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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Review of Existing Test Methods for Occupancy Sensors

One of the key new features of connected lighting systems (CLS) is their ability to collect data from various types of integral sensors and share that data with other lighting or building systems. Occupancy and vacancy sensors have been widely adopted as an energy-saving strategy in buildings, yet published test methods for reproducibly characterizing their performance remain few and limited in their sophistication. As a result, it has been difficult to predict the performance of such sensors in a specific application, and in practice, they frequently do not meet energy-savings expectations. Occupants at times remove or otherwise bypass occupancy sensors that hinder their work or otherwise do not perform as expected, thereby compromising the sensors’ potential to reduce energy consumption. Poor performance can result from multiple causes – ranging from fundamental limitations of the sensor technology, to misconfiguration, to poor placement in the room or space. Innovative occupancy sensors, some of them combining multiple sensing technologies (i.e., multimodal), have come on the market over the years, with claims of improved performance compared to their predecessors. However, in practice, their performance has neither differed enough from the performance of previous products to necessitate a test method that facilitated comparison between them, nor has it led to high deployment or high user satisfaction in human-occupied spaces with persistent presence. While the performance of both common and novel occupancy sensors has been the subject of many published research articles, the test methods that have been employed for them typically have been loosely described and have incorporated custom equipment or techniques that render them difficult to reproduce, or have been limited in their ability to fairly characterize devices that utilize varying sensor technology. The lack of a fully described, technology-agnostic test method that yields reproducible results across different implementations has been a barrier to the commercial success of new occupancy-sensor products, as users and specifiers who have been disappointed with previous products are often unwilling to take a chance with new ones. Motivated by a desire to fairly characterize new technologies that continue to enter the market and claim not only improved occupancy detection but, in some cases, additional capabilities (e.g., the ability to measure traffic or discern between different object types), this report presents the results of a literature review of recently published fully described test methods for characterizing occupancy-sensor performance, as well as research articles containing ad-hoc test methods. The review also identifies and consolidates test conditions for characterizing sensor performance in indoor spaces and identifies apparent test method gaps that need to be filled in order to evaluate emerging technologies and products. The identified test-method conditions are intended to enable the development of a future technology-agnostic test method that facilitates occupancy-sensor performance characterization more-accurately representing performance in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Outdoor Test Bed Performance of a Power Line Sensor Using a Real-Time Event Simulator

This report summarizes the design and application of an outdoor power line sensor testbed (OPLST) with a real-time simulator and power meter to compare a potential transformer (PT) and current transformer (CT) versus an advanced line-post sensor. The OPLST was created to validate advanced medium-voltage (20/34.5 kV) outdoor power line sensors used in electrical distribution systems. Electrical utilities have installed metering and relay-protection transformers like PTs and CTs for several decades. The PTs/CTs are iron core measurement transformers based on the electromagnetic induction principle and provide reliable data in normal grid operation. However, new outdoor power line sensors (OPLS) using other technologies like voltage divider, Rogowski coil and optical principles have become available and may have favorable performance and costs compared to PTs/CTs. Therefore, the importance of testing these technologies with the PT/CT, to compare the measured phase voltage/current at different power grid scenarios is crucial to understand the performance of these new OPLS. For this study a G&W Electric Model CVS-36-O power line sensor was chosen as the OPLS to test with voltage/current signals. An OPAL-RT Technologies Model OP4510 real-time simulator and Schweitzer Engineering Laboratories Model SEL-735 power meter were installed with the 20/34.5 kV OPLST to compare the measured transient events collected from an advanced OPLS and the PT/CT. This system is installed at the Distributed Energy Communications and Control (DECC) lab, Oak Ridge National Laboratory (ORNL). The simulator generated different power grid scenarios (electrical faults, capacitor bank operation, service restoration, etc.), and its analog-output signals were connected to the voltage/current amplifiers that feed the 20/34.5 kV aerial cable loop through the PT/CT devices. Additional PT/CT devices were also wired with the medium voltage aerial cable loop to measure the phase current/voltage signals and server as references. After each test, common format for transient data exchange (COMTRADE) files were collected from the SEL-735 power meter and used to compare the performance of the OPLS with the PT/CT. The behavior of analog signals, harmonic components, total harmonic distortion and crest factors were assessed and found favorable for the G&W sensor as compared to the reference PT/CT.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Performance of Microreactor Test Article with Embedded Sensors During Testing in The Single Primary Heat Extraction and Removal Emulator

The nuclear industry is pursuing microreactors that can be factory assembled and deployed to remote regions for reliable power generation. One class of microreactors uses a monolithic metal core block coupled to heat pipes that use passive heat flow, increasing the surface area for heat transfer without requiring active coolant flow through the reactor core. Additional experimental testing is required to understand the heat rejection limitations of heat pipes and thermal stresses in the monolithic core block due to significant temperature gradients. This report describes the initial characterization and testing of a stainless-steel test article that was fabricated with embedded sensors to measure heat pipe performance limits, as well as spatially distributed temperatures and strains during electrically heated thermal testing to simulate nuclear heating. The electrically heated testing was performed in the Single Primary Heat Extraction and Removal Emulator facility located at Idaho National Laboratory. The ultimate goals of this work are to (1) accurately monitor temperature and strain distributions that result from differential thermal expansion in the test articles and (2) quantify the heat rejection limits of heat pipes as a function of operating temperature and working fluid during steady-state and transient operations. Initial tests focused on the feasibility of using advanced fiber-optic sensors and other sensor technologies to improve the understanding of temperature and strain distributions within the electrically heated experiments. However, these sensing capabilities could benefit the broader microreactor community if the sensors could be used to monitor component and system health during nuclear operations to inform a limited number of microreactor operators, ultimately reducing operation and maintenance costs and moving toward semiautonomous operation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

High Throughput Data-Driven Design of Laser-Crystallized 2D MoS 2 Chemical Sensors: A Demonstration for NO 2 Detection

High throughput characterization and processing techniques are becoming increasingly necessary to navigate multivariable, data-driven design challenges for sensors and electronic devices. For two-dimensional materials, device performance is highly dependent upon a vast array of material properties including the number of layers, lattice strain, carrier concentration, defect density, and grain structure. In this work, laser crystallization was used to locally pattern and transform hundreds of regions of amorphous MoS 2 thin films into 2D 2H-MoS 2 . Here a high throughput Raman spectroscopy approach was subsequently used to assess the process-dependent structural and compositional variations for each illuminated region, yielding over 6000 distinct nonresonant, resonant, and polarized Raman spectra. The rapid generation of a comprehensive library of structural and compositional data elucidated important trends between structure–property processing relationships involving laser-crystallized MoS 2 , including the relationships between grain size, grain orientation, and intrinsic strain. Moreover, extensive analysis of structure/property relationships allowed for intelligent design and evaluation of major contributions to device performance in MoS 2 chemical sensors. In particular, it is found that NO 2 sensor performance is strongly dependent on the orientation of the MoS 2 grains relative to the crystal plane.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Setups for eliminating static charge of the ATLAS18 strip sensors

Abstract Construction of the new all-silicon Inner Tracker (ITk), developed by the ATLAS collaboration to beable to track charged particles produced at the High-Luminosity LHC, started in 2020 and is expected tocontinue till 2028. The ITk detector will include 18,000 highly segmented and radiation hard n+-in-psilicon strip sensors (ATLAS18), which are being manufactured by Hamamatsu Photonics. Mechanical and electrical characteristics of produced sensors are measured upon their delivery at several institutes participating in a complex Quality Control (QC) program. The QC tests performed on each individual sensor check the overall integrity and quality of the sensor.During the QC testing of ATLAS18 strip sensors, an increased number of sensors thatfailed the electrical tests was observed. In particular, IV measurements indicated an early breakdown,while large areas containing several tens or hundreds of neighbouring strips with low interstrip isolationwere identified by the Full strip tests, and leakage current instabilities were measured in a long-term leakage current stability setup. Moreover, a high surface electrostatic charge reaching a level of several hundreds of volts per inch was measured on a large number of sensors and on the plastic sheets, whichmechanically protect these sensors in their paper envelopes. Accumulated data indicates a clearcorrelation between observed electrical failures and the sensor charge-up.To mitigate the above-described issues, the QC testing sites significantly modified the sensor handlingprocedures and introduced sensor recovery techniques based on irradiation of the sensor surface with UVlight or application of intensive flows of ionized gas. In this presentation, we will describe the setupsimplemented by the QC testing sites to treat silicon strip sensors affected by static charge andevaluate the effectiveness of these setups in terms of improvement of the sensor performance.

Instruments & Instrumentation↗
DOE OSTI2021

Electromechanical response of piezoelectric thin films subjected to large strain

The use of piezoelectric thin sensors, when subjected to large static strain levels in ultrasonic applications is reported in this paper. A novel flipped beam bending method is proposed to induce static strain level nearing twice the incipient yield strain in the beam material (~0.39%). First, the effect of static large strain on ultrasonic guided wave propagation in the beam was studied using the velocity measurements obtained from a laser Doppler vibrometer. Next, the ultrasonic response of thin sensors is studied under compressive and tensile static strain (±0.72%) with the sensors symmetrically bonded on the lower and upper surfaces, and at the same axial location. The ultrasonic guided wave response to varying levels of static strain is recorded at different center frequencies (50–400 kHz) of the narrow banded ultrasonic excitation. As a case study, the variation of the ultrasonic guided wave response of polyvinylidene difluoride (PVDF) thin sensors with center frequencies at different static strain levels was analyzed and compared with that of lead zirconate titanate (PZT) thin sensors. PZT sensors show a higher variation of sensing performance with strain when compared to PVDF sensors. Apart from static strain, the possible effects on the change in performance of sensors, such as the change in the capacitance is discussed. The characterization method provides a reusable beam arrangement to study the ultrasonic sensor performance at large static strain levels. Characterization at large strain level allows the development of fail-safe sensors even under large strain and permanent plastic deformation of structure on which they are bonded, allowing accurate ultrasonic structural health monitoring even in the presence of damage progression. Piezopolymer sensor like PVDF are least susceptible to static strain due to large yield strain and low modulus and can serve as fail-safe sensors under large strain.

Rathod, Vivek↗
DOE OSTI2024

Performance of Pixel and Strip AC-LGAD Sensors with Different Design Parameter on a 120 GeV Proton Beam

We present the results of an extensive evaluation of strip and pixel AC-LGAD sensors tested with a 120 GeV proton beam, focusing on the influence of design parameters on the sensor temporal and spatial resolutions. Results show that reducing the thickness of pixel sensors significantly enhances their time resolution, with 20- μm-thick sensors achieving around 20 ps. Uniform performance is attainable with optimized sheet resistance, making these sensors ideal for future timing detectors. Conversely, 20-μm-thick strip sensors exhibit higher jitter than similar pixel sensors, negatively impacting time resolution, despite reduced Landau fluctuations with respect to the 50-μm-thick versions. Additionally, it is observed that a low resistivity in strip sensors limits signal size and time resolution, whereas higher resistivity improves performance. This study highlights the importance of tuning the n+ sheet resistance and suggests that further improvements should target specific applications like the Electron-Ion Collider or other future collider experiments. In addition, the detailed performance of four AC-LGADs sensor designs is reported as examples of possible candidates for specific detector applications. These advancements position AC-LGADs as promising candidates for future 4D tracking systems, pending the development of specialized readout electronics.

Lara, Carlos Pérez↗
DOE OSTI2024

Beam test performance studies of CMS Phase-2 Outer Tracker module prototypes

A new tracking detector will be installed as part of thePhase-2 upgrade of the CMS detector for the high-luminosity LHC era.This tracking detector includes the Inner Tracker, equipped withsilicon pixel sensor modules, and the Outer Tracker, consisting ofmodules with two parallel stacked silicon sensors. The Outer Trackerfront-end ASICs will be able to correlate hits from chargedparticles in these two sensors to perform on-module discriminationof transverse momenta (p$_{T}$). The p$_{T}$information is generated at a frequency of 40 MHz and will be usedin the Level-1 trigger decision of CMS. Prototypes of theso-called 2S modules were tested at the Test Beam Facility at DESYHamburg between 2019 and 2020. These modules use the finalfront-end ASIC, the CMS Binary Chip (CBC), and for the firsttime the Concentrator Integrated Circuit (CIC), optical readoutand on-module power conversion. In total, seven modules were tested,one of which was assembled with sensors irradiated with protons. Animportant aspect was to show that it is possible to read out modulessynchronously. A cluster hit efficiency of about 99.75 % wasachieved for all modules. The CBC p$_{T}$ discriminationmechanism has been verified to work together with the CIC andoptical readout. The measured module performance meets therequirements for operation in the upgraded CMS tracking detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Wireless Patch Antenna Characterization for Live Health Monitoring Using Machine Learning

Temperature monitoring in extreme environments, such as coal-fired power plants, was addressed by designing and testing wireless patch antennas for use in machine learning-aided temperature estimation. The sensors were designed to monitor the temperature and health of boiler systems. Wireless interrogation of the sensor was performed using a Vector Network Analyzer (VNA) and a pair of interrogation antennas to capture resonance behavior under varying thermal and spatial conditions with sensitivities ranging from 0.052 to 0.20 $\frac{𝑀𝐻𝑧}{°C}$. Sensor calibration was conducted using a Long Short-Term Memory (LSTM) model, which leveraged temporal patterns to account for hysteresis effects. The calibration method demonstrated improved performance when combined with an LSTM model, achieving up to a 76% improvement in temperature estimation error when compared with Linear Regression (LR). The experiments highlighted an innovative solution for patch antenna-based non-contact temperature measurement, which addresses limitations with conventional methods such as RFID-based systems, infrared, and thermocouples.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Single-atom materials boosting wearable orthogonal uric acid detection

Abstract Uric acid (UA) is a vital biomarker for the diagnosis and management of various health conditions, including cardiovascular diseases, gout, kidney disorders, metabolic syndrome, and wound healing. Despite significant advances in wearable sensor technology, challenges persist in developing wearable sensors that are capable of maintaining high sensitivity, selectivity, and stability. In this study, we present an epidermal sensing platform enhanced with single-atom materials (SAMs) designed for flexible and orthogonal electrochemical detection of UA. We designed and synthesized an SAM with Fe-N 5 active sites to boost the electrochemical sensing signals, integrating it with laser-engraved graphene (LEG) to fabricate a wearable SAM-based UA patch sensor. This design provides superior UA detection performance compared to sensors based on conventional nanomaterials. In addition, we enhanced the detection accuracy and range by using an orthogonal approach that combines direct oxidation through differential pulse voltammetry (DPV) along with parallel biocatalytic amperometric detection. The resulting SAM-based UA orthogonal sensor patch demonstrated exceptional performance in wearable applications through tests measuring sweat UA levels in subjects before and after consuming a purine-rich diet. Graphical Abstract

Ding, Shichao↗
DOE OSTI2022

Flexible CO 2 Sensor Architecture with Selective Nitrogen Functionalities by One‐Step Laser‐Induced Conversion of Versatile Organic Ink

Abstract Nitrogen‐containing carbons (NC) are a class of sustainable materials for selective CO 2 adsorption. A versatile concept is introduced to fabricate flexible NC‐based sensor architectures for room‐temperature sensing of CO 2 in a one‐step laser conversion of primary films cast from abundant precursors. By the unidirectional energy impact in conjunction with depth‐dependent attenuation of the laser beam, a layered sensor heterostructure with a porous transducer and active sensor layer is formed. Comprehensive microscopic and spectroscopic cross‐sectional analyses confirm the preservation of the high content of imidazolic nitrogen in the sensor. The performance is optimized in terms of material morphology, chemical composition, and surface chemistry to achieve a linear relative resistive response of up to Δ R / R 0 = −14.3% (10% of CO 2 ). Thermodynamic analysis yields Δ ads H values of −35.6 and 34.1 kJ·mol −1 for H 2 O and CO 2 , respectively. The sensor is operable even in humid environments (e.g., ∆ R / R 0,RH = 80% = 0.53%) and shows good performance upon strong mechanical deformation.

flexible gas sensors↗
DOE OSTI2023

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 μS/cm) and the mean precision of all other sensors combined (9.12 μS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Molecular Engineering of 2D Nanomaterial Field-Effect Transistor Sensors: Fundamentals and Translation across Innovation Spectrum

We report over the last decade, 2D layered nanomaterials have attracted significant attention across the scientific community due to their rich and exotic properties. Various nanoelectronic devices based on these 2D nanomaterials have been explored and demonstrated, including those for environmental applications. Here, the fundamental attributes of 2D layered nanomaterials for field-effect transistor (FET) sensors and tunneling FET (TFET) sensors, which provide versatile detection of water contaminants such as heavy-metal ions, bacteria, nutrients, and organic pollutants, are discussed. The major challenges and opportunities are also outlined for designing and fabricating 2D nanomaterial FET/TFET sensors with superior performance. Translation of these FET/TFET sensors from fundamental research to applied technology is illustrated through a case study on graphene-based real-time FET water sensors. A second case study centers on large-scale sensor networks for water-quality monitoring to enable intelligent drinking water and river-water systems. Overall, 2D nanomaterial FET sensors have significant potential for enabling a human-centered intelligent water system that can likely be applied to other precarious water supplies around the globe.

2D nanomaterials↗
DOE OSTI2021

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

Abstract The femtosecond laser has emerged as a powerful tool for micro- and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization, high-temperature stable, Type II femtosecond laser modifications were continuously inscribed, point by point, with only an insertion loss at 1 dB m −1 or 0.001 dB per point sensor device. High-temperature performance of fiber sensors was tested at 1000 °C, which showed a temperature fluctuation of ±5.5 °C over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Wang, Mohan (ORCID:0000000166784993)↗
DOE OSTI2020

Artificial illumination identification from an unmanned aerial vehicle

Artificial illumination identification within images is a useful tool for many applications. Performing such identification allows for an estimation of the illumination source spectrum, which in turn can be used for additional applications ranging from spectral detection and exploitation to statistics about nighttime light usage. Illumination identification has been performed in laboratory settings but not from an unmanned aerial vehicle (UAV) platform. Here, we test the feasibility of using a UAV and commercial off-the-shelf multispectral imaging sensor to perform such artificial illumination identification through linear discriminant analysis using nighttime UAV images. The results are very promising, showing source classification accuracies of 83.3%, 92.3%, 100%, and 100% for the incandescent, light-emitting diode, high pressure sodium, and metal halide illumination sources, respectively. We show that the information gained from the source identification can be further used to inform additional analysis, such as spectral identification. The high resolution of UAV imaging techniques combined with the knowledge of the illumination source can lead to better exploitation of such nighttime data for many applications.

42 ENGINEERING↗
DOE OSTI2020

Layout and performance of HPK prototype LGAD sensors for the High-Granularity Timing Detector

The High-Granularity Timing Detector is a detector proposed for the ATLAS Phase II upgrade. The detector, based on the Low-Gain Avalanche Detector (LGAD) technology, will cover the pseudo-rapidity region of 2.4 < |n| < 4.0 with two end caps on each side and a total area of 6.4 m 2 . The timing performance can be improved by implanting an internal gain layer that can produce signals with a fast rising edge. It significantly improves the signal-to-noise ratio. The required average timing resolution per track for a minimum ionizing particle is 30 ps at the start and 50 ps at the end of the HL-LHC operation. This is achieved with several layers of LGAD. The innermost region of the detector would accumulate a 1MeV neutron-equivalent fluence up to 2.5 10 15 n eq /cm 2 including a safety factor of 1.5 before being replaced during the scheduled shutdowns. The addition of this new detector is expected to play an important role in the mitigation of high pile-ups at the HL-LHC. The layout and performance of the various versions of LGAD prototypes produced by Hamamatsu (HPK) have been studied by the ATLAS Collaboration. The breakdown voltages, depletion voltages, inter-pad gaps, collected charge as well as the time resolution have been measured and the production yield of large size sensors has been evaluated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗