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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52

Evidence for Sub-Chandrasekhar Mass Type Ia Supernovae from an Extensive Survey of Radiative Transfer Models

There exists two classes of viable progenitors for normal Type Ia supernovae (SNe Ia): systems in which a white dwarf explodes at the Chandrasekhar mass (${M}_{\mathrm{ch}}$), and systems in which a white dwarf explodes below the Chandrasekhar mass (sub-${M}_{\mathrm{ch}}$). It is not clear which of these channels is dominant; observations and light-curve modeling have provided evidence for both. In this work we use an extensive grid of 4500 time-dependent, multiwavelength radiation transport simulations to show that the sub-${M}_{\mathrm{ch}}$ model can reproduce the entirety of the width–luminosity relation, while the ${M}_{\mathrm{ch}}$ model can only produce the brighter events $(0.8\lt {\rm{\Delta }}{M}_{15}(B)\lt 1.55)$, implying that fast-declining SNe Ia come from sub-${M}_{\mathrm{ch}}$ explosions. We do not assume a particular theoretical paradigm for the progenitor or explosion mechanism, but instead construct parameterized models that vary the mass, kinetic energy, and compositional structure of the ejecta, thereby realizing a broad range of possible outcomes of white dwarf explosions. We provide fitting functions based on our large grid of detailed simulations that map observable properties of SNe Ia, such as peak brightness and light-curve width, to physical parameters such as ${}^{56}\mathrm{Ni}$ and total ejected mass. These can be used to estimate the physical properties of observed SNe Ia.

79 ASTRONOMY AND ASTROPHYSICS↗

KINETIC ENERGY FROM SUPERNOVA FEEDBACK IN HIGH-RESOLUTION GALAXY SIMULATIONS

We describe a new method for adding a prescribed amount of kinetic energy to simulated gas modeled on a cartesian grid by directly altering grid cells’ mass and velocity in a distributed fashion. The method is explored in the context of supernova (SN) feedback in high-resolution (∼10 pc) hydrodynamic simulations of galaxy formation. Resolution dependence is a primary consideration in our application of the method, and simulations of isolated explosions (performed at different resolutions) motivate a resolution-dependent scaling for the injected fraction of kinetic energy that we apply in cosmological simulations of a 10{sup 9} M{sub ⊙} dwarf halo. We find that in high-density media (≳50 cm{sup −3}) with coarse resolution (≳4 pc per cell), results are sensitive to the initial kinetic energy fraction due to early and rapid cooling. In our galaxy simulations, the deposition of small amounts of SN energy in kinetic form (as little as 1%) has a dramatic impact on the evolution of the system, resulting in an order-of-magnitude suppression of stellar mass. The overall behavior of the galaxy in the two highest resolution simulations we perform appears to converge. We discuss the resulting distribution of stellar metallicities, an observable sensitive to galactic wind properties, and find that while the new method demonstrates increased agreement with observed systems, significant discrepancies remain, likely due to simplistic assumptions that neglect contributions from SNe Ia and stellar winds.

79 ASTRONOMY AND ASTROPHYSICS↗

Distribution of blackouts in the power grid and the Motter and Lai model

Carreras, Dobson, and colleagues have studied empirical data on the sizes of the blackouts in real grids and modeled them with computer simulations using the direct current approximation. They have found that the resulting blackout sizes are distributed as a power law and suggested that this is because the grids are driven to the self-organized critical state. In contrast, more recent studies found that the distribution of cascades is bimodal resulting in either a very small blackout or a very large blackout, engulfing a finite fraction of the system. Here we reconcile the two approaches and investigate how the distribution of the blackouts changes with model parameters, including the tolerance criteria and the dynamic rules of failure of the overloaded lines during the cascade. Finally, we study the same problem for the Motter and Lai model and find similar results, suggesting that the physical laws of flow on the network are not as important as network topology, overload conditions, and dynamic rules of failure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CFD modeling of debris melting phenomena during late phase Candu 6 severe accident

The objective of this paper was to study the phase change of the debris formed on the Candu 6 calandria bottom in a postulated accident sequence. The molten pool and crust formation were studied employing the Ansys-Fluent code. The 3D model using Large Eddy Simulation (LES) predicts the conjugate, radiative and convective heat transfer inside and from the corium pool. LES simulations require a very fine grid to capture the crust formation and the free convection flow. This aspect (fine mesh requirement) correlated with the long transient has imposed the use of a slice from the 3D calandria geometry in order not to exceed the computing resources. The preliminary results include heat transfer coefficients, temperature profiles and heat fluxes through calandria wall. From the safety point of view it is very important to maintain a heat flux through the wall below the CHF assuring the integrity of the calandria vessel. This can be achieved by proper cooling of the tank water which contains the vessel. Also, transient duration can be estimated being important in developing guidelines for severe accidents management. The debris physical structure and material properties have large uncertainties in the temperature range of interest. Thus, further sensitivity studies should be carried out in order to better understand the influence of these parameters on this complex phenomenon. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SU-F-T-362: Quantification and Modelling of the Ionization Chamber Simulation Effective Points On Monaco Treatment Planning System

Purpose: Because of statistical noise in Monte Carlo dose calculations, effective point doses may not be accurate. Volume spheres are useful for evaluating dose in Monte Carlo plans, which have an inherent statistical uncertainty.We use a user-defined sphere volume instead of a point, take sphere sampling around effective point make the dose statistics to decrease the stochastic errors. Methods: Direct dose measurements were made using a 0.125cc Semiflex ion chamber (IC) 31010 isocentrically placed in the center of a homogeneous Cylindric sliced RW3 phantom (PTW, Germany).In the scanned CT phantom series the sensitive volume length of the IC (6.5mm) were delineated and defined the isocenter as the simulation effective points. All beams were simulated in Monaco in accordance to the measured model. In our simulation using 2mm voxels calculation grid spacing and choose calculate dose to medium and request the relative standard deviation ≤0.5%. Taking three different assigned IC over densities (air electron density(ED) as 0.01g/cm3 default CT scanned ED and Esophageal lumen ED 0.21g/cm3) were tested at different sampling sphere radius (2.5, 2, 1.5 and 1 mm) statistics dose were compared with the measured does. Results: The results show that in the Monaco TPS for the IC using Esophageal lumen ED 0.21g/cm3 and sampling sphere radius 1.5mm the statistical value is the best accordance with the measured value, the absolute average percentage deviation is 0.49%. And when the IC using air electron density(ED) as 0.01g/cm3 and default CT scanned EDthe recommented statistical sampling sphere radius is 2.5mm, the percentage deviation are 0.61% and 0.70%, respectivly. Conclusion: In Monaco treatment planning system for the ionization chamber 31010 recommend air cavity using ED 0.21g/cm3 and sampling 1.5mm sphere volume instead of a point dose to decrease the stochastic errors. Funding Support No.C201505006.

60 APPLIED LIFE SCIENCES↗

Self-assembly of a drop pattern from a two-dimensional grid of nanometric metallic filaments

We report experiments, modeling, and numerical simulations of the self–assembly of particle patterns obtained from a nanometric metallic square grid. Initially, nickel filaments of rectangular cross section are patterned on a SiO 2 flat surface, and then they are melted by laser irradiation with ~18-ns pulses. During this time, the liquefied metal dewets the substrate, leading to a linear array of drops along each side of the squares. The experimental data provide a series of SEM images of the resultant morphology as a function of the number of laser pulses or cumulative liquid lifetime. These data are analyzed in terms of fluid mechanical models that account for mass conservation and consider flow evolution with the aim to predict the final number of drops resulting from each side of the square. The aspect ratio, δ, between the square sides' lengths and their widths is an essential parameter of the problem. Our models allow us to predict the δ intervals within which a certain final number of drops are expected. The comparison with experimental data shows a good agreement with the model that explicitly considers the Stokes flow developed in the filaments neck region that lead to breakup points. Furthermore, numerical simulations that solve the Navier-Stokes equations along with slip boundary condition at the contact lines are implemented to describe the dynamics of the problem.

42 ENGINEERING↗

Toward prediction of turbulent atmospheric flows over propagating oceanic waves via machine-learning augmented large-eddy simulation

Wind-wave interactions have important effects on the energy harvesting of offshore wind farms. High-fidelity large-eddy simulation (LES) is a powerful approach for investigating wind-wave interactions in turbulent oceanic environments. Due to the large scale of the flow domain and the high grid resolution required to resolve multi-scale flow motions, however, brute-force LES of wind-wave interactions is computationally very expensive. We propose augmenting brute-force LES via machine-learning data-driven modeling (ML-LES) to dramatically reduce the computational time required to obtain converged turbulence statistics when the brute-force approach is employed. Namely, we employ a convolutional neural network (CNN) autoencoder trained and validated with LES data sets to develop a highly efficient ML-LES approach for computing turbulence statistics from just a few snapshots of instantaneous LES flow fields. Further, our results demonstrate the accuracy and efficiency of ML-LES in predicting the mean velocity, velocity fluctuations, and turbulence kinetic energy in highly stretched computational grid systems required to carry out simulations in real-life oceanic environments.

42 ENGINEERING↗

A Petri Net model for distributed energy system

Electrical networks need to evolve to become more intelligent, more flexible and less costly. The smart grid is the next generation power energy, uses two-way flows of electricity and information to create a distributed automated energy delivery network. Building a comprehensive smart grid is a challenge for system protection, optimization and energy efficient. Proper modeling and analysis is needed to build an extensive distributed energy system and intelligent electricity infrastructure. In this paper, the whole model of smart grid have been proposed using Generalized Stochastic Petri Nets (GSPN). The simulation of created model is also explored. The simulation of the model has allowed the analysis of how close the behavior of the model is to the usage of the real smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

TURBULENCE IN THE INTERGALACTIC MEDIUM: SOLENOIDAL AND DILATATIONAL MOTIONS AND THE IMPACT OF NUMERICAL VISCOSITY

We use a suite of cosmological hydrodynamical simulations, run by two fixed grid codes, to investigate the properties of solenoidal and dilatational motions of the intergalactic medium (IGM) and the impact of numerical viscosity on turbulence in an ΛCDM universe. The codes differ only in the spatial difference discretization. We find that (1) The vortical motion grows rapidly since z = 2 and reaches ∼10 km s{sup –1}-90 km s{sup –1} at z = 0. Meanwhile, the small-scale compressive ratio r{sub CS} drops from 0.84 to 0.47, indicating comparable vortical and compressive motions at z = 0. (2) Power spectra of the solenoidal velocity possess two regimes, ∝k {sup –0.89} and ∝k {sup –2.02}, while the total and dilatational velocity follow the scaling k {sup –1.88} and k {sup –2.20}, respectively, in the turbulent range. The IGM turbulence may contain two distinct phases, the supersonic and post-supersonic phases. (3) The non-thermal pressure support, measured by the vortical kinetic energy, is comparable with the thermal pressure for ρ{sub b} ≅ 10-100, or T < 10{sup 5.5} K at z = 0.0. The deviation of the baryon fraction from the cosmic mean shows a preliminary positive correlation with the turbulence pressure support. (4) A relatively higher numerical viscosity would dissipate both the compressive and vortical motions of the IGM into thermal energy more effectively, resulting in less developed vorticity, remarkably shortened inertial range, and leading to a non-negligible uncertainty in the thermal history of gas accretion. Shocks in regions outside of clusters are significantly suppressed by numerical viscosity since z = 2, which may directly cause the different levels of turbulence between the two codes.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrating Cloud Processes in the Community Atmosphere Model, Version 5.

This paper provides a description on the parameterizations of global cloud system in CAM5. Compared to the previous versions, CAM5 cloud parameterization has the following unique characteristics: (1) a transparent cloud macrophysical structure that has horizontally non-overlapped deep cumulus, shallow cumulus and stratus in each grid layer, each of which has own cloud fraction, mass and number concentrations of cloud liquid droplets and ice crystals, (2) stratus-radiation-turbulence interaction that allows CAM5 to simulate marine stratocumulus solely from grid-mean RH without relying on the stability-based empirical empty stratus, (3) prognostic treatment of the number concentrations of stratus liquid droplets and ice crystals with activated aerosols and detrained in-cumulus condensates as the main sources and evaporation-sedimentation-precipitation of stratus condensate as the main sinks, and (4) radiatively active cumulus. By imposing consistency between diagnosed stratus fraction and prognosed stratus condensate, CAM5 is free from empty or highly-dense stratus at the end of stratus macrophysics. CAM5 also prognoses mass and number concentrations of various aerosol species. Thanks to the aerosol activation and the parameterizations of the radiation and stratiform precipitation production as a function of the droplet size, CAM5 simulates various aerosol indirect effects associated with stratus as well as direct effects, i.e., aerosol controls both the radiative and hydrological budgets. Detailed analysis of various simulations revealed that CAM5 is much better than CAM3/4 in the global performance as well as the physical formulation. However, several problems were also identifed, which can be attributed to inappropriate regional tuning, inconsistency between various physics parameterizations, and incomplete model physics. Continuous efforts are going on to further improve CAM5.

CAM5↗

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studying real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

BSEC ecohydrological and water quality fluxes from RHESSys Simulations in USGS gauged watersheds

Baltimore Environmental Social Collaborative (BSEC) Water and Water Quality Simulations from RHESSys Model The repository contains RHESSys (Tague & Band, 2004; source code) simulated ecohydrological and nutrient (nitrogen only) fluxes at daily, basin-average (RHESSys_basin_output) and monthly, grid (RHESSys_patch_output) levels. We currently simulated the following 8 watersheds in Baltimore: Dead Run Baisman Run Scotts Level Branch Moores Run Powder Mill Run Maidens Choice Run Stony Run The watershed boundaries of all studied watersheds are stored in Watershed_Boundary folder. Variables and their units are listed in the metadata. Spatial projection, NAD83 / UTM zone 18N (EPSG:26918) is used for patch-level, netCDF-format files. For more information, please contact Ruoyu Zhang (rz3jr@virginia.edu).

Baltimore MD↗

High-fidelity simulation-driven model development for coarse-grained computational fluid dynamics

Nuclear reactor safety analysis requires analysis of a broad range of accident scenarios and determining their consequences. For a nuclear power plant behavior, it is impossible to obtain experimental data at sufficiently large scales to support calibration and validation of various system models. In single-phase flow convective problems, high-resolution methods of Computational Fluid Dynamics (CFD) such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide high fidelity results under conditions where physical measurements are unavailable. However, such high-resolution simulations are computationally expensive and not suitable for simulation of long transient scenarios in nuclear reactor accidents. In this work, we investigate the use of a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. Notably, fine-mesh simulations are used to construct physics-informed statistical surrogate of coarse-mesh SGS model. For an initial analysis, we consider a case of turbulent natural convection in a volumetrically heated fluid layer with a thermally insulated lower boundary and isothermal upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a severe nuclear reactor accident, as well as in containment mixing and passive cooling. For this type of flow, the SGS effect is modeled by an added turbulent diffusivity in the energy equation. It is shown that a global correction for the energy equation is sufficient to achieve a significant improvement to the CG-CFD prediction of thermal mixing in the fluid layer. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NETL- AVESTAR

NETL's Advanced Virtual Energy Simulation Training and Research, or AVESTAR, Center is designed to promote operational excellence for the nation's energy systems, from smart power plants to smart grid. The AVESTAR Center brings together advanced dynamic simulation and control technologies, state-of-the-art simulation-based training facilities, and leading industry experts to focus on the optimal operation of clean energy plants in the smart grid era.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SCALE modeling of foil irradiations at WSU’s TRIGA with sensitivity/uncertainty analysis

We report the Washington State University TRIGA reactor was modeled in the SCALE system’s KENO neutron transport code. The model includes 119 fuel rods, a central boral control rod, 4 control blades, 5 irradiation ports, and 20 graphite reflector blocks within a rectangular aluminum grid box. The model accurately simulated the irradiation of depleted uranium and highly enriched uranium foils and predicted reaction rate ratios for 238 U(n,2n) 237 U / 238 U(n,γ) 239 U and 99 Mo / fission, which compared favorably to empirical values previously measured at Los Alamos. Finally, a sensitivity/uncertainty analysis was performed using the continuous-energy TSUNAMI-3D module of SCALE.

237Np↗

Dendrite-resolved, full-melt-pool phase-field simulations to reveal non-steady-state effects and to test an approximate model

In this report we study the epitaxial, columnar growth of (multiply oriented) dendrites/cells for a spot melt in a polycrystalline Al–Cu substrate using two-dimensional, phase-field, direct numerical simulations (DNS) at the full-melt-pool scale. Our main objective is to compare the expensive DNS model to a much cheaper but approximate “line” model in which a single-crystal phase-field simulation is confined to a narrow rectangular geometry. To perform this comparison, we develop algorithms that automatically extract quantities of interest (QoIs) from both DNS and line models. These QoIs allow us to quantitatively assess the assumptions in the line model and help us analyze its discrepancy with the DNS model. We consider four sets of heat source parameters, mimicking welding and additive manufacturing conditions, that create a combination shallow and deep melt pools. Our largest DNS simulation used 16K x 14K grid points in space. Our main findings can be summarized as follows. Under AM conditions, the QoIs of line models are in excellent agreement with the full DNS results for both shallow and deep melt pools. Under welding conditions, the primary spacing of the DNS model is smaller than the prediction of line model. We identify a geometric crowding effect that accounts for the discrepancies between the DNS and line models. We propose two potential mechanisms that determine the response of the microstructure to geometric crowding.

36 MATERIALS SCIENCE↗