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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 19 records

Efficient proactive vehicle relocation for on-demand mobility service with recurrent neural networks

One major challenge for on-demand mobility service (OMS) providers is to seamlessly match empty vehicles with trip requests so that the total vacant mileage is minimized. In this work, we develop an innovative data-driven approach for devising efficient vehicle relocation policy for OMS that (1) proactively relocates vehicles before the demand is observed and (2) reduces the inequality among drivers' income so that the proactive relocation policy is fair and is likely to be followed by drivers. Our approach represents the fusion of optimization and machine learning methods, which comprises three steps: First, we formulate the optimal proactive relocation as an optimal/stable matching problems and solve for global optimal solutions based on historical data. Second, the optimal solutions are then grouped and fed to train the deep learning models which consist of fully connected layers and long short-term memory networks. Low rank approximation is introduced to reduce the model complexity and improve the training performances. Finally, we use the trained model to predict the relocation policy which can be implemented in real time. We conduct comprehensive numerical experiments and sensitivity analyses to demonstrate the performances of the proposed method using New York City taxi data. Here, the results suggest that our method will reduce empty mileage per trip by 54-70% under optimal matching strategy, and a 25-32% reduction can also be achieved by following stable matching strategy. We also validate that the predicted relocation policies are robust in the presence of uncertain passenger demand level and passenger trip-requesting behavior.

33 ADVANCED PROPULSION SYSTEMS↗

AMAROK: A Radio Frequency Development Platform for High-Power, Full-Scale Positive Ion Sources for DIII-D Neutral Beam Injectors

Next-generation neutral beam injection (NBI) systems demand RF ion sources capable of efficiently coupling >120 kW at 2–4-MHz frequencies, yet existing designs face voltage standoff and impedance-matching challenges. To address this, the advanced multicoil antenna for RF operations at kilowatts (AMAROK) was developed as a high-power RF inductively coupled plasma (ICP) source delivering up to 200 kW in the 2–4-MHz range via four phase-controlled generators for flexible power sharing. Two antenna designs—a single-strap multiturn (MT) and a multistrap single-turn (ST) design—were evaluated to optimize resonance, impedance matching, and power coupling across plasma loads. Here, a semi-analytical self-resonant frequency (SRF) model, validated experimentally, predicts resonance trends for arbitrary turn counts and tubing diameters, enabling rapid antenna optimization. Strap-to-strap mutual inductance in the ST configuration showed strong spatial dependence, guiding generator operation and total load inductance. These insights informed a custom π -topology matching network, achieving stable impedance matching over a wide range of plasma-driven loads. Collectively, these results position AMAROK as a versatile testbed for advancing high-power RF source technology in fusion NBI applications.

DIII-D↗

Phase-stabilized 2D/3D hetero-bilayers via lattice matching for efficient and stable inverted solar cells

2D-on-3D (2D/3D) perovskite heterostructures with engineered energy landscapes offer the potential to realize efficient and stable inverted solar cells. However, managing the energy landscape using 2D perovskites with thicker inorganic layers n > 1 necessitates the usage of the chemically unstable methylammonium MA + . Here, we synthesized formamidinium (FA)-rich and pure-FA n = 3 Ruddlesden-Popper (RPP) and Dion-Jacobson perovskite (DJP) single crystals by identifying ligands with suitably lattice-matched organic and inorganic components of the 2D lattice. These crystals were translated onto 3D perovskites as capping layers, forming 2D/3D hetero-bilayers (HBs). Degradation studies revealed that HBs with butylammonium-based RPPs as capping layers rapidly phase segregate into non-perovskites under combined extrinsic stressors, compromising the underlying 3D layer, whereas FA-rich DJPs based on 3-aminomethylpiperidine retain their phase stability. The DJP HBs also possess a favorable energy landscape and electron transport at the 2D/3D interface, enabling inverted solar cells with a champion PCE of 25.33% and remarkable stability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Stable CdTe Photoanodes with Energetics Matching Those of a Coating Intermediate Band

Here, a TiO 2 coating was grown on a CdTe absorber by atomic layer deposition for stabilization against its photocorrosion during photoelectrochemical water splitting. Under simulated sunlight (AM 1.5G, 100 mW cm –2 ), this multilayer CdS/CdTe/TiO 2 /Ni/NiO x photoanode produced a light-limited photocurrent density of 24.5 ± 0.5 mA cm –2 and a photovoltage of 780 ± 20 mV. This record energy-conversion performance was comparable to those of baseline CdS/CdTe solar cells and was achieved only after the development of proper CdTe surface treatments prior to coating the stabilization layer. The TiO 2 coating, with its in-gap charge-transport intermediate band, facilitates hole transport as light exits the CdTe/TiO 2 interface. With proper interfacial chemistry, the electrochemical potential energy of the coating intermediate band matched that of the CdTe valence band. Moreover, the stabilized CdS/CdTe/TiO 2 /Ni/NiO x photoanodes showed 100 h stability for water oxidation under light-on/light-off cycles. This study provides insightful guidance for designing stabilization contacts for efficient and stable light-driven water oxidation.

14 SOLAR ENERGY↗

Activation of Lattice and Adatom Oxygen by Highly Stable Ceria-Supported Cu Single Atoms

Requiring catalysts to be both active yet stable over long periods of time under variable reaction conditions including high and low temperatures is a daunting challenge due to the almost mutual exclusivity of these constraints. Using CO oxidation as a probe reaction, in this work we demonstrate that thermally stable single atom copper catalysts prepared by high temperature synthesis (atom trapping) on ceria can achieve this feat by allowing modulation of the Cu charge state through facile charge transfer between active site and support. This provides the catalysts with an ability to activate either lattice or adatom oxygen atoms, accessing additional reaction channels depending on the reaction conditions. Such adaptability allows dynamic response of catalysts enabling them to remain active under variable reaction conditions. The inherent stability of the catalyst arises from the enhanced strength of the Cu-O interactions from high temperature synthesis that exist even when Cu oxidation state varies, which retards sintering and deactivation. As we show here, one can circumvent the dilemma of designing catalysts that are simultaneously active and stable by matching the redox properties of the active site and support and establishing an environmental adaptability around the active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Climate Patterns Using Clustering Autoencoder Techniques

Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k -means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k -means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.

Kurihana, Takuya↗

Broadband and Tunable Microwave Absorption Properties from Large Magnetic Loss in Ni–Zn Ferrite

Highly effective electromagnetic (EM) wave absorber materials with strong reflection loss (RL) and a wide absorption bandwidth (EBW) in gigahertz (GHz) frequencies are crucial for advanced wireless applications and portable electronics. Traditional microwave absorbers lack magnetic loss and struggle with impedance matching, while ferrites are stable, exhibit excellent magnetic and dielectric losses, and offer better impedance matching. However, achieving the desired EBW in ferrites remains a challenge, necessitating further composition design. In this study, impedance matching is successfully enhanced and EBW in Ni–Zn ferrite is broadened by successive doping with Mn and Co , without incorporation of any polymer filler. It is found that Ni 0.4 Co 0.1 Zn 0.5 Fe 1.9 Mn 0.1 O 4 material exhibits exceptional EM wave absorption, with a maximum RL of −48.7 dB. It also featured a significant EBW of 10.8 GHz, maintaining a 90% absorption rate (RL < −10 dB) for a thickness of 4.5 mm. These outstanding properties result from substantial magnetic losses and favorable impedance matching. These findings represent a significant step forward in the development of microwave absorber materials, addressing EM wave pollution concerns within GHz frequencies, including the frequency band used in popular 5G technology.

36 MATERIALS SCIENCE↗

Strain localization criteria for viscoplastic geomaterials

This report presents a viscoplastic localization criterion to detect quasi-instantaneous (i.e., load-induced) and delayed (creep-induced) strain localization in rate-dependent solids. The study is based on the theory of controllability and a viscoplastic description of the mechanical response. Analytical precursors of unstable states are defined through systems of ordinary differential equations (OEDs). The use of the proposed criteria is illustrated at the material point level through a set of strain localization analyses simulating active strain localization of a porous rock. In addition, full-field finite element simulations of compression tests conducted under various pressures are reported to demonstrate the role of local unstable viscoplasticity in the spontaneous propagation of deformation bands under stationary boundary conditions. The study shows that the viscoplastic localization criterion maintains a negative sign as long as the behavior is unstable, that is, the rate of deformation is accelerating. The sign switch coincides with the transition to decelerating deformation. The analyses revealed that pulses of overstress always emerge in correspondence with the growth of unstable behavior, and the peak matches the transition to stable behavior. The local responses recovered from full-field analyses were consistent with those observed in analyses at material point level and the predictions of the presented theory.

36 MATERIALS SCIENCE↗

Standardizing a Renewed Fission Product Yield Library and Related Covariances (Part II)

A complete library of independent fission product yields including covariance information was generated by a sequential Bayesian methodology whose prior information consisted of independent fission product yields and branching ratios of the possible decay modes reported in the recently released ENDF/B-VIII.0 nuclear data library. The Bayesian procedure consisted in the adjustment of independent fission product yields to match the set of stable and long-lived cumulative yields reported in the ENDF/B-VIII.0 nuclear data library which, in this work, were considered as legacy values together with their uncertainties. According to the χ 2 -metric, the results obtained by this methodology show a systematic improvement in the agreement with legacy reported cumulative yields for the entire adjusted independent fission product yield library.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Compound refractive lenses for X-rays

Compund refractive lenses are primarly used for focusing and transport of X-rays and for forming a stable optical cavity and mode matching to maximize FEL gain [1]. In this report, we cover focusing behavior and effects of curvature of compound refractive lenses on X-ray beam propagation. Our analysis is limited to X-ray beams with transverse Gaussian profile and is thus purely analytical in nature.

43 PARTICLE ACCELERATORS↗

Computation and Comparison of the Stable Northeastern US Marine Boundary Layer

In this work we investigate the behavior of stable marine boundary layers located near the coast of the Northeastern United States. Using the ExaWind large eddy simulation (LES) codes, three stable atmospheric conditions were chosen to match the Cape Wind measurements of Archer et al. with wind speeds of 5 m/s, 10 m/s, and 15 m/s at the 20 m measurement height. The behavior of the stable boundary layers, including mean flow quantities and turbulent statistics, are examined and compared to previous computations of the neutral and unstable offshore boundary layer at the same location. This study also examines the domain and mesh requirements necessary to capture the turbulent scales for the stable offshore boundary layers. Finally, we compare solutions computed using both Nalu-Wind and AMR-Wind solvers, and compare their predicted solutions and performance in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Status of the Slow Extraction Commissioning for the Mu2e Experiment at Fermilab

We present the current status of slow-extraction commissioning for the Mu2e experiment at Fermilab. The system employs third-integer resonant extraction of 8 GeV protons from the Delivery Ring to deliver a uniform, slow-spilled beam to the production target. During recent commissioning periods, we achieved stable optics, reproducible injection and energy matching, and consistent multi-spill operation. The sextupole circuits and fast-ramping quadrupoles were exercised near nominal resonance conditions, yielding promising extraction performance. A prototype spill-regulation system based on the ARIA-10 SoC was commissioned with integrated diagnostics, demonstrating closed-loop operation and establishing the framework for PID- and RFKO-based control. These commissioning results lay the foundation for achieving precision-regulated, high-quality slow extraction in upcoming Mu2e operations.

Narayanan, A. [Fermilab]↗

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Abstract. Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds often significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, as of the Weather Research and Forecasting model v4.3.3, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. We simulate a wind plant in pseudo-steady states under idealized stable, neutral, and unstable conditions with matching hub-height wind speeds using two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, average hub-height wind speed losses within the plant differ between PBL schemes by between −0.20 and 0.22 m s−1, and correspondingly, capacity factors range between 39.5 %–53.8 %. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.

17 WIND ENERGY↗

A provably stable numerical method for the anisotropic diffusion equation in confined magnetic fields

We present a novel numerical method for solving the anisotropic diffusion equation in magnetic fields confined to a periodic box which is accurate and provably stable. We derive energy estimates of the solution of the continuous initial boundary value problem. A discrete formulation is presented using operator splitting in time with the summation by parts finite difference approximation of spatial derivatives for the perpendicular diffusion operator. Weak penalty procedures are derived for implementing both boundary conditions and parallel diffusion operator obtained by field line tracing. We prove that the fully-discrete approximation is unconditionally stable. Discrete energy estimates are shown to match the continuous energy estimate given the correct choice of penalty parameters. A nonlinear penalty parameter is shown to provide an effective method for tuning the parallel diffusion penalty and significantly minimises rounding errors. Several numerical experiments, using manufactured solutions, the “NIMROD benchmark” problem and a single island problem, are presented to verify numerical accuracy, convergence, and asymptotic preserving properties of the method. Finally, we present a magnetic field with chaotic regions and islands and show the contours of the anisotropic diffusion equation reproduce key features in the field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced Anode for Internal Reforming and Thermal Management in Solid Oxide Fuel Cells

Solid oxide fuel cell (SOFC) is an efficient and clean electrical power generation system compared to conventional combustion based technologies with energy efficiency reaching as high as 85-90% in co-generation mode (electricity and heat). Other advantages of SOFCs are hybridization, modularity of construction, small CO 2 foot print per kWh of generated electricity and fuel flexibility. Hydrocarbons present in the gaseous fuel is utilized in SOFCs by internal or external reforming. There are two different internal reforming concepts: Direct Internal Reforming (DIR) and Indirect Internal Reforming (IIR). For DIR operation, the endothermic reforming reaction and the exothermic reaction from the oxidation reaction are operated together in the single unit eliminating the requirement for a separate fuel reformer. This configuration also simplifies the overall system design, making SOFC more attractive and efficient means of producing electrical power. The main advantage of the DIR type of operation is that the H 2 or CO consumption by the electrochemical reaction could directly promote the conversion of methane at the anode side of the fuel cell resulting in high conversion and high efficiency. The DIR operation, however, requires an anode material that has desired dual catalytic (hetero and electro) properties for reforming reaction and electrochemical reactions. The anode materials also need to remain resistant to carbon formation at the operating temperature and atmosphere with stable cell performance. Another requirement is to match the reforming reactions and electrochemical reactions to avoid local cooling or overheating, which can result in mechanical failure due to thermally induced stresses. Direct internal reforming (DIR) of hydrocarbon fuels simplifies the overall SOFC system design making it more attractive and efficient for producing electrical power. Low cost alloy anodes for distributed internal reforming of methane and other hydrocarbon fuels offer increased fuel-flexibility, reliability, and long term performance stability of solid oxide fuel cells (SOFC). The research program examined modification of the chemical compositions and microstructure of high entropy alloy (HEA) anode materials using thermochemical calculations and process simulation and modeling to achieve distributed reforming over the entire anode to eliminate hot zones. Cell fabrication and testing of the HEA anodes using button cell configuration has been performed to demonstrate the advantages of new anode over traditional Ni-YSZ anodes for distributed reforming and carbon free operation. Technical accomplishments include identification and synthesis of HEA carbon-resistant anode, demonstration of reduction in reforming rate confirmed by GC and modelling data validating effectiveness for thermal management in cell/stacks, electrochemical testing of HEA anode in single cell (HEA-GDC||YSZ||LSM-YSZ) and Characterization of pretest and posttest anode materials by TEM and SEM-EDS confirming carbon-free operation.

30 DIRECT ENERGY CONVERSION↗

Foundations for high-order, conservative cut-cell methods: Stable discretizations on degenerate meshes

Cut-cell methods for unsteady flow problems can greatly simplify the grid generation process and allow for high-fidelity simulations on complex geometries. However, cut-cell methods have been limited to low orders of accuracy. This is driven, largely, by the variety of procedures typically introduced to evaluate derivatives in a stable manner near the highly irregular embedded geometry. Here, a completely new approach, termed TEMO (truncation error matching and optimization), is taken to solve this problem. The approach is based on two simple and intuitive design principles. These principles directly allow for the construction of stable 8th To the best of the authors' knowledge, these are the highest orders ever achieved for a cut-cell discretization by a significant margin. This is done for both explicit and compact finite differences and is accomplished without any geometric transformations or artificial stabilization procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lean-Stratified Combustion System with Miller Cycle for Downsized Boosted Application - Part 2

Automotive manufacturers relentlessly explore engine technology combinations to achieve reduced fuel consumption under continued regulatory, societal and economic pressures. For example, technologies enabling advanced combustion modes, increased expansion to effective compression ratio and reduced parasitics continue to be developed and integrated within conventional and hybrid propulsion strategies across the industry. Here, a high-efficiency gasoline engine capable for use in conventional or hybrid electric vehicle platforms is highly desirable. This paper is the second of two papers describing the multi-cylinder integration of a technology package combining lean-stratified combustion with Miller cycle for downsized boosted applications. The first paper describes the design, analysis and single-cylinder testing conducted to down-select the combustion system deployed to the multi-cylinder engine. This paper defines a light-duty engine package capable of achieving a 35% fuel economy improvement at US Tier 3 emission standards over a naturally aspirated stoichiometric baseline vehicle. A multi-mode combustion system was developed enabling highly efficient lean-stratified operation at light-load and stoichiometric Miller-cycle operation at mid- to high-loads. A central direct-injection four-valve layout was designed with high-tumble ports and a bowl-in-piston capable of stable operation under highly dilute mixtures when properly matched to fuel spray characteristics, injection strategy, and a high-energy ignition system. Boost system layout and base engine architecture were selected to minimize parasitics and maximize after treatment effectiveness. A multi-cylinder engine was developed and calibrated over a steady-state map. Results fed vehicle simulations over the EPA city and highway test cycles to predict the fuel economy improvement and tailpipe emissions potential. Fuel economy improvements over the baseline vehicle were projected at 42% and 39% for active-urea and passive-ammonia SCR after treatment systems respectively. Controls complexity to achieve regulatory compliance and the cost of the lean after treatment system were identified as the primary challenges to commercial viability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗