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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Real-Time Simulation of Modular Multilevel Converters

Modular multilevel converters (MMCs) are one of the most popular configurations of voltage-source converters (VSCs) used in applications like high-voltage direct current (HVdc) transmission systems and flexible alternate current transmission systems (FACTS). They have a large number of modules with thousands of capacitors and semiconductor devices, which make it hard to simulate in real-time. In this paper, a low-cost high-performance computing (HPC) configuration to simulate MMCs in real-time is proposed. The configuration uses a HPC digital signal processor (DSP) with 8 cores. An advanced MMC simulation algorithm is implemented using HPC techniques to optimize the real-time performance in the DSP. A comparison is performed with existing solutions to show the superiority of the proposed configuration and algorithms.

Debnath, Suman↗
DOE OSTI2017

Adaptive building load control to enable high penetration of solar photovoltaic generation

This paper investigates the ability of a collection of deferrable heating, ventilation and air conditioning (HVAC) loads to directly emulate energy storage devices (ESD), that is, to absorb any low frequency fluctuations in solar generation. We find the optimal number of aggregated HVAC loads to absorb solar fluctuation in the same frequency band based on frequency analysis. To guarantee quality of service in afleet of residential buildings, an optimization problem is formed to compute optimal schedule of the HVAC loads considering temperature comfort band and available solar generation. By minimizing the tracking error between solar generation and total consumption, the proposed method also quantifies the minimum capacity of ESD (battery or fly-wheel) . The simulation results show that the proposed techniques are able to achieve good solar tracking performance as well as obtain a minimal ESD capacity. Therefore, we show that most of the renewable generation can be consumed locally through an intelligent coordination of HVAC loads, their impacts on the grid would be minimal and the required ESD capacity can be minimized.

Dong, Jin↗
DOE OSTI2016

Privacy-Assured Aggregation Protocol for Smart Metering: A Proactive Fault-Tolerant Approach [Proactive Fault-Tolerant Aggregation Protocol for Privacy-Assured Smart Metering]

Smart meters are integral to demand response in emerging smart grids, by reporting the electricity consumption of users to serve application needs. But reporting real-time usage information for individual households raises privacy concerns. Existing techniques to guarantee differential privacy (DP) of smart meter users either are not fault tolerant or achieve (possibly partial) fault tolerance at high communication overheads. In this paper, we propose a fault-tolerant protocol for smart metering that can handle general communication failures while ensuring DP with significantly improved efficiency and lower errors compared with the state of the art. Our protocol handles fail-stop faults proactively by using a novel design of future ciphertexts, and distributes trust among the smart meters by sharing secret keys among them. We prove the DP properties of our protocol and analyze its advantages in fault tolerance, accuracy, and communication efficiency relative to competing techniques. We illustrate our analysis by simulations driven by real-world traces of electricity consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Сoncentric GaAs Nanorings Growth Modelling

The nanostructures formation process using the droplet epitaxy technique was investigated by Monte Carlo simulation. The simulation was fulfilled for two-dimensional and three-dimensional geometry substrates. The nanostructures morphology dependence on the growth temperature was presented. Crystal clusters, single and double rings were observed. The nanostructures shape was shown to be determined by the gallium diffusion length. The conditions of double rings formation during the droplet epitaxy were considered using analytical and numerical approaches. The factors that determine the rings location and shape were analyzed. The growth morphology was demonstrated to be dependent on the initial distance L between the droplets. The double ring formation was possible at a low droplet density only, when the As-stabilized region could be created between the droplets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Toward a Theory of Superdense Time in Simulation Models

In this work, we develop a theory of superdense time that encompasses existing uses of superdense time in discrete event simulations and points to new forms that have not previously been explored. A central feature of our development is a set of axioms for superdense time. Furthermore, the sufficiency of these axioms is demonstrated by using them to prove that a general model of a discrete event simulation procedure, expressed in terms of a mathematical system, constitutes a state transition function. Several forms of superdense time, both known and novel, are shown to satisfy the axioms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

BEopt™ (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]

The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. The BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. The BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. The BEopt software uses EnergyPlus®, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols. The sequential search optimization technique used by the BEopt software: Finds minimum-cost building designs at different target energy-savings levels Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. Download A BEopt™ Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.

Christensen, Craig↗
DOE OSTI2022

Putting multipoint kinetics to the test: preliminary analysis of the MUSE-4 experiment with APOLLO3

Modeling neutron kinetics is a challenging task and over the years, several approaches have been developed offering different tradeoffs between precision and cost. Probably the most popular one is point kinetics (PK), which, despite being very cheap, provides good results for many applications. One of the limitations of PK is that it is not able to model effects that happen before the prompt jump time scale. In practice, applications, where those time scales are interesting, are rare and those for which experimental data are available are even rarer. One of those cases is the MUSE-4 experiment for which the focus is on the very fast behavior and where we have no thermal feedback. As we have shown in a recent paper, a simple extension of PK, known as multipoint kinetics (MPK), can overcome this limitation. In this paper, which is intended as a preliminary study, we show how a simple MPK model can qualitatively reproduce the fast behavior that we cannot model with PK. Moreover, we will show how to exploit its low cost and compact form to model also slow effects as the precursors built up, behaviours that are not affordable to model with more expensive techniques, such as kinetic Monte Carlo simulations. For the periodic pulse transients with no feedbacks we will also provide an analytical solution in closed form. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A GPU-based 2D shallow water quality model

In this paper, a 2D shallow water flow solver integrated with a water quality model is presented. The interaction between the main water quality constituents included is based on the Water Quality Analysis Simulation Program. Efficiency is achieved by computing with a combination of a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) device. This technique is intended to provide robust and accurate simulations with high computation speedups with respect to a single-core CPU in real events. The proposed numerical model is evaluated in cases that include the transport and reaction of water quality components over irregular bed topography and dry–wet fronts, verifying that the numerical solution in these situations conserves the required properties (C-property and positivity). The model can operate in any steady or unsteady form allowing an efficient assessment of the environmental impact of water flows. The field data from an unsteady river reach test case are used to show that the model is capable of predicting the measured temporal distribution of dissolved oxygen and water temperature, proving the robustness and computational efficiency of the model, even in the presence of noisy signals such as wind speed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases

Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Two Models of Adhesive Debonding of Sylgard

This report begins with a brief summary of the range of modeling methods used to simulate adhesive debonding. Then the mechanical simulation of the blister debonding test, and the thermomechanical simulation of the potted hemisphere problem are described. For both simulations, details of the chosen modeling techniques, and the reasons for choosing them (and rejecting alternate modeling approaches) will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An Integrated Study on a Novel High Temperature High Entropy Alloy

This report summarizes our recent works of theoretical modeling, simulation, and experimental validation of the simulation results on the new refractory high entropy alloy (HEA) design and oxide doped refractory HEA research. The simulation of the stability and thermal dynamics simulation on potential thermal stable candidates were performed and related HEA with oxide doped samples were synthesized and characterized. The HEA ab initio density functional theory and molecular dynamics physical property simulation methods and experimental texture validation techniques development, achievements already reached, course work development, students and postdoc training, and future improvement research directions are briefly introduced.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Agile Design-to-Simulation Workflow Using a New Conforming Moving Least Squares Method

This report summarizes the accomplishments and challenges of a two year LDRD effort focused on improving design-to-simulation agility. The central bottleneck in most solid mechanics simulations is the process of taking CAD geometry and creating a discretization of suitable quality, i.e., the "meshing" effort. This report revisits meshfree methods and documents some key advancements that allow their use on problems with complex geometries, low quality meshes, nearly incompressible materials or that involve fracture. The resulting capability was demonstrated to be an effective part of an agile simulation process by enabling rapid discretization techniques without increasing the time to obtain a solution of a given accuracy. The first enhancement addressed boundary-related challenges associated with meshfree methods. When using point clouds and Euclidean metrics to construct approximation spaces, the boundary information is lost, which results in low accuracy solutions for non-convex geometries and mate rial interfaces. This also complicates the application of essential boundary conditions. The solution involved the development of conforming window functions which use graph and boundary information to directly incorporate boundaries into the approximation space.

42 ENGINEERING↗
DOE OSTI2019

Electrochemically-Driven Phase Transformations in Battery Compounds (Final Technical Report)

Ion-insertion compounds for advanced batteries frequently exhibit phase transformations as the concentration of the working ion varies. Under the large electrochemical driving forces inherent to practical use, systems are often driven far from equilibrium and exhibit phase transition behavior not seen in other materials. An improved understanding of phase transformation pathways in electrode materials upon cycling will lead to new materials design concepts and electrochemical duty cycle management strategies that improve capacity utilization at high charge/discharge rates, reduce voltage and capacity hysteresis, and extend battery life. The main goal of this project is to develop a predictive understanding of the phase transition behavior of battery compounds when electrochemically driven far from equilibrium through a combined experimental- theoretical approach. Research focuses on elucidating how the phase transition behaviors in a diverse group of selected model systems (olivines, lithium metal, etc.) are regulated by various factors including transformation strains, plasticity, metastable transformation pathways, electrode microstructure, surface reaction and ion diffusion kinetics, and what are the unique features of phase transitions in battery compounds. To this end, operando X-ray-based characterization techniques are applied to interrogate the structure and composition evolution of electrode materials and interfaces at nano- and meso-scales. Mesoscale modeling techniques such as phase-field simulation are employed to shed light on the experimental observations and establish a unified framework for describing phase transition behaviors in battery compounds.

25 ENERGY STORAGE↗
DOE OSTI2019

[Office of Basic Energy Sciences (BES)] Roundtable on Producing and Managing Large Scientific Data with Artificial Intelligence and Machine Learning

To identify specific Priority Research Opportunities (PROs) for artificial intelligence and machine learning (AI/ML) at the US Department of Energy’s scientific user facilities, the Office of Basic Energy Sciences (BES) convened a roundtable of facility experts encompassing the fields of physics, chemistry, materials synthesis science, computational science, detector and accelerator technology, theory, modeling, simulation, and atomic-scale characterization techniques. The roundtable met on October 22–23, 2019, to identify coordinated, long-term AI/ML research efforts that will drive major advances in neutron, photon, and nanoscale sciences. This report describes the four PROs identified at the roundtable: PRO 1 on how AI/ML can extract high-value information from the large datasets; PRO 2 on how AI/ML can use such information in real time to maximize the facilities’ scientific output; PRO 3 on using AI/ML virtual laboratories (i.e., computational models of experimental facilities) to aid the facilities and user community in design and control of machine parameters and the design and execution of experiments, including training AI/ML models for PROs 1 and 2; and PRO 4 on how a shared scientific data infrastructure can provide tools to assemble and analyze the totality of data coming from user facilities. A section of the end of the report provides a summary on computer science and mathematics that highlights where enhanced AI/ML capabilities could be particularly impactful for BES user facilities.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Wind Turbine Lightning Mitigation System Radar Cross Section Reduction

Modern wind turbines employ Lightning Mitigation Systems (LMSs) in order to reduce costly damages caused by lightning strikes. Lightning strikes on wind turbines occur frequently making LMS configurations a necessity. An LMS for a single turbine includes, among other equipment, cables running inside each blade, along the entire blade length. These cables are connected to various metallic receptors on the outside surface of the blades. The LMS cables can act as significant electromagnetic scatterers which may cause interference to radar systems. This interference may be mitigated by reducing the Radar Cross-Section (RCS) of the wind turbine's LMS. This report investigates proposed modifications to LMS cables in order to reduce the RCS when illuminated by Re locatable Over the Horizon Radar (ROTHR) systems which operate in the HF band (3 - 30 MHz). The proposed modifications include breaking up the LMS cables using spark gap connections, and changing the orientation of the LMS cable within the turbine blade. Both simulated analyses of such RCS mitigation techniques is provided as well as recommendations on further research.

17 WIND ENERGY↗
DOE OSTI2020

Weak lensing in DES Y3: redshift distributions, shape catalogue, and mass mapping

The size of galaxy surveys have rapidly escalated with time, growing from thousands of galaxies of the first pioneering surveys to current and future surveys (DES, KiDS, HSC, LSST, Euclid, WFIRST), which map (or plan to map) a few hundreds millions of galaxies. These ambitious programs have the potential to answer many open questions in Cosmology (or, depending on their results, to open new exciting scenarios, involving new physics beyond the standard cosmological model and the standard model of particle physics). In particular, this thesis focuses on the first three years of data from the Dark Energy Survey (DES Y3), which comprises 100 million galaxies observed in 5 different optical bands over 5000 square degrees of the southern hemisphere. DES and the data set used in this thesis are discussed in detail in Chapter 3, which together with Chapter 1 and 2 constitutes Part I of this thesis. The scientifically positive outcome of DES and other photometric galaxy surveys goes h and in h and with a supreme understanding of the data, of the observational systematics affecting the measurements, and of the limits of the theoretical modelling of the observables. One of the main challenge of galaxy photometric surveys like DES is to correctly estimate the distance to the galaxies. Photometric surveys observe the galaxies in a limited number of broad optical bands, and the estimate of their \textit{redshifts} is somewhat uncertain, which constitutes one of the main limiting factor of their cosmological analyses. Part II and its Chapter 4 are devoted to a new auxiliary technique recently developed that allows to infer (or calibrate) redshift distributions exploiting cross-correlation with small reference samples with secure redshifts. The so called ``clustering-redshift'' method is discussed in depth, as well as its role in the overall DES Y3 redshift calibration strategy. Part III and Chapter 5 are devoted to another key aspect of photometric surveys, that enables the stu dy of weak gravitational lensing: the shape catalogue. The official DES Y3 shape catalogue is presented, together with all the systematic tests performed to validate it such that it can be considered science-ready. Last, part IV focuses on how to use weak gravitational lensing and the DES Y3 shape catalogue to create weak lensing mass maps, i.e., maps of the mass distribution of the Universe. Chapter 6 discusses different map making techniques, whereas Chapter 7 presents a simulated cosmological analysis using the high order moments of the mass maps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Emergent Recursive Multiscale Interaction in Complex Systems

This project studied the potential for multiscale group dynamics in complex social systems, including emergent recursive interaction. Current social theory on group formation and interaction focuses on a single scale (individuals forming groups) and is largely qualitative in its explanation of mechanisms. We combined theory, modeling, and data analysis to find evidence that these multiscale phenomena exist, and to investigate their potential consequences and develop predictive capabilities. In this report, we discuss the results of data analysis showing that some group dynamics theory holds at multiple scales. We introduce a new theory on communicative vibration that uses social network dynamics to predict group life cycle events. We discuss a model of behavioral responses to the COVID-19 pandemic that incorporates influence and social pressures. Finally, we discuss a set of modeling techniques that can be used to simulate multiscale group phenomena.

42 ENGINEERING↗