Search NASA⌕ Search

SEARCH · Search NASA

Results for “Grid Simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

On the estimation of gravitational wave spectrum from cosmic domain walls

We revisit the production of gravitational waves from unstable domain walls analyzing their spectrum by the use of field theoretic lattice simulations with grid size 1024{sup 3}, which is larger than the previous study. We have recognized that there exists an error in the code used in the previous study, and the correction of the error leads to the suppression of the spectrum of gravitational waves at high frequencies. The peak of the spectrum is located at the scale corresponding to the Hubble radius at the time of the decay of domain walls, and its amplitude is consistent with the naive estimation based on the quadrupole formula. Using the numerical results, the magnitude and the peak frequency of gravitational waves at the present time are estimated. It is shown that for some choices of parameters the signal of gravitational waves is strong enough to be probed in the future gravitational wave experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

What do we mean by the word “Shock”?

From one vantage point, a shock is a continuous but drastic change in state variables that occurs over very small time and length scales. These scales and associated changes in state variables can be measured experimentally. From another vantage point, a shock is a mathematical singularity consisting of instantaneous changes in state variables. This more mathematical view gives rise to analytical solutions to idealized problems. And from a third vantage point, a shock is a structure in a hydrocode prediction. Its width depends on the simulation’s grid resolution and artificial viscosity. These three vantage points can be in conflict when ideas from the associated fields are combined, and yet combining them is an important goal of an integrated modeling program. This presentation explores an example of how models for real materials in the presence of real shocks react to a hydrocode’s numerical shocks of finite width. The presentation will include an introduction to plasticity for the novice, an historical view of plasticity algorithms, a demonstration of how pursuing the meaning of “shock” has resulted in hydrocode improvements, and will conclude by answering some of the questions that arise from that pursuit. After the technical part of the presentation, a few slides advertising LANL’s Computational Physics Student Summer Workshop will be shown.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Evaluating the functionality and streamflow impacts of explicitly modelling forest-snow interactions and canopy gaps in a distributed hydrologic model

Many plot-scale observational studies found that snow cover dynamics in forest gaps are distinctly different from open and continuously forested areas, and canopy gaps have the potential to increase snow retention and alter the snow regime. However, our knowledge on forest-snow interactions in discontinuous forests with canopy gaps and their implications for forest and water management is far more limited. We address this knowledge gap through a major enhancement of a widely used distributed hydrologic model, DHSVM. We developed a canopy gap component as a unique vegetation type that is characterized on the subgrid scale, with physics-based representation of processes that allow independent evolution of snowpack in forest gaps. We validated the enhanced DHSVM for three experimental sites in close proximity consisting of a completely open site, a densely forested site, and a canopy gap site. Despite the scale mismatch between point measurements and grid-scale simulations, the modeled snow water equivalent (SWE) agreed reasonably well with the continuous observations collected during one full ablation season at all sites. Evaluation of snowpack energetics suggested that snow ablation at three sites was controlled primarily by net radiation that critically depends on the canopy cover and structure. While the rate of snowmelt remained relatively constant in the forest during the ablation season, the gap demonstrated marked temporal variability in ablation rate as a result of complex interplay between canopy structure of the adjacent forest and the angle of solar incidence. The comparison of this enhanced version to the original DHSVM highlighted the importance of explicitly accounting for forest impacts on the gap snowpack energy balance. Between the two versions, the greatest difference in snow ablation rates was found in smaller gaps. The enhanced model tends to predict notably later melt for small to medium canopy gaps (the ratio of gap radius to canopy height r/h = 1.3), and snow melt rates exhibit great sensitivity to changing gap size in medium-size gaps (0.5 = r/h = 1.3).

Forest-Snow Dynamics, Canopy Gap, Snow Hydrology, ↗
DOE OSTI2018

Polarization Filter for Microstrip Lumped-Element Kinetic Inductance Detectors

Polarization sensitivity is a major requirement in future cosmic microwave background studies. Even though lumped-element kinetic inductance detectors (LEKIDs) have already demonstrated a good performance in the millimeter range, the typical configuration based on linear meander inductors exhibits a cross polarization up to 30%. In this work, we propose a new configuration of LEKIDs coupled to a microstrip transmission line where the continuous ground plane has been replaced with parallel lines in order to be used as a polarizing grid. Microwave simulations and preliminary experiments show that the polarizer acts as an effective ground plane with no influence in the electromagnetic performance and that the cross polarization can be decreased to 3%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

A new high-order spectral difference method for simulating viscous flows on unstructured grids with mixed-element meshes

In the present study, a spectral difference (SD) method is developed for viscous flows on meshes with a mixture of triangular and quadrilateral elements. The standard SD method for triangular elements, which employs Lagrangian interpolating functions for fluxes, is not stable when the designed accuracy of spatial discretization is third order or higher. Unlike the standard SD method, the method examined here uses vector interpolating functions in the Raviart-Thomas (RT) spaces to construct continuous flux functions on reference elements. The spectral-difference Raviart-Thomas (SDRT) method was originally proposed by Balan et al. and implemented on triangular-element meshes for invisid flow only. Our present results demonstrated that the SDRT method is stable and high-order accurate in two dimensions (2D) for a number of test problems by using triangular-, quadrilateral-, and mixed-element meshes for both inviscid and viscous flows. A stability analysis is also performed for mixed elements. Furthermore, we found our current SDRT scheme is stable for fourth-order accurate spatial discretizations. However, a stable fifth-order SDRT scheme remains to be identified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A parallel-in-time algorithm for variable step multistep methods

This paper presents a multigrid reduction in time (MGRIT) algorithm for achieving time parallelism using multistep backward difference formula (BDF) methods on variably-spaced temporal grids. This MGRIT approach transforms the linear multistep methods into single step methods applied to groups of time steps. Stability considerations are addressed through lowering of the order on coarse grids. The methods are presented for fixed and variable time step formulations. Furthermore, numerical results show moderate speedups for the heat equation as well as two IEEE power grid test problems characterized by nonlinear differential algebraic equations (DAE) of index 1. The performance of MGRIT with BDF is compared to MGRIT with Runge-Kutta for both the fixed and variable step methods of the same order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Resistive magnetohydrodynamic reconnection: Resolving long-term, chaotic dynamics

In this paper, we address the long-term evolution of an idealised double current system entering reconnection regimes where chaotic behavior plays a prominent role. Our aim is to quantify the energetics in high magnetic Reynolds number evolutions, enriched by secondary tearing events, multiple magnetic island coalescence, and compressive versus resistive heating scenarios. Our study will pay particular attention to the required numerical resolutions achievable by modern (grid-adaptive) computations, and comment on the challenge associated with resolving chaotic island formation and interaction. We will use shock-capturing, conservative, grid-adaptive simulations for investigating trends dominated by both physical (resistivity) and numerical (resolution) parameters, and confront them with (visco-)resistive magnetohydrodynamic simulations performed with very different, but equally widely used discretization schemes. This will allow us to comment on the obtained evolutions in a manner irrespective of the adopted discretization strategy. Our findings demonstrate that all schemes used (finite volume based shock-capturing, high order finite differences, and particle in cell-like methods) qualitatively agree on the various evolutionary stages, and that resistivity values of order 0.001 already can lead to chaotic island appearance. However, none of the methods exploited demonstrates convergence in the strong sense in these chaotic regimes. At the same time, nonperturbed tests for showing convergence over long time scales in ideal to resistive regimes are provided as well, where all methods are shown to agree. Both the advantages and disadvantages of specific discretizations as applied to this challenging problem are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

DISTRIBUTION OF ACCRETING GAS AND ANGULAR MOMENTUM ONTO CIRCUMPLANETARY DISKS

We investigate gas accretion flow onto a circumplanetary disk from a protoplanetary disk in detail by using high-resolution three-dimensional nested-grid hydrodynamic simulations, in order to provide a basis of formation processes of satellites around giant planets. Based on detailed analyses of gas accretion flow, we find that most of gas accretion onto circumplanetary disks occurs nearly vertically toward the disk surface from high altitude, which generates a shock surface at several scale heights of the circumplanetary disk. The gas that has passed through the shock surface moves inward because its specific angular momentum is smaller than that of the local Keplerian rotation, while gas near the midplane in the protoplanetary disk cannot accrete to the circumplanetary disk. Gas near the midplane within the planet's Hill sphere spirals outward and escapes from the Hill sphere through the two Lagrangian points L{sub 1} and L{sub 2}. We also analyze fluxes of accreting mass and angular momentum in detail and find that the distributions of the fluxes onto the disk surface are well described by power-law functions and that a large fraction of gas accretion occurs at the outer region of the disk, i.e., at about 0.1 times the Hill radius. The nature of power-law functions indicates that, other than the outer edge, there is no specific radius where gas accretion is concentrated. These source functions of mass and angular momentum in the circumplanetary disk would provide us with useful constraints on the structure and evolution of the circumplanetary disk, which is important for satellite formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

CHARACTERIZING THE GALACTIC WHITE DWARF BINARY POPULATION WITH SPARSELY SAMPLED RADIAL VELOCITY DATA

We present a method to characterize statistically the parameters of a detached binary sample-binary fraction, separation distribution, and mass-ratio distribution-using noisy radial velocity data with as few as two, randomly spaced, epochs per object. To do this, we analyze the distribution of {Delta}RV{sub max}, the maximum radial velocity difference between any two epochs for the same object. At low values, the core of this distribution is dominated by measurement errors, but for large enough samples there is a high-velocity tail that can effectively constrain the parameters of the binary population. We discuss our approach for the case of a population of detached white dwarf (WD) binaries with separations that are decaying via gravitational wave emission. We derive analytic expressions for the present-day distribution of separations, integrated over the star formation history of the Galaxy, for parameterized initial WD separation distributions at the end of the common-envelope phase. We use Monte Carlo techniques to produce grids of simulated {Delta}RV{sub max} distributions with specific binary population parameters, and the same sampling cadences and radial velocity errors as the observations, and we compare them to the real {Delta}RV{sub max} distribution to constrain the properties of the binary population. We illustrate the sensitivity of the method to both the model and observational parameters. In the particular case of binary WDs, every model population predicts a merger rate per star which can easily be compared to specific Type Ia supernova rates. In a companion paper, we apply the method to a sample of {approx}4000 WDs from the Sloan Digital Sky Survey. The binary fractions and separation distribution parameters allowed by the data indicate a rate of WD-WD mergers per unit stellar mass in the Galactic disk, {approx}1 Multiplication-Sign 10{sup -13} mergers yr{sup -1} M{sup -1}{sub Sun }, remarkably similar to the rate per unit mass of Type Ia supernovae in Milky Way like galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Development of APCVD BSG and POCl 3 Codiffusion Process for Double-Side TOPCon Solar Cell Precursor Fabrication

This paper presents a commercially viable process for fabricating a high-quality double-side tunnel oxide passivating contact (DS-TOPCon) cell precursor using APCVD-deposited boron silicate glass and ex-situ POCl 3 diffusion in a single high-temperature step, eliminating the need for additional masking and diffusion processes. A two-tier temperature profile was developed, involving a pre-annealing at above 900°C in nitrogen (N2) ambient followed by POCl 3 diffusion at 840°C. We investigated the effect of varying pre-annealing temperatures, ranging from 875°C to 950°C, on the passivation quality and metal-Si contact properties of both n-TOPCon and p-TOPCon layers. The resultant DS-TOPCon cell precursor after silicon nitride (SiNX) passivation exhibited an excellent iV OC of close to 730 mV. In addition, a rapid asymmetric poly-Si thinning technique, developed in this work, enabled adjustment of the front n + poly-Si thickness while maintaining the rear p + poly-Si thickness. Two types of DS-TOPCon cell architectures can be fabricated: i) full-area thin (≈40nm) n-TOPCon layer on the front and ii) selective-area thick (≈200nm) n-TOPCon fingers underneath the metal grid. Device simulations suggest that full-area DS-TOPCon cell with 40 nm n + poly-Si and selective-area DS-TOPCon cell with 200 nm n + poly fingers on the front, fabricated from our current DS-TOPCon cell precursor, can achieve cell efficiencies of 22.1 and 23.5%, respectively. Detailed power loss analysis and device simulation reveal that further improvements in material and device parameters have potential to push the cell efficiencies of DS-TOPCon cell structure beyond 25%, making it a promising alternative to fabricate a high-efficiency next-generation solar cells at low cost.

14 SOLAR ENERGY↗
DOE OSTI2025

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗
DOE OSTI2020

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗
DOE OSTI2019

A Cooperative Multi-Agent Deep Reinforcement Learning Framework for Real-Time Residential Load Scheduling

Internet-of-Things (IoT) enabled monitoring and control capabilities are enabling increasing numbers of household users with controllable loads to actively participate in smart grid energy management. Realizing an efficient real-time energy management system that takes advantage of these developments requires novel techniques for managing the increased complexity of the control action space in resolving multiple challenges such as the uncertainty in energy prices and renewable energy output along with the need to satisy physical grid constraints such as transformer capacity. Addressing these challenges, we develop a multi-household energy management framework for residential units connected to the same transformer and containing DERs such as PV, ESS and controllable loads. The goal of our framework is to schedule controllable household appliances and ESS such that the cost of procuring electricity from the utility over a horizon is minimized while physical grid constraints are satisfied at each scheduling step. Traditional energy management frameworks either perform global optimization to satisfy grid constraints but suffer from high computational complexity (for example Integer Program, Mixed Integer Programming frameworks and centralized reinforcement learning) or perform decentralized real-time energy management without satisfying global grid constraints (for example multi-agent reinforcement learning with no cooperation). In contrast, we propose a cooperative multiagent reinforcement learning (MARL) framework that i) operates in real-time, and ii) performs explicit collaboration to satisfy global grid constraints. The novelty in our framework is two fold. Firstly, our framework trains multiple independent learners (IL) for each household in parallel using historical data and performs real-time inferencing of control actions using the most recent system state. Secondly, our framework contains a low complexity knapsack based cooperation agent which combines the outputs of ILs to minimize cost while satisfying grid constraints. Simulation results show that our cooperative MARL approach achieves significant cost improvement over centralized reinforcement learning and day-ahead planning baselines. Moreover, our approach strictly satisfies physical constraints with no apriori knowledge of system dynamics while the baseline approaches have occasional violations. We also measure the training and inference time by ranging the number of households from 1 to 25. Results show that our cooperative MARL approach scales best among various approaches.

14 SOLAR ENERGY↗
DOE OSTI2022

Applied Mathematics Challenge: Simulation of Power Electronics in Future Power Grid

There has been a buzz around increased grid modernization for more than a decade. Grid modernization includes, but is not limited to, upgrades to the grid to enhance reliability, resilience, security, and access to clean energy sources. One significant change that has been happening in this context is the increased penetration of computing power and controlled devices like power electronics in the power grid. As this change happens, the operation and characteristics of the power grid are set to undergo a significant change. The power grid moves from an older electric machine dominated grid that used analog electronics for controls to a power electronics dominated grid that uses digital computing for controls. As this transition happens, there are significant problems of applied mathematics that will need to be resolved in power electronics and power grid. The problems include the ability to simulate in different timescales, while also leveraging the significantly improved computing capabilities available today. In this paper, the challenges related to simulation of power electronics are discussed and the challenge problems laid down that applied mathematics may help resolve in future.

Debnath, Suman↗
DOE OSTI2018

OpenRES

The OpenRES is an open-source library of intermittent energy resources developed in the JModelica.org platform, and provides capability for performing long-term power grid dynamic simulation with renewable ancillary services (e.g., load ramp, frequency and voltage regulation).

Qin, Yining↗