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At least 307 records · Page 17

Surface enhanced performance of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ cathodes by infiltration Pr-Ni-Mn-O progress

Herein the present study reports the enhancement of electrochemical oxygen reduction activity of porous La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (LSCF) cathodes by coating a thin film of Pr-Ni-Mn oxide (PNM5) using a multi-step infiltration process. XRD examination reveals that PNM5 mainly contains a multiphase mixture of Pr 6 O 11 , PrNiO 3 , MnO and NiO. SEM morphology shows a thin PNM5 film and small particles are formed on the surface of LSCF backbone particles. Impedance spectrum analysis indicates that PNM5 infiltrated LSCF exhibits dramatically reduced polarization resistance (R p ), reaching R p of 0.244 Ω cm 2 at 973 K, which is one-half of the baseline LSCF cathode. The activation energy of LSCF cathodes infiltrated with PNM5 is 1.45 eV, slightly lower than the baseline LSCF cathode (1.77 eV). Distribution of relaxation time (DRT) function analysis shows PNM5 infiltration layer significantly promotes the oxygen reduction reaction (ORR) of cathode surface. With the increase in firing temperature, the total resistance increases and R p changes from ion transport to oxygen reduction reaction. Degradation rate of the PNM5-infiltrated LSCF is also lower, 0.02168% vs 0.07093% for the baseline LSCF over a 200-h period. A single cell testing indicated that the peak power density of the PNM5-infiltrated cell was increased by 140.66%. Overall, PNM5 could be a potential catalyst for boosting the performance of a commercial LSCF cathode for solid oxide fuel cells (SOFC).

36 MATERIALS SCIENCE↗

Explaining System-Level Prognostics with Established Machine Learning Methods

System-level prognostics is crucial for ensuring reliability and enabling predictive maintenance in complex systems with interconnected components. This study presents a framework that integrates data-driven methods to predict the remaining useful life (RUL) of a subsystem under multiple and concurrent faults within a nuclear power plant system with explainable artificial intelligence (XAI). A nuclear power plant (NPP) operation was simulated to model the degradation behavior of NPP components, and four machine learning models—Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory (LSTM)—were evaluated for prognostics with a novel system RUL parameter. The LSTM model demonstrated potential superior repeatability, while SHAP (SHapley Additive exPlanations) for explainability provided consistent and trustworthy global explanations. In contrast, LIME (Local Interpretable Model-agnostic Explanations) offered localized interpretability but showed reduced stability for sequential data. Key findings include the interplay between component-level degradation and system-wide performance, with LSTM effectively capturing these dynamics through sequence-level predictions. The XAI techniques enhanced transparency by identifying critical features influencing model predictions and aligning with domain knowledge. Furthermore, this framework has significant implications for improving trust and understanding in predictive maintenance, particularly in safety-critical industries like nuclear energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Boosting energy efficiency of Li-rich layered oxide cathodes by tuning oxygen redox kinetics and reversibility

In developing electrode materials for next-generation Li-ion batteries, significant efforts have been given to the energy, power density and cycling stability, with much less (if any) attention paid to the energy efficiency – arguably, the most important practical measure for large-scale applications. This is particularly true for the oxygen-redox active electrodes, such as Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , the notorious energy-inefficient cathode that has an extremely high capacity but comes with large voltage hysteresis and voltage decay. Herein, we report the rational design of an energy-efficient Li-rich layered cathode along with high energy, power density and cycling stability enabled by tuning oxygen redox activity. Specifically, the target material Li 1.12 Ni 0.22 Co 0.13 Mn 0.52 O 2 exhibits an ultrahigh energy efficiency at 1 C (90.6%), high capacity (> 200 mAh g -1 ) with 98.9% retention and less than 150 mV decay at the extended 200 cycles. Overall, through direct comparison between the material and Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , we show that the compositional change, although slightly, greatly improves the oxygen redox kinetics and reversibility, thereby boosts energy efficiency. The findings offer a strategy to narrow the gap between scientific interest and practical application of oxygen-redox chemistry.

36 MATERIALS SCIENCE↗

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 2: Appendices

The computer programs and derivations generated in support of the modeling and design optimization program are presented. Programs for the buck regulator, boost regulator, and buck-boost regulator are described. The computer program for the design optimization calculations is presented. Constraints for the boost and buck-boost converter were derived. Derivations of state-space equations and transfer functions are presented. Computer lists for the converters are presented, and the input parameters justified.

Lee, F. C.↗

A Facility for Testing High-Power Electric Propulsion Systems in Space: A Design Study

This paper will describe the results of the preliminary phase of a NASA design study for a facility to test high-power electric propulsion systems in space. The results of this design study are intended to provide a firm foundation for a subsequent detailed design and development activities leading to the deployment of a valuable space facility supporting the new vision of space exploration. The objectives for human and robotic exploration of space can be accomplished affordably, safely and effectively with high-power electric propulsion systems. But, as thruster power levels rise to the hundreds of kilowatts and up to megawatts, their testing will pose stringent and expensive demands on existing Earth-based vacuum facilities. These considerations and the access to near-Earth space provided by the International Space Station (ISS) have led to a renewed interest in space testing. The ISS could provide an excellent platform for a space-based test facility with the continuous vacuum conditions of the natural space environment and no chamber walls to modify the open boundary conditions of the propulsion system exhaust. The platform would be designed to accommodate the side-by-side testing of multiple types of electric thrusters currently under development and thus provide a strong basis for comparing their relative performance. The utility of testing on the station is further enhanced by the human presence, enabling close interaction with and modification of the test hardware in a true laboratory environment. These conditions facilitate rapid development and flight certification at potentially lower cost than with conventional Earth-bound facilities. As an added benefit, the propulsive effect of these tests could provide some drag compensation for the station, reducing the re-boost cost for the orbital facility. While it is expected that the ISS will not be capable of generating continuous levels of high power, the utilization of state-of-the-art energy storage media would be sufficient to achieve very high power levels over intervals short enough to be feasible and long enough to provide ample demonstration of steady-state operation. This paper will outline the results of the preliminary phase of the design study with emphasis on the requirements that will dictate the system design.

Petro, Andrew J.↗

An Inductor Current Estimation Approach for DC/DC Converters Based on Bisection Method

The trends toward higher power density and efficiency for the DC/DC converters has posed more strict requirements for inductors. The inductor current in turn affect the operating characteristics of the converters significantly and thus needs to be accurately estimated. In this paper, a new bisection-method-based inductor current estimation approach considering the variation of inductance is proposed. The proposed approach can be adapted and applied for various DC/DC converters, including the widely used buck and boost converters and etc. Comparing to the conventional estimation method using constant inductance, the proposed method can obtain more precise estimations of both the inductor current waveform and the power loss. Experimental results on a buck converter with a ferrite-core inductor are presented to validate the effectiveness of the proposed approach.

Zhao, Zhe↗

Coupled Heat Power Operation of Smart Buildings via Modular Pumped Hydro Storage

In the United States, building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings’ energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low-grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high-efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground level. This unique design eliminates the geographical limitation associated with the existing state-of-the-art energy storage technologies. It is easy to be scaled for building level, community level, and grid level applications. By using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g., from thermal storage, combined cooling, heat and power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Here, several groups of comparison experiments have been conducted, and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Learning curves for drug response prediction in cancer cell lines

Motivated by the size and availability of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As drug sensitivity studies continue generating drug response data, a common question is whether the generalization performance of existing prediction models can be further improved with more training data. We utilize empirical learning curves for evaluating and comparing the data scaling properties of two neural networks (NNs) and two gradient boosting decision tree (GBDT) models trained on four cell line drug screening datasets. The learning curves are accurately fitted to a power law model, providing a framework for assessing the data scaling behavior of these models. The curves demonstrate that no single model dominates in terms of prediction performance across all datasets and training sizes, thus suggesting that the actual shape of these curves depends on the unique pair of an ML model and a dataset. The multi-input NN (mNN), in which gene expressions of cancer cells and molecular drug descriptors are input into separate subnetworks, outperforms a single-input NN (sNN), where the cell and drug features are concatenated for the input layer. In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training set sizes for two of the tested datasets, whereas the mNN consistently performs better at the higher range of training sizes. Moreover, the trajectory of the curves suggests that increasing the sample size is expected to further improve prediction scores of both NNs. These observations demonstrate the benefit of using learning curves to evaluate prediction models, providing a broader perspective on the overall data scaling characteristics. A fitted power law learning curve provides a forward-looking metric for analyzing prediction performance and can serve as a co-design tool to guide experimental biologists and computational scientists in the design of future experiments in prospective research studies.

60 APPLIED LIFE SCIENCES↗

X-43C Plans and Status

X-43C Project is a hypersonic flight demonstration being executed as a collaboration between the National Aeronautics and Space Administration (NASA) and the United States Air Force (USAF). X-43C will expand the hypersonic flight envelope for air breathing engines beyond the history making efforts of the Hyper-X Program (X-43A). X-43C will demonstrate sustained accelerating flight during three flight tests of expendable X-43C Demonstrator Vehicles (DVs). The approximately 16-foot long X-43C DV will be boosted to the starting test conditions, separate from the booster, and accelerate from Mach 5 to Mach 7 under its own power and autonomous control. The DVs are to be powered by a liquid hydrocarbon-fueled, fuel-cooled, dual-mode, airframe integrated scramjet engine system developed under the USAF HyTech Program. The Project is managed by NASA Langley Research Center as part of NASA s Next Generation Launch Technology Program. Flight tests will be conducted by NASA Dryden Flight Research Center over water off the coast of California in the Pacific Test Range. The NASA/USAF/industry project is a natural extension of the Hyper-X Program (X-43A), which will demonstrate short duration (~ 10 seconds) gaseous hydrogen-fueled scramjet powered flight at Mach 7 and Mach 10 using a heavyweight, largely heat sink construction, experimental engine. The X-43C Project will demonstrate sustained accelerating flight from Mach 5 to Mach 7 (~ 4 minutes) using a flight-weight, fuel-cooled, scramjet engine powered by much denser liquid hydrocarbon fuel. The X-43C DV design flows from integrating USAF HyTech developed engine technologies with a NASA Air Breathing Launch Vehicle accelerator-class configuration and Hyper-X heritage vehicle systems designs. This paper describes the X-43C Project and provides background for NASA s current hypersonic flight demonstration efforts.

Moses, Paul L.↗

X-43C Flight Demonstrator Project Overview

The X-43C Flight Demonstrator Project is a joint NASA-USAF hypersonic propulsion technology flight demonstration project that will expand the hypersonic flight envelope for air-breathing engines. The Project will demonstrate sustained accelerating flight through three flights of expendable X-43C Demonstrator Vehicles (DVs). The approximately 16-foot long X-43C DV will be boosted to the starting test conditions, separate from the booster, and accelerate from Mach 5 to Mach 7 under its own power and autonomous control. The DVs will be powered by a liquid hydrocarbon-fueled, fuel-cooled, dual-mode, airframe integrated scramjet engine system developed under the USAF HyTech Program. The Project is managed by NASA Langley Research Center as part of NASA's Next Generation Launch Technology Program. Flight tests will be conducted by NASA Dryden Flight Research Center off the coast of California over water in the Pacific Test Range. The NASA/USAF/industry project is a natural extension of the Hyper-X Program (X-43A), which will demonstrate short duration (approximately 10 seconds) gaseous hydrogen-fueled scramjet powered flight at Mach 7 and Mach 10 using a heavy-weight, largely heat sink construction, experimental engine. The X-43C Project will demonstrate sustained accelerating flight from Mach 5 to Mach 7 (approximately 4 minutes) using a flight-weight, fuel-cooled, scramjet engine powered by much denser liquid hydrocarbon fuel. The X-43C DV design flows from integrating USAF HyTech developed engine technologies with a NASA Air-Breathing Launch Vehicle accelerator-class configuration and Hyper-X heritage vehicle systems designs. This paper describes the X-43C Project and provides the background for NASA's current hypersonic flight demonstration efforts.

Moses, Paul L.↗

Comprehensive Comparative Analysis: VSI-based vs. CSI-based Motor Drive Systems with Sinusoidal Output Voltage

The emergence of wide-bandgap (WBG) power devices opens opportunities for current source inverters (CSIs) to provide a promising alternative drive configuration for motor drive applications. The sinusoidal output voltage of CSI offers significant advantages for numerous motor drive applications, including reducing the risks associated with motor terminal overvoltages and bearing discharge currents. This paper compares the performance of CSIs and voltage source inverters (VSIs) with the same performance capabilities. More specifically, sine filters are added to the VSI output terminals to match the CSI performance, and a front-end boost converter is added to the VSI to match the CSI’s voltage-boost capability. The results show that the CSI active components require 48% less volume than the VSI, combined with other performance advantages that make it an appealing candidate for some future motor drive applications.

current source inverter, motor drive system, passi↗

Microgrid Resilience: A Holistic and Context-Aware Resilience Metric

Microgrids present an effective solution for the coordinated deployment of various distributed energy resources and furthermore provide myriad additional benefits such as resilience, decreased carbon footprint, and reliability to energy consumers and the energy system as a whole. Boosting the resilience of distribution systems is another major benefit of microgrids. This is because they can also serve as a backup power source when the utility grid's operations are interrupted due to either high-probability low-impact events like a component failure or low-probability high-impact events - be it a natural disaster or a planned cyberattack. However, the degree to which any particular system can defend, adapt, and restore normal operation depends on various factors including the type and severity of events to which a microgrid is subjected. These factors, in turn, are dependent on the geographical location of the deployed microgrid as well as the cyber risk profile of the site where the microgrid is operating. Therefore, in this work, we attempt to capture this multi-dimensional interplay of various factors in quantifying the ability of the microgrid to be resilient in these varying aspects. This paper, thus, proposes a customized site-specific quantification of the resilience strength for the individual microgrid's capability to absorb, restore, and adapt to the changing circumstances for sustaining the critical load when a low-probability high-impact event occurs - termed as - context-aware resilience metric. We also present a case study to illustrate the key elements of our integrated analytical approach.

microgrid↗

Planning for performance augmentation for the Space Shuttle

The necessity of performance augmentation for the Space Shuttle to assure its capability of delivering a 32,000 pound payload to a 150 nautical mile circular orbit at an inclination of 98 deg and to then retrieve a 25,000 pound spacecraft from that orbit is discussed. The performance augmented Space Shuttle must meet all design mission requirements and will offer potential payload growth to accommodate new payloads and new concepts. The performance augmentation program includes the uprating of the Space Shuttle main engines to the range of 115% of rated power level for nominal operations, the development of solid rocket motor filament-wound case segments, and the use of a liquid boost module.

Goldsby, W. D.↗

Voltage-Boosting Driver For Switching Regulator

Driver circuit assures availability of 10- to 15-V gate-to-source voltage needed to turn on n-channel metal oxide/semiconductor field-effect transistor (MOSFET) acting as switch in switching voltage regulator. Includes voltage-boosting circuit efficiently providing gate voltage 10 to 15 V above supply voltage. Contains no exotic parts and does not require additional power supply. Consists of NAND gate and dual voltage booster operating in conjunction with pulse-width modulator part of regulator.

Trump, Ronald C.↗

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Combining resonant and tail-based anomaly detection

In many well-motivated models of the electroweak scale, cascade decays of new particles can result in highly boosted hadronic resonances (e.g., Z / W / h ). This can make these models rich and promising targets for recently developed resonant anomaly detection methods powered by modern machine learning. We demonstrate this using the state-of-the-art classifying anomalies through outer density estimation () method applied to supersymmetry scenarios with gluino pair production. We show that , despite being model agnostic, is nevertheless competitive with dedicated cut-based searches, while simultaneously covering a much wider region of parameter space. The gluino events also populate the tails of the missing energy and H T distributions, making this a novel combination of resonant and tail-based anomaly detection. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

An evaluation of a hubless inducer and a full flow hydraulic turbine driven inducer boost pump

The purpose of the study was to compare the performance of several configurations of hubless inducers with a hydrodynamically similar conventional inducer and to demonstrate the performance of a full flow hydraulic turbine driven inducer boost pump using these inducers. A boost pump of this type consists of an inducer connected to a hydraulic turbine with a high speed rotor located in between. All the flow passes through the inducer, rotor, and hydraulic turbine, then into the main pump. The rotor, which is attached to the main pump shaft, provides the input power to drive the hydraulic turbine which, in turn, drives the inducer. The inducer, rotating at a lower speed, develops the necessary head to prevent rotor cavitation. The rotor speed is consistent with present main engine liquid hydrogen pump designs and the overall boost pump head rise is sufficient to provide adequate main pump suction head. This system would have the potential for operating at lower liquid hydrogen tank pressures.

Lindley, B. K.↗