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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 703 records · Page 39

Space platform power system hardware testbed

The scope of the work on the NASA Space Platform includes the design of a multi-module, multi-phase boost regulator, and a voltage-fed, push-pull autotransformer converter for the battery discharger. A buck converter was designed for the charge regulator. Also included is the associated mode control electronics for the charger and discharger, as well as continued development of a comprehensive modeling and simulation tool for the system. The design of the multi-module boost converter is discussed for use as a battery discharger. An alternative battery discharger design is discussed using a voltage-fed, push-pull autotransformer converter. The design of the charge regulator is explained using a simple buck converter. The design of the mode controller and effects of locating the bus filter capacitor bank 20 feet away from the power ORU are discussed. A brief discussion of some alternative topologies for battery charging and discharging is included. The power system modeling is described.

Sable, D.↗

Microwave dielectric properties of LiNbO$_{\mathbf{3}}$ and AlN at millikelvin temperatures and single-photon power

Electro-optic materials are paramount to achieving efficient and reliable microwave-optical signal transduction in the quantum regime. It is of great interest to investigate the performance of these materials at the quantum level and at cryogenic temperatures to assess their compatibility with superconducting circuit-based quantum systems. In this work, we present a detailed study of the microwave electric properties of single-crystal bulk LiNbO$_{3}$ and AlN at millikelvin temperatures and at the single-photon level. We characterize the materials' dielectric loss tangent throughout a wide range of electromagnetic power levels in a temperature range from a few tens of millikelvin to above 1~K. Our findings indicate that both materials' loss tangent behavior is consistent with the two-level system model up to a certain power threshold, beyond which it increases logarithmically with power. This suggests that two-level system loss mechanisms dominate at the single-photon level, while additional loss channels become relevant at higher powers and temperatures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Develop and test fuel cell powered on-site integrated total energy system. Phase 3: Full-scale power plant development

An integrated 5 kW power system based upon methanol fuel and a phosphoric acid fuel cell operating at about 473 K is described. Description includes test results of advanced fuel cell catalysts, a semiautomatic acid replenishment system and a completed 5 kW methanol/system reformer. The results of a preliminary system test on a reformer/stack/inverter combination are reported. An initial design for a 25 kW stack is presented. Experimental plans are outlined for data acquisition necessary for design of a 50 kW methanol/steam reformer. Activities related to complete mathematical modelling of the integrated power system, including wasteheat utilization, are described.

Kaufman, A.↗

Network-cognizant voltage droop control

The present disclosure provides techniques for network-cognizant droop control in power systems, such as a power distribution system. An example device includes a processor configured to determine, based on (i) a model representing a structure of a power system that includes a plurality of energy resources and (ii) an indication of predicted uncontrollable power injections in the power system, for each controllable energy resource in the plurality of energy resources, a respective value of a first droop coefficient and a respective value of a second droop coefficient. The processor may be further configured to cause at least one controllable energy resource in the plurality of energy resources to modify an output power of the at least one energy resource based on the respective value of the first droop coefficient and the respective value of the second droop coefficient.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗

Component-level Performance and Mass Sensitivity Analysis of NEP MW-class Power System

Nuclear electric propulsion (NEP) is a promising option towards enabling missions to Mars and is an area of interest for NASA’s Space Nuclear Propulsion project. This project is currently investigating technology development opportunities for an NEP vehicle. Physics-based modeling can be used in the early stages of technology development to gain understanding of the effects of technology and performance assumptions on the system performance and mass. This information can then inform technology maturation planning for near term development. By using a Brayton power conversion model and vehicle mass model for megawatt class NEP applications, a sensitivity analysis is performed to assess the impact of individual components’ performance on the power conversion system performance and system mass. A Monte Carlo simulation is also used to determine the variability in system mass based on uncertainty within the modeling parameters. The sensitivity analysis shows a high sensitivity to power conversion inlet temperature, compressor inlet temperature, and recuperator performance. A Monte Carlo analysis suggests a range of -10% to +15% for a 90% confidence interval on system mass based on the uncertainties in the model inputs.

Nuclear electric propulsion↗

NEP power subsystem modeling

The Nuclear Electric Propulsion (NEP) system optimization code consists of a master module and various submodules. Each of the submodules represents a subsystem within the total NEP power system. The master module sends commands and input data to each of the submodules and receives output data back. Rocketdyne was responsible for preparing submodules for the power conversion (both K-Rankine and Brayton), heat rejection, and power management and distribution.

Harty, Richard B.↗

Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications

A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.

42 ENGINEERING↗

Thermal Design Challenges for In-Flight Exposure to an Electric Propulsion Plasma Plume Environment

The use of electric propulsion to carry out NASA in-space propulsion demands has been increasing. A big part of fulfilling this demand is the Power and Propulsion Element (PPE) for NASA's Lunar Gateway. When built, the PPE will have the largest electric propulsion system to ever fly on a spacecraft, which brings new and difficult challenges. The environment created by the electric propulsion system during on-orbit operation of the thrusters has been shown to be different than those measured during operation in terrestrial vacuum facilities. Understanding the on-orbit environment created by the thrusters and its impacts on the spacecraft is the goal of the Plasma Diagnostic Package (PDP). The PDP is a sensor package, which is being developed by NASA GRC (Glenn Research Center), to fly on the PPE. The PDP will measure different aspects of the thruster plume in order to develop higher fidelity modeling of EP (Electric Power) systems. In order to capture quality measurements of the plume the PDP will need to install sensors in close proximity of it. This poses several unique thermal design challenges. Some of these challenges include: the long duration exposure to plume induced heating, the effects of plume induced erosion and sputter deposition on thermal control surfaces, and the extreme environments of a cis-lunar orbit. This paper looks to define the thermal challenges, explain modeling techniques, and offer design solutions for unique challenges of the PDP mission.

Thermal↗

Hydropower operation in future power grid with various renewable power integration

Hydropower generation may play an increasingly important role in the power grid under increasing contribution of variable renewable sources such as wind and solar. An improved understanding of the changes to hydropower dispatch under future higher VRE grid conditions reveals research gap that should be informed power grid planning and reservoir water releases policies considering multiple other water uses and varying hydrologic condition. Here this study aims to understand the role of hydropower in a changing power grid by employing a production cost model, PLEXOS, across future power system scenarios, planning horizons, and regions. We explore optimized hydropower dispatch to understand its potential role in minimizing the system cost and renewable curtailment. We also examine the sensitivity of hydropower revenue under various grid scenarios of the Eastern U.S. and hydrology conditions. Results indicate hydropower generation follows net load and compensates for the variability of solar and wind generation. Although energy prices are lower during some periods in the future grid scenarios, there is a potential for higher revenue for hydropower by providing both energy and ancillary services during times of stress. Additionally, hydropower revenue is sensitive to hydrology in the SERC region, which we considered as an example. The feasibility of hydropower dispatching with higher ramps between low and high hourly-capacity factors, as indicated in the optimization model, requires further study to consider other water use and ecology constraints.

13 HYDRO ENERGY↗

GRIDAPPSD/distopf (33583-E)

DistOPF is an open-source Python package providing a three-phase, asymmetric optimal power flow (OPF) tool specifically designed for distribution systems. The key inventive features include: - Asymmetrical 3-phase OPF modeling for distribution systems with unbalanced phases - Comprehensive control optimization supporting both active (P) and reactive (Q) power control variables - Built-in visualization and validation tools - Standard test system benchmarking platform for algorithm development and comparison - Modular CSV-based input system using Pandas DataFrames for flexible model specification - Standard power distribution model importer enabling direct conversion from CIM and OpenDSS format to optimization-ready models - Multiple solve interface compatibility (PYOMO, CVXPY, SciPy) with automatic solver selection based on problem type

Gray, Nathan [Pacific Northwest National Laborator↗

Influence of the air-cooled supercritical carbon dioxide recompression cycle design-point on molten salt power tower techno-economic performance

Here, this paper investigates the techno-economic performance of a molten salt power tower integrated with an air-cooled supercritical carbon dioxide recompression cycle. Prior research into the cycle design point showed trade-offs between efficiency, cost, and temperature difference across the heat input, resulting in trade-offs between the design-point generation of the molten salt power tower system and the cost of sensible-heat thermal energy storage. Prior research into cycle off-design showed that colder ambient temperature designs have higher efficiencies on cold days but lower efficiency and capacity degradation on hot days. We present a framework to evaluate how cycle design, cost, and corresponding off-design performance affect the techno-economic performance of the molten salt power tower system. We use a steady-state off-design cycle model assuming fixed shaft speeds, inventory control, and air-cooler fan power control and integrate the cycle model with the molten salt power tower model from the National Renewable Energy Laboratory's System Advisor Model. First, we present a surrogate model that uses a heuristic approach to correct the interpolation when the cycle reaches capacity limitations at ambient temperatures hotter than design. Next, we evaluate how the recompression cycle design-point ambient temperature, air-cooler approach temperature, air-cooler fan power, and recuperator conductance influence cycle and system design metrics. Finally, we complete annual simulations using an hourly "duck curve" pricing schedule and present annual performance metrics to evaluate the cumulative effects of the cycle design parameters and corresponding off-design performance on molten salt power tower techno-economics.

14 SOLAR ENERGY↗

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Tao, Wei-Kuo↗

Electrical Transmission on the Lunar Surface: DC Transmission - Part 1

This report summarizes a portion of the results from a grant at Auburn University to study the electrical and thermal energy management for lunar facilities. Over the past year (June 1989 to May 1990) the following topics have been investigated: June 1989 to November 1989 - Literature survey, assessment of lunar power needs, and overview study of the requirements of a lunar power system; November 1989 to April 1990 - Develop models for the study of dc electrical power transmission lines for the lunar surface; March 1990 to May 1990 - Develop models for the study of ac electrical power transmission lines for the lunar surface. Because of the large amount of information in the model development and application to a wide parameter space this report is being bound separately. This report specifically contains the model development and parameter study for dc electrical power transmission lines. The end of the funding year (May 1990) will conclude with an annual report including the literature survey, the overview of the requirements of a lunar power system, and summaries of the dc and ac models of electrical transmission lines.

Gordon, Lloyd B.↗

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Momoh, J. A.↗