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At least 847 records · Page 47

Progress Toward the Critical Design of the Superconducting Rotor for NASA's 1.4 MW High-Efficiency Electric Machine

NASA Glenn Research Center is developing a 1.4 MW high-efficiency electric machine for future electrified aircraft to reduce energy consumption, emissions, and noise. This wound-field, synchronous machine employs a self-cooled, superconducting rotor to achieve excellent specific power and efficiency. This paper presents the progress made over the past year toward a critical design of the superconducting rotor, including refined analysis and risk reduction testing on prototype superconducting coils. A 3D finite element model of the rotor is developed to simulate the combined loading imposed by the initial cool down of the rotor from room temperature to cryogenic temperature and the subsequent rotation of the rotor up to the design speed. The model is evaluated to better predict the stress state in the critical components and the reduction in physical gap between the stator and rotor due to the resulting radial deflections. This model includes an enhanced model of the superconducting coil that considers the coil as an assembly of four individual coil layers. An improved coil fabrication process is described in detail. Two sub-scale test coils are fabricated and then tested under repeated thermal cycling between room temperature and liquid nitrogen temperature (77 K). It is demonstrated that the proposed coil fabrication procedure can produce no-insulation, high temperature superconducting coils that can survive several thermal cycles without apparent degradation.

electric machines↗

Progress Toward the Critical Design of the Superconducting Rotor for NASA's 1.4 MW High Efficiency Electric Machine

NASA Glenn Research Center is developing a 1.4 MW high-efficiency electric machine for future electrified aircraft to reduce energy consumption, emissions, and noise. This wound-field, synchronous machine employs a self-cooled, superconducting rotor to achieve excellent specific power and efficiency. This paper presents the progress made over the past year toward a critical design of the superconducting rotor, including refined analysis and risk reduction testing on prototype superconducting coils. A 3D finite element model of the rotor is developed to simulate the combined loading imposed by the initial cool down of the rotor from room temperature to cryogenic temperature and the subsequent rotation of the rotor up to the design speed. The model is evaluated to better predict the stress state in the critical components and the reduction in physical gap between the stator and rotor due to the resulting radial deflections. This model includes an enhanced model of the superconducting coil that considers the coil as an assembly of four individual coil layers. An improved coil fabrication process is described in detail. Two sub-scale test coils are fabricated and then tested under repeated thermal cycling between room temperature and liquid nitrogen temperature (77 K). It is demonstrated that the proposed coil fabrication procedure can produce no-insulation, high temperature superconducting coils that can survive several thermal cycles without apparent degradation.

Scheidler, Justin↗

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗

Operando X-ray Absorption Spectroscopy Study of SnO 2 Nanoparticles for Electrochemical Reduction of CO 2 to Formate

Tin–based electrocatalysts exhibit a remarkable ability to catalyze CO 2 to formate selectively. Understanding the size-property relationships and exploring the evolutions of active size still lack complete understanding. Herein, we prepared SnO 2 nanoparticles (NPs) with controllable size supported on commercial carbon spheres (SnO 2 /C–n, n=1,2,3) by a simple low-temperature annealing method. The transmission electron microscopy(TEM)/scanning transmission electron microscope (STEM) images and fitting results of the small angle X-ray scattering (SAXS) profile confirm the increased size of SnO 2 NPs as the increase of SnO 2 loading. The catalytic performance of SnO 2 has proved the size-dependent effect during CO 2 reduction reaction process. The as-prepared SnO 2 /C–1 displayed the maximum Faradic efficiency of formate (FE HCOO– ) of 82.7% at –1.0 V vs. RHE. In contrast, SnO 2 /C–2 and SnO 2 /C–3 with larger particle sizes achieved lower maximum FE HCOO– and larger overpotential. Moreover, we employed operando XAS to study the evolution of the oxidation state and local coordination environment of SnO 2 under working conditions. In addition to the observed the shifts of rising edge of Sn K-edge X-ray absorption near edge structure (XANES) spectra to lower energy side as the applied voltage decreases, the decreased coordination number of Sn in the Sn-O scattering path and the presence of Sn mental contribution in extended X-ray absorption fine structure (EXAFS) spectra verify the reduction of SnO 2 to SnO x and metallic Sn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled rotor-flexible fuselage vibration reduction using open loop higher harmonic control

A fundamental study of vibration prediction and vibration reduction in helicopters using active controls was performed. The nonlinear equations of motion for a coupled rotor/flexible fuselage system have been derived using computer algebra on a special purpose symbolic computer facility. The trim state and vibratory response of the helicopter are obtained in a single pass by applying the harmonic balance technique and simultaneously satisfying the trim and the vibratory response of the helicopter for all rotor and fuselage degrees of freedom. The influence of the fuselage flexibility on the vibratory response is studied. It is shown that the conventional single frequency higher harmonic control is capable of reducing either the hub loads or only the fuselage vibrations but not both simultaneously. It is demonstrated that for simultaneous reduction of hub shears and fuselae vibrations a new scheme called multiple higher harmonic control is required.

Papavassiliou, I.↗

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Neural Optimizer With Decision-Focused Learning for Optimal Energy Storage Operation

Here, this article introduces a neural optimizer-based framework for optimizing battery energy storage system (BESS) control for grid services, including demand charge and energy cost reduction. By leveraging decision-focused learning (DFL), the proposed framework ensures seamless integration and adaptation, significantly enhancing control performance. A patch time-series transformer is employed for peak load forecasting, incorporating aleatoric uncertainty quantification to account for forecasting uncertainties within the decision-making process. The framework utilizes a solver-in-the-loop approach to generate optimal BESS actions, which are then used to train the neural optimizer-based agent. By co-optimizing both BESS operational modes and output power within the NN, the system achieves improved performance and robustness. After initial training, the forecasting and control models are jointly fine-tuned to account for forecasting errors, further improving decision precision and efficiency through DFL. Case studies are performed to validate the performance of the framework using multiple real-world datasets, demonstrating superior performance in monthly peak load forecasting compared to state-of-the-art models. In addition, the results are compared against existing decision-making approaches. The results demonstrate a reduction in monthly peak forecasting error by approximately 15% across various performance measures and achieve an optimization gap for BESS operation that is about three times smaller compared to existing methods.

Kim, Hyeonjin [Pacific Northwest National Laborato↗

Amino-tethering synthesis strategy toward highly accessible sub-3-nm L1 0 -PtM catalysts for high-power fuel cells

Because of the poor accessibility of embedded active sites, platinum (Pt)-based electrocatalysts suffer from insufficient Pt utilization and mass transport in membrane electrode assemblies (MEAs), limiting their performance in polymer electrolyte membrane fuel cells. Here, we report a simple and universal approach to depositing sub-3-nm L1 0 -PtM nanoparticles over external surfaces of carbon supports through pore-tailored amino (NH 2 )-modification, which enables not only excellent activity for the oxygen reduction reaction, but also enhanced Pt utilization and mass transport in MEAs. Using a low loading of 0.10 mg Pt ∙cm -2 , the MEA of PtCo/KB-NH 2 delivered an excellent mass activity of 0.691 A∙mgPt -1 , a record-high power density of 0.96 W∙cm -2 at 0.67 V, and only a 30-mV drop at 0.80 A∙cm -2 after 30,000 voltage cycles, which meets nearly all targets set by the Department of Energy. Finally, this work provides an efficient strategy for designing advanced Pt-based electrocatalysts and realizing high-power fuel cells.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Chemical Vapor Deposition for Atomically Dispersed and Nitrogen Coordinated Single Metal Site Catalysts

Abstract Atomically dispersed and nitrogen coordinated single metal sites (M‐N‐C, M=Fe, Co, Ni, Mn) are the popular platinum group‐metal (PGM)‐free catalysts for many electrochemical reactions. Traditional wet‐chemistry catalyst synthesis often requires complex procedures with unsatisfied reproducibility and scalability. Here, we report a facile chemical vapor deposition (CVD) strategy to synthesize the promising M‐N‐C catalysts. The deposition of gaseous 2‐methylimidazole onto M‐doped ZnO substrates, followed by an in situ thermal activation, effectively generated single metal sites well dispersed into porous carbon. In particular, an optimal CVD‐derived Fe‐N‐C catalyst exclusively contains atomically dispersed FeN 4 sites with increased Fe loading relative to other catalysts from wet‐chemistry synthesis. The catalyst exhibited outstanding oxygen‐reduction activity in acidic electrolytes, which was further studied in proton‐exchange membrane fuel cells with encouraging performance.

Liu, Shengwen↗

Parameterization of generic positive sequence models to represent behavior of inverter based resources in low short circuit scenarios

The connection of large inverter based resources (IBR) in transmission systems is often located geographically and electrically far away from load centers. This, coupled with the displacement of synchronous machine plants, results in a reduction of the network short circuit strength at the point of connection. Under these conditions, state-of-the-art positive sequence simulation platforms and models can have difficulties maintaining numerical stability and/or providing an accurate representation of IBR plant dynamic behavior. As a result, computationally heavy time domain electromagnetic transient (EMT) simulations may be required to evaluate these systems. In this paper, a recently developed improved generic positive sequence model is parameterized to provide a representation of IBR behavior in low short circuit networks. Further, comparisons against generic and detailed EMT models demonstrate the suitability of the improved positive sequence model to study practical stability issues experienced with presently in-service plants. Such a model can provide some of the accuracy of an EMT representation with a much lower computational burden. The performance of the positive sequence model is validated against the behavior shown by both open white box and closed black box EMT domain models from around the world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermal loading effects on chalk hydromechanical behavior for nuclear waste disposal

Safe disposal of heat-generating nuclear waste depends on host rock stability under thermal, hydrological, and mechanical stresses. This study investigates the effect of thermal loading on mechanical behavior of the shallowly buried Ghareb formation chalk through triaxial and hydrostatic constant strain rate and creep tests at temperatures up to 100 ˚C and effective pressures up to 20.7 MPa. Experimental results show that thermal loading reduces the elastic moduli of chalk by 50–75%, and a transition occurs above 60 ˚C where creep rates increase rapidly. Water saturation nearly doubles the thermally induced strain compared to dry conditions and strongly decreases material rigidity. Thermal loading also leads to significant pore pressure increases under undrained conditions and leads to reductions in the apparent permeability during drained conditions. Laboratory experimental data were used to parameterize and develop a preliminary constitutive model for predicting future deformation during repository operations in the Ghareb. The strongly coupled effects – mechanical weakening, fluid pressure fluctuations, and permeability modification – demonstrate that elevated repository temperatures will have a pronounced effect on the near field Ghareb behavior during waste disposal operations. The findings indicate that the coupled interactions must be considered in predictive models and repository design to ensure long-term nuclear waste isolation and safety.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ultra-low magnetization and hysteresis loss in APC Nb 3 Sn superconductors

For the accelerator magnets of the next hadron collider, reducing superconductor persistent-current magnetization is not only important for achieving the desired field quality, but also crucial for its sustainability because the magnetization loss is the major heat load to the magnet cold mass. For conventional Nb 3 Sn conductors this requires reduction of effective subelement size (D eff ). For the restacked-rod-process (RRP ® ) conductors a physical subelement size (D sub ) as small as 35 µm (corresponding to a D eff close to 45 µm) can be reached, but at a significant price in J c . Another way to reduce the magnetization is by introducing artificial pinning centers (APC) using the internal oxidation approach. APC conductors outperform conventional Nb 3 Sn wires in two aspects: 1) higher J c at high fields, and 2) much lower J c and magnetization at low fields (e.g. below 5 T). Here, in this work we explored the fabricability of APC wires with small D sub . A 180-stack APC wire was produced and drawn to 0.7- and 0.5 mm diameters with good quality, with D sub s of 34 and 24 µm (D eff s of 36 and 25 µm), respectively. For the 34 µm-D sub wire, its non-Cu J c is higher than that of an RRP ® wire used for the High-Luminosity Large Hadron Collider (HL-LHC) project above 13 T (e.g. 36% higher at 4.2 K, 18 T), while its non-Cu magnetization at 1 T, ΔM(1 T), is only 29% of the RRP ® wire. Its non-Cu hysteresis loss for a cycle between 1 and 14 T, Q h (1–14 T), is 37% of the RRP ® wire. For the 24 µm-D sub wire, its non-Cu J c surpasses the HL-LHC RRP ® wire above 17.5 T, while its ΔM(1 T) and Q h (1–14 T) are only 17% and 23% of the RRP® wire, respectively. Its non-Cu Q h (±3 T) even meets the specification of the International Thermonuclear Experimental Reactor project.

Xu, X [Fermi National Accelerator Laboratory (FNAL↗

Texturing and residual stress in metals as a result of sliding

Pole figures of the texturing produced by friction in the alloys Cu - 10 at. % Sn, Cu - 10 at. % Si, 440 C stainless steel, and AISI 52100 bearing steel were obtained with an energy-dispersive X-ray diffractometer. While the texturing behavior of these alloys is generally similar to that of pure metals, the 52100 steel and the Cu5Si phase of Cu - 10 at. % Si show no texturing at the loads and speeds used in this experiment. Photographic methods were used in an attempt to measure the uniform residual stress in the wear tracks produced on some pure metals. The stress in copper and iron was, however, below the limit of detectability - about 4.3 x 10 to the 7th power N/sq m (6000 psi). Line broadening under all test conditions in the case of copper and at high load and speed conditions in iron is attributed, at least in part, to the reduction of crystallite size and, perhaps, to nonuniform residual stress, as well.

Wheeler, D. R.↗

Insights into the nature and control of rotor noise

The dynamics of four important farfield rotating blade noise sources are summarized and techniques for noise reduction are discussed. These four noise areas include the role of unsteady blade surface loads on rotational noise, the effect of turbulent inflow on the radiated broadband noise of an airfoil, the influence of the trailing vortex on impulsive noise and tail rotor noise, and the effect of blade geometry on high-speed impulsive noise. These noise mechanisms occur to varying degrees on both helicopter rotors and propellers. Considerable theoretical work was done in the area of high-speed impulsive noise resulting from the geometry of the rotating blade system. Both model and full-scale experimental correlation of helicopter and propeller high-speed noise are presented. The effect of blade number and airfoil thickness distribution in reducing the high-speed noise is shown.

Pegg, R. J.↗

An electric vehicle propulsion system's impact on battery performance: An overview

The performance of two types of batteries, lead-acid and nickel-zinc, was measured as a function of the charging and discharging demands anticipated from electric vehicle propulsion systems. The benefits of rapid high current charging were mixed: although it allowed quick charges, the energy efficiency was reduced. For low power (overnight) charging the current wave shapes delivered by the charger to the battery tended to have no effect on the battery cycle life. The use of chopper speed controllers with series traction motors resulted in a significant reduction in the energy available from a battery whenever the motor operates at part load. The demand placed on a battery by an electric vehicle propulsion system containing electrical regenerative braking confirmed significant improvment in short term performance of the battery.

Bozek, J. M.↗

Frequency effect on the fatigue life of a laminated composite

Effects of load frequency on the fatigue behavior of notched (+ or - 45 deg)2s laminated graphite/epoxy composites are investigated. Experimental results are obtained using four frequencies at three load levels. Temperature rises near the center hole are also measured. It is found that when temperature increase during the fatigue test is small, fatigue life increases as the load frequency increases. However, an increase in the near hole temperature results in a reduction in fatigue life. A theoretical model based upon crack propagation in viscoelastic media is presented. The model is modified to account for the temperature effect.

Sun, C. T.↗

Schottky diode mm detectors with improved sensitivity and dynamic range

A detector which features a low-barrier Si Schottky diode is discussed. The unbiased diode has a sensitivity of -60 dBm and a range of 50 dB at 95 GHz, and fixed tuning yields a sensitivity within 2 dB from 75-110 GHz. A limitation of the low-barrier diode is a reduction in the low-level sensitivity by 16 dB under a 100 kilohms load. Use of the diode with a video impedance of 120 kilohms enables the offset voltage to be nulled with an appropriate control. Operation of the diode in a waveguide mount for use as a mixer is described, along with detector rectification.

Kerr, A. R.↗

New component development for multi-100 kW low-cost solar array applications

Studies of the cost and performance of flexible arrays have shown that the most dramatic reductions in the $/Watt figure of merit are achieved by increasing performance. An examination of those properties that contribute to array performance indicated areas where radical changes in current design practice and philosophy would result in significant cost and performance impacts. To take advantage of the predicted cost reductions, modules were fabricated and tested that had ultra-thin superstrates as a load carrying member and large area dielectric wraparound (DWA), gridded back surface and copper contacted solar cells.

Pack, G. J.↗