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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Constraints on the Electromagnetic Counterpart of the Neutron-star–Black-hole Merger GW200115

We report the results of our follow-up campaign for the neutron-star—black-hole (NSBH) merger GW200115 detected during the O3 run of the Advanced LIGO and Advanced Virgo detectors. We obtained wide-field observations with the Deca-Degree Optical Transient Imager covering ~20% of the total probability area down to a limiting magnitude of w = 20.5 AB at ~23 hr after the merger. Our search for counterparts returns a single candidate (AT2020aeo), likely not associated with the merger. In total, only 25 sources of interest were identified by the community and later discarded as unrelated to the GW event. We compare our upper limits with the emission predicted by state-of-the-art kilonova simulations and disfavor high-mass ejecta (>0.1 M⊙), indicating that the spin of the system is not particularly high. By combining our optical limits with gamma-ray constraints from Swift and Fermi, we disfavor the presence of a standard short-duration burst for viewing angles ≲15° from the jet axis. Our conclusions are, however, limited by the large localization region of this GW event, and accurate prompt positions remain crucial to improving the efficiency of follow-up efforts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Safety Compliance Verification of Fuel Cell Electric Vehicle Exhaust

NREL has been developing compliance verification tools for allowable hydrogen levels prescribed by the Global Technical Regulation Number 13 (GTR-13) for hydrogen fuel cell electric vehicles (FCEVs). As per GTR-13, FCEV exhaust is to remain below 4 vol% H2 over a 3-second moving average and shall not at any time exceed 8 vol% H2 and that this requirement is to be verified with an analyzer that has a response time of less than 300 ms. To be enforceable, a means to verify regulatory requirements must exist. In response to this need, NREL developed a prototype analyzer that meets the GTR metrological requirements for FCEV exhaust analysis. The analyzer was tested on a commercial fuel cell electric vehicle (FCEV) under simulated driving conditions using a chassis dynamometer at the Emissions Research and Measurement Section of Environment and Climate Change Canada and FCEV exhaust was successfully profiled. Although the prototype FCEV Exhaust Analyzer met the metrological requirements of GTR-13, the stability of the hydrogen sensor was adversely impacted by condensed water in the sample gas. FCEV exhaust is at an elevated temperature and nearly saturated with water vapor. Furthermore, condensed water is present in the form of droplets. Condensed water in the sample gas can collect on the hydrogen sensing element, which would not only block access of hydrogen to the sensor but can also permanently damage the sensor. In the past year, the design of the gas sampling system was modified to mitigate against the transport of liquid water to the sensing element. Laboratory testing confirmed the effectiveness of the modified sampling system water removal strategy while maintaining the measurement range and response time required by GTR-13. Testing of the upgraded analyzer design on an FCEV operating on a chassis dynamometer is scheduled for the summer of 2021.

DIRECT ENERGY CONVERSION,HYDROGEN↗
DOE OSTI2025

Decomposing Cloud Radiative Feedbacks by Cloud-Top Phase

Changes in cloud scattering properties and emissivity that arise from atmospheric warming cause substantial radiative feedbacks in model projections of anthropogenic climate change, and the relative importance of the underlying mechanisms is poorly understood. One leading hypothesis is that ice-to-liquid conversions cause clouds to optically thicken, producing a major negative feedback. We test this hypothesis by developing a method to decompose cloud radiative feedbacks by cloud-top phase. The method is applied to an ensemble of six state-of-the-art global climate models run with prescribed sea surface temperature. In these simulations, the global mean of the net cloud scattering and emissivity feedback from cloud-phase conversions ranges from −0.17 to −0.01 W m −2 K −1 , while the overall net cloud feedback ranges from 0.02 to 0.91 W m −2 K −1 . The multimodel mean of the cloud scattering and emissivity feedback from cloud-phase conversions is approximately 19% of the magnitude of the multimodel mean of the overall cloud feedback (−0.10 vs 0.52 W m −2 K −1 ). These results indicate that cloud-phase conversions cause a robust negative feedback by changing cloud scattering and emissivity, but this mechanism makes a modest contribution to the overall cloud feedback at the global scale.

Climate change↗
DOE OSTI2023

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO 2 ) and the US decarbonized 1848 MtCO 2 . In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO 2 , while the US will maintain a lock-in level of 736 (±133) MtCO 2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Projection of Future Fire Emissions Over the Contiguous US Using Explainable Artificial Intelligence and CMIP6 Models

Abstract Increasing temperature and water cycle changes due to warming climate may increase the frequency and intensity of wildfires. Fire emission projections are useful for informing strategies for adaptation and mitigation of fire impacts on societies and ecosystems. Here, we construct a neural network (NN) model explained by the Shapley Additive explanation to predict fire PM 2.5 emissions change and understand their drivers over the contiguous US (CONUS) in the mid‐21st century under a high greenhouse gas emissions scenario (SSP5‐8.5). Using future meteorology and leaf area index (LAI) simulated by eight global climate models from the Coupled Model Intercomparison Project Phase 6, future population density, and present‐day land use and land cover (LULC) as input to the NN model, the total fire PM 2.5 emissions over CONUS are projected to increase by 4%–75% (model spread). Among different regions, fire emissions in the western US are projected to increase more significantly in June‐July‐August than in other seasons and regions, with the median ratios of future to present‐day fire emissions ranging from 1.67 to 2.86. The increases in fire emissions are mainly driven by increasing normalized temperature (23%–29%) and decreasing soil moisture (2%–10%) in the future. When future LULC change is considered, the projected fire emissions further increase by 58%–83% over the western US compared to projections without LULC change because of future increases in vegetation fraction. The results highlight the important role of warmer temperature, decreasing soil moisture, and LULC change in increasing fire emissions in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydropower Role in a Power Grid with a High Proportion of Variable Renewables

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordination of multiple tools, including water resources modeling, ecological modeling, and technical and economic power grid modeling, informs dam water releases. Better representation of ecological constraints and other water use details in the suit of power grid models are required to identify the hydropower flexibility to provide multiple power grid services. Impacts of water planning and hydropower operation changes to a power grid are better understood by production cost model simulations with technical and economic data, including unserved energy, reserve failures, transmission congestion to serve load, and local marginal price increases. Similarly, PCM simulation of current and future projected power grid information, including LMP, and carbon emission rates, informs short-term water release plans and long-term investments for power plant upgrades for technical and ecological needs. Hydropower operations of several case studies are simulated to understand operation patterns, revenue, water release decisions in multiple time scales (month, day, minutes), hydropower contracts scheduling, and water variability impacts.

environmental↗
DOE OSTI2025

Open-source library for performance-portable neutrino reaction rates: Application to neutron star mergers

A realistic and detailed description of neutrinos in binary neutron star (BNS) mergers is essential to build reliable models of such systems. To this end, we present bns_nurates, a novel open-source numerical library designed for the efficient on-the-fly computation of neutrino interactions, with particular focus on regimes relevant to BNS mergers. bns_nurates targets a higher level of accuracy and realism in the implementation of commonly employed reactions by accounting for relevant microphysics effects on the interactions, such as weak magnetism and mean field effects. It also includes the contributions of inelastic neutrino scattering off electrons and positrons and (inverse) nucleon decays. Finally, it offers a way to reconstruct the neutrino distribution function in the framework of moment-based transport schemes. As a first application, we compute both energy-dependent and energy-integrated neutrino emissivities and opacities for conditions extracted from a BNS merger simulation with m1 transport scheme. We find some qualitative differences in the results when considering the impact of the additional relevant reactions and of microphysics effects. For example, neutrino-electron/positron scattering reactions are important for the energy exchange of heavy-type neutrinos as they do not undergo semileptonic charged-current processes, when μ± are not accounted for. Moreover, weak magnetism and mean field effects can significantly modify the contribution of β processes for electron-type (anti)neutrinos, increasing at the same time the importance of (inverse) neutron decays. Here, the improved treatment for the reaction rates also modifies the conditions at which neutrinos decouple from matter in the system, potentially affecting their emission spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Characterizing the X-Ray Emission of Intermediate-mass Pre-main-sequence Stars

We use X-ray and infrared observations to study the properties of three classes of young stars in the Carina Nebula: intermediate-mass (2–5 M {sub ⊙}) pre-main-sequence stars (IMPS; i.e., intermediate-mass T Tauri stars), late-B and A stars on the zero-age main sequence (AB), and lower-mass T Tauri stars (TTS). We divide our sources among these three subclassifications and further identify disk-bearing young stellar objects versus diskless sources with no detectable infrared (IR) excess emission using IR (1–8 μm) spectral energy distribution modeling. We then perform X-ray spectral fitting to determine the hydrogen-absorbing column density (N {sub H}), absorption-corrected X-ray luminosity (L {sub X}), and coronal plasma temperature (kT) for each source. We find that the X-ray spectra of both IMPS and TTS are characterized by similar kT and N {sub H}, and on average L {sub X}/L {sub bol} ~ 4 × 10{sup -4}. IMPS are systematically more luminous in X-rays (by ~0.3 dex) than all other subclassifications, with median L {sub X} = 2.5 × 10{sup 31} erg s{sup -1}, while AB stars of similar masses have X-ray emission consistent with TTS companions. These lines of evidence converge on a magnetocoronal flaring source for IMPS X-ray emission, a scaled-up version of the TTS emission mechanism. IMPS therefore provide powerful probes of isochronal ages for the first ~10 Myr in the evolution of a massive stellar population, because their intrinsic, coronal X-ray emission decays rapidly after they commence evolving along radiative tracks. We suggest that the most luminous (in both X-rays and IR) IMPS could be used to place empirical constraints on the location of the intermediate-mass stellar birth line.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Field-Emission Electron Source Embedded in a Field-Enhanced Conduction-Cooled Superconducting RF Cavity

We present simulations and experimental progress toward the development of a high-current electron source with the potential to deliver high charge electron bunches at GHz-level repetition rates. To achieve these goals electrons are generated through field-emission and the cathode is immersed in a conduction-cooled superconducting 650-MHz RF cavity. The field-emitters consist of microscopic silicon pyramids and have a typical enhancement factor of about 500. To trigger field-emission, the peak field inside the RF cavity of about 6 MV/m is further enhanced by placing the field-emitters on the top of a superconducting Nb rod inserted in the RF cavity. So far, we cannot control the duration of the electron bunches which is of the order of RF period. Also, the present cryo-cooler power of about 2 W limits the beam current to microamp level.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Demonstration of neutron-yield enhancement by laser preheating and magnetization of laser-driven cylindrical implosions

Magnetized liner inertial fusion (MagLIF) is a fusion concept that uses magnetized, preheated fuel to reduce the implosion velocities and convergence ratios required for ignition. A scaled, laser-driven experimental platform to study MagLIF has been demonstrated on the OMEGA laser system, providing comprehensive experimental data on MagLIF scaling, utilizing the higher shot rate on OMEGA compared to the Z machine. Using this platform, a broader experimental space for MagLIF has been studied. Presented in this article are experimental results that demonstrate that the combination of preheat and magnetization enhances the neutron yield by 470% compared to a reference implosion, significantly more than the yield enhancement by the field or preheat alone. These results are achieved while maintaining a relatively low convergence ratio (<20). Here, the experiments were supported by one-, two-, and three-dimensional radiation-hydrodynamics simulations, all of which suggest that multiple sources of mix play different key roles depending on the scale of the MagLIF experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Three-dimensional reconstruction of laser-direct-drive inertial confinement fusion hot-spot plasma from x-ray diagnostics on the OMEGA laser facility (invited)

A deep-learning convolutional neural network (CNN) is used to infer, from x-ray images along multiple lines of sight, the low-mode shape of the hot-spot emission of deuterium–tritium (DT) laser-direct-drive cryogenic implosions on OMEGA. The motivation of this approach is to develop a physics-informed 3-D reconstruction technique that can be performed within minutes to facilitate the use of the results to inform changes to the initial target and laser conditions for the subsequent implosion. The CNN is trained on a 3D radiation-hydrodynamic simulation database to relate 2D x-ray images to 3D emissivity at stagnation. The CNN accounts for the lack of an absolute spatial reference and the different bands of photon energies in the x-ray images. While previous works studied the effect of mode-1 asymmetries on implosion performance using nuclear diagnostics, this work focuses on the effect of mode 2 inferred from x-ray diagnostics on implosion performance. A current analysis of 19 DT cryogenic implosions indicates there is an upper limit of ~20% reduction in the neutron yield caused by an ℓ = 2 amplitude for ℓ 2 /ℓ 0 ≤ 0.32. Here, these conclusions are supported by 2D simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Neutron generation dynamics inside a MA-class dense plasma focus Z-pinch

Dense plasma focii (DPFs) are appealing as energy efficient sources of short pulses of ions, neutrons, and x rays. The output of these sources is expected to scale with input current (I4), but has been shown to drop at the MA level [S. K. H. Auluck, “On the failure of neutron yield scaling in the dense plasma focus,” Phys. Plasmas 30, 080701 (2023)]. New results on the MegaJOuLe Neutron Imaging Radiography DPF showed neutron yield production in agreement with the input current scaling beyond the previously observed drop. This work provides insight into the pinch formation on a DPF and reports on the two different mechanisms leading to neutron generation inside a DPF using a combination of kinetic simulations and experimental data. A combination of particle-in-cell (PIC) and 1D shock theory results are used to describe the pinch formation and disassembly and the corresponding thermonuclear and beam-target mechanisms. The temporal evolution of the pinch column predicted by the PIC simulations shows qualitative agreement with the experimental data from plasma photon emission as well as temporal neutron pulse shapes. In MJ-class DPFs, both thermonuclear and beam-target mechanisms can occur over the course of the implosion and contribute to the total neutron production. Hence the neutron source size of a DPF will change throughout the implosion. Experimental neutron radiographs show the increase in source size as the pinch breaks apart, in agreement with simulation's prediction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling the Far-infrared Polarization Spectrum of a High-mass Star-forming Cloud

The polarization spectrum, or wavelength dependence of the polarization fraction, of interstellar dust emission provides important insights into the grain alignment mechanism of interstellar dust grains. We investigate the far-infrared polarization spectrum of a realistic simulated high-mass star-forming cloud under various models of grain alignment and emission. We find that neither a homogeneous grain alignment model nor a grain alignment model that includes collisional dealignment is able to produce the falling spectrum seen in observations. On the other hand, we find that a grain alignment model with grain alignment efficiency dependent on local temperature is capable of producing a falling spectrum that is in qualitative agreement with observations of OMC-1. For the model most in agreement with OMC-1, we find no correlation between the temperature and the slope of the polarization spectrum. However, we do find a positive correlation between the column density and the slope of the polarization spectrum. We suggest this latter correlation to be the result of wavelength-dependent polarization by absorption.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗
DOE OSTI2021

OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

ABSTRACT We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius–Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R–L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R–L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quasi-differential neutron induced neutron emissions from 235 U, and 239 Pu

Uncertainty in nuclear reaction cross sections, angular distributions, and other nuclear data directly impact how well simulations of nuclear systems represent physical observations. Here, to determine how well the nuclear data in ENDF/B-VIII.0, JEFF-3.3, and JENDL-4.0 evaluations describe the physical behaviour of 235 U, and 239 Pu when subjected to a neutron flux, the neutron emission spectrum was measured for carbon, 93.0% 235 U, and 93.9% 239 Pu samples, and compared against detailed MCNP6 simulations. The measurements were performed at the Los Alamos Neutron Science Center using a quasi-differential method previously developed at Rensselaer Polytechnic Institute. The measurement spanned 0.82–20 MeV and 30–150 degrees. The measurements show there are a significant number of discrepancies between library predictions of the neutron yield and physical observation. A few of the main discrepancies found are described in this paper. Based on these results a new evaluation utilizing these results for carbon, 235 U, and 239 Pu is recommended.

235U↗