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At least 1,351 records · Page 75

EDIPIC-2D

EDIPIC codes were developed for simulation of kinetic effects in low-temperature plasmas. They can be used for simulation of plasmas in electrostatic approximation and include many atomistic and plasma-surface interaction processes needed for simulations of low temperature plasmas. These codes include a detailed model of secondary electron emission induced by electrons and ions. The Monte-Carlo model of electron-neutral collisions and the Langevin model of Coulomb collisions for electrons are also implemented.

Sydorenko, Dmytro↗

Multiscale Nuclear-Electronic Orbital Quantum Dynamics in Complex Environments

Many renewable energy conversion processes rely on the movement of protons as well as electrons through either electrocatalysis or photoexcitation. The simulation of such processes requires a quantum mechanical description of coupled nuclear-electronic dynamics in a solvent or heterogeneous chemical environment. The overall objective of this project is the development of theoretical and computational capabilities for simulating nuclear-electronic quantum dynamics in complex environments and the creation of high-performance, open-source software. This multiscale framework will enable simulations of the real-time dynamics of nonequilibrium excited state proton-coupled electron transfer, quantum decoherence, vibronic energy transfer, and ultrafast radiolysis, as well as their associated time-resolved multidimensional spectroscopies. An important outcome of this project will be a sustainable, reusable, and interoperable open-source software ecosystem. This software will be designed for emerging exascale and future national leadership computers. Another key outcome will be a multiscale quantum dynamics method and software enabling simulations of nonequilibrium nuclear-electronic quantum dynamics in complex environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Convergence of Cloud Droplet Spectral Relative Dispersion During Entrainment‐Mixing Based on Particle‐Resolved Direct Numerical Simulations

Entrainment-mixing processes critically impact cloud microphysical properties, but their effects on the relative dispersion (d) of cloud droplet size distributions (CDSDs) remain elusive. A direct numerical simulation model is initialized with different CDSDs to fill the gap. These results show that d decreases for broad CDSDs and increases for narrow ones, ultimately converging to approximately 0.5 regardless of initial CDSDs during the evaporation-dominated mixing stage. The supersaturation fluctuation and the shape of CDSDs jointly influence the convergence behavior of d. Further sensitivity tests show that the initial microphysical/dynamical/thermodynamical conditions exert negligible effects on the final converged value of d but affect the convergence rate (k). The k generally increases with increasing droplet number concentration and dissipation rate, and increases with decreasing liquid water content, relative humidity of entrained air, and mixing fraction of cloudy air. A conceptual model with two timescales is proposed; k and the timescales are negatively correlated, meaning that slow mixing and/or evaporation process results in slow convergence of d. In conclusion, this finding provides an important reference for improving understanding and parameterization of d during the entrainment-mixing processes.

54 ENVIRONMENTAL SCIENCES↗

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background: Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims: The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods: We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key Results: Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions: While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications: This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗

Hybrid receiver study

The results are presented of a 4 month study to design a hybrid analog/digital receiver for outer planet mission probe communication links. The scope of this study includes functional design of the receiver; comparisons between analog and digital processing; hardware tradeoffs for key components including frequency generators, A/D converters, and digital processors; development and simulation of the processing algorithms for acquisition, tracking, and demodulation; and detailed design of the receiver in order to determine its size, weight, power, reliability, and radiation hardness. In addition, an evaluation was made of the receiver's capabilities to perform accurate measurement of signal strength and frequency for radio science missions.

Stone, M. S.↗

Enhanced TCAS 2/CDTI traffic Sensor digital simulation model and program description

Digital simulation models of enhanced TCAS 2/CDTI traffic sensors are developed, based on actual or projected operational and performance characteristics. Two enhanced Traffic (or Threat) Alert and Collision Avoidance Systems are considered. A digital simulation program is developed in FORTRAN. The program contains an executive with a semireal time batch processing capability. The simulation program can be interfaced with other modules with a minimum requirement. Both the traffic sensor and CAS logic modules are validated by means of extensive simulation runs. Selected validation cases are discussed in detail, and capabilities and limitations of the actual and simulated systems are noted. The TCAS systems are not specifically intended for Cockpit Display of Traffic Information (CDTI) applications. These systems are sufficiently general to allow implementation of CDTI functions within the real systems' constraints.

Goka, T.↗

NAME Modeling and Data Assimilation: A Strategic Overview

In this presentation a strategic overview of modeling and related data analysis and assimilation components of the North American Monsoon Experiment (NAME) are given. Building on the NAME science plan, a strategy is outlined for accelerating progress on the fundamental modeling issues pertaining to NAME science goals. The strategy takes advantage of NAME enhanced observations, and should simultaneously provide model-based guidance to the evolving multi-tiered NAME observing program. The NAME modeling strategy recognizes three distinct, but related, roles that observations play in model development and assessment. These are: (1) to guide model development by providing constraints on model simulations at the process level (e.g. convection, land/atmosphere and ocean/atmosphere interactions); (2) to help assess the veracity of model simulations of the various key NAMS phenomena (e.g. low level jets, land sea breezes, tropical storms), and the linkages to regional and larger-scale climate variability; and (3) to provide initial and boundary conditions, and verification data for model predictions.

Schubert, Siegfried↗

Simulating Bone Loss in Microgravity Using Mathematical Formulations of Bone Remodeling

Most mathematical models of bone remodeling are used to simulate a specific bone disease, by disrupting the steady state or balance in the normal remodeling process, and to simulate a therapeutic strategy. In this work, the ability of a mathematical model of bone remodeling to simulate bone loss as a function of time under the conditions of microgravity is investigated. The model is formed by combining a previously developed set of biochemical, cellular dynamics, and mechanical stimulus equations in the literature with two newly proposed equations; one governing the rate of change of the area of cortical bone tissue in a cross section of a cylindrical section of bone and one governing the rate of change of calcium in the bone fluid. The mechanical stimulus comes from a simple model of stress due to a compressive force on a cylindrical section of bone which can be reduced to zero to mimic the effects of skeletal unloading in microgravity. The complete set of equations formed is a system of first order ordinary differential equations. The results of selected simulations are displayed and discussed. Limitations and deficiencies of the model are also discussed as well as suggestions for further research.

Pennline, James A.↗

The effects of level of knowledge upon human problem solving in a process control task

The effect of knowledge of a system on the performance of the operator has been investigated using PLANT, a generic simulation of a process. Four sets of written instructions representing the what, how, and why of system control were utilized by groups of subjects who controlled PLANT in a variety of familiar and unfamiliar situations. Written test results at the end of the experiments showed that the instructions had no effect on the primary goal of production, but those groups receiving guidelines for operation (the how) controlled the system in a more stable manner. Principles (the why) had no apparent effect on the subjects' performance. There was no difference between groups in diagnosing unfamiliar events.

Morris, N. M.↗

r-Process Nucleosynthesis: Connecting Rare-Isotope Beam Facilities with the Cosmos

This is a pivotal time for the study of r-process nucleosynthesis. Recently, a neutron star merger GW170817 was observed in extraordinary detail with gravitational waves and electromagnetic radiation from radio to γ rays. The very red color of the associated kilonova suggests that neutron star mergers are an important r-process site. Astrophysical simulations of neutron star mergers and core collapse supernovae are making rapid progress. Detection of both electron neutrinos and antineutrinos from the next Galactic supernova will constrain the composition of neutrino-driven winds and provide unique nucleosynthesis information. Finally, FRIB and other rare-isotope beam facilities will soon have dramatic new capabilities to synthesize many neutron-rich nuclei that are involved in the r-process. The new capabilities can significantly improve our understanding of the r-process and likely resolve one of the main outstanding problems in classical nuclear astrophysics. Yet, to make best use of the new experimental capabilities and to fully interpret the results, a great deal of infrastructure is needed in many related areas of astronomy, astrophysics, and nuclear theory. We place these experiments in context by discussing astrophysical simulations and observations of r-process sites, observations of stellar abundances, Galactic chemical evolution, and nuclear theory for the structure and reactions of very neutron-rich nuclei. This review paper was initiated at a three week International Collaborations in Nuclear Theory program in June 2016, where we explored promising r-process experiments and discussed their likely impact, and their astronomical, astrophysical, and nuclear theory context.

79 ASTRONOMY AND ASTROPHYSICS↗

Unfolding bovine α-lactalbumin with T-jump: Characterizing disordered intermediates via time-resolved x-ray solution scattering and molecular dynamics simulations

The protein folding process often proceeds through partially folded transient states. Therefore, a structural understanding of these disordered states is crucial for developing mechanistic models of the folding process. Characterization of unfolded states remains challenging due to their disordered nature, and incorporating multiple methods is necessary. Combining the time-resolved x-ray solution scattering (TRXSS) signal with molecular dynamics (MD), we are able to characterize transient partially folded states of bovine α-lactalbumin, a model system widely used for investigation of molten globule states, during its unfolding triggered by a temperature jump. We track the unfolding process between 20 μs and 70 ms and demonstrate that it passes through three distinct kinetic states. The scattering signals associated with these transient species are then analyzed with TRXSS constrained MD simulations to produce protein structures that are compatible with the input signals. Without utilizing any experimentally extracted kinetic information, the constrained MD simulation successfully drove the protein to an intermediate molten globule state; signals for two later disordered states are refined to terminal unfolded states. From our examination of the structural characteristics of these disordered states, we discuss the implications disordered states have on the folding process, especially on the folding pathway. Finally, we discuss the potential applications and limitations of this method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

Williams Colin P.↗

RFI and SCRIMP Model Development and Verification

Vacuum-Assisted Resin Transfer Molding (VARTM) processes are becoming promising technologies in the manufacturing of primary composite structures in the aircraft industry as well as infrastructure. A great deal of work still needs to be done on efforts to reduce the costly trial-and-error methods of VARTM processing that are currently in practice today. A computer simulation model of the VARTM process would provide a cost-effective tool in the manufacturing of composites utilizing this technique. Therefore, the objective of this research was to modify an existing three-dimensional, Resin Film Infusion (RFI)/Resin Transfer Molding (RTM) model to include VARTM simulation capabilities and to verify this model with the fabrication of aircraft structural composites. An additional objective was to use the VARTM model as a process analysis tool, where this tool would enable the user to configure the best process for manufacturing quality composites. Experimental verification of the model was performed by processing several flat composite panels. The parameters verified included flow front patterns and infiltration times. The flow front patterns were determined to be qualitatively accurate, while the simulated infiltration times over predicted experimental times by 8 to 10%. Capillary and gravitational forces were incorporated into the existing RFI/RTM model in order to simulate VARTM processing physics more accurately. The theoretical capillary pressure showed the capability to reduce the simulated infiltration times by as great as 6%. The gravity, on the other hand, was found to be negligible for all cases. Finally, the VARTM model was used as a process analysis tool. This enabled the user to determine such important process constraints as the location and type of injection ports and the permeability and location of the high-permeable media. A process for a three-stiffener composite panel was proposed. This configuration evolved from the variation of the process constraints in the modeling of several different composite panels. The configuration was proposed by considering such factors as: infiltration time, the number of vacuum ports, and possible areas of void entrapment.

Loos, Alfred C.↗

Performance Assessment of a Generic Nuclear Waste Repository in Shale - 18392

A performance assessment (PA) is an important component of a comprehensive safety analysis for a nuclear waste repository. In a PA, probabilistic simulations of the total repository system are performed, and results are evaluated against performance metrics. Uncertainty and sensitivity analyses help prioritize additional research and model development. The United States Department of Energy (DOE) has been developing a state of the art PA simulation software tool-kit, Geologic Disposal Safety Assessment (GDSA) Framework, that couples increasingly higher fidelity models of subsystem processes into total system PA simulations. Over the past several years, PAs of generic repositories in three geologic media (salt, shale, and crystalline rock) have demonstrated ongoing developments in capability. The current PA of a nuclear waste repository in a generic shale formation showcases GDSA Framework, including capabilities in domain discretization (Cubit), multi-physics simulations (PFLOTRAN), uncertainty and sensitivity analysis (Dakota), and visualization (Paraview). The generic shale reference case considers the disposal of 22,000 metric tons heavy metal of commercial spent nuclear fuel (SNF) in a generic shale formation. PA simulations account for the thermal load and radionuclide inventory of the waste form, components of the engineered barrier system including waste package and buffer, and components of the natural barrier system including the host rock shale and underlying and overlying stratigraphic units. Two repository layouts are considered, one for emplacement of waste packages containing 12 pressurized water reactor (PWR) assemblies, and one for 4-PWR waste package emplacement. Model domains are half-symmetry and contain between 7 and 22 million grid cells. Grid refinement captures the detail of individual waste packages, emplacement drifts, access drifts, and shafts. Simulations are run in a high-performance computing (HPC) environment on 512 or 2048 processes. The governing equations describing coupled heat and fluid flow and reactive transport are solved with PFLOTRAN, an open-source, massively parallel multiphase flow and reactive transport code. Additional simulated processes include waste package degradation; waste form dissolution; radioactive decay and ingrowth in aqueous, solid, and adsorbed phases; and a simple biosphere based on a pumping well. Simulations are run to 106 y; dose and radionuclide concentrations are observed within aquifers at a point approximately 5 km downgradient of the repository. Dakota is used to sample likely ranges of input parameters including waste form and waste package degradation rates and properties of engineered and natural materials to quantify uncertainty in predicted concentrations and sensitivity to input parameters. Given the assumptions of the reference case, results of 12-PWR and 4-PWR simulations are very similar. Dose at the pumping well 5-km downgradient of the repository does not exceed 10-9 Sv/y. I-129 is the largest contributor to dose. The dose due to Cl-36, the next largest contributor, is orders of magnitude smaller. At the pumping well, the concentration of I-129 5-km downgradient does not exceed 10-14 mol/L. Rank correlation coefficients indicate that the maximum concentration of I-129 within the aquifer is sensitive to shale (repository host rock) porosity and aquifer permeability. These results affirm that HPC-capable codes can be used to simulate important multi-physics couplings directly in a total system performance assessment of a geologic repository, and can be used in prioritization of future research and model development. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

On simulation of local fluxes in molecular junctions

We present a pedagogical review of the current density simulation in molecular junction models indicating its advantages and deficiencies in analysis of local junction transport characteristics. In particular, we argue that current density is a universal tool which provides more information than traditionally simulated bond currents, especially when discussing inelastic processes. However, current density simulations are sensitive to the choice of basis and electronic structure method. We note that while discussing the local current conservation in junctions, one has to account for the source term caused by the open character of the system and intra-molecular interactions. Our considerations are illustrated with numerical simulations of a benzenedithiol molecular junction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

V&V Integrated Program Planning for Wind Plant Performance

The Department of Energy Atmosphere to Electrons (A2e) initiative has undertaken an experimental planning process for a validation directed program and an experimental planning process directed at improving simulations of wind plant performance. The validation process has been divided into two main sections: Integrated Program Planning, and Integrated Experiment and Model Planning and Execution. This document covers the Integrated Program Planning process in detail as it has been applied to the validation and assessment of models of various fidelity to predict wind plant performance. Three main parts of this process are presented in this document: the Phenomenon Identification and Ranking Table, the Validation Hierarchy, and the Prioritized Phenomenon and Experiment Mapping table. The document concludes with a description of validation program process next steps, which includes the planning and execution of integrated experiment and model campaigns

17 WIND ENERGY↗