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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 433 records · Page 24

Stratospheric Aerosol Injection Can Reduce Risks to Antarctic Ice Loss Depending on Injection Location and Amount

Owing to increasing greenhouse gas emissions, the Antarctic Ice Sheet is vulnerable to rapid ice loss in the upcoming decades and centuries. Here this study examines the effectiveness of using stratospheric aerosol injection (SAI) that minimizes global mean temperature (GMT) change to slow projected 21st century Antarctic ice loss. We simulate 11 different SAI cases which vary by the latitudinal location(s) and the amount(s) of the injection(s) to examine the climatic response near Antarctica in each case as compared to the reference climate at the turn of the last century. We demonstrate that injecting at a single latitude in the northern hemisphere or at the Equator increases Antarctic shelf ocean temperatures pertinent to ice shelf basal melt, while injecting only in the southern hemisphere minimizes this temperature change. We use these results to analyze the results of more complex multi-latitude injection strategies that maintain GMT at or below 1.5°C above the pre-industrial. All these multi-latitude cases will slow Antarctic ice loss relative to the mid-to-late 21st century SSP2-4.5 emissions pathway. Yet, to avoid a GMT threshold estimated by previous studies pertaining to rapid West Antarctic ice loss (1.5°C above the pre-industrial GMT, though large uncertainty), our study suggests SAI would need to cool about 1.0°C below this threshold and predominately inject at low southern hemisphere latitudes (~15°S - 30°S). These results highlight the complexity of factors impacting the Antarctic response to SAI and the critical role of the injection strategy in preventing future ice loss.

54 ENVIRONMENTAL SCIENCES↗

Statistical Modeling and Analysis of k -Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes

Two-dimensional layered materials/flakes, also known as crystalline atom-thick layer nanosheets, have recently been receiving great attention in electronics fabrication due to their unique and intriguing properties. The k-layer coverage area (i.e., the area covered by k number of overlapping layers) of the printed flake pattern significantly impacts on the properties of the printed electronics. In this work, we constructed a statistical model to describe the k-layer coverage of randomly distributed two-dimensional materials. A series of results are obtained to provide not only the expectation but also the variance of the coverage area. The boundary effects on the random flakes coverage are also studied. In addition, an approximated statistical testing approach is also developed in this work to detect abnormal coverage patterns. Furthermore, the case studies based on simulated data and real flakes images obtained from the inkjet printing process demonstrate the accuracy and effectiveness of the proposed model and analysis methods.

36 MATERIALS SCIENCE↗

Constructing a Simulation Surrogate with Partially Observed Output

Gaussian process surrogates are a popular alternative to directly using computationally expensive simulation models. When the simulation output consists of many responses, dimension-reduction techniques are often employed to construct these surrogates. However, surrogate methods with dimension reduction generally rely on complete output training data. This article proposes a new Gaussian process surrogate method that permits the use of partially observed output while remaining computationally efficient. The new method involves the imputation of missing values and the adjustment of the covariance matrix used for Gaussian process inference. The resulting surrogate represents the available responses, disregards the missing responses, and provides meaningful uncertainty quantification. In conclusion, the proposed approach is shown to offer sharper inference than alternatives in a simulation study and a case study where an energy density functional model that frequently returns incomplete output is calibrated.

42 ENGINEERING↗

Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data

In this paper, we propose a personalized Tucker decomposition (perTucker) to address the limitations of traditional tensor decomposition methods in capturing heterogeneity across different datasets. perTucker decomposes tensor data into shared global components and personalized local components. We introduce an order orthogonality assumption and develop a proximal gradient regularized block coordinate descent algorithm guaranteed to converge to a stationary point. The unique and common representations learned by perTucker reveal intrinsic statistical patterns in data and provide valuable information for a wide range of downstream analytics, including anomaly detection, source classification, and clustering. We demonstrate perTucker’s effectiveness through a simulation study and two case studies on solar flare detection and tonnage signal classification.

14 SOLAR ENERGY↗

Quantum algorithm for the linear Vlasov equation with collisions

The Vlasov equation is a nonlinear partial differential equation that provides a first-principles description of the dynamics of plasmas. Its linear limit is routinely used in plasma physics to investigate plasma oscillations and stability. In this paper, we present a quantum algorithm that simulates the linearized Vlasov equation with and without collisions, in the one-dimensional electrostatic limit. Rather than solving this equation in its native spatial and velocity phase space, we adopt an efficient representation in the dual space yielded by a Fourier-Hermite expansion. For a given simulation time, the Fourier-Hermite representation is exponentially more compact, thus yielding a classical algorithm that can match the performance of a previously proposed quantum algorithm for this problem. Further, this representation results in a system of linear ordinary differential equations (ODEs) which can be solved with well-developed quantum algorithms: a Hamiltonian simulation in the collisionless case, and quantum ODE solvers in the collisional case. In particular, we demonstrate that a quadratic speedup in system size is attainable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Towards a classification of bifurcations in Vlasov equations

Here, we propose a classification of bifurcations of Vlasov equations, based on the strength of the resonance between the unstable mode and the continuous spectrum on the imaginary axis. We then identify and characterize a new type of generic bifurcation where this resonance is weak, but the unstable mode couples with a stable mode and a Casimir invariant of the system to form a size-3 Jordan block. We derive a three-dimensional reduced noncanonical Hamiltonian system describing this bifurcation. Comparison of the reduced dynamics with direct numerical simulations on a test case gives excellent agreement. We finally discuss the relevance of this bifurcation to specific physical situations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Self-Organizing Nano Grid (SONG) for Energy Access Clusters

In this paper, a bottom-up dc Self-Organizing Nano Grid (SONG) for rural electrification at ultra-low-cost through a flexible and scalable topology is presented. The proposed nano grid requires no communication and uses dc-bus signaling to convey excess energy in the system through the bus voltage, allowing independent agents to conduct energy transactions based on their needs in a decentralized manner. Moreover, this article proposes a concept that uses a novel multi-source, multi-segment droop control strategy with demand coordination, allowing for dynamic self-balancing of the system under fluctuating operating conditions. The unique use of a surplus photovoltaic (PV) power droop mode precisely estimates energy availability to minimize load chattering that helps in stabilizing the dc-bus. In addition, this architecture uses standard dc/dc converters for a low-cost, modular, Plug and Play ( PnP ) solution with highly automated operation, enabling local assembly, operation, and maintenance by non-technical personnel. The proposed SONG concept was validated in simulation and with a 700W, laboratory-scale, custom made nano grid system. The simulation and experimental test cases show the feasibility of the SONG system by demonstrating the proposed multi-source, multi-segment droop control strategy without load chattering under varying operating conditions.

dc-dc converter↗

Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration

This paper presents an innovative wave energy conversion system that integrates an interleaved Cuk converter with advanced nonlinear control for seamless grid integration. The system efficiently extracts power on the DC side using the interleaved Cuk converter, while an inverter manages power transfer to the grid or load on the AC side. A nonlinear control architecture, based on the Lyapunov energy function, ensures stable and optimal operation under varying wave conditions, effectively addressing the challenges of variability and unpredictability inherent in wave energy. The proposed system also incorporates features to enhance power quality and minimize losses, making it a robust solution for renewable energy integration. The system's effectiveness in harnessing wave energy and achieving smooth grid integration is validated through comprehensive computer simulations in MATLAB/Simulink, with case study results demonstrating its capabilities.

HYDRO ENERGY,TIDAL AND WAVE POWER↗

Oscillatory Power Control and Consensus in Unbalanced Networks Using Grid Forming Inverters

In this paper, a state-space nonlinear control previously designed for balanced operation of grid-forming (GFM) inverters is extended to unbalanced operations. Unbalanced voltages and currents are analyzed, and their time-varying direct, quadrature, and zero components are parameterized in terms of six constant parameters. These parameters provide primary control design choices for not only an inverter’s terminal voltage but also its injections of both real and oscillatory power. It is shown that the proposed GFM control can precisely achieve a desired balanced terminal voltage under unbalanced loads. It is also shown that, by allowing the terminal voltage to be slightly unbalanced, oscillatory power can be adaptively minimized. Lastly, it is illustrated that oscillatory power can also be shared among multiple GFM inverters. Case studies and their simulations demonstrate that the proposed GFM control is effective in meeting the aforementioned objectives.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Nonintrusive Optical Approach to Characterize Heliostats in Utility-Scale Power Tower Plants: Camera Position Sensitivity Analysis

Optics plays a major role in the effectiveness of concentrating solar power (CSP) technologies. The nonintrusive optical (NIO) approach developed by the National Renewable Energy Laboratory uses uncrewed aircraft system (UAS)-based imaging to survey heliostats in a commercial-scale power tower CSP plant and characterize their optical errors. The image processing algorithm uses photogrammetry to calculate the camera position for each image frame, and the accuracy of the estimated optical errors is highly sensitive to the calculated camera position accuracy. In this study, we simulate a series of case studies in python to examine the impact of different parameters of the sensitivity of the camera calculation, including the number of facet corners used as control points for the photogrammetric calculation, precision error in the detected pixel locations of the facet corners in the image, and precision error of the canting and mounting positions of the facets of the heliostat. The case studies consider heliostat geometry based on three commercial designs to serve as representative examples of different possible sizes of heliostats that the NIO method could be applied to. The results show that increasing the number of control points can improve accuracy for heliostats with many facets, pixel precision has a significantly larger impact on camera calculation accuracy than facet canting and mounting errors, and the camera distance and focal length must be chosen to ensure adequate pixel accuracy on the heliostat surface depending on the size of heliostat. In conclusion, based on the results, recommendations for the allowable values of each parameter are provided to achieve the required NIO optical error estimation accuracy depending on the size of heliostat.

14 SOLAR ENERGY↗

Resilient State Recovery Using Prior Measurement Support Information

Resilient state recovery of cyber-physical systems has attracted much research attention due to the unique challenges posed by the tight coupling between communication, computation, and the underlying physics of such systems. By modeling attacks as additive adversary signals to a sparse subset of measurements, this resilient recovery problem can be formulated as an error correction problem. To achieve exact state recovery, most existing results require less than 50% of the measurement nodes to be compromised, which limits the resiliency of the estimators. In this paper, we show that observer resiliency can be further improved by incorporating data-driven prior information. Here, we provide an analytical bridge between the precision of prior information and the resiliency of the estimator. By quantifying the relationship between the estimation error of the weighted ℓ 1 observer and the precision of the support prior, this quantified relationship provides guidance for the estimator’s weight design to achieve optimal resiliency. Several numerical simulations and an application case study are presented to validate the theoretical claims.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗

Scalable Interpolation on GPUs for Thermal Fluids Applications

The need for efficient interpolation arises in many use cases for spectral element simulations. Towards this end, we present a fast and robust GPU-enable interpolation utility for NekRS, a spectral-element, Navier-Stokes solver. This utility is based on the findpts and findpts eval routines from the gslib library. To demonstrate the functionality, we added support for particle tracking. The GPU implementation of the interpolation allows for tracking 100 times more particles for the same computational cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Contaminant Transport Simulation with the P2R Model for the Composite Analysis Base Case

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The updated Hanford CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within and downgradient of the Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Designing SOC electrodes for better lifetime performance

Presentation for talk at the 2024 Pacific Rim Meeting of the Electrochemical Society October 6-11, 2024. The talk covers a review of NETL's solid oxide cell (SOC) performance degradation modeling framework and present case studies on how simulations are used to design better SOC electrodes.

Abernathy, Harry↗

Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids

The OPEN COG Grid project is a collaborative effort between LLNL, NREL, and Texas A&M University (TAMU) to develop synthetic power system datasets that (i) contain all technical information that would be available in a real system, allowing to conduct studies ranging from dynamic simulation to long term planning studies; ii) are accessible to researchers from the broader data sciences community, as oppossed to power system experts only; and (iii) This report summarizes the work conducted during the first 15 months of execution of the project. These activities encompassed: 1. Conduct a survey of existing open data sets and open source power systems simulators, their supported use cases, and accessibility (Chapter 1). 2. Define a new extensible specification for power system data, covering all parameters necessary for most computational use cases (Chapter 2). 3. Collecting real technical system data to complete missing parameters in existing open source datasets (Chapter 3). 4. Develop models that capture the behavior of emergent actors in power grids, neglected by existing datasets; aggregated residential demand response (Chapter 4) and demand response of cryptocurrency miners (Chapter 5). 5. Collect detailed spatial information on distributed energy resources, particular, solar photovoltaic facilities (Chapter 6). The following chapters provide detailed descriptions of these tasks, the assumptions taken, and their findings. In conducting these tasks, the project team produced: two (ac&#x2;cepted) conference papers; one journal paper under submission; one draft journal paper pending submission; released one repository with the developed power system data specifi&#x2;cation, with documentation and examples; and one extended dataset for the Texas power grid under review for release. The team hopes these contributions will enhance access to power system data and remove barriers to the development of new computational techniques for power systems, particularly, those inspired by cognitive sciences.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Creation of a Weather Drivers Test Suite for Inclusion in ASHRAE Standard 140

Weather conditions are an important boundary condition for building performance simulation (BPS) calculations. For existing test cases in ASHRAE Standard 140 "Method of Test for Evaluating Building Performance Simulation Software" (ANSI/ASHRAE 2020), it was assumed that the software being tested could adequately read and interpret the weather data in the provided standard weather files. As differences between the programs have been reduced and as more programs have shifted to sub-hourly time steps this assumption has become more stretched. To address these concerns a new test suite testing a program's ability to read and interpret the data from a standard weather file was developed. The purpose of the test suite is to test the use of the typical data used from standard weather files.

54 ENVIRONMENTAL SCIENCES↗

The inviscid incompressible limit of Kelvin–Helmholtz instability for plasmas

The Kelvin–Helmholtz Instability (KHI) is an interface instability that develops between two fluids or plasmas flowing with a common shear layer. KHI occurs in astrophysical jets, solar atmosphere, solar flows, cometary tails, planetary magnetospheres. Two applications of interest, encompassing both space and fusion applications, drive this study: KHI formation at the outer flanks of the Earth’s magnetosphere and KHI growth from non-uniform laser heating in magnetized direct-drive implosion experiments. Here, we study 2D KHI with or without a magnetic field parallel to the flow. We use both the GAMERA code, which solves the compressible Euler equations, and the STRATOSPEC code, which solves the Navier-Stokes equations under the Boussinesq approximation, coupled with the magnetic field dynamics. GAMERA is a global three-dimensional MHD code with high-order reconstruction in arbitrary nonorthogonal curvilinear coordinates, which is developed for a large range of astrophysical applications. STRATOSPEC is a three-dimensional pseudo-spectral code with an accuracy of infinite order (no numerical diffusion). Magnetized KHI is a canonical case for benchmarking hydrocode simulations with extended MHD options. An objective is to assess whether or not, and under which conditions, the incompressibility hypothesis allows to describe a dynamic compressible system. For comparing both codes, we reach the inviscid incompressible regime, by decreasing the Mach number in GAMERA, and viscosity and diffusion in STRATOSPEC. Here, we specifically investigate both single-mode and multi-mode initial perturbations, either with or without magnetic field parallel to the flow. The method relies on comparisons of the density fields, 1D profiles of physical quantities averaged along the flow direction, and scale-by-scale spectral densities. We also address the triggering, formation and damping of filamentary structures under varying Mach number or Atwood number, with or without a parallel magnetic field. Comparisons show very satisfactory results between the two codes. The vortices dynamics is well reproduced, along with the breaking or damping of small-scale structures. We end with the extraction of growth rates of magnetized KHI from the compressible regime to the incompressible limit in the linear regime assessing the effects of compressibility under increasing magnetic field. The observed differences between the two codes are explained either from diffusion or non-Boussinesq effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗