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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ENDF/B-VIII.1 Validation (Preliminary Release 2 + New 239 Pu)

This document should serve as a reference for validation testing of nuclear data files included in the second preliminary release of ENDF/B-VIII.1 and the newly evaluated 239 Pu nuclear data file to be included in the third preliminary release of ENDF/B-VIII.1. Experiment names listed in this report are based on International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook designations. Additional information on ICSBEP handbook designations can be found at https://www.oecd-nea.org/jcms/pl_20291/icsbep-handbook. The validation metrics used in this report include the effective neutron multiplication factor, k eff , and tritium production. All validation metrics were calculated using the radiation transport code Monte Carlo N-Particle (MCNP).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The Locus Algorithm IV: Performance metrics of a grid computing system used to create catalogues of optimised pointings

This paper discusses the requirements for and performance metrics of the the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,779 quasars. Initial operational tests indicated a need for a software system to analyse the data and a High Performance Computing system to run that software in a scalable manner. Practical assessments of the performance of the software in a serial computing environment were used to provide a benchmark against which the performance metrics of the HPC solution could be compared, as well as to indicate any bottlenecks in performance. These performance metrics indicated a distinct split in the performance dictated more by differences in the input data than by differences in the design of the systems used. This indicates a need for experimental analysis of system performance, and suggests that algorithmic complexity analyses may lead to incorrect or naive conclusions, especially in systems with high data I/O overhead such as grid computing. Further, it implies that systems which reduce or eliminate this bottleneck such as in-memory processing could lead to a substantial increase in performance.

Creaner, Oisín↗
DOE OSTI2021

Developing Low Noise, Rad-hard Detectors for Parity Violating Experiments

As parity-violating electron scattering (PVeS) experiments continue to push the frontiers of precision electro-weak asymmetry measurements, the demands on the experimental techniques and apparatus are also pushed. In particular, the need for higher resolution and radiation-hardness of the main integrating detectors has increased over the successive generations of PVeS experiments. The demand for precise measurement of GHz event rates has pushed the field toward the use of thin quartz Cerenkov light based detectors. We have been designing and testing such thin quartz detectors specifically for the upcoming experiments at Jefferson Lab, PREX-II and CREX, but this work also greatly influences the detector development for several future experiments including MOLLER at Jefferson Lab. These are all PVeS experiments that will use the new thin quartz Cerenkov detector design concept for their main asymmetry measurements (as well as for beam monitoring). The new design concept gives not only significant performance improvements compared to its predecessor from PREX-I, but also we have now thoroughly characterized its operational design and performance using a combination of test-beam data and detailed particle and optical Monte Carlo Geant4 simulations. These activities have culminated in the development and implementation of a "bench-marked" Monte Carlo package, QSIM, which constitutes a powerful design tool for present and future PVeS quartz detectors. The benchmarked simulation can replicate real photoelectron distributions (RMS and Mean) from testbeam data with ~5% precision – limited mainly by the systematic uncertainty of the PMT gain measurements.

Villarreal, Carlos Bula Villarreal↗
DOE OSTI2022

Glassy Carbon Substrate Oxidation Effects on Electrode Stability for Oxygen Evolution Reaction Catalysis Stability Benchmarking

Employing benchmarking metrics to capture the activity and stability of electrocatalysts for the oxygen evolution reaction (OER) in acid is a critical practice that enables meaningful comparison of catalyst material candidates reported throughout the literature. In this work, we find that ubiquitously used glassy carbon electrode substrates oxidize under typical OER operating conditions, forming a pacified, electrically insulating, and oxygen-rich surface layer that causes drastic loss of current density over the course of extended chronoamperometric stability tests at an anodic potential of 1.7 VRHE. We show that the experimentally observed stability of glassy carbon-based electrodes is approximately two orders of magnitude lower than that expected solely from dissolution-based catalyst intrinsic stability of Ir-based catalysts. We additionally find that glassy carbon-based electrode stability measured by chronoamperometric holds is greatly impacted by catalyst loading, with high catalyst loadings improving the stability of the overall electrode via a protective effect on the glassy carbon substrate. Altogether, our investigation highlights that glassy carbon is not electrochemically inert under OER conditions on the timescale of common stability tests, which can cause electrodes to exhibit performance losses that do not reflect the intrinsic stability of the actual catalyst material being investigated. In light of our findings, we underscore the usefulness of metrics, such as the S-number, to reflect intrinsic catalyst material stability.

25 ENERGY STORAGE↗
DOE OSTI2024

Development of a low-pressure Multi-Mesh THGEM detector for fission experiments at FRIB

Abstract A small-area imaging detector prototype for position measurement of fission fragments produced in low energy heavy-ion reactions is presented in this study. The detector readout is equipped with a 2-dimensional, position-sensitive gaseous avalanche readout based on the novel Multi-Mesh Thick-GEM (MM-THGEM), and is coupled to a delay-line board for particle localization. The prototype has an effective area of 10 × 10 cm 2 and is operated in isobutane at low pressure (7–10 Torr). We present and discuss a series of systematic evaluation tests performed by irradiating the detector with α-particles and fission fragments emitted by small-rate sources ( 241 Am, 249 Cf and 252 Cf). Position and time resolutions of about 0.42 mm and 1 ns were achieved, respectively. This work serves as a benchmark for the development of a large-scale array of detectors for experiments with fission and fission-like reaction products at the Facility for Rare Isotope Beams (FRIB).

Instruments & Instrumentation↗
DOE OSTI2024

Measurement and modeling of beam transport in the FODO line of the Spallation Neutron Source Beam Test Facility

Ongoing studies at the Spallation Neutron Source (SNS) Beam Test Facility (BTF) seek to understand and model bunch dynamics in a high-power LINAC front-end. The BTF has recently been upgraded with a reconfiguration from a U-shaped line to a Straight line. We report the current state of model benchmarking, with a focus on RMS beam sizes within the FODO line. The beam measurement is obtained via three camera/screen pairs in the FODO line. This presentation discusses the methodology and results of this measurement.

Thompson, Trent↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multiple Critical Unresolved Region Integral Experiment (MCURIE): A Proposed Integral Critical Experimental Framework for Unresolved Region and Intermediate Energies

The Critical Unresolved Region Integral Experiment (CURIE) critical experiment was performed at the National Criticality Experiments Research Center (NCERC) at the Device Assembly Facility (DAF) at the Nevada Nuclear Security Sites (NNSS) in 2020. The objective of CURIE was to improve the quality of integral nuclear data in the uranium-235 ( 235 U) unresolved resonance region (URR) by performing benchmark integral experiments that were sensitive to the URR energy ranges. The CURIE experiment was evaluated for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook and the benchmark evaluation was accepted in 2022. The URR is a region within the intermediate neutron energy range (the intermediate energy ranges from 0.7 eV to 100 keV). The observed resonance structure in neutron cross sections is due to discrete energy levels in the nucleus and are characterized by resonance parameters. In the URR region, the resonance parameters are only partially resolved as the resolution of the experiment techniques becomes comparable to the average width of the resonances themselves, and the resonances are so close to one another that the structure cannot be determined empirically. The ENDF/B-VIII.0 and JEFF-3.3 nuclear data libraries define the URR as beginning at 2.25 keV and continuing until 25 keV. There are minimal intermediate neutron energy benchmarks available in the ICSBEP benchmark handbook, and aside from CURIE there are none that are highly sensitive in the URR energy region. There is a current need for additional experiments sensitive to the URR energy region. There is a new proposed subgroup for the Organization for Economic Co-operation and Development and Nuclear Energy Agency (OECD NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC), so any new models or information will need experimental validation and testing. The NEA Working Party on Nuclear Criticality Safety (WPNCS) recent experimental needs and priority list includes intermediate energy 235 U and 238 U experiments, as does the recent Integral Experiments to Address Nuclear Criticality Safety Needs Meeting (May 2023). A variant on the original CURIE experiment called the Multiple Critical Unresolved Region Integral Experiment (MCURIE) is proposed to provide further investigation of the intermediate and URR energy region for uranium. MCURIE will utilize existing fuels at NCERC but use alternative moderators and reflectors to modify the neutron absorption, scattering, and fission spectra of the experiments, allowing for precise targeting of nuclear data sensitivities. The overall goal of MCURIE is to develop a framework for designing and performing integral benchmark experiments with high sensitivities in the intermediate and URR energy regions for nuclear data validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Retrospective on Recent DOE-Funded Studies Concerning the Extraction of Rare Earth Elements & Lithium from Geothermal Brines (Final Report)

Rare earth elements (REE) and lithium are non-toxic metals that are considered critical materials due to their use in electronics, magnets, batteries, and a wide variety of industrial processes important for the economy and military preparedness. Demand for REE and lithium is increasing and these critical materials are imported, so identifying and exploiting domestic sources of REE and lithium is a national priority. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) has been in the forefront of sponsoring research investigating the potential recovery of REE, lithium, and other critical minerals from geothermal brines. It has been proposed that the future of geothermal energy should include “hybrid systems” that combine electricity generation with other revenue-generating activities, such as recovery of valuable and critical minerals, including REE and lithium. Two recent GTO funding opportunities have focused on the recovery of REE and other valuable minerals from geothermal brines. The research supported by the GTO’s mineral recovery program is focused on three areas: resource characterization, technology for the extraction of REE, and technology for the extraction of lithium (Tables 1 and 2). This report is a retrospective study examining the outcome of GTO’s two recent mineral recovery programs (DE-FOA-0001016 in FY 2014 and DE-FOA-0001376 in FY 2016). In this report, the knowledge, technology, and techniques that were developed by researchers funded by GTO are summarized and discussed. Four projects were funded to assess the concentrations and amounts of REE found in geothermal brines and oil field produced waters. The GTO-funded studies compiled publically available data on REE concentrations from brines and produced water from all over the USA. In addition, new samples were collected and characterized from major geothermal and hydrocarbon basins in the Western USA. The studies examined the relationship between lithology and REE concentrations and developed models examining the influence of geology on REE concentrations in produced brines. It was determined that REE are frequently found at higher concentrations in oil field produced water than geothermal brines, but that some geothermal areas had significant REE resources. Significant reservoirs of REE were identified in the Western USA. In some cases, concentrations of REE were more than 1000 times the concentrations found in seawater. Collectively, these studies represent a comprehensive picture of REE resources associated with geothermal and hydrocarbon systems in the USA. The studies did not examine lithium resources, but in some cases, lithium concentration data was collected. Data from these studies are housed in the Geothermal Data Repository (GDR) and represent a significant information resource and it is recommended that these data be further analyzed in a future study. Eight projects were funded to develop new technology for REE extraction from geothermal fluids. These projects investigated sorption as an approach for removal and recovery of REE from geothermal brines. The projects investigated cutting-edge technology for selective sorption of ions from complex solutions, including the application of metal-organic frameworks and biosorbent proteins. The REE sorption studies tested different combinations of metal-binding ligands and solid supports. The most promising metal-binding ligands for REE included phosphonic acid, thiol, and carboxylic acid functional groups. Ligands were attached or incorporated into a wide variety of solid supports. In most cases, attachment was via covalent bonding to organic resins, polymers, or silica-based supports. Most of the REE projects were conducted at a low technology readiness level (TRL) and showed promise, but direct comparison between technologies was not possible based on the available information. It is recommended that testing and reporting be standardized to the extent possible to facilitate comparisons between technologies. Two projects were directed at novel lithium extraction technology. Both projects investigated the use of inorganic sorbents, including manganese oxides. One study also examined the use of metal- ion imprinted polymers as selective ion-exchange resins for the separation of lithium and manganese from brines. Both approaches showed promise for the selective extraction of lithium from brines, including potentially geothermal brines. Results from these GTO studies indicated that selective REE and lithium extraction is possible, but interference from co-occurring solutes, such as calcium, magnesium, or heavy metals, will interfere with process efficiency and negatively impact process economics. Techno-economic analysis conducted as part of the resource and technology studies suggest extraction of REE from geothermal brines is unlikely to be economically viable, especially since non-geothermal produced waters frequently have higher REE concentrations. It is recommended that benchmarks for techno-economic analysis be established to the extent possible for future studies, to facilitate direct comparison of various technologies. Based on the collective results of this program, it appears that hybrid geothermal power would benefit more from recovery of lithium and other metals, rather than REE. It is recommended that future studies be conducted at a higher- TRL and that sorbents be tested against actual geothermal fluid samples. Prior higher-TRL efforts to extract metals from geothermal brines should be further evaluated for lessons learned.

36 MATERIALS SCIENCE↗
DOE OSTI2020

OpenGraphGym: A Parallel Reinforcement Learning Framework for Graph Optimization Problems

This paper presents an open-source, parallel AI environment (named OpenGraphGym) to facilitate the application of reinforcement learning (RL) algorithms to address combinatorial graph optimization problems. This environment incorporates a basic deep reinforcement learning method, and several graph embeddings to capture graph features, it also allows users to rapidly plug in and test new RL algorithms and graph embeddings for graph optimization problems. This new open-source RL framework is targeted at achieving both high performance and high quality of the computed graph solutions. This RL framework forms the foundation of several ongoing research directions, including 1) benchmark works on different RL algorithms and embedding methods for classic graph problems; 2) advanced parallel strategies for extreme-scale graph computations, as well as 3) performance evaluation on real-world graph solutions.

Zheng, Weijian↗
DOE OSTI2023

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Abstract Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Vik, Dean (ORCID:000000027546899X)↗
DOE OSTI2022

Deep learning methods for obtaining photometric redshift estimations from images

ABSTRACT Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it is impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of particular interest. Here, we investigate different deep learning methods for obtaining photo-z estimates directly from images, comparing these with ‘traditional’ machine learning algorithms which make use of magnitudes retrieved through photometry. As well as testing a convolutional neural network (CNN) and inception-module CNN, we introduce a novel mixed-input model that allows for both images and magnitude data to be used in the same model as a way of further improving the estimated redshifts. We also perform benchmarking as a way of demonstrating the performance and scalability of the different algorithms. The data used in the study comes entirely from the Sloan Digital Sky Survey (SDSS) from which 1 million galaxies were used, each having 5-filtre (ugriz) images with complete photometry and a spectroscopic redshift which was taken as the ground truth. The mixed-input inception CNN achieved a mean squared error (MSE) =0.009, which was a significant improvement ($30{{\ \rm per\ cent}}$) over the traditional random forest (RF), and the model performed even better at lower redshifts achieving a MSE = 0.0007 (a $50{{\ \rm per\ cent}}$ improvement over the RF) in the range of z < 0.3. This method could be hugely beneficial to upcoming surveys, such as Euclid and the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), which will require vast numbers of photo-z estimates produced as quickly and accurately as possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Membrane Pretreatment and Cell Conditioning for Proton Exchange Membrane Water Electrolysis

As the research community studying proton exchange membrane water electrolysis (PEMWE) grows, it is important to develop methods that achieve transparent, reproducible research. Reproducibility of performance and durability is a challenge facing the PEMWE field, as the published literature includes a wide spread of results obtained with nominally similar materials. Prior round-robin performance benchmarking efforts [1] have identified inadequate cell conditioning as a major source of variation in apparent cell performance. Inadequate pre-treatment and conditioning can lead to instability in initial performance and adds ambiguity to durability measurements. However, excessively prolonged conditioning procedures limit the throughput of testing and the pace of research. Pretreatment and conditioning methods vary significantly across the research literature, but little systematic investigation is available into the mechanisms of these procedures or how procedural differences may impact results. This presentation will discuss investigations into the effects of membrane pre-treatment and operating procedures during cell conditioning on initial performance and catalyst-specific accelerated stress tests, with the aim of recommending procedures to enable clear, reproducible, and high-throughput research. Methods investigated include the use of hydrogen peroxide, acids, and hydration at elevated temperature for membrane pretreatment, and conditioning procedures such as current or voltage holds and cycling. The investigations cover both the impacts of these procedures on cell performance and stability as well as underlying mechanisms and processes taking place in the cell materials.

cell↗
DOE OSTI2023

Validating Mixtures of 233 U, 235 U, and 239 Pu for the Sum-of-Fractions Method [Slides]

A joint effort by PNNL and ORNL examined mixtures of 233 U, 235 U, and 239 Pu to determine subcritical mass limits based on similarities to critical benchmark experiments through the Sum-of-Fractions method. Results of the validation efforts by ORNL were used to determine areas of applicability based on EALF and moderator/reflector type. TSUNAMI-1D, TSUNAMI-IP, and VADER sequences used for generating sensitivities, similarity assessments, and statistical testing. Validation efforts provided here using the Sum-of-Fractions method results in k eff values below established calculational margins and provides additional flexibility to limits provided in ANSI/ANS-8.15.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Optimal Operations Management of Mobility-on-Demand Systems

The emergence of the sharing economy in urban transportation networks has enabled new fast, convenient and accessible mobility services referred to as Mobilty-on-Demand systems (e.g., Uber, Lyft, DiDi). These platforms have flourished in the last decade around the globe and face many operational challenges in order to be competitive and provide good quality of service. A crucial step in the effective operation of these systems is to reduce customers' waiting time while properly selecting the optimal fleet size and pricing policy. In this paper, we jointly tackle three operational decisions: (i) fleet size, (ii) pricing, and (iii) rebalancing, in order to maximize the platform's profit or its customers' welfare. To accomplish this, we first devise an optimization framework which gives rise to a static policy. Then, we elaborate and propose dynamic policies that are more responsive to perturbations such as unexpected increases in demand. We test this framework in a simulation environment using three case studies and leveraging traffic flow and taxi data from Eastern Massachusetts, New York City, and Chicago. Our results show that solving the problem jointly could increase profits between 1% and up to 50%, depending on the benchmark. Moreover, we observe that the proposed fleet size yield utilization of the vehicles in the fleet is around 75% compared to private vehicle utilization of 5%.

Wollenstein-Betech, Salomón↗
DOE OSTI2020

Alaskan carbon-climate feedbacks will be weaker than inferred from short-term manipulations: Alaskan Benchmark Data and Model runs

This submission aimed to assess differences in short-term step warming manipulations and long-term chronic response to climate change in Alaskan ecosystems. Briefly, climate warming is occurring fastest at high latitudes. Based on short-term field experiments, this warming is projected to stimulate soil organic matter decomposition, and promote a positive feedback to climate change. We show here that the tightly coupled, nonlinear nature of high-latitude ecosystems implies that short-term (< 10 year) warming experiments produce emergent ecosystem carbon stock temperature sensitivities inconsistent with emergent multi-decadal responses. We first demonstrate that a well-tested mechanistic ecosystem model accurately represents observed carbon cycle and active layer depth responses to short-term summer warming in four diverse Alaskan sites. We then show that short-term warming manipulations do not capture the non-linear, long-term dynamics of vegetation, and thereby soil organic matter, that occur in response to thermal, hydrological, and nutrient transformations belowground. Our results demonstrate significant spatial heterogeneity in multi-decadal Arctic carbon cycle trajectories and argue for more mechanistic models to improve predictive capabilities.The model used in the current study is available publicly (https://github.com/jinyun1tang/ECOSYS), and the current submission contains the python/ matlab codes for analyzing output from the model (includng a readme file to explain the codes). The benchmark data, also enclosed, was collected from a range of published and publicly available sources (extracted using GRABIT: https://www.mathworks.com/matlabcentral/fileexchange/7173-grabit). These sources describe warming induced changes in tundra/ boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Continuous-Energy ENDF/B-VIII.0 Cross Section and SCALE 6.2.4 Performance for Nuclear Criticality Safety Applications: 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238 U, 239 Pu

As part of the nuclear data evaluation and validation cycle, the ENDF/B-VIII.0 cross-section library released in 2018 requires testing to determine areas of improvement and deterioration. Previous work by the authors investigated the performance of 16 O, 56 Fe, and 63,65 Cu cross sections, with this study acting as an extension of the prior work. In addition to the isotopes and nuclear criticality safety benchmarks of interest to the prior work, benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook were selected for their k eff sensitivity to 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238U, or 239 Pu cross sections and were modeled in the SCALE code system maintained by Oak Ridge National Laboratory. In total, 253 benchmark configurations were selected for their sensitivities and modeled using SCALE 6.2.4 Criticality Safety Analysis Sequences (CSAS) continuous-energy Monte Carlo k eff calculations. This collection includes and expands upon the 99 benchmarks in the prior work. The AMPX-processed ENDF/B-VIII.0 library was decomposed into individual ENDF/B-VIII.0 datum libraries for each isotope of interest. Doing so allowed for the individual substitution of an ENDF/B-VIII.0 cross section in the place of ENDF/B-VII.1, determining isotope-specific effects of ENDF/B-VIII.0 relative to ENDF/B-VII.1. Full library calculations with entirely ENDF/B-VII.1 data or entirely ENDF/B-VIII.0 data were also executed. As a measure of performance, the average relative deviation was determined as the ratio of the deviation between calculated and experimental keff to the propagated calculational and experimental uncertainty. With calculated full library and isotope-specific ENDF/B-VIII.0 k eff ’s, an optimized combination of data libraries was estimated and confirmed with SCALE calculations. This showed that reverting 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 resulted in improved performance relative to the full ENDF/B-VIII.0 library. Across all 253 benchmarks, the average relative deviation was 1.29σ for the full ENDF/B-VII.1 library, 1.17σ for the full ENDF/B-VIII.0 library, and 0.97σ for the optimized combination. The reversion of 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 in the 99 benchmarks of the prior work resulted in further improved experimental agreement compared to the previously reported improvement from 16 O and 65 Cu alone. Therefore, it is suggested that applications with significant sensitivities to 239 Pu, 58 Ni, 16 O, and 65 Cu consider their choice of nuclear data library.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗