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DOE OSTI2021

Fission In R-Process Elements

The goal of the FIRE topical collaboration in nuclear theory is to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This will be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration is composed of LLNL (lead) and LANL for fission work, BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r -process simulations. Under DOE/NNSA agreement, both universities receive funds from DOE Office of Science, while national laboratories receive funds directly from NA221.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗
DOE OSTI2019

TENDL: Complete Nuclear Data Library for Innovative Nuclear Science and Technology

The TENDL library is now established as one of the major nuclear data libraries in the world, striving for completeness and quality of nuclear data files for all isotopes, evaluation methods, processing and applied performance. To reach this status, some basic principles have been applied which sets it apart from other libraries: reproducible dedicated evaluations when differential data are available, through determination of nuclear models implemented in TALYS and their parameters, completeness (with or without experimental data), format and processing standardization, automation of production and reproducibility. In this paper, we will outline how such an approach has become a reality, and recall some of the past successes since the first TENDL release in 2008. Next, we will demonstrate the performance of the latest TENDL releases for different application fields, as well as new approaches for uncertainty quantification based on Bayesian inference methods and possible differential and integral adjustments. Also, current limitations of the library performances due to modelling and needs for new and more precise experimental data will be outlined.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Science and Engineering Team Repository Selection and Validation

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD), Science and Engineering Team (SET) has engaged Brookhaven National Laboratory (BNL) in the selection, development and management of a knowledge management platform. This platform will serve as a repository for programmatic documents, data, and other relevant files. In support of this effort, BNL implemented a sixteen-month process to ensure the selection of the most relevant and user-friendly repository from among several commercially available and open source options.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

Galaxy bias from the Dark Energy Survey Science Verification data: Combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ~116 deg 2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2–0.4), 0.97 ± 0.15 (z = 0.4–0.6), 1.38 ± 0.39 (z = 0.6–0.8), and 1.45 ± 0.56 (z = 0.8–1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Moreover, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The Journal of Open Source Software (JOSS): Bringing Open-Source Software Practices to the Scholarly Publishing Community for Authors, Reviewers, Editors, and Publishers

Open-source software (OSS) is a critical component of open science, but contributions to the OSS ecosystem are systematically undervalued in the current academic system. The Journal of Open Source Software (JOSS) contributes to addressing this by providing a venue (that is itself free, diamond open access, and all open-source, built in a layered structure using widely available elements/services of the scholarly publishing ecosystem) for publishing OSS, run in the style of OSS itself. A particularly distinctive element of JOSS is that it uses open peer review in a collaborative, iterative format, unlike most publishers. Additionally, all the components of the process—from the reviews to the papers to the software that is the subject of the papers to the software that the journal runs—are open. We describe JOSS’s history and its peer review process using an editorial bot, and we present statistics gathered from JOSS’s public review history on GitHub showing an increasing number of peer reviewed papers each year. We discuss the new JOSSCast and use it as a data source to understand reasons why interviewed authors decided to publish in JOSS. JOSS’s process differs significantly from traditional journals, which has impeded JOSS’s inclusion in indexing services such as Web of Science. In turn, this discourages researchers within certain academic systems, such as Italy’s, which emphasize the importance of Web of Science and/or Scopus indexing for grant applications and promotions. JOSS is a fully diamond open-access journal with a cost of around US$\$$5 per paper for the 401 papers published in 2023. The scalability of running JOSS with volunteers and financing JOSS with grants and donations is discussed.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

Final Report: Sublinear Algorithms for In-situ and In-transit Data Analysis at Exascale.

Post-Moore's law scaling is creating a disruptive shift in simulation workflows, as saving the entirety of raw data to persistent storage becomes expensive. We are moving away from a post-process centric data analysis paradigm towards a concurrent analysis framework, in which raw simulation data is processed as it is computed. Algorithms must adapt to machines with extreme concurrency, low communication bandwidth, and high memory latency, while operating within the time constraints prescribed by the simulation. Furthermore, in- put parameters are often data dependent and cannot always be prescribed. The study of sublinear algorithms is a recent development in theoretical computer science and discrete mathematics that has significant potential to provide solutions for these challenges. The approaches of sublinear algorithms address the fundamental mathematical problem of understanding global features of a data set using limited resources. These theoretical ideas align with practical challenges of in-situ and in-transit computation where vast amounts of data must be processed under severe communication and memory constraints. This report details key advancements made in applying sublinear algorithms in-situ to identify features of interest and to enable adaptive workflows over the course of a three year LDRD. Prior to this LDRD, there was no precedent in applying sublinear techniques to large-scale, physics based simulations. This project has definitively demonstrated their efficacy at mitigating high performance computing challenges and highlighted the rich potential for follow-on re- search opportunities in this space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The Prompt Processing System and Data Quality Monitoring in the ProtoDUNE-SP Experiment

The DUNE Collaboration is conducting an experimental program (named protoDUNE) which involves a beam test of two large-scale prototypes of the DUNE Far Detector at CERN operating in 2018-2019. The volume of data to be collected by the protoDUNE-SP (the single-phase detector) will amount to a few petabytes and the sustained rate of data sent to mass storage is in the range of a few hundred MB per second. After collection the data is committed to storage at CERN and transmitted to Fermi National Accelerator Laboratory in the US for processing, analysis and long-term preservation. The protoDUNE experiment requires substantial Data Quality Monitoring capabilities in order to ascertain the condition of the detector and its various subsystems. We present the design of the protoDUNE Prompt Processing System, its deployment at CERN and its performance during the data challenges and actual data taking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

LLNL Data Disk Evaluation Report and Information Gathering Document #449.R1.3

This is a report on Data Storage Disk Evaluation and characterization. The purpose of this memo is to capture new recipients due to some recent characterization issues with the Hammer Mill process. The Data Storage Disk Evaluation report was generated utilizing data acquired during 2009 and 2010 from submitted storage media.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

WHONDRS 48 Hour Diel Cycling Study at the Columbia River in Washington, USA

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of the upstream Priest Rapids Dam-induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Columbia River, WA, USA. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

TU-AB-204-00: Advances in Cone-Beam CT and Emerging Applications

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both the likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity

The 2018 Basic Research Needs Workshop on Extreme Heterogeneity identified five Priority Research Directions for realizing the capabilities needed to address the challenges posed in this era of rapid technological change. This report captures the outcomes of that workshop. In the context of extreme heterogeneity, it defines basic research needs and opportunities in computer science research to develop smart and trainable operating and runtime systems, programming environments, and predictive tools that will make future systems easier to adapt to scientists’ computing needs and easier for facilities to deploy securely.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Dissolution Behavior of Iron and Steel Materials in Liquid Magnesium

The dissolution of metallic elements from Fe and steel materials into pure liquid Mg was investigated with the aim of improving control of impurities in Mg during processes such as Mg-alloy production and Ti smelting. Pure Mg was melted between 1073 and 1323 K (800 and 1050 °C) for 24 to 96 hours in closed crucibles made of pure Fe, low-carbon steel, or austenitic stainless steel SUS316. From the experiments using the pure Fe crucible, the relationship between the solubility of Fe in liquid Mg [C{sub sol,Fe} (mass pct)] and temperature [T (K)] was determined to be log(C{sub sol,Fe}) = − 3.67 × 10{sup 3}/T + 2.48 (± 0.06), from which the standard Gibbs energy of Fe dissolution in liquid Mg was evaluated. The amount of Fe dissolved from low-carbon steel was the same as that from pure Fe. From SUS316, not only Fe but also Cr and Ni dissolved into liquid Mg; the Fe and Cr concentrations in liquid Mg did not change significantly over time, whereas the Ni concentration increased monotonically. Preferential Ni dissolution resulted in a Ni-poor layer on the SUS316 surface. Finally, using the experimental data of Fe dissolution from low-carbon steel, the Fe contamination route in the current Ti smelting process, where a large amount of Mg is used as a reducing agent, is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Kinetic Modeling of a Silicon Refining Process in a Moist Hydrogen Atmosphere

We developed a kinetic model that considers both silicon loss and boron removal in a metallurgical grade silicon refining process. This model was based on the hypotheses of reversible reactions. The reaction rate coefficient kept the same form but error of terminal boron concentration could be introduced when relating irreversible reactions. Experimental data from published studies were used to develop a model that fit the existing data. At 1500 °C, our kinetic analysis suggested that refining silicon in a moist hydrogen atmosphere generates several primary volatile species, including SiO, SiH, HBO, and HBO{sub 2}. Using the experimental data and the kinetic analysis of volatile species, we developed a model that predicts a linear relationship between the reaction rate coefficient k and both the quadratic function of p(H{sub 2}O) and the square root of p(H{sub 2}). Moreover, the model predicted the partial pressure values for the predominant volatile species and the prediction was confirmed by the thermodynamic calculations, indicating the reliability of the model. We believe this model provides a foundation for designing a silicon refining process with a fast boron removal rate and low silicon loss.

36 MATERIALS SCIENCE↗
DOE OSTI2019

WHONDRS 48 Hour Diel Cycling Study at the Jordan River, Israel

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of groundwater pumping induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Jordan River, Israel. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

WHONDRS 48 Hour Diel Cycling Study at the Erpe River, Germany

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of wastewater treatment plant effluent induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Erpe River, Germany. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in September 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Determination of Solar System R-Process Abundances using ENDF/B-VIII.0 and TENDL-2015 libraries

Recent multi-messenger detection of the binary neutron star merger (GW170817) energized the astrophysical community and encouraged further research for determination of nuclear physics observables. Comprehensive studies of atomic nuclei in the cosmos provide an opportunity for investigating these astrophysical phenomena and acquiring complementary information on stellar nucleosynthesis processes that can be verified using the latest nuclear data. Evaluated Nuclear Data File (ENDF) libraries contain complete collections of reaction cross sections over the energy range relevant to astrophysics, fission yields and decay data. These data collections have been used worldwide in nuclear science, industry and national security applications. There is great interest in exploring the ENDF/B-VIII.0 and TALYS Evaluated Nuclear Data Library (TENDL-2015) for nuclear astrophysics purposes and comparing findings with the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars (KADoNiS). The Maxwellian-averaged cross sections (MACS) and astrophysical reaction rates have been calculated using the ENDF/B-VIII.0 and TENDL-2015 evaluated data sets. The calculated cross sections were combined with the solar system abundances and fitted using the classical model of stellar nucleosynthesis. Astrophysical rapid- and slow-neutron capture, r- and s-process, respectively, abundances were obtained from present data and compared with available values. Further analysis of MACS reveals potential evaluated libraries data deficiencies and a strong need for new measurements. The current results demonstrate a large nuclear astrophysics potential of evaluated libraries and mutually beneficial relations between nuclear industry and research e orts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗