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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 559 records · Page 31

Optimal Litz Wire Design for High-Power Wireless Charging System

In this study, an optimized Litz wire and polyphase coil winding design is proposed for high-power wireless charging systems operating at 85 kHz frequency. Litz wire in a wireless charging system contributes to more than half of the losses of the system, making it a critical design component. Here, the Litz wire is optimized through Finite Element Analysis (FEA) considering electrical and mechanical design aspects and the design was validated through experimental tests on different Litz wires with various strand-diameters, twisting ratio, and number of strands. The proposed optimal Litz wire maximizes the system efficiency considering the tradeoff between coil resistance and mutual inductance. The optimal Litz wire shows that Litz wire constructed with the 63µm strands significantly outperform the traditionally used Litz wire with 100µm strand diameter. Additionally, the coil with optimal Litz wire design shows 60% reduction in the copper volume for the same loss, and at the same time increase the coil-to-coil efficiency by more than 2% by increasing the mutual inductance and reducing coil current. The optimized Litz wire was implemented in a 22-kW wireless charging system achieving 94.7% efficiency.

Aydin, Emrullah [ORNL]↗

Traffic Prediction for Merging Coordination Control in Mixed Traffic Scenarios

Connected and autonomous vehicles (CAVs) have the potential to bring in safety, mobility, and energy benefits to transportation. The control decisions of CAVs are usually determined for a look-ahead horizon based on previewed traffic information. This requires an effective prediction of future traffic conditions and its integration with the CAV control framework. However, the short-term traffic prediction using information from connectivity is a challenging research topic, especially for mixed traffic scenarios. This work focuses on the development of a traffic prediction framework for a merging coordination controller. The previously developed merging controller coordinates the merging sequence and travel speed of CAVs to maximize the energy efficiency and overall mobility. In mixed traffic scenarios, the controller receives information regarding the position of all the vehicles traveling inside a control zone and controls the desired speed of all CAVs. The controller has no control on the human-driven vehicles. The merging controller does not have direct information or an explicit prediction on the behaviors of human-driven vehicles. Aiming to improve the performance of the merging controller in various mixed traffic conditions, a traffic prediction algorithm is developed and evaluated in this work. The performance of this traffic prediction algorithm is investigated for various penetration rates of connectivity for a single-lane secondary road merging to a single-lane primary road. The results show that compared to a constant speed assumption of human-driven vehicles, the proposed traffic prediction algorithm is able to reduce the prediction error of the arrival time of human-driven vehicles at the merging zone by more than 50%.

Shao, Yunli↗

SU-G-BRC-14: Multi-Lesion, Multi-Rx, Brain Radiosurgery with Novel Single Isocenter Technique

Purpose: There is a strong trend to treat multiple brain metastases with radiosurgery rather than whole brain irradiation. This feasibility study investigates a novel planning technique for radio-surgical treatment of multiple brain lesions with differing dose prescriptions, a single isocenter, and dynamic conformal arcs. The novel technique will be compared to the well-established single-isocenter volumetric modulated arc therapy (VMAT) technique commonly used for treating brain lesions. Methods: Six patients with metastatic brain lesions were selected for a prospective treatment planning study to evaluate Interdigitating MLC Dynamic Conformal Arc (IMDCA) technique. Arcs were planned for simultaneous irradiation to maximize beam delivery efficiency. To accommodate varying PTV dose prescriptions, selected arcs were re-irradiated in reverse. Beam weights were adjusted until all prescription constraints were met. The number of lesions ranged between 2 to 4 (mode = 3). For comparison, SRS VMAT plans were generated utilizing an established single-isocenter, 3 arc planning template. All plans were compared by means of Paddick conformity index (PCI), RTOG Conformity Index (RCI), gradient index (GI), and the normal brain volume receiving 10% (V10) of the highest prescription dose. The monitor units and delivery time were tabulated for each plan. Results: IMDCA achieved conformal plans (PCI = 0.72±0.03, RCI = 1.33±0.03) with steep dose fall-off (GI = 3.79±0.03) on average for all of the plans evaluated. The VMAT plans had slightly better conformity (PCI = 0.85 ± 0.03, RCI = 1.13 ± 0.03) than IMDCA, but overall worse GI (4.29 ± 0.06). IMDCA plans had lower V10% values, required 50% fewer MUs, and had 34% shorter beam delivery time on average compared to VMAT plans. Conclusion: IMDCA plans with varying dose prescriptions for multiple lesions, had comparable dosimetric coverage as VMAT plans, but were obtained with significantly lower integral dose, fewer monitor units, and quicker delivery time.

60 APPLIED LIFE SCIENCES↗

BitGNN: Unlocking the Performance Potential of Binary Graph Neural Networks on GPUs

Graph Neural Networks (GNNs) have shown compelling results in many graph-based learning tasks. They are, however, time-consuming. Recent work has shown a promising direction in improving GNN speed and shrinking the size — network binarization, which binarizes network values and operations. Prior work, however, mainly focused on algorithm designs, leaving it open on how to fully materialize the performance potential. This work fills the gap by proposing techniques to best map binary GNNs and their computations to fit the nature of bit manipulations, optimizations and algorithms to maximize BSpMM kernel efficiency, and solutions to other factors influencing the end-to-end time on GPUs. Results on real-world graphs show that the proposed techniques outperform state of-the-art binary GNN implementations by 21-67× with little accuracy loss.

Chen, Jou-An↗

Temperature Control of Crystal Optics for Ultrahigh-Resolution Applications

The temperature control of crystal optics is critical for ultrahigh resolution applications such as those used in meV-resolved Inelastic Scattering. Due to the low count rate and long acquisition time of these experiments, for 1-meV energy resolution, the absolute temperature stability of the crystal optics must be maintained below 4 mK to ensure the required stability of lattice constant, thereby ensuring the energy stability of the optics. Furthermore, the temperature control with sub-mK precision enables setting the absolute temperature of individual crystal, making it possible to align the reflection energy of each crystal’s rocking curve in sub-meV resolution thereby maximizing the combined efficiency of the crystal optics. In this contribution, we report the details of an EPICS control system using PT1000 sensors, Keithley 3706A 7.5 digits sensor scanner, and Wiener MPOD LV power supply for the analyzer crystals of the Inelastic X-ray Scattering (IXS) beamline 10-ID at NSLS-II**. We were able to achieve absolute temperature stability below 1 mK and sub-meV energy alignment for several asymmetrically cut analyzer crystals. The EPICS ePID record was used for the control of the power supplies based on the PT1000 sensor input that was read with 7.5 digits accuracy from the Keithley 3706A scanner. The system enhances the performance of the meV-resolved IXS spectrometer with currently a 1.4 meV total energy resolution and unprecedented spectral sharpness for studies of atomic dynamics in a broad range of materials.

Gofron, Kaz↗

Status of the laser manipulations of H- beam at J-PARC

The laser manipulations of H- ion beam by single or double neutralization is a very promising technique and highly essential to utilized in accelerator processes such as stripping, pulse chopping, collimation, extraction, and beam diagnostics for the present and future high-intensity proton accelerators. At J-PARC, we are preparing for a POP (Proof-of-Principle) demonstration 400 MeV H- stripping by using only lasers. A prototype YAG laser system and a laser cavity system to reduce the laser power are being developed through 3 MeV H- neutralization studies. Fermilab utilizes H- neutralization at 0.75 MeV by establishing a laser Notcher system for a gap in the H- pulse needed for a clean beam extraction from the ring. To minimize the laser power and maximize the interaction efficiency are common issue at both laboratories. Under the US-Japan collaboration for high-intensity neutrino beam, we are closely working to establish recycling/reusing of seed laser pulses to reduce a size of the laser system. In parallel, we have also developed non-destructive beam diagnostic systems at lower H- energy of 3 MeV, which will be implemented to the 400 MeV as well as easily applicable to the Fermilab linac including PIP-II linac. Installation of the laser system at J-PARC linac for 400 MeV H- stripping is ongoing to start the POP experimental study in 2023.

43 PARTICLE ACCELERATORS↗

Final Report DOE SSL Grant (No. DE-EE0006673) Advanced Light Extraction Structure for OLED Lighting

The innovation proposed in this grant is to demonstrate a novel internal light extraction (ILE) design that can maximize the energy efficiency of Organic Light Emitting Diode (OLED) lighting devices without negatively impacting the device voltage, efficacy or angular color dependences. Even though, OLEDs have unique features compared to its inorganic counterparts, LEDs, in terms of technology development and market readiness levels, it still lags LEDs by several years. The main challenges as identified in the National Research Council’s 2013 Assessment on Solid State Lighting, are the cost of the materials and the low light extraction efficacy [1]. Improving the light extraction will improve both the $/Klm and lm/W, two important metrics DOE uses to measure the cost effectiveness of a light source.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Mobility Data and Models Informing Smart Cities

Using emerging data platforms, new mobility technologies, and travel demand models (TDMs), researchers, industry, and communities seek to improve the quality of transportation while maximizing the energy efficiency, equity, and safety of transportation services. As transportation may soon reach over 30% of U.S. energy consumption and with urban areas representing an increasing proportion of the U.S. population (>80% since 2010), a critical need exists to engage in urban data science-informed approaches to enhancing mobility. The objective of this study is to explore and document how aspiring Smart Cities are using data and models to inform mobility and energy initiatives within Smart City programs and in so doing identify gaps in knowledge and processes guiding Smart City mobility investment strategies, programs, projects, and pilots. A primary focus of the Smart Cities studied was the creation of an integrated data sharing environment approach. Most of these systems are being developed in parallel with multiple new data analysis tools, while regional metropolitan planning organizations continue to slowly evolve TDMs to take into account impacts of long-term strategies for emerging mobility technologies and services. Smart City initiatives in the United States have keen interests in leveraging knowledge and research on the mobility benefits and risks of automated, connected, efficient/electric, and shared on-demand mobility services; and understanding the related energy, environmental, economic, and societal impacts of these shifts. The results serve to identify key gaps in data, knowledge, and methods required to advance energy efficient urban mobility innovation, and to enable research and analysis collaboration between Smart Cities and the U.S. Department of Energy's efforts enabling new Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility.

33 ADVANCED PROPULSION SYSTEMS↗

Enhancing Steam-Side Heat Transfer via Microdroplet Ejection using Inorganic Coatings

During condensation of water on a superhydrophobic nanostructured surfaces, droplets coalesce and jump (droplet ejection) due to the release of excess surface energy. Meticulously designed nanostructured surfaces or coatings capable of droplet ejection can enhance heat transfer performance by easy removal of droplets during condensation. In the present work, the capabilities of the Nelumbo droplet ejection coatings technology currently used in commercial heat exchangers are explored and optimized for materials and conditions relevant to steam condensers. Specifically, this includes (1) adapting and optimizing the procedures and chemistries to deposit droplet ejecting coatings on materials used in the steam condenser, (2) testing of the heat transfer, durability, and fouling of the fabricated coatings under a variety of steam condenser relevant conditions, and (3) modeling of the impact of droplet dynamics and interfacial properties on heat transfer in steam condensers. We experimentally demonstrated that at low supersaturation conditions (S~1.02), developed superhydrophobic nanostructured surface gives a 40% higher peak heat transfer flux and a 17% higher peak overall heat transfer coefficient (U) with droplet ejection mechanism compared to the dropwise condensation mechanism on the same nanostructured surface. Though the experimentally observed droplet ejection mechanism was short-lived (~3 min) due to the limitation of the chiller to maintain a constant supersaturation condition in fabricated steam condenser. And large variations in water inlet temperature (+ to - 2 degrees C) caused flooding of nanostructure (Wenzel state) at higher supersaturation (S > or = 1.12). This is an important finding because typical supersaturation levels in field operation are over 1.8 and as such, either the flooding potential for these materials should be improved or operation at lower supersaturation may be required to maximize heat transfer efficiency. If supersaturation conditions can be maintained reliably in the steam condenser in addition to droplet ejection mechanism during condensation, this could provide a potential 2% reduction in water flow rate which equates to a savings of over 3900 gallons of water per minute for a 500 MW steam turbine and over $0.3MM savings annually given a 0.02 cent marginal water withdrawal cost. It is also worth noting that these savings are based on improvement of droplet ejection coatings over coatings capable of performing consistent dropwise mechanism in in-field surface condensers. Savings due to the droplet ejections coatings when compared to bare substrates could be much higher. Additionally, the present work provides the importance of steam condenser operating conditions and insights into the challenges in modeling the condensing droplet dynamics on surfaces.

20 FOSSIL-FUELED POWER PLANTS↗

Dimensionally Reduced Model for Rapid and Accurate Prediction of Gas Saturation, Pressure, and Brine Production in a CO 2 Storage Application: Case Study Using the SACROC Field as Part of SMART Task 5

This technical report presents work conducted by the sub surface analysis team of the Strategic Systems Analysis & Engineering group at NETL for Task 5 of SMART Phase 1. This study involved the development of deep learning models for CO 2 geologic storage that are capable of accurate prediction of spatio-temporal outputs of CO 2 saturation, pressure, and brine production in three dimensional space over a storage operation's injection and post-injection timeframes. The model framework involves ensembling multi-layer encoder networks that provide dimesionality reduction of geologic inputs with fully connected long short-term memory (LSTM) neural networks that generate time-series prediction This approach offers a means to maximize training time efficiency, reduce computational memory burden, and minimize prediction turnaround.

54 ENVIRONMENTAL SCIENCES↗

Initiating a Roadmap for Solar Fuels R&D: Imagining Beyond Thermochemical Cycles

Sandia National Laboratories in collaboration with the National Renewable Energy Laboratory outline a framework for developing a solar fuels roadmap based on novel concepts for hybridizing gas-splitting thermochemical cycle s with high-temperature electro chemical steps. We call this concept SoHyTEC, a Solar Hybrid Thermochemical-Electrochemical Cycle. The strategy focuses on transforming purely thermochemical cycles that split water (H 2 O) and carbon dioxide (CO 2 ) to produce hydrogen (H 2 ) and carbon monoxide (CO) , respectively, the fundamental chemical building blocks for diverse fuels and chemicals , by substituting thermochemical reactions with high-temperature electrochemical steps. By invoking high-temperature electrochemistry, the energy required to complete the gas-splitting cycle is divided into a thermal component (process temperature) and an electrical component (applied voltage). These components, sourced from solar energy, are independently variable knobs to maximize overall process efficiency. Furthermore, a small applied voltage can reduce cycle process temperature by hundreds of degrees , opening the door to cost-effective solar concentrators and practical receiver/reactor de signs. Using the SoHyTEC concept as a backdrop, we outline a framework that advocates developing methods for automating information gathering, critically evaluating thermochemical cycles for adapting into SoHyTEC, establishing requirements based on thermodynamic analysis, and developing a model-based approach to benchmarking a SoHyTEC system against a baseline concentrating solar thermal integrated electrolysis plant. We feel these framework elements are a necessary precursor to creating a robust and adaptive technology development roadmap for producing solar fuels using SoHyTEC. In one example, we introduce high-temperature electrochemistry as a method to manipulate a fully stoichiometric two-step metal oxide cycle that circumvents costly separation processes and ultra-high cycle temperatures. We also identify and group water-splitting chemistries that are conceptually amenable to hybridization.

14 SOLAR ENERGY↗

Collimation Systems for the PSR

This note provides a review of collimator systems being used or considered in high-intensity proton accelerators like SNS, J-PARC, LHC, and PIP-II. These facilities use collimators to remove beam halo, restrict transverse size and momentum in the beam to constrain beam losses around collimators and minimize beam losses downstream, particularly losses arising from particles missing the design location at the stripping foil when injected into the proton storage ring. Collimators are placed either in the transport injection lines (single-pass collimators) or in the rings (multi-pass collimators). Collimators in the transport line are placed around stripping foils in H- accelerators, allowing the beamline optics to get rid of the unstripped protons into well localized absorbers. Rings and proton accelerators mostly rely on tungsten scrapers and collimators in a multi-stage configuration to clean the scattered beam particles mainly responsible for heavy losses at high energies. Placement of the collimators is carefully chosen in terms of the right phase advance to maximize the collimating efficiency, whether the collimation is intended to match an injection stripping foil or a downstream acceptance. Collimation systems are designed with the specific concerns of each facility in mind, although all of them prioritize the minimization of activation due to beam losses to enable hands-on access during maintenance periods. At LANSCE, there are no high-energy collimators, although pairs of horizontal and vertical jaws are routinely used in the LEBT to clean and control the transverse beam profile delivered downstream. This report will help in understanding, together with the beam dynamics simulations, which collimation schemes would be most effective for the PSR upgrade. For example, SNS designed off-momentum collimators to be placed in a 90° arc bend, a high-dispersion region in the beam injection line, very similar to the bend at Line D in LANSCE. This system was very effective at minimizing losses during injection into the SNS accumulator ring and is being re-designed for future operation.

43 PARTICLE ACCELERATORS↗

Hydroelectric Power and Hydrogen Production Integration

Hydropower-based hydrogen production could introduce opportunities for new revenue streams for hydropower plants, including from energy storage and regeneration as well as from sale of the hydrogen product to external markets. Hydrogen-based energy storage and regeneration could also help support Idaho Power’s decarbonization goals by decreasing dependence on fossil-based peaking power plants. Additionally, integration of hydrogen production with hydropower generation could help address the issue of low dissolved oxygen river water conditions that commonly accompany hydropower plant operations by utilizing the oxygen byproduct from an electrolytic hydrogen production process as a resource for mitigation of low dissolved oxygen water conditions. Comprehensive techno-economic analysis of the hybrid hydroelectric and hydrogen energy storage system has revealed critical insights into the pathways and considerations for optimizing the economic value and environmental benefits of such systems. Among the three identified pathways of natural gas blending, regeneration, and direct sale of hydrogen, the direct sale of hydrogen emerges as the most profitable, particularly given the current pricing dynamics of hydrogen and electricity. However, as we anticipate a future grid characterized by higher renewable energy penetration, the landscape may evolve, featuring lower average electricity prices, heightened fluctuations, and more significant seasonal variations. Consequently, the attractiveness of electricity regeneration through hydrogen and the benefits of long-duration hydrogen storage are expected to increase substantially in such a dynamic energy scenario. The careful selection of component sizes within the hybrid system proves to be paramount for ensuring cost-effectiveness. Notably, the size of the hydrogen market has emerged as a critical determinant for the optimal size of the electrolyzer. Hydrogen storage should be sized to meet energy shifting requirements. The appropriate size of the fuel cell/microturbine generator hinges on the shape of electricity prices and the available revenue streams derived from participating in grid services. Striking the right balance among these components is essential for maximizing the overall efficiency and profitability of the hydrogen facility. Furthermore, the by-product of electrolysis, namely oxygen, introduces an additional dimension to the system's functionality. The oxygen generated can be effectively utilized for dissolved oxygen (DO) mitigation, particularly with larger electrolyzer sizes capable of satisfying the complete oxygen demand for this purpose. While the economic benefits derived from saved oxygen purchase costs may be relatively modest compared to other revenue streams, the environmental advantages of repurposing oxygen for DO mitigation could help Idaho Power meet their environmental obligations. In addition to the identified factors shaping the viability of hybrid hydrogen production and hydroelectric generation, it is noteworthy that the integration of hydrogen energy storage offers a unique advantage during unusually wet years. In such periods of increased water inflow, the hydrogen storage capacity serves as a valuable supplement to the reservoir. By utilizing hydrogen energy storage as a complementary reservoir, the system gains flexibility in reservoir management when dealing with fluctuations in water availability.

08 HYDROGEN↗

Search for Dark Showers from Higgs Boson Decays Through the Photon Portal

One of the primary goals of the CMS detector is to find particles beyond the standard model. We present a search for dark showers produced from decays of the Higgs boson using collision data from the CMS experiment at the LHC. These dark showers then decay into jets made entirely of photons, which we can observe in the detector. Thus, our analysis focuses on reconstructing and analyzing these jets and maximizing signal selection efficiency for data from the Monte Carlo simulation. The photon signature of dark jets can then be confirmed via an invariant-mass distribution of these two photon jets. If found, these particles would provide evidence of physics theories beyond the Standard Model.

MacMullin, Alexandra [Skidmore Coll.]↗

Deep nonparametric estimation of operators between infinite dimensional spaces

Learning operators between infinitely dimensional spaces is an important learning task arising in machine learning, imaging science, mathematical modeling and simulations, etc. This paper studies the nonparametric estimation of Lipschitz operators using deep neural networks. Non-asymptotic upper bounds are derived for the generalization error of the empirical risk minimizer over a properly chosen network class. Under the assumption that the target operator exhibits a low dimensional structure, our error bounds decay as the training sample size increases, with an attractive fast rate depending on the intrinsic dimension in our estimation. Our assumptions cover most scenarios in real applications and our results give rise to fast rates by exploiting low dimensional structures of data in operator estimation. We also investigate the influence of network structures (e.g., network width, depth, and sparsity) on the generalization error of the neural network estimator and propose a general suggestion on the choice of network structures to maximize the learning efficiency quantitatively.

97 MATHEMATICS AND COMPUTING↗

Design, construction and evaluation of a 12.2 GHz, 4.0 kW-CW coupled-cavity traveling wave tube

An analytical and experimental program to study design techniques and to utilize these techniques to optimize the performance of an X-band 4 kW, CW traveling wave tube ultimately intended for satellite-borne television broadcast transmitters is described. The design is based on the coupled-cavity slow-wave circuit with velocity resynchronization to maximize the conversion efficiency. The design incorporates a collector which is demountable from the tube. This was done to facilitate multistage depressed collector experiments employing a NASA designed axisymmetric, electrostatic collector for linear beam microwave tubes after shipment of the tubes to NASA.

Ayers, W. R.↗

Automatic phase control in solar power satellite systems

Various approaches to the problem of generating, maintaining and distributing a coherent, reference phase signal over a large area are suggested, mathematically modeled and analyzed with respect to their ability to minimize: phase build-up, beam diffusion and beam steering phase jitter, cable length, and maximize power transfer efficiency. In addition, phase control configurations are suggested which alleviate the need for layout symmetry.

Lindsey, W. C.↗

Bandwidth limitations on noiseless optical channel capacity

The channel capacity of an optical communications link utilizing direct photon detection can be substantially larger than the heterodyne detection quantum limit. In the limit of a noiseless channel the capacity per received photon can even be infinite. In most communications systems the real constraint is to deliver a certain throughput capacity measured in nats/second. The current investigation has the objective to show that due to physical limitations on the minimum time resolution which can be achieved, and for any given throughput capacity in nats/second, there exists an optimum PPM word size which maximizes the 'power efficiency capacity' expressed in nats/photon. Such an optimization will allow the system-designer to minimize the amount of power needed to achieve the desired throughput without violating his bandwidth constraint.

Butman, S. A.↗