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DOE OSTI2020

Design and pre-flight performance of SPIDER 280 GHz receivers

In this work we describe upgrades to the Spider balloon-borne telescope in preparation for its second flight, currently planned for December 2021. The Spider instrument is optimized to search for a primordial B-mode polarization signature in the cosmic microwave background at degree angular scales. During its first flight in 2015, Spider mapped ~10% of the sky at 95 and 150 GHz. The payload for the second Antarctic flight will incorporate three new 280 GHz receivers alongside three refurbished 95- and 150 GHz receivers from Spider's first flight. In this work we discuss the design and characterization of these new receivers, which employ over 1500 feedhorn-coupled transition-edge sensors. We describe pre-flight laboratory measurements of detector properties, and the optical performance of completed receivers. These receivers will map a wide area of the sky at 280 GHz, providing new information on polarized Galactic dust emission that will help to separate it from the cosmological signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

"Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs"

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment leveraged a heterogeneous fleet of 100 longitudinally-controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this paper. The MegaController is a hierarchical control architecture, which consists of two main layers. The upper layer is called Speed Planner, and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock on-board sensors. The Speed Planner ingests live data feeds provided by third parties, as well as data from our own control vehicles, and uses both to perform the speed assignment. The architecture of the speed planner allows for modular use of standard control techniques, such as optimal control, model predictive control, kernel methods and others, including Deep RL, model predictive control and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers, or only some. Control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars, and electronic selection of ACC set points in others. The proposed architecture allows for the combination of all possible settings proposed above. Most configurations were tested throughout the ramp up to the MegaVandertest.

Lee, Jonathan↗

DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Development and Characterization of a Self-Tightening Tourniquet System

Uncontrolled hemorrhage remains a leading cause of death in both emergency and military medicine. Tourniquets are essential to stopping hemorrhage in these scenarios, but they suffer from subjective, inconsistent application. Here, we demonstrate how tourniquet application can be automated using sensors and computer algorithms. The auto-tourniquet self-tightens until blood pressure oscillations are no longer registered by the pressure sensor connected to the pneumatic pressure cuff. The auto-tourniquet’s performance in stopping the bleed was comparable to manual tourniquet application, but the time required to fully occlude the bleed was longer. Application of the tourniquet was significantly smoother, and less variable, for the automatic tourniquet compared to manual tourniquet application. This proof-of-concept study highlights how automated tourniquets can be integrated with sensors to provide a much more consistent application and use compared to manual application, even in controlled, low stress testing conditions. Future work will investigate different sensors and tourniquets to improve the application time and repeatability.

Vega, Saul J.↗

DOE OSTI2022

Tunable polyvinyl chloride (PVC) and thermoplastic polyurethane (TPU)-based soft polymer gel sensors

Abstract Polyvinyl chloride (PVC) gels have recently been found to exhibit mechanoelectrical transduction under mechanical deformation. These mechanoelectrical properties of PVC gels are largely uncharacterized and the underlying transduction mechanisms are currently unknown. These soft electroactive polymers have tunable properties such as modulus and response voltage based on physical dimensions and the amount of plasticizer content within the material making them ideal candidates for complaint sensors. This study aims to investigate PVC gels comprised of various plasticizers to further investigate underlying mechanisms of mechanoelectrical transduction and broaden possible sensing applications. Plasticizers used in this study include dibutyl adipate, dibutyl phthalate, dioctyl phthalate, otherwise known as bis(2-ethylhexyl) phthalate, diisodecyl adipate, and the environmentally friendly biodegradable plasticizer acetyl tributyl citrate (ATBC). ATBC is often used in cosmetics and food packaging applications and is even used as a food additive which may lead to future biocompatibility for these gel sensors. These plasticizers are used to produce PVC gel sensors that are experimentally tested for mechanoelectrical transduction properties and sensing performance. In this study, a Langmuir adsorptive model is fit to the collected mechanoelectrical transduction data. These results are also nondimensionalized and compared to the characteristic dimensionless Langmuir adsorptive model. This simple model agrees very well with the experimental data. Additionally, a study on the mechanoelectrical transduction of an alternative polymer lattice structure, thermoplastic polyurethane (TPU), is discussed. This is a novel electroactive polymer investigated for mechanoelectrical transduction properties. This portion of the study aims to further knowledge of underlying mechanisms of mechanoelectrical transduction as well as show feasibility of additional lattices for soft polymer gel sensors. These TPU gel sensors show strikingly similar mechanoelectrical transduction properties to analogous PVC gels, insinuating that the polymer structure has a limited role in the underlying sensing mechanism and PVC itself is not unique to polymer gel sensing. The TPU-based soft polymer gel sensors however do display some level of mechanoelectrical hysteresis which may be attributed to viscoelastic properties and display a small amount of fatigue possibly due to exudation of liquid plasticizer. This study provides further characterization of mechanoelectrical response for varying plasticizers, provides a theoretical framework for underlying mechanisms, and displays the potential for further polymeric gel sensors.

Instruments & Instrumentation↗

DOE OSTI2024

Evaluation of Leak Detection Technologies for Low Global Warming Potential (GWP), Flammable Refrigerants

Current commercial refrigeration systems use refrigerants with global warming potential (GWP) values ranging from 1250 to 4000. The emergence of low GWP alternatives (GWP <150) is expected to significantly reduce direct emissions in this sector, playing a crucial role in the ongoing electrification and decarbonization initiatives. However, many of these low GWP alternatives pose a flammability risk, necessitating robust sensing solutions to ensure the reliable and safe operation of the equipment. This paper examines various sensing mechanisms suitable for potential applications in systems that employ flammable refrigerants, specifically those designated as A2L class. It provides a summary of A2L refrigerants and their properties, followed by a comprehensive review of sensor classes, covering their working principles, features, advantages, and limitations. Additionally, the article delves into key performance characteristics such as accuracy, selectivity, sensitivity, dynamic characteristics, and durability, among other properties. The article discusses areas for improvement and suggests corresponding approaches for potential sensors in facilitating the successful adoption of flammable refrigerants. Finally, this paper presents the latest findings from experimental evaluation of 5 different sensing principles in detecting the composition variation as a result of various operational conditions. Reliability and sensitivity of the sensor in responding to shifts in true composition and the resultant LFL value is also discussed.

Reshniak, Viktor↗

DOE OSTI2026

The NREL Sensor Laboratory Detection of Hydrogen Emissions

The development of a functional hydrogen detection system is a multifaceted process that integrates hardware, deployments strategies, and analytics which can be supported by the NREL Sensor Laboratory: 1. Support of the design, validation and optimization of sensing prototypes; 2. Guide optimized sensing element development, including control electronics; 3. Laboratory testing to validate/optimize metrological performance (measurement range, detection limit, etc.); 4. Provide test sites for field deployments representative of real-world scenarios with controlled hydrogen releases; 5. Develop sensor placement and operation guidance; 6. Provide guidance on electronics to accommodate facility integration; 7. Electrical safety designs to allow for operation within restricted zones; 8. Integration into facility monitoring and control systems; 9. Guide incorporation of cyber security elements to protect facilities from malicious attacks; 10. Modeling and application of advanced analytics to detect and quantify emissions; 11. Higher Order dispersion models to guide sensor placement for reliable detection; 12. Advanced analytics for improved metrological performances, and to inform inverse modeling; 13. Market support and commercialization (national and international markets); 14. Commercial deployments in H2@SCALE markets (e.g., HUBs and other large-scale hydrogen markets); and 15. Leverage off international collaborations/partnerships (e.g., NREL is on the advisory board for the European initiative "pre-Normative Research on Hydrogen Releases Assessment"-NHyRA).

08 HYDROGEN↗

DOE OSTI2020

Large Exciton Diffusion Coefficients in Two Dimensional Covalent Organic Frameworks with Different Domain Sizes Revealed by Ultrafast Exciton Dynamics

Large singlet exciton diffusion lengths are a hallmark of high performance in organic-based devices such as photovoltaics, chemical sensors, and photodetectors. In this study, exciton dynamics of a two-dimensional covalent organic framework, 2D COF-S, is investigated using ultrafast spectroscopic techniques. After photoexcitation, the COF-S exciton decays via three pathways: (1) excimer formation (4 +/- 2 ps), (2) excimer relaxation (160 +/- 40 ps), and (3) excimer decay (>3 ns). Excitation fluence-dependent transient absorption studies suggest that COF-5 has a relatively large diffusion coefficient (0.08 cm(2)/s). Furthermore, exciton-exciton annihilation processes are characterized as a function of COF-S crystallite domain size in four different samples, which reveal domain-size-dependent exciton diffusion kinetics. These results reveal that exciton diffusion in COF-S is constrained by its crystalline domain size. These insights indicate the outstanding promise of delocalized excitonic processes available in 2D COFs, which motivate their continued design and implementation into optoelectronic devices.

Flanders, Nathan C.↗

DOE OSTI2026

Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields

Adaptive optics restore ideal imaging performance in complex samples by measuring and correcting optical aberrations but often require custom-built microscopes with carefully aligned wavefront sensing/shaping devices and can be susceptible to sample motion. Here we describe NeAT, a computational framework using neural fields for adaptive optics two-photon fluorescence microscopy. NeAT estimates wavefront aberration and recovers sample structure from a 3D image stack without requiring external datasets for training. Incorporating motion correction in learning and correcting conjugation errors commonly found in commercial microscopes, NeAT is designed for deployment in biological laboratories for in vivo imaging. We validate NeAT’s performance using a custom-built microscope with a wavefront sensor under varying signal-to-noise ratios, aberration and motion conditions. With a commercial microscope, we demonstrate real-time aberration correction for in vivo morphological and functional imaging in the living mouse brain, with NeAT improving the signal and accuracy of glutamate and calcium imaging of synapses and neurons.

Kang, Iksung↗

DOE OSTI2023

Development of a large array of Silicon Drift Detectors for high-rate synchrotron fluorescence spectroscopy

An array of small-area Silicon Drift Detectors (SDD), named Hera, has been developed at Brookhaven National Laboratory (BNL) in the past few years. Its primary application is high-rate spectroscopy at synchrotrons. Each SDD pixel is a 1 mm × 1 mm square to match the footprint of the original diode-based pixel detector called Maia, which was developed for the same application. The replacement of the diode with an SDD allows for better energy resolution at short shaping times and an increased stability of the detector. 32, 96, and 384-channel arrays were designed and fabricated and achieved a Full Width Half Maximum (FWHM) as low as 176 eV at 5.9 keV with peaking time of 1 μs at -13°C. The sensor design, simulation, fabrication, its readout system, and its spectroscopic performance are reported.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

The SparkPix-S ASIC for the sparsified readout of 1 MHz frame-rate X-ray cameras at LCLS-II: pixel design and simulation results

Exploiting the “sparse” nature of the information in XPCS (X-ray Photon Correlation Spectroscopy) and XSVS (Speckle Visibility Spectroscopy) experiments, we present the SparkPix-S, a 3-sides buttable Application Specific Integrated Circuit (ASIC) based on a sparsified readout strategy for large-format hybrid detectors. The SparkPix-S architecture, based on the successful ePix family, will be composed as follows: a front-end 2-D matrix of 384×352 square pixels with 50 µm pitch is arranged to match the dimensions of a PIN Si-sensor matrix; charge readout, signal shaping and amplitude discrimination is performed at pixel-level, by means of a low-power (<18 µW) analog processor, which, in case of an event, negotiates access to an analog bus placed every other column; on the chip periphery (balcony), the information on each bus is digitized by an array of successive approximation analog-to-digital converters (SAR-ADCs) running at 10 Msps; on the digital back-end the global logic will generate the output data stream using low-voltage differential signalling (LVDS). A first prototype of the SparkPix-S, with a reduced matrix size of 96×96 pixels, is currently under production on a 130 nm CMOS technology. Simulated performance results show an equivalent noise charge <60 el. r.m.s. at 1 MHz repetition rate, with a maximum input energy of 60 keV and capability to discriminate charge signals with equivalent energy as low as 900 eV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning

Abstract Ground motions associated with aircraft overflights can cover a significant portion of the seismic data collected by shallowly emplaced seismometers, such as new nodal and Distributed Acoustic Sensing systems. This article describes the first published framework for automated detection of aircraft on single channel and multichannel seismic data. The seismic data are converted to spectrograms in a sliding time window and classified as aircraft or nonaircraft in each window using a deep convolutional neural network trained with analyst-labeled data. A majority voting scheme is used to convert the output from the sequence of sliding time windows onto a decision time sequence for each channel and to combine the binary classifications on the decision time sequences across multiple channels. Precision, recall, and F-score are used to quantify the detection performance of the algorithm on nodal data using fourfold time-series cross validation. By applying our framework to data from the Sage Brush Flats nodal array in Southern California, we provide a benchmark performance and demonstrate the advantage of using an array of sensors.

Geochemistry & Geophysics↗

DOE OSTI2023

Testing of an Optical Fiber--Based Gamma Thermometer in the High Flux Isotope Reactor Gamma Irradiation Facility

This report describes the design, thermal modeling, and gamma irradiation testing of an optical fiber–based gamma thermometer (OFBGT), which was irradiated in the High Flux Isotope Reactor (HFIR) Gamma Irradiation Facility (GIF). OFBGTs are a promising technology for application in nuclear reactors because they can provide a distributed measurement of gamma ray heating rate, unlike thermocouple-based gamma thermometers, which are fixed in-core sensors that can be used in boiling water reactors to calibrate local power range monitors. OFBGTs measure gamma ray heating rate by measuring the temperature difference between a pair of optical fibers; one fiber is in thermal contact with a heat sink (usually the reactor coolant), and the other is in thermal contact with a thermally isolated mass. The device can be calibrated with a heating wire within the thermal mass. The OFBGT that was designed and fabricated at Oak Ridge National Laboratory can measure distributed gamma ray heating rate over an effective measurement length of 61 cm, and the outer diameter of the sensor is 12.7 mm, giving the prototypical sensor design a relatively small footprint. The sensor housing is backfilled with Ar to ensure a well-predicted thermal response that is not affected by humidity or chemical interactions during operation. For calibration, the sensor design uses a Ni–Cr wire, which can be supplied with currents from 0 to 1 A to capture the wide range of potential gamma ray heating rates expected in HFIR’s spent fuel elements. The OFBGT was thermally modeled analytically and numerically; both models account for temperature-dependent thermal conductivities of the materials and show good agreement. The thermal response of the sensor inside spent HFIR fuel elements was simulated for times up to 1 year after discharge of the fuel element. Out-of-pile open-air tests indicated that the steady-state response of the sensor matches modeled results within experimental uncertainty. Calibration tests were performed using electrical heating in the HFIR spent fuel pool, above the fuel elements, to establish a relationship between the difference in spectral shift measured by optical fibers located inside and outside the OFBGT and the applied electrical heating. Subsequently, the OFBGT was placed within the the spent fuel element from HFIR cycle 501 to measure the spatial profile of the gamma heating rates. Results showed good agreement between the theoretical and measured gamma dose rate profiles, with maximum deviations of ~10% or less.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

CMS Outer Tracker Module QA

The High Luminosity Large Hadron Collider is a planned upgrade to the LHC that will allow it to take up to 7 times as much data. Upgrades to all detector systems, including the Outer Tracker, are necessary to allow them to handle the increased radiation and pileup. Fermilab has been tasked with assembling modules for the Outer Tracker system. This presentation discusses the QA tests performed on these modules and the integration procedure required to ensure all modules work in sync. The QA tests include sensor IV curves, MaPSA testing, visual inspection, skeleton testing, and module testing. There are additional tests that can only be performed on integrated modules that are working in sync, and developing an understanding of the timing and latency of the modules is necessary to perform this synchronization.

Hobbeheydar, Samuel [Fermilab; Carnegie Mellon U. ↗

DOE OSTI2026

CMS Outer Tracker Module QA

Hobbeheydar, Samuel [Fermilab; Carnegie Mellon U. ↗

DOE OSTI2021

Direct Mercury Detection in Landfill Leachate Using a Novel AuNP-Biopolymer Carbon Screen-Printed Electrode Sensor

A novel Au nanoparticle (AuNP)-biopolymer coated carbon screen-printed electrode (SPE) sensor was developed through the co-electrodeposition of Au and chitosan for mercury (Hg) ion detection. This new sensor showed successful Hg2+ detection in landfill leachate using square wave anodic stripping voltammetry (SWASV) with an optimized condition: a deposition potential of −0.6 V, deposition time of 200 s, amplitude of 25 mV, frequency of 60 Hz, and square wave step voltage of 4 mV. A noticeable peak was observed at +0.58 V associated with the stripping current of the Hg ion. The sensor exhibited a good sensitivity of ~0.09 μA/μg (~0.02 μA/nM) and a linear response over the concentration range of 10 to 100 ppb (50–500 nM). The limit of detection (LOD) was 1.69 ppb, which is significantly lower than the safety limit defined by the United States Environmental Protection Agency (USEPA). The sensor had an excellent selective response to Hg2+ in landfill leachate against other interfering cations (e.g., Zn2+, Pb2+, Cd2+, and Cu2+). Fifteen successive measurements with a stable peak current and a lower relative standard deviation (RSD = 5.1%) were recorded continuously using the AuNP-biopolymer-coated carbon SPE sensor, which showed excellent stability, sensitivity and reproducibility and consistent performance in detecting the Hg2+ ion. It also exhibited a good reliability and performance in measuring heavy metals in landfill leachate.

Hwang, Jae-Hoon (ORCID:0000000220100864)↗

DOE OSTI2020

WEC fault modelling and condition monitoring: A graph-theoretic approach

The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC-Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph-theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.

16 TIDAL AND WAVE POWER↗