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DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Heterogeneity of Bulk Oxygen Isotopic Compositions in Anhydrous Interplanetary Dust Particles

Introduction: Anhydrous interplanetary dust particles are one of the least altered ancient solar systemmaterials. Their bulk chemical compositions match those of CI chondrites within a factor of 2-3, except for carbonwhich is enriched in both anhydrous and hydrated IDPs by ~4x CI [1]. Hydrous IDPs often show 16O-poor isotopiccompositions, likely due to the interaction with isotopically heavy H2O [2]. Anhydrous IDPs are interpreted tooriginate from comets from the outer solar system [3]. Oxygen isotopic data for these materials is scarce, but resultspoint to a wider range of compositions [4]. This heterogeneity might be a result of mixing between a 16O-rich and a16O-poor reservoir formed via self-shielding and photodissociation of CO [5]. Here, we report bulk oxygen isotopiccompositions of three anhydrous IDPs in context of their mineralogical composition and discuss possible origins ofisotopic heterogeneity. Experimental: Bulk chemical composition and mineralogy of 70 nm thin ultramicrotomed sections of threeanhydrous IDPs (L2099A7, L2099A8, and L2071AB1) were analyzed using a Thermo Scientific Titan Themis G360-300 TEM equipped with a four-quadrant energy-dispersive X-ray detector (Super-X G2) at University ofMünster. Bulk oxygen isotopic compositions were measured using a NanoSIMS 50 at the Max-Planck-Institut fürChemie in Mainz. A focused Cs+ ion beam (~1 pA, ~100 nm) was rastered over a field of view varying from 5 x 5 to6 x 6 μm2, depending on particle size for 15 layers. Negative secondary ions of 16O, 17O, 18O, 12C14N, and 28Si werecollected on electron multipliers. The 16OH contribution to the 17O peak was 1-2 ‰. As a standard, a matrix regionof meteorite CR2 Queen Alexandra Range (QUE) 99177 was used, whose oxygen isotopic composition wasmeasured by [6]. Results and Discussion: Particles A7 and A8 are both fine-grained, consisting mostly of small, 100 nm-sizedequilibrated aggregates (EA). Both particles exhibit discontinuous magnetite rims with thicknesses up to 50 nm inA7 and 100 nm in A8 on the outsides. In Particle AB1, the upper part of the particle consists of a few EAs, while thelower part contains lots of small GEMS grains with 100-200 nm diameter clustered together. Magnetite rims arenearly absent, the rare rims reaching maximum 20 nm thickness, indicating that AB1 is of more primitive naturethan the other two IDPs [1]. Furthermore, it contains several diffuse GEMS-like areas, identified by an amorphoussilicate groundmass with small nano-inclusions of Fe,Ni-metal and Fe-sulfides. All three particles are subsolar forall major element/Si ratios. Mean S/Si of particles A7 and A8 is 0.046 and 0.048, respectively, while it is an order ofmagnitude higher in AB1 (0.184). This reflects the higher degree of thermal alteration in A7 and A8, resulting in theloss of volatile S and oxidation of Fe-sulfides and FeNi-metal to magnetite as present in particle rims. A8 is rather16O-poor with δ17OSMOW = 7.8 ± 3.4 ‰ and δ18OSMOW = 9.5 ± 3.1 ‰ (1σ), followed by A7 with δ17OSMOW = − 0.8 ±4.6 ‰ and δ18OSMOW = −2.2 ± 3.4 ‰. In contrast to that, AB1 has the most 16O-rich bulk composition with δ17OSMOW= −24.2 ± 5.4 ‰ and δ18OSMOW = −25.3 ± 3.6 ‰. All investigated IDPs plot slightly above the CCAM line aspreviously reported for other anhydrous IDPs [4], maybe due to a contribution from circumstellar dust from AGBstars enriched in 17O [7]. The 16O-rich composition of AB1 is similar to the most 16O-rich anhydrous IDP U2015D21measured by [8] which is dominated by GEMS [9] and the GEMS-rich IDP GM4-2 reported by [10]. Nevertheless,it is unlikely that GEMS are the carrier for the 16O-rich composition of AB1 because most GEMS have O isotopiccompositions indistinguishable from terrestrial values, although errors on these analyses are large [11]. The isotopicheterogeneity is best explained by contribution of grains from different regions in the protoplanetary disk, samplingdifferent O isotope reservoirs, created by self-shielding and photodissociation of CO. This process resulted in 16O-rich CO gas and 16O-poor H2O that froze as ice-mantles onto dust grains [12]. Alternatively, the higher degree ofheating in A7 and A8 could have influenced isotopic fractionation, because higher δ17,18O values are reported fromthe regions of the atmosphere where small particles are heated and oxidized, as observed for the thermal alteration ofcosmic spherules [13]. Acknowledgements: We would like to thank NASA Astromaterials Acquisition & Curation Office for providing IDPsamples and DFG for funding this project (VO1816/5-1)

B Schulz↗

DOE OSTI2021

AGR 5/6/7 Data Qualification Report for ATR Cycles 162B through 168A

This report provides the qualification status of experimental data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation. AGR-5/6/7 was conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The objectives of the AGR-5/6/7 experiments are to: (i) irradiate reference-design fuel particles to support fuel qualification, (ii) establish operating margins for the fuel beyond normal operating conditions, and (iii) provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination (PIE) and safety testing. The test train contains five separate capsules that were independently controlled and monitored. Each capsule contains multiple 12.51-mm-long compacts filled with low enriched uranium carbide/oxide (UCO) TRISO fuel particles. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) is to verify successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions in support of plant design and licensing. AGR 5/6/7 will also provide irradiated-fuel performance data on fission-gas release from failed particles during irradiation. The AGR-5/6/7 capsules were irradiated in the ATR northeast flux trap location. The experiment began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of 360.9 effective full power days. The AGR 5/6/7 experiment was able to remain in the reactor core during all three Powered Axial Locator Mechanism (PALM) cycles (163A, 165A, and 167A) without overheating its fuel compacts. This report includes irradiation monitoring data from nine ATR Cycles: 162B, 163A, 164A, 164B, 165A, 166A, 166B, 167A, and 168A, as stored in the Nuclear Data Management and Analysis System (NDMAS). During irradiation, data records consisted of instantaneous measurements recorded every minute and provided by text files automatically every 2 hours. The AGR 5/6/7 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates [capsule inlet, outlet, and downstream at detector], pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates and release to birth rate ratios [R/Bs]) for each of the five capsules. A total of 94,989,908 TC temperature and sweep gas data records were received and processed by NDMAS for AGR 5/6/7 irradiation. Of these records, 41,593,387 (or 43.7% of the total) met data collection and accuracy requirements and are labeled as Qualified. A total of 57,746,693 TC temperature readings were captured from 54 installed TCs. Among them, 10,034,676 TC temperature records (only 17.4%) were Qualified and 47,701,371 TC temperatures (or 82.6%) are Failed due to 48 TC failures (63.5%) and due to missing values (19.1%). To assess performance of the operational TCs, analysis of daily correlations between TCs found no evidence of virtual junction failure for any TCs. Analyses on control charts of TC temperature differences revealed trending in TC readings for TC2, 4, 5, and 13 in Capsule 3, but there is no conclusive indication of TC drift failure that caused those trends. Therefore, TC control charts are not used to disqualify TC data, but only for users’ consideration. For sweep gas flow rates, a total of 31,519,747 gas flow records (84.4%) are Qualified for use for AGR-5/6/7 experiment; 5,723,468 gas flow records (15.4%) are Failed due mostly to missing values; and 74,641 high sweep gas flow rates (0.2 %) are Trend. A large number of Failed missing TC temperature and gas flow values were caused by an error in the data output script that outputted a ‘NULL’ value when values were unchanged. This problem was fixed during the outage of Cycle 166B, which led to a substantially decreased number of missing values during the last three cycles. Nonetheless, a large amount of non-missing data remained because of the high data acquisition frequency (1-minute) and still provided sufficient data to effectively monitor the experiment as designed. For FPMS data, NDMAS received and processed fission product release and R/B data for nine ATR cycles, when ATR core reached full power during AGR 5/6/7 irradiation. These data consist of 110,388 release rate records and 110,388 R/B records for the twelve radionuclides (Kr 85m, Kr 87, Kr 88, Kr 89, Kr 90, Xe 131m, Xe 133, Xe 135, Xe 135m, Xe 137, Xe 138, and Xe 139) for each of the five capsules. Equivalent numbers of uncertainty records associated the release rates and R/B values were provided. To date, qualification status of the FPMS data stored in the NDMAS dat

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗