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NASA NTRSDate not supplied

Importance of Contrast-to-Noise Ratio Sensitivity Function in Nondestructive Evaluation

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection (POD) with 95% confidence for detection of cracklike flaws of a specific size. This requirement comes from fracture control. Fracture control is a risk assessment and control approach for preventing structural failure of fracture critical hardware during its service life. One of the approaches of fracture control is damage tolerance safe life analysis, which assumes that NDE reliably detectable size flaw may exist in the hardware post nondestructive evaluation. Analysis and/or testing are performed to verify that the hardware will not fail during its service life despite existence of such a flaw. NDE methods are conventionally qualified by probability of detection (POD) demonstration testing to ensure reliable flaw detection. Here, a novel and alternative to POD flaw detection reliability approach that uses contrast-to-noise ratio (CNR) is given. The approach uses CNR sensitivity function (SF) and CNR. CNR SF is the minimum CNR needed for reliable flaw detection as a function of certain flaw indication characteristics. Primary difference between POD approaches and CNR flaw detection reliability approach is resolution of flaw detection system. POD approach does not account for the resolution of the system, while CNR approach accounts for the flaw detection resolution. Resolution is determined from the modulation transfer function (MTF) of the flaw detection system. CNR flaw detection reliability approach emphasizes quantitative assessment of “how well each flaw indication is detected”. Therefore, CNR approach is helpful in reducing number of flaws in the sample used in NDE procedure qualification, resulting in cost and time savings. CNR approach is also a case of multi-hit flaw detection analysis which has better flaw detectability size than conventional single-hit flaw detectability. Thus, CNR approach, where applicable, may be superior to conventional POD approach. The paper is an overview of development of CNR modeling, CNR SF modeling and measurement by the author. The paper gives key references to currently used NDE procedure POD qualification approaches including those specific to CNR and CNR SF development in multi-hit flaw detection in NDE. The paper covers core topics in nondestructive evaluation engineering.

Contrast-to-noise ratio↗

NASA NTRSDate not supplied

Transfer function models for using empirical and physics-based simulation signal response data

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part geometry specimens or in real parts. Typically, surface fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or cylindrical specimens. If a nondestructive evaluation (NDE)technique is required to provide a reliably detectable flaw size, denoted asa90/95, for induced flaws in a part, then a direct method for qualifying the NDE procedure is to use appropriate induced flaw specimens and perform NDE procedure demonstration on the specimens. Probability of detection (POD)analysis of the empirical data may provide estimation of a90/95. This approach is described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where embedded tight cracklike induced flaws are to be detected reliably using a signal response based NDE procedure. Here, it is assumed that it is not practical to make surface or embedded induced flaw specimens in part geometry or configuration. Therefore, a direct POD demonstration testing cannot be undertaken. It is also assumed that simulation of signal response is possible for both surface and embedded induced flaws in part geometry specimens using a physics-based model. The proposed approach for NDE procedure qualification uses artificial flaws in simple geometry and part geometry specimens, and induced flaws in the same type of simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws in simple geometry and part geometry specimens. Moreover, simulated signal response data is generated for surface and embedded flaws. Thus, a case of five signal response versus flaw size datasets is considered. Three of the datasets are empirical and two datasets are physics model-based simulation datasets. A method of devising and using transfer function calculation dataset blocks to estimate the either the reliably detectable flaw size or the demonstration flaw size is provided.

Nondestructive evaluation↗

NASA NTRSDate not supplied

An Eddy Current Case Study using NASA’s Transfer Function and Limited-Sample Probability of Detection Guidebooks

Probability of detection (POD) requirements for NASA fracture-critical human-rated systems can be met by (1) claiming ‘similarity’ to NASA Standard Nondestructive Evaluation (NDE) flaw sizes or (2) by inspector-specific POD demonstration, known as NASA Special NDE. Standard NDE flaw sizes are intended to represent the detection capability of most qualified inspectors, and were primarily based on POD studies in the development of the Space Shuttle Program Orbiter fracture control plan. However, these Standard NDE flaw sizes were based on fatigue cracks in flat panels of one material alloy over a limited range of panel thicknesses. While the POD study was comprehensive, the inspection conditions are relatively narrow. An evaluation of similarity between the Standard NDE POD study and flight component conditions is required to apply Standard NDE to specific flight component inspections. A similarity evaluation may include differences in materials, surface finish, component geometry (e.g., curvature, corners, welds), and inspection access. Similarity is typically based on a qualitative engineering evaluation. Recently, NASA published a quantitative methodology to assess similarity. If similarity is not supported by test and analysis, then the methodology provides a transfer function of flaw size for Special NDE POD demonstration. NASA recommends that Special POD demonstrations use flaws that are flight-like or more difficult to detect than flight component flaws, which are commonly induced fatigue cracks. Often, it is not feasible to induce fatigue cracks in flight component geometry, and therefore, a simpler representative geometry is used, commonly a flat panel, for POD demonstration. Inducing cracks in simple geometry specimens can be time-consuming and expensive, and thus, minimizing the number of flawed specimens is desired. Traditionally, NASA Special NDE demonstration was limited to MIL-HDBK-1823A methods or the binomial point-estimate method (PEM), commonly known as 29/29. Recently, NASA published a limited-sample POD (LS-POD) methodology for signal-response NDE techniques (e.g., eddy current) that provides POD demonstration with fewer specimens than previous approaches. LS-POD suggests a minimum of 10 flawed specimens, compared to 29 in the PEM and the suggested minimum of 40 from MIL-HDBK-1823A. The methodology also includes new guidance on evaluating the probability of false calls. In this presentation, these new transfer function and LS-POD methodologies are described and illustrated through an eddy current detection capability of far-side flaws on thin welded panels. A geometry-based transfer function is developed using electro-discharge machined (EDM) notches in flight component and simple geometry to estimate the Special NDE flaw size that is representative of the critical initial flaw size required by the fracture analysis. Then, fatigue cracks are induced in simple flat panels of the transferred flaw size, and the LS-POD methodology is used for Special NDE demonstration.

P. A. Parker↗

DOE OSTI2014

Intelligent feature selection techniques for pattern classification of Lamb wave signals

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

SURROGATE MODEL DEVELOPMENT AND VALIDATION FOR RELIABILITY ANALYSIS OF REACTOR PRESSURE VESSELS

In nuclear light water reactors (LWRs), the reactor coolant, core and shroud are contained within a massive, thick walled steel vessel known as a reactor pressure vessel (RPV). Given the tremendous size of these structures, RPVs typically contain a large population of pre-existing flaws introduced in the manufacturing process. After many years of operation, irradiation-induced embrittlement makes these vessels increasingly susceptible to fracture initiation at the locations of the pre-existing flaws. Because of the uncertainty in the loading conditions, flaw characteristics and material properties, probabilistic methods are widely accepted and used in assessing RPV integrity. The Fracture Analysis of Vessels – Oak Ridge (FAVOR) computer program developed by researchers at Oak Ridge National Laboratory is widely used for this purpose. This program can be used in order to perform deterministic and probabilistic risk-informed analyses of the structural integrity of an RPV subjected to a range of thermal-hydraulic events. FAVOR uses a one-dimensional representation of the global response of the RPV, which is appropriate for the beltline region, which experiences the most embrittlement, and employs an influence coefficient technique to rapidly compute stress intensity factors for axis-aligned surface-breaking flaws. The Grizzly code is currently under development at Idaho National Laboratory (INL) to be used as a general multiphysics simulation tool to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled RPVs. Grizzly can be used to model the thermo-mechanical response of an RPV under transient conditions observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local 3D models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. To use Grizzly for probabilistic analysis, it is necessary to have a way to rapidly evaluate stress intensity factors. To accomplish this goal, a reduced order model (ROM) has been developed to efficiently represent the behavior of a detailed 3D Grizzly model used to calculate fracture parameters. This approach uses the stress intensity factor influence coefficient method that has been used with great success in FAVOR. Instead of interpolating between tabulated solutions, as FAVOR does, the ROM approach uses a response surface methodology to compute fracture solutions based on a sampled set of results used to train the ROM. The main advantages of this approach are that the process of generating the training data can be fully automated, and the procedure can be readily used to consider more general flaw configurations. This paper demonstrates the procedure used to generate a ROM to rapidly compute stress intensity factors for axis-aligned flaws. The results from this procedure are in good agreement with those produced using the traditional influence coefficient interpolation procedure, which gives confidence in this method. This paves the way for applying this procedure for more general flaw configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Exploring the feasibility of crack detection in plate weldments through an interposed layer of viscoelastic material.

Development of new approaches in the nondestructive evaluation of welded steel plates for large naval structures continues to be an area of interest for the DoD and the military complex. In this report we will evaluate an elastic-microwave based detection and imaging method using both numerical finite element (3D FEM) and experimental methods. The evaluation was performed on two test articles that were designed to represent critical structural components with flaws of interest. Details of the materials and the mechanical drawings were provided with the test articles. Flaws, cracks and weld defects have been included in the test articles to determine detection sensitivity and accuracy of the proposed method. Our approach uses a microwave interferometer (MI) to record the scattered response of flaws in the steel plated as it is driven by an incident elastic field. The MI can “see” (penetrate) through the viscoelastic coating to the upper surface of the plate. Out-of-plane displacement amplitudes of 10nm in the frequency range (1kHz to 25kHz) are readily observable, with the key feature being, that the surface bond between the coating and the steel plate are undisturbed. The non-contact aspect of the interferometer allows for large surface regions to be accurately and efficiently scanned in space and time. Spatiotemporal data sets of this kind and specialized wavefield processing provide powerful detection and imaging modalities. From these wavefield data sets, a plate thickness mapping capability has been demonstrated that can detect thickness changes on the order of 0.79 mm (1/32”) with spatial resolution on the order of the spatial sampling rate, 15mm (~5/8”). We have also shown that a topological energy analysis of the wavefield data can detect and locate small flaws, on the order of 5-10 mm (0.025-0.40”) in the welded joint of a 1.5” thick T-plate. As before, these results are obtained through a 2” thick viscoelastic coating without altering the integrity of coating or the coating bond. These results show that we are detecting and locating damage (flaws) in the plate that are much smaller than the wavelength of the propagating guided modes. Classical scattering theory places a (λ/2) resolution limit on the detectability of flaws in terms of the incident field [22], however, since the spatial resolution of the scanned region is much smaller, (Δx=Δy=15mm) and the inherent natural focusing of the time reversal operation, we are able to detect smaller flaws on the order of (λ/10). It is important to realize that we are not imaging the flaw but detecting and localizing a difference between a reference (pristine) sample and the measured (damaged) sample, relative to a spatial grid on the surface. The current scan resolution is 15mm x 15mm. At present we cannot expect to resolve individual flaws within a grid space only their cumulative effect. Even with the current limitations, this imaging approach appears to be a promising alternative to current methods where the coating layer is removed.

36 MATERIALS SCIENCE↗

DOE OSTI2018

NDE Technology Development Program for Hanford DST Non-Visual Volumetric Inspection Technology – Phase II; Technical Letter Report on Air-slot NDE Sensor Maturation Testing

The Pacific Northwest National Laboratory (PNNL) located in Richland, Washington, hosted and administered Phase II Flaw Detection Performance Tests in August 2018 that allowed the newly matured ultrasonic guided wave phased-array (GWPA) air-slot NDE sensor—“Hanford-Probe A”—developed by Guidedwave to be evaluated for its flaw detection capability and repeatability. A portion of the Phase II Flaw Detection Performance Tests was performed on a subset of test flaws on which the original GWPA sensor was evaluated during Phase I Sensor Effectiveness Testing (SET) to facilitate a comparison in flaw detection performance between Hanford-Probe A and the original GWPA sensor demonstrated in Phase I. The objective of the performance comparison was to determine the extent to which GWPA sensor design changes impacted the flaw detection performance upon which selection of the sensor technology was originally based for the purpose of determining whether the flaw detection performance of the newly matured Hanford-Probe A GWPA air-slot NDE sensor is at least equal to that of the original GWPA sensor evaluated under Phase I SET. This technical letter report presents the results produced by the new Hanford-Probe A on the Phase I test flaws and the results of the flaw detection performance comparison between Hanford-Probe A and the original GWPA sensor demonstrated in Phase I.

47 OTHER INSTRUMENTATION↗

NASA NTRS2024

Considerations for Qualifying Reliable Eddy Current Array Technique for Detection of Backwall Cracks

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection(POD) with 95% confidence for detection of cracklike flaws of a qualified size. In this case, the flaws are on backside of material. Eddy current array (ECA) probe or a single sensor eddy current probe in c-scanning mode is used for the flaw detection. Here, two geometries are considered for the test specimens. The two geometries are, a flat plate, and tube or pipe. The probe is assumed to be on outer diameter (OD)surface and the flaw is assumed to be at the inner diameter (ID) surface for tube inspection. The flaw and probe are on opposite side of wall thickness for inspection of plate material. The application may be used for acreage inspection or just for inspection of butt weld and heat affected zone (HAZ) in a tube, cylinder, or plate. The proposed approach is based on developing an instrument standardization or calibration procedure. Decision threshold of inspection procedure is determined using empirical qualification and noise data. The work explores essential parameters that are required to meet certain conditions to ensure reliable flaw detection. Physics-based simulation of eddy current array flaw detection is used to understand effect of essential parameters on signal response (amplitude and phase),and therefore flaw detectability. Simulation data is used to justify choice of calibration reference standard requirements and the qualification approach. An ECA technique qualification model is provided. The paper gives brief description of tasks to be completed for qualifying ECA technique for reliable detection of cracklike flaws.

Eddy current array inspection, nondestructive eval↗

DOE OSTI2015

Reactor Pressure Vessel Fracture Analysis Capabilities in Grizzly

Efforts have been underway to develop fracture mechanics capabilities in the Grizzly code to enable it to be used to perform deterministic fracture assessments of degraded reactor pressure vessels (RPVs). Development in prior years has resulted a capability to calculate -integrals. For this application, these are used to calculate stress intensity factors for cracks to be used in deterministic linear elastic fracture mechanics (LEFM) assessments of fracture in degraded RPVs. The -integral can only be used to evaluate stress intensity factors for axis-aligned flaws because it can only be used to obtain the stress intensity factor for pure Mode I loading. Off-axis flaws will be subjected to mixed-mode loading. For this reason, work has continued to expand the set of fracture mechanics capabilities to permit it to evaluate off-axis flaws. This report documents the following work to enhance Grizzly’s engineering fracture mechanics capabilities for RPVs: • Interaction Integral and -stress: To obtain mixed-mode stress intensity factors, a capability to evaluate interaction integrals for 2D or 3D flaws has been developed. A -stress evaluation capability has been developed to evaluate the constraint at crack tips in 2D or 3D. Initial verification testing of these capabilities is documented here. • Benchmarking for axis-aligned flaws: Grizzly’s capabilities to evaluate stress intensity factors for axis-aligned flaws have been benchmarked against calculations for the same conditions in FAVOR. • Off-axis flaw demonstration: The newly-developed interaction integral capabilities are demon- strated in an application to calculate the mixed-mode stress intensity factors for off-axis flaws. • Other code enhancements: Other enhancements to the thermomechanics capabilities that relate to the solution of the engineering RPV fracture problem are documented here.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1984

Estimating the Lifetimes of Nickel/Cadmium Cells

Equation based on model of flaw growth. Model assumes cell fails by growth of preexisting flaws. Flaws described by three important quantities: total number of flaws, distribution of flaw sizes and rate of flaw growth. When flaw reaches critical size failure occurs. Flaw concept, in addition to providing ready explanation for reduced lifetime, predicts two important charateristics: statistical variability of lifetime data and dependence of lifetime on volume of sample.

Fedors, R. F.↗

NASA NTRS1996

Finite Element Modeling of the Thermographic Inspection for Composite Materials

The performance of composite materials is dependent on the constituent materials selected, material structural geometry, and the fabrication process. Flaws can form in composite materials as a result of the fabrication process, handling in the manufacturing environment, and exposure in the service environment to anomalous activity. Often these flaws show no indication on the surface of the material while having the potential of substantially degrading the integrity of the composite structure. For this reason it is important to have available inspection techniques that can reliably detect sub-surface defects such as inter-ply disbonds, inter-ply cracks, porosity, and density changes caused by variations in fiber volume content. Many non-destructive evaluation techniques (NDE) are capable of detecting sub-surface flaws in composite materials. These include shearography, video image correlation, ultrasonic, acoustic emissions, and X-ray. The difficulty with most of these techniques is that they are time consuming and often difficult to apply to full scale structures. An NDE technique that appears to have the capability to quickly and easily detect flaws in composite structure is thermography. This technique uses heat to detect flaws. Heat is applied to the surface of a structure with the use of a heat lamp or heat gun. A thermographic camera is then pointed at the surface and records the surface temperature as the composite structure cools. Flaws in the material will cause the thermal-mechanical material response to change. Thus, the surface over an area where a flaw is present will cool differently than regions where flaws do not exist. This paper discusses the effort made to thermo-mechanically model the thermography process. First the material properties and physical parameters used in the model will be explained. This will be followed by a detailed discussion of the finite element model used. Finally, the result of the model will be summarized along with recommendations for future work.

Bucinell, Ronald B.↗

NASA NTRSDate not supplied

Effects of Defects Analysis and Sizing Framework for Efficient Design of Composite Structures

Design of large composite structures requires striking a balance between permitted flaw size,strength margins, weight, and production rate. Stringent requirements manufacturing flaws can result in a lightweight structure because the strength properties are assumed to be closer to pristine. However, these stringent requirements can lead to production delays due to increased inspection and rework needed during the layup and rejection of parts after cure. Conversely, permitting larger flaws can reduce production delays, but will likely result in a heavier structure due to increased conservatism needed to maintain acceptable structural margins. The tradeoff between these criteria can vary between different structures and material systems, so the balance between manufacturing and design requirements is always a moving target. Assessment of this tradeoff requires having the ability to quickly evaluate the impact of flaw size on strength margin across an entire structure for a large number of load cases. The approach taken in this work is to implement an effects of defects analysis and sizing framework within HyperX. HyperX performs optimization of composite structures; this capability has been enhanced to include structural flaw data in the margin of safety calculations performed during optimization. Both the flaw import process and analysis of flaws have been generalized such that any flaw type from any source can be considered. The resulting tool enables rapid assessment of the impact of defects both at a vehicle and part level.

Effects of defects↗

NASA NTRSDate not supplied

Effects of Defects Analysis and Sizing Framework for Efficient Design of Composite Structures

Effects of defects↗

DOE OSTI2018

Hanford Under-tank Inspection with Ultrasonic Volumetric Non-destructive Examination Technology - 18470

The U.S. Department of Energy (DOE) and the Hanford Site Tank Operations Contractor Washington River Protection Solutions, LLC (WRPS) are sponsoring a non-destructive evaluation (NDE) technology development program to identify and mature volumetric (non-visual) NDE technology that will enable the examination of Hanford double-shell tank (DST) bottoms. NDE technology for Hanford under-tank examination will be made possible through technology maturation that includes adaptation of NDE sensor technology to overcome access challenges presented by tank risers and refractory pad air-slots, followed by integration with robotic delivery systems, and ultimately qualification and deployment of the inspection systems. The stages of technology maturation and the testing and evaluation required to support the process are organized under three program phases: Phase I - NDE Capability Testing: Identify and down-select NDE technologies based on flaw detection and characterization abilities only; Phase 2 - NDE Delivery System Testing: Mature promising NDE technologies to adapt transducer hardware and robotic delivery system to address access challenges; Phase 3 - Full-scale Demonstration of Integrated NDE System: Demonstrate adapted NDE technologies in a cold test platform to challenge flaw detection and navigation abilities. Phase I of the program, which was initiated and completed in FY2017, focused on completing the following five key activities: 1. Identifying a broad cross section of potentially applicable NDE volumetric inspection technologies for under-tank examination. 2. Down-selecting the broad set of NDE technologies to a set of strong candidates based on initial flaw detection performance and potential to be adapted/matured to overcome primary tank access challenges posed by access risers and/or refractory pad air-slots. 3. Evaluating the flaw detection performance of the candidate sensors through testing. 4. Using the test results to baseline sensor performance against the flaw detection requirements established for high-level waste tanks. 5. Assessing the trade-offs and vulnerabilities of the candidate sensors that would negatively impact sensor performance reliability or complicate tank inspection operations. The completion of the first three key activities satisfied the first two Phase I test objectives, which were to complete Technology Screening and Sensor Effectiveness Testing. Completion of the fourth key activity satisfied the final test objective of Phase I, which was to determine the extent to which the sensors can satisfy high-level waste tank flaw detection requirements. Sensor flaw detection performance testing yielded several suitable sensor technology options, although each has specific risks or challenges that would need to be accepted or overcome. Thus, the fifth key activity was performed to evaluate sensor risks and challenges for consideration with flaw detection performance. The Phase I evaluation outcomes will be used to support the Phase I programmatic objective, which is to identify one or more NDE sensor technologies for adaptation and maturation for the DST environment. Selection of one or more sensors will mark the culmination of Phase I of the NDE Technology Development Program and allow progression to Phase II.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Initial Probabilistic Evaluation of Reactor Pressure Vessel Fracture with Grizzly and Raven

The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled reactor pressure vessels (RPVs). Grizzly can be used to model the thermal/mechanical response of an RPV under transient conditions that would be observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. These capabilities have been demonstrated previously. A typical RPV is likely to contain a large population of pre-existing flaws introduced during the manufacturing process. This flaw population is characterized stastistically through probability density functions of the flaw distributions. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation during a transient event. This report documents initial work to perform probabilistic analysis of RPV fracture during a PTS event using a combination of the RAVEN risk analysis code and Grizzly. This work is limited in scope, considering only a single flaw with deterministic geometry, but with uncertainty introduced in the parameters that influence fracture toughness. These results are benchmarked against equivalent models run in the FAVOR code. When fully developed, the RAVEN/Grizzly methodology for modeling probabilistic fracture in RPVs will provide a general capability that can be used to consider a wider variety of vessel and flaw conditions that are difficult to consider with current tools. In addition, this will provide access to advanced probabilistic techniques provided by RAVEN, including adaptive sampling and parallelism, which can dramatically decrease run times.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Reactor Pressure Vessel Fracture Mechanics Development and Concrete Application Testing for Grizzly

The Grizzly code is being developed to address degradation issues in nuclear reactor structures and components. For light-water reactors, Grizzly currently has capabilities to simulate degradation processes and their effects on structural integrity in two key areas: reactor pressure vessels (RPVs) and reinforced concrete structures. This report documents improvements made to Grizzly’s ability to address both of these structural systems. For RPVs, the reduced-order models (ROMs) used in fracture mechanics calculations have been expanded to allow their application over a broader range of the parameter space than was permitted by the previous models. The ROMs currently used in Grizzly for the evaluation of flaws that are fully embedded within the RPV (as opposed to surface-breaking flaws) are based on a model that is known to be conservative, indicating higher stress intensity factors than would be obtained from direct simulations. A more accurate model that eliminates these excess conservatisms has been recently included in the American Society of Mechanical Engineers Boiler and Pressure Vessel Code but was not applicable for flaws near the RPV surface, which is where the most critical flaws are usually located. That model has recently been extended for increased applicability in this near-surface region. The ROMs for embedded flaws in the Grizzly code have been expanded to include these recent extensions, which permit their use in a much broader set of cases than previously possible. Direct 3D simulations have been used to check these ROMs and have shown good agreement in most cases, although there are still some cases that need further investigation. There are considerable benefits to using these these more accurate and less conservative ROMs for embedded flaws. On a benchmark probabilistic fracture mechanics problem tested here, the conditional probability of fracture initiation computed for a population of flaws in a single plate in an RPV decreased by over a factor of 3. To address aging in reinforced concrete structures, a capability to simulate multiple degradation mechanisms, including alkali-silica reaction and radiation-induced volumetric expansion has been developed in Grizzly over the past several years. This had previously been demonstrated on laboratory-scale specimens but not on full-scale nuclear concrete structures with reinforcement. To demonstrate the applicability of Grizzly to the analysis of large-scale structures of interest, a full 3D model of a representative reinforced concrete structure, including a complex arrangement of reinforcing bars, was developed and demonstrated in Grizzly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2011

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Generazio, Edward R.↗

DOE OSTI2015

Wind Turbine Development at Montana State University

A survey of wind turbine blade manufacturers, repair companies, wind farm operators, and third party investigators has directed the focus of this investigation on several types of flaws commonly found in wind turbine blades: waviness and porosity/voids. Several commercial scale wind turbine blades were inspected for the development of metrics for the identification, analysis and disposition. Analysis of flaw geometries yielded metrics which utilize specific parameters to physically characterize a defect. Data as it relates flaw parameters to frequencies of occurrence have been complied. Basic statistical analysis shows that the frequency of flaw parameters generally follows standard distributions. A testing program was then developed around this flaw data. Results from static testing indicate that there is strong correlation between flaw parameters and mechanical response. Preliminary results from the in-field data collection effort and coupon level testing have established a protocol by which a defect in a blade can be characterized quantifiably. With this data it is possible to develop probabilistic analysis, damage progression models and criticality assessment tools that will enable improved blade design methodology and the development of a risk management framework which describes the probability of failure for blades with defects.

17 WIND ENERGY↗