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At least 73 records · Page 4

Measurements and Computations of Natural Transition on the NASA Juncture-Flow Model with a Symmetric Wing

Experiments were performed in the 14- by 22-Foot Subsonic Tunnel to assess natural transition on the symmetric-airfoil wings of the NASA Juncture-Flow Model. Infrared thermography was used to visualize the heating on the upper surface of both wings of the full-span model, and on the fuselage, for angles of incidence ranging from -10° to 10° at a fixed Reynolds number of 2.4E6 based on the chord length at the wing planform break. The fuselage boundary layer transitioned well upstream of the wing-root leading edge for all conditions. Transition fronts were identified by a steep rise in the surface temperature, and the transition coordinates were transformed from an image-based to a body-fixed system. Additionally, the state of the boundary layer was estimated at pressure ports distributed on the wings through observation of the pressure coefficient as a function of the angle of incidence. For increasing angles of incidence, the transition front was observed to advance upstream, in a mostly spanwise-uniform fashion, from near midchord at α = 0°; however, for increasingly negative angles of incidence, the transition front first receded and then advanced in a nonuniform jagged manner that is typically observed with stationary crossflow. The transition wedges first appeared inboard of the wing break and then spread outboard to near the tip by α = -6°. The upstream shift in transition at positive angles of incidence and the outboard progression of crossflow-dominated transition at increasingly negative angles of incidence are consistent with trends identified in a computational assessment of the boundary-layer transition based on both linear stability analysis and Reynolds-averaged-Navier-Stokes-based transition models. The stability results obtained from the Langley Stability and Transition Analysis Code were used to recalibrate a dual N-factor criterion, which allowed for the prediction of transition fronts that showed excellent agreement with the experiment. The Reynolds-averaged-Navier-Stokes-based models, from the NASA OVERFLOW 2.3 solver, that accounted for the crossflow instability showed mixed results in comparison with the experiment, with the helicity-based Langtry-Menter model performing the best. The experimental data, particularly the cases involving strong influence from both Tollmien-Schlichting and crossflow instabilities, will be valuable for the continued validation and improvement of transition models.

boundary layer transition↗

Fluid-Thermal-Structural Interactions in Ramp-Induced Shock-Wave Boundary-Layer Interactions at Mach 6

Shock-wave boundary-layer interactions (SWBLI) pose unique challenges for the slender airframes and sharp control surfaces characteristic of high-speed airbreathing aircraft. Spikes in pressure and thermal loading have been shown to occur in SWBLI regions; thus, predicting their location and behavior proves critical for assuring aircraft structural integrity and fatigue resilience. SWBLIs frequently lead to severe turbulent boundary-layer separation and corresponding unsteady motions characterized by a wide range of frequencies. Low-frequency motion has been shown to couple with the structure of a compliant panel, and turbulent boundary layers thus present a particular danger for thin control surfaces. Previous studies have shown that the thermal loading on a compliant panel in a ramp-induced SWBLI may have a signi cant impact on the panel vibrations. A multitude of studies has investigated the heating on rigid structures, but a charactrization of the heating effects on compliant structures is necessary to fully understand the fluid-thermal-structural interactions (FTSI) occurring in ramp-induced SWBLIs. This studuses infrared thermography and high-frequency Kulite pressure transducers to examine the heating loads on rigid and compliant ramps at various angles and flow conditions at Mach 6.

Hypersonic↗

Infrared Thermography Flight Experimentation

Analysis was done on IR data collected by DFRC on May 8, 2002. This includes the generation of a movie to initially examine the IR flight data. The production of the movie was challenged by the volume of data that needed to be processed, namely 40,500 images with each image (256 x 252) containing over 264 million points (pixel depth 4096). It was also observed during the initial analysis that the RTD surface coating has a different emissivity than the surroundings. This fact added unexpected complexity in obtaining a correlation between RTD data and IR data. A scheme was devised to generate IR data near the RTD location which is not affected by the surface coating This scheme is valid as long as the surface temperature as measured does not change too much over a few pixel distances from the RTD location. After obtaining IR data near the RTD location, it is possible to make a direct comparison with the temperature as measured during the flight after adjusting for the camera s auto scaling. The IR data seems to correlate well to the flight temperature data at three of the four RID locations. The maximum count intensity occurs closely to the maximum temperature as measured during flight. At one location (RTD #3), there is poor correlation and this must be investigated before any further progress is possible. However, with successful comparisons at three locations, it seems there is great potential to be able to find a calibration curve for the data. Moreover, as such it will be possible to measure temperature directly from the IR data in the near future.

Blanchard, Robert C.↗

Flash Infrared Thermography Contrast Data Analysis Technique

This paper provides information on an IR Contrast technique that involves extracting normalized contrast versus time evolutions from the flash thermography inspection infrared video data. The analysis calculates thermal measurement features from the contrast evolution. In addition, simulation of the contrast evolution is achieved through calibration on measured contrast evolutions from many flat-bottom holes in the subject material. The measurement features and the contrast simulation are used to evaluate flash thermography data in order to characterize delamination-like anomalies. The thermal measurement features relate to the anomaly characteristics. The contrast evolution simulation is matched to the measured contrast evolution over an anomaly to provide an assessment of the anomaly depth and width which correspond to the depth and diameter of the equivalent flat-bottom hole (EFBH) similar to that used as input to the simulation. A similar analysis, in terms of diameter and depth of an equivalent uniform gap (EUG) providing a best match with the measured contrast evolution, is also provided. An edge detection technique called the half-max is used to measure width and length of the anomaly. Results of the half-max width and the EFBH/EUG diameter are compared to evaluate the anomaly. The information provided here is geared towards explaining the IR Contrast technique. Results from a limited amount of validation data on reinforced carbon-carbon (RCC) hardware are included in this paper.

Koshti, Ajay↗

Building envelope anomaly characterization and simulation using drone time-lapse thermography

Defects in building envelopes deteriorate over time without being visible to the human eye, while significantly impacting energy performance due to unaccounted heat transfer. Defects can be characterized in the infrared (IR) spectrum. However, IR readings are typically recorded at singular points in time, when in several cases anomalies can only be revealed at specific times of the day, possibly in different seasons of the year. This paper presents a novel workflow for 3D envelope defect characterization and modeling using aerial time-lapse IR data collection using drones. A comprehensive envelope thermal profile is developed for a case study building employing the photogrammetry software Agisoft Photoscan, which generates temporal IR inspections of building skins using multiple thermography orthomosaics. Point-cloud data is then translated into a CAD model and thermal zones for whole Building Energy Modeling (BEM) using Honeybee as a frontend to EnergyPlus to showcase the potential of inclusion of detailed 4D data. Envelope contributions in this case study’s anomalies showed heat losses of 6447.6 kWh, and Energy Use Intensity (EUI) differences of ~2 kWh/m 2 /year from the baseline. Finally, why there is currently little translation of this work in BEM software is discussed, while identifying limitations and future research in the employment of time-lapse thermography using drones for more accurate building envelope inspection and modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advancement of Commercial Intumescent Expanding Foams for Deactivation and Decommissioning in the Nuclear Sector - 20198

Florida International University (FIU), in collaboration with The Department of Energy's Office of Environmental Management (DOE-EM), Savannah River National Laboratory (SRNL), and sites across the Savannah River complex, have identified an operational requirement for a fixative technology that is intended to immobilize and/or isolate residual contamination within a 3-dimensional space. Fixation of radiological contamination can reduce worker risk and mitigate potentially hazardous conditions, however nearly every marketed contamination fixative has been found to be flammable; a significant concern in radiological facilities. Coupled with this, industry fixatives are normally used as a thin coating which can present problems when attempting to stabilize irregular geometry or areas that are difficult to access whilst ensuring full coverage. The technical evaluation and advancement of commercial-off-the-shelf (COTS) polyurethane foams has yielded a down-selected candidate that shows potential in meeting the requirements to support deactivation and decommissioning activities. Several performance criteria have been established and tested to progress the technology readiness level towards an active field demonstration (TRL-7). Such criteria include: mechanical failure limits, adhesive and cohesive properties, thermal/fire resilience, determining thermal behavior, ability to immobilize contamination, and a means of non-destructive evaluation of applications. The test scenario examined was targeted towards an application for decommissioning nuclear pipework, in which the down-selected polyurethane foam would act as a barrier to segregate pipework and mitigate the potential for release during cutting, packaging, and storage operations. Testing carried out at SRNL included: mechanical evaluation of tensile, compressive, and adhesion strength by dynamic mechanical analysis (DMA), as well as thermogravimetric analysis (TGA). FIU examined the foam's fixative properties by utilizing phosphorescent europium-dysprosium doped strontium aluminate powder to investigating the extent to which contamination can be immobilized. FIU has also exploited previous successes in the field of intumescent technologies to assess the down-selected foam's tolerance to an extreme fire scenario, while maintaining the ability to effectively mitigate a contamination release. Parallel to this, extensive thermal investigations were carried out to determine the upper boundary of anticipated heat generation during the curing process as heat generation has the potential to compromise rubber parts of contaminated enclosures. These investigations subsequently yielded a promising method for a non-destructive application evaluation by means of infrared thermography. Utilizing the high sensitivity of modern IR cameras, coupled with the heat generated during the curing process of the polyurethane foam, FIU has been exploring the concept of monitoring the external pipe surface for indications of an irregular or abnormal application, thus informing operational decision making. The testing carried out utilized several current 'best fit' ASTM standards, which serve as helpful guidelines for testing, however, a precise definition of the operational parameters and requirements is still necessary. With continued collaboration with SRNL, FIU aims refine said definitions and develop new standards by which this, and other decommissioning technologies, can be accredited by relevant standards based testing. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Advanced IR System For Supersonic Boundary Layer Transition Flight Experiment

Infrared thermography is a preferred method investigating transition in flight: a) Global and non-intrusive; b) Can also be used to visualize and characterize other fluid mechanic phenomena such as shock impingement, separation etc. F-15 based system was updated with new camera and digital video recorder to support high Reynolds number transition tests. Digital Recording improves image quality and analysis capability and allows for accurate quantitative (temperature) measurements and greater enhancement through image processing allows analysis of smaller scale phenomena.

Banks, Daniel W.↗

Infrared On-Orbit RCC Inspection With the EVA IR Camera: Development of Flight Hardware From a COTS System

In November 2004, NASA's Space Shuttle Program approved the development of the Extravehicular (EVA) Infrared (IR) Camera to test the application of infrared thermography to on-orbit reinforced carbon-carbon (RCC) damage detection. A multi-center team composed of members from NASA's Johnson Space Center (JSC), Langley Research Center (LaRC), and Goddard Space Flight Center (GSFC) was formed to develop the camera system and plan a flight test. The initial development schedule called for the delivery of the system in time to support STS-115 in late 2005. At the request of Shuttle Program managers and the flight crews, the team accelerated its schedule and delivered a certified EVA IR Camera system in time to support STS-114 in July 2005 as a contingency. The development of the camera system, led by LaRC, was based on the Commercial-Off-the-Shelf (COTS) FLIR S65 handheld infrared camera. An assessment of the S65 system in regards to space-flight operation was critical to the project. This paper discusses the space-flight assessment and describes the significant modifications required for EVA use by the astronaut crew. The on-orbit inspection technique will be demonstrated during the third EVA of STS-121 in September 2005 by imaging damaged RCC samples mounted in a box in the Shuttle's cargo bay.

Gazanik, Michael↗

Infrared Contrast Analysis Technique for Flash Thermography Nondestructive Evaluation

The paper deals with the infrared flash thermography inspection to detect and analyze delamination-like anomalies in nonmetallic materials. It provides information on an IR Contrast technique that involves extracting normalized contrast verses time evolutions from the flash thermography infrared video data. The paper provides the analytical model used in the simulation of infrared image contrast. The contrast evolution simulation is achieved through calibration on measured contrast evolutions from many flat bottom holes in the subject material. The paper also provides formulas to calculate values of the thermal measurement features from the measured contrast evolution curve. Many thermal measurement features of the contrast evolution that relate to the anomaly characteristics are calculated. The measurement features and the contrast simulation are used to evaluate flash thermography inspection data in order to characterize the delamination-like anomalies. In addition, the contrast evolution prediction is matched to the measured anomaly contrast evolution to provide an assessment of the anomaly depth and width in terms of depth and diameter of the corresponding equivalent flat-bottom hole (EFBH) or equivalent uniform gap (EUG). The paper provides anomaly edge detection technique called the half-max technique which is also used to estimate width of an indication. The EFBH/EUG and half-max width estimations are used to assess anomaly size. The paper also provides some information on the "IR Contrast" software application, half-max technique and IR Contrast feature imaging application, which are based on models provided in this paper.

Koshti, Ajay↗

Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.

aerial inspection↗

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗

Solar Tower Experiments for Radiometric Calibration and Validation of Infrared Imaging Assets and Analysis Tools for Entry Aero-Heating Measurements

The NASA Engineering and Safety Center sponsored Hypersonic Thermodynamic Infrared Measurements assessment team has a task to perform radiometric calibration and validation of land-based and airborne infrared imaging assets and tools for remote thermographic imaging. The IR assets and tools will be used for thermographic imaging of the Space Shuttle Orbiter during entry aero-heating to provide flight boundary layer transition thermography data that could be utilized for calibration and validation of empirical and theoretical aero-heating tools. A series of tests at the Sandia National Laboratories National Solar Thermal Test Facility were designed for this task where reflected solar radiation from a field of heliostats was used to heat a 4 foot by 4 foot test panel consisting of LI 900 ceramic tiles located on top of the 200 foot tall Solar Tower. The test panel provided an Orbiter-like entry temperature for the purposes of radiometric calibration and validation. The Solar Tower provided an ideal test bed for this series of radiometric calibration and validation tests because it had the potential to rapidly heat the large test panel to spatially uniform and non-uniform elevated temperatures. Also, the unsheltered-open-air environment of the Solar Tower was conducive to obtaining unobstructed radiometric data by land-based and airborne IR imaging assets. Various thermocouples installed on the test panel and an infrared imager located in close proximity to the test panel were used to obtain surface temperature measurements for evaluation and calibration of the radiometric data from the infrared imaging assets. The overall test environment, test article, test approach, and typical test results are discussed.

Splinter, Scott C.↗

Capturing a failure of an ASIC in-situ, using infrared radiometry and image processing software

Failures in electronic devices can sometimes be tricky to locate-especially if they are buried inside radiation-shielded containers designed to work in outer space. Such was the case with a malfunctioning ASIC (Application Specific Integrated Circuit) that was drawing excessive power at a specific temperature during temperature cycle testing. To analyze the failure, infrared radiometry (thermography) was used in combination with image processing software to locate precisely where the power was being dissipated at the moment the failure took place. The IR imaging software was used to make the image of the target and background, appear as unity. As testing proceeded and the failure mode was reached, temperature changes revealed the precise location of the fault. The results gave the design engineers the information they needed to fix the problem. This paper describes the techniques and equipment used to accomplish this failure analysis.

infrared↗

Performance of Compact Pulsed Thermal Imaging System for In-Service Applications. Pulsed thermal tomography nondestructive examination of additively manufactured reactor materials and components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Neural Learning Based Blind Source Separation for Detection of Material Defects in Pulsed Thermography Images

In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

Zhang, Xin↗

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.

42 ENGINEERING↗