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At least 1,135 records · Page 63

Glow Discharge Boronization and Real-Time Boronization Using an Impurity Powder Dropper in LHD

In the Large Helical Device (LHD), boronization is utilized for wall conditioning, employing two distinct methods: glow discharge using diborane gas and the injection of boron powder into the plasma via an impurity powder dropper (IPD). Glow discharge boronization is conducted after maintenance when the vacuum vessel is exposed to air and just before the start of an experimental campaign. In contrast, real-time boronization using the IPD is performed during discharges. The distribution of boron on plasma-facing components was assessed through long-term material probes in the case of glow discharge and through numerical simulations for the IPD method. Results indicated non-uniform boron distributions in both cases. The impact of these boronization techniques on impurity levels and the lifetime of their effects were also examined. Both methods effectively reduced oxygen and iron in the plasma, with the iron impurities originating from the first wall. For glow discharge boronization, the reduction in oxygen levels persisted until the end of the experimental campaign, whereas the reduction in iron levels only lasted a few days. In the case of boron injection during long pulse discharges exceeding 200 s, the suppression of oxygen and iron was observed. The effect on iron quickly diminished within several seconds after the injection ended, whereas the effect on oxygen lasted more than 100 s. The difference in the lifetimes of the boronization effects is further discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electrochemically driven phase transformation for high-efficiency heat pumping

To reduce energy consumption and improve energy utilization in space conditioning, advanced heat pumping technologies are needed. The chemical looping heat pump (CLHP) is a promising thermodynamic cycle that has theoretically shown the potential to achieve a cooling coefficient of performance (COP c ) increase of over 20% relative to conventional vapor compression systems. In this paper, the key process of the CLHP is experimentally demonstrated, and the system performance and non-ideal behavior are predicted using the component-level models. The results show the feasibility of electrochemical phase change of a working fluid; the peak COP c was 7.64 with a cooling capacity of 3.6 mW (cooling density of 2.57 W m -2 ) at both sink and source temperature of 23°C based on laboratory experiments. The COP c can theoretically reach up to 13 at a temperature lift of 15°C as long as an electrochemical cell can achieve a greater degree of conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calibration and Initial Results of Space Radiation Dosimetry Using the iMESA-R

The integrated Miniaturized Electrostatic Analyzer-Reflight (iMESA-R) is a space weather instrument designed to measure plasma density, temperature, and spacecraft charging, along with total ionizing dose and dose rate. A constellation consisting of five nearly identical instruments has been designed and developed to act as science payloads hosted on-board Department of Defense satellites operating in low-Earth orbit. To validate the dosimetry component of the iMESA-R, a radiation test study was performed to calibrate the dosimeter and ascertain the attenuation due to the instrument aluminum housing. An 80 curie Cobalt-60 radioisotope source emitting beta, X-ray, and gamma ray radiation decay products was used to calibrate the dosimeter response as a function of distance and instrument shielding. We present results of the calibration study along with initial on-orbit data presented from the first operational iMESA-R hosted on-board Space Test Program Satellite 5 in a polar Earth orbit. The initial on-orbit data demonstrate the ability to map the radiation environment, particularly the South Atlantic Anomaly and the auroral regions using total ionizing dose rate due to electrons of E > 1.5 MeV and protons of E > 25 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗

Investigating structure and dynamics of unentangled poly(dimethyl- co -diphenyl)siloxane via molecular dynamics simulation

Polysiloxane is one of the most important polymeric materials in technological use. Polydimethylsiloxane displays glass-like mechanical properties at low temperatures. Incorporation of phenyl siloxane, via copolymerization for example, improves not only the low-temperature elasticity but also enhances its performance over a wide range of temperatures. Copolymerization with the phenyl component can significantly change the microscopic properties of polysiloxanes, such as chain dynamics and relaxation. However, despite much work in the literature, the influence of such changes is still not clearly understood. In this work, we systematically study the structure and dynamics of random poly(dimethyl- co -diphenyl)siloxane via atomistic molecular dynamics simulations. As the molar ratio Φ of the diphenyl component increases, we find that the size of the linear copolymer chain expands. At the same time, the chain-diffusivity slows down by over an order of magnitudes. In conclusion, the reduced diffusivity appears to be a result of a complex interplay between the structural and dynamic changes induced by phenyl substitution.

36 MATERIALS SCIENCE↗

Effects of laser-annealing on fixed-frequency superconducting qubits

As superconducting quantum processors increase in complexity, techniques to overcome constraints on frequency crowding are needed. The recently developed method of laser-annealing provides an effective post-fabrication method to adjust the frequency of superconducting qubits. In this work, we present an automated laser-annealing apparatus based on conventional microscopy components and demonstrate preservation of highly coherent transmons. In addition, we perform noise spectroscopy to investigate the change in defect features, in particular, two-level system defects, after laser-annealing. Finally, we present a local heating model as well as demonstrate aging stability for laser-annealing on the wafer scale. Our work constitutes an important step toward both understanding the underlying physical mechanism and scaling up laser-annealing of superconducting qubits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development and validation of fully open-source R2S shutdown dose rate capabilities in OpenMC *

We present the first fully open-source capabilities for shutdown dose rate (SDR) calculations of fusion energy facilities based on the Rigorous 2-Step (R2S) methodology. These capabilities have been implemented in the OpenMC Monte Carlo particle transport code, building on its existing capabilities while also leveraging new features that have been added to the code to support SDR calculations, such as decay photon source generation. Each of the individual physics components in the R2S workflow—neutron transport, activation, decay photon source generation, and photon transport—have been verified through code-to-code comparisons with MCNP6.2 and FISPACT-II 4.0. These comparisons generally demonstrate excellent agreement between codes for each of the physics components. The full cell-based R2S workflow was validated by performing a simulation of the first experimental campaign from the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For short cooling times, the dose calculated by OpenMC agrees with the experimental measurements within the stated experimental uncertainties. For longer cooling times, an overprediction of the shutdown dose was observed relative to experiment, which is consistent with previous studies in the literature. Altogether, these features constitute a combination of capabilities in a single, open-source codebase to provide the fusion community with a readily-accessible option for SDR calculations and a platform for rapidly analyzing the performance of fusion technology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Constraints on Large-Scale White Noise in the Cosmic Density Field

We present observational constraints on large-scale white noise (LSWN) in the cosmic density field, a phenomenon predicted to arise from non-linear mode coupling during cosmological evolution. Building on the theoretical framework of Paper I, where we demonstrated that non-linearities inevitably redistribute power from small to large scales through mode mixing, we confront these predictions with current cosmological data. We modify the CLASS Boltzmann code to incorporate a white noise component $k_\mathrm{BH}/k$ in the primordial power spectrum and perform parameter estimation using current cosmological data. The non-detection of excess power on the largest observable scales places stringent upper bounds: $k_\mathrm{BH} \leq 1.80 \times 10^{-13}~\mathrm{Mpc}^{-1}$ at 99% confidence. These constraints imply the primordial power spectrum must deviate from perfect scale invariance on small scales, either through a cutoff at $k_{\mathrm{cut}} \lesssim 3~\mathrm{pc}^{-1}$ or through running of the spectral index with $α_s \lesssim -0.015$. Our results demonstrate that LSWN provides a powerful probe of the primordial spectrum at scales orders of magnitude smaller than directly observable, offering unique constraints on early-universe physics.

Barenboim, Gabriela [Valencia U., IFIC; Valencia U↗

Conditional Sixth-Harmonic Injection to Improve the Linear Modulation Range of Three-Phase Voltage-Source Converters

Overmodulation techniques are used to improve dc bus voltage utilization for three-phase voltage-source converters (VSCs), resulting in significant reduction in fundamental voltage gain. Conventional pulse width modulation (PWM) techniques for three-phase VSCs cannot enhance the linear range of dc bus utilization by more than 15.5%. Here, in this letter, a conditional sixth-harmonic injection technique is introduced, which can theoretically improve the linear modulation range by up to 19.2% for three-phase ac systems without additional hardware components. Experimental validation of the proposed scheme is presented, with its performance compared against the conventional third-harmonic PWM technique.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Heat Transfer and Pressure Loss of Additively Manufactured Internal Cooling Channels With Various Shapes

Abstract Additive manufacturing (AM) provides the ability to fabricate highly customized internal cooling passages that are relevant to gas turbine components. This experimental study examines the pressure loss and heat transfer performance of a range of fundamental channel shapes that were produced using direct metal laser sintering. Circular, hexagonal, pentagonal, elliptical, diamond, square, rectangular, trapezoidal, and triangular channel cross sections were investigated. To maintain the same convective surface area between shapes, the wetted perimeters of the channel cross sections were kept constant. Parallel computational fluid dynamic simulations were performed to understand the relationships in cooling performance between several channel shapes. Several characteristic length scales were evaluated to scale the pressure loss and heat transfer measurements. Among the channel shapes investigated, the diamond channel showed the lowest Nusselt number and friction factor. The pentagon exhibited a similar Nusselt number as the circular channel despite having a lower friction factor. There was no difference in scaling the friction factor or Nusselt number results of the different channel shapes between using the square root of cross-sectional area compared to hydraulic diameter as the characteristic length scale

Engineering↗

pnnl/JAX-CanVeg

Differentiable land surface model reimplementing an existing simulator, CANOAK, in JAX—a Google-developed Python package for high-performance machine learning research using automatic differentiation. The model's purpose is to perform hybrid land surface modeling that seamlessly couples process-based components with deep neural networks

Jiang, Peishi↗

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A robust and efficient generalized real cascade model

This paper describes a new separation cascade model that allows for arbitrary cascade connectivity and includes the effects of mixing, material losses and generalized separation element performance. The model also accommodates mixtures with an arbitrary number of component species. The mathematical and numerical framework of this model includes both time-dependent and steady state cascade simulation. Robust numerical approximations of the continuous mathematical model are accomplished using the Sundials suite of nonlinear algebraic and differential-algebraic equation solvers. Verification of the model is accomplished using manufactured solutions while validation is demonstrated by comparison to published experimental results and benchmarks.

36 MATERIALS SCIENCE↗

Understanding Plant Signaling Via Innovations in Probe Delivery and Imaging

The goal of this project was to develop tools for studying plant processes in living tissues. We wanted a method for introducing probes for studying plant processes such that plants could remain intact and imaged iteratively. Towards this end, we successfully optimized carbon nanofibers that we showed could deliver non-permeable signaling probes/biomolecules to plant cells. These were created on a rigid backing and also successfully transferred to a flexible backing to use with curved plant structures. We also built fiber optic microscopes that permit iterative non-destructive fluorescence or light micrographs and created protocols and devices to stabilize plant organs during imaging. These tools were developed in conjunction with research aimed understanding receptor-mediated peptide trafficking and responses relevant to plant cell growth and defense tradeoff. During this project, we designed and built two fiberoptic fluorescence microscopes; (b) designed, fabricated and validated different nanospike designs for delivering probes to plants, including the feasibility of delivering DNA constructs for expression studies; (c) developed fluorescent peptide probes (active and inactive versions of a secreted receptor ligand called phytosulfokine or PSK) and performed mobility tests after application to plants using microscopy; (d) used appropriate genetic plant backgrounds to facilitate PSK trafficking and response mechanisms; (e) determined the transcriptional changes due to PSK-induced signaling related to growth/defense tradeoff; (f) performed experiments showing the growth/defense tradeoff involves repression of specific defense components in response to PSK. This project also involved the training of two PhD students and five Masters students.

47 OTHER INSTRUMENTATION↗

Notes on Minimum Area for Radar Antenna

Perhaps no single radar component has a more profound effect on Synthetic Aperture Radar (SAR) performance than the antenna. Especially for spaceborne SAR, one particular common design constraint for the antenna is the minimum antenna area constraint. While useful, it relies on a number of assumptions and approximations that may not always be valid or applicable. Indeed, useful operational systems have been built and flown that do not strictly adhere to this constraint. A closer examination of this constraint yields insights into what the real limitations are, or might be.

42 ENGINEERING↗

Efficient, reliable and cost-effective reversible solid oxide cell technology for hydrogen and electricity production

This report summarizes the work performed by University of California San Diego (UCSD) – OxEon Energy LLC (OxEon) for the U. S. Department of Energy/National Energy Technology Laboratory (DOE/NETL) under Cooperative Agreement DE-FE0031940 entitled “Efficient, Reliable and Cost Effective Reversible Solid Oxide Cell Technology for Hydrogen and Electricity Production”. This reversible solid oxide cell (RSOC) technology has two main novel elements: (i) a compact and low-cost stack architecture that consists of multi-cell cell modules in electrical parallel and series connections and (ii) high performance and fuel-flexible reversible cells with electrodes or all components made by sputtering deposition process for efficient operation in both fuel cell (power generation) and electrolysis (hydrogen production) modes.

30 DIRECT ENERGY CONVERSION↗

Limits on Leptonic TeV Emission from the Cygnus Cocoon with Swift-XRT

$\gamma$-ray observations of the Cygnus Cocoon, an extended source surrounding the Cygnus X star-forming region, suggest the presence of a cosmic ray accelerator reaching energies up to a few PeV. The very-high-energy (VHE; 0.1-100~TeV) $\gamma$-ray emission may be explained by the interaction of cosmic-ray hadrons with matter inside the Cocoon, but an origin of inverse Compton radiation by relativistic electrons cannot be ruled out. Inverse Compton $\gamma$-rays at VHE are accompanied by synchrotron radiation peaked in X-rays. Hence, X-ray observations may probe the electron population and magnetic field of the source. We observed eleven fields in or near the Cygnus Cocoon with the Neil Gehrels Swift Observatory's X-Ray Telescope (Swift-XRT) totaling 110 ksec. We fit the fields to a Galactic and extra-galactic background model and performed a log-likelihood ratio test for an additional diffuse component. We found no significant additional emission and established upper limits in each field. By assuming that the X-ray intensity traces the TeV intensity and follows an dN/dE ∝ E -2.5 spectrum, we obtained a 90% upper limit of F X < 8.7 x 10 -11 erg cm -2 s -1 or 5.2 x10 -11 erg cm -2 s -1 on the X-ray flux of the entire Cygnus Cocoon between 2 and 10 keV depending on the choice of hydrogen column density model. This suggests that no more than one quarter of the $\gamma$-ray flux at 1 TeV is produced by inverse Compton scattering, when assuming an equipartition magnetic field of ~20 μG.

79 ASTRONOMY AND ASTROPHYSICS↗

Resilience Metrics Framework for Solar Photovoltaics

This presentation was given at the Photovoltaic Specialist Conference (PVSC) 54 in New Orleans, Louisiana. Photovoltaic (PV) systems are routinely exposed to extreme weather, including wind and hail storms. Historically, most systems have proven to be resilient to such events, but some storms have damaged PV systems, leading to physical and financial loss. Storm hardening measures and specific system attributes can reduce this risk. This work introduces a set of resilience metrics and a framework for quantifying, comparing, and predicting PV system resilience. The framework is divided into two parts: 1) predictive, attribute metrics based on site and component characteristics, and 2) impact metrics that assess post-storm performance. Metrics are weighted and aggregated, producing hazard-specific resilience scores. We derive damage functions from storm-impacted PV systems, establishing a baseline against which post-storm performance can be compared. This damage was widely variable across hail and wind intensities, and field hail damage was less than predicted by laboratory tests, suggesting that system features - in addition to storm conditions - influence damage likelihood. Finally, the metrics framework is demonstrated using three case studies of storm damaged PV systems. Although additional data are needed to create attribute specific damage functions and establish metric weights, this study presents a methodology for evaluating PV resilience and contributes new damage functions to the literature.

14 SOLAR ENERGY↗

A Data Quality-Aware Framework to Reliably Forecast Photovoltaic Generation and Consumer Load for an Improved Resilience of Microgrids

Photovoltaic (PV) power and consumer load forecasting plays a critical role to ensure operational resilience of the electric grid. Most data-driven forecasting algorithms rely heavily on the continuous availability of good quality data for periodic training and validation. When deployed at the grid’s edge, prolonged disruptions to communications during extreme events degrade data quality. Factors such as missing observations, epistemic uncertainties, data drift, and concept drift are manifestations of data quality that impact the generalization of such field-deployed forecasting models. Currently, there exists no mechanism in the literature to dynamically switch between models under varying degrees of data quality as quantified by certain metrics for each factor highlighted above. This paper addresses this shortcoming by conceptually introducing a data qualityaware framework for reliable PV generation and consumer load forecasting. The framework’s design incorporates components of missing values, divergence tests, and continuous monitoring of generalization performance to detect changes in data quality caused by communications disruptions and trigger specific classes of forecasting models grouped under three use cases (UC1- UC3). As a first step towards validating this framework, real data collected from an actual field microgrid system is used to demonstrate the viability of the three use cases. Results show that the performance is the best in UC1 with an unadjusted R-square value of 0.954, followed by 0.939 for UC2 and 0.757 for UC3.

Sundararajan, Aditya↗