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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A moment-conserving discontinuous Galerkin representation of the relativistic Maxwellian distribution

Kinetic simulations of relativistic gases and plasmas are critical for understanding diverse astrophysical and terrestrial systems, but the accurate construction of the relativistic Maxwellian, the Maxwell–Jüttner distribution, on a discrete simulation grid is challenging. Difficulties arise from the finite velocity bounds of the domain, which may not capture the entire distribution function, as well as errors introduced by projecting the function onto a discrete grid. Here, we present a novel scheme for iteratively correcting the moments of the projected distribution applicable to all grid-based discretizations of the relativistic kinetic equation. In addition, we describe how to compute the needed nonlinear quantities, such as Lorentz boost factors, in a discontinuous Galerkin scheme through a combination of numerical quadrature and weak operations. The resulting method accurately captures the distribution function and ensures that the moments match the desired values to machine precision.

astrophysical plasmas↗
DOE OSTI2019

Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model

Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny-associated photosynthetic capacity, and is evaluated against ground-based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light use efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO 2 and water fluxes in the tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

An Analysis of Concentrating Solar Power with Thermal Energy Storage in a California 33% Renewable Scenario (Report Summary) (Presentation)

This analysis evaluates CSP with TES in a scenario where California derives 33% of its electricity from renewable energy sources. It uses a commercial grid simulation tool to examine the avoided operational and capacity costs associated with CSP and compares this value to PV and a baseload generation with constant output. Overall, the analysis demonstrates several properties of dispatchable CSP, including the flexibility to generate during periods of high value and avoid generation during periods of lower value. Of note in this analysis is the fact that significant amount of operational value is derived from the provision of reserves in the case where CSP is allowed to provide these services. This analysis also indicates that the 'optimal' configuration of CSP could vary as a function of renewable penetration, and each configuration will need to be evaluated in terms of its ability to provide dispatchable energy, reserves, and firm capacity. The model can be used to investigate additional scenarios involving alternative technology options and generation mixes, applying these scenarios within California or in other regions of interest.

14 SOLAR ENERGY↗
DOE OSTI2013

Analysis of Concentrating Solar Power with Thermal Energy Storage in a California 33% Renewable Scenario

This analysis evaluates CSP with TES in a scenario where California derives 33% of its electricity from renewable energy sources. It uses a commercial grid simulation tool to examine the avoided operational and capacity costs associated with CSP and compares this value to PV and a baseload generation with constant output. Overall, the analysis demonstrates several properties of dispatchable CSP, including the flexibility to generate during periods of high value and avoid generation during periods of lower value. Of note in this analysis is the fact that significant amount of operational value is derived from the provision of reserves in the case where CSP is allowed to provide these services. This analysis also indicates that the 'optimal' configuration of CSP could vary as a function of renewable penetration, and each configuration will need to be evaluated in terms of its ability to provide dispatchable energy, reserves, and firm capacity. The model can be used to investigate additional scenarios involving alternative technology options and generation mixes, applying these scenarios within California or in other regions of interest.

14 SOLAR ENERGY↗
DOE OSTI2020

Accelerating geostatistical modeling using geostatistics-informed machine Learning

Ordinary Kriging (OK) is a popular geostatistical algorithm for spatial interpolation and estimation. The computational complexity of OK changes quadratically and cubically for memory and speed, respectively, given the number of data. Therefore, it is computationally intensive and also challenging to process a large set of data, especially in three-dimensional (3D) cases. This paper develops a geostatistics-informed machine learning (GIML) model to improve the efficiency of OK by reducing the number of points required to be estimated using OK. Specifically, only a very few of the unknown points are estimated by OK to get the weights and estimations, which are used as the training dataset. Moreover, the governing equations of OK are used to guide our proposed machine learning to better reproduce the spatial distributions. Our results show that the proposed GIML can reduce the computational time of OK by at least one order of magnitude. The effectiveness of the GIML is evaluated and compared using a 2D case. Furthermore, we demonstrate its efficiency and robustness by considering a different number of training samples on various 3D simulation grids.

58 GEOSCIENCES↗
DOE OSTI2019

Modeling Analysis of the Swell and Wind-Sea Climate in the Salish Sea

Accurate model hindcast of wave climate in complex estuarine systems is challenging because high-resolution wave model and wind forcing are required. In this study, a modeling approach using the unstructured-grid Simulating WAves Nearshore and wind product from a high-resolution regional Weather Research and Forecasting hindcast was used to simulate the swell and wind-sea climate in the Salish Sea, a large estuary with many interconnected waterways on the Pacific Northwest coast of North America. The model hindcast was validated with observed data at four wave buoys in the Salish Sea. Spatial distribution and seasonal variations of wave climate in the Salish Sea were analyzed. Of the three major basins in the Salish Sea, the Strait of Juan de Fuca has the largest waves and is dominated by swells propagated from the Pacific Ocean. Significant wave heights in the Strait of Georgia have spatial and seasonal distribution patterns similar to those found in the Strait of Juan de Fuca. Waves in Puget Sound are small and primarily dominated by the wind-sea climate. Strong seasonal variations are observed in the Strait of Juan de Fuca and Strait of Georgia, but there is little seasonality of wave climate in Puget Sound. The high-resolution wave hindcast conducted in this study provides a comprehensive and important data set for better understanding the role of wave climate in coastal processes and natural hazards assessment in the Salish Sea.

wave climate, salish sea, modeling, swell, sea sta↗
DOE OSTI2021

Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Additionally, extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 900 nearshore stations had an Optimum Hotspot Identifier value of 5 (kW/m) at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Selective bond formation triggered by short optical pulses: quantum dynamics of a four-center ring closure

Here we report bond formation induced by an ultrashort UV pulse. The photochemical process is described by quantum dynamics as coherent electronic and nuclear motions during the ultrashort pulse induced ring closure of norbornadiene to quadricyclane. Norbornadiene consists of two ethylene moieties connected by a rigid (CH 2 ) 3 bridge. Upon photoexcitation, two new sigma bonds are formed, resulting in the closure of a four-atom ring. As a medium-sized polyatomic molecule, norbornadiene exhibits a high density of strongly coupled electronic states from about 6 eV above the ground state. We report on inducing the formation of the new bonds using a short femtosecond UV pulse to pump a non-equilibrium electronic density in the open form that evolves towards the closed ring form. As the coherent electronic-nuclear coupled dynamics unfold, the excited states change character through non-adiabatic interactions and become valence states for the two new C–C bonds of quadricyclane. Our three-dimensional fully quantum dynamical grid simulations during the first 200 fs show that short UV pulses of different polarization initiate markedly different initial non-equilibrium electronic densities that follow different dynamical paths to the S 0 /S 1 conical intersection. They lead to different initial relative yields of quadricyclane, thereby opening the way to controlling bond-making with attopulses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

A NEW DENSITY VARIANCE-MACH NUMBER RELATION FOR SUBSONIC AND SUPERSONIC ISOTHERMAL TURBULENCE

The probability density function of the gas density in subsonic and supersonic, isothermal, driven turbulence is analyzed using a systematic set of hydrodynamical grid simulations with resolutions of up to 1024{sup 3} cells. We perform a series of numerical experiments with root-mean-square (rms) Mach number M ranging from the nearly incompressible, subsonic (M=0.1) to the highly compressible, supersonic (M=15) regime. We study the influence of two extreme cases for the driving mechanism by applying a purely solenoidal (divergence-free) and a purely compressive (curl-free) forcing field to drive the turbulence. We find that our measurements fit the linear relation between the rms Mach number and the standard deviation (std. dev.) of the density distribution in a wide range of Mach numbers, where the proportionality constant depends on the type of forcing. In addition, we propose a new linear relation between the std. dev. of the density distribution {sigma}{sub {rho}} and that of the velocity in compressible modes, i.e., the compressible component of the rms Mach number, M{sub comp}. In this relation the influence of the forcing is significantly reduced, suggesting a linear relation between {sigma}{sub {rho}} and M{sub comp}, independent of the forcing, and ranging from the subsonic to the supersonic regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Divertor leg filaments in NSTX-U

This study presents the first observation of divertor localized turbulence in the NSTX-Upgrade spherical tokamak. Previous work in NSTX discharges described fluctuations on the divertor target due to blobs generated on the low field side midplane. In the region that shows disconnection from upstream turbulence (private flux region and proximity of the strike point), divertor-localized fluctuations are observed via imaging of C III and D-α emission in diverted L-mode discharges and are characterized in this paper. Field-aligned filaments connected to the divertor target plate are radially localized at the separatrix on the outer divertor leg and in the private flux region on the inner divertor leg. These are limited to the region below the X-point with fluctuation levels up to 10%–20%. The filaments have comparable poloidal and radial correlation lengths (10–100 ion gyroradii ρ i ) and parallel correlation lengths of several meters. Toroidal mode numbers are in the range of 10–30 and 2–10 for outer and inner leg filaments. The poloidal motion of outer leg filaments has the same direction and comparable magnitude to advection due to E x B drift calculated by the multi-fluid edge transport code UEDGE with inclusion of cross field drifts. Disconnection between inner and outer leg filaments as well as the absence of correlation with upstream turbulence support the hypothesis of X-point disconnection for divertor leg filaments. Simulations with the ArbiTER linear eigenvalue solver and a resistive-balooning model were performed with a simulation grid limited to the divertor legs. Instabilities localized to the bad curvature side of the divertor legs were observed, in qualitative agreement with the experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System

Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and compressive sensing) that have been proposed recently to address the challenge of unobservability. The proposed approach exploits both the low rank structure and a suitable transform domain representation to leverage the correlation structure of the spatio-temporal data matrix while incorporating the powerflow constraints of the distribution grid. Simulations are carried out on three phase unbalanced IEEE 37 test system to verify the effectiveness of the proposed approach. The performance results reveal - (1) the superiority over traditional matrix completion and (2) very low state estimation errors for high compression ratios representing very low observability.

Dahale, Shweta↗
DOE OSTI2018

Integrated Transmission and Distribution Systems Restoration with Distributed Generation Scheduling

The self-healing smart grids enable system operators to quickly and efficiently recover transmission and distribution systems from outages and blackouts. The current restoration procedure solves the transmission and distribution system restoration problems separately without considering their impacts on each other, which may prolong the restoration process. However, with the emerging active distribution networks, distributed generators can contribute into the bottom-up restoration strategy. The interaction between the restoration of two interconnected systems should be taken into account. In this paper, a hybrid model of transmission and distribution systems restoration (HTDSR) is proposed by exchanging data of power and voltage between two separate optimization problems. The effectiveness of the HTDSR algorithm is demonstrated through case studies of the integrated IEEE 13-bus distribution network and IEEE 39-bus transmission grid. Simulation results demonstrate that the integrated restoration strategy with optimal scheduling of distributed generation sources can expedite the restoration process.

Distributed generation↗
DOE OSTI2017

Using a critical infrastructure game to provide realistic observation of the human in the loop by criminal justice students

Understanding human behavior is crucial in anticipating adversarial actions during cyberattacks. The Criminal Justice (CJ) discipline offers the necessary frameworks to unpack the complex facets of adversarial behavior and movement, and should therefore be leveraged for their possible contributions to the area of proactive cybersecurity. Yet the discipline remains weak at training current and future CJ workforce on these matters in a hands-on manner. This paper presents a cybersecurity training exercise where a power grid simulator is used to educate CJ students via experiential learning about concepts of cyberattacks and cybersecurity as well as exposing them to doing hands-on cybersecurity field research. The paper reports on Game use as an important opportunity to observe humans put under additional stress in operating conditions. The paper discusses what CJ students learn from multidisciplinary simulation-based exercises, the challenges and limitations they face, and how training this workforce could help contribute towards proactive cyberdefense of critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Cyber Framework for Steering and Measurements Collection Over Instrument-Computing Ecosystems

We propose a framework to develop cyber solutions to support the remote steering of science instruments and measurements collection over instrument-computing ecosystems. It is based on provisioning separate data and control connections at the network level, and developing software modules consisting of Python wrappers for instrument commands and Pyro server-client codes that make them available across the ecosystem network. We demonstrate automated measurement transfers and remote steering operations in a microscopy use case for materials research over an ecosystem of Nion microscopes and computing platforms connected over site networks. The proposed framework is currently under further refinement and being adopted to science workflows with automated remote experiments steering for autonomous chemistry laboratories and smart energy grid simulations.

Al Najjar, Anees↗
DOE OSTI2021

Sequence Impedance Measurement of Utility-Scale Wind Turbines and Inverters – Reference Frame, Frequency Coupling, and MIMO/SISO Forms

Sequence impedance responses with or without considering frequency coupling in both MIMO and SISO forms are increasingly used for the stability analysis of three-phase power electronic systems; however, many aspects of sequence impedance measurement are not fully explored. It is not clear if the sequence impedance has a reference frame similar to the dq impedance. If so, the role of the grid voltage angle estimation in aligning the sequence impedance reference frame has not been discussed. Additionally, existing methods for measuring the sequence impedance with frequency coupling are complicated, are not feasible for large wind turbines and inverters, and provide the sequence impedance responses in only either MIMO or SISO form. This paper presents a sequence impedance measurement method that considers the frequency coupling, performs reference frame alignment, demonstrates the impact of the grid voltage angle estimation, and obtains the sequence impedance response in both MIMO and SISO forms. This paper demonstrates the proposed method and practical problems associated with the sequence impedance measurement of utility-scale wind turbines and inverters on a 1.9-MW Type III wind turbine and a 2.2-MVA inverter using an impedance measurement system built around a 7-MW/13.8-kV grid simulator and a 5-MW dynamometer.

17 WIND ENERGY↗
DOE OSTI2017

smoothG

smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found

Barker, AndrewT.↗
DOE OSTI2013

Fundamental Drivers of the Cost and Price of Operating Reserves

Operating reserves impose a cost on the electric power system by forcing system operators to keep partially loaded spinning generators available for responding to system contingencies variable demand. In many regions of the United States, thermal power plants provide a large fraction of the operating reserve requirement. Alternative sources of operating reserves, such as demand response and energy storage, may provide more efficient sources of these reserves. However, to estimate the potential value of these services, the cost of reserve services under various grid conditions must first be established. This analysis used a commercial grid simulation tool to evaluate the cost and price of several operating reserve services, including spinning contingency reserves and upward regulation reserves. These reserve products were evaluated in a utility system in the western United States, considering different system flexibilities, renewable energy penetration, and other sensitivities. The analysis demonstrates that the price of operating reserves depend highly on many assumptions regarding the operational flexibility of the generation fleet, including ramp rates and the fraction of fleet available to provide reserves.

24 POWER TRANSMISSION AND DISTRIBUTION↗