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At least 235 records · Page 13

Computational Modeling of a 3D Printed Recuperator and Subsequent Experimental Loop for Supercritical Carbon Dioxide Cycles

Oak Ridge National Laboratory (ORNL), in collaboration with mechanical-thermal energy storage (mTES) provider EarthEn, a US Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) recipient at ORNL’s Innovation Crossroads 2023, is utilizing a state-of-the-art patented 3D printing technique to design an additively manufactured (AM) supercritical CO2 (sCO2) recuperator (REC) for EarthEn’s charge/discharge cycle. The AM REC will be printed at ORNL’s Manufacturing Demonstration Facility using Inconel Alloy 718 and tested on a closed-loop, ∼100 kW scale experimental facility that is under construction. The testing will compare the printed design against a commercial-off-the-shelf Printed Circuit Heat Exchanger (PCHE) REC. The design of the sCO2 facility is guided by a Modelica-based system model which is primarily dependent on the open-source TRANSFORM library developed at ORNL and uses the open-source CoolProp library for thermophysical properties of sCO2 via the External Media library. It is envisioned that an iterative process will be followed between the physical loop and the system model wherein the initial experimental data will be used to tune the model, which in turn will be used to guide future loop operation. Simultaneously, the AM REC is being designed using computer-aided design models, and it is also being analyzed for hydraulic and thermomechanical response using commercial computational fluid dynamics software, Simcenter STAR-CCM+, on highperformance computing resources.1

See, Nate [ORNL] (ORCID:0000000178581202)↗

Additive Manufacturing of Lattice Structures for Catalyst Applications

Abstract The design and fabrication of Inconel 718 open-pore lattice structures via Laser Powder Bed Fusion (LPBF) has been investigated in this research, focusing on applications such as catalyst supports in jet fuel production. The study explores the impact of laser power and scanning speed on the geometrical resolution of these structures aiming to achieve high porosity (porosity > 60%) and specific pore sizes ranging from 500–1000 μm, intending to serve as catalyst supports, replacing conventionally manufactured foams to reduce costs. Results demonstrate the significant influence of processing parameters on the geometrical aspects of printed lattice structures, with laser power having a more pronounced effect on geometrical accuracy than scanning speed. Additionally, the mechanical properties of the printed lattice structures showed a correlation with the lattice strut sizes, as lattices with less porosity and thicker struts resulted in higher maximum shear stress.

36 MATERIALS SCIENCE↗

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗

Modelling of cracking during beam oscillation laser welding of a creep-resistant nickel alloy

During high power laser welding of Inconel 740H, horizontal solidification cracks form at locations between approximately 70–80% of the weld depth. With the integration of circular beam oscillation, the laser energy density distribution and underlying thermo-mechanical conditions were altered. By coupling three-dimensional heat transfer, fluid flow, and stress modelling tools, the role that circular beam oscillation plays in the formation of the strain rates and stresses driving this cracking phenomenon was identified. While the addition of a circular oscillation pattern appeared to lower the stress levels along the solidification front, it did not eliminate the appearance of horizontal cracking. Only when the beam amplitudes reached 1.6 mm did solidification cracking disappear, but the weld depths were also significantly reduced.

Gao, Mingze↗

Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition

This dataset is comprised of in situ sensing data collected during laser-based, blown powder directed energy deposition (DED) of Inconel 718 representing eight different printing conditions: (1) nominal, (2) +15% scan speed, (3) +12% laser power, (4) +42% powder feed rate, (5) +100% jerk limit, (6) +10% layer height, (7) +20% hatch spacing, (8) +20% carrier gas flow. All eight DED builds constructed an identical test coupon geometry consisting of geometric features representative of industrial print requirements (e.g., bulk deposition, thin walls, overhangs). In situ data consists of xyz-coordinates (100 Hz) and on-axis melt pool camera video (60 Hz), both of which have been temporally synchronized to spatially map the melt pool camera data. In addition, post-build X-ray computed tomography (XCT) data for each of the eight test geometries have been spatially registered to the recorded xyz-coordinates, allowing for comparisons between melt pool camera data and flaws identified in the XCT data.

additive manufacturing↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, DMREF, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR).

36 MATERIALS SCIENCE↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗

A Co-Registered In-Situ and Ex-Situ Dataset from an Electron Beam Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-09)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Arcam Q10 Electron Beam Powder Bed Fusion (EB-PBF) Inconel 738 build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise Near Infrared (NIR) in-situ imaging data, in-situ temporal sensor data, ex-situ X-Ray Computed Tomography (X-CT) scans, and the target part geometries. Additionally, anomaly detections produced by a trained Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

Thermomechanical Modeling and Analysis of a High-Temperature Light Trapping Planar Cavity Receiver

Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.

concentrating solar power↗

Northstar Mo100 Target Beam Spot Size Sensitivity Study

Northstar Mo100 target for production of the medical isotope Mo99 is particularly sensitive to beam over focusing because of the intended high power density. At 38 MeV and 6.32 mA (240 kW beam power, nominally 160 kW th in the target), small deviation from the nominal 12 mm FWHM beam can significantly increase the target disk temperatures and more importantly the load bearing target window temperature. A rhodotron will be the source of the electron beam to be used in the isotope production. This machine operates in a pulsed beam mode, currently expected to be at 50 Hz, which results in a 100 C temperature oscillation above and below the steady state temperature that is the focus of this study. This must be considered in the determination of minimum beam spot size that can be accepted by the target without risk of failure. In addition to the nominal beam spot size of 12 mm, the analysis of 10, 11 and 14.5 mm beam spot sizes are analyzed. The primary conclusion is that an over focused beam to just 11 mm FWHM is the minimum beam spot allowable, based on window temperature and the Ultimate Tensile Stress (UTS) of the window material Inconel 718 as a function of temperature. In contrast an under focused beam of 14.5 mm FWHM has much reduced target and window temperatures, but there is a resulting 6% drop in isotope production, all other factor staying the same. These results are presented herein.

07 ISOTOPE AND RADIATION SOURCES↗

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

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. Quality control (QC) requires nondestructive evaluation (NDE) of actual AM structures. Pulsed thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, detection sensitivity of this method 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. The ML methods with higher accuracy require longer run time. However, this runtime is sufficiently short to perform QC within a realistic time frame.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High Temperature Erosion Modeling in Particle Based CSP Systems

1. Introduction. Wear and erosion damage of materials from solid particle and surface interactions is a major issue in various industries. Although more common in mining and oil and gas production, erosion is becoming a critical issue in renewable technologies as well such as particle based concentrated solar thermal power (CSP) systems. In particle based CSP systems, solid particles are used to absorb solar energy and as thermal storage. However, these particles may cause significant amount of wear to system components while through the system at high temperatures. This damage can be costly, and therefore, requires a greater understanding of solid particle erosion in CSP systems. Throughout the years, models and tools have been developed to predict and control erosion in industries such as oil and gas production. However, these erosion models and erosion prediction tools have been mainly developed based on erosion data for much higher velocities and lower temperatures, i.e. the operating conditions for which the existing models have been built are not pertinent to those expected in CSP system. It is known that erosion depends on many factors such as material properties, erodent particle properties, and particle impact speed and angle. However, the effect of temperature on erosion is not vastly investigated. In this work, a temperature-based correlation is introduced that will be used to modify the existing erosion models to predict erosion rates at velocities and temperatures relevant to Gen3 CSP systems. The existing models are first validated against erosion experiments run at low temperatures and low velocities. Subsequently, a temperature correction term is developed that can extend the existing models to high temperatures, based on the available experimental data showing the effect of temperature on impact erosion. 2. Erosion Models. Continuing sequence of impacts from solid particles on surfaces would result in loss of material due to mechanical interaction between solid surface and particles. Erosion equations have been developed to predict erosion under different conditions and erosion mechanism, including cutting and deformation erosion. These models are mainly either mechanistic, empirical, and semi-mechanistic models, when the latter combine the theory of the erosion mechanism and particle motion with the available experimental data. One of the first empirical correlation was introduced by American Petroleum Institute (API) Recommended Practice (RP) 14E [1]. This correlation was very conservative, and several improved empirical and semi-mechanistic equations were developed in the years following. More recently, the models introduced by Erosion/Corrosion Research Center (E/CRC) at the University of Tulsa and Arabnejad. et al. [2] are frequently used in the literature and industry, as they account for many parameters affecting erosion including particle impact speed and angle, material density and hardness, and particle size and shape. However, both these models were developed based on data at relatively high velocities and also do not take into account any mechanical changes in material associated with thermal cycling at high temperatures. 3. Erosion Prediction at High Temperatures. In this work, the accuracy of Arabnejad et al. model and E/CRC model is investigated to predict impact erosion at conditions relevant to Gen3 CSP systems. Two significant deviations expected in Gen3 systems compared to operating conditions used to build these models are particle impact velocities and system temperature. As a first step, the performance of these models was validated at low velocities and temperatures. Impact erosion experiments were conducted on SS316 coupons using HSP 40/70 ceramic particles. Assuming particle rate of 1 kg/s/m, 0.0254 m of particle curtain thickness, and particle velocity of 1.5 m/s in the system, an overall erosion of 0.59 mm/year was calculated. The experimental results were subsequently compared to those from computational simulations and erosion of 0.47 mm/year was obtained using the Arabnejad et al. model. The results indicated that the models work well at low velocities and low temperature conditions. To account for temperature effect, a mathematical correlation was developed using data published by DUCOM [3] for Inconel 600 eroded by alumina particles at high velocities. The correlation was applied to both Arabnejad et. al model and the E/CRC model. The prediction results from these modified models were within 20% of this experimental data. Predictions of of erosion by the modified E/CRC model at three different temperatures are made. Similar to the calculation at low temperature, a typical CSP system with 1 kg/s/m of particle flow rate per unit length of the particle curtain and a curtain thickness of 0.0254 m is assumed. The annual thickness loss calculations were run for different particle impact velocities, assuming a uniform particle impact area equal to the cross-sectional area of the curtain (particle-particle interactions and dispersion of particles are not considered in obtaining the results). It is observed that erosion increases exponentially as temperature increases. Furthermore, it is also noted that, erosion changes non-linearly with impact velocity. Currently, experiments are also being conducted to measure erosion of SS316 at 800 ºC with HSP 40/70 particles at low impact velocities. We expect to use the results from high temperature testing to further improve the temperature correlation function. Similar models are also being developed for abrasion erosion resulting from particle sliding along the surfaces as well as attrition from particle to particle and particle to surface interactions. References. [1] Institute, A. P. (1991). API Recommended Practice for Design and Installation of Offshore Production Platform Piping System, API RP 14E. [2] Arabnejad, H., Mansouri, A., Shirazi, S. A., and McLaury, B. S. (2015a). Development of mechanistic erosion equation for solid particles. Wear, 332–333, 1044–1050. http://doi.org/10.1016/j.wear.2015.01.031. [3] https://ducom.com/high-temperature-erosion-evaluating-sample-wear/

14 SOLAR ENERGY↗

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Abrasion wear at high temperature in particle receiver type Concentrating Solar Power Systems

The use of solid particles as a heat transfer fluid in receivers for concentrating solar powerplants has garnered much attention in the past decade. Particles are not only stable at temperatures above 700 °C but are also able to absorb solar energy directly, which gives them a distinct advantage over conventional molten salts. The use of particles can, however, cause material degradation from the flow of hot or cold particles through discharge hoppers or along the inner receiver surfaces and other system components (e.g. tubes, valves etc.), depending on operating mode of the receiver. Stainless steel alloy 316, nickel-based alloy Inconel® 740H®, Haynes 230, and a 60% alumina, low-cement refractory castable from Allied Mineral Products were tested for wear from first-of-a-kind high-temperature low-velocity abrasion-erosion experiments. The tests are designed to simulate potential conditions in Generation 3 falling particle Concentrating Solar Power (CSP) systems. Simultaneous experiments were conducted at room temperature as well to draw comparison on the role of temperature on abrasion wear rates. It was noted that the abrasion wear rate in candidate materials was driven by the oxidation resistance of the material. The findings from these experiments will be used to determine life-time of critical components in particle receiver concentrated solar powerplants.

14 SOLAR ENERGY↗

Vadose and Saturated Zone Flow and Transport Calculations for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington

The purpose of the fate and transport modeling described in this environmental calculation file (ECF) is to evaluate the impacts to groundwater associated with waste disposal operations at Mixed Waste Low-Level Burial Ground (LLBG) Trenches 31 and 34 to satisfy requirements in DOE O 435.1, Radioactive Waste Management. The model integrates the flow and transport in the vadose zone beneath the active trenches with the saturated zone downgradient of the trenches to predict the radionuclide concentration at the point of assessment (POA). DOE M 435.1-1, Radioactive Waste Management Manual, defines the POA as the point of highest projected dose or concentration beyond a 100 m (328 ft) buffer zone surrounding the disposed waste. The modeling is conducted in accordance with the DOE G 435.1, Implementation Guide for Use with DOE M 435.1-1, performance assessment (PA) guidelines. The modeling involves evaluation of the groundwater concentrations and radionuclide arrival times during the 1,000-year compliance and 10,000-year sensitivity-uncertainty periods per DOE O 435.1 and DOE M 435.1. This analysis does not consider radionuclide release during facility operations, only the post-closure impacts of the radionuclides to the environment. The evaluation of potential radiological dose to groundwater receptors caused by releases from a closed facility containing radioactive waste typically includes the following: (1) Release of radionuclides from that facility (2) Transport of those radionuclides through the environment, and (3) Exposure to humans to environmental concentration levels of those radionuclides The fate and transport three-dimensional (3D) model analysis involves the post-closure impacts to the environment of the technetium-99, iodone-129, and uranium (all isotopes in the waste). The residual inventory estimates include several radionuclides, but technetium-99 is typically responsible for almost all of the beta-gamma dose equivalent associated with groundwater (water resources) protection per 40 CFR 141, “National Primary Drinking Water Regulations” (e.g., see the results in WCH-520, Performance Assessment of Environmental Restoration Disposal Facility, Hanford Site, Washington; hereinafter referred to as the ERDF PA), and iodone-129 can also be a significant dose contributor for some waste (e.g., RPP-RPT-59958, Performance Assessment for the Integrated Disposal Facility, Hanford Site, Washington; hereinafter referred to as the IDF PA). Uranium does not typically factor significantly into the impacts to groundwater, even during the 10,000-year sensitivity-uncertainty period, but always remains of interest as a contaminant. This ECF does not address vadose and saturated zone modeling for Trench 94 of the 200 East Area LLBG. Current information confirms the validity of the low corrosion rate of the naval reactor plant carbon steel (HY-80), and the even lower corrosion rate of the nickel-iron-chromium alloy reactor vessel (Inconel Alloy 600) presented in DOE/EIS-0259, Final Environmental Impact Statement on the Disposal of Decommissioned, Defueled Cruiser, Ohio Class, and Los Angeles Class Naval Reactor Plants. Based on these low corrosion rates, the time to breach the reactor vessel to allow release of radionuclides from the activated metal of the reactor vessel internal structure is at least 10,000 years. This time to breach precludes the need to evaluate the vadose and saturated zone transport of contaminants released from the reactor compartment disposal packages in the 200 East Area LLBGs PA (CP-63826, Waste Release Model Package Report for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of Repair Techniques for Cast Iron Engine Blocks by Additive Manufacturing

ORNL partnered with Cummins Inc to demonstrate the feasibility of using additive manufacturing techniques to deposit large volume of new material on cast iron in the context of remanufacturing. Remanufacturing at Cummins Inc is carried out to repair any field damage and, in some cases, provide additional value by adding new features. Large volume deposition on difficult to weld materials is a challenging problem due to involved metallurgy. Phase-1 of this work evaluated the feasibility of using laser directed energy deposition technique to deposit new material layer by layer on cast iron engine blocks. During phase-1 deposits were made using Inconel-718, Nickel, Nr-Cr-B braze filler. Leveraging the knowledge gained during Phase-1, Phase-2 focused on developing a low- cost crack resistant ferrous alloy to repair cast iron via volume deposition techniques without preheating. Three different alloy chemistries were identified, and trials were performed on cast iron substrates to identify the optimal chemistry that provided adequate resistance to cracking in both, the deposits as well as the cast iron substrate.

42 ENGINEERING↗

Milestone Report: Effect of High Temperature CO 2 on Haynes 230 Alloy

The supercritical carbon dioxide (sCO 2 ) Brayton cycle is a promising candidate for future nuclear reactors due to its ability to improve power cycle energy conversion efficiency. The sCO 2 Brayton cycle can operate with an efficiency of 45-50% at operating temperatures of 550-700 C. One of the greatest hurdles currently faced by sCO 2 Brayton cycles is the extreme corrosivity of sCO 2 . This affects the longevity of the power cycle and thus the levelized cost of electricity. Past studies have shown that sCO 2 corrosion occurs through the formation of metal carbonates, oxide layers, and carburization, and alloys with Cr, Mo and Ni generally exhibit less corrosion. While stainless steels may offer sufficient corrosion resistance at the lower range of temperatures seen by the sCO 2 Brayton cycles, more expensive alloys such as Inconel and Haynes are typically needed for the higher temperature regions. This study investigates the effects of corrosion on the Haynes 230 alloy, focusing on changes in the mechanical properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗