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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-energy X-ray source and detector for wellbore inspection

A system, method, and apparatus for wellbore inspection comprise an electron accelerator to generate X-rays, a rotating collimator assembly configured to produce a cone of X-rays, and at least one detector assembly configured to collect backscattered X-rays. A position assembly can be provided to move the electron accelerator, rotating collimator assembly, and detector through a wellbore. A computer system is configured to receive data from the detector and generate an image of the wellbore.

Kroc, Thomas K.↗
DOE OSTI2022

An Autonomous Robot for Shell and Tube Heat Exchanger Inspection

Shell and tube heat exchangers (STHEs) are critical to energy conversion efficiency of power plants. Eddy current examination is a way to evaluate working conditions of these tubes. However, the current testing apparatus requires human to manually insert an eddy current testing (ECT) probe into and extract it out of individual tubes, and meanwhile monitor measurement results for diagnosis. It is a time-consuming and labor-intensive procedure even for an experienced technician. To tackle this challenge, in this work, we developed a robot enabled ECT system for autonomous inspection of STHEs. The robotic platform employs Mecanum wheeled chassis for high mobility, machine vision to locate tube bundle and tube inlets, a rotational Cartesian mechanism to operate at planes with all possible inclinations, and a task-specific mechanism for ECT probe delivery. Machine vision locates tube bundle and tube inlets by an April tag detection algorithm and a Circle Hough Transform (CHT) algorithm, respectively. Assisted by a guidance cone, the ECT probe is continuously fed into the tubes with a fill factor of 0.819. During this process, the eddy current data are automatically collected and real-time analyzed by convolutional neural networks (CNN), showing accuracy of nearly 100% for identifying defective and non-defective tubes and 85% for four types of defective tubes and non-defective tubes.

autonomy, deep learning, eddy current testing, hea↗
DOE OSTI2023

Inspection system of wellbores and surrounding rock using penetrating X-rays

A system, method, and apparatus for wellbore inspection comprise an electron accelerator to generate X-rays, a rotating collimator assembly configured to produce a cone of X-rays, and at least one detector assembly configured to collect backscattered X-rays. A position assembly can be provided to move the electron accelerator, rotating collimator assembly, and detector through a wellbore. A computer system is configured to receive data from the detector and generate an image of the wellbore.

Kroc, Thomas K.↗
DOE OSTI2023

Data fusion enhanced multi-modality wellbore integrity inspection system

A downhole multi-modality inspection system includes a first imaging device operable to generate first imaging data and a second imaging device operable to generate second imaging data. The first imaging device includes a first source operable to emit energy of a first modality, and a first detector operable to detect returning energy induced by the emitted energy of the first modality. The second imaging device includes a second source operable to emit energy of a second modality, and a second detector operable to detect returning energy induced by the emitted energy of the second modality. The system further includes a processor configured to receive the first imaging data and the second imaging data, and integrate the first imaging data with the second imaging data into an enhanced data stream. The processor correlates the first imaging data and the second imaging data to provide enhanced data for detecting potential wellbore anomalies.

Kasten, Ansas Matthias↗
DOE OSTI2024

Electrothermal vaporization as a new method for pre-inspection check samples

The use of electrothermal vaporization (ETV) has not been readily applied to nuclear safeguards or pre inspection check (PIC) sample analysis, even though the technique is ideally suited for low level (pg) isotopic quantification due to its high analyte transport efficiency. Here demonstrate the ETV method for PIC safeguard analysis. The ETV system is an automated, commercial of the shelf (COTS) technology, with the capability to introduce solid samples to a mass spectrometer platform. The system has been shown to simultaneously determine uranium assay, and the major isotopic ratios for uranium and plutonium. The ETV unit has demonstrated analysis up to 50 samples a day autonomously. The utilization of this ETV methodology provide a secondary option to the current PIC analysis and offers high throughput, enhanced sensitivity, and broader isotopic detection platform.

Hexel, Cole↗
DOE OSTI2024

Solar mirror soiling and heliostat inspection from a mobile imaging system and mobile platform

A system or method for an imaging system is provided for inspecting a heliostat. The imaging system includes a platform and a camera mounted on the platform and a heliostat having a plurality of mirrored facets. The camera is positioned to acquire a first image that serves as a reference image and a second image that is a reflected image from at least one facet. The camera stores image data associated with the first image and the second image, and wirelessly transmits the stored image data to a computing apparatus. The computing apparatus compares the first image with the second image and determines a performance parameter associated with the heliostat.

Yellowhair, Julius↗
DOE OSTI2026

Modular Accelerator Robotics Framework Implementation For Accelerator Inspection

Accelerator tunnels, such as the ones at Fermilab, remain highly radioactive after beam shutoff due to induced radiation from the beam. This residual radiation creates a hazardous environment for manual inspection and repair of beamline components. To minimize worker radiation dose and reduce beam downtime, the AD Robotics Initiative previously built a fleet of low-cost custom mobile robots. However, the custom Python sockets server-client architecture lacked standardization, causing development delays and complicating the integration of new sensors and actuators. Here, we developed a modular system using ROS2 and Docker to standardize the teleoperation and control interfaces. This system was validated by implementing a teleoperation controller with real-time, low-latency, and high-definition video feedback. The aim of this framework is for a new feature or even a robot to be integrated into the system simply by documenting the hardware configuration. Current integration of LiDAR, Odometry, and Depth Cameras provides the foundation for Simultaneous Localization and Mapping (SLAM) tasks. Finally, future work involves integration into the accelerator control system and the attachment of a 6 degree-of-freedom robotic arm for telemanipulation.

Rayyan Khana, M. [Unlisted, US, IL] (ORCID:0009000↗
DOE OSTI2023

X-ray Inspection Model Validation with Physical Dosimetry

A non-functional printed circuit board assembly was developed using ULTIboard and a simple computational transport model was created for use with the Monte Carlo software MCNP. EBT 3 film radiography was used to compare with Monte Carlo simulation to validate the board representation. The computational transport model was then revised to include connection pins, solder balls, highly attenuating internal structures, and copper trace distribution. Results from the revised model were compared to the EBT 3 films to observe improvements to dose profiles. It was found that this method was useful in verifying the placement of components, as the dose profiles were observed to follow the same trends. The experiment was then repeated using XRQA 2 films to achieve the same level of contrast with 1% the dose of EBT 3 films. It was found that high contrast may be achieved using these films to identify major issues with the model geometry, at a cost of dose profile accuracy. A second validation method was applied to the model using 37 CaF 2 thermoluminescent dosimeters (TLDs). TLD measurements were compared with the simplified and complex transport models to identify the features that have the greatest impact on simulation accuracy. The TLD calibration to CaF 2 was found to be accurate within 5.6%, while calibration to dose in Si was found to be accurate within 4.7%. Finally, it was observed that the accurate representation of solder balls and proper modeling of highly attenuating internal structures had the greatest impact on simulation accuracy.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections

Understanding building envelope thermodynamics is an essential foundation of building sciences, mainly due to the envelope’s role as a boundary layer for exterior environments, as well as a container and regulator of internal microclimates. This paper presents a scoping literature review of select Non-destructive Testing (NDT) techniques for building envelope scanning and surveying for thermodynamic diagnostics. The investigation focuses specifically on reviewing six NDT techniques: Ground Penetrating Radar (GPR), Light Detection and Ranging (LiDAR)/Laser Scanning, Thermography, Ultrasound, Close-Range Photogrammetry and Through Wall Imaging Radar (TWIR). The aim is to identify knowledge gaps in terms of their use in accurately characterizing envelope compositions for further integration in Building Energy Modeling (BEM). Each technique was evaluated according to set categories imbibed from the American Society of Heating, Refrigerating, and Air Conditioning Engineering (ASHRAE) Standard 211P that showcase the technique’s ability to extract various relevant information. A framework is then developed to inform users on how to use hybrid NDT-based workflows applied in building envelope energy audits. The study concludes by discussing possibilities of utilizing NDT in large-scale audit automation, BEM integration, and developing built environment policies focusing on increasing existing building performance through retrofitting design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗
DOE OSTI2020

Development of Robotic Inspection Systems for In-situ Characterisation Prior to Decommissioning - 20306

The University of Bristol's South West Nuclear Hub is part of two large UK academic research collaborations aiming to reduce the costs of nuclear power by trialing innovative solutions to major decommissioning challenges. Robotics and Artificial Intelligence in Nuclear (RAIN) and the National Centre for Nuclear Robotics (NCNR) are the two collaborations tasked by the UK research councils to coordinate this activity, for the benefit of the nuclear industry. This paper presents a summary of Bristol's research aimed at generating and demonstrating a series of technologies ready for commercialization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗