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At least 559 records · Page 31

Asteroseismic Inversions of Mixed Acoustic-Gravity Modes to Probe the Stellar Core Structure

The discovery of mixed acoustic-gravity modes of oscillations of moderate mass stars opens a unique opportunity to infer the structure of the inner energy-generating cores and thus test the stellar evolution theory. The mixed modes have properties of internal gravity waves (g-modes) in the convectively stable helium core and properties of acoustic modes outside the core. We select several sets of the oscillation mode frequencies in the mass range from about 1.3 to 1.6 solar masses from the Kepler Legacy database, and apply the optimally localized averaging inversion technique previously developed for low-degree helioseismology. The inversion technique takes into account the uncertainties in the determination of the mass and radius of the stars, as well as the surface effects. The methodology provides sensitivity kernels for various structure properties, including the sound speed, density, and Ledoux parameter of convective stability, and, thus, the direct relationship between the stellar properties and the deviation of observed frequencies from the reference models. The inversion results reveal significant deviations in the core structure from the reference models calculated using the MESA evolutionary code for the stellar parameters obtained by the asteroseismic model grid fitting. Our analysis shows that the best resolution of the inner helium core and surrounding shell is achieved in inversions for the Ledoux parameter.

SMD↗

An Approach to Evaluating the Impact of Small-Core Turbofan Technologies on Engine and Aircraft Performance

NASA’s Hybrid Thermally Efficient Core (HyTEC) project aims to accelerate the development of small-core turbofan engine technologies to enable a fuel burn reduction of 5 to 10 percent for next-generation aircraft, compared to 2020s best-in-class technology. This paper presents a demonstration of methods for evaluating the potential performance impact of small-core engine technologies developed under Phase 1 of the HyTEC project. The approach involves model-based systems analysis, where small-core innovations are integrated into baseline turbofan and aircraft systems models, creating a notional vision system. Performance of the vision system is examined at both the engine and vehicle level. The examined performance metrics include: engine bypass ratio, overall pressure ratio, high pressure compressor exit corrected mass flow, and aircraft fuel burn. The CFM LEAP-1B28 and Boeing 737 MAX 8 are chosen as the baseline state-of-the-art systems. Preliminary results map a design space for the small-core vision system and quantify the distinct effects of technologies on the key metrics.

Michael A Bennett↗

Core Body Temperature Predictions Using Metabolic Energy Expenditure and Heart Rate During Simulated Extravehicular Activity

Long duration spaceflight missions will require crew to become more autonomous in conducting extravehicular activities (EVA) without direct communication with Mission Control for biomedical support. To enable such autonomy, we are developing a Crew State and Risk Model (CSRM) as a collection of key physiology domains that drive EVA crew capabilities and workloads. One model component of CSRM is human thermal regulation. In this paper, customized development of a baseline model to predict core body temperature is presented using physiology inputs of heart rate and metabolic rate. The model development dataset included a baseline study where participants (n=6, equal male and female) performed a 5-hour EVA in a two-part session while wearing a hybrid space suit simulator (HS3). The first session included an end-to-end EVA traversing 1500 meters to a geology site and traversing back to a habitat conducting geology, payload relocation, and maintenance operations every 500 meters. The second session included standalone tasks of a 2000-meter traverse followed by geology tasks. Thermal measures of core body temperature, local skin temperature, liquid cooling garment temperature, heart rate, and metabolic rate were collected through the test duration. Multiple regression was used to build a linear equation to predict core body temperature from inputs of heart rate and metabolic rate. Heat storage was calculated via predicted core body temperature plus LCG and skin temperatures. The model was tested against a dataset from a pressurized suited test (n=6, equal male and female) in the NASA Active Response Gravity Offload System (ARGOS) conducting similar end-to-end EVA and standalone tasks. Predicted error of the model against the raw test cases was 0.2±0.15 °C. The baseline prediction of core body temperature using heart rates and metabolic rates allows for simple real-time tracking from data collected in-flight to monitor crew consumables and thermal flight limits during EVA.

Bradley Hoffmann↗

An Approach to Evaluating the Impact of Small-core Turbofan Technologies on Engine and Aircraft Performance

NASA’s Hybrid Thermally Efficient Core (HyTEC) project aims to accelerate the development of small-core turbofan engine technologies to enable a fuel burn reduction of 5 to 10 percent for next-generation aircraft, compared to 2020s best-in-class technology. This paper presents a demonstration of methods for evaluating the potential performance impact of small-core engine technologies developed under Phase 1 of the HyTEC project. The approach involves model-based systems analysis, where small-core innovations are integrated into baseline turbofan and aircraft systems models, creating a notional vision system. Performance of the vision system is examined at both the engine and vehicle level. The examined performance metrics include: engine bypass ratio, overall pressure ratio, high pressure compressor exit corrected mass flow, and aircraft fuel burn. The CFM LEAP-1B28 and Boeing 737 MAX 8 are chosen as the baseline state-of-the-art systems. Preliminary results map a design space for the small-core vision system and quantify the distinct effects of technologies on the key metrics.

Michael Bennett↗

NASA Hybrid Thermally Efficient Core (HyTEC) Project Overview

The HyTEC Project goal is to mature compact core aircraft engine technologies as part of the NASA-led Sustainable Flight National Partnership (SFNP) that contributes to the United States Aviation Climate Action Plan goal for aviation net zero carbon emissions by 2050. Individual technologies were proposed and defined by industry partners, and then selected technology maturation activities are cost shared. Phase 1 contracts were awarded in 2021, and since then, the project has matured numerous technologies to TRL 4-5. Some of the Phase 1 efforts have been completed with successful results. An initial systems analysis study has been completed to estimate the impact of Phase 1 technologies against project performance metrics, with results indicating significant progress is being made toward meeting those metrics. HyTEC will culminate with an engine core demonstration that will integrate many of the Phase 1 technologies into a large-scale integrated ground demonstration that will achieve TRL 6 to enable industry to transition the technologies into the next single-aisle engine architecture. The goal of the demonstration is to fully meet the project performance metrics that define a compact engine core with substantial improvements in efficiency, durability, performance, hybridization, and sustainability over the baseline established in the year 2020. HyTEC will also incorporate hybrid electric technology into the engine core with the intention to bring the first electrified turbofan engines into production. The core demonstration has been awarded with a cost-share partnership and is planned to occur by the end of 2028.

Anthony L Nerone↗

Fully integrated multi-phase buck converter with coupled air core inductors

A multi-phase buck switching converter having grouped pairs of phases, each phase using two magnetically coupled air-core inductors. For each group, a first driver circuit controlling switching of a first power transistor switching circuit coupled to a first air-core inductor output for driving an output load at the first phase. A second driver circuit controlling switching of a second power transistor switching circuit coupled to a second air-core inductor output for driving said output load at the second phase. The first and second phases are spaced 180° apart. The coupled air-core inductors per group of such orientation, separation distance and mutual inductance polarity relative to each other such that magnetic coupling between the two or more inductors at each phase results in a net increase in effective inductance per unit volume. Each air-core inductor is a metal slab of defined length, height and thickness formed using back-end-of-line semiconductor manufacturing process.

Zhang, Xin↗

The effect of barrier films and exposure on the aging of vacuum insulation panels with fumed silica cores

Vacuum insulation panels have very low thermal conductivities compared to conventional insulation materials. The reduction of the core pressure significantly lowers gas phase conduction and overall thermal conductivity. As a consequence, increases in gas pressure can significantly increase thermal conductivity of the VIP. In addition, the thermal conductivity of the core is sensitive to moisture content. For vacuum insulation panels with fumed silica cores, work shows that the measured thermal conductivity increases by 0.5 x 10-3 W/mK per mass percent increase in water content [1]. This is significant since the thermal conductivity of vacuum insulation panels with fumed silica cores is in the range of 0.004 W/mK. This work investigates the long-term behavior of vacuum insulation panels comprised of fumed silica cores with polymer (ethylene vinyl alcohol) and metalized (aluminized) barrier films exposed to different exposure conditions: ambient conditions; exterior conditions in a mixed humid climate; and 24oC and 80 percent relative humidity. Results show that the increase in thermal conductivity is more pronounced for vacuum insulation panels made using polymer barrier films compared to the same panel protected by a metalized film. The increase is more pronounced when exposed to high relative humidity, 80 percent. After almost two years exposure, the decrease in thermal conductivity for vacuum insulation panels protected by a metalized barrier films are between 4 and 11 percent depending on exposure condition. The smallest decrease is for ambient conditions where the largest decrease is for exposure to 80 percent relative humidity. Similar behavior was observed for panels protected using polymer films, except the decrease in thermal conductivity was significantly higher, between approximately 20 and 60 percent, in the same order as for panels protected by metalized films. Measurements are ongoing with an attempt to develop a better relationship between these types of tests and vacuum insulation panel service life.

Aldykiewicz Jr, Antonio↗

Multi-core high-temperature, irradiation-resistant thermocouple, and related methods

A multi-core thermocouple includes a plurality of wires, an insulation core surrounding the plurality of wires, a sheath surrounding the insulation core, and a plurality of electrical junctions. The plurality of electrical junctions may include a first electrical junction formed between a first wire of the plurality of wires and the sheath at a first axial mid-section of the multi-core thermocouple, the first electrical junction including a first swaged axial mid-section of the sheath and a second electrical junction formed between a second wire of the plurality of wires and the sheath at a second, different axial mid-section of the multi-core thermocouple, the second electrical junction including a second swaged axial mid-section of the sheath.

Skifton, Richard S.↗

FunMC^2: A Filter for Uncertainty Visualization of Marching Cubes on Multi-Core Devices

Visualization is an important tool for scientists to extract understanding from complex scientific data. Scientists need to understand the uncertainty inherent in all scientific data in order to interpret the data correctly. Uncertainty visualization has been an active and growing area of research to address this challenge. Algorithms for uncertainty visualization can be expensive, and research efforts have been focused mainly on structured grid types. Further, support for uncertainty visualization in production tools is limited. In this paper, we adapt an algorithm for computing key metrics for visualizing uncertainty in Marching Cubes (MC) to multi-core devices and present the design, implementation, and evaluation for a Filter for uncertainty visualization of Marching Cubes on Multi-Core devices (FunMC2). FunMC2 accelerates the uncertainty visualization of MC significantly, and it is portable across multi-core CPUs and GPUs. Evaluation results show that FunMC2 based on OpenMP runs around 11× to 41× faster on multi-core CPUs than the corresponding serial version using one CPU core. FunMC2 based on a single GPU is around 5× to 9× faster than FunMC2 running by OpenMP. Moreover, FunMC2 is flexible enough to process ensemble data with both structured and unstructured mesh types. Furthermore, we demonstrate that FunMC2 can be seamlessly integrated as a plugin into ParaView, a production visualization tool for post-processing.

Wang, Jay↗

Study of effect of PWR cold leg temperature gradient on reactor core condition

Effects of temperature and flow gradients in Westinghouse designed three-loop Pressurized Water Reactor (PWR) cold legs, the piping between the main coolant pump and the reactor vessel, were evaluated using Computational Fluid Dynamics (CFD) code STAR CCM+ and coupled neutronic and thermal-hydraulic (T/H) code system VERA. In the parametric study, several symmetric and asymmetric temperature gradients that were significantly larger than those observed from plant measurements were applied to the cold leg inlets for comparison with the base case without any temperature gradient. A CFD model using the STAR-CCM+ code was developed for a portion of the RCS region between the Reactor Coolant Pump (RCP) and the core inlet based on previously validated modeling approach. The CFD simulation results were processed for the temperature and flow rate distributions at the core inlet as input to the VERA calculations. The VERA code system consists of COBRA-TF (CTF) for thermal-hydraulics, MPACT for reactor physics and neutron transport, and ORIGEN for isotopic depletion. The VERA model was for depletion calculations of a high-burnup loading pattern with the reactor core in pin-by-pin and subchannel resolution. The results of the study indicate that the postulated temperature gradients within the PWR cold legs do not result in any significant changes in the core inlet temperature distributions and the core power distributions during the reactor operation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Flattening the Radial Temperature Profile across the Transformational Challenge Reactor Core

The Transformational Challenge Reactor (TCR) program is demonstrating an agile development approach to advanced nuclear reactor design, which has traditionally utilized a linear design process. In leveraging artificial intelligence, additive manufacturing, advanced materials, and cutting-edge modeling and simulation, the TCR program aims to minimize the high cost and lengthy deployment timelines now standard in the nuclear industry. Within a relatively short period of time, a robust and mature advanced gas-cooled reactor was iteratively designed under the TCR program, using these cutting-edge technologies. The TCR is a 3 MWt gas-cooled microreactor fueled with uranium nitride (UN) tristructural isotropic (TRISO) fuel particles. Though manufactured via traditional means, these UN TRISO particles are loaded into additively manufactured silicon carbide (SiC) cans [4]. Once loaded with TRISO particles, the SiC cans are densified using a chemical vapor infiltration process. The additively manufactured SiC enables significantly more freedom in the design of the fuel form than could ever be achieved using traditionally manufactured SiC. The helium coolant, pressurized to 5 MPa, enters the core at 300°C and nominally exits it at 500°C. Typically, the most thermally limiting components in any reactor design are the fuel assemblies in the core center. To provide a wide thermal margin in these central fuel assemblies, the flow may be biased toward the center of the core to more effectively cool these fuel assemblies with more power deposition and flatten the core’s radial temperature distribution. An analytical fluid model of the TCR core was developed to explore methods for biasing the flow away from the cooler outer fuel assemblies and towards the hotter inner ones. Higher-fidelity models developed in STAR-CCM+ 2020.3.1, a computational fluid dynamics code, were then utilized to verify the analytical model’s findings.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Equilibrium Core Model for Micro Pebble Bed Reactors Using OpenMC

Estimating the equilibrium state for pebble bed reactors (PBRs) presents complex challenges as it requires simultaneous consideration of changes in the pebbles’ movement as well as their fuel compositions. Whereas traditional approaches use multigroup diffusion codes for neutronics calculations of PBRs’ equilibrium state, the double-heterogeneity of PBRs complicates neutron cross-section generation. Continuous-energy Monte Carlo (MC) methods are better suited for detailed PBR analysis because of their natural handling of double-heterogeneity, but they demand substantially more computational resources. Here, this study introduces a novel method for efficiently estimating the equilibrium state in small and micro PBRs with reduced computational cost. The method is anticipated to accelerate the processes of core design and performing parametric studies for utilizing advanced fuel and structural materials. The HTR-10 reactor design was used for validating the method’s predictions and evaluating its computational efficiency. When compared to reference calculation values from the literature, criticality (k-effective) was predicted to be approximately within the margin of error of the MC transport calculation, average core power density (in megawatts per cubic meter) was predicted within 2.5% relative error, and maximum thermal flux (10 13 n/cm 2 .s −1 ) was predicted within 1.8% relative error. The calculated inventory of fission products and fuel composition in the equilibrium core were within 15% and 16.6%, respectively, when compared to reported values from the literature. The difference is attributed to variance in the considered values of the core temperature, which was found to significantly affect the depletion analyses.

Equilibrium core↗

On dysprosium utilisation in multi-main-phase Nd–Dy–Fe–B magnets with core–shell microstructures

The development of high-performance Nd–Dy–Fe–B magnets that minimise the consumption of the scarce rare earth (RE) element Dy remains a major global scientific and technological quest. Here, we designed an alloy microstructure comprising of a uniform Dy-lean core–Dy-rich shell in a series of multi-main-phase (MMP) Nd–Dy–Fe–B magnets. The resulting MMP Dy1 and Dy3 magnets with an overall Dy level of 1 and 3 wt.% possessed values of 0.48 and 0.29 T/wt.% of coercivity increment per unit weight percentage of the Dy addition, respectively. Most importantly, the resulting MMP Dy3 magnet exhibited a high coercivity (2.38 T), an excellent thermal stability of the coercivity (|β| = 0.531%/°C), a high squareness factor (> 95%), all with little diminishment in the remanent magnetisation (1.35 T) and maximum energy product (43.6 MGOe). These properties are superior to the currently available sintered Nd–Dy–Fe–B magnets which utilise higher levels of Dy of 5 wt.%. Via magnetic and multi-scale microstructural characterisation experiments and micromagnetic simulations, the formation of the Dy-lean core–Dy-rich shell microstructure is rationalised via solid-state-diffusion and solution reprecipitation during liquid-phase sintering. The Dy-lean core–Dy-rich shell microstructure and the non-ferromagnetic low-Fe RE-rich grain boundary phase led to the synergistic magnetic performance. This is significant in the context of the MMP Nd–Dy–Fe–B magnets being applied to large-scale production. The present work establishes a pathway for the more sustainable utilisation of Dy in permanent magnets via formation of a uniform core–shell microstructure.

36 MATERIALS SCIENCE↗

Immobilization of cesium and iodine into Cs 3 Bi 2 I 9 perovskite-silica composites and core-shell waste forms with high waste loadings and chemical durability

Cs$_3$Bi$_2$I$_9$, a defect perovskite derivative, is a potential host phase to immobilize iodine and cesium with high waste loadings. In this work, two strategies were explored to form Cs$_3$Bi$_2$I$_9$-silica composites and a core-shell structure in order to improve chemical durability of waste form materials meanwhile maintaining high waste loadings. Cs$_3$Bi$_2$I$_9$ loadings as high as 70 wt.% were incorporated into a silica matrix to form silica-ceramic composites, and 20 wt.% Cs$_3$Bi$_2$I$_9$ was encapsulated into silica to form a core–shell structure by low temperature spark plasma sintering. Chemical durability of the composite and core-shell waste forms was evaluated by semi-dynamic leaching experiments, and Cs and I were incongruently released from waste form matrices. A BiOI alteration layer formed, acting as a passivation layer to reduce the release of radionuclides. The long-term iodine release rate was low (30 mg m$^{-2}$ day$^{-1}$) for the 70 wt.%Cs$_3$Bi$_2$I$_9$–silica composite leached in deionized water at 90 °C, which can be further reduced to 5 × 10$^{-3}$ mg m$^{-2}$ day$^{-1}$ for the 20 wt.% core-shell structure. This work highlights a robust way to immobilize the highly mobile radionuclides with high waste loadings through encapsulation into durable matrices and a surface passivating mechanism that can greatly reduce the elemental transport from waste form materials and significantly enhance their chemical durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Minimizing development costs for efficient many-core visualization using MCD3

Scientific visualization software increasingly needs to support many-core architectures. However, development time is a significant challenge due to the breadth and diversity of both visualization algorithms and architectures. With this work, we introduce a development environment for visualization algorithms on many-core devices that extends the traditional data-parallel primitive (DPP) approach with several existing constructs and an important new construct: meta-DPPs. We refer to our approach as MCD 3 — Meta-DPPs, Convenience routines, Data management, DPPs, and Devices. The twin goals of MCD 3 are to reduce developer time and to deliver efficient performance on many-core architectures, and our evaluation considers both of these goals. For development time, we study 57 algorithms implemented in the VTK-m software library and determine that MCD 3 leads to significant savings. For efficient performance, we survey ten studies looking at individual algorithms and determine that the MCD 3 hardware-agnostic approach leads to performance comparable to hardware-specific approaches: sometimes better, sometimes worse, and better in the aggregate. In total, we find that MCD 3 is an effective approach for scientific visualization libraries to support many-core architectures.

97 MATHEMATICS AND COMPUTING↗

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Core–Shell Gold Nanoparticle-Star Copolymer Composites with Gradient Transfer and Transport Properties: Toward Electro-Optical Sensors and Catalysis

A series of hybrid core–shell nanomaterials was prepared by solvent phase transfer methods with gold (Au) nanoparticles (NPs) as a core and star copolymers (h-PEI-b-PCL-Cbz) as a shell—consisting of hyperbranched polyethyleneimine (h-PEI) with different poly(ε-caprolactone) (PCL) chain lengths and a carbazole-contained terminating agent (Cbz). By varying the PCL chain length, these core–shell nanomaterials exhibited gradient energy transfer properties, surface hydrophobicity, electropolymerizability, and ionic probe transport and diffusion properties. The systematic copolymer formation was verified with quadruple-detector size exclusion chromatography (SEC) and 1H nuclear magnetic resonance (NMR). High-resolution atomic force microscopy-infrared spectroscopy (AFM-IR) chemical mapping verified nanoparticle-substrate adhesion and film formation. The design of these hybrid NPs and elucidation of gradient properties will be useful for future applications of the core–shell systems in electro-optical sensing and catalysis.

36 MATERIALS SCIENCE↗

Carbon Nanosphere-Encapsulated Fe Core–Shell Structures for Catalytic CO 2 Hydrogenation

In this work, we synthesized a unique carbon nanosphere (CNS)-encapsulated Fe core–shell catalyst (CNS–Fe) for CO 2 hydrogenation. The synthesized CNS–Fe catalyst exhibited a core–shell structure with a core of ca. 40 nm containing iron species and a shell thickness of ca. 10 nm composed of mainly graphitic carbon. X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermogravimetric analysis were used to characterize the fresh and spent CNS–Fe catalysts and reveal a mixture of Fe 3 O 4 , metallic Fe, and Fe 5 C 2 in the core and graphitic carbon as the shell with defect sites. Hydrogen temperature-programmed reduction, X-ray absorption near-edge structure, and extended X-ray absorption fine structure for the fresh CNS–Fe confirmed the composition of the iron species encapsulated in the CNS. The catalytic performance of CNS–Fe was investigated at ambient pressure for CO2 hydrogenation with hydrocarbons (CH 4 , C 2 –C 4 = , C 2 –C 4 0 ), and CO was observed as the main product.

36 MATERIALS SCIENCE↗