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At least 289 records · Page 16

Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0 °C above 1850–1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30 °N, 15 °N, 15 °S, and 30 °S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-to-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5 °C vs. 2.0 °C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO 2 concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

42 ENGINEERING↗

Evidence of restricted heat transport in National Ignition Facility Hohlraums

We present experimental evidence of restricted electron thermal conduction in the high-Z coronal plasma regions of laser-driven Hohlraums on the National Ignition Facility. Four separate measurements, three of which are direct observations of Hohlraum dynamics, corroborate this finding. (1) The velocity of the coronal plasma ablated and heated by the outer-cone laser beams is determined by time-dependent imaging of the gold plasma plume, or “bubble.” The velocities of the incoming plume (perpendicular to the Hohlraum axis) are consistent with high-fidelity 2D radiation-hydrodynamic simulations using flux-limited thermal electron conduction with a flux multiplier f = 0.03. Simulations using f = 0.15, which is very nearly classical Spitzer–Härm transport, predict plume velocities slower than measured. (2) Specific features in time-resolved images of the Hohlraum wall at an angle of 19° are also more consistent with f = 0.03 simulations compared to f = 0.15. (3) Spectroscopic tracers were added to the Hohlraum wall in the outer-beam bubble region. The ratios of hydrogen-like to helium-like line emission are sensitive to the electron temperature of the bubble. The hydrogen-like to helium-like ratios extracted from the time-integrated spectra of manganese and cobalt tracers from two observation angles are consistent with f = 0.03 and not with f = 0.15. (4) The time of peak capsule emission, or “bang time,” an integrated measurement, is also more consistent with f = 0.03 than with f = 0.15. Overall, while these findings do not identify the causes of restricted thermal conduction in Hohlraums, they motivate future experiments to test specific hypotheses and focus on model development in the regions of the plasma exhibiting restricted transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The X-ray emission of cerium oxide

Using a combination of spectral simulation with FEFF and experimental data for metallic Ce, it has been possible to extract the Cerium Oxide-only M 4,5 X-ray Emission Spectrum (XES) from an experimental result, which had been produced utilizing a combined CeOxide/Ce sample. In this paper, it is shown that the XES emission for CeOxide-only is significantly different for the M 4 and M 5 edges, with the M 4 XES consistent with normal XES and the M 5 XES exhibiting a continued enhancement associated with a threshold effect, connected to Resonant Inverse Photoelectron Spectroscopy (RIPES).

36 MATERIALS SCIENCE↗

Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0

Atmospheric aerosol microphysical processes are a significant source of uncertainty in predicting climate change. Specifically, aerosol nucleation, emissions, and growth rates, which are simulated in chemical transport models to predict the particle size distribution, are not understood well. However, long-term size distribution measurements made at several ground-based sites across Europe implicitly contain information about the processes that created those size distributions. This work aims to extract that information by developing and applying an inverse technique to constrain aerosol emissions as well as nucleation and growth rates based on hourly size distribution measurements. We developed an inverse method based upon process control theory into an online estimation technique to scale aerosol nucleation, emissions, and growth so that the model–measurement bias in three measured aerosol properties exponentially decays. The properties, which are calculated from the measured and predicted size distributions, used to constrain aerosol nucleation, emission, and growth rates are the number of particles with a diameter between 3 and 6 nm, the number with a diameter greater than 10 nm, and the total dry volume of aerosol ( N 3–6 , N 10 , V dry ), respectively. In this paper, we focus on developing and applying the estimation methodology in a zero-dimensional “box” model as a proof of concept before applying it to a three-dimensional simulation in subsequent work. The methodology is first tested on a dataset of synthetic and perfect measurements that span diverse environments in which the true particle emissions, growth, and nucleation rates are known. The inverse technique accurately estimates the aerosol microphysical process rates with an average and maximum error of 2 % and 13 %, respectively. Next, we investigate the effect that measurement noise has on the estimated rates. The method is robust to typical instrument noise in the aerosol properties as there is a negligible increase in the bias of the estimated process rates. Finally, the methodology is applied to long-term datasets of in situ size distribution measurements in western Europe from May 2006 through June 2007. At Melpitz, Germany, and Hyytiälä, Finland, the average diurnal profiles of estimated 3 nm particle formation rates are reasonable, having peaks near noon local time with average peak values of 1 and 0.15 cm –3 s –1 , respectively. The normalized absolute error in estimated N 3–6 , N 10 , and V dry at three European measurement sites is less than 15 %, showing that the estimation framework developed here has potential to decrease model–measurement bias while constraining uncertain aerosol microphysical processes.

54 ENVIRONMENTAL SCIENCES↗

Observation of shock-front separation in multi-ion-species collisional plasma shocks

We observe shock-front separation and species-dependent shock widths in multi-ion-species collisional plasma shocks, which are produced by obliquely merging plasma jets of a He/Ar mixture (97% He and 3% Ar by initial number density) on the plasma liner experiment. Visible plasma emission near the He-I 587.6-nm and Ar-II 476.5–514.5-nm lines is simultaneously recorded by splitting a single visible image of the shock into two different fast-framing cameras with different narrow bandpass filters (589 ± 5 nm for observing the He-I line and 500 ± 25 nm for the Ar-II lines). For conditions in these experiments (pre-shock ion and electron densities ≈5×10 14 cm –3 , ion and electron temperatures of ≈2.2 eV, and relative plasma-merging speed of 22 km/s), the observationally inferred magnitude of He/Ar shock-front separation and the shock widths themselves are <1 cm, which correspond to ~50 post-shock thermal ion–ion mean free paths. These experimental length scales are in reasonable qualitative and quantitative agreement with results from 1D multi-fluid simulations using the CHICAGO code. However, we note there are differences between the experimentally inferred and simulation-predicted ionization states and line emission intensities, particularly in the post-shock region. Overall, the experimental and simulation results are consistent with theoretical predictions that the lighter He ions diffuse farther ahead within the overall shock front than the heavier Ar ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterizing the Directionality of Gravitational Wave Emission from Matter Motions within Core-collapse Supernovae

Abstract We analyze the directional dependence of the gravitational wave (GW) emission from 15 3D neutrino radiation hydrodynamic simulations of core-collapse supernovae (CCSNe). Using spin weighted spherical harmonics, we develop a new analytic technique to quantify the evolution of the distribution of GW emission over all angles. We construct a physics-informed toy model that can be used to approximate GW distributions for general ellipsoid-like systems, and use it to provide closed form expressions for the distribution of GWs for different CCSN phases. Using these toy models, we approximate the protoneutron star (PNS) dynamics during multiple CCSN stages and obtain similar GW distributions to simulation outputs. When considering all viewing angles, we apply this new technique to quantify the evolution of preferred directions of GW emission. For nonrotating cases, this dominant viewing angle drifts isotropically throughout the supernova, set by the dynamical timescale of the PNS. For rotating cases, during core bounce and the following tens of milliseconds, the strongest GW signal is observed along the equator. During the accretion phase, comparable—if not stronger—GW amplitudes are generated along the axis of rotation, which can be enhanced by the low T /∣ W ∣ instability. We show two dominant factors influencing the directionality of GW emission are the degree of initial rotation and explosion morphology. Lastly, looking forward, we note the sensitive interplay between GW detector site and supernova orientation, along with its effect on detecting individual polarization modes.

Astronomy & Astrophysics↗

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Amplified spontaneous emission in the extreme ultraviolet by expanding xenon clusters

Focused short-wavelength free-electron laser (FEL) pulses interacting with gas phase samples can induce by inner-shell ionization a short-lived population inversion, followed by coherent collective emission of directed, short, and strong radiation bursts. We extend our studies into the warm-dense matter (WDM) regime by investigating the nanoplasmas produced in an ensemble of nanometer-sized clusters by FEL irradiation. Here, additional pathways can also lead to strong, laserlike emission: Electron-ion collisions can yield a long-lived population inversion, and subsequent amplified spontaneous emission. We observe amplified spontaneous emission (ASE) in the extreme ultraviolet in xenon clusters excited by soft x-ray FEL pulses, we diagnose the generated nanoplasmas by fluorescence spectroscopy, and we study under various cluster and FEL parameters the directed ASE from the Xe 2+ 65 nm line. We show its exponential increase as a function of FEL irradiation power, and an accompanying collisional broadening of the emission spectra. These findings are corroborated by extensive numerical simulations based on theory, combining detailed hydrodynamic and kinetic simulations with time-dependent calculations of radiation transport, amplification, and collective emission in the WDM nanoplasma. Furthermore, our theoretical findings underline that population inversion is due to electron-ion collisions and that the observed decoherence processes can be empirically characterized by a phenomenological decoherence time in the range of 100–200 fs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast neutrino cooling of nuclear pasta in neutron stars: Molecular dynamics simulations

The direct Urca process of rapid neutrino emission can occur in nonuniform nuclear pasta phases that are expected in the inner crusts of neutron stars. Here, the periodic potential for a nucleon in nuclear pasta allows momentum conservation to be satisfied for direct Urca reactions. We improve on earlier work by modeling a rich variety of pasta phases (gnocchi, waffle, lasagna, and anti-spaghetti) with large-scale molecular dynamics simulations. We find that the neutrino luminosity due to direct Urca reactions in nuclear pasta can be 3 to 4 orders of magnitude larger than that from the modified Urca process in the NS core. Thus neutrino radiation from pasta could dominate radiation from the core and this could significantly impact the cooling of neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The galaxy–halo connection of emission-line galaxies in IllustrisTNG

ABSTRACT We employ the hydrodynamical simulation IllustrisTNG-300-1 to explore the halo occupation distribution (HOD) and environmental dependence of luminous star-forming emission-line galaxies (ELGs) at z ∼ 1. Such galaxies are key targets for current and upcoming cosmological surveys. We select model galaxies through cuts in colour–colour space allowing for a direct comparison with the Extended Baryon Oscillation Spectroscopic Survey and the Dark Energy Spectroscopic Instrument (DESI) surveys and then compare them with galaxies selected based on specific star formation rate (sSFR) and stellar mass. We demonstrate that the ELG populations are twice more likely to reside in lower density regions (sheets) compared with the mass-selected populations and twice less likely to occupy the densest regions of the cosmic web (knots). We also show that the colour-selected and sSFR-selected ELGs exhibit very similar occupation and clustering statistics, finding that the agreement is best for lower redshifts. In contrast with the mass-selected sample, the occupation of haloes by a central ELG peaks at ∼20 per cent. We furthermore explore the dependence of the HOD and the autocorrelation on environment, noticing that at fixed halo mass, galaxies in high-density regions cluster about 10 times more strongly than low-density ones. This result suggests that we should model carefully the galaxy–halo relation and implement assembly bias effects into our models (estimated at ∼4 per cent of the clustering of the DESI colour-selected sample at z = 0.8). Finally, we apply a simple mock recipe to recover the clustering on large scales (r ≳ 1 Mpc h−1) to within 1 per cent by augmenting the HOD model with an environment dependence, demonstrating the power of adopting flexible population models.

79 ASTRONOMY AND ASTROPHYSICS↗

Cathode Modeling and Diode Performance in a Planar Geometry using Space-charge-limited Emission

Space-charge-limited (SCL) emission parameters are varied to study the performance effects in a planar diode using an electromagnetic particle-in-cell simulation software suite, EMPIRE. Oscillations in the simulations are found and linked to the emission parameters, namely the breakdown threshold, the emission delay time, and the current density ramp time. The oscillations are suggested to be a transverse oscillator due to the perfect magnetic conductor boundary condition in steady-state operation and the formation of a virtual cathode in the diode driven by the SCL boundary condition.

97 MATHEMATICS AND COMPUTING↗

Increased Asian Sulfate Aerosol Emissions Remarkably Enhance Sahel Summer Precipitation

Observational evidence shows that Sahel summer precipitation has experienced a considerable increase since the 1980s, coinciding with significant diverging trends of increased sulfate emissions in Asia and decreased emissions in Europe (dipole pattern of aerosols between Asia and Europe). The decrease in European sulfate aerosols has substantial effects on the Sahel summer precipitation increase, but the corresponding effect of increased Asian sulfate is unknown. Multi-model simulations in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) show, compared to decreased European aerosols, that increased Asian aerosols similarly enhance the Sahel summer precipitation but with different large-scale atmospheric circulation changes. Further analysis of the Sixth Coupled Model Intercomparison Project (CMIP6) simulations under historical attribution and various emission scenarios reinforces the results about the climate impacts of anthropogenic aerosols and suggests that in future scenarios with strong international cooperation and rapid climate mitigations (SSP2-45), the Sahel drought will be intensified likely due to the decline in Asian aerosol emissions. Our results suggest that Asian anthropogenic aerosols are likely a non-negligible driver of the recent recovery in Sahel precipitation amounts

54 ENVIRONMENTAL SCIENCES↗

Validation of neutron emission and neutron energy spectrum calculations on a Mega Ampere Spherical Tokamak with directional relativistic spectrum simulator

The recently developed directional relativistic spectrum simulator (DRESS) code has been validated for the first time against numerical calculations and experimental measurements performed on the Mega Ampere Spherical Tokamak . In this validation, the neutron emissivities and rates computed by DRESS are benchmarked against TRANSP/NUBEAM predictions while the neutron energy spectra provided by DRESS taking as input TRANSP/NUBEAM and ASCOT/BBNBI in Gyro-Orbit mode fast ion distributions are validated against proton pulse height spectra measured by the neutron flux monitor. Finally, excellent agreement was found between DRESS and TRANSP/NUBEAM predictions of local and total neutron emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Energy Emissions Accounting Methods Can Determine Whether Direct Air Capture with Storage Achieves Net Removal

The voluntary carbon market within the United States has expanded rapidly in recent years and enabled private companies and other organizations to provide revenue streams to carbon dioxide removal (CDR) technologies. For a CDR technology to participate in the voluntary carbon market (VCM), the emissions associated with constructing and operating the technology must be less than the CO 2 captured from the atmosphere. Assessing the extent to which this is true for direct air capture with storage (DACS), a relatively energy-intensive CDR technology, strongly depends on the accounting method used to assess the emissions intensity of purchased energy. We simulate the hourly weather-dependent operation of sorbent- and solvent-based DACS in California, Louisiana, Texas, and Wyoming, representing a wide range of local weather and electric and natural gas grid compositions. In all cases, the single most important emissions accounting decision is the method used to estimate the emissions intensity of purchased grid electricity, which varies the calculated net removal by −1049% to +108%. All other factors influencing net removal introduce a variation of at most ±14%. No electricity emissions accounting method is universally conservative across all scenarios, and none is objectively more accurate. High-spatiotemporal-resolution, high-quality, publicly available data sets and models for electricity emissions accounting do not currently exist and are urgently needed to enable standardization of emissions accounting methods to more accurately determine the true emissions impacts of DACS and other energy-intensive facilities.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

Quantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year -1 (1Tg = 10 12 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH 4 year -1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of -34 to -46 Tg CH 4 year -1 , we estimated that the global net land methane emissions are 149–176 Tg CH 4 year -1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

58 GEOSCIENCES↗

Overview of Nuclear Data Measurement and Analysis at RPI [Slides]

This presentation discusses the experimental, simulation, and nuclear data methods that were validated for the RPI γ-Multiplicity Detector. When the neutron capture γ-cascade data is well-known, the γ-emission spectra can be accurately calculated using the modified simulation tools. The RPI γ-Multiplicity Detector system is now ready for analysis and recommendations for isotopes with deficiencies in γ-ray data. The presentation also discusses future work which includes developing a method for analyzing and adjusting nuclear data for 59 Co, 55 Mn and other measured isotopes including 181 Ta. Additionally, future work includes comparing experimental γ-emission spectra with MCNP-6.2/DICEBOX simulations for 238 U and 235 U. In summation, new capture and transmission measurements for 54 Fe will help improve resonance parameter evaluation. Neutron capture gamma cascade spectra and yields were measured in the resolved resonance region and compared to evaluations. In addition, the pulsed neutron die-away method was developed as a tool to provide data for validation of TSLs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impacts of sea ice leads on sea salt aerosols and atmospheric chemistry in the Arctic

Abstract. The processes contributing to Arctic cold-season (November–April) sea salt aerosols (SSAs) remain uncertain. Observations from coastal Alaska suggest that emissions from open leads in sea ice, which are not included in climate models, may play a dominant role. Their Arctic-wide significance has not yet been quantified. Here, we create an emission parameterization of SSAs from leads by combining satellite data of lead area (the Advanced Microwave Scanning Radiometer–Earth Observation System (AMSR-E) product) and a chemical transport model (GEOS-Chem) to quantify pan-Arctic SSA emissions from leads during the cold season from 2002 to 2008 and to predict their impacts on atmospheric chemistry, evaluating the results of our simulated SSAs against in situ observations. The AMSR-E product detects large leads with certainty (> 3 km in size), and, hence, our study is limited to quantifying emissions from large leads. Lead emissions vary seasonally and interannually. Simulated total monthly SSA emissions increase by 1.1 %–1.8 % (≥60° N latitude) and 5.6 %–7.5 % (≥75° N) for the 2002–2008 cold seasons. SSA concentrations primarily increase at the location of leads, where standard model concentrations are low. GEOS-Chem overestimates SSA concentrations at Arctic sites compared to ground observations, even when lead emissions are not included, suggesting underestimation of SSA sinks and/or uncertainties in SSA emissions from blowing snow and the open ocean. Multi-year monthly mean surface bromine atom (Br) concentrations increase by 2.8 %–8.8 % due to SSAs from leads for the 2002–2008 cold seasons. Changes in ozone concentrations are negligible. While leads contribute < 10 % to Arctic-wide SSA emissions in the years 2002–2008, these emissions occur in regions of low background aerosol concentrations. Leads may increase in frequency under future climate change, which could increase SSA emissions from leads.

Emme, Erin J. (ORCID:0000000268406352)↗

NCERC-CL TREAT Free Field Characterization Foil Reaction Rate Results

This report summarizes the analysis and preliminary MCNP reaction rate modeling of free field characterization measurements performed in the Transient Reaction Test Facility (TREAT) at Idaho National Laboratory (INL) between 12/18/2023 and 2/22/2024. A series of seven irradiations were performed using the Big-BUSTER (Broad Use Specimen Transient Experiment Rig) core configuration. Foil sets including 19.5% LEU-Zr alloy wire, S, Au, Fe, Ni, Co, Ti, and Zr were deployed in each irradiation. Identical foil sets were supplied to Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and INL. All foils were supplied by INL. Additional details on the experiment can be found in [2]. The foil sets were shipped to the National Criticality Experiments Research Center Counting Laboratory (NCERC-CL) branch at LANL (NCERC-CL NISC) and were received on 3/25/2024. Additional details on receipt and counting are reported in [3]. All reactor dosimetry measurements were performed in adherence to the ASTM standards applicable to reactor dosimetry. Measured reaction rates from Au, Co, Fe, Ni, and Ti are reported. Select reaction rate ratios and simulated reaction rates and ratios are discussed. Reaction rates for all measured reaction products were modeled with MCNP 6.3.1 and a TREAT input deck supplied by Edward Lum. Neutron emission estimates calculated using the measured and simulated reaction rates show excellent agreement between the three fast-threshold n-p reactions with the percent differences being < 9% between the three reactions. The capture reactions had poorer, but still reasonable, agreement with < 20% percent differences between the neutron emission estimates of the three capture reactions. The percent difference between the fast-threshold and capture reactions is ∼ 100% for each reaction. This supports the TREAT model is not accurately modeling the neutron spectrum and additional measurements are required to characterize TREAT and match measurements to simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗