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DOE OSTI2016

Nondestructive Examination Guidance for Dry Storage Casks

In this report, an assessment of NDE methods is performed for components of NUHOMS 80 and 102 dry storage system components in an effort to assist NRC staff with review of license renewal applications. The report considers concrete components associated with the horizontal storage modules (HSMs) as well as metal components in the HSMs. In addition, the report considers the dry shielded canister (DSC). Scope is limited to NDE methods that are considered most likely to be proposed by licensees. The document, ACI 349.3R, Evaluation of Existing Nuclear Safety-Related Concrete Structures, is used as the basis for the majority of the NDE methods summarized for inspecting HSM concrete components. Two other documents, ACI 228.2R, Nondestructive Test Methods for Evaluation of Concrete in Structures, and ORNL/TM-2007/191, Inspection of Nuclear Power Plant Structure--Overview of Methods and Related Application, supplement the list with additional technologies that are considered applicable. For the canister, the ASME B&PV Code is used as the basis for NDE methods considered, along with currently funded efforts through industry (Electric Power Research Institute [EPRI]) and the U.S. Department of Energy (DOE) to develop inspection technologies for canisters. The report provides a description of HSM and DSC components with a focus on those aspects of design considered relevant to inspection. This is followed by a brief description of other concrete structural components such as bridge decks, dams, and reactor containment structures in an effort to facilitate comparison between these structures and HSM concrete components and infer which NDE methods may work best for certain HSM concrete components based on experience with these other structures. Brief overviews of the NDE methods are provided with a focus on issues and influencing factors that may impact implementation or performance. An analysis is performed to determine which NDE methods are most applicable to specific components.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model

The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a ‘steering’ of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Historical Building Stability Monitoring by Means of a Cosmic Ray Tracking System

Cosmic ray radiation is mostly composed, at sea level, by high energy muons, which are highly penetrating particles capable of crossing kilometers of rock. The ubiquitous and steady presence at the Earth's surface and the high penetration capability have motivated the use of cosmic ray radiation also in fields beyond particle physics, from geology, archaeology, speleology to industrial applications and homeland security. In particular, in recent years, the novel technique of muon tomography has been proposed, with the aim of performing non invasive inspection of large non accessible volumes, material atomic number Z and density discrimination, and three dimension image reconstruction of the inspected volume. In the present paper, after a short recall of the physical principles and mathematical formalism on which muon tomography is based, a number of examples of application of the novel technique in industry and homeland security issues is given. Moreover, a new application of cosmic rays detection techniques in the field of civil engineering is proposed. The aim is the monitoring of the stability of large structures, in particular the static monitoring of historical buildings, where conservation constraints are more severe and the time evolution of the deformation phenomena under study may be of the order of months or years. The new technique may be seen, in some way, as the reverse problem of muon tomography. As a significant case study, the monitoring of the wooden vaulted roof of the Palazzo della Loggia in the town of Brescia, in Italy, has been considered. The feasibility as well as the performances and limitations of a monitoring system based on cosmic ray tracking have been studied by Monte Carlo simulation and discussed in comparison with more traditional monitoring systems. (authors)

42 ENGINEERING↗

DOE OSTI2015

Evaluation of PV Module Field Performance

This paper describes an effort to inspect and evaluate PV modules in order to determine what failure or degradation modes are occurring in field installations. This paper will report on the results of six site visits, including the Sacramento Municipal Utility District (SMUD) Hedge Array, Tucson Electric Power (TEP) Springerville, Central Florida Utility, Florida Solar Energy Center (FSEC), the TEP Solar Test Yard, and University of Toledo installations. The effort here makes use of a recently developed field inspection data collection protocol, and the results were input into a corresponding database. The results of this work have also been used to develop a draft of the IEC standard for climate and application specific accelerated stress testing beyond module qualification. TEP Solar Test Yard, and University of Toledo installations. The effort here makes use of a recently developed field inspection data collection protocol, and the results were input into a corresponding database. The results of this work have also been used to develop a draft of the IEC standard for climate and application specific accelerated stress testing beyond module qualification. TEP Solar Test Yard, and University of Toledo installations. The effort here makes use of a recently developed field inspection data collection protocol, and the results were input into a corresponding database. The results of this work have also been used to develop a draft of the IEC standard for climate and application specific accelerated stress testing beyond module qualification.

14 SOLAR ENERGY↗

DOE OSTI2022

Nondestructive Evaluation of Stress Corrosion Cracking in a Welded Steel Plate Using Guided Ultrasonic Waves

Stress corrosion cracking (SCC) had occurred in early-generation high-level nuclear waste tanks constructed by welding carbon steel. This paper describes an ultrasonic inspection system and its fundamental ability to detect and quantify the length of SCC on thick welded steel plates. The finite element method (FEM) was applied to simulate the welding process to estimate the welding residual stress field. Growth of stress corrosion cracks is driven by crack stress intensities exceeding the subcritical cracking threshold intensity. The subject plate was experimentally inspected with ultrasonic nondestructive evaluation (NDE) techniques to characterize the extent of SCC. The NDE system uses a piezoelectric transducer to generate guided waves in the thick steel plate, and a scanning laser Doppler vibrometer (SLDV) to measure multidimensional time–space wavefield data over a user-defined scanning area in the plate surface. The measured wavefield data can show wave interactions in a localized area in the plate due to the presence of the discontinuities of the SCC. To generate an inspection image that can precisely show the crack’s location and/or the dimension, the wavefield data are further processed to generate inspection image that maps the entire sample plate so the crack can be clearly identified in the plate while its length can be readily estimated. In conclusion, the ultrasonic test results for crack length agree well with the visually estimated length and are close to that predicted by the FEM for cracks in the weld residual stress field.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluating Model Robustness for Defect Identification and Classification in a Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from a composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating the composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of the composite aerostructure material. The methods developed here are both highly reliable with a top recall value of 98.64% as well as extremely efficient requiring an average of 4 s during the inferencing stage to evaluate new composites. Lastly, we investigate model robustness to concept drift by measuring its performance over time.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Comparative Study on Deep Learning Methods for Defect Identification and Classification in Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of composite aerostructure material. Furthermore, the methods developed here are both highly reliable with a top recall value of 98.63% as well as extremely efficient requiring an average of 4 seconds during the inferencing stage to evaluate new composites.

composites↗

DOE OSTI2013

Preliminary Thermal Modeling of HI-Storm 100S-218 Version B Storage Modules at Hope Creek Cuclear Power Station ISFSI

As part of the Used Fuel Disposition Campaign of the U. S. Department of Energy, Office of Nuclear Energy (DOE-NE) Fuel Cycle Research and Development, a consortium of national laboratories and industry is performing visual inspections and temperature measurements of selected storage modules at various locations around the United States. This report documents thermal analyses in in support of the inspections at the Hope Creek Nuclear Generating Station ISFSI. This site utilizes the HI-STORM100 vertical storage system developed by Holtec International. This is a vertical storage module design, and the thermal models are being developed using COBRA-SFS (Michener, et al., 1987), a code developed by PNNL for thermal-hydraulic analyses of multi assembly spent fuel storage and transportation systems. This report describes the COBRA-SFS model in detail, and presents pre-inspection predictions of component temperatures and temperature distributions. The final report will include evaluation of inspection results, and if required, additional post-test calculations, with appropriate discussion of results.

site inspections↗

DOE OSTI2016

NonDestructive Evaluation for Industrial & Development Applications

Provide overview of weld inspection for Non-Destructive Testing at LANL. This includes radiography (RT/DR/CR/CT for x-ray & neutron sources), ultrasonic testing (UT/PAUT), dye penetrant inspection (PT), eddy current inspection (ET) and magnetic particle testing (MT). Facilities and capabilities for weld inspection will be summarized with examples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

SolarAPP+ Performance Review (2022 Data)

The Solar Automated Permit Processing Plus (SolarAPP+) platform is an online portal to facilitate and expedite rooftop solar photovoltaic (PV) permitting processes. SolarAPP+ allows PV contractors to upload system specifications, have those specifications automatically reviewed for code compliance, and receive instant approval for code-compliant systems. SolarAPP+ also provides inspection checklists to verify installation practices and adherence to approved designs. SolarAPP+ is available to authorities having jurisdiction (AHJs) at no cost. This report is part of an ongoing series of reviews of SolarAPP+ performance. Consistent with previous performance reviews, we summarize SolarAPP+ adoption trends to date and compare various metrics for PV systems permitted through SolarAPP+ versus systems permitted through conventional AHJ permitting processes. As of the end of 2022, the National Renewable Energy Laboratory (NREL) had contacted over 1,500 AHJs with significant solar permitting volume regarding SolarAPP+. Of those, 607 AHJs had at least expressed interest in the platform. 16 AHJs had begun piloting the platform and 15 of these had publicly launched the platform by the end of 2022. In 2022, 206 installers submitted 11,092 permits through the SolarAPP+ platform, including 708 permits for solar+storage systems. SolarAPP+ permits accounted for around 37% of all permits issued in participating AHJs. We compare permitting timelines through SolarAPP+ to traditional AHJ permitting processes to assess the platform's performance. Consistent with previous SolarAPP+ performance reviews, we find that permitting timelines are significantly shorter for SolarAPP+ projects. Based on median timelines, a typical SolarAPP+ project is permitted and inspected 8 business days sooner than traditional projects. We estimate that automatic SolarAPP+ permitting saved between 3,500 and 13,900 hours of AHJ staff time in 2022. Finally, we find evidence that SolarAPP+ may improve inspection outcomes, with SolarAPP+ projects failing inspections about 28% less frequently than traditional projects.

14 SOLAR ENERGY↗

DOE OSTI2025

WRPS Hanford Update [Slides]

The purpose of this report is to coordinate with the staff from WRPS, the current contract holder for operations at the Hanford site to better inform design decisions for the Autonomous systems for Hanford waste tank handling project. The project goals are to support risk reduction associated with monitoring, inspection and mapping of Hanford tank underground pits and includes: 1. A pit mock-up demonstration of Idaho National Laboratory’s (INL) Autonomous Pit Exploration System (APES) technology, which has two configurations: A. The Autonomous Robotic Arm, which is a proposed collaboration with Florida International University (FIU) and has capabilities to visually inspect, monitor, map and conduct simple tool manipulation tasks in the tank pits, and B. The robotic crawler configuration, which has capabilities to deploy to the bottom of the pits and conduct closer and bottom-up visual inspections. 2. An Implementation Plan that identifies Hanford site-wide application of the INL remote robotics technologies to enhance the performance of the tank farm systems and the characterization of the waste they contain to mitigate risk and optimize the overall waste mission. 3. A first-of-a-kind environmental digital twin will be produced. Digital twins to date require permanently installed sensors in order to produce asset specific predictions. This project will use the intermittent signals during inspections from deployed sensors on robotic systems to produce the data sets used by AI/ML to enable predictions of issues on tanks.

42 - ENGINEERING↗

DOE OSTI2015

Higher harmonic ultrasonic guided waves for structural integrity assessment of dry storage canisters - 15381

Dry storage of used fuel from nuclear power plants has gone from an interim storage solution to a longer-term solution, which necessitates monitoring the integrity of the stainless steel canister that confines the used fuel. Since the storage facilities are located around the country in a variety of different environments there is a wide range of degradation mechanisms that could occur over time in the cylindrical canister. One potential degradation mode that has created significant concern is stress corrosion cracking. We propose using higher harmonic ultrasonic guided waves as a tool to nondestructively inspect used fuel canisters. Higher harmonics are generated when a wave propagates through a nonlinear elastic media. These higher harmonics have been shown to be quite sensitive to microstructural features such as dislocation substructures, persistent slip bands, precipitates, etc. The use of ultrasonic guided waves to inspect the canister is attractive due to the size of the canister and the ability of guided waves to inspect a reasonably large domain relative to traditional bulk wave ultrasonics. We will highlight our recent progress on theory, numerical simulations, and laboratory experiments to develop higher harmonic guided waves as a tool to detect microstructural changes that precede macro-scale damage. Analyzed structures include plates and hollow cylinders, and we focus on localized damage initiation, as is the case for stress corrosion cracking. Recent experiments focus on using magnetostrictive transducers in activating the fundamental shear horizontal mode (SH0) and the third harmonic that is generated due to the material nonlinearity. The magnetostrictive transducer comprises a thin iron-cobalt foil, a meandering electric coil, and a permanent magnet. These transducers are inexpensive, easy to use, and are very efficient at generating shear waves. In applications where the wavelength is larger than the plate thickness, the waves are guided by the traction free boundary conditions and propagate in the plane of the plate. For this canister application, the shear horizontal waves energize the entire thickness of the canister and propagate along the shell in the direction dictated by the meander coil. Experiments indicate that magnetostrictive transducers can generate waves that propagate in plate thicknesses of 1 mm to at least 16 mm. The SH0 mode is nondispersive and generates a third harmonic of the same mode that is shown to be sensitive to localized plastic strain and unseen fatigue damage. It has a strong potential to detect the very early stages of stress corrosion cracking. Due to the geometric configuration of dry storage casks, the transducers will need to be delivered to the inspection points by a robotic system that navigates through the cask ventilation system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Localized Imaging and Mapping for Underwater Fuel Storage Basins - 18364

Current methods for inspection of spent nuclear fuel storage basins involve lowering a single camera for visual inspection of walls and other structures. We present a localized inspection solution where the images are automatically annotated by localization information and a 3D model of the inspected area is generated. The system consists of an underwater sensor pod containing a stereo pair of cameras, light source, inertial measurement unit, and a pressure sensor. The sensors are time synchronized to provide precise measurements. We describe both the sensor pod and the algorithms that keep the pod localized. Preliminary results from in-air testing of a prototype are presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Monitoring Waste Tanks Using Guided Wave Technology - 18576

There are many challenges associated with the inspections of double-shell storage tanks containing radioactive waste, including limited space for accessibility and maneuverability, environments with high radiation, temperature and toxicity, and unknown physical conditions. Contents of the tank and limited space may prevent access of scanning devices that employ conventional NDE techniques such as ultrasonics, eddy current, or magnetic based methods. Resolving these challenges will become more urgent as the nuclear industry is forced to address the complications of the aging nuclear infrastructure - specifically at tank storage locations on laboratory sites across the DOE complex. A powerful, new approach to inspecting and monitoring the structural integrity of large structures, such as double-shelled tanks, is being developed using ultrasonic guided waves. Acoustic waves that propagate in a plate or other structure where the wavelength is larger than the thickness of the structure are known as ultrasonic guided waves. Ultrasonic guided waves can potentially propagate distances of tens to hundreds of feet in plate-like structures, such as those that comprise the walls and bottom of a storage tank. Guided waves enable the examination of relatively large inspection volumes from the outside surface of the structure. In double-shell tanks, the technology offers promise for examining the floor of the structure or the walls by placing guided wave sensors at accessible locations in the annulus. This guided wave technology has the capability to detect and localize areas of damage or degradation. While guided wave has recently been used in the nuclear and oil and gas industries for inspecting one-dimensional piping systems, current research is developing methods to apply this technology to the two-dimensional surfaces of double-shell storage tanks. Permanently installed sensors are being developed which would remotely collect data that would be analyzed to monitor the structural condition of the tank. Initial tests have been conducted on single plate structures to study guided wave interaction with various shapes and sizes of pertinent simulated damage mechanisms, and the experimental results were compared with hybrid finite-element numerical models. Dispersion curves were calculated to study guided wave modes and their properties in carbon steel plates and to evaluate behaviors at joints between plates. The next steps in the research process include applying the transmitters and sensors to full scale mockups, developing more mature data interpretation, and then demonstrations at an actual site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Lidar Mapping and Surveillance of Nuclear Infrastructure

Wear is unavoidable, whether it occurs in a nuclear facility or abridge on the highway its detection is crucial to preventing the failure of a system. While tools capable of detecting localized damage exist, industry lacks methods to evaluate the health of larger infrastructure. Routine inspection of nuclear facilities must be undertaken to ensure the safety of personnel and proper containment of nuclear materials. Most systems in a nuclear facility are designated as radioactive and confined spaces. To constantly monitor such systems in person would be hazardous but with a remote inspection tool it can be done in a safer and easier way. Lidar: Operates by emitting a laser pulse and looking for the reflected light. Allows user to gain 3D information of the environment. Project Objective: To develop an inspection tool for evaluating the health of large scale infrastructure using Lidar and machine learning. Autonomous Platform + Lidar + Data Fusion + Big Data. Use SLAM to build a 2D map of the environment. Point cloud created by transforming the points between reference frames. Point cloud to Surface: Inherent representation of surface geometry; Difficult to process with conventional techniques. Point cloud to Image: Easily processed by conventional machine learning algorithms. The quantity of data generated will necessitate a big data framework to manage the data for processing. Additional Sensors: Detecting the temperature (a) chemical makeup (b) and radiation emission (c) of a surface could assist in detecting problems. Human inspection can detect irregularities in both physical objects and their point-cloud representations. This is a good indication that mapping nuclear sites using Lidar will provide qualitative insight into the health of the facility. If deep learning can be used to automatically identify problem areas then the completed tool could become an invaluable asset.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

A methodology to analyze photovoltaic tracker uptime

A metric is developed to analyze the daily performance of single-axis photovoltaic (PV) trackers. The metric relies on comparing correlations between the daily time series of the PV power output and an array of simulated plane-of-array irradiances for the given day. Mathematical thresholds and a logic sequence are presented, so the daily tracking metric can be applied in an automated fashion on large-scale PV systems. The results of applying the metric are visually examined against the time series of the power output data for a large number of days and for various systems. The visual inspection results suggest that overall, the algorithm is accurate in identifying stuck or functioning trackers on clear-sky days. Visual inspection also shows that there are days that are not classified by the metric where the power output data may be sufficient to identify a stuck tracker. Based on the daily tracking metric, uptime results are calculated for 83 different inverters at 34 PV sites. The mean tracker uptime is calculated at 99% based on 2 different calculation methods. The daily tracking metric clearly has limitations, but as there is no existing metrics in the literature, it provides a valuable tool for flagging stuck trackers.

14 SOLAR ENERGY↗

DOE OSTI2019

Degradation Mechanism Detection in Photovoltaic Backsheets by Fully Convolutional Neural Network

Materials and devices age with time. Material aging and degradation has important implications for lifetime performance of materials and systems. While consensus exists that materials should be studied and designed for degradation, materials inspection during operation is typically performed manually by technicians. The manual inspection makes studies prone to errors and uncertainties due to human subjectivity. In this work, we focus on automating the process of degradation mechanism detection through the use of a fully convolutional deep neural network architecture (F-CNN). We demonstrate that F-CNN architecture allows for automated inspection of cracks in polymer backsheets from photovoltaic (PV) modules. The developed F-CNN architecture enabled an end-to-end semantic inspection of the PV module backsheets by applying a contracting path of convolutional blocks (encoders) followed by an expansive path of decoding blocks (decoders). First, the hierarchy of contextual features is learned from the input images by encoders. Next, these features are reconstructed to the pixel-level prediction of the input by decoders. The structure of the encoder and the decoder networks are thoroughly investigated for the multi-class pixel-level degradation type prediction for PV module backsheets. The developed F-CNN framework is validated by reporting degradation type prediction accuracy for the pixel level prediction at the level of 92.8%.

14 SOLAR ENERGY↗

DOE OSTI2014

State-of-the-art of non-destructive testing methods and technologies for application to nuclear power plant safety-related concrete structures

The inspection of nuclear power plant concrete structures presents challenges different from conventional civil engineering structures. Wall thicknesses can be in excess of one meter and the structures often have increased steel reinforcement density with more complex detailing. The accessibility for any testing method may be limited due to the presence of liners and other components and there can be a number of penetrations or cast-in-place items present. The objective of the report is to present the state-of-the art of non-destructive testing methods and technologies for the inspection of thick, heavily-reinforced nuclear power plant concrete cross-sections with particular respect to: •locating steel reinforcement and identification of its cover depth •locating tendon ducts and identification of the condition of the grout materials •detection of cracking, voids, delamination, and honeycombing in concrete structures •detection of inclusions of different materials or voids adjacent to the concrete side of the containment liner •methods capable of identification of corrosion occurrence on the concrete side of the containment liner.

42 ENGINEERING↗