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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Catalytic Removal of Oxygen Impurities from Pressurized Oxy-Combustion Flue Gas for the Production of High-Purity Carbon Dioxide

Flue gas purification is important for pressurized oxy-combustion systems to produce pure carbon dioxide (CO 2 ) streams ready for storage or utilization. A catalytic approach to removing oxygen (O 2 ) impurities from pressurized oxy-combustion flue gas via reduction with methane (CH 4 ) was investigated in this work. Two types of catalysts were studied: palladium (Pd)-based catalysts supported on titania (TiO 2 ) prepared by incipient wetness impregnation and cobalt–manganese (CoMn) composite catalysts prepared by coprecipitation. The performance of the catalysts was evaluated in a high-pressure–high-temperature, fixed-bed reactor at a pressure of 15 bar and a gas hourly space velocity of 30 000 h –1 (standard conditions), with a simulated feeding gas composed of 3 vol % O 2 , 1.5 vol % CH 4 , and CO 2 as the balance gas. Among the Pd catalysts, 5% Pd/TiO 2 achieved the maximum 86% O 2 removal at ≥350 °C. The CoMn oxide catalysts displayed comparable or better activities for O 2 reduction compared with the Pd catalysts. Among them, the Co 40 Mn 1 catalyst exhibited the best performance, able to reduce 99.9% of O 2 impurities at ~370 °C with negligible carbon monoxide (CO) formation (<10 ppmv). Both trivalent and divalent Co and Mn were detected on the catalyst surface, and the superior activity of Co 40 Mn 1 might be associated with the resultant disordered structure. Furthermore, the activity of the catalyst was not affected by the presence of a trace amount of nitric oxide (NO) gas contaminant. Results of this study provide the basis for scale-up studies in both the synthesis and performance of non-noble metal catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Development of the 3 m{sup 3} Low Level Radioactive Waste Container in Taiwan - 20037

Chinshan Nuclear Power Plant stopped its business operation in July, 2019, and Kuosheng Nuclear Power Plant will also be permanently shut down in 2023. Nuclear Reactor Facilities Regulation Act requires a nuclear facility must be dismantled in 25 years after being permanently ceased operation. According to the approved decommissioning plan of Chinshan Nuclear Power Plant and the proposed one of Kuosheng Nuclear Power Plant, the 3 m{sup 3} low level radioactive waste container is planned to store the low level radioactive wastes with higher radiation produced during the decommissioning. However, 3 m{sup 3} low level radioactive waste containers are not used or developed in Taiwan before. To meet such need, Institute of Nuclear Energy Research develops a new type of 3 m{sup 3} low level radioactive waste container and performs the corresponding analyses and tests based on Guidelines of Applying the Usage License of Low Level Radioactive Waste Containers and Regulations for the Safe Transport of Radioactive Material. In this article, it provides the information of the low level radioactive waste containers that have been approved or is under reviewing in Taiwan, and so do the design specifications of the developed 3 m{sup 3} waste container. Besides, the numerical evaluation and test results of the developed 3 m{sup 3} waste container are also included in this article. Based on the evaluation and test results, the developed 3 m{sup 3} waste container satisfies the requirements of the storage container and industrial package type 2. Institute of Nuclear Energy Research will submit the usage license applications to the authority this year, and the usage licenses would be granted in 2021, expectedly. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Monte Carlo Dropout Uncertainty Quantification of Long Short-Term Memory Autoencoder Anomaly Detection in a Liquid Sodium Cold Trap

Advanced high-temperature fluid reactors, such as sodium-cooled fast reactors (SFRs) and molten salt–cooled reactors (MSCRs), require coolant purification systems to prevent fluid contamination and local freezing that can lead to plugging. Liquid sodium purification can be achieved with a cold trap, where the sodium temperature is reduced to a near-freezing point to precipitate out impurities. Automation of monitoring of the cold trap performance with machine learning algorithms can aid in early detection of incipient anomalies. An efficient approach to loss-of-coolant–type anomaly detection in a cold trap monitored with more than two dozen thermal-hydraulic sensors consists of a long short-term memory (LSTM) autoencoder. This work develops the uncertainty quantification of the LSTM autoencoder performance for cold trap anomaly detection using the Monte Carlo (MC) dropout method. The MC dropout methodology creates a distribution of sister distributions that all slightly differ from each other because of random neurons being turned off for testing. The variances of the sister network distributions are used to make an uncertainty interval. Our analysis shows that the uncertainty in the autoencoder performance is largest near the peak of the anomaly signal. Using the MC dropout method, we investigate the uncertainty in the anomaly detection with missing sensor inputs. This capability allows the reactor operator to evaluate resilience of the anomaly detection system and to make informed decisions about continuity of operation in the event of sensor failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Complete Documentation of Applicable Regulations and Regulatory Authority for Transportation

This report fulfills the M4 milestone M4MR-20PN0303023, “Complete Documentation of Applicable Regulations and Regulatory Authority for Transportation. Microreactors are very small nuclear reactors with a power output of 20MWe or less and are designed to be factory-built, modular in nature, and highly portable. The objective of this report is to identify and document applicable regulations, the appropriate regulatory authority, and the associated framework for microreactor transport. Sections 2 and 3 of this report summarize U.S. Department of Transportation (DOT) and NRC regulations related to the transportation of Class 7 (radioactive) materials. These sections concentrate on the transport of fissile material packages and Type B packages, which would be most applicable to the transport of a microreactor before and after irradiation. Section 4 summarizes DOE hazardous and radioactive material transportation regulations. Section 5 summarizes U.S. Coast Guard regulations related to the transport of radioactive material. Section 6 discusses state requirements for the permitting of oversize and/or overweight truck shipments. Section 7 presents detailed schedules of requirements for transporting fissile material packages and Type B packages based on NRC and DOT regulations. The schedules are presented in a two-column format, the right column is the regulatory requirement and the left column is the citation of the regulation in which the requirement is found.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

ECAR-3386 AS-RUN THERMAL ANALYSIS OF THE AGC-3 EXPERIMENT

The third Advanced Graphite Creep (AGC-3) experiment was designed to irradiate various types of graphite specimens at a temperature of 900°C. The specimens were irradiated in an instrumented leadout capsule experiment in the east flux trap of the ATR during cycles 152B, 154B, 155A, and 155B. Temperature was monitored using twelve thermocouples located at various elevations in the reactor core, and a helium-argon gas mixture was used for gas gap temperature control of the specimens. The purpose of this analysis is to calculate specimen temperature using measured data on reactor power and helium-argon gas flows, and as-run calculations of heating rates and displacement per atom (DPA) in graphite. The accuracy of the model is assessed by comparing measured and calculated thermocouple temperatures. Uncertainty in gas gaps may preclude an accurate temperature calculation. In these cases, adjustments are made to the thermal model in order to reconcile the measured and calculated thermocouple temperature and to ensure the accuracy of the calculated specimen temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Activation of Thermal Insulation and Contamination Prevention

The goals of this paper are to enhance the understanding of the potential activation and contamination hazards from the use of insulating materials in the Molten Chloride Reactor Experiment and to foster safer work environments through informed decision-making and strategic planning. It was written to resolve a gating comment from the core heating system preliminary design review. The largest dose expected from the considered insulation materials is about 0.1 mrem per year from Pyrogel. Although Cerablanket stood out among the insulation materials for encouraging ALARA practices, it has a higher thermal conductivity. At low power levels, focusing on reducing the generation of dust from ERD activities may be more effective for reducing the potential spread of contamination than changing the insulating material type. However, regardless of the material chosen, PPE and safety conscious procedural practices can help reduce the production and spread of activated dust––thus minimizing the radiological hazard to workers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

Assessment of Grizzly Capabilities for Reactor Pressure Vessels and Reinforced Concrete Structures

Over the last several years, capabilities to simulate the progression and effects of degradation in critical structures in light water reactor (LWR) nuclear power plants have been under development in the Grizzly code. Age-related material degradation is important for a number of systems in LWRs, but the main focus for Grizzly development has been on reactor pressure vessels (RPVs) and concrete structures because of their central role and the difficulty of replacement of these structures if they are found to be degraded to an unacceptable degree. The capabilities for analyzing both RPVs and concrete structures in Grizzly have reached a point where the feature sets are sufficiently complete to perform credible analyses of those types of structures. Because of this, the emphasis has shifted from foundational development to assessing the accuracy of these modeling capabilities on representative problems of interest and on improving the physical basis of those models to improve their ability to predict the actual response of those structural systems. This report documents a first set of test cases that have been developed to assess the Grizzly code on real-world problems for these two types of structures. For RPVs, these test cases consist of a set of benchmark problems where Grizzly is compared to another code. For concrete structures, a set of models of experimental specimens designed to characterize the multidimensional swelling response of reinforced concrete members due to alkali-silica reaction (ASR) has been developed and compared with experimental results. Both the RPV and concrete test cases developed here are much more computationally intensive than the small regression tests that are used in the testing that Grizzly undergoes every time a proposed set of changes is made to ensure that those changes do not adversely affect previously established behavior. A system for regularly running these large problems to monitor the behavior of the code as it is developed has been instituted. While these test cases generally indicate good comparison with the benchmark results, they also indicate areas where further development is warranted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Multidimensional modeling of fuel-cladding friction in an LWR fuel rod

Solving finite element problems with friction often increases the level of difficulty to obtain properly converged solutions. This type of challenge becomes more salient when advanced, possibly multiscale, material models are employed to capture the thermomechanical behavior of fuel and cladding materials. Here the present work details our recent developments in a nuclear fuel performance finite element code for the systematic consideration of friction in nuclear reactor finite element simulations. We show the application of friction and its effects on the mechanics of light-water reactor rods accounting for various fuel constitutive modeling techniques, model dimensionalities, pellet assumed geometries, and power conditions. In particular, we focus on the fuel rod mechanical behavior as it relates to fuel constitutive models, sensitivity to the coefficient of friction, pellet states of stress, and rod elongation. We discuss the trade-offs between the various multidimensional modeling options and highlight the relevance of frictional effects in the prediction of the fuel rod deformation and interfacial stresses. To relate our modeling results with actual reactor operation, simulations including frictional effects are compared with fuel rod elongation experimental data and some challenges for carrying out a full validation of the axial mechanics are discussed.

42 ENGINEERING↗
DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

ECAR-2322 As-Run Thermal Analysis Of The AGC-2 Experiment

The second Advanced Graphite Creep (AGC-2) experiment was designed to irradiate various types of graphite specimens at a temperature of 600°C. The specimens were irradiated in an instrumented leadout capsule experiment in the south flux trap of the ATR during cycles 149A, 1498, 1508, 151A, and 1518. Temperature was monitored using twelve thermocouples located at various elevations in the reactor core, and a helium-argon gas mixture was used for gas gap temperature control of the specimens. The purpose of this analysis is to calculate specimen temperature using measured data on reactor power and helium-argon gas flows, and as-run calculations of heating rates and displacement per atom (DPA) in graphite. The accuracy of the model is assessed by comparing measured and calculated thermocouple temperatures. Uncertainty in gas gaps may preclude an accurate temperature calculation. In these cases, adjustments are made to the thermal model in order to reconcile the measured and calculated thermocouple temperature and to ensure the accuracy of the calculated specimen temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

University of Missouri Research Reactor (MURR) Design Demonstration Element End Fitting Structural Rigidity Analysis

The primary objective of this work is to assess the extent to which the stiffness (measured by means of maximum displacement) of the end fittings in the DDE contributes to the stiffness of the entire element, and how it compares to the equivalent stiffness of the end fittings in the LEU element. Structural analysis of both the LEU element and the DDE were performed using COMSOL 5.3a finite element software. Supporting combs are used on the leading and trailing edges of fuel plates for both the LEU element and the DDE. Therefore, simulations with and without combs are performed as two bounding boundary conditions on the leading edge of the fuel plates. Three types of loads are analyzed in this work: the hydraulic load due to the channel flow disparity-induced pressure differential, the thermal load due to the thermal expansion of the fuel plates, and a point load equal in magnitude to the LEU element’s weight.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Recent progress in the design of the K-DEMO divertor

The preliminary conceptual design of the Korean fusion demonstration reactor (K-DEMO) with a major radius of 6.8 m and the fusion power of 2200 MW has been studied since 2012. The overall configuration of the K-DEMO divetor system based on the ITER-like water-cooled tungsten technology is a double-null type symmetric divertor subdivided into 32 toroidal modules for the vertical maintenance. A detached divertor scenario with impurity seeding was considered as the primary approach for the power exhaust to reduce the peak heat flux lower than the engineering limit of 10 MW/m 2 . The power exhaust performance at the scrap off layer was estimated by using UEDGE-2D code, a two-dimensional fluid transport code for collisional edge plasma and neutral species like N, Ne, and Ar. Particle and heat flux on inboard and outboard divertor targets were calculated for the detached cased depending on parameters such as the impurity seeding rate, pumping rate, and the pedestal density. On the other hand, a magnetic solution like X-divertor, snowflake divertor, and super X-divertor to expand the plasma wet area was considered for K-DEMO since the detached divertor increasing a radiation fraction by impurity seeding might be able to be unstable. However, the extremely high current of poloidal coils was required more than the engineering limit, 20 MA, to form magnetic field lines for the alternative divertors. Based on the physical calculation of the edge plasma, engineering analyses were carried out to find out the thermal and structural reliability. The thermo-hydraulic analysis confirmed thermal stability, whether all comprising materials are operating within their allowable temperature windows when the case of the peak heat flux is set to 10 MW/m 2 on the outboard divertor target. The response surface optimization method derived two optimal design candidates employing two kinds of heat sink materials, respectively: the reduced activation ferritic martensitic (RAFM) steel and CuCrZr alloy. Additionally, the drawbacks and merits of the two materials were definite. The optimal design with applying RAFM steel was vulnerable to withstand thermal and mechanical loads since low thermal conductivity caused too thin thickness of the heat sink. On the other hand, the CuCrZr alloy has critical drawbacks in terms of activation and radioactive waste despite its high thermal conductivity. Meanwhile, preliminary electromagnetic (EM) analysis was carried out to estimate the EM loads caused by the abnormal behaviors of plasma since EM loads are one of the most critical external loads for designing a DEMO divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗
DOE OSTI2023

Determination of Average Burnup in AGR-3/4 Compacts 1-4 and 7-4

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program third and fourth irradiation experiments (AGR-3/4), originally planned as separate tests, were combined in one test train for irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The irradiation test began on December 14, 2011, and ended on April 12, 2014 (Collin 2016). The originally planned AGR-3 and AGR-4 irradiation experiments were both focused on obtaining data on fission product transport to support the improvement of modeling. The AGR-3 experimental plan was focused on gaseous and metallic fission product release from the kernels and diffusion in the coatings during irradiation and post-irradiation safety testing. The AGR-4 experimental plan was focused on diffusivities and sorptivities in the compact matrix and reactor graphite. These two goals were combined in the AGR-3/4 irradiation, which consisted of 12 independently monitored capsules that each contained four AGR-3/4 compacts in a single stack surrounded by an inner ring of matrix or graphite and an outer ring of graphite. Two capsule types were used: a standard capsule and a so-called fuel body, in which the outer graphite ring included a floor and cap that fully enclosed the fuel. The fuel body design supported post-irradiation safety testing of the intact fuel and ring assembly to provide data on fission product transport and release from the matrix and graphite at accident temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Corrosion of SS 316, Inconel 617, Inconel 625 in molten chloride salt with emphasis on the speciation of Cr, Ni, and Co in molten salt matrix by XAFS

Dr. Hartmann’ report summarizes the corrosion behavior of materials used in the construction and operation of molten salt reactors which is is of great interest to the molten salt reactor (MSR) community. In the present study we intent to decipher the very elemental phenomena on the corrosion of austenitic chromium-containing stainless steel SS316, as well as Inconel 625 and ASME-coded high temperature Alloy (Inconel) 617. We initiated and are in continuation of conducting ampoule type corrosion testing at 550 °C and 650 °C to determine chromium diffusivity and the related activation energy as well as the speciation of the corrosion products.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Reactor Supply Chain Assessment (GAIN Report)

Several net-zero scenario evaluations predict a rapid ramp up of nuclear energy in the coming decades. If this materializes, it will most likely strain the supply chains associated with the potential advanced reactor concepts awaiting deployment. To help assess the current and potential capacities of the various advanced reactor supply chains, the Gateway for Accelerated Innovation in Nuclear (GAIN) conducted a survey of companies able to produce components for advanced reactors in the near future (namely for sodium, gas-cooled, and molten salt reactors). Using an aggressive nuclear deployment scenario, the objective was to assess the ability of the various supply chains to meet the considerable demand projections for certain key components (vessels, heat exchangers, pumps, graphite, and sensors) and identify potential challenges. While individual companies were unable to meet the most optimistic nuclear deployment rate projections, it was found that on aggregate, a United States-based supply chain projected that expansion could be ramped up to meet a larger future demand of these components. However, meeting projected demand for several more complex items (namely gas or salt heat exchangers) was found to be more challenging. Deploying new reactors at scale necessitates the production of more and more supply chain components, requiring a ramp up in production. Supply chain companies were surveyed, and respondents appeared less able to meet short term demand (next year) versus longer-term demand projections (5 and 10 years). This reflects the need to obtain orders with adequate lead times (can range from 3 to 30 months). Future demand will need to be met by expanding existing capacity. These expansions will require suppliers to raise capital or secure other types of support (federal loans or grants) to invest in facilities, equipment, and workforce. Individual suppliers indicated financial investments could be in the range of $\$ $100 million to $\$ $1 billion for their own facilities (depending on the type of facility). The biggest risk, according to respondents, related to general uncertainties surrounding the future nuclear industry and whether the potential demand projections will materialize into real demand that is actionable from a business perspective. Businesses do not seem willing to take investments risks without clear orders. If businesses are not able to invest to expand the supply, it will either delay the deployment of advanced nuclear technology, or the supply chain will be met by suppliers outside of the United States. This report only focuses on the domestic supply chain’s ability to meet the various projections stipulated here for the specific assessed components (vessels, heat exchangers, pumps, graphite, and sensors). The report does not cover all reactor designs or all components that may ultimately be needed for any one reactor design. It also does not address whether any specific aspect of the supply chain will be cost competitive in the global market, nor how potential state-backed entities could affect the expansion of a United States-based supply chain. The largest challenges in ramping up capacity among respondents appear to be workforce related. This includes workforce availability, experience, training, and turnover. In addition to facility investment, suppliers will also need to invest heavily in long-term workforce training to meet production goals. This issue is not nuclear-specific, and the expansion of any supply chain will likely face similar challenges. While suppliers evaluated expected normal business demand from other markets outside of nuclear, it is possible that other market segments could expand more than predicted and compete for the same suppliers. One potential market that may compete for the same supplier resources is the United States military, as many of these suppliers support both the commercial nuclear sector as well as the Navy with reactors and components. In summary, suppliers in the United States believe that there is a way to increase production in order to begin meeting the demand which will exist for advanced reactors—as long as appropriate investments can be made in the supply chain in an appropriate timeframe. Based on the capacity projections and lead times, investment will be needed to meet the 5-year and 10-year production targets. Therefore, if significant nuclear deployment is to occur in the 2030s, investment and ramp up of the advanced nuclear supply chain will need to begin in the near future for the United States to successfully deploy these advanced reactors with domestic supply chains.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computationally expensive. This work proposes a context-aware multi-fidelity Monte Carlo method that optimally balances the costs of training low-fidelity models with the costs of Monte Carlo sampling. It generalizes the previously developed context-aware bi-fidelity Monte Carlo method to hierarchies of multiple models and to more general types of low-fidelity models. When training low-fidelity models, the proposed approach takes into account the context in which the learned low-fidelity models will be used, namely for variance reduction in Monte Carlo estimation, which allows it to find optimal trade-offs between training and sampling to minimize upper bounds of the mean-squared errors of the estimators for given computational budgets. This is in stark contrast to traditional surrogate modeling and model reduction techniques that construct low-fidelity models with the primary goal of approximating well the high-fidelity model outputs and typically ignore the context in which the learned models will be used in upstream tasks. Further, the proposed context-aware multi-fidelity Monte Carlo method applies to hierarchies of a wide range of types of low-fidelity models such as sparse-grid and deep-network models. Numerical experiments with the gyrokinetic simulation code Gene show speedups of up to two orders of magnitude compared to standard estimators when quantifying uncertainties in small-scale fluctuations in confined plasma in fusion reactors. This corresponds to a runtime reduction from 72 days to four hours on one node of the Lonestar6 supercomputer at the Texas Advanced Computing Center.

42 ENGINEERING↗
DOE OSTI2023

Bridging microscale to macroscale mechanical property measurements of FeCrAl alloys by crystal plasticity modeling

FeCrAl alloys are candidates for accident tolerant fuel cladding of light water reactors. In this work, a microstructure- and temperature-dependent crystal plasticity model is employed to bridge microscale to macroscale mechanical property measurements of FeCrAl alloys. With the visco-plastic self-consistent (VPSC) polycrystal plasticity framework, a mechanism-based single crystal plasticity (MSCP) model adopts the Arrhenius type rate equation to describe the dependence of the critical resolved shear stress for dislocation slips on their temperature-dependent intrinsic frictional resistance and the microstructure-dependent irradiation hardening. The intrinsic frictional resistance associated with {110}<111> and {112}<111> slip systems were measured by in-situ micromechanical testing on unirradiated/irradiated samples at 25-500 °C. The irradiation hardening is estimated by the Bacon-Kocks-Scattergood (BKS) model with density and size of radiation-induced defects measured from microstructural characterization. Several features associated with thermo-mechanical behavior of unirradiated/irradiated polycrystalline FeCrAl alloys are captured. High density of deformation-induced dislocations and radiation-induced defects results in obvious hardening at room temperature, which is weakened at high temperature, and facilitates damage evolution during deformation. Moreover, both high temperature and radiation-induced defects, which facilitate dislocation multiplication, trigger large hardening rate. Finally, the proposed method together with application of accelerator-based ion irradiation technique is a surrogate approach to simulate neutron damage, improving the efficiency associated with evaluation of mechanical properties of FeCrAl alloys exposed to temperature, stress and radiation conditions.

36 MATERIALS SCIENCE↗