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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Exploiting Acoustic Anisotropy to Detect Recrystallization in a Ni Single Crystal Using Ultrasonic Nondestructive Inspection

Ultrasonic inspection was used to detect regions of recrystallization (RX) within a single crystal of Ni. RX can produce polycrystalline regions within single-crystal (SX) materials. Because RX regions act as initiator sites for failure by fatigue-crack growth in otherwise SX Ni-based superalloys, RX is an issue of direct concern for the service life of high-performance turbine blades. Detection and discrimination of RX regions in single-crystal materials are significant challenges for current nondestructive inspection technologies. The present study leverages the elastic anisotropy of single crystals, which produces acoustic anisotropy, to ultrasonically detect and characterize RX regions produced within single-crystal specimens. Single crystals of pure Ni were processed to create controlled regions of RX. These specimens were ultrasonically examined in an immersion tank using a high-resolution, polyvinylidene fluoride transducer to detect acoustic impedance changes across the boundaries between different crystals (i.e., grains) within the RX region. Data from time-of-flight and absolute peak amplitude measurements were used to create acoustic images that were compared against electron microscope images of the RX regions. The ultrasonic inspection technique described here successfully detected not only the locations of RX regions, but also the approximate sizes and shapes of the RX regions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Metallurgical Inspection Method to Assess the Damage in Performance-Limiting Nb 3 Sn Accelerator Magnet Coils

The design and production of Nb 3 Sn-based dipole and quadrupole magnets is critical for the realization of the High-Luminosity Large Hadron Collider (HL-LHC) at the European Organization for Nuclear Research (CERN). Nb 3 Sn superconducting coils are aimed at enhancing the bending and focusing strengths of accelerator magnets for HL-LHC and beyond. Due to the brittle nature of Nb 3 Sn, the coil fabrication steps are very challenging and require very careful QA/QC. Flaws in the Nb 3 Sn filaments may lead to quenches, and eventually, performance limitation below nominal during magnet testing. A novel inspection method, including advanced non-destructive and destructive techniques, was developed to explore the root-causes of quenches occurring in performance-limiting coils. The most relevant results obtained for MQXF coils through this innovative inspection method are presented. This approach allows for precise assessment of the physical events associated to the quenches experienced b y magnet coils, mainly occurring under the form of damaged strands with transversely broken sub-elements. Coil-slice preparation, micro-optical observations of transverse and longitudinal cross-sections, and a deep etching technique of copper will be illustrated in the present work, with a focus on the results achieved for a CERN coil from a non-conforming quadrupole magnet prototype, and two coils fabricated in the US, in the framework of the Accelerator Upgrade Project (AUP) collaboration, from two different non-conforming quadrupole magnets, respectively. The results obtained through the proposed inspection method will be illustrated.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Post-Closure Inspection Report for the Tonopah Test Range and Nevada Test and Training Range, Nevada, For Calendar Year 2019, Revision 0

This report provides the results of the annual post-closure use restriction (UR) inspections at the closed corrective action sites (CASs) located on the Tonopah Test Range (TTR) and Nevada Test and Training Range (NTTR) that are accessed through the TTR/NTTR main gate. This report covers post-closure UR inspections for calendar year 2019, and includes visual inspections and repair activities completed at the following corrective action units (CAUs): • CAU 400, Bomblet Pit and Five Points Landfill (TTR) • CAU 407, Roller Coaster RadSafe Area (TTR) • CAU 424, Area 3 Landfill Complexes (TTR) • CAU 453, Area 9 UXO Landfill (TTR) • CAU 487, Thunderwell Site (TTR)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Technology Development for Under Tank Inspection of Double-Shell Tanks - 20045

The Department of Energy (DOE) Office of River Protection (DOE-ORP) is responsible for management and cleanup of the tank farms located at the Hanford Site. Nuclear waste at Hanford is stored in 149 single-shell tanks (SSTs) and 27 double-shell tanks (DSTs). The vast majority of the liquid radioactive waste is stored in the DSTs. The 27 DSTs, located in six tank farms, were constructed from 1967 to 1986 and, compared to the SSTs, provide greatly improved protection from leakage and better accessibility for inspection. The DSTs and ancillary equipment are expected to exceed their design life before their waste is removed and sent to the Waste Treatment and Immobilization Plant. The DST Integrity Project (DSTIP) must ensure that the DST system can meet the River Protection Project mission goals. This paper provides a programmatic overview of the DSTIP with a focus on development of under-tank inspection technologies. Currently, two categories of nondestructive examination (NDE) techniques for DSTs are implemented on the Hanford site: (1) surface (SNDE) and (2) volumetric (VNDE). Further discussion on current inspection techniques is provided in this paper. The technology development approach for advanced VNDE techniques will also be generally discussed as a precursor for another more detailed WM2020 paper and presentation by PNNL. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Site A and Plot M 2023 Surveillance Report and 2024 Inspection Report

This report is prepared for the U. S. Department of Energy (DOE) Office of Legacy Management (DOE-LM) by the Worker Safety & Environment (WSE) Division at Argonne National Laboratory (Argonne). Beginning in 2024, Argonne drafted a combined report containing the annual inspection results for the current year and the annual surveillance data/discussion from the previous year. The annual inspection results will be contained within an appendix at the end of the surveillance report. The results of the environmental monitoring program at Site A and Plot M and an assessment of the impact of the site on the environment and the public are presented in this publication as well as findings and assigned corrective actions as a result of the Site A/Plot M annual inspection. Funding to support this program was provided by DOE-LM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Polarimetry-Enhanced Imaging towards Autonomous Solar Field and Receiver Inspections

During the typical operation of a Concentrating Solar Power (CSP) plant, a large portion of the energy (~45%) can be lost due to various imperfect conditions, such as blocking, shading, mirror soiling, tracking and canting errors, etc. It is necessary to develop efficient and effective field inspection technology to optically survey and characterize a CSP field, which can be used as an input for autonomous control, maintenance scheduling and spot repair whenever necessary to maximize the overall efficiency of the plant. In this project, We aim to apply polarimetric imaging for CSP collector and receiver inspection and develop polarimetric drone cameras (via integrating polarimetric imagers onto drones) for autonomous field inspection in CSP plants.

14 SOLAR ENERGY↗
DOE OSTI2026

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗
DOE OSTI2023

Visual, Optical and Replica Inspections: Surface Preparation of 650 MHz NB Cavity for PIP-II Linac

Surface preparation of niobium superconducting RF cavities is a critical step for achieving good RF performance under the superconducting state. Surface defect, roughness, and contamination affect the accelerating gradient and quality factor of the cavities. We report surface inspection methods used to control the surface processing of 650 MHz cavities designated for the pre-production and prototype cryomodules for PIP-II linac. The cavity surface was routinely inspected visually, with an optical camera, and by microscopic scanning of surface replicas. This article covers details on the surface inspection methods and surface polishing process used to repair the surface.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Savannah River Site H-Canyon Tunnel Inspection Lidar Mapping Solution - 19477

Over the summer of 2018, the Savannah River National Laboratory (SRNL) formed and hosted a robotics and sensor intern team and tasked them with developing a proof of concept for a modular sensor suite to be deployed in the next H-Canyon Air Exhaust (HCAEX) Tunnel inspection in spring 2019. The developed sensor suite includes a planar Lidar sensor for depth imaging, two Panospheric 4K cameras, and an inertial measurement unit to aid in base localization. The Lidar is actuated to rotate about the vertical axis, which allows for the team to gather 3D mapping data. These rotating planar scans can also be fused with the camera and IMU data to generate colorized internal maps of the tunnel. The supporting software was developed iteratively over the summer and leveraged prior research conducted at the University of Texas at Austin, which facilitated the stitching of Lidar scans, the fusion of the sensor data, and even algorithms to provide in-situ navigation feedback to the operators of the crawler. This software simultaneously represents huge leaps forward in the mapping and degradation measurement abilities of the crawler over past inspection units, while also allowing the operator much greater situational awareness. The improvement in awareness reduces risks of the robot becoming stuck or disabled inside the tunnel, which would jeopardize the success of both this and future inspections. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Development of the Intelligent, Preventive Infrared (IR) Inspection System Housed in Hybrid Robotic Platforms

Robots and robotic systems that are designed for inspection, environmental study, and health and safety aid are becoming an increasing necessity. However, there is a number of challenges that accompany robots that are designed for these specific applications. These challenges include: navigating compact, enclosed spaces, travelling over multiple terrains and large obstacles, using the proper sensing and detection methods to assess an environment, and the use of lightweight and durable materials. The robotic platforms currently in development look at all of these challenges and attempt to overcome them. These designs specific use of hybrid robotic platforms, or platform that utilizes soft and rigid materials, allows for a more flexible platform and makes environments more navigable. To further improve the navigation of the platforms and environmental assessment, a novel infrared detection system is housed in the platforms to create a robot that can be used for the applications listed above and more. Objectives: Further develop two types of robotic platforms that utilize additive manufacturing, soft materials, and rigid materials. Continue the development of an intelligent and inhibitory infrared detection system based on an artificial intelligence (AI) algorithm. Continued study and fabrication of active soft materials designed for both sensing and actuation in hybrid robotic systems. Improve additive manufacturing fabrication to design rigid and semi-rigid components for hybrid robotic platforms. Transformable Wheel Robotic Platform: The chassis, wheels, tires and inspection system housing use different additive manufacturing techniques for fabrication. Continued work with additive manufacturing has lead to studies in metal-based printing and modular design and manufacturing. The new platform design with integrated electrical component printed. This will allow integration of the sensor housing onto the platform. Electrical components are being tested for battery life and performance. To improve this performance, such as integration of Lithium Polymer (LiPo) batteries. Snake Robotic Platform: The main focus of the development has centered around liquid-based soft actuators. That act on the principles of electrostatic and hydraulic actuation. A liquid dielectric sits between two compliant electrodes, contained by a flexible polymer shell. The electrodes and film gradually collapse toward each other from one corner of the electrode to the other. When the electrodes and film close together, a majority of the fluid is pushed into the area not covered by an electrode. A thin layer of the liquid dielectric remains between the electrode. The actuators will be stacked to cause large displacement, and move the linkages. The chassis of this platform uses purely additively manufactured linkages. Intelligent, Preventive IR Inspection System: Development of the AI for the system has lead to using a Scikit-Learn which assists in creating predictive models based on Regression, clustering, classification etc. To improve the infrared thermometry for low emissivity sources, work on the fabrication of a tandem photoconductive infrared thermometer was a main focus. Distance-Voltage-Temperature response data has been collected in the range of 7 cm - 100 cm and 200-400 deg. C. Modifications were made to the existing test bench to have a better control over the data. Automated data collection was realized using a Python code and an Arduino controlled stepper motor to increase the sample rate. A protective enclosure has been built around the setup to minimize the effect of the environment on the measurements. To better predict temperature, different AI models are being optimized. The regression model, LARS showed a high accuracy but had convergence issues and only works for the current test set-up. Results: The Transformable Wheel Robot has developed into a more flexible and modular platform. With the improvements to the current work, effort on the tire or soft gripper design been a large focus. The soft grippers will be interchange able to allow for increased performance in identified terrain types. The development of the liquid-based actuators allows the snake robotic platform to achieve the goals of being flexible and able to navigate confined spaces. However, there is room for improvement. Optimization work is currently being done in COMSOL Multiphysics. With the current IR system set-up the LARS model perfectly predicts the data; however, considering the mobility aspect of the project other models will allow for an optimized system. Testing of other model types is currently being done.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Using Robotic Manipulators for Radioactive Waste Inspection - 20090

The global nuclear industry has a growing volume of nuclear waste which needs to be scanned, sorted according to its activity and material type, then processed into the correct waste packages for long term storage and disposal. It is vital that there is a detailed understanding of the waste inventory stored in long term waste containers, as knowledge of their contents could predict or prevent any adverse effects in storage. The numerous 'scan and sort' tables which are currently used at many different facilities around the world to sort waste into their correct containers are human operated and require very slow gamma scanning procedures combined with educated guesswork to manually sort the waste. This often leads to excessive conservatisms, with placement of lower activity wastes in higher activity containers, which in turn costs significantly more to store. In the United Kingdom it costs UK Pounds 46 k per cubic meter to store intermediate level waste compared to just UK Pound 2.9 k per cubic meter to store low level waste according to a 2008 Department of Energy and Climate Change report in the UK. A proposed solution to this problem, is the use of a robotic manipulator to automatically inspect the 'scan and sort table' in order to produce an accurate 3D model of the table's waste contents and attach an overlaid radiation map. The radiation map contains spectrometry data and can in consequence be used to distinguish and locate specific radioisotopes. The 3D model should be as accurate as possible in order to allow for a second robot arm with an attached gripper to grasp the objects and place them into their designated long-term storage container. Various scanning procedures are explored in this study including basic raster scanning, adaptive raster scanning and point sampling. The optimal solution will in practice be defined by the required application and activity level of the wastes being inspected. The results presented in this study indicate that it is possible to produce a centimeter accurate 3D model of a mixed assortment of components on a nuclear waste 'scan and sort' table. In addition, it was shown that the waste objects emitting radiation could be accurately identified and located, with an overlaid radiation map. This study is applicable across the nuclear waste management sector. Many of the ideas and concepts developed in this study are applicable in other decommissioning settings for example, dismantling of legacy gloveboxes or routine inspection of nuclear waste packages in storage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

DOESC Remote Canister Closure System UT Inspection Couplant Solutions

The DOE Standard Canister (DOESC) Remote Canister Closure System is a remotely operated welding and inspection mechanism designed for the packaging of DOE-managed spent nuclear fuel into canisters. The ultrasonic testing (UT) inspection, included in the system, requires the use of water tanks that are opened to act as a couplant between the canister and the sensors. With the couplant, the UT inspection can guarantee accurate results determining imperfections in the weld.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2026

Intern Poster Session 08/13: Autonomous Nuclear Robotics: Applications in nuclear waste inspection and hot cell experiments

The nuclear industry is experiencing renewed interest in autonomous robotics, yet most deployed systems remain teleoperated with limited autonomy. This work presents two contributions toward fully autonomous nuclear robotic systems: autonomous waste inspection at the Hanford Site and an autonomous hot cell laboratory framework. Inspections of Hanford's underground waste storage tanks are performed manually at significant cost and personnel exposure. We developed a reinforcement-learning (RL) training pipeline for a custom-built inspection arm. In parallel, we are designing an autonomous laboratory framework for post-irradiation examination in hot cells at the Specimen Preparation Laboratory (SPL) that integrates computer vision, task and motion planning, hardware execution, and operator-in-the-loop control. These systems demonstrate a path toward safer, more efficient nuclear operations by reducing human exposure while maintaining rigorous human oversight at critical decision points.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗
DOE OSTI2019

The Post-Closure Inspection Report For Closed Non- Resource Conservation And Recovery Act (RCRA) Corrective Action Units (CAUs) On The Nevada National Security Site (NNSS), For Calendar Year 2018

This letter serves as the Calendar Year 2018 post-closure inspection letter report for the following Non-RCRA CAUs located on the NNSS, including CAUs located on the Nevada Test and Training Range (NTTR) that are accessed through the NNSS Main Gate. Use restriction issues that were identified in the 2017 inspections were addressed in 2018.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Collaboration on SBIR/TTO Phase II Project for Optical QC Device and Collaboration on SBIR/TTO Phase II-b Project for Advanced Quality Inspection Device Development: Cooperative Research and Development CRADA Number CRD-16-00652 (Final Report)

The overall goal of this program is to develop and commercialize a turnkey quality control solution for the entire PEM fuel cell manufacturing process including membrane, gas diffusion layers, catalyst, and assembled systems. This quality control solution is unique to each customer’s specific needs but includes a suite of in-line quality control systems for roll-to-roll manufacturing that can target thin, transparent membrane as well as opaque membrane, catalyst, and GDLs. The Phase II developed the CPNUVV system for thin, transparent membrane that operates using polarized filters to enhance defect resolution and determine thickness. However, PEM material manufacturers want a complete, turnkey solution for all components of the PEM fuel cell. In the Phase IIB, Mainstream will partner with NREL, and transition reflectance technology NREL developed (US Patent 9,234,843) to operate in real-time on a web-line to develop a total solution to PEM quality control. The device will identify and mark defects as well as monitor materials thickness in real-time to improve line efficiency and to reduce waste. The research performed at NREL under this CRADA increases the basis of knowledge about optical inspection methods, how they perform with regards to fuel cell component materials, and how they can be implemented in in-line, real-time configurations to provide quality inspection for roll-to-roll (R2R) manufacturing. Methods explored were found to be sensitive to catalyst loading in electrodes on both membrane and gas diffusion media substrates and to membrane thickness, across a broad range of thickness. The latter capability is novel and now patented and provides a previously unstudied and undemonstrated capability for R2R manufacturing of membranes.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Framework and Tool for Artificial Intelligence & Machine Learning (AI/ML) Enabled Automated Non-Destructive Inspection of Composites Aerostructures Manufacturing

Vehicles and systems in the field of aerospace have two major requirements: a high demand for a large quantity and an expectation to perform for their lifetime with little to no failures. Thus, there is a need for a fast production rate of aerospace products with high quality. Improvements to production rate have many benefits, including a reduction in energy consumption per unit manufactured. This would be from factory energy usage, which is required to build and verify a product. Manufacturing process specifications require inspection of parts to determine if any flaws are present. Depending on factory planning and product quality, especially at higher rates, the evaluation process can pose a production rate bottleneck. This project was comprised of using artificial intelligence and machine learning (AI/ML) methods on inspection evaluations with the objective of reducing the required time to produce an aerospace structure or product and without reducing the final quality.

42 ENGINEERING↗