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DOE OSTI2012

Phased Array Ultrasonic Sound Field Mapping through Large-Bore Coarse Grained Cast Austenitic Stainless Steel (CASS) Components

A sound field beam mapping exercise was conducted to assist in understanding the effects of coarse-grained microstructures found in cast austenitic stainless steel (CASS) materials on acoustic longitudinal wave propagation. Ultrasonic laboratory measurements were made on three specimens representing four different grain structures. Phased array (PA) probes were fixed on each specimen surface and excited in the longitudinal mode at specific angles while a point receiver was scanned in a raster pattern over the end of the specimen, generating a transmitted sound field image. Three probes operating at nominal frequencies of 0.5, 0.8, and 1.0 MHz were used. A 6.4 mm (0.25-in.) thick slice was removed from the specimen end and beam mapping was repeated three times, yielding four full sets of beam images. Data were collected both with a constant part path for each configuration (probe, specimen and slice, angle, etc.) and with a variable part path (fixed position on the surface). The base specimens and slices were then polished and etched to reveal measureable grain microstructures that were compared to the sound field interactions and scattering effects seen in the collected data.

cast austenitic stainless steel↗

DOE OSTI2019

Evaluation of Low-cost, Full HD, CMOS Cameras for Use in the Calcine Retrieval Project - 19530

This paper describes results from radiation testing conducted on low-cost, commercial off-the-shelf, full high-definition (HD) resolution (1920 x 1080 p), complementary metal-oxide-semiconductor (CMOS) camera sensors. The purpose of the testing was to evaluate the sensors' suitability for use in the Calcine Retrieval Project by determining their image quality and life expectancy while operating in an ionizing radiation field of 20.0 Gy/h. The two camera sensors tested were the Axis FA1105 and Axis FA1125. These commercial camera sensors were designed for retail security surveillance and have no radiation-hardened (rad-hard) components. In addition to radiation testing, the sensors' field-of-view, resolution, and low-light image quality were tested at several target distances to ensure they meet project requirements. Testing was divided into two phases. During Phase 1, four FA1105 sensors and four FA1125 sensors were tested simultaneously without any shielding in radiation fields of 25.5 Gy/h and 49.3 Gy/h. In Phase 2, three FA1105 and five FA1125 sensors were shielded by 22.2 mm of lead and tested simultaneously in radiation fields of 26.8 Gy/h, 52.3 Gy/h, 143.0 Gy/h, 200.7 Gy/h, 404.6 Gy/h, and 2,317.5 Gy/h. Dose rate values were established using film dosimetry readings. Apertures in the shielding allowed for a 40-degree field of view while shielding all parts of the sensor except for directly in front of the CMOS sensor array. All testing was conducted at the Idaho Accelerator Center in Pocatello, Idaho, using a 450 keV X-ray generator. Sensor images were automatically captured at regular intervals throughout the testing for qualitative evaluation by the test team. Film dosimetry was placed near the sensors to record actual dose totals. The 450 keV setting generates X-ray radiation with an energy level close to the primary gamma energy level produced by the Cesium-137 isotope in the calcine, which is 662 keV. Results from Phase 1 indicate the sensors failed at an average cumulative dose of 226.3 Gy. For a given 20.0 Gy/h field this results in a mean time to failure (MTTF) of 11.3 hours. Recorded images from all sensors showed minimal image degradation due to radiation-induced noise. When the sensors finally failed, the failure mode was an abrupt loss of video. The image went black suggesting some other component in the sensor head besides the CMOS sensor array was responsible for the failure. During a portion of Phase 1 testing, a commercial, rad-hard camera was irradiated in the 25.5 Gy/h field along with the eight Axis FA series sensors. Image quality from the FA series sensors significantly outperformed the image quality of the rad-hard camera in radiation-induced noise tolerance, image resolution, and dynamic range. During Phase 2 testing, all sensors produced excellent images in radiation fields as high as 404.6 Gy/h. One FA1125 sensor was tested at the highest dose rate of 2,317.5 Gy/h. At this dose rate, the image was color shifted towards red and contained a significant amount radiation-induced noise. The sensor did not fail and was producing usable imagery after one hour, at which time the test was ended due to allotted beam-time at the test facility. Eighteen hours after X-rays were shut off, the sensor image returned to normal color and all eight sensors continued to operate without any visible, permanent image degradation. For Phase 2 testing, it was not possible to establish a MTTF since none of the shielded sensors failed during the allotted test time. However, given the highest cumulative dose of 4,142.1 Gy received by a shielded FA1125 sensor, a minimum life expectancy of 207 hours (8.6 days) is predicted while operating in a 20.0 Gy/h field. Test results indicate the radiation tolerance of the FA series sensor's CMOS array, along with the small form factor, full HD image quality, wide dynamic range, and Ethernet standard makes it suitable for short-term use in monitoring and visually documenting waste remediation efforts for the Calcine Retrieval Project at the INL. The sensor's low-cost of about $140 US, compared to commercial rad-hard cameras costing between $5,000 and $7,000 US each, allow them to be used as an affordable, disposable resource for many short-duration, radioactive waste remediation efforts where decontamination of an expensive, commercial rad-hard camera is undesirable or not possible. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2012

Science Goals for the ARM Recovery Act Radars

Science Goals for the ARM Recovery Act Radars. In October 2008, an ARM workshop brought together approximately 30 climate research scientists to discuss the Atmospheric Radiation Measurement (ARM) Climate Research Facility's role in solving outstanding climate science issues. Through this discussion it was noted that one of ARM's primary contributions is to provide detailed information about cloud profiles and their impact on radiative fluxes. This work supports cloud parameterization development and improved understanding of cloud processes necessary for that development. A critical part of this work is measuring microphysical properties (cloud ice and liquid water content, cloud particle sizes, shapes, and distribution). ARM measurements and research have long included an emphasis on obtaining the best possible microphysical parameters with the available instrumentation. At the time of the workshop, this research was reaching the point where additional reduction in uncertainties in these critical parameters required new instrumentation for applications such as specifying radiative heating profiles, measuring vertical velocities, and studying the convective triggering and evolution of three-dimensional (3D) cloud fields. ARM was already operating a subset of the necessary instrumentation to make some progress on these problems; each of the ARM sites included (and still includes) a cloud radar (operating at 35 or 94 GHz), a cloud lidar, and balloon-borne temperature and humidity sensors. However, these measurements were inadequate for determining detailed microphysical properties in most cases. Additional instrumentation needed to improve retrievals of microphysical processes includes radars at two additional frequencies for a total of three at a single site (35 GHz, 94 GHz, and a precipitation radar) and a Doppler lidar. Evolving to a multi-frequency scanning radar is a medium-term goal to bridge our understanding of two-dimensional (2D) retrievals to the 3D cloud field. These additional microphysical measurements would allow detailed cloud properties to be derived even in the presence of light precipitation. It is important to couple these detailed measurements of cloud microphysics to vertical motion on the cloud scale to couple microphysics with meteorological processes. Vertically pointing Doppler radars provide the vertical motion of cloud particles but, to separate particle motion from air motion, a wind profiler is required. The American Recovery and Reinvestment Act provided the means to address these needs and implement a multi-frequency suite of radars, including scanning radars, at each of the ARM sites. In addition, Doppler lidars have been deployed at several sites. With these new measurement capabilities, ARM has the measurement capabilities to tackle the problems of improving microphysical profile descriptions and evaluating the relationship between our current narrow-field-of view, zenith perspective on clouds to a description of the full 3D cloud field and its temporal evolution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Hyper-resistivity and electron thermal conductivity due to destroyed magnetic surfaces in axisymmetric plasma equilibria

In order to model the effects of small-scale current-driven magnetic fluctuations in a mean-field theoretical description of a large-scale plasma magnetic field B(x,t), a space and time dependent hyper-resistivity {Lambda}(x,t) can be incorporated into the Ohm's law for the parallel electric field E Dot-Operator B. Using Boozer coordinates, a theoretical method is presented that allows for a determination of the hyper-resistivity {Lambda}({psi}) functional dependence on the toroidal magnetic flux {psi} for arbitrary experimental steady-state Grad-Shafranov axisymmetric plasma equilibria, if values are given for the parallel plasma resistivity {eta}({psi}) and the local distribution of any auxiliary plasma current. Heat transport in regions of plasma magnetic surfaces destroyed by resistive tearing modes can then be modeled by an electron thermal conductivity k{sub e}({psi})=({epsilon}{sub 0}{sup 2}m{sub e}/e{sup 2}){Lambda}({psi}), where e and m{sub e} are the electron charge and mass, respectively, while {epsilon}{sub 0} is the permittivity of free space. An important result obtained for axisymmetric plasma equilibria is that the {psi}{psi}-component of the metric tensor of Boozer coordinates is given by the relation g{sup {psi}{psi}}({psi}){identical_to}{nabla}{psi} Dot-Operator {nabla}{psi}=[{mu}{sub 0}G({psi})][{mu}{sub 0}I({psi})]/{iota}({psi}), with {mu}{sub 0} the permeability of free space, G({psi}) the poloidal current outside a magnetic surface, I({psi}) the toroidal current inside a magnetic surface, and {iota}({psi}) the rotational transform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Permanent magnets for ELM suppression in tokamaks: feasibility and operational compatibility

Permanent magnets can provide static magnetic fields without power supplies or feed lines, offering a simpler alternative to conventional electromagnets in tokamaks. This work examines permanent magnet arrays (PMAs) for edge localized mode (ELM) control in double-null (DN) configurations, where traditional RMP coils exhibit limited effectiveness. Linear plasma response calculations using IPEC assess high-field-side (HFS) permanent magnet placement, benchmarking performance against DIII-D low-field-side (LFS) internal coils (I-coils) while evaluating engineering constraints. Modeling results demonstrate that HFS permanent magnet configurations generate HFS plasma response amplitudes more than 5 times larger than conventional I-coil systems. While other resonant response metrics show comparable or reduced response relative to I-coils, the combination of conventional RMP systems and permanent magnets is expected to provide enhanced performance. Operational impact assessments of persistent magnetic fields, including sideband field effects and startup/ramp-up compatibility, reveal acceptable performance within established operational boundaries. This analysis establishes PMAs as a technically viable approach for DN ELM control with reductions in system complexity, motivating further experimental validation on existing tokamak facilities.

3D magnetic perturbation↗

DOE OSTI2022

Supernova Shock Breakout/Emergence Detection Predictions for a Wide-field X-Ray Survey

There are currently many large-field surveys that are operational and are being planned including the powerful Vera C. Rubin Observatory Legacy Survey of Space and Time. These surveys will increase the number and diversity of transients dramatically. However, for some transients, like supernovae (SNe), we can gain more understanding by directed observations (e.g., shock breakout and γ-ray detections) than by simply increasing the sample size. For example, the initial emission from these transients can be a powerful probe of these explosions. Upcoming ground-based detectors are not ideally suited to observing the initial emission (shock emergence) of these transients. These observations require a large field-of-view X-ray mission with a UV follow-up within the first hour of shock breakout. The emission in the first 1 hr to even 1 day provides strong constraints on the stellar radius and asymmetries in the outer layers of stars, the properties of the circumstellar medium (e.g., inhomogeneities in the wind for core-collapse SNe and accreting companions in thermonuclear SNe), and the transition region between these two areas. This paper describes a simulation for the number of SNe that could be seen by a large field-of-view lobster-eye X-ray and UV observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The gravitational lensing imprints of DES Y3 superstructures on the CMB: a matched filtering approach

Low-density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence |$\kappa$|⁠. This effect provides insight into the distribution of matter within voids, and can also be used to study the growth of structure. We measure this lensing imprint by cross-correlating the Planck CMB lensing convergence map with voids identified in the Dark Energy Survey Year 3 (DES Y3) data set, covering approximately 4200 deg|$^2$| of the sky. We use two distinct void-finding algorithms: a 2D void-finder that operates on the projected galaxy density field in thin redshift shells, and a new code, Voxel, which operates on the full 3D map of galaxy positions. We employ an optimal matched filtering method for cross-correlation, using the Marenostrum Institut de Ciències de l’Espai N-body simulation both to establish the template for the matched filter and to calibrate detection significances. Using the DES Y3 photometric luminous red galaxy sample, we measure |$A_\kappa$|⁠, the amplitude of the observed lensing signal relative to the simulation template, obtaining |$A_\kappa = 1.03 \pm 0.22$| (⁠|$4.6\sigma$| significance) for Voxel and |$A_\kappa = 1.02 \pm 0.17$| (⁠|$5.9\sigma$| significance) for 2D voids, both consistent with Lambda cold dark matter expectations. We additionally invert the 2D void-finding process to identify superclusters in the projected density field, for which we measure |$A_\kappa = 0.87 \pm 0.15$| (⁠|$5.9\sigma$| significance). The leading source of noise in our measurements is Planck noise, implying that data from the Atacama Cosmology Telescope, South Pole Telescope and CMB-S4 will increase sensitivity and allow for more precise measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Study of Additive Manufacturing Application to Geothermal Technologies

Geothermal reservoir characterization, field construction, and reservoir operations are very technology intensive activities that contribute significantly to the cost of delivering electricity produced from geothermal resources. Many geothermal technologies, such as downhole tools and drilling equipment, have unusual material, design, and manufacturing considerations dictated by the harsh geothermal environment and extreme aspect ratios required for deployment in a borehole. An additional challenge that faces geothermal applications is the low tool production volume needed to support the industry. Whereas tens of thousands of Oil & Gas wells are drilled and completed in the U.S. annually, there are typically only tens of geothermal wells that are drilled and completed. If a tool typically used in Oil & Gas applications cannot be directly used for geothermal, then the cost associated with making the tool suitable for geothermal is often prohibitive. There is therefore a much smaller inventory of technologies available to geothermal as compared to Oil & Gas and the level of efficiency and sophistication associated with field practice suffers accordingly. A number of advanced manufacturing methods, such as additive manufacturing, have received increased R&D as well as commercial attention in recent years because of their ability to rapidly prototype complex parts. Additive manufacturing in particular provides an opportunity to increase the technology available to the geothermal industry by either reducing fabrication costs associated with complex components or enabling economic production of low volume parts where specialized tooling is often required. Additional potential benefits of additive manufacturing include increased design freedom to make higher performing parts that cannot be made conventionally, the ability to integrate components into assemblies without joining operations, and the ability to economically fabricate variations on design in cases, such as casting molds, where there are large up-front costs associated with tooling. We have recently completed a study that investigated technology needs, representative use cases, manufacturability, and a techno-economic framework for comparing conventional to additive manufacturing methods for geothermal applications. This paper will provide an overview of this recent effort, describe the different elements of the assessment, and summarize the key takeaways related to both the feasibility of using additive manufacturing for geothermal technology applications as well as the potential benefits and impacts.

Polsky, Yarom↗

DOE OSTI2016

Polarization enhanced Nuclear Quadrupole Resonance with an atomic magnetometer

Nuclear Quadrupole Resonance (NQR) has been demonstrated for the detection of 14-N in explosive compounds. Application of a material specific radio-frequency (RF) pulse excites a response typically detected with a wire- wound antenna. NQR is non-contact and material specific, however fields produced by NQR are typically very weak, making demonstration of practical utility challenging. For certain materials, the NQR signal can be increased by transferring polarization from hydrogen nuclei to nitrogen nuclei using external magnetic fields. This polarization enhancement (PE) can enhance the NQR signal by an order of magnitude or more. Atomic magnetometers (AM) have been shown to improve detection sensitivity beyond a conventional antenna by a similar amount. AM sensors are immune to piezo-electric effects that hamper conventional NQR, and can be combined to form a gradiometer for effective RF noise cancellation. In principle, combining polarization enhancement with atomic magnetometer detection should yield improvement in signal-to-noise ratio that is the product of the two methods, 100-fold or more over conventional NQR. However both methods are even more exotic than traditional NQR, and have never been combined due to challenges in operating a large magnetic field and ultra-sensitive magnetic field sensor in proximity. Furthermore we present NQR with and without PE with an atomic magnetometer, demonstrating signal enhancement greater than 20-fold for ammonium nitrate. We also demonstrate PE for PETN using a traditional coil for detection with an enhancement factor of 10. Experimental methods and future applications are discussed.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗

DOE OSTI2020

High precision control and deep learning-based corn stand counting algorithms for agricultural robot

This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, such as emergence rate, biomass, vigor, and stand counting, are measured manually. This is highly labor-intensive and prone to errors. The robot, termed TerraSentia, is designed to automate the measurement of plant traits for efficient phenotyping as an alternative to manual measurements. In this paper, we formulate a Nonlinear Moving Horizon Estimator that identifies key terrain parameters using onboard robot sensors and a learning-based Nonlinear Model Predictive Control that ensures high precision path tracking in the presence of unknown wheel-terrain interaction. Moreover, we develop a machine vision algorithm designed to enable an ultra-compact ground robot to count corn stands by driving through the fields autonomously. The algorithm leverages a deep network to detect corn plants in images, and a visual tracking model to re-identify detected objects at different time steps. We collected data from 53 corn plots in various fields for corn plants around 14 days after emergence (stage V3 - V4). The robot predictions have agreed well with the ground truth with C robot =1.02×C human -0.86 and a correlation coefficient R=0.96. The mean relative error given by the algorithm is -3.78%, and the standard deviation is 6.76%. These results indicate a first and significant step towards autonomous robot-based real-time phenotyping using low-cost, ultra-compact ground robots for corn and potentially other crops.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Risk Importance Measures in the Designand Operation of Nuclear Power Plants

This monograph presents and discusses risk importance measures as quantified by the probabilistic risk assessment (PRA) models of nuclear power plants (NPPs) developed according to the current standards and practices. Usually, PRA tools calculate risk importance measures related to a single ?basic event? representing particular failure mode. This is, then, reflected in many current PRA applications. The monograph focuses on the concept of ?component-level? importance measures that take into account different failure modes of the component including common-cause failures (CCFs). In opening sections the roleof risk assessment in safety analysis of an NPP is introduced and discussion given of ?traditional?, mainly deterministic, design principles which have been established to assign a level of importance to a particular system, structure or component. This is followed by an overview of main risk importance measures for risk increase and risk decrease from current PRAs. Basic relations which exist among the measures are shown. Some of the current practical applications of risk importancemeasures from the field of NPP design, operation and regulation are discussed. The core of the monograph provides a discussion on theoreticalbackground and practical aspects of main risk importance measures at the level of ?component? as modeled in a PRA, starting from the simplest case, single basic event, and going toward more complexcases with multiple basic events and involvements in CCF groups. The intent is to express the component-level importance measures via theimportance measures and probabilities of the underlying single basic events, which are the inputs readily available from a PRA model andits results. Formulas are derived and discussed for some typical cases. The formulas and their results are demonstrated through some practicalexamples, done by means of a simplified PRA model developed in and run by RiskSpectrum? tool, which are presented in the appendices. The monograph concludes with discussion of limitations of the use of risk importance measures and a summary of component-level importance cases evaluated.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2014

Final Scientific/Technical Report for DOE/EERE project Advanced Magnetic Refrigerant Materials

A team led by GE Global Research developed new magnetic refrigerant materials needed to enhance the commercialization potential of residential appliances such as refrigerators and air conditioners based on the magnetocaloric effect (a nonvapor compression cooling cycle). The new magnetic refrigerant materials have potentially better performance at lower cost than existing materials, increasing technology readiness level. The performance target of the new magnetocaloric material was to reduce the magnetic field needed to achieve 4 °C adiabatic temperature change (ΔT adiabatic ) from 1.5 Tesla to 0.75 Tesla. Such a reduction in field minimizes the cost of the magnet assembly needed for a magnetic refrigerator. Such a reduction in magnet assembly cost is crucial to achieving commercialization of magnetic refrigerator technology. This project was organized as an iterative alloy development effort with a parallel material modeling task being performed at George Washington University. Four families of novel magnetocaloric alloys were identified, screened, and assessed for their performance potential in a magnetic refrigeration cycle. Compositions from three of the alloy families were manufactured into regenerator components. At the beginning of the project a previously studied magnetocaloric alloy was selected for manufacturing into the first regenerator component. Each of the regenerators was tested in magnetic refrigerator prototypes at a subcontractor at at GE Appliances. The property targets for operating temperature range, operating temperature control, magnetic field sensitivity, and corrosion resistance were met. The targets for adiabatic temperature change (ΔT adiabatic ) and thermal hysteresis were not met. The high thermal hysteresis also prevented the regenerator components from displaying measurable cooling power when tested in prototype magnetic refrigerators. Magnetic refrigerant alloy compositions that were predicted to have low hysteresis were not attainable with conventional alloy processing methods. Preliminary experiments with rapid solidification methods showed a path towards attaining low hysteresis compositions should this alloy development effort be continued.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A scanning drift tube apparatus for spatiotemporal mapping of electron swarms

A “scanning” drift tube apparatus, capable of mapping of the spatiotemporal evolution of electron swarms, developing between two plane electrodes under the effect of a homogeneous electric field, is presented. The electron swarms are initiated by photoelectron pulses and the temporal distributions of the electron flux are recorded while the electrode gap length (at a fixed electric field strength) is varied. Operation of the system is tested and verified with argon gas; the measured data are used for the evaluation of the electron bulk drift velocity. The experimental results for the space-time maps of the electron swarms — presented here for the first time — also allow clear observation of deviations from hydrodynamic transport. The swarm maps are also reproduced by particle simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Vacuum RF Breakdown of Accelerating Cavities in Multi-Tesla Magnetic Fields

Ionization cooling of intense muon beams requires the operation of high-gradient, normal-conducting RF structures within multi-Tesla magnetic fields. The application of strong magnetic fields has been shown to lead to an increase in vacuum RF breakdown. This phenomenon imposes operational (i.e. gradient) limitations on cavities in ionization cooling channels, and has a bearing on the design and operation of other RF structures as well, such as photocathodes and klystrons. We present recent results from Fermilab's MuCool Test Area (MTA), in which 201 and 805 MHz cavities were operated at high power both with and without the presence of multi-Tesla magnetic fields. We present an analysis of damage due to breakdown in these cavities, as well as measurements related to dark current and their relation to a conceptual model describing breakdown phenomena.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Texture development and coercivity enhancement in cast alnico 9 magnets

The effect of Y addition and magnetic field on texture and magnetic properties of arc-melted alnico 9 magnets has been investigated. Small additions of Y (1.5 wt.%) develop a (200) texture for the arc-melted alnico 9 magnet. Such a texture is hard to form in cast samples. To achieve this goal, we set up a high-field annealing system with a maximum operation temperature of 1250 °C. This system enabled annealing in a field of 45 kOe with subsequent draw annealing for the solutionized buttons; we have been able to substantially increase remanence ratio and coercivity, from 0.70 and 1200 Oe for the Y-free alnico 9 to 0.90 and 1400 Oe for the Y-doped alnico 9, respectively. A high energy product of 7.3 MGOe has been achieved for the fully heat-treated Y-doped alnico 9. The enhancement of coercivity is believed to arise from the introduction of magnetocrystalline anisotropy from 80 nm Y 2 Co 17 -type grains, which are exchange-coupled to the main-phase alnico rods.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Observation and analysis of lower-hybrid-current-drive density limit in EAST

Lower hybrid current drive (LHCD) experiments with line-averaged density up to ~5.1 × 10 19 m –3 were performed in EAST L-mode plasmas. When the line-averaged density rises above a critical value, the hard x-ray (HXR) emission falls to the noise level, indicating that the LHCD density limit is encountered. The experimental results show that the LHCD density limit can be increased with higher wave source frequency (ƒ 0 ) and higher magnetic field (B t ). Although a higher LHCD density limit is obtained by a higher magnetic field for both 2.45 GHz and 4.6 GHz waves, the results show a stronger dependence on the magnetic field for the 4.6 GHz case. Analysis suggests that, for normal operation with a relatively low magnetic field (1.6 T $\leqslant$ B t $\leqslant$ 2.5 T) on EAST, the dominant mechanisms responsible for the LHCD density limit are different between the 2.45 GHz and 4.6 GHz waves. The wave accessibility plays a more significant role during 4.6 GHz LHCD experiments, while parasitic losses due to parametric decay instability (PDIs) dominate the accessibility issue in the 2.45 GHz case. Collisional loss in the scrape-off layer (SOL) may explain the 4.6 GHz result when combined with the accessibility limit at high density and low temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Entanglement-enhanced ac magnetometry in the presence of Markovian noise

Entanglement is a resource to improve the sensitivity of quantum sensors. In an ideal case, using an entangled state as a probe to detect target fields, we can beat the standard quantum limit by which all classical sensors are bounded. However, since entanglement is fragile against decoherence, it is unclear whether entanglement-enhanced metrology is useful in a noisy environment. Its benefit is indeed limited when estimating the amplitude of dc magnetic fields under the effect of parallel Markovian decoherence, where the noise operator is parallel to the target field. In this paper, on the contrary, we show an advantage to using an entanglement over the classical strategy under the effect of parallel Markovian decoherence when we try to detect ac magnetic fields. We consider a scenario to induce a Rabi oscillation of the qubits with the target ac magnetic fields. Although we can, in principle, estimate the amplitude of the ac magnetic fields from the Rabi oscillation, the signal becomes weak if the qubit frequency is significantly detuned from the frequency of the ac magnetic field. We show that, by using the Greenberger-Horne-Zeilinger (GHZ) states, we can significantly enhance the signal of the detuned Rabi oscillation even under the effect of parallel Markovian decoherence. Further, our method is based on the fact that the interaction time between the GHZ states and ac magnetic fields scales as 1/L to mitigate the decoherence effect, where L is the number of qubits, which contributes to improving the bandwidth of the detectable frequencies of the ac magnetic fields. Our results pave the way for new applications of entanglement-enhanced ac magnetometry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗