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At least 703 records · Page 39

Detailed Investigations of Interactions between Ionizing Radiation and Neutral Gases

We are investigating phenomena that stem from the many body dynamics associated with ionization of an atom or molecule by photon or charged particle. Our program is funded through the Department of Energy EPSCoR Laboratory Partnership Award in collaboration with Lawrence Berkeley National Laboratory. We are using variations on the well established COLTRIMS technique to measure ions and electrons ejected during these interactions. Photoionization measurements take place at the Advanced Light Source at LBNL as part of the ALS-COLTRIMS collaboration with the groups of Reinhard Dörner at Frankfurt and Ali Belkacem at LBNL. Additional experiments on charged particle impact are conducted locally at Auburn University where we are studying the dissociative molecular dynamics following interactions with either ions or electrons over a velocity range of 1 to 12 atomic units.

74 ATOMIC AND MOLECULAR PHYSICS↗

Additive Manufactured Materials Studies

The production of additively manufactured (AM) materials, is a growing technology that potentially offers more cost effective ways to produce metallic components for various uses. Mechanical properties of some AM metals have been studied, but more work is needed to better understand their dynamic properties as a function of orientation. Due to the melting and reheating of molten metal during fabrication, these materials tend to have internal porosity and slightly different microstructures along the weldments and normal to the weldments that may cause the materials to behave differently than their forged counterparts. The AM process builds up a part layer by layer, which provides opportunities to tailor geometry and optimize structural performance in addition to minimizing the amount of material waste for oddly shaped parts, thereby reducing cost. These advanced materials hold great promise for revolutionizing design, fabrication, and assembly of engineered components and could be used for many NNSA-specific applications including armoring complex elements of nuclear weapons, and customized diagnostic components in subcritical experiments. We have conducted materials studies in collaboration with the University of Nevada, Las Vegas (UNLV) as well as Los Alamos National Laboratory (LANL) under our Site-Directed Research and Development program and the Nevada Science Initiative. We are currently placing emphasis on quantifying how dynamic properties are affected by directionality and porosity of the material. A study of dynamic failure events in forged, layered, and additive manufactured (AM) titanium alloy subject to hypervelocity impact was conducted in collaboration with UNLV. Experiments were conducted using a two stage light-gas gun, 0.22-caliber Lexan projectiles, and different types of titanium target plates. A four-channel Photonic Doppler Velocimetry (PDV) system was used to study the free surface velocities to provide an understanding of the different failure mechanisms in these materials. The experimental measurements were used to validate computational simulations, which describe the behavior of these materials under shock. It was determined that AM, forged titanium, and multi-layered stacks produce similar velocity profiles during the early stage of impact, with the AM targets exhibiting spall at lower velocities and the multi-layered stacks exhibiting vibrations between plates. Simulations of solid and layered forged materials provide a good match to experimental data.

36 MATERIALS SCIENCE↗

MO-FG-BRA-07: Intrafractional Motion Effect Can Be Minimized in Tomotherapy Stereotactic Body Radiotherapy (SBRT)

Purpose: Tomotherapy has unique challenges in handling intrafractional motion compared to conventional LINAC. In this study, we analyzed the impact of intrafractional motion on cumulative dosimetry using actual patient motion data and investigated real time jaw/MLC compensation approaches to minimize the motion-induced dose discrepancy in Tomotherapy SBRT treatment. Methods: Intrafractional motion data recorded in two CyberKnife lung treatment cases through fiducial tracking and two LINAC prostate cases through Calypso tracking were used in this study. For each treatment site, one representative case has an average motion (6mm) and one has a large motion (10mm for lung and 15mm for prostate). The cases were re-planned on Tomotherapy for SBRT. Each case was planned with 3 different jaw settings: 1cm static, 2.5cm dynamic, and 5cm dynamic. 4D dose accumulation software was developed to compute dose with the recorded motions and theoretically compensate motions by modifying original jaw and MLC to track the trajectory of the tumor. Results: PTV coverage in Tomotherapy SBRT for patients with intrafractional motion depends on motion type, amplitude and plan settings. For the prostate patient with large motion, PTV coverage changed from 97.2% (motion-free) to 47.1% (target motion-included), 96.6% to 58.5% and 96.3% to 97.8% for the 1cm static jaw, 2.5cm dynamic jaw and 5cm dynamic jaw setting, respectively. For the lung patient with large motion, PTV coverage discrepancies showed a similar trend of change. When the jaw and MLC compensation program was engaged, the motion compromised PTV coverage was recovered back to >95% for all cases and plans. All organs at risk (OAR) were spared with < 5% increase from original motion-free plans. Conclusion: Tomotherapy SBRT is less motion-impacted when 5cm dynamic jaw is used. Once the motion pattern is known, the jaw and MLC compensation program can largely minimize the compromised target coverage and OAR sparing.

60 APPLIED LIFE SCIENCES↗

Architecture for Quantum Time-dependent Circuits (ArQTIC) v1.0

ArQTiC is a domain-specific full-stack software package built for the dynamic simulations of materials on quantum computers. Its main contributions include providing a software library for high-level programming of such simulations on quantum computers, and providing post-processing capabilities that allow users to more efficiently analyze results from the quantum computer. Paired with the power to optimize and execute quantum circuits, ArQTiC opens the field of dynamic materials simulations on quantum computers to a broader community of scientists from a wider range of domain sciences, paving the way for accelerated progress towards physical quantum supremacy.

Bassman, Lindsay↗

An Investigation of Time Distributions for Task Primitives to Support the HUNTER Dynamic Human Reliability Analysis

As an effort to support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method. GOMS-HRA was developed to provide cognition-based time and human error probability information for dynamic HRA calculation in the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework. HUNTER is a framework to support the dynamic modelling of human error in conjunction with other modelling tools. In this paper, we investigate time distributions using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which suggests an HRA data collection framework to complement full-scope simulator research as well as collect input data for dynamic HRA using simplified simulators such as the Rancor Microworld Simulator. In this study, time required for GOMS-HRA task primitives to satisfy thirteen statistical distributions is investigated. Then, the time distributions from student operators and professional operators are compared and discussed. As a result, this study identified several time distributions on five GOMS-HRA task primitives at a statistically significant level. According to analyses to date, a greater number of significant time distributions was found in abnormal or emergency operating procedures rather than standard operating procedures. In the future, it is expected that the result of this study can provide objective reference on elapsed time data for task primitives as well as help to realistically simulate scenarios within dynamic HRA.

99 GENERAL AND MISCELLANEOUS↗

Thermal Energy Storage Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

25 ENERGY STORAGE↗

Adaptive Dynamic Event Tree in RAVEN code

RAVEN is a software tool that is focused on performing statistical analysis of stochastic dynamic systems. RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other applications (system codes). Among the several capabilities currently present in RAVEN, there are five different sampling strategies: Monte Carlo, Latin Hyper Cube, Grid, Adaptive and Dynamic Event Tree (DET) sampling methodologies. The scope of this paper is to present a new sampling approach, currently under definition and implementation: an evolution of the DET me

Dynamic Event Tree↗

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

Achieving performance portability for high-performance computing (HPC) applications in scientific fields has become an increasingly important initiative due to large differences in emerging supercomputer architectures. Here we test some key kernels from molecular dynamics (MD) to determine whether the use of the OpenACC directive-based programming model when applied to these kernels can result in performance within an acceptable range for these types of programs in the HPC setting. We find that for easily parallelizable kernels, performance on the GPU remains within this range. On the CPU, OpenACC-parallelized pairwise distance kernels would not meet the performance standards required, when using AMD Opteron “Interlagos” processors, but with IBM Power 9 processors, performance remains within an acceptable range for small batch sizes. These kernels provide a test for achieving performance portability with compiler directives for problems with memory-intensive components as are often found in scientific applications.

Sedova, Ada↗

THERMAL DIAGNOSTICS WITH THE ATMOSPHERIC IMAGING ASSEMBLY ON BOARD THE SOLAR DYNAMICS OBSERVATORY: A VALIDATED METHOD FOR DIFFERENTIAL EMISSION MEASURE INVERSIONS

We present a new method for performing differential emission measure (DEM) inversions on narrow-band EUV images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. The method yields positive definite DEM solutions by solving a linear program. This method has been validated against a diverse set of thermal models of varying complexity and realism. These include (1) idealized Gaussian DEM distributions, (2) 3D models of NOAA Active Region 11158 comprising quasi-steady loop atmospheres in a nonlinear force-free field, and (3) thermodynamic models from a fully compressible, 3D MHD simulation of active region (AR) corona formation following magnetic flux emergence. We then present results from the application of the method to AIA observations of Active Region 11158, comparing the region's thermal structure on two successive solar rotations. Additionally, we show how the DEM inversion method can be adapted to simultaneously invert AIA and Hinode X-ray Telescope data, and how supplementing AIA data with the latter improves the inversion result. The speed of the method allows for routine production of DEM maps, thus facilitating science studies that require tracking of the thermal structure of the solar corona in time and space.

79 ASTRONOMY AND ASTROPHYSICS↗

Observation of electron cloud instabilities and emittance dilution at the Cornell electron-positron Storage ring Test Accelerator

Electron cloud related emittance dilution and instabilities of bunch trains limit the performance of high intensity circular colliders. One of the key goals of the Cornell electron-positron storage ring Test Accelerator (CesrTA) research program is to improve our understanding of how the electron cloud alters the dynamics of bunches within the train. Single bunch beam diagnostics have been developed to measure the beam spectra, vertical beam size, two important dynamical effects of beams interacting with the electron cloud, for bunch trains on a turn-by-turn basis. Experiments have been performed at CesrTA to probe the interaction of the electron cloud with stored positron bunch trains. The purpose of these experiments was to characterize the dependence of beam-electron cloud interactions on the machine parameters such as bunch spacing, vertical chromaticity, and bunch current. The beam dynamics of the stored beam, in the presence of the electron cloud, was quantified using: 1) a gated beam position monitor (BPM) and spectrum analyzer to measure the bunch-by-bunch frequency spectrum of the bunch trains, 2) an x-ray beam size monitor to record the bunch-by-bunch, turn-by-turn vertical size of each bunch within the trains. In this study we report on the observations from these experiments and analyze the effects of the electron cloud on the stability of bunches in a train under many different operational conditions.

43 PARTICLE ACCELERATORS↗

MFDn Kernels v1.0

MFDn kernels is a collection of small subroutines designed to capture essential characteristics of the Many-Fermion Dynamics---nuclear (MFDn) application (DOI: 10.1016/j.procs.2010.04.012). It features multiple implementations with different programming models/languages of simplified routines analogous to those found in the full application. The main use is to explore the performance and utility of different programming models, languages and compilers.

Cook, Brandon↗

East River Surface and Pore Water FTICR-MS Data Associated with “Implications of sample treatment on characterization of the riverine environmental metabolome”

Surface and pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) using two different sample pre-treatment methods (solid phase extraction, no solid phase extraction) and two electrospray ionization methods (ESI-positive, ESI-negative) to identify the impacts of these choices on the final dataset. This study aimed to understand how the different sample processing methods influence the resulting FTICR-MS dataset. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

54 ENVIRONMENTAL SCIENCES↗

East River Pore Water FTICR-MS Data associated with "Geomorphic and Hydrogeochemical Controls on Fine-Scale Hyporheic Microbiome Assembly and Function"

Pore water samples were collected from distributed locations around Meander A in East River (Crested Butte, CO, USA) during the summer of 2018. This dataset consists of the characterization of dissolved organic matter using 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS; in .xml format) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory).This study aimed to understand organic matter assemblages differ within a streambed with differing geomorphology and the interplay between streambed organic matter and microbiome function. Any published work that utilizes data presented in this dataset should cite the dataset using the DOI number. If using the dataset, please acknowledge the U.S. Department of Energy (DOE) Office of Science (BER) Subsurface Biogeochemical Research (SBR) program, the Environmental Molecular Sciences Laboratory (EMSL), and Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS). The publication DOI will be added to this abstract when available.

54 ENVIRONMENTAL SCIENCES↗

Preventing Run-Time Bugs at Compile-Time Using Advanced C++

When writing software, we develop algorithms that tell the computer what to do at run-time. Our solutions are easier to understand and debug when they are properly modeled using class hierarchies, enumerations, and a well-factored API. Unfortunately, even with these design tools, we end up having to debug our programs at run-time. Worse still, debugging an embedded system changes its dynamics, making it tough to find and fix concurrency issues. This paper describes techniques using C++ to detect run-time bugs *at compile time*. A concurrency library, developed at Fermilab, is used for examples in illustrating these techniques.

43 PARTICLE ACCELERATORS↗

xesn: Echo state networks powered by Xarray and Dask

Xesn is a Python package that allows scientists to easily design Echo State Networks (ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture introduced by Jaeger (2001) that are part of a class of techniques termed Reservoir Computing. One defining characteristic of these techniques is that all internal weights are determined by a handful of global, scalar parameters, thereby avoiding problems during backpropagation and reducing training time significantly. Because this architecture is conceptually simple, many scientists implement ESNs from scratch, leading to questions about computational performance. Xesn offers a straightforward, standard implementation of ESNs that operates efficiently on CPU and GPU hardware. The package leverages optimization tools to automate the parameter selection process, so that scientists can reduce the time finding a good architecture and focus on using ESNs for their domain application. Importantly, the package flexibly handles forecasting tasks for out-of-core, multi-dimensional datasets, eliminating the need to write parallel programming code. Xesn was initially developed to handle the problem of forecasting weather dynamics, and so it integrates naturally with Python packages that have become familiar to weather and climate scientists such as Xarray (Hoyer & Hamman, 2017). However, the software is ultimately general enough to be utilized in other domains where ESNs have been useful, such as in signal processing (Jaeger & Haas, 2004).

97 MATHEMATICS AND COMPUTING↗

Principles of water oxidation and O2-based hydrocarbon transformation by multinuclear catalytic sites

Abstract The central thrust of this integrated experimental and computational research program was to obtain an atomistic-level understanding of the structural and dynamic factors underlying the design of catalysts for water oxidation and selective reductant-free O2-based transformations. The focus was on oxidatively robust polyoxometalate (POM) complexes in which a catalytic active site interacts with proximal metal centers in a synergistic manner. Thirty five publications in high-impact journals arose from this grant. I. Developing an oxidatively and hydrolytically stable and fast water oxidation catalyst (WOC), a central need in the production of green fuels using water as a reductant, has proven particularly challenging. During this grant period we have designed and investigated several carbon-free, molecular (homogenous), oxidatively and hydrolytically stable WOCs, including the Rb8K2[{Ru4O4(OH)2(H2O)4}(γ-SiW10O36)2]·25H2O (1) and [Co4(H2O)2(α-PW9O34)2]10- (2). Although complex 1 is fast, oxidatively and hydrolytically stable WOC, Ru is neither abundant nor inexpensive. Therefore, development of a stable and fast carbon-free homogenous WOC, based on earth-abundant elements became our highest priority. In 2010, we reported the first such catalyst, complex 2. This complex is substantially faster than 1 and stable under homogeneous conditions. Recently, we have extended our efforts and reported a V2-analog of the complex 2, i.e. [Co4(H2O)2(α-VW9O34)2]10- (3), which shows an even greater stability and reactivity. We succeeded in: (a) immobilizing catalysts 1 and 2 on the surface of various electrodes, and (b) elucidating the mechanism of O2 formation and release from complex 1, as well as the Mn4O4L6 “cubane” cluster. We have shown that the direct O-O bond formation is the most likely pathway for O2 formation during water oxidation catalyzed by 1. II. Oxo transfer catalysts that contain two proximal and synergistically interacting redox active metal centers in the active site form another part of considerable interest of our grant because species with such sites [including methane monooxygenase (MMO) and more] are some of the most effective oxygenase catalysts known. Our team conducted the following research on γ-M2-Keggin complexes: (a) investigated stability of the trimer [{Fe3(OH)3(H2O)2}3(γ-SiW10O36)3]15-, 4, in water, and developed the chemistry and catalysis of the di-iron centered POM, [γ(1,2)-SiW10{Fe(OH)}2O38]6-, 5, in organic solvents (Figure 2). We also study the thermodynamic and structural stability of γ-M2-Keggin in aqueous media for different M’s (d-electron metals). We have defined two structural classes of POMs with proximally bound d-electron metal centers. We refer to these structural isomers of the {γ-M2SiW10} family of POMs as “in-pocket” and “out-of pocket”. We have elucidated the factors controlling the structure and stability of the V, Fe, Ru, Tc, Mo and Rh derivatives of [(SiO4)M2(OH)2W10O32]4- using a range of computational tools. We have: (a) demonstrated that heteroatom X in these polyanions may function as an “internal switch” for defining the ground electronic states and, consequently, the reactivity of the γ-M2-Keggin POM complexes; (b) elucidated reactivity of divacant lacunary species and polyperoxotungstates (PPTs), {Xn+O4[WO(O2)2]4}n-, which could be degradation products of γ-M2-Keggin complexes in aqueous media; (c) elucidated the role of the POM ligand in stabilization of {Ru2} and {(Ru-oxo)2} fragments in the reactant and product of the reaction of {γ-[(Xn+O4)Ru2(OH)2W10O32]}(8-n)- (where X = Si4+, P5+ and S6+) with O2, and (d) the mechanisms of olefin epoxidation catalyzed by these di-d-transition metal substituted and divacant lacunary γ-M2-Keggin complexes. III. Complementing the efforts presented above was the development of less time-consuming but reasonably accurate computational methods allowing one to explore more deeply large catalytic systems. We developed Reactive Force Field (ReaxFF) to study interaction of the targeted POMs with water, proton and hydroxide ions in the liquid phase. We tested our ReaxFF parameters on the Lindqvist POMs, M6O19n-, where M = Nb and Ta. These parameters are made available as part of the ReaxFF code. In addition, we have developed parameters for Sc, Ti, Fe, Co and Ni in combination with H, C, N, O, as well as the same metal (M-M) for the spin-polarized self-consistent-charge density-functional tight-binding (DFTB) method. Test calculations showed that the DFTB method with the present parameters in most cases reproduces structural properties very well. These parameters are made available as part of the DFTB code. Thus, this DOE BES funded research project has clarified several key areas impacting (a) water oxidation and O2-based hydrocarbon transformation, (b) stabilization of key structures and catalytic intermediates in such processes, (c) immobilization of molecular catalysts on metal oxide surfaces, and (d) application of optimal computational methods to study reaction dynamics in large systems.

58 GEOSCIENCES↗

Impact of Changes in ENDF/B-VII.1 and ENDF/B-VIII.0 235U Nuclear Data Indicated by NDSE Studies on LLNL Pulsed Sphere Simulations

A recent journal article by J.A. Gomez et al. measured gamma-ray die-off curves of three subcritical static highly-enriched uranium (HEU) assemblies driven by an external neutron source with a new detector system. This new detector system was developed for being used in dynamically driven subcritical assemblies as part of the Neutron Diagnosed Subcritical Experiments (NDSE) program. Simulations of these die-off curves with various nuclear data and comparison to experimental data indicated that a decrease of the ENDF/B-VII.1 235 U(n,inl) cross section by a factor 0.8 and 0.85 for ENDF/B-VIII.0 would lead to better predictions of experimental data. Here, we test the proposed changes with another type of measurement response, namely neutron-leakage spectra emitted in LLNL pulsed sphere measurements. These spheres were pulsed by 14-MeV neutrons produced via the D+T reaction in their center. The proposed changes in nuclear data have a distinctly smaller impact on predicting pulsed-sphere neutron-leakage spectra than for the die-off curves; they lead to a worsened prediction of the inelastic valley of LLNL pulsed-sphere neutron spectra indicating that the proposed change could constitute a compensating error. Changes in the inelastic angular distributions along with the cross section might be worthwhile to study

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimal Electric Grid Black Start Restoration Subject to Intentional Threats

Efficient restoration of the electric grid from significant disruptions – both natural and manmade – that lead to the grid entering a failed state is essential to maintaining resilience under a wide range of threats. Restoration follows a set of black start plans, allowing operators to select among these plans to meet the constraints imposed on the system by the disruption. Restoration objectives aim to restore power to a maximum number of customers in the shortest time. Current state-of-the-art for restoration modeling breaks the problem into multiple parts, assuming a known network state and full observability and control by grid operators. These assumptions are not guaranteed under some threats. This paper focuses on a novel integration of modeling and analysis capabilities to aid operators during restoration activities. A power flow-informed restoration framework, comprised of a restoration mixed-integer program informed by power flow models to identify restoration alternatives, interacts with a dynamic representation of the grid through a cognitive model of operator decision-making, to identify and prove an optimal restoration path. Application of this integrated approach is illustrated on exemplar systems. Validation of the restoration is performed for one of these exemplars using commercial solvers, and comparison is made between the steps and time involved in the commercial solver, and that required by the restoration optimization in and of itself, and by the operator model in acting on the restoration optimization output. Publications and proposals developed under this work, along with a path forward for additional expansion of the work, and summary of what was achieved, are also documented.

24 POWER TRANSMISSION AND DISTRIBUTION↗