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DOE OSTI2020

Structural integrity of additively manufactured stainless steel with cold sprayed barrier coating under combined cyclic loading

Integration of metal additive manufacturing (AM) and cold spray (CS) technologies provide an unprecedented opportunity to manufacture coated material systems with complex geometrical features. The application of these material systems in functionally critical components requires adequate structural integrity, particularly in the presence of cyclic loading. This article researches the multiaxial fatigue (axial-torsional cyclic loading) behavior of a coated material system consisting of 15Cr-5Ni precipitation-hardening stainless steel (15-5 PH SS) substrate additively manufactured by direct metal laser sintering with a layer of chromium carbide nickel (CrC-Ni) barrier coating deposited by CS. The influence of AM and CS-induced residual stresses on fatigue performance of test specimens was thoroughly studied. Additionally, the effect of surface roughness and processes induced defects were considered to explain the crack growth mechanism. Stresses assessed by synchrotron X-ray diffraction indicated a substantial accumulation of residual stresses, particularly in the outer surface of the as-fabricated 155 PH SS specimens. The state of residual stress was changed notably following the deposition of CrC-Ni coating in the axial, hoop, and radial directions of the fatigue test specimen. Also, CS deposition of CrC-Ni coating caused significant improvement in the surface quality of the additively manufactured components. Fatigue test results indicated, CS deposition of CrC-Ni substantially enhances the fatigue life of the AM-produced 15-5 PH SS substrate in all loading conditions, particularly in the high cycle fatigue regime. The improvement in the fatigue life of the specimens with coating was associated with a reduction in equivalent residual stress at the substrate surface and improvement in the specimens' surface condition (i.e., reduced surface roughness). The fractographic analysis of the specimen indicated the cracks tend to initiate in the surface of both as-fabricated and cold-sprayed specimens. However, the mechanism of crack growth changed notably following the deposition of CrC-Ni coating. The cracks tended to propagate in the planes parallel or with a small deviation from the build layers of the AM-produced specimens. On the other hand, deposition of CrC-Ni coating increased the deviation of crack growth plane from the build layers of the substrate.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Co-Pyrolysis of Chicken and Cow Manure

Conventional pyrolysis is a relatively simple way for biochar production; however, a single biomass feedstock approach is not promising for the development of multiple properties of biochar used in various applications. Here, this study provides a detailed comparison in terms of pyrolysis kinetics between the cow manure and chicken manure, in addition to the co-pyrolysis by mixing the two livestock at different ratios. Eight different heating rates were tested, 5–40 °C/min with 5 °C/min step, on both livestock using the nitrogen as a gas agent with a flowrate of 50 ml/min. The initial results show that for the slow heating rates, 5 °C/min, the thermal degradation of the cow manure is different compared to that obtained from chicken manure. For the cow manure, the first peak, associated with hemicellulose decomposition, is higher than the second peak, associated with cellulose decomposition, which is the other way around for chicken manure. At 5 °C /min, the hemicellulose decomposition took place at 250 °C and 300 °C for the chicken manure and cow manure, respectively. The cellulose decomposition was started at 300 °C for chicken manure and 470 °C for cow manure. The lowest heat rate was selected for the co-pyrolysis case study to allow a quasi-equilibrium state to avoid measurement errors and heat transfer limitation in terms of thermal lag. Co-pyrolysis is studied with different blend ratios between the chicken and cow manure, where the 40% cow manure shows a positive result in terms of keeping an exothermic reaction over the co-pyrolysis process.

09 BIOMASS FUELS↗

DOE OSTI2024

Advanced Instrumentation for Metal Additive Manufacturing

Laser powder bed fusion (LPBF) is the most widely used process for metal additive manufacturing (AM), particularly where complex geometries provide performance advantages unattainable with traditional manufacturing techniques. However, LPBF is highly sensitive to innate variability in both the powder spreading and fusion steps, often leading to defects such as pores that are difficult to detect yet significantly impair component mechanical properties and fatigue life. This thesis presents a range of novel instruments enabling both precise assessment of powder layer characteristics and in-situ thermal metrology of metal AM to advance the quality control of LPBF. First, leveraging a custom X-ray microscope and a radiation-transport model developed through this work, transmission X-ray imaging is used to study spreading of thin metal powder layers. Effective layer depth is directly mapped at a process-relevant size scale, surpassing optical techniques that can only estimate local deposition from layer surface topography. Layer packing density and quality are shown to be influenced by powder flowability and particle size relative to nominal powder layer thickness. Layer quality is additionally connected to the geometry of the spreading implement and its velocity. This technique and its presented findings enable pairing feedstocks with spreading strategies that create layers with consistent packing density and uniformity. Second, a twofold approach is employed to optically interrogate the laser fusion step of LPBF for observing signatures of defect formation. Aperture division multiplexing is conceptualized, providing for simultaneous laser delivery and high-fidelity infrared (IR) process monitoring through a common optic. In-situ microscopy at 50 μm spatial resolution and at mid-wave IR wavelengths is proven readily achievable with the first purpose-built optic of this type. Next, a bespoke imaging spectrometer, along with a temperature-emissivity separation technique, is used to retrieve accurate process temperatures over a 1000 K range. Data from these instruments are correlated to porosity as fine as 4.3 μm in two LPBF test artifacts, as verified using computed tomography (CT), establishing the viability of robust optically-based component qualification.

Penny, Ryan↗

DOE OSTI2025

Molten Salt Corrosion Tests of Additively Manufactured Stainless Steel 316H

Molten salt reactors (MSRs) have drawn considerable interest due to their favorable safety features, high thermal efficiency, and compatibility with different fuel cycles. Yet, the success of MSRs hinges critically on the performance of structural materials to be used in these aggressive molten salt environments, where corrosion and material compatibility remain primary challenges to long-term reliability. Additively manufactured (AM) nuclear structural materials prompt the use of novel geometries and compositions to enhance material performance and reduce costs of constructing MSRs. The rapid solidification conditions inherent to AM processing impart distinctive microstructural features, including cellular sub-structures, dislocation densities, residual stress, and oxide inclusions, which can influence material performance in MSR components. While the mechanical properties of AM stainless steels have been widely studied, their corrosion behavior, particularly in molten salt environments, has received far less attention. Addressing these needs, the Advanced Materials and Manufacturing Technologies (AMMT) program provides a framework for systematically evaluating how unique microstructures produced by AM processes influence the performance of these materials in these demanding environments and for developing reproducible testing workflows that can support future code qualification efforts and standards development. Bridging this knowledge gap is essential for assessing the viability of AM alloys in MSRs and informing qualification strategies. A further challenge is the absence of standardized protocols for molten salt corrosion testing. Accordingly, this report provides an account of the corrosion evaluation of AM 316H stainless steel in NaCl 2 -MgCl 2 molten salt at 550 °C, with exposure times of 100 and 500 hours. It documents the experimental procedures implemented under the AMMT program, including salt preparation, exposure protocols, and post-test characterization methods, to establish reproducibility and transparency. Importantly, the study examines AM 316H samples in the as-fabricated condition, directly reflecting the surface state most relevant to engineering applications, and compares their behavior to machine-cut surfaces. Overall, preliminary evaluations have noted that surface conditions (e.g. morphology, contamination, etc.) have a noticeable impact on the corrosion resiliency. The impact of the corrosion is difficult to detect at 100h, unless, in the case of AM 316H, the specimen surface is decontaminated. After 500 h, as-fabricated surfaces of AM and wrought 316H display evidence of general versus preferential corrosion attack, respectively. Both AM and wrought 316H machine-cut surfaces exhibit a continuous Cr depletion zone, evident of general corrosion. While the estimated extent of corrosion appears within the same order of magnitude regardless of the surface condition, it is apparent that more predictable behavior is observed on machine-cut surfaces. Nonetheless, further investigation is necessary to fully elucidate the corrosion mechanism under these conditions.

36 - MATERIALS SCIENCE↗

DOE OSTI2020

Evaluation of Techniques for Vegetation Removal from UAV-Based Photogrammetric DSM near WIPP Land Withdrawal Act Boundary, NM

The Waste Isolation Pilot Plant is located within New Mexico's karst landscape and is the United States' only deep geologic radioactive waste repository which isolates transuranic waste from defense activities underground in a bedded salt formation. Characteristic karst topography in this region is made up of material (such as limestone) that can be dissolved by water over a long period of time, and includes features such as springs, surface streams, sinking streams, caves, and sinkholes. Karst features can potentially impact the integrity of the waste repository in the future and compromise WIPP's performance, particularly when coupled with incompatible land-use activities within the Land Withdrawal Act (LWA) boundary as well as increased water withdrawals outside the LWA. In order to better capture the ground surface topography to support hydrology modeling efforts, the U.S. DOE has enlisted FIU to develop a high-resolution digital elevation model (DEM). In a previous field study, a high-resolution digital surface model (DSM) of an adjacent representative site, Basin 6, was developed by photogrammetry using aerial images captured with unmanned aerial vehicles. The DSM generated was based on point clouds representing the entire landscapes, including points of terrain, vegetation and infrastructure. These above-ground features need to be removed to create a DSM/DEM with good representation of the bare ground. In recent years, many techniques including both pre- and post-processing of DSMs, were developed for vegetation removal with varied success. This research focuses on applying and comparing various vegetation removal methods using point clouds generated of the Basin 6 pilot study area. The 3D RGB-based point cloud classification using Python scripts was a modification of the procedure by Themistocleous (2019). The method using Liblas classifies the point cloud three-dimensionally, whereas the method by Themistocleous (2019) is two-dimensional. The preliminary result of the method using Liblas, however, still had a large amount of vegetation remaining compared to the Pix4D Machine Learning method. The vegetation layer remains highly visible in the DEMs processed using the vegetation indices as opposed to the Pix4D Machine Learning method, which produces a DEM where mostly bare ground is seen. Further modifications to the input parameters are required to improve the vegetation vs. bare ground classification using this approach. The next step will be to improve the method using Liblas and to also test other vegetation removal methods found in the literature review to compare them against the two described here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Determining the Effects of Neutron Irradiation on the Structural Integrity of Additively Manufactured Heat Exchangers for Very Small Modular Reactor Applications, DOE Final Report (Project # 19-16980)

Auburn University (AU) teamed with the University of Missouri Research Reactor (MURR) and Kansas State University (KSU) to determine how to best use laser-powder bed fusion (L-PBF) additive manufacturing (AM) methods for generating radiation resistant nickel-based superalloys, Inconel alloy 625 and 718, for special purpose reactor (SPR) or very small modular reactor (vSMR) heat-exchangers (HeXs). Compact, conformal, and durable HeXs that are tolerant of extreme environments are needed for supporting the technical maturity of next-generation, portable compact reactors. AM is an enabler for realizing this new wave of HeXs – providing a means to make customizable hot and cold stream architectures with novel flow path geometries (e.g., tortuous channels with non-uniform, asymmetric cross-sections) and reduced layer-to-layer contact resistance (i.e., no separate bonding procedure required). AM further enables a more time/cost efficient means for fabricating SPRs by reducing the number of suppliers required for HeX assembly and allowing for on-site HeX fabrication. The project aim has been to better understand how neutron irradiation affects the microstructure and properties of additively manufactured nickel-based superalloys, to accelerate their safe, reliable use in the modular reactor industry. The major objective was to qualify/quantify the microstructure and microhardness of nickel-based superalloys (including Inconel 718 and 625) additively manufactured via the L-PBF process in the neutron-dosed (irradiated) and non-irradiated states over a course of 3 years. Effects of build orientation during L-PBF and post-AM heat treatments on neutron resistance, microstructure and mechanical properties were also investigated. Neutron damage mechanisms via hardening were characterized. This project combined subject-matter experts in AM, mechanical/microstructure metallic part characterization, and neutron irradiation, as well as unique assets and capabilities at AU and MURR at MU, to ensure project results translated to effectively addressing known gaps in nuclear science and engineering. Parts were fabricated using L-PBF systems readily available at AU. Specimens were then irradiated using MURR facilities; a manipulator equipped hot cell was also used to measure material hardness after dosing. MURR, a 10 MW, light-water nuclear reactor, is the largest, highest powered, highest-flux university owned research reactor in the U.S. The major findings in this project provide evidence that AM can serve as an alternative way to build structural components for future advanced small modular reactors using advanced materials like Inconel 625 (IN625) or Inconel 718 (IN718). After full spectrum neutron irradiation, vertically as-built AM IN625 samples were observed to display better resistance towards radiation-induced-hardening defects relative to traditionally machined metals. A Vickers microhardness tester, using settings of 1 kgf and dwell time of 15 seconds per indentation, was used to measure hardness in this study. The as-built, vertically printed samples experienced 1.2% of radiation hardening vs. 5.25% radiation hardening observed in wrought IN625. Another set of IN625 and IN718 samples were exposed to fast neutron irradiation. It was observed that IN718 showed more resistance towards radiation hardening compared to IN625 samples indicating IN718 had a better performance. Results showed that the IN718 samples experienced less change (-2.5 to 3.24 %) in microhardness. On the other hand, IN625 samples underwent more (0.9 to 7.21%) change in microhardness after fast neutron irradiation. AM IN625 samples were irradiated using an ion (proton) beam in cyclotron. The mechanical properties of AM samples post irradiation were compared with wrought samples. The irradiated region on the samples were tested using nano-hardness indention. It was observed that the beam current and time used in this study generated an annealing effect and thus reduced the hardness of the samples. The sum of the project results provide precious insight into how one may minimize radiation hardening in AM materials while maintaining material property constraints. Results should assist engineers in selecting an appropriate heat treatment for AM nickel-based superalloys for increased radiation resistance. Results should increase confidence levels for adopting AM for building nuclear reactor components which perform the same or better than conventionally manufactured components. Fast neutron irradiation testing provided an accelerated means of obtaining radiation effects without making materials radioactive and difficult to handle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗