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NASA NTRS2016

The Far-Ultraviolet Spectra of Two Hot PG1159 Stars

PG 1159 stars are hot, hydrogen-deficient (pre-) white dwarfs with atmospheres mainly composed of helium, carbon, and oxygen. The unusual surface chemistry is the result of a late helium-shell flash. Observed element abundances enable us to test stellar evolution models quantitatively with respect to their nucleosynthesis products formed near the helium-burning shell of the progenitor asymptotic giant branch stars. Because of the high effective temperatures (T(sub eff)), abundance determinations require ultraviolet spectroscopy and non-local thermodynamic equilibrium model atmosphere analyses. Up to now, we have presented results for the prototype of this spectral class and two cooler members (T(sub eff) in the range 85,000-140,000 K). Here we report on the results for two even hotter stars (PG 1520+525 and PG 1144+005, both with T(sub eff) = 150,000 K) which are the only two objects in this temperature-gravity region for which useful far-ultraviolet spectra are available, and revisit the prototype star. Previous results on the abundances of some species are confirmed, while results on others (Si, P, S) are revised. In particular, a solar abundance of sulphur is measured in contrast to earlier claims of a strong S deficiency that contradicted stellar evolution models. For the first time, we assess the abundances of Na, Al, andCl with newly constructed non-LTE model atoms. Besides the main constituents (He, C, O), we determine the abundances (or upper limits) of N, F, Ne, Na, Al, Si, P, S, Cl, Ar, and Fe. Generally, good agreement with stellar models is found.

Werner, K.↗

DOE OSTI2015

THE DIFFUSE INTERSTELLAR BANDS AND ANOMALOUS MICROWAVE EMISSION MAY ORIGINATE FROM THE SAME CARRIERS

We argue that the observed spectroscopic and statistical properties of the diffuse interstellar band (DIB) carriers are those that are needed to produce the anomalous microwave emission (AME). We explore this idea using a carrier-impartial model for AME based on the observed DIB statistical properties. We show that an observed distribution of profile widths for narrow DIBs can be mapped into an AME spectrum. The mapping model is applied to width distributions observed for HD 204827 and HD 183143, selected because their spectroscopic and statistical properties bracket those for most other sight lines. The predicted AME spectra for these sight lines agree well with the range of spectral shapes, and peak frequencies, ∼23–31 GHz, typically observed for AME. We use the AME spectral profiles to derive a strong constraint between the average carrier size and its rotational temperature. The constraint is applied to a variety of postulated molecular carrier classes, including polycyclic aromatic hydrocarbons, fulleranes, hydrocarbon chains, and amorphous hydrocarbon clusters. The constraint favors small, cold carriers with average sizes of ∼8–15 carbon atoms, and average rotational temperatures of ∼3–10 K, depending on carrier type. We suggest new observations, analyses, and modeling efforts to help resolve the ambiguities with regard to carrier size and class, and to further clarify the DIB–AME relationship.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1996

Are Planetary Regolith Particles Back Scattering? Response to a Paper by M. Mishchenko

In a recent paper Mishchenko asserts that soil particles are strongly forward scattering, whereas particles on the surfaces of objects in the solar system have been inferred to be back scattering. Mishchenko suggests that this apparent discrepancy is an artifact caused by using an approximate light scattering model to analyse the data, and that planetary regolith particles are actually strong forward scatterers. The purpose of the present paper is to point out the errors in Mishchenko's paper and to show from both theoretical arguments and experimental data that inhomogencous composite particles which are large compared to the wavelength of visible light, such as rock fragments and agglutinates, can be strongly back scattering and are the fundamental scatterers in media composed of them. Such particles appear to be abundant in planetary regoliths and can account for the back scattering character of the surfaces of many bodies in the solar system. If the range of phase angles covered by a data set is insufficient, serious errors in retrieving the particle scattering properties can result whether an exact or approximate scattering model is used. However, if the data set includes both large and small phase angles, approximate regolith scattering models can correctly retrieve the sign of the particle scattering asymmetry.

Hapke, Bruce↗

DOE OSTI2025

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2005

Measurable characteristics of lysozyme crystal growth

The behavior of protein crystal growth is estimated from measurements performed at both the microscopic and molecular levels. In the absence of solutal flow, it was determined that a model that balances the macromolecular flux toward the crystal surface with the flux of the crystal surface well characterizes crystal growth observed using microscopic methods. Namely, it was determined that the model provides accurate estimates for the crystal-growth velocities upon evaluation of crystal-growth measurements obtained in time. Growth velocities thus determined as a function of solution supersaturation were further interpreted using established deterministic models. From analyses of crystal-growth velocities, it was found that the mode of crystal growth varies with respect to increasing solution supersaturation, possibly owing to kinetic roughening. To verify further the hypothesis of kinetic roughening, crystal growth at the molecular level was examined using atomic force microscopy (AFM). From the AFM measurements, it was found that the magnitude of surface-height fluctuations, h(x), increases with increasing solution supersaturation. In contrast, the estimated characteristic length, xi, decreases rapidly upon increasing solution supersaturation. It was conjectured that the magnitude of both h(x) and xi could possibly determine the mode of crystal growth. Although the data precede any exact theory, the non-critical divergence of h(x) and xi with respect to increasing solution supersaturation was nevertheless preliminarily established. Moreover, approximate models to account for behavior of both h(x) and xi are also presented.

Muramidase/chemistry↗

DOE OSTI2017

Intermittency in Precipitation: Duration, Frequency, Intensity, and Amounts Using Hourly Data

Abstract Intermittency is a core characteristic of precipitation, not well described by data and very poorly modeled. Detailed analyses are made of near-global gridded (about 1°) hourly or 3-hourly precipitation rates from two updated observational datasets [3-hourly TRMM 3B42, version 7, and hourly CMORPH, version 1.0, bias corrected (CRT)] and from special runs of CESM from January 1998 to December 2013 to obtain hourly values. The analyses explore the intermittency of precipitation: the frequency, intensity, duration, and amounts. A comparison is made for all products using several metrics with a focus on the duration of events, and a new metric is proposed based on the ratio of the frequency of precipitation at certain rates (0.2–2 mm h−1) for hourly versus 3-hourly versus daily data. For all seasons and rain rates, TRMM values are similar in pattern to CMORPH, but durations are about 80%–85%. It is mainly over land in the monsoons that CMORPH exceeds TRMM rain durations. Observed duration of precipitation events in CMORPH over oceans are 12–15 h in the tropics and subtropics, much less than the ~20 h for CESM. Hence, the observational results differ somewhat but both are considerably different from the model, which has too much precipitation overall, and it precipitates far too often at low rates and not enough for intense rates, with the divide about 1–2 mm h−1. There is a need to properly represent precipitation phenomena and processes either explicitly or implicitly (parameterized).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

DOE OSTI2014

Models Derived from In Vitro Analyses of Spleen, Liver, and Lung Leukocyte Functions Predict Vaccine Efficacy against the Francisella tularensis Live Vaccine Strain (LVS)

Currently, there are no licensed vaccines and no correlates of protection against Francisella tularensis, which causes tularemia. We recently demonstrated that measuring in vitro control of intramacrophage bacterial growth by murine F. tularensis-immune splenocytes, as well as transcriptional analyses, discriminated Francisella vaccines of different efficacies. Further, we identified potential correlates of protection against systemic challenge. Here, we extended this approach by studying leukocytes derived from lungs and livers of mice immunized by parenteral and respiratory routes with F. tularensis vaccines. Liver and lung leukocytes derived from intradermally and intranasally vaccinated mice controlled in vitro Francisella Live Vaccine Strain (LVS) intramacrophage replication in patterns similar to those of splenocytes. Gene expression analyses of potential correlates also revealed similar patterns in liver cells and splenocytes. In some cases (e.g., tumor necrosis factor alpha [TNF-α], interleukin 22 [IL-22], and granulocyte-macrophage colony-stimulating factor [GM-CSF]), liver cells exhibited even higher relative gene expression, whereas fewer genes exhibited differential expression in lung cells. In contrast with their strong ability to control LVS replication, splenocytes from intranasally vaccinated mice expressed few genes with a hierarchy of expression similar to that of splenocytes from intradermally vaccinated mice. Thus, the relative levels of gene expression vary between cell types from different organs and by vaccination route. Most importantly, because studies comparing cell sources and routes of vaccination supported the predictive validity of this coculture and gene quantification approach, we combined in vitro LVS replication with gene expression data to develop analytical models that discriminated between vaccine groups and successfully predicted the degree of vaccine efficacy. Thus, this strategy remains a promising means of identifying and quantifying correlative T cell responses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

MODFLOW6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, Southern Nevada

The hydrograph for well ER-5-3-2 in Frenchman Flat, southern Nevada, has previously unexplained water-level fluctuations. Four, three-dimensional, groundwater models (MODFLOW 6) were developed to evaluate potential stresses and hydrologic conditions affecting the well ER-5-3-2 hydrograph. Four model scenarios were developed that simulated: (1) wellbore leakage without recharge, (2) wellbore leakage with recharge, (3) shallow (low transmissivity) and deep (high transmissivity) carbonate rocks, and (4) lateral heterogeneity of carbonate rocks. Input and output files for the four model scenarios are in the model and output directories, respectively. Hydraulic conductivity, specific storage, and wellbore-leakage rates (when simulated) were estimated with parameter estimation (PEST) by minimizing a weighted composite, sum-of-squares objective function. The objective function was informed by measurement and Tikhonov regularization observations. Measurement observations included drawdowns from the constant-rate aquifer test and water-level altitudes measured in well ER-5-3-2 from 2001-2021. Tikhonov regularization informed hydraulic conductivity and specific storage parameters that were insensitive to measurement observations, where homogeneity was the preferred relation. Batch files, executables, and MODFLOW 6, PEST, and post-processing utilities are in the ancillary directory. Supplementary data also are included in the ancillary directory, including site information, high-frequency water-level and aquifer-test data, transmissivity estimates, water-chemistry data, and water-temperature analyses. This USGS data release contains data, analyses, and model files for the simulations and analysis results described in U.S. Geological Survey Scientific Investigations Report (https://doi.org/10.3133/sir20225132).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Global Sensitivity Analyses for Test Planning with Black-Box Models for Mars Sample Return

This work describes sensitivity analyses performed on complex black-box models used to support experimental test planning under limited resources in the context of the Mars Sample Return program, which aims at bringing to Earth rock and atmospheric samples from Mars. We develop a systematic workflow that allows the analysts to simultaneously obtain quantitative insights on key drivers of uncertainty, on the direction of impact, and the presence of interactions. We apply novel optimal transport-based global sensitivity measures to tackle the multivariate nature of the output. On the modeling side, we apply multi-fidelity techniques that leverage low-fidelity models to speed up the calculations and make up for the limited amount of high-fidelity samples, while keeping these in the loop for accuracy guarantees. The sensitivity analysis reveals insights useful for the analysts to understand the model's behavior and identify the factors to focus on during testing in order to maximize the value of information extracted from them to ensure mission success when limited resources are available.

Giuseppe Cataldo↗

DOE OSTI2025

Enhancing approximate modular Bayesian inference by emulating the conditional posterior

In modular Bayesian analyses, complex models are composed of distinct modules, each representing different aspects of the data or prior information. In this context, fully Bayesian approaches can sometimes lead to undesirable feedback between modules, compromising the integrity of the inference. The “cut-distribution” prevents unwanted influence between modules by “cutting” feedback. The direct sampling (DS) algorithm is standard practice for approximating the cut-distribution, but it can be computationally intensive, especially when the number of imputations required is large. An enhanced method is proposed, the Emulating the Conditional Posterior (ECP) algorithm, which leverages emulation to increase the number of imputations. Through numerical experiment it is demonstrated that the ECP algorithm outperforms the traditional DS approach in terms of accuracy and computational efficiency, particularly when resources are constrained. Here, it is also shown how the DS algorithm can be improved using ideas from design of experiments. Some practical recommendations are given for algorithm choice in modular Bayesian analyses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

New insights into fuel blending effects: Intermolecular chemical kinetic interactions affecting autoignition times and intermediate-temperature heat release

Fuel blending effects on chemically-dominated fuel properties, such as gasoline anti-knock quality, are influenced by fundamental chemical kinetic interactions between the blending agent and the base fuel. Historically, quantification of such interactions has focused on changes to the radical pool, including $\dot{O}$H and HO 2 , while intermolecular interactions pertaining to carbonated, non-fuel-specific intermediates are typically overlooked. In this regard, this work aims to derive new insight into intermolecular chemical kinetic interactions that are intrinsic to fuel blending effects via a case study on blends of 0–30% ethanol (by volume) into FGF-LLNL (a multi-component gasoline surrogate for FACE-F research gasoline) using a rapid compression machine at a diluted/stoichiometric fuel loading, compressed pressure of 40 bar and low- to intermediate-temperature regimes that are representative of boosted SI engine operation. Ethanol blending effects on the intermediate temperature heat release (ITHR) of FGF-LLNL are characterized using experimental measurements, where ethanol is found to promote the extent of ITHR and suppress the transition from ITHR to main ignition. Chemical kinetic modeling is undertaken using a recently updated gasoline surrogate model. Sensitivity analyses on ITHR characteristics further corroborate the ethanol blending effects, and highlight the significant dependence of ITHR on both fuel-specific and non-fuel-specific reactions. An approach allowing comprehensive characterization of the complex intermolecular chemical kinetic interactions between constitutes in a fuel blend is then proposed. Application of the approach to FGF-LLNL/E0–E30 reveals that ethanol perturbs the heat release and autoignition characteristics of FGF-LLNL not only by directly changing the $\dot{O}$H and HO 2 radical pools via fuel-specific reactions, but also through intermolecular interactions where participating intermediates can be produced and consumed by various sub-chemistries. Disabling the intermolecular interactions in carbonated species between ethanol and FGF-LLNL sub-chemistries leads to somewhat slower ITHR evolution and lower ignition reactivity. The role of the individual intermolecular interaction is also characterized using the proposed approach. Lastly, implications of intermolecular interactions for future studies that aim to improve model performance are highlighted, where it is found that further investigations on the core C0-C4 chemistry are needed for developing highly accurate chemistry models for complex fuel blends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

MSD CoP Webinar: Accounting for distributive justice in model-based decision support

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Model-based analyses play an ever-increasing role in informing policy and decision-making. However, many large-scale societal challenges unavoidably involve questions about the fair distribution of positive and negative consequences. How are the costs of the energy transition distributed over households and businesses? How are flood risks redistributed under different flood risk management plans? How are the impacts of climate change and climate mitigation distributed over different parts of the world?These kinds of questions play an important role when deliberating public policy, and the lack, in many cases, of clear answers becomes an obstacle to decision-making. At recent COPs, for example, wicked questions about loss and damages and the phase-out versus phase-down of coal became obstacles to global climate action, illustrating the misalignment of the direction of scientific research and decision-makers' information needs. In this talk, I'll explore advances that are being made that enable analysts to start providing grounded model-based answers to questions of distributive justice, as well as argue that analysts should embrace and explicate the normative nature of their work instead of hiding behind the purported neutrality of science. Presenters: Dr. Jan Kwakkel (Delft University of Technology) Moderator(s): Rebecca Saari (MSD CoP Working Group Co-Chair; Univ. of Waterloo), Matt Sparks (Univ. of Waterloo); Sarah Fletcher (MSD CoP Working Group Co-Chair; Stanford University), Juan Moreno-Cruz (Univ. of Waterloo), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 13, 2024 from 1 PM - 2:15 PM ET

Kwakkel, Jan H.↗

DOE OSTI2022

The Feasibility and the Benefits of the Advanced Nuclear Fuel Pellet Designs with Radially Varying Fuel Zoning and Burnable Poison Concentration (Final Summary Report)

As part of the work supported by the US Department of Energy (DOE) Office of Nuclear Energy (NE) Gateway for Accelerated Innovation in Nuclear (GAIN) FY 2021 Voucher, Exelon Generation, now Constellation, and Oak Ridge National Laboratory (ORNL) entered into a cooperative research and development agreement (CRADA) to evaluate and assess the feasibility and impact of various conceptual advanced nuclear fuel pellet designs (ANFPDs). The objective of this project was to perform modeling and simulation and analyses using the advanced modeling and simulation capabilities of VERA/BISON, developed by DOE, to determine the viability and benefits of numerous advanced nuclear fuel pellet design concepts in terms of fuel cycle costs, operational safety, and margin improvement. Whereas the detailed coupled neutronic and thermal hydraulic analyses performed using VERA provided in-depth knowledge in terms of fuel cycle performance, the detailed VERA results were used in subsequent fuel performance analyses using BISON. These subsequent analyses focused on several key fuel performance criteria, such as peak fuel centerline temperature (FCT), fission gas release (FGR), gap closure, plenum pressure, and cladding hoop stress. These key fuel performance criteria were analyzed for some of the conceptual fuel designs and were compared with the results obtained for UO 2 fuel. The results provided detailed information to enable better understanding of the performance of the fuel types analyzed. Understanding the advantage of loading these conceptual fuel designs into the core is important not only to Constellation but also to the entire light-water reactor (LWR) fleet in the United States.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2012

Physics Mining of Multi-Source Data Sets

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

Helly, John↗

DOE OSTI2019

Status Update on IAEA MODARIA II Working Group 1 (Assessment and Decision Making) - 19391

During WM2018, the work being done under the International Atomic Energy Agency (IAEA)'s Modelling and Data for Radiological Impact Assessments (MODARIA) II Programme (https://wwwns.iaea.org/projects/modaria/modaria2.asp?s=8 and l=129) was introduced. The Programme comprises seven working groups covering a wide range of topics. Amongst them, Working Group 1 (WG1) is focused on dose assessment and decision aiding tools to address existing exposure situations due to past practices involving naturally occurring radioactive material (NORM) and nuclear legacy sites. Specifically, this covers the development of methods and toolsets for risk-informed decision-making for such complex sites, and includes practical demonstration of decision-making processes and tools through case studies. During 2018 WG1 participants met twice to discuss the status and plans of work being conducted by the WG. The group held its Second Interim Meeting from 7 to 11 May 2018 at the Jozef Stefan Institute (JSI) in Ljubljana, Slovenia. The objectives of the meeting were to: (1) Discuss the status of WG1 work; (2) Start preparation of the interim draft version of the MODARIA II WG1 Report (herein referred to as the 'Interim Report'); (3) Review the progress of planned data analyses, model-model comparisons, and model-data comparisons being conducted through case studies for the Tessenderlo Chemie Site in Belgium, the Zapadnoe Uranium Mill Tailings Site in Ukraine, and a Former Tin Processing Facility Site in Brazil; (4) Discuss calculations conducted for a NORM Site in China for potential addition to the WG1 case studies; (5) Report on progress on topical studies and other assignments performed to support the preparation of several sections of the Interim Report; and (6) Discuss plans for incorporating some preliminary case studies considered by MODARIA I WG1 and MODARIA I WG3. During the meeting in Slovenia, WG1 participants also visited the Zirovski vrh (RZV) Uranium Mine and Mill Tailings Site near Ljubljana. From 22 to 25 October 2018, WG1 members also participated in the MODARIA II Third Technical Meeting in Vienna, Austria. The meeting facilitated analysis of the progress made so far by the seven working groups, as well as exploration of the dissemination of the results of the MODARIA II Programme through publication in scientific journals dealing with the various subject areas covered by the Programme. WG1 participants focused on the preparation of its Interim Report, and engaged in technical exchanges with the IAEA Le Trench Project on characterization, assessment, remediation and management of buried waste at legacy trench sites, as well as the To Enhance uncertainties Reduction and stakeholders Involvement Towards integrated and graded Risk management of humans and wildlife In long-lasting radiological Exposure Situations (TERRITORIES) project (https://territories.eu/). Currently, WG1 is in the process of preparing a draft report to document the results of its various case studies and special topics, and is preparing for the final Interim Meeting in May 2019 and the final Technical Meeting in October 2019, before the conclusion of the MODARIA II Program at the end of 2019. This paper will provide a status update of these activities, along with preliminary information on the WG1 report, including potential recommendations for future activities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Phase Diagrams and Electromagnetic Propertiesof s–wave Superconductivity of the Extended Hubbard Model with the Attractive Pair–Hopping Interaction

The characteristics of the extended Hubbard model with the pair–hopping interaction J, i.e. the Penson–Kolb–Hubbard model, are analysed for the case of attractive J (J > 0). The effects of on–site U interaction on the properties of the s–wave superconducting state and mutual stability of the superconducting s–wave and magnetic orderings are examined. The electromagnetic and thermodynamic characteristics of the s–wave superconducting phase for arbitrary particle concentration n and interactions are analysed. The system is evaluated for the case of nearest–neighbours hopping on d–dimensional hypercubic d = 2 (SQ) and d = 3 (SC) nonfrustrated lattices. For SQ lattice the effects of phase fluctuations on the properties of the superconducting state are discussed within the Kosterlitz–Thouless (KT) scenario. The KT critical temperatures T{sub KT} are calculated and compared to the T{sub c} obtained within the BCS–HFA. The Uemura type plots, T{sub KT} vs. λ{sup 2}(0), are obtained and evaluated as a function of pairing strength and concentration. The results are compared with the case of repulsive J (J < 0) pair–hopping interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

On a Unified Core Characterization Methodology to Support the Systematic Assessment of Rare Earth Elements and Critical Minerals Bearing Unconventional Carbon Ores and Sedimentary Strata

A significant gap exists in our understanding and ability to predict the spatial occurrence and extent of rare earth elements (REE) and certain critical minerals (CM) in sedimentary strata. This is largely due to a lack of existing, systematic, and well-distributed REE and CM samples and analyses in United States sedimentary basins. In addition, the type of sampling and characterization performed to date has generally lacked the resolution and approach required to constrain geologic and geographic heterogeneities typical of subsurface, mineral resources. Here, we describe a robust and systematic method for collecting core scale characterization data that can be applied to studies on the contextual and spatial attributes, the geologic history, and lithostratigraphy of sedimentary basins. The methods were developed using drilled cores from coal bearing sedimentary strata in the Powder River Basin, Wyoming (PRB). The goal of this effort is to create a unified core characterization methodology to guide systematic collection of key data to achieve a foundation of spatially and geologically constrained REEs and CMs. This guidance covers a range of measurement types and methods that are each useful either individually or in combination to support characterization and delineation of REE and CM occurrences. The methods herein, whether used in part or in full, establish a framework to guide consistent acquisition of geological, geochemical, and geospatial datasets that are key to assessing and validating REE and CM occurrences from geologic sources to support future exploration, assessment, and techno-economic related models and analyses.

54 ENVIRONMENTAL SCIENCES↗