In-situ infrared thermographic inspection for local powder layer thickness measurement in laser powder bed fusion
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The core electron temperature drops rapidly during the sawtooth crash in tokamak plasmas, which causes heat loss and may lead to fast particle losses or even a disruption. Several models have been proposed for the periodic crash, including the Kadomtsev model with magnetic reconnection and the quasi-interchange model with the growth of higher-mode-number pressure-driven instabilities. 3D MHD simulations were performed for these two models with a goal to develop intuition and to predict qualitatively how different types of sawtooth will appear in various diagnostics. The structures of electron density ne and electron temperature Te show a dominant (1, 1) mode for the Kadomtsev case and a dominant (4, 4) mode for the quasi-interchange case. The oscillations of ne and Te have a positive correlation near the inversion layer for both cases, while their frequencies and amplitudes are different depending on the dominant modes. Particularly, for the Kadomtsev case, we find a relation between the amount of flux reconnected during a sawtooth event and ne or Te oscillations. Therefore, we connect recently developed measurement capabilities for ne and Te to the internal sawtooth behavior. We propose that this method of analysis can help in identifying the type of sawtooth in future experiments augmented by simulations.
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Sequential scattering measurements are often performed under a fixed experimental-time budget, even though the expected count rate varies strongly across the measured coordinate. When the dwell time at each measurement position can be controlled independently, this variation creates a general resource-allocation problem: how should the available time be distributed to minimize the uncertainty of the reconstructed profile? We formulate this problem as a constrained variational optimization for measurements governed by Poisson counting statistics. When each measurement is treated independently, minimizing the averaged squared relative uncertainty yields an inverse-square-root intensity allocation. The formulation is then generalized to include correlations between neighboring measurements and an instrumental resolution operator, leading to an allocation criterion that equalizes the marginal reduction in posterior uncertainty per unit measurement time. Bonse–Hart ultra-small-angle neutron scattering (USANS), in which reciprocal space is sampled sequentially through analyzer-angle stepping, provides an experimentally grounded application. Computational benchmarking shows that the optimized allocation outperforms uniform-time and constant-relative-error strategies, while application to an experimentally measured graphite USANS profile from the Spallation Neutron Source, using Poisson resampling under alternative schedules, demonstrates how counting time should be redistributed toward weak-intensity regions under an identical total duration. The resulting framework applies to sequential scattering and related scanning measurements whenever local dwell times are adjustable and directly determine the measurement uncertainties, and when the relevant correlation and instrumental-response models are available.
We extend the results of arXiv:2209.12903 by studying local projective measurements performed on subregions of two copies of a CFT 2 in the thermofield double state and investigating their consequences on the bulk double-sided black hole holographic dual. We focus on CFTs defined on an infinite line and consider measurements of both finite and semi-infinite subregions. In the former case, the connectivity of the bulk spacetime is preserved after the measurement. In the latter case, the measurement of two semi-infinite intervals in one CFT or of one semi-infinite interval in each CFT can destroy the Einstein-Rosen bridge and disconnect the bulk dual spacetime. In particular, we find that a transition between a connected and disconnected phase occurs depending on the relative size of the measured and unmeasured subregions and on the specific Cardy state the measured subregions are projected on. We identify this phase transition as an entangled/disentangled phase transition of the dual CFT system by computing the post-measurement holographic entanglement entropy between the two CFTs. We also find that bulk information encoded in one CFT in the absence of measurement can sometimes be reconstructed from the other CFT when a measurement is performed, or can be erased by the measurement. Finally, we show that a purely CFT calculation of the Renyi entropy using the replica trick yields results compatible with those obtained in our bulk analysis.
ABSTRACT Reverberation mapping is a robust method to measure the masses of supermassive black holes outside of the local Universe. Measurements of the radius–luminosity (R−L) relation using the Mg ii emission line are critical for determining these masses near the peak of quasar activity at z ≈ 1−2, and for calibrating secondary mass estimators based on Mg ii that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg ii lags from our 5-yr Australian Dark Energy Survey reverberation mapping programme, which substantially improves the number and quality of Mg ii lag measurements. As the Mg ii feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multiepoch spectra before analysing the Mg ii line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H β and Mg ii R−L relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4{{\ \rm per\ cent}}$.
Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.
The first local velocity measurements of helical equilibrium plasmas in the Reversed Field Pinch (RFP) Single Helical Axis (SHAx) state using a Charge Exchange Recombination Spectroscopy (CHERS) diagnostic are presented. Measurements show strong axisymmetric and non-axisymmetric flow, with n ¼ 5 components of flow related to the ðm; nÞ¼ð1; 5Þ dominant magnetic mode on the order of the axisymmetric flow in certain regions of the plasma, as well as significant n > 5 flow. Flow measurements are compared with NIMROD simulations of visco-resistive, single-fluid MHD in toroidal and cylindrical geometries with limited axial periodicity. Both measurements and the simulation with toroidal geometry show stronger inboard flows relative to the outboard flows, which is attributed to the toroidal geometry of the device. In the experiment, the n ¼ 5 component of flow is phase shifted from the reconnection-like flow pattern observed in the single-fluid simulations, possibly due to decoupling of the ion and electron fluids over much of the plasma. Finally, the strength of the helical angular flow shear relative to the critical shear necessary to disrupt nonlinear coupling between tearing modes is calculated around the helical magnetic axis. The shear in the measured flow is on the order of the theoretical critical threshold needed to nonlinearly decouple modes, but the measurement uncertainty in the gradient of the flow is large.
Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.
Here, we present the first local, quantitative measurements of ion current filamentation and magnetic field amplification in interpenetrating plasmas, characterizing the dynamics of the ion Weibel instability. The interaction of a pair of laser-generated, counterpropagating, collisionless, supersonic plasma flows is probed using optical Thomson scattering (TS). Analysis of the TS ion-feature revealed anticorrelated modulations in the density of the two ion streams at the spatial scale of the ion skin depth c/ω pi = 120 μm, and a correlated modulation in the plasma current. The inferred current profile implies a magnetic field amplitude ~30 ± 6 T , corresponding to ~1% of the flow kinetic energy, indicating that magnetic trapping is the dominant saturation mechanism.
Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.
In this work, we use the thermoelectricity to directly measure the temperature at different radial positions within instrumented Al1100 billets during friction extrusion. Site-specific and uninterrupted temperature measurements were possible by measuring the local voltages at several thermoelectric junctions consisting of aluminum-nickel pairs during extrusion. Measurements were conducted for a constant die rotation speed of 150 RPM and different extrusion feed rates of 2, 8, 32, and 80 mm.min-1. X-ray computed tomography was used to locate the positions of the thermoelectric junctions inside the processed billet, thus allowing for site-specific microstructural characterization at the precise measurement points. Smooth particle hydrodynamic modeling allowed to determine the thermal, strain, and strain rate fields developing during FE. The applicability and limitations of this temperature measurement approach are discussed as a function of the peak extrusion and torsion stresses relative to the matrix of extrusion feed rates.
A recent chemical explosive test in P-Tunnel at the Nevada National Security Site, Nevada, USA, was conducted to better understand how signals propagate from explosions in the subsurface. A primary signal of interest is the migration of gases that can be used to differentiate chemical from nuclear explosions. Gas migration is highly dependent on the rock permeability which is notoriously difficult to determine experimentally in the field due to a potentially large dependence on the scale over which measurements are made. Here, we present pre-explosion permeability estimates to characterize the geologic units surrounding the recent test. Permeability measurements were made at three scales of increasing size: core samples (≈2 cm), borehole packer system tests (≈1 m), and a pre-shot cavity pressurization test (> 10 m) across ten tuff units. Permeability estimates based on core measurements showed little difference from borehole packer tests. However, permeability in most rock units calibrated from cavity pressurization tests resulted in higher permeability estimates by up to two orders of magnitude. Here, we demonstrate that the scale of the measurement significantly impacts the characterization efforts of hydraulic properties in volcanic tuff, and that local-scale measurements (< 10 m scale) do not incorporate enough heterogeneity to accurately predict field-scale flow and mass transport.
To examine momentum redistribution processes and study generalized helicities during plasma relaxation in Madison Symmetric Torus, MST, reversed field pinch plasma, a new probe is being tested to measure the full 3D plasma ion flow and magnetic field vectors at four spatial locations arranged in a tetrahedral shape reminiscent of a satellite measurement constellation. These measurements permit calculation of ∇ x $\vec{u}$ and canonical momentum, where $\vec{u}$ is the plasma ion flow vector. The probe consists of four probe heads arranged in a tetrahedral pattern, with an overall probe diameter of ∼31.75 mm. The probe head diameter is ∼1.0 cm, which is of the order of the ion Larmor radius. Each head has four molybdenum electrodes, also arranged in tetrahedral geometry, which are biased relative to a common return electrode, using four power supplies (one for each head), to measure the local ion flow. Additionally, each head has three orthogonal magnetic pickup coils within it to measure equilibrium and fluctuating magnetic fields.
Applications of fiber optic sensors to battery monitoring have been increasing due to the growing need of enhanced battery management systems with accurate state estimations. The goal of this review is to discuss the advancements enabling the practical implementation of battery internal parameter measurements including local temperature, strain, pressure, and refractive index for general operation, as well as the external measurements such as temperature gradients and vent gas sensing for thermal runaway imminent detection. A reasonable matching is discussed between fiber optic sensors of different range capabilities with battery systems of three levels of scales, namely electric vehicle and heavy-duty electric truck battery packs, and grid-scale battery systems. The advantages of fiber optic sensors over electrical sensors are discussed, while electrochemical stability issues of fiber-implanted batteries are critically assessed. This review also includes the estimated sensing system costs for typical fiber optic sensors and identifies the high interrogation cost as one of the limitations in their practical deployment into batteries. Finally, future perspectives are considered in the implementation of fiber optics into high-value battery applications such as grid-scale energy storage fault detection and prediction systems.
Abstract The Pantanal region of Brazil is the largest seasonally flooded tropical grassland and, according to local chamber measurements, a substantial CH 4 source. CH 4 emissions from wetlands have recently become of heightened interest because global atmospheric 13 CH 4 data indicate they may contribute to the resumption of atmospheric CH 4 growth since 2007. We have regularly measured vertical atmospheric profiles for 2 years in the center of the Pantanal with the objectives to obtain an estimate of CH 4 emissions using an atmospheric approach, and provide information about flux seasonality and its relation to controlling factors. Boundary layer‐free troposphere differences observed in the Pantanal are large compared to other wetlands. Total emissions based on a planetary boundary layer budgeting technique are 2.0–2.8 TgCH 4 yr −1 (maximum flux ∼0.4 gCH 4 m −2 d −1 ) while those based on a Bayesian inversion using an atmospheric transport model are ∼3.3 TgCH 4 yr −1 . Compared to recent estimates for Amazonia (∼41 ± 3 TgCH 4 yr −1 , maximum flux ∼0.3 gCH 4 m −2 d −1 ) these emissions are not that large. Our Pantanal data suggest a clear flux seasonality with CH 4 being released in large amounts just after water levels begin to rise again after minimum levels have been reached. CH 4 emissions decline substantially once the maximum water level has been reached. While predictions with prognostic wetland CH 4 emission models agree well with the magnitude of the fluxes, they disagree with the phasing. Our approach shows promise for detecting and understanding longer‐term trends in CH 4 emissions and the potential for future wetlands CH 4 emissions climate feedbacks.
The parallel development of ultramicroelectrodes (UMEs) and groundbreaking scanning probe microscopy techniques in the late 1980s led to the development of the scanning electrochemical microscope. Scanning electrochemical microscopy (SECM) was born from the idea of using a tiny electrode to measure the local electrochemical behavior at operating electrodes. From its foundations, the technique displayed an inherent versatility in measuring sample properties beyond topography. It allowed experimenters to measure and map chemical reactions occurring at diverse interfaces, from inspecting the reversibility of redox mediators at metal electrodes, to detecting the hallmarks of cellular respiration on living plant leaves. Related but distinct electrochemical scanning probe techniques, such as electrochemical atomic force microscopy (EC-AFM), scanning ion conductance microscopy (SICM), and scanning electrochemical cell microscopy (SECCM) have developed in parallel. These techniques have demonstrated exquisite spatial resolution down to the nanoscale regime. However, it is the proposition of this review that SECM remains unmatched at revealing the chemical aspects of electrochemistry. Furthermore, it is our intention to review and demonstrate that the versatile architecture of SECM continues to evolve and address fundamental and emerging challenges in the fields of energy storage and conversion, chemical biology, materials science, and environmental chemistry, among others.