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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 325 records · Page 18

Ground Simulator Studies of the Effects of Valve Friction, Stick Friction, Flexibility, and Backwash on Power Control System Quality

Report presents results of tests made on a power control system by means of a ground simulator to determine the effects of various combinations of valve friction and stick friction on the ability of the pilot to control the system. Various friction conditions were simulated with a rigid control system, a flexible system, and a rigid system having some backlash. For the tests, the period and damping of the simulated airplane were held constant.

Brown, B Porter↗

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Neutrino transport in general relativistic neutron star merger simulations

Abstract Numerical simulations of neutron star–neutron star and neutron star–black hole binaries play an important role in our ability to model gravitational-wave and electromagnetic signals powered by these systems. These simulations have to take into account a wide range of physical processes including general relativity, magnetohydrodynamics, and neutrino radiation transport. The latter is particularly important in order to understand the properties of the matter ejected by many mergers, the optical/infrared signals powered by nuclear reactions in the ejecta, and the contribution of that ejecta to astrophysical nucleosynthesis. However, accurate evolutions of the neutrino transport equations that include all relevant physical processes remain beyond our current reach. In this review, I will discuss the current state of neutrino modeling in general relativistic simulations of neutron star mergers and of their post-merger remnants. I will focus on the three main types of algorithms used in simulations so far: leakage, moments, and Monte-Carlo scheme. I will review the advantages and limitations of each scheme, as well as the various neutrino–matter interactions that should be included in simulations. We will see that the quality of the treatment of neutrinos in merger simulations has greatly increased over the last decade, but also that many potentially important interactions remain difficult to take into account in simulations (pair annihilation, oscillations, inelastic scattering).

Foucart, Francois (ORCID:0000000346174738)↗

Solar Dynamic Power System Fault Diagnosis

The objective of this research is to conduct various fault simulation studies for diagnosing the type and location of faults in the power distribution system. Different types of faults are simulated at different locations within the distribution system and the faulted waveforms are monitored at measurable nodes such as at the output of the DDCU's. These fault signatures are processed using feature extractors such as FFT and wavelet transforms. The extracted features are fed to a clustering based neural network for training and subsequent testing using previously unseen data. Different load models consisting of constant impedance and constant power are used for the loads. Open circuit faults and short circuit faults are studied. It is concluded from present studies that using features extracted from wavelet transforms give better success rates during ANN testing. The trained ANN's are capable of diagnosing fault types and approximate locations in the solar dynamic power distribution system.

Momoh, James A.↗

MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and Testing of a Vehicle Management System for Autonomous Spacecraft Habitat Operations

As the increased distance between Earth-based mission control and the spacecraft results in increasing communication delays, small crews cannot take on all functions performed by ground today, and so vehicles must be more automated to reduce the crew workload for such missions. In addition, both near-term and future missions will feature significant periods when crew is not present, meaning the vehicles will need to operate themselves autonomously. NASA's Advanced Exploration Systems Program pioneers new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond low-Earth orbit. Under this program, NASA has developed and demonstrated multiple technologies to enable the autonomous operation of a dormant space habitat. These technologies included a fault-tolerant avionics architecture, novel spacecraft power system and power system controller, and autonomy software to control the habitat. The demonstration involved simulation of the habitat and multiple spacecraft sub-systems (power storage and distribution, avionics, and air-side life-support) during a multi-day test at NASA's Johnson Space Center. The foundation of the demonstration was ‘quiescent operations' of a habitat during a 55 minute eclipse period. For this demonstration, the spacecraft power distribution system and air-side life support system were simulated at a high level of fidelity; additional systems were managed, but with lower fidelity operational constraints and system behavior. Operational constraints for real and simulated loads were developed by analyzing on-orbit hardware and evaluating future Exploration capable technology. A total of 13 real and simulated loads were used during the test. Eight scenarios including both nominal and off-nominal conditions were performed. Over the course of the test, every application performed its desired functions successfully during the simulated tests. The results will inform both future tests, as well as provide insight to NASA's domestic and international partners, as they construct the next generation of space habitats to be used on beyond-Earth missions.

Autonomous Systems and Operations↗

Design and Build of Reactor Simulator for Fission Surface Power Technology Demonstrator Unit

The Nuclear Systems Team at NASA Marshall Space Flight Center (MSFC) focuses on technology development for state of the art capability in non-nuclear testing of nuclear system and Space Nuclear Power for fission reactor systems for lunar and Mars surface power generation as well as radioisotope power systems for both spacecraft and surface applications. Currently being designed and developed is a reactor simulator (RxSim) for incorporation into the Technology Demonstrator Unit (TDU) for the Fission Surface Power System (FSPS) Program, which is supported by multiple national laboratories and NASA centers. The ultimate purpose of the RxSim is to provide heated NaK to a pair of Stirling engines in the TDU. The RxSim includes many different systems, components, and instrumentation that have been developed at MSFC while working with pumped NaK systems and in partnership with the national laboratories and NASA centers. The main components of the RxSim are a core, a pump, a heat exchanger (to mimic the thermal load of the Stirling engines), and a flow meter for tests at MSFC. When tested at NASA Glenn Research Center (GRC) the heat exchanger will be replaced with a Stirling power conversion engine. Additional components include storage reservoirs, expansion volumes, overflow catch tanks, safety and support hardware, instrumentation (temperature, pressure, flow) for data collection, and power supplies. This paper will discuss the design and current build status of the RxSim for delivery to GRC in early 2012.

Godfroy, Thomas↗

An Implanted, Stimulated Muscle Powered Piezoelectric Generator

A totally implantable piezoelectric generator system able to harness power from electrically activated muscle could be used to augment the power systems of implanted medical devices, such as neural prostheses, by reducing the number of battery replacement surgeries or by allowing periods of untethered functionality. The features of our generator design are no moving parts and the use of a portion of the generated power for system operation and regulation. A software model of the system has been developed and simulations have been performed to predict the output power as the system parameters were varied within their constraints. Mechanical forces that mimic muscle forces have been experimentally applied to a piezoelectric generator to verify the accuracy of the simulations and to explore losses due to mechanical coupling. Depending on the selection of system parameters, software simulations predict that this generator concept can generate up to approximately 700 W of power, which is greater than the power necessary to drive the generator, conservatively estimated to be 50 W. These results suggest that this concept has the potential to be an implantable, self-replenishing power source and further investigation is underway.

Lewandowski, Beth↗

A digital computer simulation and study of a direct-energy-transfer power-conditioning system

An investigation of the behavior of the power-conditioning system as a whole is a necessity to ensure the integrity of the aggregate system in the case of space applications. An approach for conducting such an investigation is considered. A description is given of the application of a general digital analog simulator program to the study of an aggregate power-conditioning system which is being developed for use on the International Ultraviolet Explorer spacecraft. The function of the direct energy transfer system studied involves a coupling of a solar array through a main distribution bus to the spacecraft electrical loads.

Burns, W. W., III↗

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Numerical simulation of the actuation system for the ALDF's propulsion control valve

A numerical simulation of the actuation system for the propulsion control valve (PCV) of the NASA Langley Aircraft Landing Dynamics Facility was developed during the preliminary design of the PCV and used throughout the entire project. The simulation is based on a predictive model of the PCV which is used to evaluate and design the actuation system. The PCV controls a 1.7 million-pound thrust water jet used in propelling a 108,000-pound test carriage. The PCV can open and close in 0.300 second and deliver over 9,000 gallons of water per sec at pressures up to 3150 psi. The numerical simulation results are used to predict transient performance and valve opening characteristics, specify the hydraulic control system, define transient loadings on components, and evaluate failure modes. The mathematical model used for numerically simulating the mechanical fluid power system is described, and numerical results are demonstrated for a typical opening and closing cycle of the PCV. A summary is then given on how the model is used in the design process.

Korte, John J.↗

An Integrated Transmission-Distribution Co-Simulation for a Distribution System with High Renewable Penetration

Traditionally, transmission and distribution system dynamic simulations are performed independently. However, dynamic co-simulation of transmission-distribution systems can be beneficial in analyzing distribution systems with high penetration of distributed renewable resources. The authors describe a framework for conducting transmission-distribution dynamic co-simulation (TDDS). A model of a real network including detailed models of solar photovoltaic units in the distribution system is constructed. The initial operating point of the network is validated against field measurements. The TDDS tool is used to simulate a single line-to-ground fault on the distribution system, highlighting the need for conducting transmission-distribution co-simulations.

14 SOLAR ENERGY↗

DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]

Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.

Sahu, Abhijeet↗

A Fully Decentralized Modulation Scheme for Modular Multilevel Converters

As the number of submodules rapidly increase, control architecture of Modular Multilevel Converters (MMCs) is transforming from centralized to distributed in order to address the challenges of tremendous computational burden and massive wiring. In this digest, we propose a modulation scheme for the MMCs with distributed controls, where each submodule is able to handle both controls and modulation in a decentralized manner. It enables the distributed controllers to synchronize in terms of fast-switching pulse width modulation (PWM). Aiming at this key technical challenge, this research develops a physics-informed PWM control strategy of mirroring the spontaneous synchronization feature of coupled oscillator’s behavior at switching frequency. Thanks to less reliance on wirings and communications, the proposed approach has the potential of i) improving reliability of MMC systems, and ii) reducing cost and space requirements for MMCs. The proposed approach has been preliminarily verified through a simulation tool for power electronics systems.

Lu, Minghui [BATTELLE (PACIFIC NW LAB)]↗

Test Results from a Direct Drive Gas Reactor Simulator Coupled to a Brayton Power Conversion Unit

Component level testing of power conversion units proposed for use in fission surface power systems has typically been done using relatively simple electric heaters for thermal input. These heaters do not adequately represent the geometry or response of proposed reactors. As testing of fission surface power systems transitions from the component level to the system level it becomes necessary to more accurately replicate these reactors using reactor simulators. The Direct Drive Gas-Brayton Power Conversion Unit test activity at the NASA Glenn Research Center integrates a reactor simulator with an existing Brayton test rig. The response of the reactor simulator to a change in Brayton shaft speed is shown as well as the response of the Brayton to an insertion of reactivity, corresponding to a drum reconfiguration. The lessons learned from these tests can be used to improve the design of future reactor simulators which can be used in system level fission surface power tests.

Hervol, David S.↗

Phase change energy storage for solar dynamic power systems

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Chiaramonte, F. P.↗

A machine learning-based fast frequency response control for a VSC-HVDC system

An HVDC system can realize a very fast frequency response to the disturbed system under a contingency because its active power control is decoupled from the frequency deviation. However, most of existing HVDC frequency control strategies are coupled with system primary frequency control and secondary frequency control. Since the traditional system frequency control is dominated by the thermal generators, the advantage of the fast response of the HVDC system is not made fully used. The development of a frequency response estimation based on a machine learning algorithm provides another approach to improve the frequency response capability of the HVDC system. Different from other frequency deviation tracking strategies, a machine learning based HVDC frequency response control can directly increase the power flow of a HVDC system by estimation of the system generator or load lost. In this paper, a fast frequency response control using a HVDC system for a large power system disturbance based on the multivariate random forest regression (MRFR) algorithm is proposed. The simulation is carried out with an integrated power system model based on the North American interconnections. The simulation results indicate that the proposed MRFR based frequency response control can significantly improve the frequency low point during an event, while stabilizing the frequency in advance.

42 ENGINEERING↗