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DOE OSTI2011

Atomic dynamics and interatomic interaction in quasicrystals

The previous experimental data on the partial spectra of thermal atomic vibrations in icosahedral (Al{sub 62}Cu{sub 25.5}Fe{sub 12.5}) and decagonal (Al{sub 71.3}Ni{sub 24}Fe{sub 4.7}) quasicrystals have been used to perform a comparative analysis of the atomic dynamics features and determine the role that Al, Cu, Ni, and Fe atoms play in the formation of interatomic interaction in the alloys studied. A physical model of the decagonal quasicrystal structure is proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2012

Kinetic models of current sheets with a sheared magnetic field

Thin current sheets, whose existence in the Earth's magnetotail is confirmed by numerous spacecraft measurements, are studied analytically and numerically. The thickness of such sheets is on the order of the ion Larmor radius, and the normal component of the magnetic field (B{sub z}) in the sheet is almost constant, while the tangential (B{sub x}) and shear (B{sub y}) components depend on the transverse coordinate z. The current density in the sheet also has two self-consistent components (j{sub x} and j{sub y}, respectively), and the magnetic field lines are deformed and do not lie in a single plane. To study such quasi-one-dimensional current configurations, two kinetic models are used, in particular, a numerical model based on the particle-in-cell method and an analytical model. The calculated results show that two different modes of the self-consistent shear magnetic field B{sub y} and, accordingly, two thin current sheet configurations can exist for the same input parameters. For the mode with an antisymmetric z profile of the B{sub y} component, the magnetic field lines within the sheet are twisted, whereas the profiles of the plasma density, current density component j{sub y}, and magnetic field component B{sub x} differ slightly from those in the case of a shearless magnetic field (B{sub y} = 0). For the symmetric B{sub y} mode, the magnetic field lines lie in a curved surface. In this case, the plasma density in the sheet varies slightly and the current sheet is two times thicker. Analysis of the dependence of the current sheet structure on the flow anisotropy shows that the sheet thickness decreases significantly with decreasing ratio between the thermal and drift plasma velocities, which is caused by the dynamics of quasi-adiabatic ions. It is shown that the results of the analytical and numerical models are in good agreement. The problems of application of these models to describe current sheets at the magnetopause and near magnetic reconnection regions are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

STREAMM-tools (Simulation Toolkit for Renewable Energy Advanced Materials Modeling) [SWR-15-29]

The Simulation Toolkit for Renewable Energy and Advanced Materials Modeling (STREAMM) is a python package that generates structures and input files for quantum chemical and molecular dynamics codes. STREAMM does not directly conduct simulations rather it is meant to drive quantum chemical and molecular dynamics codes to allow for high-throughput computational analysis of materials. The STREAMM package is written for python2.7 (https://www.python.org/download/releases/2.7/) and incorporates some of the core modules from the pymatgen (http://pymatgen.org/) code.

Sides, Scott↗

DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗

DOE OSTI2012

On the Nonlinear Dynamics and Quasi-Statics of Tape Joined Structures

Tape joints have been a key tool in assembly of nuclear weapons for almost 40 years. In that time sufficient experience has been gained to have confidence on the robustness of this technology within established design constraints; the structural dynamics of systems assembled by tape joints are much less well understood. Though there is lore that tape joined structures behave linearly in the axial direction, even that is contradicted by the literature, where such structures are found to be bi-linear (nonlinear) in axial modes. Experimental results presented here show much more significant nonlinearity when such systems vibrate in such a way that there is bending across the joint cross-section. In addition, it will be difficult to understand the nonlinear structural dynamics before the pre-loads on the tape joints is known. Therefore, a strategy to deduce the joint pre-loads from surface strain measurements has been developed. This technique exploits finite element analysis to generate an approximate Green’s function to map tape loads to surface strain and employs numerical optimization to solve an inverse problem. This technique is demonstrated on the same test specimen employed in the dynamics experiments.

Segalman, Daniel Joseph↗

DOE OSTI2012

Predictions of one-group interfacial area transport in TRACE

In current nuclear reactor system analysis codes utilizing the two-fluid model, flow regime dependent correlations are used to specify the interfacial area concentration (a i). This approach does not capture the continuous evolution of the interfacial structures, and thus, it can pose issues near the transition boundaries. Consequently, a pilot version of the system analysis code TRACE is being developed that employs the interfacial area transport equation (IATE). In this approach, dynamic estimation of a i is provided through mechanistic models for bubble coalescence and breakup. The implementation of the adiabatic, one-group IATE into TRACE is assessed against experimental data from 50 air-water, two-phase flow conditions in pipes ranging in inner diameter from 2.54 to 20.32 cm for both vertical co-current upward and downward flows. Predictions of pressure, void fraction, bubble velocity, and a i data are made. TRACE employing the conventional flow regime-based approach is found to underestimate a i and can only predict linear trends since the calculation is governed by the pressure. Furthermore, trends opposite to that of the data are predicted for some conditions. In contrast, TRACE with the one-group IATE demonstrates a significant improvement in predicting the experimental data with an average disagreement of {+-} 13%. Additionally, TRACE with the one-group IATE is capable of predicting nonlinear axial development of a, by accounting for various bubble interaction mechanisms, such as coalescence and disintegration. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

An Intraseasonal Mode of Atmospheric Variability Relevant to the U.S. Hydroclimate in Boreal Summer: Dynamic Origin and East Asia Connection

In this work intraseasonal modes of atmospheric variability over the Northern Hemisphere (NH) midlatitudes in boreal summer are identified via an empirical orthogonal function (EOF) analysis of the daily 10–90-day bandpass-filtered 250-hPa streamfunction for the period of 1950–2016. The first two EOF modes are characterized, respectively, by (i) a single-signed streamfunction anomaly that extends across the NH and (ii) a regional dipole structure with centers over the Aleutian Islands and northeastern Pacific. The third EOF mode (EOF-3) is a quasi-stationary wave train over the Pacific–North American sector with an equivalent barotropic structure in the vertical. EOF-3 is associated with a northwest–southeast oriented anomalous precipitation dipole over the United States. A nonmodal instability analysis of the boreal summer climatological flow in terms of the 250-hPa streamfunction reveals that one of the top “optimal mode” disturbances mimicking the EOF-3 structure grows from an initial precursor disturbance over East Asia through extracting kinetic energy from background flow and attains its maximum amplitude in around nine days. An additional lag regression analysis illustrates that anomalous latent heating associated with cloud and precipitation formation over East Asia is responsible for generating the precursor disturbance for the EOF-3-like optimal mode. This result suggests the existence of an important connection between the hydrological cycles of East Asia and North America, which is dynamically intrinsic to the boreal summer upper-tropospheric flow. Knowledge of such a connection will help us better understand and model hydroclimate variability over these two continents.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Ab Initio Evaluation of Plutonium Dioxide $S(α,β)$ and Thermal Neutron Cross Sections

Plutonium Dioxide (PuO 2 ) is an advanced fuel-cycle nuclear fuel material for thermal and fast reactors, with a melting point at 3261.8 K and thermal conductivity above 3 Wm -1 K -1 for temperatures below 1500 K. Plutonium from spent UO 2 is reprocessed to form chemically stable mixed oxide (MOX) fuel. In contrast to metallic fuels, the low PuO 2 conductivity results in high thermal gradients between fuel center and surface, resulting in structural annealing and efficient fission product migration over burnup. Crystal binding affects the doppler broadening of epithermal resonances for nuclear fuels and scattering behavior of thermal neutrons. Currently, there is no ENDF/B Thermal Scattering Law, i.e., $S(α,β)$, evaluation for PuO 2 , only free atom cross sections for Plutonium and Oxygen, respectively, which neglect lattice contributions to total cross section. Herein, ab initio lattice dynamics (AILD) techniques are employed to calculate the phonon density of states (DOS) using spin-orbit-coupling density functional theory (DFT) to predict the PuO2 paramagnetic ground-state structure. These results highlight the evaluation of $S(α,β)$ for Plutonium and Oxygen, respectively in PuO 2 and consequential generation of thermal neutron scattering cross sections for high fidelity criticality safety analysis and reactor calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming

In this report, we study the sensitivity of discrete-time dynamic programs with nonlinear dynamics and objective to perturbations in the initial conditions and reference parameters. Under uniform controllability and boundedness assumptions for the problem data, we prove that the directional derivative of the optimal state and control at time $k$, $x^*_k$, and $u^*_k$, with respect to the reference signal at time $i$, $d_i$, will have exponential decay in terms of $|k-i|$ with a decay rate $\rho$ independent of the temporal horizon length. The key technical step is to prove that a version of the convexification approach proposed by Verschueren et al. can be applied to the KKT conditions and results in a convex quadratic program with uniformly bounded data. In turn, Riccati techniques can be further employed to obtain the sensitivity result, borne from the observation that the directional derivatives are solutions of quadratic programs with structure similar to the KKT conditions themselves. We validate our findings with numerical experiments on a small nonlinear, nonconvex, dynamic program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Dynamics of the transition from the metastable tetragonal st12 to the diamond-cubic phase in germanium characterized by neutron spectroscopy

The complex phase diagram of germanium allows for exotic crystalline phases recoverable from high pressure. Among these, the tetragonal st12 phase is unusual as it shares characteristics with amorphous Ge resulting in desirable band-gap characteristics. Here, we leverage a high neutron flux and large volume pressure capabilities to characterize st12-Ge and its dynamics upon conversion to diamond-cubic Ge with inelastic neutron scattering. Here, we exploit the characteristics of time-of-flight neutron scattering for time-resolved investigations. This analysis may suggest the existence of a transient disordered state upon annealing befitting the known structural relationship between st12-Ge and amorphous Ge, a relationship that can open the potential for band-gap tuning.

Elemental semiconductors↗

DOE OSTI2016

Hierarchical Model for the Analysis of Scattering Data of Complex Materials

Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replaced by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Molecular Dynamics Simulation and Analysis of Interfacial Water at Selected Sulfide Mineral Surfaces under Anaerobic Conditions

In this paper, we report on a molecular dynamics simulation (MDS) study of the behavior of interfacial water at selected sulfide mineral surfaces under anaerobic conditions. The study revealed the interfacial water structure and wetting characteristics of the pyrite (100) surface, galena (100) surface, chalcopyrite (012) surface, sphalerite (110) surface, and molybdenite surfaces (i.e., the face, armchair-edge, and zigzag-edge surfaces), including simulated contact angles, relative number density profiles, water dipole orientations, hydrogen-bonding, and residence times. For force fields of the metal and sulfur atoms in selected sulfide minerals used in the MDS, we used the universal force field (UFF) and another set of force fields optimized by quantum chemical calculations for interactions with interfacial water molecules at selected sulfide mineral surfaces. Simulation results for the structural and dynamic properties of interfacial water molecules indicate the natural hydrophobic character for the selected sulfide mineral surfaces under anaerobic conditions as well as the relatively weak hydrophobicity for the sphalerite (110) surface and two molybdenite edge surfaces. Part of the financial support for this study was provided by the U.S. Department of Energy (DOE) under Basic Science Grant No. DE-FG-03-93ER14315. The Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences (BES), of the DOE, funded work performed by Liem X. Dang. Battelle operates Pacific Northwest National Laboratory for DOE. The calculations were carried out using computer resources provided by BES. The authors are grateful to Professor Tsun-Mei Chang for valuable discussions.

Jin, Jiaqi↗

DOE OSTI2022

GeN-ROM—An OpenFOAM®-based multiphysics reduced-order modeling framework for the analysis of Molten Salt Reactors

This work presents a projection-based multiphysics Model Order Reduction (MOR) framework for the analysis of nuclear systems and its application to parametric simulations of Molten Salt Reactors (MSR). The framework, named GeN-ROM, is developed using OpenFOAM® and employs a Proper Orthogonal Decomposition aided Reduced-Basis technique (POD-RB). It can be used to reduce steady-state and transient multiphysics problems involving parametric fluid dynamics, heat exchange, and neutronics phenomena. For the treatment of structural elements in the hydraulic systems, a porous medium approach has been adopted. The reduction process is data-driven and snapshot information is extracted via POD to learn the solution manifold and to build global spatial basis functions. At the data collection phase, GeN-ROM makes use of the solvers available in GeN-Foam, a similarly OpenFOAM®-based multiphysics framework developed for the analysis of nuclear reactors. The global bases are used both to approximate the solution fields and to project the full-order equations onto lower-dimensional subspaces, thus considerably reducing the number of unknowns in a numerical system. This reduction leads to significant computational speedups, which is ideal for multi-query applications such as uncertainty quantification or design optimization. The developed tool has been tested using a 2D multiphysics model of the Molten Salt Fast Reactor (MSFR) with steady-state and transient scenarios, with speedups on the order of 10 – 10 5 .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

HCV RNA traffic and association with NS5A in living cells

The spatiotemporal dynamics of Hepatitis C Virus (HCV) RNA localisation are poorly understood. To address this we engineered HCV genomes harbouring MS2 bacteriophage RNA stem-loops within the 3′-untranslated region to allow tracking of HCV RNA via specific interaction with a MS2-Coat-mCherry fusion protein. Despite the impact of these insertions on viral fitness, live imaging revealed that replication of tagged-HCV genomes induced specific redistribution of the mCherry-tagged-MS2-Coat protein to motile and static foci. Further analysis showed that HCV RNA was associated with NS5A in both static and motile structures while a subset of motile NS5A structures was devoid of HCV RNA. Further investigation of viral RNA traffic with respect to lipid droplets (LDs) revealed HCV RNA-positive structures in close association with LDs. These studies provide new insights into the dynamics of HCV RNA traffic with NS5A and LDs and provide a platform for future investigations of HCV replication and assembly. - Highlights: • HCV can tolerate can bacteriophage MS2 stem-loop insertions within the 3′ UTR. • MS2 stem-loop containing HCV genomes allow for real-time imaging of HCV RNA. • HCV RNA is both static and motile and associates with NS5A and lipid droplets.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Simulations of nanocrystals under pressure: Combining electronic enthalpy and linear-scaling density-functional theory

We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure. Based on a definition of the system volume as that enclosed within an electronic density isosurface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett.94, 145501 (2005)], it supports both geometry optimizations and molecular dynamics simulations. We introduce an approach for calibrating the parameters defining the volume in the context of geometry optimizations and discuss their significance. Results in good agreement with simulations using explicit solvents are obtained, validating our approach. Size-dependent pressure-induced structural transformations and variations in the energy gap of hydrogenated silicon nanocrystals are investigated, including one comparable in size to recent experiments. A detailed analysis of the polyamorphic transformations reveals three types of amorphous structures and their persistence on depressurization is assessed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗