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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Meteoric 10Be Flux Calibration Data for the East River Watershed, Colorado, USA

This data package contains tabular and geospatial data used to quantify and model meteoric beryllium-10 fluxes in the East River watershed, Colorado, USA. The tabular component includes calibration-site data from five glacial moraine sites and includes environmental variables used to evaluate spatial controls on meteoric 10Be delivery, including elevation, mean annual precipitation (MAP), mean snow depth, and mean snow water equivalent (SWE). These site-level data were used to compare observed fluxes with environmental gradients across the watershed and to evaluate the effects of erosion correction on flux estimates. The package also includes supporting slope and curvature values used to assess topographic inputs to the erosion analysis. A second component of the data package contains updated manuscript tables and regression outputs used to summarize the relationships between meteoric 10Be flux and environmental predictors. These tables include meteoric 10Be sample information and AMS results, site-level environmental values, site-level meteoric 10Be inventory and flux values, watershed-averaged predicted fluxes, soil bulk density measurements, fine-fraction values, soil pH measurements, and regression statistics including slope, intercept, coefficient of determination, and p-value. The regression products include both standard linear regressions and regressions in which the intercept is constrained to pass through zero, and they support the analyses presented in the companion manuscript. Together, these tabular files provide the numerical basis for the manuscript tables and the regression-based interpretation of meteoric 10Be flux variability in a snow-dominated mountain watershed. The geospatial component of the package consists of GeoTIFF raster files used to generate the map products presented in Figures 2 and 6 of the companion manuscript. These rasters represent watershed-scale spatial layers for environmental variables and regression-based predictions of meteoric 10Be flux. This dataset contains comma-separated values files (.csv), Microsoft Excel files (.xlsx), GeoTIFF raster files (.tif), and upporting metadata files, including CSV data dictionaries and readme text files (.csv, .txt). The tabular files can be opened with standard spreadsheet software, and the raster files can be viewed and analyzed in GIS software such as ArcGIS Pro or QGIS. Together, these files document the numerical and spatial datasets used to calibrate and predict meteoric 10Be delivery in the East River watershed.

East River↗
DOE OSTI2020

Distribution Development for Residual Inventory at the New York West Valley Site - 20400

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351 ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into Agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States. NFS, a private company, built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations ended in 1972 and never reopened, leaving behind radioactive and chemical wastes. Operations led to contamination in a number of facilities and locations. Some of that contamination has migrated from waste disposal zones to other layers, formations, and features on and off the WNYNSC. Phase I decommissioning activities are ongoing and involve the removal of a number of areas and structures that have been associated with contamination. The purpose of this work is to outline the approach for characterizing contamination not associated with disposed wastes, contaminated structures, or specific releases. In this work, the term, residual radiological activity, is used to describe environmental contamination that exists subsequent to the completion of Phase I decommissioning activities, that is not associated with disposed wastes, contaminated structures, or specific releases. Contamination from the Site was quantified relative to data that characterize the concentrations of radionuclides that exist in background. Background concentrations are those present in the area but having no influence from Site related activities. The existence of residual radiological activity that is elevated relative to background has the potential to contribute to future risks to human health and the environment. As a consequence, the residual inventory information is used to inform the West Valley Probabilistic Performance Assessment (PPA) model to characterize potential future risks to human health and the environment. The centralized West Valley Data Management System (DMS) was the source of information for the data assembled in this analysis. The DMS is a fairly large compilation consisting of thousands of records from investigation studies, with sample dates ranging from 1990 to present. Samples from monitoring wells, boreholes, geoprobe studies, surface water, surface soils, storm water outfalls, ventilation stack filters, plant and animal tissues, and more are included in the DMS. Results are typically reported in units of activity per unit volume. For the purpose of the analyses presented here, all results were converted into consistent units of pCi per unit volume. Since 1990, data have been collected from various locations across the WNYNSC at different times with varying frequency over the course of several decades. As a consequence, a number of potential issues can arise with respect to the assembly of a dataset that is deemed adequate for the characterization of residual radiological activity. These issues were assessed and resolved to the extent possible through careful consideration of the properties of the distributions. The intent was to use data which characterize the current state of the Site. Radionuclides can be designated to one of several groups depending on their origin. In this work the groups considered were 1) Naturally Occurring Radioactive Material (NORM), 2) fallout, and 3) Other (including power plant, medical research, etc). This grouping is a useful construct with respect to the interpretation of fixed laboratory results. For example, NORM radionuclides that exist within a decay chain should have approximately equivalent distributions of concentrations if they are representative of background conditions. Insights such as these can be used as a check to identify sample results that need to be further investigated or omitted due to issues associated with reported results from fixed laboratory analyses. This type of analysis provided a foundation for the assessment of the adequacy of sample results for use in subsequent components of an assessment. The general process for the assessment of residual radiological contamination at the Site consists of a sequence of several steps. First, for each analyte, several statistical tests were performed to assess the weight of evidence against the null hypothesis that the mean of the distribution of concentrations was equal to zero. If the mean of the distribution of concentrations for a given radionuclide was not found to be greater than zero, then it was removed from consideration as a component of the residual radiological contamination. If there was significant evidence to reject the hypothesis of the mean being equal to zero, the second step was to compare the distribution of the data from the Site to that of the corresponding background. A suite of tests was used to compare the distributions of the site and background data. The results of these tests were collectively used to determine if site data are elevated relative to background. The third step was to develop distributions using a Bayesian framework to characterize the distribution of mean of the increment present above background for each of the radionuclides. The Bayesian model implemented allowed for the comparison of site-specific records to background concentrations to better approximate contamination attributed to the Site. A final screening step was employed for radionuclides that exceed background. This screening step compared 95% upper confidence limits (UCLs) from the increment distribution developed in the previous step to the risk screening levels. This approach yields a list of analytes that were determined to be elevated relative to background.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Natural Gas LCA

This presentation was provided via a pre-recorded presentation at the 2025 Coordinating Research Council Life Cycle Analysis of Transportation Workshop at Argonne National Laboratory on October 9, 2025. The presentation provides an overview of the methods and data sources used in the report, Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile and briefly discusses discrepancies between top-down and bottom-up inventory methods and how those might be overcome.

LCA↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Validating and Comparing Energy Estimation Methods at Water Resource Recovery Facilities

Water resource recovery facilities play a crucial role in the water-energy nexus, consuming a substantial amount of energy in the United States. Growing treatment volumes and more stringent water quality standards are expected to increase the amount of energy needed to treat wastewater, but accurately estimating energy consumption and potential remains challenging due to variability in scale, treatment methods, and effluent treatment standards. In this study, we used publicly available data to evaluate the accuracy of methods for estimating energy consumption and generation, then quantified uncertainty based on key factors like flow rate, treatment level, and geographic location. To validate methods, we estimated energy consumption and generation at the facility-level, then compared estimates to self-reported data from utilities in major U.S. cities. We found that process models of treatment trains under best practice configurations were accurate relative to other methods for estimating electricity use, total energy use, and electricity generation from biogas utilization, and less complex methods based on effluent treatment level and prime movers also performed well for estimating electricity consumption and generation, respectively. Applying the evaluated methods to a national inventory of treatment facilities, we estimate that annual energy consumption ranged from 56.3 x 10^3 to 82.5 x 10^3 TJ in 2012 and 83.6 x 10^3 to 127 x 10^3 TJ in 2042. Our results indicate that not all estimation methods are suited for every use case, so we recommend that researchers and practitioners select an estimation method based on data availability and desired computational intensity.

Hodson, Abigayle↗
DOE OSTI2025

A building performance-based approach to determining energy resilience for grocery stores in the event of a power outage

Evaluating progress toward a built environment that is best equipped to serve communities during a regional power outage will require metrics that capture the energy resilience of the unique buildings and businesses most crucial to the well-being of those nearby. We focused on grocery stores as key buildings for which access, and thus energy resilience, is critical during a disaster when power is unavailable. We evaluated the energy resilience of these buildings by offering and testing building-scale metrics that assess business continuity potential during a power outage. Metrics proposed in this study are calculated based on the unique power loads characteristic to grocery stores, primarily refrigeration and maintaining safe indoor environmental conditions. Building simulations based on varying levels of backup power were carried out against occupant safety and comfort parameters to apply these metrics, with additional criteria imposed on grocery stores to capture the inventory and sales loss from food spoilage resulting from a lack of refrigeration power. Findings from this study demonstrate the feasibility of our proposed metrics and methodology to serve as a low-data burden means for stakeholders to evaluate the energy resilience of grocery stores, with greater implications in helping to understand the impact on community-scale energy resilience.

Siegel, Lino Sanchez↗
DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 2005

The survey was an on-board survey of transit riders on all regular route services for bus and light-rail in the Minneapolis-Saint Paul metropolitan area. The primary purpose of the study was to gather the data needed to update the mode choice models that are an integral component of the regional travel forecast model maintained by the Metropolitan Council, the metropolitan planning organization for the Minneapolis-Saint Paul metropolitan area. The survey instrument focused on identifying characteristics of the trip taken by each transit rider, including origin, destination, trip purpose, and mode of access. The survey also collected relevant socioeconomic and demographic information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Chemical Fractionation is not a Constant: Revisiting Bomb Vapor Chemistry

The debris produced by a nuclear explosion forms a hazard to response, can serve as a record used to interpret the event, and may persist in the environment necessitating long term management. Hence, understanding the radiochemical inventory of nuclear debris remains an important area of study, particularly the behavior and resulting distribution of actinides and fission products. Despite formation in a high energy environment, it has been recognized for decades that the chemical and isotopic composition of debris rarely, if ever, captures a homogenized blend of the bomb products. Instead, during cooling and debris formation, a variety of chemical processes cause separation of the different constituents. This process of chemical fractionation creates debris with a variety of different radionuclide inventories. Here we provide an overdue re-examination of our historic basis for understanding chemical fractionation in nuclear explosions through the context of new characterization of a large set of historical nuclear test data. Finally, we then discuss the implications of our findings for advancing models of radionuclide distribution and postdetonation chemical fractionation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗
DOE OSTI2025

2016 US Petroleum fuels Life Cycle Baseline Data Package

This data package accompanies the report "2016 U.S. Petroleum Fuels Life Cycle Baseline." It contains the openLCA life cycle model that generated the results and an Excel spreadsheet that contains well-to-tank life cycle inventory for all products.

Life Cycle Analysis Options - Fuels↗
DOE OSTI2021

Nuclear Material Process Modeling at the Y-12 National Security Complex

Dynamic simulation modeling is used at Y-12 to evaluate and forecast nuclear material inventories and production capacities to ensure that future supply can meet mission demand. Model outputs are analyzed by numerous Y-12 organizations and programs and coordinated with NNSA’s Office of Secondary Stage Production Modernization. Data-driven decisions for both short-term and long-term strategic planning for Y-12 mission execution are informed by the model. Dynamic simulation modeling capabilities for Y-12 nuclear material production continue to be expanded and refined.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Radial Deconsolidation Leach-Burn-Leach of Five AGR-3/4 TRISO Fuel Compacts after Post-Irradiation Heating Tests

Five AGR-3/4 fuel compacts were previously heated in the Fuel Accident Condition Simulator (FACS) furnace. Three of these compacts were also reirradiated in the Neutron Radiography (NRAD) reactor before the FACS tests. One of these was heated to 1200°C, two were heated to 1400°C, one was heated to 1600°C, and one was held for a period of time at 1600 and 1700°C. After these FACS tests, the compacts were subjected to destructive post-irradiation examination (PIE) via radial-deconsolidation-leach-burn-leach (RDLBL) at INL. The RDLBL process deconsolidated the compacts in multiple radial steps, followed by a final, single-step axial deconsolidation. The samples generated at each step were analyzed for isotopes of key fission products and actinides. After each deconsolidation step, the compact volume was assessed, and this was used to normalize the measured quantities of nuclides of interest to give volumetric concentrations as a function of radial position within the compact. The total inventories of measured fission products and actinides and the radial concentration profiles were compared with their sibling compacts within the same capsule (similar irradiation conditions) that went through RDLBL in the as-irradiated state. These data will be used to refine the fission product transport models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Passive Temperature Sensors for Nuclear Applications

Thermocouples are generally used to provide real-time temperature indications in instrumented tests performed at material and test reactors. Passive temperature monitors, such as Silicon Carbide (SiC) and melt wires, may be included in such tests as an independent technique of detecting peak temperatures experienced during irradiation. In less expensive static (drop-in) capsule tests, which have no leads attached for real-time data transmission, melt wires, and SiC temperature monitors (TMs) are essentially the only possibility for peak temperature indication. A melt wire involves placing materials (wires) of a known composition and melting temperature in a test. An inventory is maintained at Material Science Laboratory (MSL) for melt wires ranging in temperatures from 30°C to 1500°C. Unfortunately, melt wires are limited in that it can only detect whether a single temperature is or is not exceeded (melt wire melted or not). SiC TMs, which can also be used to detect peak irradiation temperatures, are advantageous because a single monitor can allow to determine the peak temperature reached within a relatively broad range (100 – 1200°C) resulting in accuracies within ±20°C. Irradiation temperature is determined by measuring a property change after isochronal annealing or during a continuously monitored annealing process using specialized equipment at MSL. Recent research has produced a passive monitor known as sublime temperature monitor. This passive sensor has the capability of recording temperature gradients and pinpointing exactly where a temperature is located along that gradient. Long measurement lengths are achieved with very high accuracy in the location of desired temperature measurements (±2 mm over a 1 m span); however, this sensor has not been deployed in a nuclear reactor. This article will focus only on passive temperature sensors currently being researched and implemented under the Advanced Sensors and Instrumentation (ASI) program at Idaho National Laboratory (INL).

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

SCALE inventory and reactivity analysis as part of the Hermes 2021 PSAR review

The readiness of SCALE for comprehensive studies of pebble-bed reactors has been demonstrated through detailed analysis of a fluoride salt–cooled, high-temperature pebble-bed reactor (PB-FHR). The methods developed for pebble-bed reactor modeling in SCALE, particularly for inventory generation, have proven effective in gaining insights into the reactor physics of this advanced reactor. Excellent agreement with another code package has been observed, further highlighting SCALE’s strong performance. The SCALE results supported the US Nuclear Regulatory Commission’s construction permit application review of the Hermes low-power PB-FHR demonstration reactor. A SCALE model of the Hermes reactor was developed at Oak Ridge National Laboratory using information from the Preliminary Safety Analysis Report (PSAR) and supplemented with publicly available data. SCALE reactivity coefficient simulations reproduced PSAR results within 1σ statistical uncertainties. Sensitivity studies emphasized the importance of graphite specifications for accurate keff predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

1990 The Twin Cities Metropolitan Area Travel Behavior Inventory

The Twin Cities Metropolitan Area 1990 Travel Behavior Inventory, or home interview survey, was conducted by Twin Cities Metropolitan Council—Saint Paul to document how Twin Cities residents use the streets, highways, and transit services in the region. The survey collected demographic, socioeconomic, and travel data for 9,476 households. Respondents were asked to record their travel and activities for a 24-hour period, in which 98,535 trips were documented. In addition to the home interview survey, the study included an establishment survey, a transit survey, external station traffic counts, and an external station origin/destination survey.

1Hz data↗