Results for “sensor performance” — Page 38

DOE OSTI2023

First survey of centimeter-scale AC-LGAD strip sensors with a 120 GeV proton beam

We present the first beam test results with centimeter-scale AC-LGAD strip sensors, using the Fermilab Test Beam Facility and sensors manufactured by the Brookhaven National Laboratory. Sensors of this type are envisioned for applications that require large-area precision 4D tracking coverage with economical channel counts, including timing layers for the Electron Ion Collider (EIC), and space-based particle experiments. A survey of sensor designs is presented, with the aim of optimizing the electrode geometry for spatial resolution and timing performance. Several design considerations are discussed towards maintaining desirable signal characteristics with increasingly larger electrodes. The resolutions obtained with several prototypes are presented, reaching simultaneous 18 μm and 32 ps resolutions from strips of 1 cm length and 500 μm pitch. With only slight modifications, these sensors would be ideal candidates for a 4D timing layer at the EIC.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

First survey of centimeter-scale AC-LGAD strip sensors with a 120 GeV proton beam

We present the first beam test results with centimeter-scale AC-LGAD strip sensors, using the Fermilab Test Beam Facility and sensors manufactured by the Brookhaven National Laboratory. Sensors of this type are envisioned for applications that require large-area precision 4D tracking coverage with economical channel counts, including timing layers for the Electron Ion Collider (EIC), and space-based particle experiments. A survey of sensor designs is presented, with the aim of optimizing the electrode geometry for spatial resolution and timing performance. Several design considerations are discussed towards maintaining desirable signal characteristics with increasingly larger electrodes. The resolutions obtained with several prototypes are presented, reaching simultaneous 18 micron and 32 ps resolutions from strips of 1 cm length and 500 micron pitch. With only slight modifications, these sensors would be ideal candidates for a 4D timing layer at the EIC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.

Brown, Nicolas E.↗

DOE OSTI2024

Electrical design of the flexible imaging diffraction diagnostic for laser experiments (FIDDLE) at the National Ignition Facility (NIF)—Requirements, design, and performance

The Flexible Imaging Diffraction Diagnostic for Laser Experiments (FIDDLE) is a newly developed diagnostic for imaging time resolved diffraction in experiments at the National Ignition Facility (NIF). It builds on the successes of its predecessor, the Gated Diffraction Development Diagnostic (G3D). The FIDDLE was designed to support eight Daedalus version 2 sensors (six more hCMOS sensors than any other hCMOS-based diagnostic in NIF to date) and an integrated streak camera. We will review the electrical requirements, design, and performance of the electrical subsystems that were created to support this large number of cameras in the FIDDLE. The analysis of the data that the FIDDLE is intended to collect relies heavily on the accurate and well-understood timing of each sensor. We report camera-to-camera timing jitter of less than 100 ps rms and sensor integration times of 2.2 ns FWHM in 2-2 timing mode. Additionally, diffraction experiments on the NIF produce electric fields (EMI) on the order of 1 kV/m, which have been observed to negatively impact the performance of some electrical components of the FIDDLE. We report on the results of testing hCMOS camera electronics in a similar EMI environment generated in an offline lab. In addition, we also summarize the use of a novel approach to using a vector network analyzer as an EMI leak detector to understand and reduce the negative impacts of EMI on the FIDDLE.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Multi-Functional Distributed Fiber Sensors for Pipeline Monitoring and Methane Detections. Final Report

As an abundant and cheap fossil energy source, natural gas has become a significant energy supply to support the United States’ economy. However, the large-scale extraction and utilization of natural gas also impose significant challenges on methane leakage. This problem is exacerbated by aging gas utility delivery systems, including interstate high-pressure pipelines, storage, and transmission facilities. This project aims to develop a cost-effective fiber optical sensing method that can perform multi-parameter real-time measurements of natural gas pipelines across long interrogation distances up to 100 km with 1-meter spatial resolution. This sensing tool can evaluate overall pipeline efficiency and reduce methane emissions for mid-stream methane infrastructures. To accomplish this objective, research and development efforts funded by this project have resulted in the following accomplishments: This project successfully has developed new functional sensory polymer materials using Metal-Organic Frameworks (MOFs) that can be coated on optical fiber through the reel-to-reel coating process. Functional polymer-coated optical fibers can perform sensitive methane detection through evanescence wave interaction and strain-based measurements to achieve 1% detection sensitivities. The new sensors fibers support both distributed measurements and multiplexed fiber sensors array for multi-point measurements. This project developed and optimized a new multi-core optical fiber that supports simultaneous and distributed measurements of strain and temperatures with 1-meter spatial resolutions across up to 100-km interrogation distance. This new fiber, combined with sensory polymercoated fiber, could perform both distributed temperature and methane detections. This project developed a new artificial intelligence big data algorithm approach that can effectively analyze high-resolution data harnessed by distributed fiber sensors to protect natural gas pipelines against external threats and detect internal defects induced by corrosion. Working with our industry partner, this project developed new optical fibers that support fiber sensor fabrications through polymer coating after the fibers are drawn. These new fibers eliminate the need for direct sensor fabrication when the fiber is fabricated on a fiber draw tower, which drastically expands fiber sensors' applicability. This research project has significantly advanced the distributed fiber sensing technology. It will dramatically increase the applicability and adaptability of distributed fiber sensors for a wide array of applications in energy, sustainability, and environmental science, including structural health monitoring of natural gas pipelines, oil infrastructures, hydrogen facilities, and environmental monitoring of carbon storage sites, water supply systems, and others.

03 NATURAL GAS↗

DOE OSTI2025

A sensing material-free and simple readout MEMS sensor for detecting Helium

Abstract In this work, we report a method that enables a standard electrostatic MEMS device to perform complex sensing functionalities, such as detecting the presence of helium without a sensing material or a conditioning circuit. Helium is a noble, odorless, non-reactive gas that is very challenging to detect. It is used in critical applications such as storing nuclear fuel waste inside a dry cask. In these applications, its leakage from the dry cask may indicate the cask's safe operation's degradation. A departure from the common practice of exciting the MEMS around its mechanical resonance, the method is based on exciting the MEMS around its electrical resonance circuit. This method shows that the tiny difference between the air dielectric constant (1.00059) and helium (1.000067) corresponding to only a few Femtofarad level capacitances produces a 25 mV difference without a conditioning circuit. Simulation results confirmed those findings and explored the sensor response at different operation conditions. This method eliminates the need for a heated microstructure and the need for absorption material. This method is not limited to gas sensing. It can be applied to other sensing mechanisms, such as acceleration and pressure measurements, and eliminate the complex circuit to read small capacitance in these applications.

Mohaidat, Sulaiman↗

DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗

DOE OSTI2023

Report of METL Mutual Inductance Level Sensor Development for Use in Liquid Metals – FY2023

A robust mutual inductance level sensor (MILS) for use in high temperature liquid metals has been developed at Argonne National Laboratory (ANL). The current design utilizes mineral insulated cables with a 300-series stainless steel sheath, magnesium oxide insulation, and a single copper conductor. Two coils are wrapped on a common core made of a 300-series stainless steel tube. One coil is energized with an alternating current (AC) source, and this electromagnetically couples with the second coil to generate an induced voltage. The voltage is measured to determine the mutual induction between the coils, and the mutual inductance measurement can be used to determine the level of a nearby liquid metal volume. The MILS can be located in an isolating thimble that is fully sealed to a vessel containing liquid metal for ease of maintenance and replacement. When the primary coil is energized with the AC source, the coil not only electromagnetic (EM) couples with the second coil, but also the surrounding liquid metal. The EM coupling with the surrounding liquid metal reduces the EM coupling with the second coil, producing an inverse-linear relationship between liquid metal level and secondary coil voltage. This has all been demonstrated at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at ANL. The most current iteration of the MILS system is the MILS-MK-II. This sensor system has been commissioned in a non-sodium test stand where calibrations were performed using a sodium analog. The calibrations proved to be highly linear and repeatable. The MILS-MK-II has been installed in the METL expansion tank where high temperature sodium tests have been performed. The MILS-MK-II has been calibrated against a known standard at temperature of 300°C, and the calibrations have proved to be highly linear and repeatable. The calibrated MILS-MK-II has been in operation in the METL facility for several thousands of hours at temperatures around 300°C. The experimental data has been used to develop and validate electromagnetic finite element models in COMSOL Multiphysics, and now these models can be used to advance the development of the sensor system. Next steps will include temperature compensation to allow for operation at various temperatures. Additionally, efforts to incorporate a self-calibration methodology are underway.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Development of risk mitigation guidance for sensor placement inside mechanically ventilated enclosures – Phase 1

Guidance on Sensor Placement was identified as the top research priority for hydrogen sensors at the 2018 HySafe Research Priority Workshop on hydrogen safety in the category Mitigation, Sensors, Hazard Prevention, and Risk Reduction. This paper discusses the initial steps (Phase 1) to develop such guidance for mechanically ventilated enclosures. This work was initiated as an international collaborative effort to respond to emerging market needs related to the design and deployment equipment for hydrogen infrastructure that is often installed in individual equipment cabinets or ventilated enclosures. The ultimate objective of this effort is to develop guidance for an optimal sensor placement such that, when integrated into a facility design and operation, will allow earlier detection at lower levels of incipient leaks, leading to significant hazard reduction. Reliable and consistent early warning of hydrogen leaks will allow for the risk mitigation by reducing or even eliminating the probability of escalation of small leaks into large and uncontrolled events. To address this issue, a study of a real-world mechanically ventilated enclosure containing GH2 equipment was conducted, where CFD modeling of the hydrogen dispersion (performed by AVT and UQTR, and independently by the JRC) was validated by the NREL Sensor laboratory using a Hydrogen Wide Area Monitor (HyWAM) consisting of a 10-point gas and temperature measurement analyzer. In the release test, helium was used as a hydrogen surrogate. Expansion of indoor releases to other larger facilities (including parking structures, vehicle maintenance facilities and potentially tunnels) and incorporation into QRA tools, such as HyRAM is planned for Phase 2. It is anticipated that results of this work will be used to inform national and international standards such as NFPA 2 Hydrogen Technologies Code, Canadian Hydrogen Installation Code (CHIC) and relevant ISO/TC 197 and CEN documents.

08 HYDROGEN↗

DOE OSTI2026

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments

In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Wireless Sensor Modalities at a Nuclear Plant Site to Collect Vibration Data

One of the major contributors to the total operating costs of domestic nuclear fleet of reactors today is the operation and maintenance (O&M) costs. These include labor-intense preventive maintenance programs involving manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets at periodic frequency, irrespective of their conditions. This has resulted in a labor-centric business model to achieve high capacity factors. To build an optimal maintenance program, it’s time to transition from this labor-centric business model to a technology-centric business model. Fortunately, there are technologies (advanced sensor, data analytics, and risk assessment methodologies) that will support this transition. The technology-centric business model will result in significant plant life extension and reduction of time-based maintenance activities. This will drive down O&M costs as labor is a rising cost and technology is a declining cost. This approach will lay the foundation for real-time condition assessment of plant assets, allowing condition-based maintenance to enhance plant safety, reliability, and economics of operation. The goal of this project is to address challenges in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and science-based data analytic capabilities to advance online monitoring and predictive maintenance in nuclear plants to improve plant performance (efficiency gain and economic competitiveness). To achieve the project goal, in partnership with Exelon Generating Company (Exelon), researchers from Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) are performing research and development (R&D) to demonstrate application of wireless sensors using the distributed antenna system and advanced data analytics to achieve predictive maintenance. In the report, wireless vibration sensors, vibration data and its indicator are described. The wireless vibration sensors presented in this report support three types of wireless communication, namely, Wi-Fi, cellular, and 900 MHz. These wireless vibration sensors are considered by partner plant site for installation on plant asset to enable online vibration monitoring to replace periodic measurements. These vibration data along with other plant process data will be utilized to develop diagnostic and prognostic models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

DOE OSTI2026

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

DOE OSTI2026

In-Situ Magnetic Field Reconstruction in the MAGIS-100 Experiment

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.; Ferm↗

DOE OSTI2022

Monitor for measuring mercury emissions

A mercury emissions monitor includes a mercury sensor tape configured to be fed in a reel-to-reel manner between first and second tape reels, wherein the mercury sensor tape includes a thin metallic film configured to form an amalgam with detected mercury. A mercury collection unit is configured to receive into a chamber a sample of a gas containing mercury, wherein the mercury collection unit is further configured to permit passage of portions of the mercury sensor tape through the chamber containing the gas sample so that the amalgam is formed with the thin metallic film. A mercury analysis unit includes a total reflection x-ray fluorescence (“TXRF”) system configured to perform a TXRF analysis of the amalgam, wherein the mercury analysis unit is configured to permit passage of the mercury sensor tape within a proximity of an XRF detector of the TXRF system. The mercury collection unit and the mercury analysis unit are positioned between the first and second tape reels so that the mercury sensor tape can move in a continuous manner from the first tape reel through the chamber of the mercury collection unit, then within sufficient proximity to the XRF detector, to be then taken up onto the second tape reel.

Kumar, Nalin↗

DOE OSTI2023

Retractable Sensor Poster for ANIMMA 2023 Conference

Material Test Reactors (MTRs) such as the Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL) are used to irradiate nuclear fuels and materials to evaluate their performance after high levels of exposure to a reactor in-pile environment. The test environment within these reactors are extremely harsh and long-term exposure causes sensor decalibration or failure. Most tests only require data points at daily intervals meaning that the sensor does not necessarily need to be in place continuously for the full experiment. One proposed solution to the issue described above is to have a sensor which can be periodically inserted through a guide tube into the test region and retracted; this would act as a reference check on the sensors installed permanently. If a compact and robust enough design can be made, it has the potential to extend the life of the sensor and keep it within calibration. This LRS entry is for a poster summarizing a presentation that will be given at the ANIMMA 2023 conference. The poster will be on display in the Measurement Sciences Laboratory booth at ANIMMA. Most of the material on this poster came from LRS entry INL/CON-23-72797.

42 ENGINEERING↗

DOE OSTI2021

Libpanda: A High Performance Library for Vehicle Data Collection

Cyber-Physical Systems (CPS) generally involve time-critical components due to physical dynamics, therefore necessitating high-performance subsystems. This is also true in data collection scenarios to infer physical phenomena. This paper covers Libpanda as an example of a component that has been designed to address performance issues in CPS implementations. Libpanda is a C++ library that interfaces software with a Comma.ai Panda device. Pandas are used for installation in modern vehicles to read the vehicle CAN bus, providing rich sensor data and limited vehicle control through message injection. The motivation to design lib-panda stems from the lack of performance in Python-based code that runs on inexpensive hardware like a Raspberry Pi. In such situations, Python code would result in utilizing 92% CPU while also dropping around 40% of the CAN packet due to bottlenecks. Without using different tools, inconsistent data collection means a loss of time-based vehicle state interpretation. Libpanda addresses these issues through implementation in a different language and implementation of different design paradigms involving asynchronous calls and multithreading. The Panda also features a GPS module that allows multiple instances to synchronize clocks for large-scale data collection scenarios. Libpanda has been designed with time-synchronization in mind to aid in the measurement of inter-vehicle dynamics. The performance improvements of libpanda have resulted in it becoming an important component in automotive dynamics research that requires a higher technical performance in large-scale experiments.

Bunting, Matthew↗

DOE OSTI2023

Test beam performance of a CBC3-based mini-module for the Phase-2 CMS Outer Tracker before and after neutron irradiation

The Large Hadron Collider (LHC) at CERN will undergo majorupgrades to increase the instantaneous luminosity up to5–7.5×10$^{34}$ cm$^{-2}$s$^{-1}$. This High Luminosityupgrade of the LHC (HL-LHC) will deliver a total of3000–4000 fb$^{-1}$ of proton-proton collisions at acenter-of-mass energy of 13–14 TeV. To cope with thesechallenging environmental conditions, the strip tracker of the CMSexperiment will be upgraded using modules with two closely-spacedsilicon sensors to provide information to include tracking in theLevel-1 trigger selection. This paper describes the performance, ina test beam experiment, of the first prototype module based on thefinal version of the CMS Binary Chip front-end ASIC before and afterthe module was irradiated with neutrons. Results demonstrate thatthe prototype module satisfies the requirements, providing efficienttracking information, after being irradiated with a total fluencecomparable to the one expected through the lifetime of theexperiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗