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Projected Operational Energy Life Cycle Data 2025

These excel files contain the environmental emission projections for key building energy sources: electricity, natural gas, propane (LPG), and fuel oil. The sources and methods are provided in the report "Projected Operational Energy Life Cycle Data Development: 2025 Update." The report and data are an update to the data previously posted here: https://netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

annual energy outlook

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Wave

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points. NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows: {technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “wavePacWave-Noacc_4-400.zip” represents the 25 minute-long experiment using the PacWave’s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. An experiment, labeled “characterization_200.zip”, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.

08 HYDROGEN

Lawrence, Massachusetts, Residential Building Efficiency and Electrification Analysis [Slides]

As part of the Communities Local Energy Action Program (CLEAP), the Lawrence Stakeholders Coalition (LSC) is interested in assessing and understanding the potential for and pathways to electrification for the City of Lawrence. The LSC's main questions are: What is the impact of various electrification packages on residential electricity bills and what types of buildings should the LSC target for electrification plus weatherization packages? This technical assistance, using ResStock tool modeling, aims to assist the Coalition's electrification and energy burden reduction planning by: 1. Providing cross-cutting data on housing stock characteristics, energy burden characteristics, fuel types, energy consumption, and system efficiency; and 2. Providing information on upgrade package costs, emissions reduction, and energy reductions by prioritized housing segment. The ResStock analysis presented here focuses on opportunities to reduce energy burden, energy consumption, and energy bills for single family homes, multifamily buildings, and mobile homes.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Data Sharing as a Catalyst for Expanding the Energy Frontier

As the energy landscape evolves to include technologies such as geothermal energy, comprehensive data become essential for driving innovation and scalability, particularly with the growing use of tools like machine learning and artificial intelligence. In emerging sectors, the cost of gathering high-quality data across large spatial areas can present a significant barrier. A key solution is leveraging existing data from well-established industries like oil and gas. However, the proprietary nature of data in these industries often hinders collaboration. This paper explores how cultivating a culture of data sharing can act as a catalyst for progress, fueling breakthroughs across both conventional and renewable energy sectors. Practical compromises that protect business interests while enabling data access are proposed, and real-world success stories are highlighted, demonstrating how collaboration has accelerated advancements in geothermal, carbon capture, and other innovative technologies.

15 GEOTHERMAL ENERGY

Computer model for refinery operations with emphasis on jet fuel production. Volume 2: Data and technical bases

The FORTRAN computing program predicts the flow streams and material, energy, and economic balances of a typical petroleum refinery, with particular emphasis on production of aviation turbine fuel of varying end point and hydrogen content specifications. The program has provision for shale oil and coal oil in addition to petroleum crudes. A case study feature permits dependent cases to be run for parametric or optimization studies by input of only the variables which are changed from the base case. The report has sufficient detail for the information of most readers.

Dunbar, D. N.

SWS Diesel Truck Fueling Data

This dataset contains fueling data for two diesel trucks operated by SWS, provided by SWS. Data fields include date and time of fueling, total amount of fuel, odometer reading at the time of fueling, and total cost of fueling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

SWS Diesel Truck Fueling Data

This dataset contains fueling data for two diesel trucks operated by SWS, provided by SWS. Data fields include date and time of fueling, total amount of fuel, odometer reading at the time of fueling, and total cost of fueling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Innovative Advanced Hydrogen Mobile Fueler (Final Technical Report)

The US Department of Energy (DOE) funded a project to design, develop, deploy and analyze the economic viability of an innovative Advanced Hydrogen Mobile Fueler (AHMF). As part of the design activity the project team defined specifications based upon vehicle requirements and compliance with specific fueling performance criteria. The AHMF was originally designed to fuel 10-20 fuel cell vehicles (FCV) per day, consistent with the requirements of the H70 fueling category. The AHMF is able to operate without remote power connections, is modular for easy transport and deployment, and can provide expanded daily capacity and multi-day operations using delivered gaseous hydrogen. Toward the end of the project, due to request from the hydrogen industry and some necessary modifications of the AHMF, the system is now modified to fuel heavy duty vehicles. The project was conducted over two primary phases, each including several key tasks, subtasks, and project milestones. Phase 1 involved the design, development, and construction of the AHMF, moving from a conceptual design through to completion of assembly and testing. In addition to reviewing several different approaches, the team chose to take a conventional station design and modify it for mobile fueling. There were several innovative components included in the design. The high pressure storage was the first to achieve a US Department of Energy (DOE) Special Permit (SP 20391) to transport high pressure hydrogen (95 MPa) in a composite cylinder. The second novel system was a liquid nitrogen (LIN) cooling system with a compact heat exchanger. Without this change, the cooling system would not be able to fit into the AHMF. Phase 2 demonstrated the AHMF by fueling fuel cell buses at a fleet in Pomona, CA. The site was chosen because a temporary fueling solution was required while a fixed station was being installed. The existing permits for the fixed station and non-public access also was a determining factor. Over two months, the buses were fueled 320 times with over 5000 kg of hydrogen from tube trailers. Existing shore power was used, and the average electrical efficiency was 0.13 kWh/kg. The average liquid nitrogen (LIN) consumption was 90.68 scf/kg. The fueling and consumption data was provided to the National Renewable Energy Laboratory (NREL) for analysis. An economic analysis was performed and will be provided in a separate report. The project was successful, but not without challenges and lessons learned. The DOT special permit led the way for the use of high pressure, composite cylinders and is being by multiple other systems and applications. The pandemic along with time for the DOT special permit approval delayed the project for years. The team also believes that hydrogen mobile fueling has a use for the industry, especially during this upcoming phase of expansion. However, it does have its limitations due to high cost to build and operate, and the same permitting challenges as a fixed station. A fully capable system at the speeds and pressures of the AHMF may not be necessary for most applications and would help reduce the cost and increase storage capacity. The on-board generator can be easily replaced with shore power or the wide range of power generation solutions in the marketplace. One of the major results of the project was the development of new code language in National Fire Protection Agency (NFPA) 2 and the International Fire Code (IFC) for on-demand mobile fueling. This will provide guidance for Authorities Having Jurisdiction (AHJ) and user on how to permit temporary fueling sites across the nation.

08 HYDROGEN

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis – Simulated Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wind turbine. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen . While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the simulated wind energy profiles, NLR used OpenFAST to simulate a 3.4-MW International Energy Agency (IEA) reference wind turbine. The hour-long wind energy profiles varied over wind turbulence intensity (Class A or Class C) and average wind speed (5, 7, or 9 m/s). To match the power limits of the 1.25-MW electrolyzer and 3.4-MW IEA wind turbine most effectively and to maximize the efficiency of hydrogen production at a given average wind speed, the profiles were sometimes scaled by two times. This means that, in some cases, the experimental setup assumed two 1.25-MW electrolyzers were coupled with the wind turbine, representing a total maximum electrolysis load of 2.5 MW. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}-{average wind speed}-{turbulence class}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “windIEA3.4-5ms-C_2-400.zip” represents the hour-long experiment using the IEA 3.4-MW turbine, subjected to an average wind speed of 5 m/s and Class C wind turbulence, and connected to two 1.25-MW electrolyzers with the power supply set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wind turbine power. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis .

08 HYDROGEN

2025 Annual INMM Graph and Tables for High Purity Germanium Detector Normalization Presentation

The data set includes gamma spectroscopy peak data for measurements taken with two different high purity germanium detectors using a mixed nuclide source and a U-235 fuel rod. There are a total of 5 specific energy peaks that were analyzed for the mixed nuclide source stemming from Am-241, Cd-109, Cs-137, and Co-60. There are a total of 3 specific energy peaks that were analyzed for the U-235 fuel rod. The data set includes the calculations and results from using a linear correction factor, absolute efficiency curve, and relative efficiency curve to compare the net peaks counts from two different detectors.

Drumm, Natalie Daphne [Sandia National Laboratorie

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Solar PV

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) research platform. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence data centers and other variable loads. This dataset entry describes the behavior of a 1.25-MW proton exchange membrane MC250 electrolyzer system, manufactured by Nel Hydrogen , [1] when fed historical data generated by the 430-kW, fixed-axis solar photovoltaic (PV) array located at NLR’s Flatirons Campus. (While the electrolyzer balance of plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.) Solar PV power output data for the 2020 calendar year were categorized on a daily basis by total energy generation and standard deviation. Each day was then ranked by these metrics, and the 25th, 50th, and 100th percentiles were selected. The 75th percentile day did not exhibit sufficient variability to make for a valuable experiment. A similar process was used for the related historical wind dataset . [2] The historical days in 2020 that represented these percentiles are Dec. 19, March 29, and May 4, respectively. The entire solar day’s power profile was then fed through the MC250 electrolyzer. Due to its length, the 100th percentile day experiment was split into two parts, and the final 3 hours of the solar day were not captured. These final 3 hours contained no spikes or dips of interest and simply represented a slow decay of input solar power. Also, a single timestamp (13:13:47 on Jan. 14, 2026) was lost in the hydrogen system supervisory control and data acquisition. Finally, during the 25th percentile experiment (solar day Dec. 19, 2020) data recording was lost from 11:00:13 to 11:14:45. The roughly 15 minutes of the solar profile were rerun at the end of the experiment and spliced into this time slot during post-processing. The electrolysis system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operation of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical solar profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. For more details on the statistical analysis process, see the slide deck “Public Reference Data for Megawatt-Scale Hydrogen Electrolysis: NLR Historical Solar PV Analysis and Profile Generation” accessible with this data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single solar PV electrolysis experiment and is formatted as: {technology}_{percentile}_{scaling factor} For instance, “solarPV-430kW_25_2x.zip” reports the experiment using the 25th percentile solar data from the historical 2020 solar PV dataset, scaled to 200%. Scaling factors were applied to the generated solar PV power output files to more closely match the 1.25-MW capacity of the electrolyzer. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and solar power input. A PDF file detailing the historical solar data statistical analysis used to generate the solar profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all experiments combined into one dataset labeled "combined_solarPV_experiments.csv". [1] nelhydrogen.com/product/mc-series-electrolyser . [2] data.nlr.gov/submissions/316 .

08 HYDROGEN

Rare Earth Carbide (Nd-C and Ce-C) Synthesis and Characterization to Inform Phase Equilibrium in Advanced Nuclear Fuels

As advances are being made regarding the performance of nuclear fuels, uranium carbides, and composites, such as (U,Zr)C and UO2 + UCx, have recently gained significant interest for deployment in nuclear space propulsion and high temperature gas-cooled reactors, respectively. However, the phase equilibria of several fission products in carbide systems remain unknown and may impact the overall fuel performance, specifically for particle nuclear fuels that are designed for commercial nuclear energy. Furthermore, comprehensive thermodynamic data on Rare Earth (RE) carbides, such as the Nd-C and Ce-C binary systems, remain limited. Presented in this study are the synthesis methods and characterizations of several Nd-C and Ce-C compositions. The findings from this research provide insights on the stability of RE-C binaries that form in irradiated nuclear fuels and address a critical knowledge gap in the current state of thermodynamics for two key RE-C systems.

Cavazos, Steven J. (ORCID:0009000130329363)

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production by conducting a statistical analysis of historical wind data over a five-year period (2020-2025) from a single 1.5MW turbine manufactured by General Electric (GE) located at NLR’s Flatirons Campus, to generate an experimental test profile that was deployed on a 1.25-MW proton exchange membrane type MC250 electrolyzer system manufactured by Nel Hydrogen . [1] While the electrolyzer balance-of-plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. The historical wind data provided several metrics, however, the analysis particularly focused on the measured power output by the wind turbine. The power output time series of data for each day was categorized by total energy generation and standard deviation, and the day that represented the highest combination of these two metrics was chosen – December 25th, 2022. This process was then repeated for a moving four-hour window within this day to identify the most statistically variable period. Finally, this four-hour period was scaled by 65% to match the 1.25 MW electrolyzer. The electrolysis system controls hydrogen production by varying DC current applied to the stack, from a maximum of 3000 A to a minimum safe operation of 300 A, or 10%. Because the current – voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical wind profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1 Hz frequency. For more details on the statistical analysis process, see the presentation labeled “ Public Reference Data for Megawatt-Scale Hydrogen Electrolysis” provided with each data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}_{scaling factor}-{electrolyzer ramp rate in amperes/second} For instance, “wind-GE1.5MW_0.65-400.zip” represents the hour-long experiment using historical data from the wind-GE1.5MW turbine, scaled to 65%, with the electrolyzer power supply set to a maximum ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and wind power input. A PDF file detailing the historical wind data statistical analysis used to generate the wind profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_historical_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis [1] nelhydrogen.com/product/mc-series-electrolyser .

08 HYDROGEN

Spark Ignition of Flowing Gases. 2: Effect of Electrode Parameters on Energy Required to Ignite a Propane-Air Mixture

Research was conducted to determine the effect of the electrode parameters of spacing, configuration, and material' on the energy required for ignition of a flowing propane-air mixture. In addition, the data were used to indicate the energy distribution along the spark length and to confirm previous observations concerning the effect of spark duration on ignition energy requirements. The data were obtained with a mixture at a fuel-air ratio of 0.0835 (by weight), a pressure of 3 inches of mercury absolute, a temperature of 80 F, and a mixture velocity of 5 feet per second. Results showed that the energy required for ignition decreased as the electrode spacing was increased; a minimum energy occurred at. a spacing of 0.65 inch for large electrodes. For small electrodes, the spacing for minimum energy was not sharply defined. Small-diameter electrodes required less energy than large-diameter electrodes if the spacing was less than the optimum distance of 0.65 inch; at a spacing equal to the optimum distance, no difference was noted. Significant effects of electrode material on ignition energy were ascribed to differences in the type of spark discharges produced; glow discharges required higher energy than the arc-glow discharges. With pure glow discharges, the ignition energy was substantially constant for lead, cadmium, brass, aluminum, and tungsten electrodes. A method is described for determining the energy distribution along a glow discharge. It was found that one-third to one-half of the energy in the spark was concentrated in a small region near the cathode electrode, and the remainder was uniformly distributed across the spark gap. It was impossible to ascertain the dependence of ignition on. this distribution. It was also observed that long-duration (600 microsec) sparks required much less energy for ignition than did short-duration (1 microsec) sparks.

Swett, Clyde. C., Jr.

Subsonic Ultra Green Aircraft Research: Truss Braced Wing Design Exploration - Phase II - Volume I

This report summarizes the Truss Braced Wing (TBW) work accomplished by the Boeing Subsonic Ultra Green Aircraft Research (SUGAR) team, consisting of Boeing Research and Technology, Boeing Commercial Airplanes, General Electric, Georgia Tech, Virginia Tech, NextGen Aeronautics, and Microcraft. A multi-disciplinary optimization (MDO) environment defined the geometry that was further refined for the updated SUGAR High TBW configuration. Airfoil shapes were tested in the NASA TCT facility, and an aeroelastic model was tested in the NASA TDT facility. Flutter suppression was successfully demonstrated using control laws derived from test system ID data and analysis models. Aeroelastic impacts for the TBW design are manageable and smaller than assumed in Phase I. Flutter analysis of TBW designs need to include pre-load and large displacement non-linear effects to obtain a reasonable match to test data. With the updated performance and sizing, fuel burn and energy use is reduced by 54% compared to the SUGAR Free current technology Baseline (Goal 60%). Use of the unducted fan version of the engine reduces fuel burn and energy by 56% compared to the Baseline. Technology development roadmaps were updated, and an airport compatibility analysis established feasibility of a folding wing aircraft at existing airports.

Bradley, Marty K.

SPARC - Plans for a New Critical Experiment Facility with a Horizontal Split Table

Several critical experiment facilities, sometimes referred to as zero power reactor facilities, have provided crucial data to aid understanding and validate nuclear-physics models since the beginning of nuclear technology. Indeed, the first man-made reactor, Chicago Pile-1, was essentially this type of reactor. However, there was a downturn in nuclear technology development toward the turn of the millennium, and the need for these specialized research facilities waned. Now there are few of these experimental facilities operational in the world and those that remain have relatively small critical assembly machines. The need for criticality safety benchmark experiments at intermediate neutron energy levels and the modern resurgence of interest in advanced reactors designs, many of which do not have historical precedents in terms of nuclear fuel composition, moderator, and coolant combinations, all combine to create a substantial need for a critical experiment facility with a large horizontal split-table (HST) machine. A HST machine is used to arrange two separate and subcritical parts of a core assembly, bring them together in a precise manner to achieve criticality using remote controls, and separate them to achieve a subcritical configuration again. A new effort was recently performed to develop user needs for a HST, assess candidate locations at the Idaho National Laboratory (INL), and develop a plan for deployment. This project is referred to as the System Physics Advanced Reactor Critical facility (SPARC). A few months after this assessment began, and shortly after as a viable pathway was emerging, a series of important presidential executive orders were issued to revitalize nuclear energy in the United States (U.S.). The relevance of SPARC to these executive orders was immediately apparent. The far-reaching potential of SPARC to these executive orders will reside in its ability to produce data which facilitates licensing of advanced nuclear reactor designs while reducing uncertainties to help increase energy production alongside new criticality safety data to enable more efficient nuclear fuel manufacture, transport, and storage.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

The "Apollo" of Aeronautics: NASA's Aircraft Energy Efficiency Program, 1973-1987

In fall 1975, 10 distinguished United States Senators from the Aeronautical and Space Sciences Committee summoned a group of elite aviation experts to Washington, DC. The Senators were holding hearings regarding the state of the American airline industry, which was struggling in the wake of the 1973 Arab oil embargo and the dramatically increasing cost of fuel. Providing testimony were presidents or vice presidents of United Airlines, Boeing, Pratt & Whitney, and General Electric. Other witnesses included high-ranking officials from the National Aeronautics and Space Administration (NASA), the U.S. Air Force, and the American Institute of Aeronautics and Astronautics. Their Capitol Hill testimony painted a bleak economic picture, described in phrases that included immediate crisis condition, long-range trouble, serious danger, and economic dislocation.

Aircraft

Technology Integration 2023 Annual Progress Report

This document summarizes the progress of VTO Technology Integration projects supported during the fiscal year 2023. VTO's Technology Integration Program supports a broad technology portfolio that includes alternative fuels, energy efficient mobility systems and technologies, and other efficient advanced technologies that can reduce transportation energy costs for businesses and consumers. The program provides objective, unbiased data and real-world lessons learned to inform future research needs and support local decision making. It also includes projects to disseminate data, information, and insight, as well as online tools and technology assistance to cities and regions working to implement alternative fuels and energy efficient mobility technologies and systems.

33 ADVANCED PROPULSION SYSTEMS