have developed a systematic approach to training and mentoring project controls staff. The approach is based on the observations and lessons learned on projects, both successful and unsuccessful, over the past 20 years. During that time, we evaluated staff development and used that experience to design a program that progresses the maturity, knowledge and experience of the individual. The program is based on the unique needs of cost and schedule specialists while incorporating the best leadership and managerial applications. The system is not limited to developing individual software skills, which is a primary focus of many project controls training programs. Instead, our system develops an individual's soft and hard skill sets. The system develops the user's skill, talent, attitude, and drive to do the best job possible. It focuses on all aspects of becoming a more productive technical team while accepting responsibility for individual growth. It also enhances the project controls team by setting up checks and balances that everyone is aware of and participates in. The system is based on 14 steps of increasing complexity in knowledge and application. The system clarifies roles, responsibilities and expectations. It helps eliminate uncertainty and reduces stress on staff and managers. It contains everyday routine actions and is simple to implement. It allows the development of a consistent rhythm to staff growth and development. Mastering the steps will allow the user to achieve excellence in cost and schedule control. The 14 steps are: 1 - Key Performance Objectives, 2 - Check Lists, 3 - Desktop Guides, 4 - System Description, 5 - Procedures, 6 - Software and On the Job Training (OTJ), 7 - Traceability Checks, 8 - Surveillances, 9 - 32 Criteria, 10 - The Contract, 11 - Customer/Government Guidance, 12 - Training and Mentoring Others, 13 - Master your weekly and daily schedules, 14 - Improving your interpersonal skills. Application and mastery of this system will produce better cost and schedule control results. Your project controls staff will write better reports, analyze data better, make better use of their time, and be more valuable to decision makers. If followed rigorously, our system will produce a great project controls team, which is invaluable to the success of each project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

HarDWR - Cumulative Water Rights Curves

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. This product is the dataset used as input to the WBM model (Grogan et al., in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (submission pending). This database contains 1,744 individual .csv files, two for each Water Management Area (WMA; see here) in the 11-state region. File naming convention: WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either S for surface water rights, or G for groundwater rights. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the ### unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al., in review) The code related to the creation of this dataset can be viewed within HarDWR GitHub Repository/dataCumulationCurves.

Economics↗
DOE OSTI2020

HarDWR - Cumulative Water Rights Curves

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on Harmonized Water Rights Records v2.0 sourced from WestDAAT - Added "Unspecified" was a water source category, and files associated with this category v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description This product an updated version of the database used as input to the WBM model (Grogan et al. in review; Grogan et al. 2022), and is the result of the step creating cumulative water rights curves described in Lisk et al. (2024). This database contains 2,667 individual .csv files, three for each Water Management Area (WMA) in the 11-state region. File Naming WMA_[###]_[X]W.csv, where [###] is the unique identifier for each WMA, and [X] is either "S" for surface water rights, "G" for groundwater rights, or "U" for unspecified. Column headers in each file: Year: the priority date year CUML: the total cumulative water rights allocated up to this priority date year (ft3s-1) Irrigation: The percent of cumulative water rights allocated to the Irrigation category up to this priority date year (%) Domestic: The percent of cumulative water rights allocated to the Domestic category up to this priority date year (%) Livestock: The percent of cumulative water rights allocated to the Livestock category up to this priority date year (%) Fish: The percent of cumulative water rights allocated to the Fish category up to this priority date year (%) Industrial: The percent of cumulative water rights allocated to the Industrial category up to this priority date year (%) Environmental: The percent of cumulative water rights allocated to the Environmental category up to this priority date year (%) Other: The percent of cumulative water rights allocated to the Other category up to this priority date year (%) In addition to the database files, there is a companion .csv file, called stateWMAs_ID.csv. The main purpose of this file is to provide the means of translating between the [###] unique identifier and the various other id of the WMA the file is attached to. This translation file has five columns, which are: basinNum: The official state given alpha-numeric identifier of the WMA basinName: the state provided English name of the area, where applicable state: the state name uniID: a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID ID: a unique numeric identifier we created as a requirement for the files to be used within WBM (Grogan et al. in review) For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in the study region. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the second index in this object, the data for California will also be in the second index for each accompanying list. wmasRightsPersGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for groundwater. wmasRightsPersSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for surface water. wmasRightsPersUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The data frames in this object are the same as the above described .csv files, specifically for water from an unspecified source. wmasRightsTotsGrd: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for groundwater. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsSur: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for surface water. This object is provided for convenience to check out original total values, if desired. wmasRightsTotsUnsp: A list of nested lists of data frames. Each state has one entry in the top level list and consist of a list with one data frame per WMA. The values in the data frames of this object would be the equivalent to multiplying the CUML column by the sector percentage columns to create the sector total ft3s-1, specifically for water from an unspecified source. This object is provided for convenience to check out original total values, if desired. wmaIDByState: A list of data frames which contain the by state allocation by WMA matrix. There is a matrix for each state in a different data frame within the object.

Economics↗
DOE OSTI2020

Demonstration of μCHP in Light Commercial Hot Water Applications

Internal combustion engine driven combined heat and power (CHP) systems produce power while the waste heat is recovered and used for another purpose. For µCHP systems (less than 50kWe output) overall efficiencies can reach over 90% for products currently on the market throughout the world. On a fuel basis this offers an advantage over using grid-based power and another fuel for heat. Additionally, the cost of natural gas on an energy unit basis is significantly less expensive than electric power. This difference can lead to substantial savings for the end user of a CHP system. In some parts of the world, particularly Germany and Japan, µCHP has become a common part of the heat and distributed generation equipment mix. Market analysis conducted in 2012 showed that in North America there is potential of a 5,300 units per year market for µCHP, resulting in an annual energy savings of approximately 13.5 TBtu and more than $84 million in annual customer savings. However, µCHP still has not seen much market penetration in North America. This study helps to identify some of the reasons why, address roadblocks that still need to be overcome and provide experience to established best practices. Nine commercial sites were initially identified (fitness club, surgical center, senior community, resort and spa, commercial laundry, two multi-family housing, restaurant and manufacturing facility). Systems from two different manufacturers were installed at five sites total, but due to unforeseen circumstances, only three of those sites were finally commissioned: test data were collected by Oak Ridge National Laboratory. While not all systems were installed as intended, the project resulted in the following key findings: Micro combined heat and power is an unfamiliar technology for building owners and plumbing and electrical contractors that serve the buildings most suited for µCHP. Manufacturers will need to be aggressive in providing training and providing broad support to successfully bring the technology to market.; The proper integration of µCHP into other building systems is the most critical part of a successful installation. Manufacturers will need to be able to provide the expertise to train, advise and support the mechanical contractors during the design and installation of the heat integration system.; Regulations governing µCHP varies across the country. There are a few UL standards (UL 2200 and UL 1741) that apply nationally. Emissions are governed by EPA except in California where the California Air Resources Board (CARB) has established their own standard. Requirements that dictate installation and interconnection are dependent on local building codes and local utility processes and requirements. Some out of date building codes do not offer clear guidance for these requirements, leading to confusion. This makes developing training and determining broadly applicable best practices difficult.; Installation costs of µCHP are a key factor in making an installation successful. It is critical that these costs and all national, state and local regulations be understood and accounted for by all parties involved in the installation before a project is undertaken.; A robust customer service organization is important to meet the needs of the customers. These systems require annual maintenance and service and local capability is needed to keep costs inline.

03 NATURAL GAS↗
DOE OSTI2023

The Port of Los Angeles Zero- and Near-Zero-Emission Freight Facilities Shore to Store Project

The City of Los Angeles Harbor Department (Harbor Department, Port of Los Angeles) partnered with Equilon Enterprises LLC (d/b/a Shell Oil Products US) (Shell), Toyota Motor North America (Toyota), and Kenworth Truck Company (Kenworth) partnered with the Port of Hueneme, United Parcel Service, Total Transportation Services Inc., Southern Counties Express, Toyota Logistics Services, Air Liquide, National Renewable Energy Laboratory, Coalition For A Safe Environment, and the South Coast Air Quality Management District to introduce hydrogen fuel into the Southern California drayage truck market by demonstrating near-commercial heavy-duty hydrogen fuel cell electric trucks at and between freight facilities throughout the region, while continuing to lay the groundwork for battery-electric operations. The Shore to Store project built on project team experience to help realize our vision of zero-emission freight operations in the future. Ten Kenworth zero-emission Class 8 fuel cell electric trucks, integrated with Toyota’s fuel cell drive technology, were operated by United Parcel Service, Total Transportation Services Inc., Southern Counties Express, and Toyota Logistics Services in commercial service. The demonstration fleet fueled at the Shore to Store hydrogen fueling stations that were built in Ontario, California, and Wilmington, California. An additional station at the Port of Long Beach (Portal Station) was available for fueling the fleet. Portal Station was supported by grants from the California Energy Commission and South Coast Air Quality Management District and used as match funding for the Shore to Store project. The Port of Hueneme demonstrated two battery-electric yard tractors, and Toyota Logistics Services demonstrated two zero-emission forklifts at their warehouse facility, showcasing elements of the entire supply chain operating with zero emissions. This project showcased a snapshot of the zero-emission supply chain of the future, providing a model by which freight facilities can support zero-emission operations. The Shore to Store project: Demonstrated the technical feasibility of zero-emission hydrogen fueled Class 8 heavy-duty trucks and electric cargo handling equipment in rigorous goods movement operation throughout the Southern California region. Cumulatively completed 59,212 miles of zero-emission operation, with 21,650 miles driven in-service with the fleets, using hydrogen fuel cell electric Class 8 heavy-duty trucks. Operated zero-emission yard tractors for a total of 2,749.6 hours. Created direct localized emission reductions in designated disadvantaged communities, including those in zip codes 90220, 90247, 90248, 90731, 90744, 90802, and 91761. For the 59,212 miles of zero-emission operation, reduced emissions by an estimated total of 15.5 kg NOX (0.163 g/km), 1.01 kg SOX (0.0106 g/km), and 304.8 metric tonnes of CO2e (3.2 kg/km) compared to diesel baseline vehicles including both tailpipe emissions and the emissions from producing the fuel sources.

08 HYDROGEN↗
DOE OSTI2022

Environmental Flow Requirements from FERC Licenses Across the US

Environmental flow requirements included in Federal Energy Regulatory Commission (FERC) hydropower licenses are important for balancing natural properties and benefits of river ecosystems (e.g., healthy species, recreation, water supply, flood control) supporting hydropower production. In some cases, environmental flow requirements may limit operational flexibility given current operational schemes and make a hydropower plant less able to provide power to the electric grid on demand. Hydropower plants may gain some flexibility as hydropower scheduling time periods are made to be more responsive to the short-term needs of an energy grid increasingly reliant on intermittent renewables. However, many flow requirements focus on the daily, monthly, or seasonal flow fluctuations which matches the time scale of most paradigms linking flow alterations to the health of river ecosystems. This dataset seeks to provide a greater understanding of how flexibility in environmental requirements can be leveraged to create positive outcomes for both the power system and the environment. It contains information on environmental flow requirements from the Protection, Mitigation, and Enhancement section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The information on environmental flow requirements was extracted from the PM&E section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The flow requirements were then categorized into flow augmentation categories based on whether the license stated a specific water management purpose for the given requirement called augmentation categories (i.e., fisheries or habitat, recreation or boating, industry, and general or unspecified; Table B). Requirements were also grouped into flow type categories (e.g., minimum flow rate, maximum flow rate, ramping rate). Additional information related to flow requirements such as the augmentation time-period and whether the flow rate was continuous (i.e., condition must be present at all-times) or instantaneous (i.e., condition present at a point in time) was also extracted from the licenses. Some licenses had specific flow requirements based on whether the project was in a wet, dry, or normal water year. If that information was presented in the license, it was also included in the data set. The location within the project was noted, hereafter, zone, in the dataset for flow requirements relating to specific areas of hydropower projects (Dam, Powerhouse, Bypass Reach). Maximum discharge capacities of hydropower facilities were also extracted from both the Existing Hydropower Assets (EHA) data set and the National Inventory of Dams (NID) databases. Each facility was coded with project identification codes from the EHA dataset to facilitate cross-referencing between datasets.

13 HYDRO ENERGY↗
DOE OSTI2024

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↗
DOE OSTI2020

Data for Post-Access Report: Tidal Energy Resource Characterization and Model Validation via the Assessment of Cost-effective Spatially Distributed Current Measurements from microFloat Swarms

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for producing accurate predictions of tidal energy production over larger arrays of tidal turbines. The data contained in this archive includes field observations of water velocity from a series of short surveys in Agate Pass taken on August 20th, 2020 using station-keeping ADCP (acoustic doppler current profiler) measurements, drifting downward-looking ADCPs, and microFloats, gathered by researchers at APL-UW under a previous project. It also includes high-resolution hydrodynamic model runs for the site during that time generated under TEAMER support. An explanatory file (.pdf format) describes the survey and field data structure. Processed data is stored in .mat format. Survey summary: start time, number of floats, water level. microFloat data: - Cleaned data for each float in survey, - Time series of position (lat., lon.), depth (relative to surface), and horizontal velocity (u, v) Drifting ADCP data: - Cleaned data for each drifting ADCP in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) Stationary ADCP data: - Cleaned data for each station-keeping data set in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) FVCOM (Finite Volume Coastal Ocean Model) model outputs: Water level and velocity, as well as derived variables (e.g., power density) from the final refined model simulations for the Agate Pass subdomain. Contained in NetCDF and ASCII files for the duration of August 18th and 20th 2020 field surveys. Additional scripts for processing the data and generating the figures in the report are included.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Impact of mid- Z gas fill on dynamics and performance of shock-driven implosions at the OMEGA laser

Shock-driven implosions with 100% deuterium (D 2 ) gas fill compared to implosions with 50:50 nitrogen-deuterium (N 2 ⁢D 2 ) gas fill have been performed at the OMEGA laser facility to test the impact of the added mid-Ζ fill gas on implosion performance. Ion temperature (Τ ion ) as inferred from the width of measured DD-neutron spectra is seen to be 34%±6% higher for the N 2⁢ D 2 implosions than for the D 2 -only case, while the DD-neutron yield from the D 2 -only implosion is 7.2±0.5 times higher than from the N 2⁢ D 2 gas fill. The T ion enhancement for N 2 ⁢D 2 is observed in spite of the higher Z, which might be expected to lead to higher radiative loss, and higher shock strength for the D 2 -only versus N 2 ⁢D 2 implosions due to lower mass, and is understood in terms of increased shock heating of N compared to D, heat transfer from N to D prior to burn, and limited amount of ion-electron-equilibration-mediated additional radiative loss due to the added higher-Z material. Further, this picture is supported by interspecies equilibration timescales for these implosions, constrained by experimental observables. The one-dimensional (1D) kinetic Vlasov-Fokker-Planck code ifp and the radiation hydrodynamic simulation codes hyades (1D) and xrage [1D, two-dimensional (2D)] are brought to bear to understand the observed yield ratio. Comparing measurements and simulations, the yield loss in the N 2 ⁢D 2 implosions relative to the pure D 2 -fill implosion is determined to result from the reduced amount of D 2 in the fill (fourfold effect on yield) combined with a lower fraction of the D 2 fuel being hot enough to burn in the N 2 ⁢D 2 case. The experimental yield and T ion ratio observations are relatively well matched by the kinetic simulations, which suggest interspecies diffusion is responsible for the lower fraction of hot D 2 in the N 2 ⁢D 2 relative to the D 2 -only case. The simulated absolute yields are higher than measured; a comparison of 1D versus 2D XRAGE simulations suggest that this can be explained by dimensional effects. The hydrodynamic simulations suggest that radiative losses primarily impact the implosion edges, with ion-electron equilibration times being too long in the implosion cores. The observations of increased T ion and limited additional yield loss (on top of the fourfold expected from the difference in D content) for the N 2 ⁢D 2 versus D 2 -only fill suggest it is feasible to develop the platform for studying CNO-cycle-relevant nuclear reactions in a plasma environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Modeled sensitivity of multi-MA accelerator performance to electrode contaminant inventory

Significant particle-in-cell code development has enabled simulations of power flow in multi-MA accelerators to include the desorption of surface contaminants, their ionization into surface plasmas, and the impact of these plasmas on efficiency. The simulations base desorption on an Arrhenius equation, whose most significant unknown is the surface contaminant inventory. The sensitivity of power-flow simulations to this inventory is studied here using Sandia National Laboratories' Z accelerator with a 7-nH MagLIF load [Phys. Plasmas 17, 056303 (2010)]. Simulations are conducted in 3D cylindrical coordinates for the current-adder, or “convolute,” region of Z and in 2D for the final feed only. Simulated contaminant inventories are varied from 1 to 32 monolayers (MLs) in 2D, and 2 to 4 ML in 3D. The results reveal sensitivities to the local ratio of E/B⁠. The high B-field, low E-field region near the short-circuit load is insensitive to the contaminant inventory, where assumed values of 4–32 ML change the load current by ≤ 2%, and agree with experiment to within 2% at peak current. A 1-ML value is the outlier, increasing the load current by 5%, but still within measurement uncertainty. In contrast, the relatively higher E-field, lower B-field convolute region has slower contaminant desorption and higher-magnitude E-field penetration of the surface plasmas. The current loss in the convolute region does increase with contaminant inventory. The loss assuming 4 ML is 12% larger than for 2 ML, with 4 ML being the better match to experiment.

Arrhenius equation↗
DOE OSTI2024

Moisture Performance of Unvented Attics With Vapor Diffusion Ports and Buried Ducts in Hot, Humid Climates

Energy efficiency measures, such as cool roofs, radiant barriers, interior radiative control coatings, and buried ducts are increasing in popularity and are promoted by energy codes because of their energy-saving potential. However, these strategies can also pose moisture risks in attics by lowering surface temperatures and increasing condensation potential and moisture accumulation. Of particular concern in hot-humid climates is dripping condensation on cold air-conditioning ductwork in the summer - commonly referred to as duct "sweating" - which threatens the attic floor with conditions conducive to mold growth and rot. One strategy to mitigate these moisture issues is to wrap ductwork in thicker duct-wrap insulation with an integrated exterior vapor barrier, but thick duct wrap can be difficult to come by, expensive, and unwieldy to work with. This study explores an alternative strategy of reducing moisture issues while embracing energy efficiency by using unvented attics with vapor diffusion ports and buried ductwork in hot-humid climates. Vapor diffusion ports have been studied so far in a wide range of U.S. climates, mostly in the context of conditioned attics. In this study, the strategy is implemented in the novel context of hot-humid climates with ductwork sitting atop blown-in attic floor insulation in unconditioned attics. Using a combination of field experiments and hygrothermal modeling, the findings of this project indicate that an unvented attic with vapor diffusion ports and buried ducts may be a key part of a successful low-cost method for reducing the attic moisture load by venting excess moisture out of the attic, keeping duct-jacket surfaces above dew point temperature, and keeping the roof deck safe from winter moisture accumulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Demonstration of x-ray fluorescence spectroscopy as a sensitive temperature diagnostic for high-energy-density physics experiments

We present the use of x-ray fluorescence spectroscopy (XFS) to a sensitive temperature diagnostic in shocked foams at temperatures of 30–75 eV. Cobalt-doped foams were shock compressed using a planar drive at the OMEGA laser facility and photo-pumped with a Zn He⁢𝛼 x-ray source. Analysis of the resulting cobalt 𝐾⁢𝛽 x-ray fluorescence spectra using collisional radiative codes allows the temperature to be determined in the shocked foams. Furthermore, this method provides a sensitive and robust technique to determine temperatures in high-energy-density physics experiments in the tens of electronvolts temperature range. In these experiments, we find that radiation hydrodynamic simulations predict a lower temperature in the shocked foams compared to analysis of the XFS data using collisional radiative models. Although additional experiments with an independent temperature diagnostic to absolutely calibrate XFS spectra for these conditions will be required to resolve this discrepancy, these results demonstrate the excellent temperature sensitivity of XFS spectra for high-energy-density physics experiments.

Atomic spectra↗
DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Package Data for CERF-Data Centers

This dataset contains sample input 100m resolution raster files for running the CERF-DC python package (see https://github.com/IMMM-SFA/cerf_data_centers) at the state level across the CONUS. Due to data availability constraints, some of the items included in this dataset are proxies or assumptions for siting factors used in the model. These are individually noted in the item descriptions and can be exchanged with more detailed information upon availability. Data Descriptions The following raster files are included in the data download: state_siting_region.tif — State areas identified by state FIPS code composite_siting_suitability.tif — Value of 1 indicates suitable siting location, 0 otherwise. The following areas are excluded from siting: Areas within 300m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds Developed lands Areas >0.8 km (0.5 miles) from developed lands land_value_dollar_per_sqft.tif — USD per square foot (sqft) derived from USDA $/acre land cost personal_property_tax_rate.tif — Personal property tax rate by state. Uses an assumed 0.0125 personal property tax rate for states with personal property tax, 0 for states without personal property tax. real_property_tax_rate.tif — Real property tax rate. Based on county level residential real estate property tax rates. sales_tax_rate.tif — Sales tax rate by state. mechanical_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through mechanical processes based on local water stress and humidity levels. water_cooling_fraction.tif — Fraction of year (values between 0 and 1, inclusive) that the data center would be cooled through evaporative (water cooled) processes based on local water stress and humidity levels. distance_to_substation.tif — Distance to nearest substation in hundreds of meters (i.e., value of 1 equals a distance of 100m). Offshore areas have a value of 0. industrial_electricity_rates_dollar_per_kwh.tif — USD/kWh industrial electricity rates. Represents the average industrial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. commercial_electricity_rates_dollar_per_kwh.tif — USD/kWh commercial electricity rates. Represents the average commercial rate across all utilities that operate within a given county. Values are derived from the US Utility Rate Database. data_center_market_locations.tif — Grid cells with positive values represent the centroid of existing data center market clusters. The value of non-zero grid cells represents the number of data centers in the market cluster. All other grid cells have a value of 0. Geospatial Metadata CRS: Albers Equal Area Conic (ESRI:102003) Extent: -2415585.0000000023283064,-1441981.2605773280374706 : 2384414.9999999976716936,1708018.7394226719625294 Dimensions: X: 48000 Y: 31500 Bands: 1 Origin: -2415585.0000000023283064,1708018.7394226719625294 Pixel Size: 100,-100 Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, 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 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 Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall↗