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67 records · Page 4

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↗

Report on Properties and Microstructure of 3D Printed Inc-718

The report presents the microstructure and mechanical properties of 3D printed Inconel 718 to assess its potential use as a structural material for the Transformation Challenge Reactor (TCR). The structural components near the outlet of the core will experience significant neutron fluxes and outlet coolant temperatures from the hot standby temperature of 300°C to nearly 550°C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. Strong spatial and chemical heterogeneity was found in as-built (ASB) Inconel 718. Three heat treatments were designed and conducted to simplify the microstructure and determine how each precipitating phase contributed to the overall strength. Baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600°C. Microstructure electron microscopy was performed on ASB Inconel 718 and heat treated to correlate the observed mechanical properties with nanoscale features. Homogenization of the microstructure led to a highly ductile Inconel with lower strength compared with wrought Inconel 718. The tensile properties of additively manufactured 718 using a standard ASTMrecommended heat treatment were consistent with literature and with the ASTM for the properties of this alloy. A higher fraction of the δ phase led to shorter uniform elongation without altering other engineering properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Gear Test Assembly - Experimental Testing and Analysis of Gears and Bearings - FY2026

The Gear Test Assembly (GTA) is an experimental test apparatus built and installed in the Mechanisms and Engineering Test Loop (METL) at Argonne National Laboratory (ANL). While designed to accommodate a variety of components intended for use in advanced compact in-vessel transfer machine, the focus of GTA been the testing of large radial spur gears. The performance of the components used in GTA motivates the choices made in the design, components, and material choices for the forthcoming METL test articles; the Gripper Test Assembly (GrTA), and the Bearing Test Assembly (BTA). To date, GTA has completed nine experimental testing campaigns and achieved over 21 million revolutions under prototypic sodium fast reactor loads and operating conditions. This report provides an overview and results for the two most recent experiments Campaign #8 and Campaign #9. `Campaign #8 was the first campaign to make use of a set of nickel alloy radial spur gears, made from Hastelloy C-22HS, and combined with heat-treated tapered roller bearings. The bearings and torque profile used allowed Campaign #8 to be directly compared with Campaign #1 where Inconel 718 gears were used instead. Campaign #8 attained 1,058,880 shaft revolutions within 23% of the 1,314,855 revolutions achieved in Campaign #1. These results demonstrate that the heat-treated tapered roller bearings show consistent increased lifetimes, approximately three times longer than for non heat-treated taper rollers, and that the particular material of the gear does not play a substantial role in performance. Similar to Campaign #7 where bearing failure resulted in fragmentation and transport of bearing material into the gear teeth led to tooth damage in the Inconel gears, a similar process led to the damage of the Hastelloy gears. Subsequent NDE analysis showed that the damage was only limited to the tooth surface and does not extend into the gear interiors. Based on the NDE reports, the Hastelloy gears can be reconditioned and put back into service for future campaigns as was done for the Inconel gears. Reconditioned Inconel 718 gears damaged in Campaign #7 were returned to service in Campaign #9 and paired with non heat-treated tapered roller bearings. In Campaign #9 a novel set of operating conditions were implemented whereby the gears and bearings were cycled between hot, submerged refueling conditions where fuel handling operations occurred and cold, dry, and inert conditions where the sodium was drained and the vessel was allowed to cool simulating long, ex-vessel storage of the fuel handling machine. A total of eight of these operating cycles were achieved before a bearing failure occurred after the accumulation of 475,692 shaft revolutions were achieved. During Campaign #9, one of the drive motors was damaged and over the course of a 240 day standby period, the entire GTA drive system was upgraded from a 480VAC system to a 240VAC system that provided the opportunity to consolidate wall-space in the METL facility and provide more space for additional test articles being installed in the coming year. The over 475,000 shaft revolutions achieved in Campaign #9 eclipses the previous record for lifetime of non heat-treated tapered roller bearings held by Campaign #3 of 392,000 shaft revolutions. Further analysis and future campaigns hope to shed light on the cause of this approximately 17% increase in lifetime.

42 ENGINEERING↗

Radiation-Induced Defect Formation Kinetics in Inconel–Cu Multimetallic Layered Composites

This study investigates the stability of Inconel–Cu Multimetallic Layered Composites (MMLCs) in nuclear reactor applications using Molecular Dynamics simulations. The focus is on understanding the underlying mechanisms governing the properties of MMLCs for advanced nuclear reactors, specifically, the mechanochemistry of the interface between Inconel and copper alloys. The selection of Inconel–Cu MMLCs is primarily due to copper’s superior thermal conductivity, enhancing heat management within reactors by preventing hotspots and ensuring uniform temperature distribution. This research examines Incoloy 800H and two Inconel variants (718 and 625), assessing their stability at 1000 K after exposure to 10 keV collision cascades up to 0.12 dpa. Notable findings include defect clustering on the {1 2 0} family of planes of Inconel and Cu, with Stacking Faults and Lomer–Cottrell locks on the Inconel side.

Ramesh, Rajesh↗

Characterization of precipitation in gradient Inconel 718 superalloy

Inconel 718 (IN718) superalloy is a well-established material for the application of aircraft engine and power generator due to its excellent performance at high temperatures. The outstanding mechanical properties of IN718 are largely determined by the precipitates. Here, we investigated the precipitation behaviors and the corresponding mechanical properties of the heat-treated gradient IN718 alloy. The microscopy studies reveal that high-density hexagonal η phase with chemistry of Ni 3 (Al,Ti,Nb) formed in the nanograined IN718 alloy after annealing at 700 °C. Additionally, the compressive stress introduced during severe plastic deformation may have prohibited the formation of γ” phase while accelerated the precipitation of γ’ phase, consequently favoring the precipitation of η phase. The corresponding evolution of mechanical behavior of gradient IN718 alloy is investigated.

36 MATERIALS SCIENCE↗

3D Printing of Inconel 718 with Enhanced Boron Composition as a Novel Solar Absorber Tube Material in the Concentrated Solar Power (CSP) System

The growing demands for elevated efficiency in the solar energy industry led researchers to focus on the development of functional solar absorber tube material in concentrated solar power (CSP) systems, when molten salts are adopted as the heat transfer fluid. In this study, the typical solar absorber tube material, Inconel 718, was enhanced with boron to achieve a higher solar absorptivity in the visible light spectrum. Combined with an additive manufacturing (AM) method, the boron composition exceeded the traditional manufacturing limit of 60 ppm without microstructural defects. The boron-enhanced Inconel 718 exhibited a high solar absorptivity of nearly 90 % while maintaining a high thermal cycle fatigue resistance after thermal cycling treatment between 550°C and 720°C. The boron composition was increased to the manufacturing failure point, and the effects of different boron compositions on mechanical properties, microstructure, and optical properties were studied. The provided microstructure-property map in this study delivers high potentials of functional AM-printed alloy material in CSP applications.

13 HYDRO ENERGY↗

Thermal tomography 3D imaging of additively manufactured metallic structures

Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with the laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer and through reconstruction of data obtained from experimental measurements. Thermal tomography reconstructions of structure shape and dimensions are shown for the Inconel 718 AM structure which has variations in the horizontal plane but is uniform along the depth dimension. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and the Inconel 718 plate is produced with the LPBF method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBHs have the same sizes as the imprinted defects in the LPBF specimens but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects and allow for estimation of their sizes and locations. Results of this study demonstrate that thermal tomography can be used for visualization and quality control in AM.

36 MATERIALS SCIENCE↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Accelerated Creep Testing (ACT) Program for Advanced Creep Resistant Alloys for High Temperature Fossil Energy (FE) Applications (Final Report)

The research objective of this study is to develop an accelerated creep testing (ACT) program for advanced creep resistant alloys for high temperature FE applications. This research produced a new ACT for metallic materials based on Time-Temperature-Stress Superposition (TTSSP). In TTSSP, there exists a fundamental relationship between creep resistance, time, temperature, and stress that can be manipulated to reduce test durations. In our study, the stepped isostress method was employed where step increases of load during creep testing accelerated the time-to-rupture. Well-posed constitutive models including sin-hyperbolic and Wilshire-Cano-Stewart where calibrated using the SSM data and employed to predict the conventional creep response of the material. In our best experiments, <100-hour tests on lnconel 718 at 750 deg C produced over a 64x acceleration of data when compared to conventional data from Japan's National Institute of Materials Science. The ACTs enable the rapid screening of candidate materials, where a small test matrix of short duration tests can be employed to determine the creep resistance (minimum-creep-strain-rate, stress-rupture, and creep deformation) of a material across decades.

20 FOSSIL-FUELED POWER PLANTS↗

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗

Application of Refractory High-Entropy Alloys for Higher-Reliability and Higher-Efficiency Brayton Cycles and Advanced Nuclear Reactors

An exceptional set of newly-discovered advanced superalloys known as refractory high-entropy alloys (RHEAs) can provide near-term solutions for wear, erosion, corrosion, high-temperature strength, creep, and radiation issues associated with supercritical carbon dioxide (sCO2) Brayton Cycles and advanced nuclear reactors. In particular, these superalloys can significantly extend their durability, reliability, and thermal efficiency, thereby making them more cost-competitive, safer, and reliable. For this project, it was endeavored to manufacture and test certain RHEAs, to solve technical issues impacting the Brayton Cycle and advanced nuclear reactors. This was achieved by leveraging Sandia’s patents, technical advances, and previous experience working with RHEAs. Herein, three RHEA manufacturing methods were applied: laser engineered net shaping, spark plasma sintering, and spray coating. Two promising RHEAs were selected, HfNbTaZr and MoNbTaVW. To demonstrate their performance, erosion, structural, radiation, and hightemperature experiments were conducted on the RHEAs, stainless steel (SS) 316 L, SS 1020, and Inconel 718 test coupons, as well as bench-top components. The experimental data is presented, analyzed, and confirms the superior performance of the HfNbTaZr and MoNbTaVW RHEAs vs. SS 316 L, SS 1020, and Inconel 718. In addition, to gain more insights for larger-scale RHEA applications, the erosion and structural capabilities for the two RHEAs were simulated and compared with the experimental data. The experimental data confirm the superior performance of the HfNbTaZr and MoNbTaVW RHEAs vs. SS and Inconel. Most importantly, the erosion and the coating material experimental data show that erosion in sCO2 Brayton Cycles can be eliminated completely if RHEAs are used. The experimental suite and validations confirm that HfNbTaZr is suitable for harsh environments that do not include nuclear radiation, while MoNbTaVW is suitable for harsh environments that include radiation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

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↗