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At least 469 records · Page 26

The Study on the Shock Wave Propagation Rule of a Gas Explosion in a Gas Compartment

Combined with the k-ε turbulence model of general application, a refined finite element model of a utility tunnel’s gas compartment filled with the methane/air mixture is developed. A series of analyses are made by using the powerful industry-leading computational fluid dynamics (CFD) software flame acceleration simulator (FLACS) to study the shock wave propagation rule in the gas compartment. The longitudinal and transversal distribution laws of the explosion shock wave are gained taking into consideration the spatial characteristics of the gas compartment. The influences of a few parameters, such as initial conditions and section size of the gas compartment, on the shock wave propagation rule are further discussed. The basic procedure for predicting the peak pressure of the blast wave is provided by considering the initial conditions and the gas compartment, and the corresponding injury effect of the explosion wave on the living beings is assessed. The investigation demonstrates that the peak pressure by the coupled effect between the initial conditions is significantly influenced, especially at the upper and lower gas explosion limits. The peak pressure increases gradually as the width or height increases, and both basically meet the linear relation. The proposed method can forecast the peak pressure of the explosion shock wave in the gas compartment accurately. According to the peak pressure longitudinal and transversal distributions of the blast wave, the peak pressure is far greater than the killing pressure threshold in the underground and closed space; consequently, it is not safe for the living beings in the gas compartment.

Lin, Shu-Chao↗

Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.

Farhat, Nabil H.↗

The radiative signature of the shock acceleration process in active galactic nuclei

A time-dependent model in which plasma enters a shock region and undergoes first-order Fermi acceleration is considered. The time evolution of the particle distribution and the associated synchrotron emission has been calculated for an energy-dependent diffusion coefficient. When the emitting region is not spatially resolved, the spectrum is a power law with an exponential turnover in frequency. With increasing time, the power law and the turnover extend to higher frequencies. To test the model, observations at three or more frequencies should be made of time-resolved flux increases from the optically thin nonthermal emission region in variable active galactic nuclei. Existing data that can be used to test the model are scarce but offer qualitative support.

Bregman, Joel N.↗

Simultaneous Extreme-Ultraviolet Explorer and Optical Observations of Ad Leonis: Evidence for Large Coronal Loops and the Neupert Effect in Stellar Flares

We report on the first simultaneous Extreme-Ultraviolet Explorer (EUVE) and optical observations of flares on the dMe flare star AD Leonis. The data show the following features: (1) Two flares (one large and one of moderate size) of several hours duration were observed in the EUV wavelength range; (2) Flare emission observed in the optical precedes the emission seen with EUVE; and (3) Several diminutions (DIMs) in the optical continuum were observed during the period of optical flare activity. To interpret these data, we develop a technique for deriving the coronal loop length from the observed rise and decay behavior of the EUV flare. The technique is generally applicable to existing and future coronal observations of stellar flares. We also determine the pressure, column depth, emission measure, loop cross-sectional area, and peak thermal energy during the two EUV flares, and the temperature, area coverage, and energy of the optical continuum emission. When the optical and coronal data are combined, we find convincing evidence of a stellar 'Neupert effect' which is a strong signature of chromospheric evaporation models. We then argue that the known spatial correlation of white-light emission with hard X-ray emission in solar flares, and the identification of the hard X-ray emission with nonthermal bremsstrahlung produced by accelerated electrons, provides evidence that flare heating on dMe stars is produced by the same electron precipitation mechanism that is inferred to occur on the Sun. We provide a thorough picture of the physical processes that are operative during the largest EUV flare, compare and contrast this picture with the canonical solar flare model, and conclude that the coronal loop length may be the most important factor in determining the flare rise time and energetics.

Hawley, Suzanne L.↗

Physical Processes for Driving Ionospheric Outflows in Global Simulations

We review and assess the importance of processes thought to drive ionospheric outflows, linking them as appropriate to the solar wind and interplanetary magnetic field, and to the spatial and temporal distribution of their magnetospheric internal responses. These begin with the diffuse effects of photoionization and thermal equilibrium of the ionospheric topside, enhancing Jeans' escape, with ambipolar diffusion and acceleration. Auroral outflows begin with dayside reconnexion and resultant field-aligned currents and driven convection. These produce plasmaspheric plumes, collisional heating and wave-particle interactions, centrifugal acceleration, and auroral acceleration by parallel electric fields, including enhanced ambipolar fields from electron heating by precipitating particles. Observations and simulations show that solar wind energy dissipation into the atmosphere is concentrated by the geomagnetic field into auroral regions with an amplification factor of 10-100, enhancing heavy species plasma and gas escape from gravity, and providing more current carrying capacity. Internal plasmas thus enable electromagnetic driving via coupling to the plasma, neutral gas and by extension, the entire body " We assess the Importance of each of these processes in terms of local escape flux production as well as global outflow, and suggest methods for their implementation within multispecies global simulation codes. We complete 'he survey with an assessment of outstanding obstacles to this objective.

Moore, Thomas Earle↗

Chorus Whistler Wave Source Scales As Determined From Multipoint Van Allen Probe Measurements

Whistler mode chorus waves are particularly important in outer radiation belt dynamics due to their key role in controlling the acceleration and scattering of electrons over a very wide energy range. The key parameters for both nonlinear and quasi-linear treatment of wave-particle interactions are the temporal and spatial scales of the wave source region and coherence of the wave field perturbations. Neither the source scale nor the coherence scale is well established experimentally, mostly because of a lack of multipoint VLF waveform measurements. We present an unprecedentedly long interval of coordinated VLF waveform measurements (sampled at 16384 s(exp -1)) aboard the two Van Allen Probes spacecraft-9 h (0800-1200 UT and 1700-2200 UT) during two consecutive apogees on 15 July 2014. The spacecraft separations varied from about 100 to 5000 km (mostly radially); measurements covered an L shell range from 3 to 6; magnetic local time 0430-0900, and magnetic latitudes were approximately 15 and approximately 5 deg during the two orbits. Using time-domain correlation techniques, the single chorus source spatial extent transverse to the background magnetic field has been determined to be about 550-650 km for upper band chorus waves with amplitudes less than 100 pT and up to 800 km for larger amplitude, lower band chorus waves. The ratio between wave amplitudes measured on the two spacecraft is also examined to reveal that the wave amplitude distribution within a single chorus element generation area can be well approximated by a Gaussian exp(-0.5 x r (exp 2)/r(sub 0)(exp 2)), with the characteristic scale r(sub 0) around 300 km. Waves detected by the two spacecraft were found to be coherent in phase at distances up to 400 km.

Agapitov, O.↗

End-to-end Modeling of Lyot Coronagraph for LUVOIR: Sensitivity to Segment-Level Aberrations

Direct imaging and spectroscopic characterization of atmospheres of Earth-like exoplanets require starlight suppression to detect a faint planetary signal at small angular separations. Future space telescopes will require segmentation to survey a statistically significant population of nearby stars systems by increasing aperture size beyond the limits set by traditional monolithic apertures; however, segmentation also represents an additional challenge due to the introduction of temporal pupil discontinuities in terms of both phase and amplitude. For this study, a baseline Lyot coronagraph is used with the Large UV / Optical /Infrared (LUVOIR) mission’s 15-m on-axis, segmented optical telescope assembly (OTA). We present a high-fidelity, end-to-end modeling approach developed as part of the Segmented Coronagraph Design and Analysis (SCDA) group that includes diffractive optical propagations at the 1e-10 contrast level across the entire optical train including the OTA and intermediate re-imaging optics inside the coronagraph instrument. We perform a tolerancing analysis to assess the contrast sensitivity to wavefront perturbations for a set of key telescope terms including segment-level low-order and mid-spatial frequency aberrations. As an input to the end-to-end telescope model, we use two industry-provided segment-level wavefront aberration datasets pertaining: (1) thermal gradients and accelerations (courtesy of Ball-Aerospace and L3-Harris), and (2) telescope dynamics including line-of-sight and segment jitter (courtesy of Lockheed-Martin). Contrast performance outputs of the coronagraph are fed into a mission design reference simulator to assess the scientific yield sensitivity. End-to-end modeling will incorporate performance improvements due to active wavefront sensing and control and/or segment-level metrology to improve system performance.

Optics↗

A generalizable machine learning approach to predict land surface temperature

Monitoring of land surface and atmospheric states is highly reliant on satellite data. Traditionally, data products are generated using carefully tuned and validated algorithms for low-earth orbit (LEO) sensors. However, the emerging constellation of geostationary (GEO) sensors contributes global, high temporal resolution observations which can better capture the diurnal variability of key observables like land surface temperature (LST). Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from LEO and GEO satellites to develop a deep learning-based method for sensor-to-sensor algorithm emulation. Our model is trained on GOES-16 thermal bands to predict MODIS Terra LST and achieves a validation error <2K. Further, application of the model to unseen times of day and a second GEO sensor observing an unseen spatial domain demonstrate the generalization of the deep learning model across space, time and spectra. We anticipate that the synergies between a variety of active orbit configurations can be used to accelerate application of existing algorithms to new datasets.

Kate Marie Duffy↗

Rapid Cloud Removal of Dimethyl Sulfide Oxidation Products Limits SO 2 and Cloud Condensation Nuclei Production in the Marine Atmosphere

Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of 60 DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth’s radiation balance and climate. Quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory towards sulfur dioxide (SO 2 ) and ultimately sulfate aerosol (Veres et al. 2020). Using direct airborne flux measurements, we demonstrate that irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime (τ HPMTF < 2 hours) and terminates DMS oxidation to SO 2 in the cloudy marine boundary layer. When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO 2 production from DMS is reduced by 35% globally and near surface (0-3km) SO 2 concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for conversion of DMS to sulfate, while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate.

dimethyl sulfide↗

Petermann Glacier on the Brink: Progress, Challenges and Insights

Petermann Glacier, the largest marine-terminating glacier in northern Greenland based on catchment area and ice discharge, plays a key role in regulating ice discharge from the Greenland Ice Sheet into the Arctic Ocean. With an upstream catchment connected to the ice sheet interior via a deep subglacial canyon, its future stability has major implications for sea level rise. In this review, we synthesize recent advances in understanding Petermann’s dynamics across three critical interfaces: the ice–ocean, ice–atmosphere, and ice–bed boundaries. At the surface, observations show that reanalysis products underestimate air temperatures and melt, while regional climate models diverge significantly in their estimates of surface mass balance, underscoring the need for improved in situ data and models. At the ocean boundary, enhanced basal melting driven by both subglacial runoff and Atlantic water intrusions is identified as the dominant driver of recent mass loss of Petermann Glacier, with continued warming posing a serious threat to the stability of the floating tongue. At the bed, new geophysical synthesis reveals complex geology, likely spatial variability in geothermal heat flux, and the influence of the megacanyon on seasonal hydrology and velocity fluctuations. Petermann’s mass balance has been negative in recent decades without corresponding flow acceleration. However, the glacier has undergone significant calving events, and the current rifting that began in September 2025 highlights its vulnerability. This upcoming calving event underscores the timeliness of this review, as it will put Petermann Glacier’s terminus at its most retreated position since records began in 1923. The anticipated retreat of the ice tongue also reduces buttressing and brings the terminus closer to the grounding zone, and modeling studies suggest that calving within 12 km of the grounding zone could potentially trigger dynamic retreat, accelerating ice discharge, and a doubling of flow speeds. We conclude that improved observations, sustained monitoring of oceanographic and atmospheric properties, and high-resolution modeling are critical to constraining projections of Petermann Glacier’s future and its role in the stability of the Greenland Ice Sheet.

Dominik Fahrner↗

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

Acceleration of electrons outside flares - Coronal manifestation and possible origin

Imaging observations at decimetric and metric wavelengths of the solar corona are used to investigate a short-lasting noise storm and the associated changes of the underlying active-region plasma. It is shown that a new source appears in the active region in close temporal and spatial coincidence with the onset of the noise storm in the middle corona. The onset of the noise storm is delayed at longer wavelengths. At a given wavelength, the noise-storm source undergoes a systematic slow movement with a significant component perpendicular to the magnetic-field lines above the active region. The observations are tentatively attributed to the emission of nonthermal electrons in a system of expanding coronal loops, the expansion being initiated by the appearance of the new 21-cm source in the low atmosphere. The derived velocity of expansion is about 80 to 150 km/s. The electrons emitting the noise storm cannot be provided by the high-energy tail of the Maxwellian in the new active region source, but originate either from a nonthermal population in this source or from acceleration at higher altitudes, in the structures which give rise to the noise storm.

Raulin, J. P.↗

IER 501: Pulsed Neutron Die-Away Experiments at LLNL [Slides]

Pulsed neutron die away experiments occur as follows: (1) a pulse of neutrons is injected into a target material via a D-T neutron generator, (2) neutrons thermalize, (3) neutrons spatially equilibrate, and (4) exponential decay is measured in fundamental mode.

43 PARTICLE ACCELERATORS↗

Multitarget Rydberg gates via spatial blockade engineering

Multi-target gates offer the potential to reduce gate depth in syndrome extraction for quantum error correction. Although neutral-atom quantum computers have demonstrated native multi-qubit gates, existing approaches that avoid additional control or multiple atomic species have been limited to single-target gates. We propose single-control-multi-target CZ^n gates on a single-species neutral-atom platform that require no extra control and have gate durations comparable to standard CZ gates. Our approach leverages tailored interatomic distances to create an asymmetric blockade between the control and target atoms. Using a GPU-accelerated pulse synthesis protocol, we design smooth control pulses for CZZ and CZZZ gates, achieving fidelities of up to 99.55% and $99.24\%$, respectively, even in the presence of simulated atom placement errors and Rydberg-state decay. Our approach is most effective for N=2 (CZZ) and N=3 targets (CZZZ); for larger N, increasing spatial crowding of the targets introduces significant challenges for maintaining the required blockade asymmetry. This work presents a practical path to implementing low-overhead multi-target gates in single-species neutral-atom systems, significantly reducing the resource overhead for syndrome extraction. To motivate the impact of these gates, we apply a greedy scheduling algorithm and we demonstrate that our proposed gates can reduce the number of atom reconfiguration costs by up to 50% for color code syndrome extraction of code distances greater than 5.

Stein, Samuel A.↗

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗

The Role of Topography in Controlling Evapotranspiration Age

Abstract Evapotranspiration (ET) age is a key metric of water sustainability but a major unknown partly due to the extreme difficulty in modeling it. Groundwater is found to be important in ET age variations in small‐scale studies, yet our understanding is insufficient because groundwater systems are nested across scales. Here, we conducted GPU‐accelerated particle tracking with integrated hydrologic modeling to quantify the variations in ET age at a regional scale of ∼0.4 M km 2 . Simulation results reveal topography‐driven flow paths shaping the spatial and temporal patterns of ET age variations. On ridges, where root zone decoupling with deep subsurface storage, ET age is generally young, with seasonal variations dominated by meteorological conditions. In the valley bottom, ET age is generally old, with significant subseasonal variations caused by the convergence of subsurface flow paths. On hillslopes with water table depths ranging from 1 to 10 m, ET age shows strong seasonal variations caused by the connections with lateral groundwater regulated by ET demand. Our modeling approach provides insights into the basic linkages between ET age and topography at large scale. Our work highlights the perspective of multiscale studies of ET age, suggesting new field experiments to test these process connections and to determine if such linkages warrant inclusion in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

LICS Modeling [Slides]

We propose to design a new diagnostic based on laser inverse Compton scattering (LICS) to study the dynamics of runaway electron formation during killer-pellet triggered disruptions in DIII-D, and their subsequent loss. Obtaining a better understanding of transient runaway electrons (and how to suppress them) is one of the highest priorities of the US fusion program. To enable this, we need better measurements of the runaway electron population during and after disruptions. We intend to measure point-wise time-resolved spatial profile and energy distributions of the runaway electrons while they are in the core of the tokamak plasma. While LICS measurements of relativistic e-beams have been successfully made on accelerators, they have never been done in a tokamak. We bring two innovations to this diagnostic concept which should enable 10 times better signal-to-noise ratios than previously envisioned. In particular, we will marry bright short pulse (10’s of picosecond) laser technologies with the availability of short-pulse gated x-ray imagers developed at Los Alamos for the National Ignition Facility (NIF), to reject noise generated by the tokamak and plasma environment. We will generate a Conceptual Physics Basis, a Preliminary Design, and a Final Design package, with associated DIII-D reviews, along with prototype component testing for the diagnostic over the course of the two year duration of this proposal.

42 ENGINEERING↗

WIRE-21 Sensor Irradiation Experiment Ready for HFIR Insertion

The ability to deploy new nuclear fuels for current or future reactor concepts requires a wealth of data regarding fuel performance during normal operation, anticipated operational occurrences, and design-basis accidents. Most of these data have historically been collected during experiments in materials test reactors, ideally with online instrumentation to collect as much data as possible. However, advanced instrumentation could also allow for in situ monitoring of fuel operating conditions during commercial reactor operation to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator understanding of limiting peaking factors. The latter approach would complicate fuel handling, particularly during refueling, unless the instrumentation could be placed inside the fuel rods and transmitted wirelessly to a receiver located outside the fuel’s primary pressure boundary. To this end, Westinghouse Electric Company (WEC) developed wireless sensors based on inductive coupling that can transmit information regarding fuel centerline temperatures and rod internal pressures wirelessly from within a fuel rod to a nearby instrument thimble. After testing these sensors in lower-power university research reactors, the next step is to perform high neutron fluence testing to characterize the performance of these wireless sensors under conditions that are more representative of the intended application—in this case, light-water reactors (LWRs). The removable Be (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) provide the neutron flux, experiment volume, and access to instrument leads required to achieve these sensor testing goals. This report summarizes the design, analysis, and assembly of the Wireless Instrumented RB Experiment 2021 (WIRE-21). This is the most highly instrumented irradiation experiment ever performed in HFIR. The experiment will use seven different sensing techniques to measure temperature, pressure, neutron flux, and neutron fluence during reactor operation. In addition to WEC’s wireless temperature and pressure sensors, WIRE-21 includes an array of thermocouples, self-powered neutron detectors, spatially distributed fiber optic temperature sensors, passive SiC temperature monitors, and flux wires. The design of WIRE-21 and the cabling that was installed in HFIR also provide the infrastructure to enable accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting component temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) that would be expected in the plenum region of LWR fuels, except for the active sensing region of the wireless temperature sensor, which is targeting LWR fuel centerline temperatures (~800–1,100°C). WIRE-21 was successfully assembled, passed all nondestructive examination, and was delivered to HFIR for insertion during upcoming cycle 498 (April 2022).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗