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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 343 records · Page 19

A review on charged-particle transport modeling for laser direct-drive fusion

Inertial confinement fusion (ICF) with the laser-indirect-drive scheme has recently made a tremendous breakthrough recently after decades of intensive research effort. Taking this success to the next step, the ICF community is coming to a general consensus that laser direct-drive (LDD) fusion might be the viable way for enabling inertial fusion energy (IFE) and high-gain targets for other applications. Designing and understanding LDD fusion targets heavily rely on radiation-hydrodynamic code simulations, in which charged-particle transport plays an essential role in modeling laser-target energy coupling and bootstrap heating of fusion-produced α-particles. To better simulate charged-particle transport in LDD targets, over the past four decades the plasma physics community has advanced transport calculations from simple plasma physics models to sophisticated computations based on first-principles methods. In this review, we give an overview of the current status of charged-particle transport modeling for LDD fusion, including what challenges we still face and the possible paths moving forward to advance transport modeling for ICF simulations. We hope this review will provide a summary of exciting challenges to stimulate young minds to enter the field, facilitate further progress in understanding warm-dense matter physics, and ultimately bridge toward the success of reliable LDD fusion designs for IFE and other high-gain ICF applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of self-generated magnetic fields on x-ray emission in Kr-filled targets at the National Ignition Facility

We examine the effects of self-generated magnetic fields in a Kr gas pipe x-ray source platform. X-ray emission from Kr plasma is dependent on the plasma conditions, as the ionization state is largely a function of temperature. Magnetic fields are known to limit heat conduction, which increases temperature. We show that the emission in simulations of the gas pipe x-ray source is dependent on how self-generated magnetic fields are modeled. The inclusion of self-generated magnetic fields in simulations more accurately captures the emission of lower energy x-ray emission (L-shell), bringing results closer to experiments. The modeled x-ray emission and self-generated magnetic fields are shown to be particularly sensitive to the inclusion of the Nernst effect in simulations. Severely limiting the Nernst effect leads to a hotter Kr plasma, which can account for the discrepancy seen in earlier studies. By modifying the Nernst effect multiplier, we can achieve better experimental agreement in x-ray emission from gas pipes; the value of the multiplier that leads to the best agreement is dependent on the laser power of the drive. Currently, the suppression factor of the Nernst effect needed for high power drives (PL>200 TW) is more restrictive than what is currently put forward by non-local models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An experimentally informed design process for future inertial confinement fusion facilities

The achievement of ignition in the laboratory has renewed interest in defining the requirements for a future high-gain inertial confinement fusion (ICF) facility. Our best chance of predicting future ICF performance is with 3-D radiation hydrodynamic simulations that have been benchmarked against experimental data, but their high computational cost is prohibitive for use in practical design studies. We introduce a hierarchical approach where 3-D simulations are tuned to match experimental measurements and used to train 3-D degradation models in 1-D simulations allowing for accurate predictions over the entire OMEGA direct-drive database. A genetic algorithm was used in combination with the trained 1-D simulations to search for optimal direct-drive implosion designs at driver energies ranging from 20 kJ to 10 MJ. As the fidelity of 3-D codes improves, this approach will provide a viable experimentally informed tool for defining the next ICF facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transferable GeSn ribbon photodetectors for high-speed short-wave infrared photonic applications

We experimentally demonstrate a low-cost transfer process of GeSn ribbons to insulating substrates for short-wave infrared (SWIR) sensing/imaging applications. By releasing the original compressive GeSn layer to nearly fully relaxed state GeSn ribbons, the room-temperature spectral response of the photodetector is further extended to 3.2 μm, which can cover the entire SWIR range. Compared with the as-grown GeSn reference photodetectors, the fabricated GeSn ribbon photodetectors have a fivefold improvement in the light-to-dark current ratio, which can improve the detectivity for high-performance photodetection. The transient performance of a GeSn ribbon photodetector is investigated with a rise time of about 40 μs, which exceeds the response time of most GeSn (Ge)-related devices. In addition, this transfer process can be applied on various substrates, making it a versatile technology that can be used for various applications ranging from optoelectronics to large-area electronics. These results provide insightful guidance for the development of low-cost and high-speed SWIR photodetectors based on Sn-containing group IV low-dimensional structures.

42 ENGINEERING↗

SourceFinder: a Machine-Learning-Based Tool for Identification of Chromosomal, Plasmid, and Bacteriophage Sequences from Assemblies

High-throughput genome sequencing technologies enable the investigation of complex genetic interactions, including the horizontal gene transfer of plasmids and bacteriophages. However, identifying these elements from assembled reads remains challenging due to genome sequence plasticity and the difficulty in assembling complete sequences. In this study, we developed a classifier, using random forest, to identify whether sequences originated from bacterial chromosomes, plasmids, or bacteriophages. The classifier was trained on a diverse collection of 23,211 chromosomal, plasmid, and bacteriophage sequences from hundreds of bacterial species. In order to adapt the classifier to incomplete sequences, each complete sequence was subsampled into 5,000 nucleotide fragments and further subdivided into k-mers. This three-class classifier succeeded in identifying chromosomes, plasmids, and bacteriophages using k-mer distributions of complete and partial genome sequences, including simulated metagenomic scaffolds with minimum performance of 0.939 area under the receiver operating characteristic curve (AUC). This classifier, implemented as SourceFinder, has been made available as an online web service to help the community with predicting the chromosomal, plasmid, and bacteriophage sources of assembled bacterial sequence data (https://cge.food.dtu.dk/services/SourceFinder/).

59 BASIC BIOLOGICAL SCIENCES↗

Utah FORGE: Well 16B(78)-32 Drilling Data

This drilling data for Utah FORGE well 16B(78)-32 include a well survey, core summary, mud and mud temperature logs, daily reports of the drilling process, and additional data from the Pason oil and gas company. Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The proposed total depth was 10,658 feet, which was exceeded. Spudding began on April 26th, 2023. As of June 20th, 2023, the total depth measured 10,947 feet and the vertical depth measured 8,357 feet. Drilling included the trial use of insulated drill pipe (IDP) from Eavor Technologies, which was considered a success. IDP restricts counter-current heat transfer between drilling fluid inside the drill string and hotter returning fluid in the annulus, thereby ensuring the bottomhole assembly (BHA) remains submerged in cool fluid. Eavor rented 350 joints of IDP to FORGE which were run in two consecutive BHAs at the well. The results of this trial are included here.

15 GEOTHERMAL ENERGY↗

Predicting Thermal Excursions During in situ Oxidative Regeneration of Packed Bed Catalytic Fast Pyrolysis Catalyst

Ex situ catalytic fast pyrolysis (CFP) uses a secondary reactor to upgrade biomass pyrolysis vapors to stabilized CFP oils with reduced oxygen content. In one configuration, the secondary reactor is operated as a packed-bed swing reactor system which allows coke-deactivated beds to be decarbonized in situ while other beds remain online for vapor upgrading. In situ decarbonization must be done carefully to avoid irreversible deactivation and/or physical degradation of catalyst pellets. Given that packed bed reactors are well known to have poor heat transfer characteristics, this is a critical issue impacting scaleability and commercial viability of the technology. To predict thermal excursions during regeneration, finite element computational models have been built to assist in scaling up oxidative decarbonization of a Pt/TiO2 CFP catalyst (0.5 mm spheres) from a bench scale packed bed with 100 g of catalyst to a pilot scale packed bed with 2 kg of catalyst and internal cooling tubes. Based on transient measurements of outlet temperature and effluent CO2 concentration, and using an assumed coke profile and activation energy, this paper demonstrates that specific combinations of effective thermal conductivity and wall heat transfer coefficient can fit bench scale oxidative regeneration data equally well. For the upscaled 2 kg bed, four bench-scale “best fit” parameter pairs give different predictions for location and magnitude of thermal excursions, with the maximum computed bed temperature gradients ranging from 30 °C cm-1 to as high as 3000 °C cm-1. The larger the fraction of heat removal by conduction through the cooling tubes, the greater the differences between the parameter pairs. The modelling results presented in this paper cast doubt on the industrial viability of the proposed combination of catalyst, bed and regeneration process, and point to the need for alternate reactor designs. However, there is considerable uncertainly in some of the key model parameters. The reliability of model predictions can be increased by adding more temperature measurements at key bed locations, testing additional variations in process conditions, performing careful bed dissections to determine the true coke profile, and perhaps most importantly, directly measuring the effective thermal conductivity of the catalyst pellets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Acoustic Backscatter for In Situ Monitoring of Nuclear Sludge Wastes During Transfer - 20117

This paper presents an overview into the use of acoustic backscatter systems (ABS) for the in situ characterization of nuclear waste sludge concentration, size and aggregation, highlighting key achievements from the University of Leeds. Previous projects funded through the Engineering and Physical Sciences Research Council (EPSRC) UK and Innovate UK are firstly reviewed and linked to current research within the new TRANSCEND consortium. Detailed are a number of developments at various stages of technology readiness level, from the use of ABS to monitor small-scale sludge settling in columns, to large-scale jet-mixing and waste transfer operations. Current work with Sellafield Ltd will see new technology and world leading analysis methods deployed to measure the consolidation of complex wastes currently undergoing containment, the first time full industrial utilization of these systems has been achieved. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Radiative heat transfer in FLiBe molten salt participating medium in a vertical heated tube under forced and mixed convection laminar flows

The contribution of radiative heat transfer (RHT) to convective heat transfer in a heated vertical pipe with laminar flow and constant wall temperature, for FLiBe molten salt, is investigated computationally. The combined effects of conduction in the fluid, forced convection, buoyancy, temperature-dependent physical properties, and thermal radiation are investigated. The P1 approximation is employed in the discretization of the Radiative Transfer Equation (RTE). The COMSOL Multiphysics software is used to generate the numerical solutions. The theoretical analysis developed here demonstrates that only for intermediate values of the optical thickness, i.e. τ D ~ O 1 , the participating media effects are expected to be important. This analysis is confirmed computationally and a value of τ D ≈ 4 is shown to lead to the highest increase in overall heat transfer behavior. Under forced convection, the Nusselt ratio N u total / N u no - rad reaches a peak value of 1.76 at τ D = 4 and z/D = 200 , and is less than 1.1 for τ D < 0 . 1 and τ D > 60 . Under aiding-flow mixed convection, N u total / N u no - rad reaches a peak of 1.34 at τ D = 4 . 2 and is less than 1.1 for τ D < 0 . 4 and τ D > 36 . Under opposing-flow mixed convection, Nu total / Nu no - rad reaches a peak of 1.81 at τ D = 4 . 2 and is less than 1.1 for τ D < 0 . 2 and τ D > 50 . RHT effects on the overall heat transfer are most pronounced in opposing mixed convection, where N u total / N u no - rad is 2.26 observed at z/D = 50 . The sensitivity to wall emissivity is evaluated; in forced convection, the peak N u total / N u no - rad is 1.66 at ε = 0 (reflective wall) and 2.04 at ε = 1 (absorptive wall). Finally, the sensitivity to pipe diameter is also discussed. Overall, for a vertical heated tube, radiative heat transfer effects lead to enhancement of heat transfer by as high as a factor of two, and they depend on the optical thickness of the flow, mixed convection environment ( Gr / R e 2 and direction of flow relative to the gravitational force), surface emissivity, and entrance effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nanoprobe Based Information Processing: Nanoprobe‐Electronics

Abstract With computational architectures becoming data‐centric and with the rise of in‐memory computing, the role of memory will be ever more crucial. In turn, storing massive amount of data demands for ultra‐low power and non‐volatile types necessitating new memory technologies. Here, a controllable nanoelectromechanical (NEM) spin memory is proposed for compact nonvolatile memory arrays. It combines the advantages of both nanomechanical and spin‐transfer torque (STT) magnetic memory devices to overcome fundamental scalability roadblocks of non‐hybrid alternatives. The hybrid system paves the way to a new memory technology in the regime of sub‐10‐nm lateral size with a sub‐1‐MA cm −2 switching energy.

Yi, Bao↗

Qualification and Commissioning of Helium Flow Loop Experiment for Blanket Design Measurements

Sufficient cooling of plasma-facing materials remains an outstanding challenge in the design of fusion reactor blankets in commercial power demonstration plants. Due to its chemical inertness and low neutron interaction cross section, pressurized helium is a candidate coolant fluid for such systems; however, helium has a small thermal mass compared to liquid coolants, potentially reducing heat removal performance. To address this need, a number of heat transfer enhancements have been proposed to improve the cooling efficiency of such components, thereby decreasing pumping power needs and improving overall plant efficiency. Toward this end, a helium flow loop experiment (HFLE) has been designed and commissioned to test advanced passive heat transfer enhancements in unit-cell test sections, providing necessary data for model validation and subsequent system design. The HFLE is designed to provide flow of pressurized (up to 4 MPa) helium at flow rates up to 80 g/s, enabling heat transfer and pressure drop measurements in test pieces at Reynolds numbers in excess of 180 000. To explore the effects of novel and complex heat transfer enhancements, test sections are produced via additive manufacturing, providing geometries not typically obtainable by conventional machining. Here in this work, we present results from HFLE commissioning and the initial thermal-hydraulic tests of an additively manufactured rifled-rib test section. Results are compared to smooth pipe correlations, and plans are described for future HFLE measurements. These preliminary experiments indicate the utility of the HFLE for heat transfer enhancement testing and simulation validation activities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental Study on the Transfer of Cs, Sr, Pu and Water in Concrete for the Estimation of Contamination - 20085

As part of the 'Nuclear Energy Science and Technology and Human Resources Development project- through concentrating wisdom-by MEXT' in Japan, the major results from the second year of a project on the analysis of radionuclide contamination mechanisms of concrete and the estimation of contamination distribution at the Fukushima Daiichi nuclear power station active during 2018-2020 are presented. The transfer of Cs, Sr, Pu, and water through concrete was studied experimentally. In a saturated condition, the clay did not affect the transfer and Cs penetrated much faster than Sr. In the dried condition, clay retarded Cs transfer. Carbonation of the concrete retarded the transfer of Cs and Sr. Pu was expected to be precipitated immediately in a high pH condition of concrete. Water suction depends on the temperature. Further, the detailed mechanism was analyzed by {sup 1}H-NMR. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Right Transfer Access Control Model of Internet of Things Based on Smart Contract

Sensor nodes play a crucial role in the promotion of development of Internet of Things (IoT). Through this transaction, RO defines access control policies in script form based on ABAC's access control model to grant access right. The identity of all users in the model is identified by address. This paper builds a more flexible right transfer access control model by means of combining the Attribute-Based Access Control model (ABAC) and blockchain technology. Owing to the characteristics of ABAC’s attributes and right association, the massive problems of some sensor nodes can be solved. At the same time, for the sake of addressing the dynamic problems such as node access and right transfer, right transfer contract (TS) and access control contract (CS) are employed on the chain to ensure efficient and safe transmission of rights. To solve on-chain storage problems and ensure transparency of the operation, the idea of Rollup in Ethereum expansion is used to upload the final state of protocol policy and right exchange to the chain. Any user can know the policy and current right transfer status at any time. Finally, comparative and security analysis show that the model presented here can solve IoT devices’ massive and dynamic problems more effectively and it is more secure than the traditional models.

Wang, Jiuru↗

Compatibility of LaFe13−x−yMnxSiyH1.6 and Eutectic Liquid GaInSn Alloy

The heat transfer rate of magnetocaloric regenerators is a topic of extensive research and the cyclability of these regenerators is critical to the operation of systems with a high coefficient of performance (e.g., potentially >22, significantly higher than typical vapor compression cooling technologies). To enable a high operating frequency that will result in a high specific cooling power, the heat transfer fluid should have high thermal conductivity and lower specific heat, i.e., higher thermal diffusivity. Eutectic metal alloys possess these qualities, such as gallium–indium–tin (Galinstan), whose thermal diffusivity has been found to be approximately an order of magnitude higher than water. For this study, the effects of eutectic liquid Galinstan exposure on the phase stability of LaFe13−x−yMnxSiyH1.6 magnetocaloric powders in an active magnetic regenerator device were investigated. The powders were characterized before and after exposure to Galinstan using X-ray diffraction, in which the phases were determined using the Rietveld refinement technique and X-ray fluorescence. It was found that after Galinstan exposure, hydrogen containing phases were present in the powder, suggesting that the hydrogen was lost from the magnetocaloric phase. The magnetocaloric phase degradation indicates that the powder was incompatible with the Galinstan metal in an environment with moisture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transferable Reinforcement Learning for Smart Homes: Preprint

To harness the great amount of untapped resources at the demand side, smart home technology plays a vital role in solving the "last mile" problem in smart grid. Reinforcement learning (RL), which has demonstrated an outstanding performance in solving many sequential decision-making problems, can be a great candidate to be used in smart home control. For instance, many studies have started investigating the load scheduling problem under dynamic pricing scheme. Based on those, this study aims at providing an affordable solution to encourage a higher smart home adoption rate. Specifically, we investigate combining transfer learning (TL) with RL to reduce the training cost of an optimal RL control policy. Given an optimal policy for a benchmark home, TL can jump-start the RL training of a policy for a new home, which has different appliances and user preferences. Simulation results show that by leveraging TL, RL training converges faster and requires much less computing time for new homes that are similar to the benchmark home. In all, this study proposes a cost-effective approach for training RL control policies for homes at scale, which ultimately reduces the controller's implementation costs, increases the adoption rate of RL controllers, and makes more homes grid-interactive.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

Levelized cost and carbon intensity of solar hydrogen production via water splitting using a scalable and intrinsically safe photocatalytic Z-scheme raceway system

Generating hydrogen from local energy resources such as solar or wind would unlock a low-carbon energy carrier that could be used to reduce greenhouse gas emissions in sectors such as industry and transportation. Yet, the allocation of new or existing power generation solely to hydrogen production remains contentious due to disputes regarding emissions accounting. Photocatalytic (PC) hydrogen production technologies offer a unique solution, as hydrogen is produced directly from solar energy and water, without the need for electricity generation. However, cost projections for all photocatalytic designs to date have suggested that they are not cost competitive compared to conventional electrolysis systems manufactured at scale. Herein, we offer the first illustrative benchmark of cost and carbon intensity of hydrogen produced in a type 2 “Z-scheme” photocatalytic reactor design, which employs suspended semiconducting nanoconductor particles organized into two stacked volumes in a raceway design. The “Z-scheme” system utilizes two separate photoabsorber particles, tuned to drive either the hydrogen evolution reaction or the oxygen evolution reaction individually, connected via a reversible, charge transfer redox couple in solution. Furthermore, the results suggest a highly competitive and scalable technology, that justifies further experimental validation and prototyping in the field.

Carbon↗

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

Heat Transfer Characteristics of Particle Flow Through Additively Manufactured (SS 316L) Lattice Frame Material Based on Octet-Shape Topology

Abstract This paper presents experimentally obtained heat transfer characteristics of additively manufactured lattice frame material based on Octet-shaped unit cell. Binder jetting technology was used to print lattices in Stainless Steel 316L material. Lattice porosities ranging from 0.75 to 0.9 were investigated where thermal transport characteristics were obtained for void space occupied by air and particles. Particle diameters were varied from 266–966 microns. Effective thermal conductivity and averaged heat transfer coefficient was calculated through steady-state experiments. It was found that presence of lattice enhances the effective thermal conductivity by 2–4 times when compared to packed bed of particles alone. Furthermore, for gravity-assisted particle flow through lattice panel, significantly high convective heat transfer coefficients ranging from 200–400 W/m2K were obtained for the range of particle diameters tested. The superior thermal transport properties of Octet-shape based lattice frame material for particle flow through them makes it a very promising candidate for particle-to-supercritical carbon dioxide (sCO2) heat exchanger in concentrating solar power (CSP) application.

Aider, Youssef↗