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Adsorption of Iodine on Metal Coupons in Humid and Dry Environments

In this study, five different metal coupons were evaluated for gaseous iodine [I2(g)] adsorption including two stainless steels (i.e., SS304 and SS316), two Inconel® alloys (i.e., 625 and 718) and pure Ni (i.e., Ni-200) within a dynamic flow-through system where temperature, iodine concentration, flow rate, atmosphere, and relative humidity were controlled. Humidity was shown to be critical to iodine adsorption on SS304 and SS316 and Ni-200 at ambient temperatures. The results presented herein suggest that a moisture mediated reaction is occurring. However, higher humidity levels decrease the adsorption, suggesting an ideal range of humidity for highest corrosion. A comparison of the five metal substrates showed the highest I2(g) adsorption in the following descending order Ni-200 > SS304 > SS316 >718>625.The 625 and 718 Inconel alloys were fairly inert to iodine adsorption under the conditions tested. Characterization by scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction of the Ni-200 coupon indicates that NiI2 is formed and flakes off the surface as a black powder. The SS304 and SS316 coupons showed evidence of extensive reactions with I2(g) and formed a much more deliquescent corrosion product, which reacted with air when removed from the flow-through system for weighing on the analytical balance. These findings assist in predicting iodine adsorption behavior on a variety of metal surfaces under various conditions.

Beck, Chelsie L.↗

Effect of free surfaces on localized plastic deformation in single-crystal nickel containing helium bubbles and radiation-induced self-interstitial atom clusters

This paper presents molecular dynamics (MD) simulations of plastic deformation in single-crystal Ni models containing internal distributions of helium (He) bubbles and self-interstitial atom (SIA) clusters corresponding to experimental characterization of ex-service Inconel X-750 components. Here, we simulate single crystals with and without free surfaces at room temperature and 588K, the latter temperature corresponding to the Inconel X-750 service conditions. Both models are deformed under multiple slip to a maximum deviatoric strain of ~10 %. A dislocation slip band forms in the model without free surfaces, but not in the model with free surfaces. However, the latter exhibits nano-twin nucleation from surfaces. Helium (He) bubbles that overlap with a slip band or a nano-twinned region deform more severely than other bubbles in the model. Nevertheless, the bubbles do not link up and do not form configurations that resemble incipient cracks.

36 MATERIALS SCIENCE↗

Corrosion susceptibility and chromium loss in Austenitic steels and Nickel-based alloys in molten FLiNaK at 700 °C

A comparative study was conducted to evaluate the corrosion susceptibility of 316L, 316H, Ni 200, Inconel 625, and Hastelloy N in molten FLiNaK at 700 °C for 100 h. Top-view and cross-sectional scanning electron microscopy (SEM) imaging, combined with energy-dispersive X-ray spectroscopy (EDS) mapping, was performed to investigate microstructural and compositional changes. SEM images were further processed by introducing a contrast threshold to map cavity distribution. Using EDS mapping, intergranular and intragranular Cr loss were separately characterized. The ranking of mass loss after corrosion, from highest to lowest, is as follows: 316H > 316L > Inconel 625 > Hastelloy N > Ni 200. Cr loss was found to be correlated with Mo concentration, in agreement with many previous studies, with higher Mo content resulting in reduced Cr loss. On the other hand, there is no evidence that the high carbon content in 316H enhances corrosion resistance. The relatively low solubility of carbon in austenite at the testing temperature limits the amount of dissolved carbon. Therefore, the carbon-retarded vacancy diffusion, and consequently the reduced Cr diffusion, were not observed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗

Effect of temperature on abrasion erosion in particle based concentrating solar powerplants

The use of solid particles as a heat transfer medium is being explored for concentrated solar power plants (CSP) to increase their efficiency by achieving operating temperature >700 °C. During operation, these hot particles are expected to move along the various components within the collector system, resulting in material degradation from a combination of high-temperature oxidation and erosion. In the present study, the performance of candidate materials was evaluated through a series of abrasion erosion experiments at room temperature as well as at 800 °C. Wear in metallic and refractory type materials was investigated using CarboBead® HSP 40/70 particles inside a resistance heated kiln. Furthermore, cross-sectional scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) analysis on the specimens tested at 800 °C determined that the specific wear rate in Inconel 740H and stainless steel 316 metallic specimens was influenced by the thermally grown oxide morphology. High chromium Inconel 740H specimens exhibited greater resistance to wear with a steady state specific wear rate of 1.92E-4 mm 3 N -1 m –1 compared to 5.7E-3 mm 3 N -1 m –1 for Stainless Steel 316.

14 SOLAR 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↗

Precipitate growth kinetics under inhomogeneous concentration fields using a phase-field model

We investigate precipitation dynamics in the presence of a local solute gradient using phase-field simulations. During the homogenization heat treatment of the solidified Inconel 718 alloy, high Nb concentration within the Laves phases or at the core of the secondary arms results in Nb diffusion into the γ matrix. The volume fraction and spatial distribution of precipitation during subsequent annealing can be controlled by tailoring the Nb concentration gradient in the matrix during homogenization. We use a surrogate Ni-Fe-Nb alloy for Inconel 718 to explore the growth dynamics of δ precipitates related to the local Nb concentration levels. The simulations indicate that in the presence of a Nb concentration gradient the growth rate of δ precipitates is higher than in a matrix of uniform average Nb concentration. The higher growth rate is a result of the higher local thermodynamic driving force at the interface between the solute-rich matrix and the δ interface. Here, we propose a phenomenological model to describe the diffusion-controlled growth kinetics of the δ phase under a solute concentration gradient.

36 MATERIALS SCIENCE↗

A Digital Twin Approach to Study Additive Manufacturing Processing Using Embedded Optical Fiber Sensors and Numerical Modeling

One of the major challenges for metal-powder-based additive manufacturing is measuring and mitigating residual strain induced during the manufacturing processes. This article reports distributed fiber optic sensors embedded in Inconel alloy components as experimental means to validate numerical models of additive manufacturing process. Electroplating was used to deposit a metal protective jacket onto standard telecom single-mode fibers for strain measurements, Fiber sensors were embedded in an Inconel alloy substrate using the laser engineered net shaping (LENS) process. Here by using a Rayleigh-scattering optical frequency domain reflectometer (OFDR), temperature changes, and residual strain in the metal substrate were monitored with 5 mm spatial resolution during the LENS process. Using finite element analysis, temperature and strain profiles induced by the LENS deposition processes were also numerically studied. Discrepancies between the simulated temperature and strain profiles and those measured directly were less than 10%. Results presented in this article demonstrates a digital twin approach to fuse modeling results with distributed fiber sensor measurement data to study additive manufacturing process toward design and fabrication process optimization.

36 MATERIALS SCIENCE↗

An Analytical Solution for the Initiation and Early Progression of Fretting Wear in Spherical Contacts

Abstract This article derives analytical solutions to calculate the wear volume at the initiation of fretting motion and its early progression over the first few oscillation cycles. The Archard-based model considers a deformable hemisphere that is contact with a deformable flat block. The material pairs investigated are special alloys, the Inconel 617/Incoloy 800H, and Inconel 617/Inconel 617. The analytical study begins with a unidirectional frictional sliding contact, where the local interfacial sliding distance and the nominal sliding distance at the initiation of gross slip are derived. The obtained analytical expressions for unidirectional sliding are then used to derive the corresponding wear volume for the initiation and early progression of gross slip and the wear volume for a general fretting cycle under elastic conditions. These analytical derivations are all verified by the finite element analysis (FEA). The FEA method and the analytical solutions render virtually identical results for both similar and dissimilar material pairs. The effects of plasticity on the wear volume under elastic–plastic conditions are also investigated. It is found that the fretting wear volumes obtained from the FEA simulations, which include plasticity, are close to those obtained from the analytical expressions for purely elastic regimes. All the results are presented in normalized forms, which can be easily generalized and applied to three-dimensional fretting wear of other material pairs.

Engineering↗

Numerical Study of Solar Receiver Tube With Modified Surface Roughness for Enhanced and Selective Absorptivity in Concentrated Solar Power Tower

Abstract Concentrated solar power (CSP) is a reliable renewable energy source that is progressively lowering its cost of energy. However, the heat loss due to reflected and emitted radiation hinders the maximum achievable thermal efficiency for solar receiver tubes on the solar tower. Current solar selective coatings cannot withstand the high temperatures that come with state-of-the-art CSP towers often needing to be recoated soon after initial operation. We intend to use Inconel 718 with different additive manufacturing (AM) practices to construct surfaces that allow for more light-trapping to occur. By adjusting printing parameters, we can tailor a surface to allow for more absorption while diminishing emitted radiation heat loss. By using COMSOL Multiphysics, we can generate these theoretical surfaces to emulate a printed surface, and using the coupled Multiphysics we can simulate how the surface dictates radiation properties. Our results show that by having a rougher surface we can enhance the absorptivity of Inconel 718 (IN718) by 38.8%. We expect this work to transform how solar absorber tubes are manufactured without using selective coatings and supplement the US Department of Energy (DOE) 2030 SunShot Initiative.

14 SOLAR ENERGY↗

Challenges and Optimization of Mu2e Proton Target Design with Radiative Cooling

Mu2e, the Muon-to-Electron Conversion Experiment, aims to identify physics beyond the Standard Model, namely, the conversion of muons to electrons without the emission of neutrinos. The muons are produced from pions generated in a production target when it is hit by an 8 GeV proton beam from the Fermilab Booster/Main Injector. The proton target design space is strongly constrained by a one-year operating lifetime and the need for radiative cooling in a vacuum environment. Uncertainties in the lifetime of the existing baseline design – a monolithic, segmented tungsten target – are large, particularly due to unknown impacts of radiation damage at the very high proton fluences expected in the experiment. We have begun evaluation of a new design utilizing Inconel 718 over the WL10 used in the existing target design. As a result, the structural design of the target has evolved significantly. This evolution focuses on lowering the target temperature, minimizing obstruction to muons, increasing structural stability, maximizing fatigue lifetime, simplifying the fabrication process, and more. The thermal management, structural stability and fatigue lifetime are emphasized here. These optimizations have led to a promising new target design for the Mu2e experiment.

Liu, Z. [Fermilab]↗

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↗

EXPERIMENTAL INVESTIGATION OF IMPACT AND ABRASION EROSIONS AT LOW VELOCITIES AND COMPARISON TO CFD SIMULATIONS

Wear and erosion damage of materials due to interaction of the surface with solid particles is a major issue in various industries. This phenomenon is common in mining, and oil and gas production, causing damages worth millions of dollars annually. Erosion is becoming a critical issue in renewable technologies as well such as concentrated solar thermal power (CSP) systems. In some CSP systems, solid particles can be used to absorb solar energy and enhance the heat storage. However, these particles may cause significant amount of wear to system components while falling down the power tower at high temperatures. This damage can be costly, and therefore, investigating solid particle erosion in CSP systems is of utmost importance. In collaboration with Sandia National Laboratories, the erosion durability of particle-based Generation 3 (GEN3) CSP system are being investigated both experimentally and numerically. In order to develop models to predict the life time of such systems, erosion under low temperature and low particle impact velocity conditions are investigated. Impact erosion and abrasion erosion experiments are conducted for low velocity and low temperature conditions for various candidate particles and containment materials. The impact erosion testing is conducted for three different containment material including Stainless Steel 316, special refractory material, and Inconel 740H with CARBOBEAD HSP 40/70 ceramic particles and UNIWEST 430 silica quartz erodent particles. All this data will enable us to better model the erosion behavior of these materials and provides a data base to investigate erosion at high temperatures experienced in CSP systems. At low temperatures and low velocities the softer refractory material exhibited greater erosion by an order-of-magnitude when compared to the harder Inconel 740H and Stainless Steel 316 materials. The overall erosion ratio for all the candidate materials was of the order of 10 -7 kg/kg. We also investigated wear in containment materials from sliding of particles over the surfaces at very low angles, also referred to as abrasion. For the velocities expected in a typical 1MW CSP plant, visible surface wear was noted, but the overall mass loss per unit surface area was found to be dependent on the hardness of the containment material tested. In this manuscript, we also present Computational Fluid Dynamics (CFD) simulations and erosion prediction of low velocity impact erosion. These results are compared with the experimental data to evaluate the ability of available erosion models for predicting erosion under these conditions.

14 SOLAR ENERGY↗

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↗

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↗

Vitrification of High-Cr Glass in Research-Scale Melter

This test report describes the experimental results from a small-scale test using the research-scale melter (RSM) at Pacific Northwest National Laboratory to demonstrate processing of a high-Cr simulated feed stream, designated HLW-HCr-16. The RSM is a small, joule-heated melter capable of processing melter feed continuously. The melter is equipped with Inconel ® 693 electrodes, Monofrax ® K-3 refractory, and an Inconel 690 pour spout. An electric kiln surrounds the melter body and minimizes heat loss from the melter body during operation. The RSM is equipped with an offgas treatment system that employs quenching, wet scrubbing, and high-efficiency mist elimination. The glass-discharge section is heated to facilitate pouring of the glass. The melter is fitted with a melt cavity that is ~25 cm (10 in.) in diameter with a nominal glass depth of 8.9 cm (3.5 in.). The melter was operated with a target glass temperature of 1150°C and target plenum temperature between 550°C and 700°C for this test. The air bubbling rate was 4.2 L/min. Overall, during the continuous operation of the melter for ~ 103 hours, ~ 141 kg of glass was produced. At the conclusion of the test, the melter and exhaust lines were visually inspected for particulate deposition and corrosion. Entrained material had adhered to the underside of the melter lid and to the exhaust piping. Enrichments in elements such as Cl, F, B, K, Li, P, Na, and S were measured in these deposits through inductively coupled plasma–optical emission spectroscopy and X-ray fluorescence analysis. When the melter electrodes and air bubbler tube were removed from the glass in the RSM, the electrodes appeared discolored, but no significant loss of metal was observed. The processing of a high-Cr simulant, HLW-HCr-16, in the RSM produced glass at an average rate of 1.36 kg/h, equaling a melter-surface-area normalized glass generation rate of 654 kg/day/m 2 . The resulting glass met the toxicity characteristic leaching procedure requirement. Test results of crystallinity, electrical conductivity, and viscosity showed good processing properties of this high-Cr high-level waste glass. RSM offgas was also sampled and analyzed at periodic intervals during steady-state operating conditions. The total decontamination factor averaged by four sampling periods was 134. The concentrations of CO and NO x in emissions were 237 to 422 and 69 to 94 parts per million by volume, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrated Computational Materials and Mechanical Modeling for Additive Manufacturing of Alloys with Graded Structure Used in Fossil Fuel Power Plants

Wire-arc additive manufacturing (WAAM) has demonstrated its unique capability of producing large-size alloy components with a significantly reduced fabrication time and enhanced geometry design freedom. In this project, the team has developed an ICME (Integrated Computational Materials Engineering) modeling framework, which supports the WAAM of the AUSC (Advanced Ultra-Supercritical) power plant components. The manufacturing design has been applied to Inconel 740H, steel P91, as well as the dissimilar alloy components between steel P91 and Inconel 740H. The ICME model framework is developed by considering two types of modeling. First, mechanistic modeling has been applied to control the printing quality and understand the sequence of the dissimilar printing of the wall structure. The following models have been included in the developed ICME framework: finite element thermal model, grain structure model, residual stress simulation, crystal plasticity model, CALPHAD-based precipitation kinetic model, phase stability prediction, thermal expansion predictive model, and heuristic creep model. Secondary, a physics-based machine learning model has also been developed based on the ICME model structure. The machine learning model development is based on the ICME model prediction with calibration of the experiments. In addition, the WAAM has been utilized as a high-throughput experimental tool rapidly generating a gradient of alloy composition to facilitate experimental database generation for process-structure-property relationships. Such a database directly supported the ICME-enhanced machine learning, which further assisted in intermediate composition block design between P91 and 740H. A high-throughput screening study of the oxidation resistance has been performed based on such high-throughput experimentation. Based on the computational design, several dissimilar alloy manufacturing with post-heat treatment have been performed with a comprehensive evaluation of mechanical performance, including hardness mapping, yield strength, creep resistance. In this project, the single component of P91 and 740H processed by WAAM after heat treatment designed by ICME has demonstrated higher performance in yield strength and creep resistance than the wrought materials. The P91 sample prepared by WAAM with ICME-designed heat treatment performs better than P92 in creep resistance. The designed graded alloy printing with intermediate block shows a promising performance that exceeds the traditional welding. Moreover, the current research indicates the high need for location-specific design analysis with uncertainty quantification, an important topic that deserves more dedicated research. The achievement of this project demonstrated the promising future of WAAM in structural alloy manufacturing for energy power plant development. Successful printing requires synergetic efforts made by manufacturing, mechanical, and materials sciences.

20 FOSSIL-FUELED POWER PLANTS↗

Materials for Advanced Ultra-Supercritical (A-USC) Steam Turbines --- A-USC Component Demonstration

The U.S. Advanced Ultra-Supercritical (A-USC) Consortium was formed in 2001 as a government/industry program, sponsored by the U.S. Department of Energy (DOE) and the Ohio Coal Development Office (OCDO) and cost shared by industrial and not-for-profit partners. The purpose of the consortium was to advance the state of the art for power generation by evaluating and developing materials that allow the use of advanced steam cycles in coal-based power plants. These advanced cycles, with steam temperatures up to 1400°F (760°C), can increase the efficiency of coal-fired boilers from an average of 35% (current U.S. fleet) to more than 45% higher heating value (HHV) (>49% lower heating value [LHV]). The increase in a plant’s efficiency is limited unless new materials able to withstand these higher operating temperatures and pressures are identified and approved for use. The A-USC Consortium identified these needed materials during earlier phases of the program. It developed the welding and joining techniques along with manufacturing processes for casting and wrought products made from these new high-nickel alloys. It subjected these materials to extensive laboratory and steam loop testing. It then obtained ASME code approval for their use in U.S. boiler systems. The program’s successes leave this last remaining activity (ComTest Phase 2) that the U.S. utility industry has recommended to be accomplished prior to commercialization. The focus of the activity is the evaluation and demonstration of commercial readiness for “full scale” components to be made from these nickel-based alloy materials and provided by a U.S. domestic supply chain that is new to working with these alloys. According to studies completed by the Electric Power Research Institute (EPRI), the cost of an A-USC plant is approximately 20% higher than a non-A-USC plant because of its use of nickel-based alloys needed for the high temperature operating conditions. However, CO 2 reductions of approximately 30% from the current fleet average provide a strong incentive for its consideration. The actual costs and perceived value for CO 2 abatement will determine whether new or retrofitted plants are undertaken, although decisions to build A-USC plants in India would indicate its economic feasibility while also being part of a global carbon emissions strategy. The work by the A-USC Consortium, prior to the start of the ComTest project, has included lab scale and pilot scale materials testing, both in air and oxy-combustion. This testing has included air-cooled and steam-cooled “loops” that were installed into existing operating utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion caused by the constituents in the coal ash. The A-USC Consortium also gained ASME Code approval of the Inconel 740 material, has cast and extruded the largest high nickel precipitation hardened alloys, and developed unique welding techniques to avoid problems identified by the competing European program. However, as valuable as these material test loops and accomplishments have been for obtaining information, their scale is below that required to minimize the risk associated for a U.S. utility to build a multibillion-dollar A-USC power plant. To reduce the final identified risk barrier to full-scale commercialization of these advanced materials and systems, the A-USC Consortium (guided by a utility industry advisory committee) has identified the key areas of the technology they desire to see as being capable of full-scale manufacturing and/or fabrication from an identified, capable U.S. domestic supplier base. A significant amount of work was accomplished during Phase 1 to identity the components, as well as the component size, that would be manufactured from advanced alloys such as Inconel 740H or Haynes 282 alloys. Pathways to supply these components for ComTest have been identified, as well as any further development that would be required. The Phase 2 effort used Phase 1 findings for designing these key full-scale components for A-USC boilers and turbines to include large castings; extrusions, forgings, fabrication of water walls and steam loops with headers from advanced materials, raw material (such as pipe extrusion billets) are at the commercial readiness level to permit advancement to a demonstration project. The Phase 2 work scope was addressed by a diverse team, including government, industry, and not-for-profit partners. The work scope under Phase 2 addressed fabrication of components identified as being outside of the proven capabilities of the existing supply chain, including the following: Steam turbine rotor forging and Haynes 282 nozzle carrier casting Superheater and reheater header and tube assemblies Large-diameter pipe extrusions and forgings Test valve articles to support ASME Code approval. In addition, key fabrication steps were completed, including boiler weld overlays and simulated field repairs. Throughout, extensive inspection and quality assurance testing of the components were performed. The team worked to advance ASME Code approval for key components and processes. Although much of the focus of ComTest Phase 2 was the high-temperature nickel-based alloy materials, a broader range of materials were incorporated, which would be representative of the materials used in full-scale A-USC power plant applications and have cross-cutting applicability on other high-temperature power generation options, such as advanced nuclear, supercritical CO 2 cycles, and central solar receivers. This report that has been submitted is organized in the following manner: Section 1 contains an Executive Summary. Section 2 discusses the ComTest project background and organization. Section 3 discusses project management and reporting. Section 4 discusses the procurement of nickel-based alloy and other A-USC materials and components. Section 5 discusses the fabrication of procurement of nickel-based alloy and other A-USC materials and components. Section 6 discusses the fabrication of cast nickel-based A-USC steam turbine components. Section 7 discusses the fabrication of forged nickel-based A-USC steam turbine piping and steam pipe components. Section 8 discusses the qualification of pressure relieve valves (PRVs) for A-USC power plants. Section 9 discusses proposed plans for future evaluation of A-USC components. Section 10 contains the summary and conclusion.

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