Development of Ultra-Low Noise, Wide Bandwidth, High Gain Transimpedance Amplifiers for Experimental and Commercial Detection Systems
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42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “Sensor fusion”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Inverse rendering of fusion plasmas: Inferring plasma composition from imaging systems
In this work, we develop a differentiable rendering pipeline for visualising plasma emission within tokamaks, and estimating the gradients of the emission and estimating other physical quantities. Unlike prior work, we are able to leverage arbitrary representations of plasma quantities and easily incorporate them into a non-linear optimisation framework. The efficiency of our method enables not only estimation of a physically plausible image of plasma, but also recovery of the neutral Deuterium distribution from imaging and midplane measurements alone. We demonstrate our method with three different levels of complexity showing first that a poloidal neutrals density distribution can be recovered from imaging alone, second that the distributions of neutral Deuterium, electron density and electron temperature can be recovered jointly, and finally, that this can be done in the presence of realistic imaging systems that incorporate sensor cropping and quantisation.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?
Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.
54 ENVIRONMENTAL SCIENCES↗
Time-resolved X-ray diffraction diagnostic development for the National Ignition Facility
Here we present the development of an experimental platform that can collect four frames of x-ray diffraction data along a single line of sight during laser-driven, dynamic-compression experiments at the National Ignition Facility. The platform is comprised of a diagnostic imager built around ultrafast sensors with a 2-ns integration time, a custom target assembly that serves also to shield the imager, and a 10-ns duration, quasi-monochromatic x-ray source produced by laser-generated plasma. We demonstrate the performance with diffraction data for Pb ramp compressed to 150 GPa and illuminated by a Ge x-ray source that produces ∼7 × 10 11 , 10.25-keV photons/ns at the 400 μm diameter sample.
36 MATERIALS SCIENCE↗
A Co-Registered In-Situ and Ex-Situ Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-10)
This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, X-Ray Computed Tomography (X-CT) scans, pycnometry and tensile test results, etched micrographs from selected locations, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.
36 MATERIALS SCIENCE↗
The Sensor Dilemma in Intelligent Transportation Systems: Evaluating Radar, Lidar and Camera: Preprint
Intelligent transportation systems (ITS) are at the forefront in advancing the way we interact with and perceive the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as radar, lidar, and video imaging, which are the most popular modalities for ITS. Real-time perception data from these sensors allow intelligent infrastructure-side decision-making to improve the energy, efficiency, and safety at traffic intersections. As traffic departments across the United States transition from traditional loop detectors and emulators and embrace newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception that is reliable, inexpensive, and easy to set up and that has robust performance in varying weather conditions. However, choosing a sensor that checks all these boxes is not straightforward, as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long-range vehicles and weather resistance but lacks high resolution. Lidar is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines radar, lidar, and camera sensor capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like radar, lidar, and cameras offers the most robust solution for enhancing the safety and efficiency of ITS. Through this evaluation, we hope to draw attention to the necessity of the National Renewable Energy Laboratory's infrastructure perception and control framework, which presents a multisensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception.
33 ADVANCED PROPULSION SYSTEMS↗
Fast modulating electron cyclotron emission (FMECE) diagnostic for tokamaks
Utilizing variable-frequency channels, e.g., yttrium iron garnet (YIG) bandpass filters, in the intermediate frequency (IF) section of an electron cyclotron emission (ECE) radiometer facilitates flexibility in the volume viewed by the ECE channels as well as high resolution electron temperature and temperature fluctuation measurements in tokamaks. Fast modulating electron cyclotron emission (FMECE), a stand-alone IF section with eight channels, is a novel application of YIG filters for real-time electron temperature gradient and gradient scale length measurements. Key to FMECE is a simultaneous input/output data acquisition unit, as well as a modified type of YIG filters, which is capable of fast switching of their center (set) frequencies with a frequency slew rate of 600 μs/GHz. A new FMECE has been implemented and tested on the DIII-D tokamak, demonstrating its capability in real-time gradient measurements. Here, the data presented here shows that FMECE can identify flattening in the electron temperature profile; the latter can be used as a sensor for real time monitoring and control of plasma instabilities. Implementation and application are planned for the EAST tokamak.
47 OTHER INSTRUMENTATION↗
Improvements on the Diagnostic Residual Gas Analyzer at Wendelstein 7-X
Exhaust gas analysis provides key information on fusion processes, divertor operation, and wall state in fusion experiments and future reactors. The diagnostic residual gas analyzer (DRGA) concept has been developed for ITER with a focus on fast helium and hydrogen isotope detection. The first operation of the prototype DRGA (P-DRGA) at the stellarator Wendelstein 7-X showed potential for improvement in terms of magnetic sensor shielding, data acquisition automation, and potential new additions to the cluster of sensors on the P-DRGA. More recently, a Monte Carlo simulation of the flow of the mixed gas species effluent from the pressure-reducing orifice, down to about 8-m sampling tube and into the analysis region of the sensors, has been found to generally agree with previous calculations and measurements but revealed potential back-streaming effects for light gases, with impact on detection limits both for the prototype and for the ITER DRGA currently in design. For the upcoming campaign of the prototype, an enhanced soft iron shield will safeguard the gauges against magnetic stray field influence. The newly introduced shielding has been tested for its effect on magnetic stray fields and found to reduce the inside residual field by about two orders of magnitude.
Schlisio, G↗
Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)
This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, DMREF, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR).
36 MATERIALS SCIENCE↗
Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)
The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)
This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.
36 MATERIALS SCIENCE↗
Spectral Data Fusion From Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) Analyzers for Improved Detection of Cerium in a Simulated Dispersal Accident
Here, this work implements a mid-level data fusion methodology on spectral data from handheld X-ray fluorescence and laser-induced breakdown spectroscopy analyzers to quantify plutonium surrogate (CeO 2 ) contamination in soil samples for the first time. Spectral data from each analyzer were used independently to train supervised machine learning regressions to predict Ce concentration. Fused features from both data sets were then used to train the same models, comparing prediction performance by evaluating model precision and sensitivity. Fusing principal component scores from the two sensors yielded an order of magnitude improvement in precision and sensitivity of predictions made with an artificial neural network, compared to predictions made by models trained on independent sensor data. As a result, a boosted ensemble trained on the fused spectral features yielded an ideal predictor with root-mean-squared error on the order of 10 –6 and calculated limit of detection order 10 –5 wt %.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception: Preprint
This paper puts forth a system architecture for an infrastructure-based cooperative perception (CP) fusion engine, to provide a complete state-space digital representation, with measurable accuracy, to support a wide-range of applications. The architecture includes the inputs, functional flow, data standardization recommendations, outputs and supported applications. The CP engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure (IRI), that complements and accelerates connected and automated vehicle (CAV) technology. that the CP acquires and fuses information from sensors (radar, LiDAR, and cameras), and CAVs to intelligently perceive roadway traffic states of all moving objects, create a complete three-dimensional digital representation of that state-space, and communicate it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications for CAVs as examples. The IRI approach, as opposed to a vehicle centric approach, is found to be more scalable in that it can deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the US, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and GHG reduction.
ADVANCED PROPULSION SYSTEMS↗
Evaluation of ITER divertor shunts as a synthetic diagnostic for detachment control
Reliable diagnostics that measure the detached state of the ITER divertor plasma will be necessary to control heat flux to the divertor targets during steady state, burning plasma operation. This paper conducts an initial exploration into the feasibility of the divertor shunt diagnostic as a lightweight, robust, and real-time detachment sensor. This diagnostic is a set of shunt lead pairs that measure the voltage drop along the divertor cassette body, from which the plasma scrape-off layer (SOL) current is calculated. Using SOLPS-ITER simulations for control-relevant ITER plasma scenarios, the thermoelectric current magnitude along the SOL is shown to decrease significantly with the onset of partial detachment at the outer divertor target. Electromagnetic modelling of a simplified divertor cassette is used to develop a control-oriented inductance-resistance circuit model, from which SOL currents can be calculated from shunt pair voltage measurements. The sensitivity and frequency-response of the resulting system indicates that the diagnostic will accurately measure SOL thermoelectric currents during ITER operation. These currents will be a good measure of the detached state of the divertor plasma, making the divertor shunt diagnostic a potentially extremely valuable and physically robust sensor for real-time detachment control.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Quench Propagation on Rare-Earth Barium Copper Oxide (REBCO) Tape
Rare-earth barium copper oxide (REBCO) high-temperature superconductors can carry high currents with zero electrical resistance, enabling applications in high-field magnets, energy systems, and fusion devices. However, the localized losses of superconductivity called a quench pose a severe risk due to REBCO’s mechanical brittleness and slow quench propagation, hence complicating early detection. This work investigates quench propagation and thermal response through controlled experiments. A segmented REBCO tape soldered on a PCB with multiple voltage taps and temperature sensors was submerged in liquid nitrogen at 77 K. In the first test, current ramping produced a quench near 360 A, consistent with theoretical current limits but resulted in a local burn. In the second test, a heater-induced quench at 300 A propagated bidirectionally with measured velocities ranging from 164–226 mm/s. These measurements provide critical parameters for improving REBCO quench detection and protection system design with accounts for REBCO's limited bendability.
Ju, Han [NIU, DeKalb]↗
Diagnostics: Chapter 8 of the special issue: on the path to tokamak burning plasma operation
This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.
ITER↗
Quench Propagation On Rare-Earth Barium Copper Oxide (REBCO) Tape
Rare-earth barium copper oxide (REBCO) high-temperature superconductors can carry high currents with zero electrical resistance, enabling applications in high-field magnets, energy systems, and fusion devices. However, localized losses of superconductivity, known as quenches, pose a severe risk due to REBCO’s mechanical brittleness and slow quench propagation, complicating early detection. This work investigates quench propagation and thermal response through controlled experiments. A segmented REBCO tape soldered onto a printed circuit board (PCB) with multiple voltage taps and temperature sensors was submerged in liquid nitrogen at 77 K. In the first test, current ramping produced a quench near 360 A, consistent with theoretical current limits, but resulted in local burnout. In the second test, a heater-induced quench at 300 A propagated bidirectionally with velocities ranging from 164–226 mm/s. These results provide critical parameters for improving REBCO quench detection and protection system design while accounting for REBCO’s limited bendability.
Ju, Han [Northern Illinois U.]↗
Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception
This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.
ADVANCED PROPULSION SYSTEMS↗