Results for “Additively Manufacturing” — Page 18

DOE OSTI2026

A scalable framework for efficient coupling of thermal and microstructural simulations in additive manufacturing

Predicting microstructure evolution in metal additive manufacturing (AM) is important for process optimization, but spatiotemporal scale disparities between thermal transport and microstructure evolution create significant challenges for efficient data transfer between simulation codes. To address this, we present Stork, a scalable framework for coupling thermal and microstructural simulations. Stork uses a sparse data representation to identify and store active solidification sub-volumes, enabling highly parallel quad-linear interpolation from coarse thermal grids to fine microstructure grids without large intermediate storage. We demonstrate the framework by coupling the semi-analytic heat transfer code 3DThesis with the time-parallel cellular automata code Toucan. This approach achieves over two orders of magnitude reduction in data generation time and file size compared to prior workflows. Numerical studies show that quad-linear interpolation preserves grain morphology and crystallographic texture in laser powder bed fusion (LPBF) simulations for coarsening ratios up to 16. Overall, Stork provides a scalable pathway for high-throughput, component-scale AM simulations on modern high-performance computing systems.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High-resolution 3D strain and orientation mapping within a grain of a directed energy deposition laser additively manufactured superalloy

The industrialization of Laser Additive Manufacturing (LAM) is challenged by the undesirable microstructures and high residual stresses originating from the fast and complex solidification process. Non-destructive assessment of the mechanical performance controlling deformation patterning is therefore critical. Here, we use Dark Field X-ray Microscopy (DFXM) to map the 3D subsurface intragranular orientation and strain variations throughout a surface-breaking grain within a directed energy deposition nickel superalloy. DFXM results reveal a highly heterogenous 3D microstructure in terms of the local orientation and lattice strain. The grain comprises ≈ 5 μm-sized cells with alternating strain states, as high as 5 x10 -3 , and orientation differences <0.5°. The DFXM results are compared to Electron Backscatter Diffraction measurements of the same grain from its cut-off surface. Here, we discuss the microstructure developments during LAM, rationalising the development of the deformation patterning from the extreme thermal gradients during processing and the susceptibility for solute segregation.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Synergistic effect of microstructure and defects on the initiation of fatigue cracks in additively manufactured Inconel 718

Fatigue cracks in additively manufactured (AMed) Inconel 718 (IN-718) in machined surface condition often initiate from persistent slip bands (PSBs) unlike other popular AM alloys such as 17-4 PH stainless steel or Ti-6Al-4V, where fatigue crack initiation is exclusively from volumetric defects; therefore, a competition between PSB- vs. defect- mediated crack initiation clearly exists. To shed light on the factors governing the competition, this study investigates the characteristics of cyclic strain localization, PSB formation, and crack initiation via crystal plasticity (CP) modeling of cyclic loading on polycrystalline aggregates which are then validated by experiments. In this work, a physics-based, free slip distance (FSD) dependent slip strength evolution law is proposed, which is shown to enable the CP model to simulate the heterogeneous strain distribution in IN-718. Implementing a crack initiation criterion based on strain contrast, the locations and lives for crack initiation can also be calculated. It is shown that both FSD and resolve shear stress influence the strain localization and crack initiation behaviors. The distribution of a localization parameter calculated based on the multiplication of FSD and Schmid factor within a grain is found to correlate well with the locations of PSBs. The maximum values of the localization parameters within a microstructure are shown to correlate well with the experimentally obtained crack initiation lives. The presence of volumetric defects in IN-718 generally do not impact strain localization behavior unless their size is large compared to the grain size.

42 ENGINEERING↗

DOE OSTI2025

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗

DOE OSTI2022

In Situ X-ray Radiography and Computational Modeling to Predict Grain Morphology in $\beta$-Titanium during Simulated Additive Manufacturing

The continued development of metal additive manufacturing (AM) has expanded the engineering metallic alloys for which these processes may be applied, including beta-titanium alloys with desirable strength-to-density ratios. To understand the response of beta-titanium alloys to AM processing, solidification and microstructure evolution needs to be investigated. In particular, thermal gradients (Gs) and solidification velocities (Vs) experienced during AM are needed to link processing to microstructure development, including the columnar-to-equiaxed transition (CET). In this work, in situ synchrotron X-ray radiography of the beta-titanium alloy Ti-10V-2Fe-3Al (wt.%) (Ti-1023) during simulated laser-powder bed fusion (L-PBF) was performed at the Advanced Photon Source at Argonne National Laboratory, allowing for direct determination of Vs. Two different computational modeling tools, SYSWELD and FLOW-3D, were utilized to investigate the solidification conditions of spot and raster melt scenarios. The predicted Vs obtained from both pieces of computational software exhibited good agreement with those obtained from in situ synchrotron X-ray radiography measurements. The model that accounted for fluid flow also showed the ability to predict trends unobservable in the in situ synchrotron X-ray radiography, but are known to occur during rapid solidification. A CET model for Ti-1023 was also developed using the Kurz–Giovanola–Trivedi model, which allowed modeled Gs and Vs to be compared in the context of predicted grain morphologies. Both pieces of software were in agreement for morphology predictions of spot-melts, but drastically differed for raster predictions. The discrepancy is attributable to the difference in accounting for fluid flow, resulting in magnitude-different values of Gs for similar Vs.

36 MATERIALS SCIENCE↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogeneities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogeneities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogeneities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogenities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

ICME and In-Situ Process Monitoring for Rapid Qualification of Components Made by Laser-based Powder Bed Additive Manufacturing Processes for Nuclear Structural Applications

Additive manufacturing (AM) through selective powder bed melting of successive layers is being considered as disruptive technology for rapid production of low-cost nuclear reactor internal components with complex geometries. However, there is a potential for non-uniform distribution of physical features, such as porosity or microstructural differences, due to variations of temperature across a component build. These heterogenities make the deployment of traditional material qualification and non-destructive evaluation of AM components difficult. This research project explored the feasibility of using in-situ process monitoring methods and integrated computational materials engineering (ICME) principles as an alternate qualification methodology and approach. This project included six individual tasks: (i) design of artifacts relevant to the nuclear power industry, (ii) evaluation of laser processing and in-situ measurements, (iii) computational modeling, (iv) ex-situ microstructural characterization, (v) evaluation of scaling the methodology for large-scale structures, and (vi) development of a data package to codes and standards organizations. As a part of this research, laser powder bed fusion of metals (316L, Alloy 718, and Ti6Al4V) was explored. This document provides an overview of the research performed over three years and serves as the final U.S. Department of Energy report for this project. In the third year, the project focused on the following activities: (a) in-situ infrared and optical imaging of each layer during processing of representative stainless steel geometries; (b) development of methodologies to analyze the data; and (c) application of ICME methodologies and other experiments to estimate the relevance of defects and microstructure to tensile properties.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Explosive fragmentation of additively manufactured stainless steel

Properties of fragmentation from an explosively driven 316L stainless steel spherical shell section fabricated by a laser powder bed additive manufacturing process with minimal surface finishing are investigated. This shell is driven by an insensitive high explosive, resulting in high strain rate deformation (>8 × 10 3 s –1 ) and failure of the stainless steel. Photonic Doppler velocimetry measures the expansion rate; dynamic radiography and high-speed imaging capture the fracture behavior of the stainless steel. The fracture response of the additively manufactured stainless steel shell is compared to published experimental results on additively manufactured 316L stainless steel and conventionally manufactured wrought 316L and 304 stainless steel shell fragmentation. Despite preferred crack orientation, suggesting the influence of surface grooves on fracture time, fragment size is identical to that measured in a similar experiment on wrought 304 stainless steel. Further analysis indicates that the 316L additively manufactured stainless steel shell exhibits comparable spall strength and fragmentation toughness to conventionally manufactured stainless steel yet lower failure strain due to surface stress concentrations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Additive Manufacturing Technologies Survey

A literature search of the most prominent and widely available additive manufacturing technologies was done to understand the current developments in this area. The first section provides the introduction and scope for this report, followed by a very detailed second section on the different types of additive manufacturing technologies, how they work, the materials used, advantages and disadvantages of each technology, and manufacturer information. For comparative purposes, a third section on the most widely used subtractive technology, Computer Numerical Control (CNC) machining, is presented with information about the parameters used and the benefits and limitations of this technology. A final section with a summary and conclusions is presented with information comparing the power and utility of the different additive manufacturing technologies compared to traditional manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Robot-based Additive Manufacturing of Lego-type Modular Molds for Wind Blades

The objective of this project is to reduce the cost and lead time of horizontal wind turbine blade mold tooling and blade transportation, while maintaining the highest standards of blade quality. The solution involves a smart-design family of modular molds that are easily transportable to fabrication sites near the place of service. Key innovations include the use of additive manufacturing (AM) to integrate conformal thermal management channels, offering enhanced control over the thermal profiles tailored to specific blade materials. This approach enables in-situ quality assurance during mold fabrication, significantly improves mold life, and allows for reuse across multiple production cycles. Ultimately, the solution aims to optimize both tooling and transportation costs, contributing to the scalability of wind turbine blade production. A significant barrier to scaling up the production of large wind turbine blades lies in the high costs associated with tooling and the transportation of blades. Traditional molds are expensive, bulky, and difficult to transport, adding considerable lead time and cost to the overall manufacturing process. Additionally, transporting blades to distant locations for final assembly further exacerbates these challenges. The project aims to address these inefficiencies by demonstrating a modularized, additive-manufactured mold that meets all necessary blade specification requirements, specifically for blade lengths between 120m and 150m.

17 WIND ENERGY↗

DOE OSTI2025

Wire Arc Additive Manufacturing of Lightweight High Pressure Die Casting Tooling

Oak Ridge National Laboratory (ORNL) and Mercury Marine partnered to develop and test methods for additively manufactured tooling for aluminum die casting applications under CRADA agreement NFE- 20-08193. Tooling is the largest capital expense for high production casting projects. The lead time for tooling is often measured in months with a typical project taking 9-12 months to realize Production Part Approval Process (PPAP) ready die cast samples. This project demonstrated the technical viability of rapidly produced steel components for high pressure die casting tooling via Wire Arc Additive Manufacturing (WAAM). A 410 stainless steel tool was redesigned and optimized with conformal cooling channels and additively manufactured. The finished tool was tested and used to produce over 4000 parts, which well surpassed expectations. A secondary objective was to evaluate the durability of multi-material additively manufactured (AM) components with conformal cooling. A large multi-material tool (H13 and 410SSNiMo) was manufactured using the same methods showing potential reductions in used material and cost. However, the H13 section sustained material cracking. Further analysis showed that the potential cause was the CTE mismatch of the two materials at higher temperatures. It is also suggested that the material mix can be used if the steel processing temperature does not exceed 600 ˚C. This project has shown high potential for using the WAAM technology for creating AM parts for aluminum dies casting. However, the multi-material approach requires extended study and tests.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Impact of controlled prewetting on part formation in binder jet additive manufacturing

Binder jetting is an additive manufacturing process that bonds powder through selectively depositing binder by inkjet printing. The part is then extracted and densified by sintering and/or infiltration. The process offers low costs and fast build rates, but properties can be poor due to residual porosity after sintering. The inkjet printing process may contribute to this residual porosity by creating large pores. The droplet kinetic energy ejects some powder particles from the bed and rearranges others. Particle ejection and rearrangement are theorized to create porous regions in binder-jetted parts. In this work, small amounts of moisture are added to the spread powder before printing and the impact on part formation, part properties, and printing parameters measured with varied droplet spacing, droplet velocity, and print frequency. Moisture is added by applying an atomized fluid mixture to the powder between layer spreading and binder printing. The fluid mixture partially evaporates but leaves a stable residue to increase cohesion and enhance imbibition. Moisture addition to the powder increases the range of droplet spacings for line formation while reducing particle ejection, powder rearrangement, and balling in layer and multilayer parts. Excessive moisture addition decreases the effective saturation of printed lines, but saturation in 3D parts is less impacted. Increased surface roughness in the first few layers of a print was also mitigated with prewetting. Finally, high-speed X-ray imaging verified prewetting reduction in particle ejection and rearrangement.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Investigating Marine Environmental Degradation of Additive Manufacturing Materials for Renewable Energy Applications

Marine renewable energy is a relatively young industry where there is a great need for rapid prototyping in design-build-test campaigns to quickly mature groundbreaking technologies. Additive manufacturing has an important role to play in the industry; however, little information is available to marine energy developers to help inform them on which additive manufacturing materials are appropriate for highly loaded structures in harsh marine environments. This paper presents an initial study on the mechanical characterization of polymeric additive manufacturing materials and the degradation effects due to the marine environment. Ultem 9085, acrylonitrile styrene acrylate, and chopped carbon-filled nylon, as well as continuous carbon and glass fiber-reinforced nylon were chosen for this study. Samples were manufactured to perform a variety of tension, shear, and compression mechanical characterization tests on the materials. Half of the samples were conditioned in Pacific Ocean water for approximately 6 months at the Pacific Northwest National Laboratory's Marine and Coastal Research Laboratory before being returned for mechanical characterization. The mechanical testing results showed that the Ultem 9085 and acrylonitrile styrene acrylate materials experienced little to no degradation in stiffness or strength after exposure to the marine environment. On the other hand, the nylon-based materials suffered significant stiffness and strength degradation (over 50% in some cases) after environmental conditioning. Ultimately, these data sets should serve as starting points to allow marine renewable energy developers to make informed additive manufacturing material choices for their prototype deployments.

additive manufacturing↗

DOE OSTI2021

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↗