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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Single-Phase Jet Impingement Cooling for a Power-Dense Silicon Carbide Power Module

The adoption of silicon carbide (SiC) devices in the electric vehicle (EV) industry is increasing due to their superior performance over silicon devices. SiC devices enable further miniaturization of EV inverters, increasing their power density, which results in thermal management challenges. Here in this paper, the limits of single-phase jet impingement cooling are explored for an automotive SiC power module. We propose embedding pin fins in the direct-bonded-copper (DBC) substrate of the power module package using laser powder bed fusion additive manufacturing. The thermalhydraulic performance of the DBC-embedded pin fins is compared against folded fins that are directly soldered to the DBC substrate. A heat conduction analysis was conducted on a SiC package to determine the target heat transfer coefficient (HTC) for the heat sink. A water-ethylene glycol (WEG) jet impingement on the proposed concepts was studied using unit-cell models to achieve the target HTC. The studied designs put emphasis on the reliability and manufacturability requirements of the automotive industry. The thermal performance of DBC-embedded pin fins outperformed the DBC-soldered folded fins. The performance of the DBC-embedded pin fins is benchmarked against WEG-based cooling systems of commercial EVs. With the proposed cooling solution, we have shown a pathway of reducing the specific thermal resistance by 75% compared to BMW i3 thermal management system without any penalty on pressure drop or parasitic power.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

EAGLE-I Power Outage Data 2025

The provided EAGLE-I historic dataset includes power outage information at the county level for 2025 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

EAGLE-I↗
DOE OSTI2022

Evaluating the Capabilities of Behind-the-Meter Solar-plus-Storage for Providing Backup Power during Long-Duration Power Interruptions [Slides]

The study estimates the performance of behind-the-meter solar PV-plus-energy-storage-systems (PVESS) in providing critical-load or whole-building backup across a wide range of geographies, building types, and power interruption conditions. The study also considers a set of 10 historical long-duration power outage events and evaluates how PVESS could have performed in providing backup power during those specific events. The analysis is the first in what will be a series of studies by Berkeley Lab, in collaboration with the National Renewable Energy Laboratory, on the use of PVESS for backup power. This initial study, which relies on simulated end-use level building loads, solar generation, and storage dispatch, is intended to provide a baseline set of performance estimates and to illustrate key performance drivers.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed Data-Driven Power Iteration for Strongly Connected Networks

Here, this paper presents data-driven power iteration to distributively estimate the dominant eigenvalues of an unknown linear time-invariant system. The proposed strategy only requires a single trajectory data or measurements. Furthermore, in order to perform the distributed estimation, the communication network topology can be chosen to be any strongly connected directed graphs. The proposed data-driven power iteration is demonstrated using several numerical examples and is then applied to estimate the generalized algebraic connectivity of cooperative systems and to control the epidemic spreading.

Gusrialdi, Azwirman↗
DOE OSTI2023

Developing an AI-Powered Zero-Trust Cybersecurity Framework for Malware Prevention in Nuclear Power Plants

This study presents the development of an AI-powered Zero-Trust cybersecurity framework for malware prevention in nuclear power plants. The framework aims to enhance the security of critical systems within nuclear power plants by adopting the principles of Zero-Trust and leveraging artificial intelligence (AI) technologies. By assuming no implicit trust in any user or device and continuously authenticating and authorizing access, the framework ensures a robust defense against malware attacks. The integration of AI allows for the detection and prevention of malware through behavioral analytics, endpoint protection, network segmentation, and continuous monitoring. The paper discusses the key considerations, steps, and technologies involved in developing this framework, emphasizing the importance of regular updates, training, compliance, and auditing. The proposed framework serves as a comprehensive approach to safeguarding nuclear power plants from sophisticated malware threats and protecting the integrity and safety of critical infrastructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Constraints on Λ CDM extensions from the SPT-3G 2018 $EE$ and $TE$ power spectra

Here, we present constraints on extensions to the Λ CDM cosmological model from measurements of the E-mode polarization autopower spectrum and the temperature-E-mode cross-power spectrum of the cosmic microwave background (CMB) made using 2018 SPT-3G data. The extensions considered vary the primordial helium abundance, the effective number of relativistic degrees of freedom, the sum of neutrino masses, the relativistic energy density and mass of a sterile neutrino, and the mean spatial curvature. We do not find clear evidence for any of these extensions, from either the SPT-3G 2018 dataset alone or in combination with baryon acoustic oscillation and Planck data. None of these model extensions significantly relax the tension between Hubble-constant, H 0 , constraints from the CMB and from distance-ladder measurements using Cepheids and supernovae. The addition of the SPT-3G 2018 data to Planck reduces the square-root of the determinants of the parameter covariance matrices by factors of 1.3–2.0 across these models, signaling a substantial reduction in the allowed parameter volume. We also explore CMB-based constraints on H 0 from combined SPT, Planck, and ACT DR4 datasets. While individual experiments see some indications of different H 0 values between the TT, TE, and EE spectra, the combined H 0 constraints are consistent between the three spectra. For the full combined datasets, we report H 0 = 67.49 ± 0.53 km s -1 Mpc -1 , which is the tightest constraint on H0 from CMB power spectra to date and in 4.1σ tension with the most precise distance-ladder-based measurement of H 0 . The SPT-3G survey is planned to continue through at least 2023, with existing maps of combined 2019 and 2020 data already having ~ 3.5 x lower noise than the maps used in this analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Power Electronic Hardware-in-the-Loop (PE-HIL): Testing Individual Controllers in Large-Scale Power Electronics Systems

Large power electronics systems like multi-port autonomous reconfigurable solar power plant (MARS) are increasingly being researched upon to integrate emerging energy sources. MARS connects photovoltaic (PV) systems and energy storage systems (ESSs) to high-voltage direct current (HVdc) links/grids and high-voltage alternating current (ac) transmission grids. As these large power electronics systems incorporate complex hierarchical control systems that are close-by and communicate fast, the control systems require an unique power electronic hardware-in-the-loop (PE-HIL) real-time architecture to evaluate individual controllers. In this paper, a PE-HIL real-time architecture is proposed to evaluate one of the hundreds to thousands of digital signal processors (DSPs) that are a part of the complex hierarchical control system. The DSP connects to a central processing unit (CPU) and a field programmable gate array (FPGA) that form a part of the upper levels of the control system. The DSP is part of the lower level of the control system. The proposed PE-HIL architecture is tested and evaluated. Preliminary test results are presented to showcase the concept.

Debnath, Suman↗
DOE OSTI2020

Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch

A significant difficulty associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DC optimal power flow problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique by simulating dispatch operations on a synthetic test system over the course of a week.

94 GMLC - Grid Modernization Laboratory Consortium↗
DOE OSTI2022

Characterizing particle-based thermal storage performance using optical methods for use in next generation concentrating solar power plants

Concentrating Solar Power (CSP) generation is an attractive option for low-emission power generation; however, the high costs of thermal storage associated with concentrating solar create a large barrier for their use and adaptation into modern life. Lowering their operation costs, while maintaining high thermal storage and transfer performance is essential. Solid particle-based heat exchange systems can reduce CSP cost but are often less efficient. Efforts to increase their performance have led to use of binary size particle mixes. Presented is an optical-based thermal analysis technique used to measure near-wall thermal conductivity of particle beds essential in determining their heat exchanger efficiency. Modulated Photothermal Radiometry is used to make dynamic temperature measurements, allowing for the extraction of the most relevant thermal properties like thermal conductivity, specific heat, and effusivity. The system uses a modulated laser source causing a damped periodic heat flux, resulting in a frequency and thermal property dependent surface temperature, of which is measured using radiometry. Lock-In techniques are used to extrapolate the amplitude of the signal. Plotting the amplitude against the root angular frequency allows for effusivity measurement by ratio to a known sample. Using specific heat measurements from literature and density measurements, the thermal conductivity of the particle mixes can be calculated. The simplicity of MPTR to probe through the depth of the bed is ideal for use in CSP for dynamic thermal performance monitoring.

Corona, Javier↗
DOE OSTI2021

Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch

A significant difficulty associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DC optimal power flow problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique by simulating dispatch operations on a synthetic test system over the course of a week.

analog forecast↗
DOE OSTI2024

Power capture and power take-off load of a self-balanced dual-flap oscillating surge wave energy converter

Wave energy converters are an important part of future renewable energy infrastructure. Predicting their power matrix, capture width ratio, and power take-off loads at a targeted site is required for performance assessment before deployment. Because their testing is very expensive, numerical modeling and simulations play a significant role in those assessments. Linear potential flow theory has limited accuracy under large amplitude wave forcing. More accurate predictions can be obtained by using higher-fidelity models, which are computationally expensive. We present a framework for multi-fidelity numerical simulations to determine the hydrodynamic response, wave capture capability, and power take-off load of a full-scale dual-flap oscillating surge wave energy converter. This design exploits out-of-phase motion by setting the distance between the flaps to half the wavelength of the most occurring wave. The simulations are validated using a 1:10 model experiments in a wave tank. Based on these validations, it was determined that Euler simulations provide an acceptable prediction with 90% reduction in computational time with only 11% error. Utilizing Euler simulations at full-scale, the results demonstrate that the annual electrical energy output is 1.79 GWh under regular wave conditions. Here, one significant improvement over single-flap designs is the capture width ratio which exceeds unity.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Small-Signal Stability Constrained Optimal Power Flow of Inverter-Dominated Power Systems with Flexible Operation Mode Selection

Given the intermittence and low inertia nature of inverter-based resources (IBRs), modern power systems with high penetration of IBRs challenge the conventional optimal power flow (OPF) analysis and the system may experience unexpected failures if stability constraints are not incorporated. This study proposes a small-signal stability-constrained OPF (SSSC-OPF) with flexible operation mode selection between grid-forming (GFM) and grid-following (GFL) modes for IBRs to address these challenges. The approach aims to maintain system stability with a sufficient stability margin while minimizing operation costs. The effectiveness of the proposed method is validated through extensive case studies on the IEEE 14-bus system. The results demonstrate that the proposed method is able to support system-level power flow analysis, reduce generation costs, and ensure stability under various disturbances.

grid-following↗
DOE OSTI2025

Evaluating the Impact of Power Outages on Occupancy Patterns During the 2021 Texas Power Crisis

Large-scale power outages, such as those caused by extreme weather events, have a big impact on human behavior. A short power outage is merely a nuisance for most, and may not change people's locations. An outage that lasts for a few hours can result in spoiled food and medical supplies, and people will have to restock spoiled items. Long outages result in temperatures outside tolerable levels in homes, and may prompt people to acquire supplies, such as generators and gas, or change location. The long outages during Winter Storm Uri in Texas resulted in millions of dollars in property damage due to freezing pipes. This level of damage is expected to result in a sharp increase in supply runs and contractor activity. In this paper, we present a tool to explore differences in visiting patterns before, during, and after power outages. It allows to compare different points of interest like medical facilities, grocery stores, hardware stores, and other types of businesses.

big data↗