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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metal-Organic Framework-based Luminescent Sensors for Rare Earth Elements

Rare earth elements (REEs) are crucial for many applications and are particularly important in wind power and electric vehicle technologies, spurring projected demand increases for REEs in coming decades. However, the REE supply is restricted by a monopolistic global marketplace, tedious and costly processing steps for REE production, and environmental hazards associated with mining and processing. Coal and coal-utilization byproducts have emerged as potential domestic sources for REEs, however REE production from these sources is currently hindered by slow and expensive characterization techniques. Here, we demonstrate that metal-organic framework (MOF)-based sensitizers can effectively serve as luminescent sensors capable of rapidly detecting and distinguishing part-per-billion concentration levels of emissive REEs, including terbium, europium, dysprosium, samarium, neodymium, and ytterbium. Importantly, we demonstrate that the MOF structure plays a significant role in tuning the selectivity of the MOF for REEs in acidic environments, an essential step towards deployment in various REE-rich process streams. As a proof-of-concept, we demonstrate sensitive and reversible detection of REEs using a portable fiber-optic spectrometer

Crawford, Scott↗
NASA NTRS1994

Ground-based measurement of surface temperature and thermal emissivity

Motorized cable systems for transporting infrared thermometers have been used successfully during several international field campaigns. Systems may be configured with as many as four thermal sensors up to 9 m above the surface, and traverse a 30 m transect. Ground and canopy temperatures are important for solving the surface energy balance. The spatial variability of surface temperature is often great, so that averaged point measurements result in highly inaccurate areal estimates. The cable systems are ideal for quantifying both temporal and spatial variabilities. Thermal emissivity is also necessary for deriving the absolute physical temperature, and measurements may be made with a portable measuring box.

Owe, M.↗
NASA NTRS2006

Sensing Super-position: Visual Instrument Sensor Replacement

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This project addresses the technical feasibility of augmenting human vision through Sensing Super-position using a Visual Instrument Sensory Organ Replacement (VISOR). The current implementation of the VISOR device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of the human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system.

Maluf, David A.↗
NASA NTRS2013

Robotics On-Board Trainer (ROBoT)

ROBoT is an on-orbit version of the ground-based Dynamics Skills Trainer (DST) that astronauts use for training on a frequent basis. This software consists of two primary software groups. The first series of components is responsible for displaying the graphical scenes. The remaining components are responsible for simulating the Mobile Servicing System (MSS), the Japanese Experiment Module Remote Manipulator System (JEMRMS), and the H-II Transfer Vehicle (HTV) Free Flyer Robotics Operations. The MSS simulation software includes: Robotic Workstation (RWS) simulation, a simulation of the Space Station Remote Manipulator System (SSRMS), a simulation of the ISS Command and Control System (CCS), and a portion of the Portable Computer System (PCS) software necessary for MSS operations. These components all run under the CentOS4.5 Linux operating system. The JEMRMS simulation software includes real-time, HIL, dynamics, manipulator multi-body dynamics, and a moving object contact model with Tricks discrete time scheduling. The JEMRMS DST will be used as a functional proficiency and skills trainer for flight crews. The HTV Free Flyer Robotics Operations simulation software adds a functional simulation of HTV vehicle controllers, sensors, and data to the MSS simulation software. These components are intended to support HTV ISS visiting vehicle analysis and training. The scene generation software will use DOUG (Dynamic On-orbit Ubiquitous Graphics) to render the graphical scenes. DOUG runs on a laptop running the CentOS4.5 Linux operating system. DOUG is an Open GL-based 3D computer graphics rendering package. It uses pre-built three-dimensional models of on-orbit ISS and space shuttle systems elements, and provides realtime views of various station and shuttle configurations.

Johnson, Genevieve↗
DOE OSTI2023

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors and electrochemical RAM. Equally important, Abisko uses a deep codesign approach to pursue this goal by engaging experts from across the entire range of disciplines: materials, devices and circuits, architectures and integration, software, and algorithms. Here, the key objectives of our Abisko project are threefold. First, we are designing an energy-optimized high-performance neuromorphic accelerator based on SNNs. This architecture is being designed as a chiplet that can be deployed in contemporary computer architectures and we are investigating novel neuromorphic materials to improve its design. Second, we are concurrently developing a productive software stack for the neuromorphic accelerator that will also be portable to other architectures, such as field-programmable gate arrays and GPUs. Third, we are creating a new deep codesign methodology and framework for developing clear interfaces, requirements, and metrics between each level of abstraction to enable the system design to be explored and implemented interchangeably with execution, measurement, a model, or simulation. As a motivating application for this codesign effort, we target the use of SNNs for an analog event detector for a high-energy physics sensor.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Remote Sensing of Aircraft Contrails Using a Field Portable Digital Array Scanned Interferometer

With a Digital Array Scanned Interferometer (DASI), we have obtained proof-of-concept observations with which we demonstrate DASI capabilities for the determination of contrail properties. These include the measurement of the cloud and soot microphysical parameters, as well, the abundances of specific pollutant species such as SO(sub x) or NO(sub x). From high quality hyperspectral data and using radiative transfer methods and atmospheric chemistry analysis in the data reduction and interpretation, powerful inferences concerning cloud formation, evolution and dissipation can be made. Under this sub-topic, we will integrate DASI with computer controlled scanning of the field-of-view to direct the sensor towards contrails and exhaust plumes for tracking the emitting vehicles. The optimum DASI wavelength sensitivity range for sensing contrails is 0.35 - 2.5 micron. DASI deploys on the ground or from aircraft to observe contrails in the vicinity. This enables rapid, accurate measurement of the temporal, spatial, and chemical evolution of contrails (or other plumes or exhaust sources) with a low cost, efficient sensor.

Smith, William Hayden↗
NASA NTRS2009

Development of a Portable Oxygen Monitoring System for Operations in the International Space Station Airlock

NASA is currently engaged in an activity to facilitate effective operations on the International Space Station (ISS) after the Space Shuttle retires. Currently, the Space Shuttle delivers crew and cargo to and from ISS. The Space Shuttle provides the only large scale method of hardware return from ISS to the ground. Hardware that needs to be periodically repaired, refurbished, or recalibrated must come back from ISS on the Shuttle. One example of NASA flight hardware that is used on ISS and refurbished on the ground is the Compound Specific Analyzer for Oxygen (CSA-O2). The CSA-O2 is an electrochemical sensor that is used on orbit for about 12 months (depending on Shuttle launch schedules), then returned to the ground for sensor replacement. The shuttle is scheduled to retire in 2010, and the ISS is scheduled to operate until 2016. NASA needs a hand held sensor that measures oxygen in the ISS environment and has a 5-10 year service life. After conducting a survey of oxygen sensor systems, NASA selected a Tunable Diode Laser Absorption Spectrometer (TDLAS) as the method of measurement that best addresses the needs for ISS. These systems are compact, meet ISS accuracy requirements, and because they use spectroscopic techniques, the sensors are not consumed or altered after making a measurement. TDLAS systems have service life ratings of 5-10 years, based on the lifetime of the laser. NASA is engaged in modifying a commercially available sensor, the Vaisala OMT 355, for the ISS application. The Vaisala OMT 355 requires three significant modifications to meet ISS needs. The commercial sensor uses a wall mount power supply, and the ISS sensor needs to use a rechargeable battery as its source of power. The commercial sensor has a pressure correction setpoint: the sensor can be adjusted to operate at reduced pressure conditions, but the sensor does not self correct dynamically and automatically. The ISS sensor needs to operate in the airlock, and make accurate measurements in an environment that can change from 14.7 psia to 10.2 psia in 15 minutes. The commercial sensor needs to be repackaged into a configuration that is more compact, and better suited for ISS airlock operations. NASA has recently completed a prototype of the reconfigured system. The unit has been repackaged in a way that the optical path of the spectrometer is unchanged, but the electronics has been integrated into a case measuring 10.7 X 7.2 X 3.0 inches. Two flight qualified rechargeable batteries have been integrated into system. The batteries can power the sensor for 10 hours on a single charge. A pressure sensor has been added to the system. The modified unit automatically compensates for changes in pressure, and meets 0.2% accuracy requirements for oxygen measurements in an environment with 18 to 32% oxygen across a pressure range of 10.0 to 15.0 psia.

Graf, John↗
NASA NTRS1995

The effect of sensor spacing on wind measurements at the Shuttle Landing Facility

This document presents results of a field study of the effect of sensor spacing on the validity of wind measurements at the Space Shuttle landing Facility (SLF). Standard measurements are made at one second intervals from 30 foot (9.1m) towers located 500 feet (152m) from the SLF centerline. The centerline winds are not exactly the same as those measured by the towers. This study quantifies the differences as a function of statistics of the observed winds and distance between the measurements and points of interest. The field program used logarithmically spaced portable wind towers to measure wind speed and direction over a range of conditions. Correlations, spectra, moments, and structure functions were computed. A universal normalization for structure functions was devised. The normalized structure functions increase as the 2/3 power of separation distance until an asymptotic value is approached. This occurs at spacings of several hundred feet (about 100m). At larger spacings, the structure functions are bounded by the asymptote. This enables quantitative estimates of the expected differences between the winds at the measurement point and the points of interest to be made from the measured wind statistics. A procedure is provided for making these estimates.

Merceret, Francis J.↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community

Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Development of a forced advection sampling technique (FAST) for quantification of methane emissions from orphaned wells

Abstract. Orphaned wells, meaning unplugged and non-producing wells lacking responsible owners, pose a significant and undersampled environmental challenge due to their vast number and unknown associated emissions. We propose, develop and test an alternative method for estimating emissions from orphaned wells using a forced advection sampling technique (FAST) that can overcome many of the limitations in current methods (cost, accuracy, safety). In contrast to existing ambient Gaussian plume methods, our approach uses a fan-generated flow to force advection between the emission source and a point methane (CH4) sensor. The fan flow field is characterized using a colocated sonic anemometer to measure the 3D wind profile generated by the fan. Using time-series measurements of CH4 concentration and wind, a simple estimate of the CH4 emission rate of the source can be inferred. The method was calibrated using outdoor controlled-release experiments and then tested on four orphaned wells in Lufkin, TX, and Osage County, OK. Our results suggest that the FAST method can provide a low-cost, portable, fast and safe alternative to existing methods with reasonable estimates of orphaned well emissions over a range of leak rates below 40 g h−1 and within certain geometric and atmospheric constraints.

Dubey, Mohit L↗
NASA NTRS2013

The HyMeX Special Observation Period in Central Italy: Precipitation Measurements, Retrieval Techniques and Preliminary Results

The Mediterranean area concentrates the major natural risks related to the water cycle, including heavy precipitation and flash-flooding during the fall season. The capability to predict such high-impact events remains weak because of the contribution of very fine-scale processes and their non-linear interactions with the larger scale processes. These societal and science issues motivate the HyMeX (Hydrological cycle in the Mediterranean Experiment, http://www.hymex.orgl) experimental programme. HyMeX aims at a better quantification and understanding of the water cycle in the Mediterranean with emphasis on intense events. The observation strategy of HyMEX is organized in a long-term (4 years) Enhanced Observation Periods (EOP) and short-term (2 months) Special Observation Periods (SOP). HyMEX has identified 3 main Mediterranean target areas: North-West (NW), Adriatic (A) and South-East (SE). Within each target area several hydrometeorological sites for heavy rainfall and flash flooding have been set up. The hydrometeorological sire in Central Italy (CI) is interested by both western and eastern fronts coming from the Atlantic Ocean and Siberia, respectively. Orographic precipitations play an important role due to the central Apennine range, which reaches nearly 3000 m (Gran Sasso peak). Moreover, convective systems commonly develop in CI during late summer and beginning of autumn, often causing localized hailstorms with cluster organized cells. Western fronts may heavily hit the Tiber basin crossing large urban areas (Rome), whereas eastern fronts can cause flash floods along the Adriatic coastline. Two major basins are involved within Cl region: Tiber basin (1000 km long) and its tributary Aniene and the Aterno-Pescara basin (300 km long). The first HyMeX SOP1.1 was carried out from Sept. till Nov. 2012 in the NW target area The Italian SOP1.1 was coordinated by the Centre of Excellence CETEMPS, University of L'Aquila, a city located in the CI heart. The CI area was covered by a uniquely dense meteorological instrumentation thanks to a synergy between Italian institutions and NASA-GSFC. The following RADARs were operated: a Doppler single-polarization C-band radar located at Mt Midia; the Polar 55C Doppler dual-polarization C-band radar located in Rome; a Doppler C-hand polarimetric radar located at Il Monte (Abnazo); a polarimetric X-band mini-radar in L' Aquila; a polarimetric X-hand portable mini-radar in Rome; a single-polarization X-band mini-radar in Rome. DISDROMETERs were also deployed: 4 Parsivel optical disdrometers in Rome (at Sapienza, CNR-ISAC and CNR-INSEAN); 1 2D-video disdrometer in Rome; 3 Parsivels optical disdrometer respectively in L'Aquila (Abnazo), Avezzano (Abruzzo) and Pescara (Abnazo). Other INSTRUMENTS were available: 1 K-band vertically-pointing micro rain-radar (MRR), 2 Pludix X-band disdrometers, 1 VLF lightning sensor, 1 microwave radiometer at 23-31 GHz in Rome (at Sapienza); the raingauge network with more than 200 stations in Central Italy. Three overpasses in CI were also performed by the Falcon 20 aircraft equipped with the 950Hz cloud radar RASTA Analysis of the SOP1.1 main events in CI will be described by focusing on the raindrop size distribution statistics and its geographical variability. Intercomparison of rainfall estimates from disdrometers, raingauges and radars will be illustrated with the aim to provide a quality-controlled and physically consistent rainfall dataset for meteorological modeling validation and assimilation purposes.

Gatlin, Patrick↗
NASA NTRS1975

Calibration source for remote sensors

The source described was developed as a calibration target for the multispectral scanner (MSS) which was flown on the Earth Resources Technology Satellite A (LANDSAT 1). The wavelength region of interest covered the four (4) MSS bands extending from 0.5 to 1.1 micrometers, although the target was calibrated from 0.32 to 2.5 micrometers. The following characteristics for the target were required: (1) large aperture, sufficient to accommodate an instrument with a 9 inch (23 centimeters(cm)) aperture and 2 1/2 deg field of view (fov), (2) highly diffuse energy from target, (3) high spatial uniformity across aperture area of source, (4) spectrally calibrated in absolute units, (5) stable output over long periods of time (1-2 yrs), and (6) rugged, yet portable enough to be easily transported long distances without detrimental effects on the operational capabilities of the target. Two approaches were considered: a thirty (30) inch (76 cm) diameter integrating sphere with a twelve inch (30.5 cm) exit port, or the use of one hemisphere of a 76 cm sphere in conjunction with a Kodak ektolite screen. The screen has the property of reflecting back uniformly into a well defined area the majority of the light received. After some preliminary trials it seemed that the 76 cm sphere would give the most satisfactory results.

Mclean, J. T.↗
NASA NTRS2007

NIRSS Upgrades: Final Report

This year we were able to further the NIRSS program by re-writing the data ingest and display code from LabVIEW to C++ and Java. This was leveraged by a University of Colorado Computer Science Department Senior Project. The upgrade made the display more portable and upgradeable. Comparisons with research aircraft flights conducted during AIRS-2 were also done and demonstrate reasonable skill in determining cloud altitudes and liquid water distribution. Improvements can still be made to the cloud and liquid logic. The icing hazard index was not evaluated here since that represents work in progress and needs to be made compatible with the new CIP-Severity algorithm. CIP is the Current Icing Potential product that uses a combination decision tree/fuzzy logic algorithm to combine numerical weather model output with operational sensor data (NEXRAD, GOES, METARs and voice pilot reports) to produce an hourly icing diagnosis across the CONUS. The new severity algorithm seeks to diagnose liquid water production through rising, cooling air, and depletion by ice processes. The information used by CIP is very different from that ingested by NIRSS but some common ground does exist. Additionally, the role of NIRSS and the information it both needs and provides needs to be determined in context of the Next Generation Air Traffic System (NGATS). The Weather Integrated Products Team has a plan for an Initial Operating Capability (IOC) to take place in 2012. NIRSS is not explicitly a part of that IOC but should be considered as a follow-on as part of the development path to a 2025 full capability.

Politovich, Marcia K.↗
NASA NTRS1975

Development and testing of a portable wind sensitive directional air sampler

A portable wind-sensitive directional air sampler has been developed as part of an air pollution source identification system. The system is designed to identify sources of air pollution based on the directional collection of field air samples and their analysis for TSP and trace element characteristics. Sources can be identified by analyzing the data on the basis of pattern recognition concepts. Functional testing of a prototype sampler is described; all items exhibited performance and life sufficient to carry out field performance test operations. Life testing of the wind direction sensor and the directional porting valves, which are critical to reliable operation, was emphasized with successful results.

Deyo, J.↗
DOE OSTI2023

Fiber-Optic Raman Probe for On-line EAF Slag Analysis

Here, in Electric Arc Furnace (EAF) steelmaking, the push for improved efficiency requires accurate analysis of the chemical composition of its slag system to control slag foaming, provide refractory protection, and maintain high furnace iron yield. Therefore, the ability to obtain real-time slag chemistry data would provide a useful tool to improve the control and efficiency of the process. The work reported here aims to assess the structure and chemistry of EAF slags at high temperatures using a portable fiber-optic Raman probe. As a result, the ability to relate Raman spectra peaks to chemistry and structure is demonstrated in experimental result with EAF slags at 1550°C.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Optimization of Conditions for Photoluminescence-Based Sensing of Critical Minerals: Strategies and Outlook

Economically critical minerals and metals are vital to America’s security, with application areas in energy, advanced technologies, and defense systems. The growing implementation of renewable energy sources such as electric vehicles is expected to significantly increase demand for these minerals, while the global supply is monopolistic, with most of the production occurring in a few countries outside of the US. To mitigate potential supply chain vulnerabilities, the domestic production of economically critical metals has become a bipartisan priority of the US government, and unconventional sources such as coal and its utilization byproducts such as fly ash and acid mine drainage are being actively explored as an alternative method for meeting domestic demand. Slow and expensive characterization methods for critical metals present a significant pain point for domestic production, which has led to the exploration of alternative low-cost, portable platforms capable of detecting target metals during resource prospecting and downstream process monitoring. The National Energy Technology Laboratory has developed a portable fiber optic-based luminescence spectrometer that utilizes a metal-organic framework (MOF) material to detect and distinguish parts-per-billion levels of the visible-emitting rare earth elements terbium, dysprosium, samarium, and europium, which are all economically critical metals. Although preliminary results with this system are promising, a crucial barrier to practical deployment is the ability to operate in low pH, high ionic strength environments, as acidic conditions and the presence of other metal ions can significantly reduce luminescence signal. Here, current strategies related to sample treatment, material design, and sensor configuration are discussed in the context of improving sensor performance in application-relevant conditions. Additionally, future opportunities, such as the optimization of the sensing binding environment through computational methods and specific metals to be removed for treatment will be discussed, presenting a forward-looking view for innovation in luminescent sensing of critical metals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗