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At least 217 records · Page 12

Redox and mineral controls on Fe and Ti isotopic fractionations during calc-alkaline magmatic differentiation

Titanium and Fe isotopic compositions of lavas from a calc-alkaline differentiation suite and corresponding mineral separates from the Rindjani Volcano, Indonesia show that Fe and Ti isotopic fractionations between minerals and melts are lower than those recorded in other suites at all stages of differentiation. Here, the limited isotopic fractionation for Ti is likely due to low-Ti magnetite and clinopyroxene being the dominant carriers of Ti in Rindjani lavas, as these minerals are thought to have limited equilibrium Ti isotopic fractionation relative to silicate magmas. Other magmatic differentiation suites controlled by removal of Ti-rich magnetite and characterized by a lesser role of clinopyroxene have larger Ti isotopic fractionations. This effect is an indirect consequence of the elevated Fe 3+ /Fe 2+ ratio of calc-alkaline magmas such as Rindjani, which promotes Fe 3+ incorporation into magnetite at the expense of Fe 2+ -Ti 4+ pairs, such that increased oxygen fugacity will subdue Ti isotopic fractionation in global magmatic series. Similarly, we find negligible Fe isotopic fractionation in Rindjani bulk rocks and mineral separates, unlike previous studies. This is also likely due to the oxidized nature of the Rindjani differentiation suite, which leads to similar Fe 3+ /Fe 2+ ratios in melt and minerals and decreases overall mineral-melt Fe fractionation factors. Paired Ti and Fe isotopic analyses may therefore represent a powerful tool to assess oxygen fugacity during differentiation, independent from Fe 3+ determinations of erupted samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of electron backscattering in the MCNP6.3 code

A new electron backscattering validation suite has been developed for the MCNP® code. The calculations in this suite cover both condensed history and single-event transport methods, seven different elemental materials ranging from beryllium to uranium, and incident electron energies from 200 eV to 14.1 MeV. In general, the accuracy of the MCNP code for electron backscattering calculations is energy-dependent. For incident electron energies below 2 keV, the condensed history method is not applied while the single-event method shows poor agreement with experimental measurements due to poor accuracy of the underlying atomic data. For incident energies between 2 keV and 256 keV, the single-event method typically shows better agreement with experiments, while for incident energies above 256 keV the condensed history method gives better accuracy. Additionally, agreement with experimental data is generally worse for low- Z materials such as beryllium and carbon, which may reflect deficiencies in the data or physics underlying electron transport through light elements in the MCNP code. The new electron backscattering validation suite, along with the previously introduced electron stopping power and Lockwood energy deposition validation suites, provide MCNP users with a quantified understanding of the uncertainties in electron transport calculations. Future improvements to electron transport in the MCNP code are necessary for low energies (≤ 2 keV) and for low- Z materials.

36 MATERIALS SCIENCE↗

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗

Validation of Fast Reactor Depletion Tools Using EBR-II Measured Data

The validation of simulation tools for calculating fuel depletion and evolution in fast reactors is vital for design, licensing, deployment, operations, and material accountancy. The Physics Analysis Database (PADB) and Analytical Laboratory (AL) database contain measured data collected from Experimental Breeder Reactor II (EBR-II) and were used to validate the most recent versions of the Argonne Reactor Computation (ARC) tool suite and ORIGEN-S for calculating isotopic compositions in irradiated fast reactor fuel. The PADB contains important modeling and operational information about the EBR-II core design, fuel cycle, and analytical results from the legacy versions of the ARC tool suite. The AL database contains the measured isotopic compositions of irradiated samples taken from core subassemblies. A new procedure was developed for the ARC tool suite to perform the EBR-II depletion simulation, as well as to perform more detailed isotopic calculations using ORIGEN-S calculations by coupling it with the ARC suite. Both the ARC and ARC-ORIGEN results were compared with the AL measured data for all relevant samples and showed good agreement for the major actinides. Good agreement with measured data was also achieved using the ARC-ORIGEN approach for several fission products.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NISQ Benchmarking

Test suite of quantum algorithms for Noisy Intermediate Scale Quantum (NISQ) computers. The test suite includes benchmark-style code for quantum volume circuits (QV), fairness sampling circuits, quantum telecloning circuits, and other NISQ benchmark style algorithms on small problems (i.e., up to 100 qubits), such as Variational Quantum Eigensolver (VQE), Hamiltonian Simulation, and Grover unstructured search example circuits. These benchmark-style applications are implemented in quantum software packages, mostly IBM's QISKIT, but may include vendor-specific frameworks, such as PyQuil (for Rigetti) or Q\# for Microsoft, or CirQ (for Google) as the test suite grows with the vendor sample. The test suite also includes numerical simulation code for Quantum Alternating Operator Ansatz (QAOA) algorithms, VQE, Hamiltonian Simulation and search examples. Numerical simulation code simulates quantum computers on classical computers, which is only possible for small problem instances; the implementation framework of choice is typically within Python, using the numpy/scipy libraries as well as extensions to the Julia language.

Pelofske, Elijah↗

Iodine Waste Form Corrosion: PNNL Summary Testing Report

A test method to correlate the laboratory corrosion behavior of iodine-containing waste forms (IWFs) to a conceptual long-term corrosion models is required. Several candidate methods have been evaluated previously, and each method presents unique challenges and limitations. Dynamic leach tests have emerged as the preferred candidate test method to evaluate IWFs and parameterize an eventual long-term corrosion model. This report was prepared in support of this effort to define the test suite to evaluate the corrosion of IWFs, with the goal of defining and parameterizing a conceptual long-term corrosion model. A review was presented highlighting the high degree of variability between the IWF corrosion data that is available in the literature and the need for a standardized test suite. The targeted test suite is composed of a single interval screening test, a dynamic leach test, and post-test solid characterization of the monolithic IWF samples. The data presented serves two purposes: to expand the range of IWFs evaluated with the test suite to assess method variability and to further understand the corrosion of IWFs to best inform conceptual long-term corrosion model development. A series of IWF types were included in the testing, including hot isostatically pressed Ag-mordenite, silver functionalized silica-based aerogels, iodosodalites (hot isostatic pressing, sintered, glass bonded ceramic), iodoapatite, tellurite glass and glass composite materials.

42 ENGINEERING↗

Sierra/SolidMechanics Verification Report

This document presents the Sierra/SolidMechanics (Sierra/SM) verification plan. This plan centers on the tests in the Sierra/SM verification test suite, a subset of which are documented in the Sierra/SM Verification Tests Manual. Most of these tests are run nightly with the Sierra/SM code suite, and the results of the tests are checked against analytic solutions. For each of the tests presented in the Verification Tests Manual, the test setup, a description of the analytic solution, and comparison of the Sierra/SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This verification plan discusses these various types of tests and what they mean for Sierra/SM verification. Many other activities also contribute to Sierra/SM quality. These address code and solution quality and range from low-level unit tests, run nightly, up to full-fidelity acceptance tests, used to verify release stability. This acceptance test suite checks that new versions of Sierra/SM continue to yield the same answers for high-resolution analyst problems. Further code quality measures include an extensive suite of intermediate-size regression tests and automated nightly code quality checks. While these additional activities do not fall under a strict definition of verification, they greatly add to the quality, stability, and reliability of Sierra/SM, and are discussed here as well.

97 MATHEMATICS AND COMPUTING↗

Triton: Environmental Monitoring Technology Development, Collision Risk Data Collection (Final Report)

In this project, we assembled a sensor suite that combines a scientific echosounder (sonar) system with video and acoustic cameras (secondary sensors). The sensor suite generates data that is amenable to automated target detection algorithms and can provide inputs to animal encounter models. We developed software (archiving software) to collect data simultaneously from all sensors in the suite, analyze the sonar data automatically in near real-time to identify time periods when targets of interest were present, and automatically archive data from the secondary sensors for these time periods. The product of the archiving software is a data set for the secondary sensors, containing data only for the times when targets of interest were determined to be present by the sonar. We performed controlled field testing to verify the operation of the sensor suite and the archiving software.

47 OTHER INSTRUMENTATION↗

Route Energy Prediction (RouteE) Powertrain Validation Report

The National Renewable Energy Laboratory's flagship package in the RouteE suite, RouteE-Powertrain, is a mesoscopic energy model that predicts vehicle energy consumption given discrete attributes that describe each segment or link in a vehicle's path on a road network. High-frequency, physics-based, powertrain simulators, such as NREL's FASTSim, are well-suited to model vehicle energy consumption when real driving data and a detailed understanding of the vehicle powertrain specifications are available. However, there are a variety of situations in the past, present (real-time), and future where high-frequency driving data and/or vehicle information may not be available, but reliable energy consumption is still desired, such as energy-aware vehicle routing. These are the ideal applications for RouteE-Powertrain. The suite of RouteE tools also includes RouteE-Compass, which is an eco-routing software that incorporates energy consumption into network routing algorithms, and RouteE-Mobile, which is a prototype smartphone navigation app to demonstrate the integrated capabilities of the RouteE suite for real-world eco-routing. The focus of this validation report is to share key metrics about the data sets and models behind RouteE-Powertrain. The set of RouteE-Powertrain models discussed in this report are made available through the RouteE web API through the NREL Developer Network.

33 ADVANCED PROPULSION SYSTEMS↗

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations

We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over DM physics, astrophysics, and cosmology in modeling a range of systems—from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of warm dark matter (WDM), each comprising 1024 simulations generated using the arepo code. One suite consists of uniform-box simulations covering a ${(25\,{h}^{-1}\,{\rm{Mpc}})}^{3}$ volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the WDM particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and convolutional neural networks, to demonstrate how such simulation suites can be used to disentangle the effects of DM and baryonic physics on galactic properties. The DREAMS project can be extended further to include different DM models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of DM on these scales.

cosmological parameters↗

Improved Verification and Validation Testing and Tools including Nuclear Criticality Safety Applications with the MCNP6.3® Code [Abstract]

A new Python-based framework has been developed to enable a more consistent layout with automatable setup, execution, and documentation of all verification and validation (V&V) test suites previously established for use with the MCNP code. In this paper, the new general framework for the V&V test suites is discussed, including information on all of the current capabilities and plans for future capabilities. For nuclear criticality safety applications, the existing V&V benchmark problems within the criticality, extended criticality, and analytic k-effective test suites have been ported into this new framework. In addition, the status and updates to the Rossi-alpha and subcritical multiplicationtest suites will be discussed. Some V&V results exercising new MCNP6.3 capabilities will be demonstrated.

97 MATHEMATICS AND COMPUTING↗

Gallium isotopic constraints for the origin of the Earth-Moon system

Comparatively heavy isotopic compositions of moderately volatile elements (MVE) in lunar rocks have been advocated to reflect the loss of light isotopes during devolatilization processes from the Moon. In this study we present new gallium (Ga) isotope data for lunar highland rocks, with a focus on the Ferroan Anorthosite Suite (FAS). These are commonly thought to be direct crystallization products from the late lunar magma ocean (LMO) and should contain the majority of the Ga inventory of the Moon. As such, FAS rocks are crucial for identifying the processes that drove Ga isotope fractionation as well as for inferring the Ga isotopic composition of the bulk Moon. Our data reveal that FAS samples have a range in δ 71 Ga from -0.27 to 0.22‰ and are generally isotopically light in Ga compared to other lunar lithologies, but straddle values typical of terrestrial rocks. Although Ga is defined as an MVE, these Ga isotope variations do not correspond with concentrations of more volatile elements, indicating that Ga isotope variations in the FAS are not primarily controlled by devolatilization processes. Instead, the Ga isotopic compositions of bulk FAS rocks broadly correlate with the composition of plagioclase, with the calcium content of plagioclase decreasing as Ga becomes isotopically heavier. This suggests that fractionation of Ga isotopes in FAS rocks was caused by the preferential incorporation of isotopically light Ga into plagioclase during the later solidification stages of the LMO. The progressive crystallization and extraction of plagioclase forces the residual melt towards increasingly heavier Ga isotope ratios, corroborating similar conclusions derived from correlations between δ 71 and Eu* in the mare basalt suite. Using Ga isotope partitioning calculations, we demonstrate that an isotope fractionation coefficient between plagioclase and coexisting melt of -0.3 to -0.4‰ could explain the observed range of δ 71 values in FAS, mare basalt suite rocks, and KREEP. These calculations allow for a first order estimate of the Ga isotopic composition of the bulk silicate Moon prior to plagioclase fractionation and suggest it was close to the composition of the bulk silicate Earth. This would imply that the Moon did not lose a substantial fraction of its Ga inventory during accretion, consistent with new constraints from Rb-Sr isotope systematics that indicate the Moon's volatile deficit was primarily inherited from Theia. In conjunction with the overlap in non-mass-dependent isotope ratios, these collective observations could be reconciled if Theia and the proto-Earth formed in similar regions of the inner Solar System that were already volatile-depleted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Apatite geochemistry as a tool for understanding the petrogenesis of layered mafic-ultramafic rocks in the Bushveld Complex, South Africa

The sources of the magmas that formed the Rustenburg Layered Suite of the Bushveld Complex in South Africa remain debated, despite decades of research. Vertical and lateral variation in bulk rock and mineral separate Sr-Nd isotopic compositions, which generally indicate enriched sources, demonstrate that the layered sequence was formed by the emplacement of multiple batches of magma, crucially resulting in episodes of PGE-Cr-V mineralisation. The Lu-Hf isotope compositions of zircon are, however, at odds with the bulk rock Sr-Nd isotopic heterogeneity as they show near homogeneous compositions throughout the layered sequence (εHf (2.06 Ga) =−8). This lack of variation in Hf isotope composition has been attributed to deep, continental lithospheric mantle-related and/or crustal contamination of plume-derived Bushveld magmas. In this study, we analysed the major, trace element and Sr-Nd isotope geochemistry of apatite in the Rustenburg Layered Suite. Apatite occurs as an intercumulus mineral in the lowermost regions and a cumulus mineral in the uppermost regions of the layered sequence and can therefore be used to test existing models for the isotopic disequilibrium between bulk rock Sr-Nd and zircon Hf isotopic compositions. Apatite is largely chlorapatite in the lowermost regions and fluorapatite in the uppermost regions of the layered sequence. The Merensky Reef is unusual in that it comprises both chlorapatite and fluorapatite. Apatite throughout the layered sequence is generally unzoned and shows no evidence of late-stage alteration. Trace element data show that apatite is enriched in L/HREE, with common negative Eu-Sr anomalies. These trace element signatures are consistent with a magmatic origin for the apatite grains, with prior, or concurrent, plagioclase crystallization from the same melt. Variability in in situ Sr and Nd isotope compositions of apatite is recorded throughout the layered sequence with εNd (2.06 Ga) compositions varying between −2.5 and − 10.2 and initial 87 Sr/ 86 Sr compositions varying between 0.7079 and 0.7103 (for the Marikana dikes only). The variability in Sr-Nd isotope compositions of apatite is consistent with the bulk rock (and mineral separate) variation in Sr-Nd isotope compositions, suggesting apatite preserves primary magmatic compositions in the Rustenburg Layered Suite.

Apatite↗

Improved Verification and Validation Testing and Tools [Slides]

All MCNP team supported V&V test suites are now developed in a separate repository from the MCNP source code within a Python-based framework. This entire framework will be distributed with the upcoming MCNP6.3 release. Most V&V test suites distributed with MCNP6.2 will be distributed in new framework. New V&V test suites are done or being worked on for the MCNP6.3 release.

97 MATHEMATICS AND COMPUTING↗

MCNP® Code Version 6.3.1: Verification & Validation Testing (Rev.1)

This report describes the verification and validation testing performed on MCNP® code version 6.3.1. The purpose of this report is to act as a compendium of test suite descriptions and results. Accordingly the document is divided into two parts. Part I (this part) describes each test suite in the following sections. Part II provides the results of testing each suite and comparisons to experimental and/or alternative computational results, as appropriate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Whole plant traits of coastal dune vegetation and implications for interactions with dune dynamics

Abstract Coastal dunes are important protective features against sea level rise and coastal storms. Interactions between dune plant aboveground structures and sediment trapping that allow for dune building and maintenance are well established. More recently, studies documenting belowground biomass for promoting erosion resistance in dominant dune species have been conducted, yet a knowledge gap remains regarding species‐specific characterization of whole plants, specifically with respect to roots, rhizomes, and belowground stems. Our objective was to quantify above‐ and belowground traits of four dominant dune grasses to document the potential for species‐specific effects on dune growth, maintenance, and erosion resistance. We examined above‐ and belowground traits among four prominent dune grasses of the Atlantic and Gulf Coasts of North America: Ammophila breviligulata , Panicum amarum , Spartina patens , and Uniola paniculata . Whole plant samples of each species were collected from the foredune at the US Army Engineer Research and Development Center's Field Research Facility in Duck, North Carolina, USA, and quantified for several above‐ and belowground traits (e.g., stem height, rhizome number and length, root surface area by diameter class, root tensile strength, and mycorrhizal percent infection). Belowground factors known to impact important dune processes, such as rhizome length, mycorrhizal percent infection, and root traits, differed substantially among species. When visualized in multivariate space, all species significantly differed in suites of above‐ and belowground traits. When considering belowground only, Ammophila and Spartina were similar, despite differences in biomass allocation. Species separated along axes related to mycorrhizal association, biomass allocation, and root construction. The four co‐occurring dune grass species were dissimilar in suites of plant traits. Belowground trait differences were driven by those describing root construction, biomass allocation, and mycorrhizal infection. Dissimilarity in above‐ and belowground suites of traits may demonstrate different approaches for surviving the dune environment. Incorporating belowground traits into modeling will enhance predictions of dune response to climate change through interactions between vegetation and dune dynamics that facilitate coastal resistance and resilience.

54 ENVIRONMENTAL SCIENCES↗

Triple oxygen and hydrogen stable isotope composition of water in Murchison carbonaceous chondrite accessed by thermogravimetry-enabled laser spectroscopy

For this work, we have developed the capability to measure 17 O/ 16 O in H 2 O and OH - of hydrous minerals by a technique using thermogravimetric analysis coupled with isotope ratio infrared spectroscopy (TGA-IRIS) on a suite of liquid water standards, terrestrial mineral standards, multi-mineral synthetic mixtures of terrestrial samples, and Murchison carbonaceous chondrite. This 17 O/ 16 O analytical capability is combined with the previously developed TGA-IRIS capability of 18 O/ 16 O, which enables us to calculate Δ `17 O values. Additionally, we have made 2 H/ 1 H measurements by TGA-IRIS on the suite of materials. Analyses of 328 standard water samples sealed into silver tubes (0.25 μL, 174 VSMOW and 154 GISP) analyzed over the course of three years yielded δ 18 O values by TGA-IRIS with precision of ±0.30 ‰, δ 17 O of ±0.24 ‰, Δ `17 O of ±0.126 ‰, and δ 2 H ± 7.5 ‰ (± 1 Std. Dev.). TGA-IRIS analyses of a suite of hydrous minerals (oxy-hydroxide, mica, serpentines, sulfide, phyllosillicates) yields similar precision. TGA-IRIS analyses of the CM2 carbonaceous chondrite Murchison resulted in δ 18 O, δ 17 O, Δ `17 O, and δ 2 H values of the H 2 O and/or OH - from its hydrous minerals. Δ `17 O values of Murchison H 2 O range from 1.034 ‰ at 350 °C, to -0.368 ‰ at 650 °C, to -1.75 ‰ at 850 °C. TGA-IRIS can generate Δ `17 O values of H 2 O and/or OH - in hydrous materials that are well within the precision needed for the analysis of meteoritic samples, as well as samples returned from asteroids, such as Ryugu and Bennu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗