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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effects of fuel composition and octane sensitivity on polycyclic aromatic hydrocarbon and soot emissions of gasoline–ethanol blend surrogates

The sooting propensity of a fuel is closely coupled with the fuel composition and chemistry. A detailed understanding of their effects is, therefore, needed to develop next-generation fuels which can minimize particulate emissions. With this overarching goal, the present work numerically investigates the effects of fuel composition and octane sensitivity (S) on polycyclic aromatic hydrocarbons (PAH) and soot emissions, for four-component gasoline-ethanol blend surrogates comprising isooctane, n-heptane, toluene, and ethanol. A partially-premixed counterflow flame is chosen as the canonical configuration for this study and simulations are performed using CHEMKIN-Pro-employing a kinetic mechanism developed by Park et al. (2017). In addition, a, detailed soot model based on the sectional method is used to capture the spatial characteristics of soot emissions. The kinetic mechanism and soot model are validated using available experimental data for various targets. A total of 86 TPRF-E mixtures, spanning a wide range of concentration of each component, and a wide range of S are analyzed. The effect of each non-paraffinic fuel component on the resultant PAH and soot emissions is investigated. PAH and soot emissions are found to vary significantly depending upon the blend composition. Additionally, based on the parametric sweeps, a regression analysis is carried out to identify global parameters that govern the formation of PAHs and soot. The analysis shows that both toluene content and S have a prominent effect on the formation of PAHs and soot, with toluene content having a stronger impact. Moreover, larger PAHs have higher dependency on toluene content and S. Furthermore, a detailed analysis is carried out to understand the physical and chemical phenomena associated with the observed trends of PAH and soot emissions.

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

CFD analysis of a solid pin-fueled small modular fluoride salt-cooled reactor

A computational fluid dynamics (CFD) study is performed for the pre-conceptual solid pin-fueled small modular fluoride salt-cooled reactor developed by the Oak Ridge National Laboratory (ORNL). The solid and fluid regions in a 1/12th section of a fuel assembly are modeled. The solid region includes fuel and non-fuel pins, with heat generation in the active region of the fuel pins. Two different power profiles, uniform and center-peaked, are considered. The FLiBe coolant flows from the bottom to the top of the core, parallel to the bank of fuel and non-fuel pins. The k-ω shear-stress transport (SST) model is chosen as the baseline turbulence model. The effects of grid refinement, inlet turbulence specification, and turbulence models on the temperature and pressure drop predictions are studied. Turbulence model sensitivity is investigated by comparing the results from the k-ω SST model with other two-equation models (k-ω baseline or BSL and k-ε realizable) as well as with anisotropic Reynolds stress transport models (linear pressure-strain and stress-BSL). Here the results show that the choice of turbulence model has a significant impact on the pin temperature and bundle pressure drop predictions. The results from the baseline turbulence model show good agreement between the fuel pin temperatures and bundle pressure drop values predicted using a subchannel model previously developed by the authors of the present study.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite

Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.

42 ENGINEERING↗
DOE OSTI2024

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2022

MELCOR Accident Progression and Source Term Demonstration Calculations for a Heat Pipe Reactor

MELCOR is an integrated thermal hydraulics, accident progression, and source term code for reactor safety analysis that has been developed at Sandia National Laboratories for the United States Nuclear Regulatory Commission (NRC) since the early 1980s. Though MELCOR originated as a light water reactor (LWR) code, development and modernization efforts have expanded its application scope to includ e non-LWR reactor concepts. Current MELCOR development efforts include providing the NRC with the analytical capabilities to support regulatory readiness for licensing non-LWR techno logies under Strategy 2 of the NRC?s near- term Implementation Action Plans. Beginning with the Next Generation Nuclear Project (NGNP), MELCOR has undergone a range of enha ncements to provide analytical capabilities for modeling the spectrum of advanced non-LWR concepts. This report describes the generic plant model developed to demonstrate MELCOR capabilities to perform heat pipe reactor (HPR) safety evaluations. The generic plant mode l is based on a publicly-available Los Alamos National Laboratory (LANL) Megapower design as modified in the Idaho National Laboratory (INL) Design A description. For plant aspects (e.g., reactor building size and leak rate) that are not described in the LANL and INL references , the analysts made assumptions needed to construct a MELCOR full-plant model. The HP R uses high assay, low-enrichment uranium (HALEU) fuel with steel cladding that uses heat pipes to transfer heat to a secondary Brayton air cycle. The core region is surrounded by a stainless-steel shroud, alumina reflector, core barrel and boron carbide neutron shield. The reactor is secured inside a below-grade cavity, with the operating floor located above the cavity. Example calculations are performed to show the plant response and MELCOR capabilities to characterize a range of accident conditions. The accidents selected for evaluation consider a range of degraded and failed modes of operation for key safety functions providing re activity control, the primary and secondary system heat removal, and the effectiveness of th e confinement natural circulation flow into the reactor cavity (i.e., a flow blockage).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Variational Autoencoder Model Toward Molecular Structure Representation Learning of Fuels

Here, in this work, a Variational Autoencoder (VAE)-based data-driven modeling framework is developed with the overarching goal of enabling fuel design. The VAE model is trained on a large dataset with several chemical species to learn a compressed latent space molecular representation. Chemical structure in the form of Simplified Molecular Input Line Entry System (SMILES) string is fed as input, encoded into the VAE latent space, and decoded back to the SMILES string using Long Short-Term Memory (LSTM) networks. Complexities of the VAE training loss function are thoroughly examined by varying the weightage (beta (𝜷) parameter) of the latent space regularization term, thereby assessing the balance between reconstruction accuracy and validity, and focusing on both accurate molecular structure reconstruction and latent space consistency. Two different strategies for 𝜷 variation are evaluated: linear annealing and cyclic annealing. In addition, the impact of total correlation adjustment and hierarchical priors is also studied with regard to the balance between reconstruction fidelity and latent space regularization, and potential issues such as posterior collapse, over-regularization, and poor disentanglement of latent variables. Overall, the best performance of the model is achieved with hierarchical priors and incrementally increasing 𝜷 from 0 to a threshold value of 0.25 over 75 epochs. The generative VAE model can be readily coupled with Quantitative Structure–Property Relationship (QSPR) analysis to develop an integrated end-to-end framework for fuel-property prediction and molecular design of novel promising fuels.

fuel design↗
DOE OSTI2021

An Experimental Kinetics Study of Isopropanol Pyrolysis and Oxidation behind Reflected Shock Waves

Isopropanol has potential as a future bio-derived fuel and is a promising substitute for ethanol in gasoline blends. Even so, little has been done in terms of high-temperature chemical kinetic speciation studies of this molecule. To this end, experiments were conducted in a shock tube using simultaneous CO and H2O laser absorption measurements. Water and CO formation during isopropanol pyrolysis was also examined at temperatures between 1127 and 2162 K at an average pressure of 1.42 atm. Species profiles were collected at temperatures between 1332 and 1728 K and at an average pressure of 1.26 atm for equivalence ratios of 0.5, 1.0, and 2.0 in highly diluted mixtures of 20% helium and 79.5% argon. Species profiles were also compared to four modern C3 alcohol mechanisms, including the impact of recent rate constant measurements. The Li et al. (2019) and Saggese et al. (2021) models both best predict CO and water production under pyrolysis conditions, while the AramcoMech 3.0 and Capriolo and Konnov models better predict the oxidation experimental profiles. Additionally, previous studies have collected ignition delay time (τign) data for isopropanol but are limited to low pressures in highly dilute mixtures. Therefore, real fuel–air experiments were conducted in a heated shock tube with isopropanol for stoichiometric and lean conditions at 10 and 25 atm between 942 and 1428 K. Comparisons to previous experimental results highlight the need for real fuel–air experiments and proper interpretation of shock-tube data. The AramcoMech 3.0 model over predicts τign values, while the Li et al. model severely under predicts τign. The models by Capriolo and Konnov and Saggese et al. show good agreement with experimental τign values. A sensitivity analysis using these two models highlights the underlying chemistry for isopropanol combustion at 25 atm. Additionally, modifying the Li et al. model with a recently measured reaction rate shows improvement in the model’s ability to predict CO and water profiles during dilute oxidation. Finally, a regression analysis was performed to quantify τign results from this study.

09 BIOMASS FUELS↗
DOE OSTI2025

Depletion Benchmark of the AFIP-7 Experiment in the Advanced Test Reactor

Reactor physics depletion benchmarks for low-enriched uranium fuel are limited in number. In particular, there is very limited data for LEU benchmarks for U-10Mo (Uranium-10% Molybdenum) plate fuel developed for use in U.S. high-performance research reactors (USHPRR). USHPRR includes the Advanced Test Reactor (ATR), Advanced Test Reactor Critical Facility (ATR-C), High Flux Isotope Reactor (HFIR), University of Missouri Research Reactor (MURR), Massachusetts Institute of Technology Reactor (MITR), and National Bureau of Standards Reactor (NBSR) at the National Institute of Science and Technology. These reactors are fueled with high-enriched uranium dispersed fuel in a silicon/aluminum matrix. In support of conversion to a HALEU fuel, qualification of U-10Mo formed into a monolithic foil is being performed. Fuel qualification involves irradiated fueled specimens in the ATR. The irradiation tests provide an opportunity to benchmark depletion capabilities of reactor physics codes in support of the ATR operation, as well as develop benchmarks that can be used by other institutions to benchmark other reactor physics codes. This report documents the development of a benchmark model of the irradiation of the ATR Full -size plate In center flux trap Position 7 (AFIP-7) experiment.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Modeling Autonomous Vehicle-Targeted Aggressive Merging Behaviors in Mixed Traffic Environment

Promising advances in Autonomous Vehicle (AV) technology have fueled industry and research fields to dedicate significant effort to the study of the integration of AVs into the traffic network. This study focuses on the transition phase between all Human Driven Vehicles (HDVs) in the network to all AVs, where these different vehicle types coexist in a mixed traffic environment. This paper investigates the potential impacts of aggressive merging behaviors by human drivers on traffic performance in a mixed environment. For this, three vehicle types – AVs, HDVs, and Aggressive HDVs (AHDVs) – are modeled in an open-source microscopic traffic simulation model, SUMO. In the developed simulation, the AHDVs are modeled to emulate aggressive merging behaviors in front of AVs at a merge section of a freeway exit ramp. Several experiments are used to study the impact of such behavior. Results show travel time gains by AHDVs at the expense of AVs and HDVs.

Bae, JongIn↗
DOE OSTI2023

Catalytic upgrading of ethanol to C8+ distillate range ethers via Guerbet coupling and etherification

In this presentation we describe the catalytic approaches for conversion of ethanol into diesel fuel ethers. This involves first alcohol oligomerization, followed by acid-catalyzed dehydration. As we will show in this presentation, ethanol can be converted to higher linear and α-branched alcohols by C-C coupling reactions (ethanol oligomerization) as well as to high molecular weight esters by C-O coupling reactions with Cu/MgxAlOy (CuHT) catalysts. Alcohols may be converted to ethers via bimolecular dehydration in a subsequent step. We have identified more than 160 number of species in the products including alcohols, esters, aldehydes, ketones, and olefins. Alcohols range from C4 to C10. Both alcohols and esters follow a Schulz-Flory chain growth model. We show the relationship between the catalyst properties (BET surface area, acid and base site count and Cu loading and synthesis method) and the performance in the reactions. We also show that physical mixtures of CuHT and HT can have similar product selectivity of low loading CuHT catalysts. The selectivity towards diesel fuel precursor compounds (hereafter ‘DFPC’) increased with conversion until reaching a plateau at high ethanol conversion (~70%). Alcohol selectivity follows a Schultz-Flory distribution at all studied conversions, and that adsorbed ethanol-derived species may undergo surface oligomerization into 1-butanol and higher alcohols before desorbing in a chain-growth mechanism. Zeolite catalysts convert the C4+ alcohols into C8+ ethers in both batch and continuous flow reactors. Selectivities of up to 80% to C8+ ethers at around 70% conversion using a single pass continuous flow system are achieved. The final product feedstocks obtained from etherification have been used in technoeconomic (TEA) and lifecycle analysis (LCA), which indicate a reduction in greenhouse gas (GHG) emissions of 50% relative to conventional diesel and diesel fuel prices that are lower than biodiesel. These final feedstocks are undergoing engine testing to elucidate the physiochemical properties and compare well to diesel #2 ASTM standards.

Huber, George↗
DOE OSTI2024

Density functional theory (DFT) study of UF 6 hydrolysis: reaction pathways, spectroscopy, and chemical kinetics

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the gas-phase reaction mechanism and associated chemical kinetics are poorly understood. During the performance period we undertook development of a state-of-the-art ab initio gas-phase chemical kinetics simulation workflow to model the hydrolysis of uranium hexafluroride (UF 6 ). In doing so, we addressed several outstanding issues in the theoretical treatment of uranium-containing systems. At the outset it was unclear how to generate accurate estimates of kinetic and thermodynamic data for U-containing chemical reactions. Generation of such data has been made routine. Prior to our work, the literature associated with UF 6 hydrolysis were disparate and inaccurate. This body of work provides a modern and comprehensive theoretical assessment of the reaction mechanism, molecular clustering towards deposition, and chemical kinetics. New methodological implementations and software integrations resulting from this work are also highlighted. As much as possible, our predictions were validated against experimental data including particle morphologies, vibrational spectroscopy, atomization enthalpies, and kinetic rate constants. Nevertheless, we were unable to reconcile kinetic measurements with high-accuracy simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

BISON microstructure-based pulverization criterion in high burnup structure

To improve the economics of commercial nuclear power production, utilities are seeking to increase the allowable burnup limit of UO$_2$ fuel. One of the main factors that contributes to the current burnup limit of 62 GWd/MTU in commercial light water reactors (LWRs) is the risk of fine fragmentation or pulverization during a loss of coolant accident (LOCA). Pulverization primarily occurs at high burnups, especially when the high burnup structure (HBS) has formed. To allow the industry to pursue increased burnup and develop mitigation strategies, it is essential to have improved capability to predict the onset of pulverization. However, the mechanism of pulverization is not well understood, and the existing predictive capabilities implemented in the BISON fuel performance code are empirical in nature. In this report, mesoscale simulations are used to improve understanding of the formation mechanism of the HBS and how it responds during a LOCA transient, and inform development of a BISON pulverization criterion. A phase-field model was used to simulate the evolution of bubble pressure as a result of HBS formation. The simulations showed that gas atoms diffuse from grain interiors to the new grain boundaries created during HBS formation, and diffuse rapidly along these grain boundaries to reach existing bubbles. This causes an increase in bubble pressure in existing bubbles, leading to bubble growth during steady-state operation. To simulate the response of HBS bubbles to a LOCA transient, a newly developed phase-field model was used; in agreement with preliminary results from FY20, bubble size did not change significantly during the duration of the transient. A phase-field fracture model was used to study fragmentation patterns in the HBS, including using input from the phase-field model as initial conditions. Phase-field fracture simulations were used to determine a pulverization criterion for BISON. A function for the critical pressure for pulverization to occur was fit to data from the phase-field fracture simulations, and this function was implemented as a material property in BISON. For comparison, an analytical criterion for pulverization was developed and implemented within the same material property.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗
DOE OSTI2024

Experimental Covariance Determination for Critical Integral Experiments

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. In general, uncertainty quantification techniques ignore correlations between experiments and shared parts. Experiments, such as the TEX (Thermal/Epithermal eXperiments) campaigns, consist of many shared parts, such as the ‘Jemima’ HEU fuel plates, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes an intuitive method of determining the covariance for each of the experimental components, providing a correlation for each family of parts across the multiple cases examined within a benchmark. A proof-of-principle study using the TEX-HEU experimental campaign was performed and verified that the correlations can be calculated with information commonly found in the ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. This study showed that the introduction of model and experimental covariances reduces the χ 2 per degree of freedom from 2.203 to 1.179, indicating that the omission causes overly pessimistic bias quantifications. This technique can be seamlessly integrated to current benchmark evaluations as well as reevaluations of legacy benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Computational Modeling of Graphite Degradation due to Molten Salt Infiltration and Wear

Molten-salt reactors (MSRs) represent a promising next-generation reactor design, with graphite serving as a moderator and/or reflector in several designs. However, due to limited experimental data and operational experience, a technical understanding of the structural integrity of graphite in molten salt environments remains incomplete. This report presents a modeling-based evaluation of graphite degradation in MSR environments, focusing on the effects of salt infiltration in fuel salt-based designs and surface wear in pebble bed reactor designs. The objective of this study is to enhance understanding of the structural integrity challenges posed by these degradation mechanisms and to provide a framework for assessing graphite behavior in MSRs. The first part of the report investigates the phenomenon of molten salt infiltration into graphite. This infiltration occurs when molten salt permeates the interconnected pore structure of the graphite moderator, driven by factors such as pressure differentials and the physical properties of both the salt and graphite. The infiltration process is influenced by characteristics of the pore structure, viscosity of the molten salt, and the interfacial energies between the graphite, salt, and the atmosphere within the graphite pore. Utilizing a coupled multiphysics modeling approach with Grizzly software, the study evaluates the stress induced by internal heat sources due to infiltration, which can lead to structural concerns. This evaluation is crucial for understanding how infiltration affects the mechanical integrity of graphite components in MSRs. The study considers the Molten-Salt Reactor Experiment (MSRE) graphite stringer geometry due to the availability of relevant data. Through detailed finite element analysis, the study examines stress distributions at varying infiltration percentages, revealing that stress levels increase with higher amounts of infiltration. Rare-event simulations, using the parallel subset simulation (PSS) framework, further quantify the failure probabilities under input uncertainties, with a user-specified failure metric. The PSS framework also identifies critical input parameters that significantly affect the stress values, including infiltration amount, thermal conductivity, and power density. Additionally, considering realistic reactor scenarios, the analysis was performed to account for the combined effects of radiation and infiltration, and modeling strategies on how to analyze new reactor designs or new graphite grades are discussed. The second part of the report focuses on wear mechanisms in pebble bed-based MSRs. As graphite fuel pebbles interact with the graphite reflector block, wear can result in material loss and the formation of surface defects, which may act as stress concentrators. A similar multiphysics modeling framework is employed to assess the impact of wear on the structural integrity of graphite components. This study considers a generic fluoride-cooled high-temperature reactor (gFHR) design due to the availability of comprehensive data. Worst-case scenario dimensions of the reflector blocks were analyzed under thermal and radiation conditions. Subsequently, wear in the form of idealized pits and grooves is modeled on the inner surface of the graphite block, with the maximum stress from previous simulations. The simulations show that groove-type defects are more detrimental than pits, leading to higher stress concentrations. Considering worst-case simulation scenarios and experimental wear rates, it was determined that the formation of a surface defect critical enough to affect the stress may not be possible in a gFHR design. Overall, the findings of this research contribute to the development of robust modeling tools for predicting graphite behavior under various operational conditions in MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Characterization of the Aerosol Source Term in Dry Storage Canisters

As long-term dry storage of used nuclear fuel at independent spent fuel storage installations (ISFSI) trends toward the de facto back end of the US fuel cycle, it becomes appropriate to investigate potential degradation and dispersion scenarios for suitable risk mitigation purposes. Pitting and subsequent stress corrosion cracking of the canister wall is currently viewed as a potential scenario leading to a through-wall pathway for contamination to be transferred from within the storage container to the surrounding environment. While stress corrosion cracking measurements are currently underway to further characterize this scenario, a parallel effort endeavors to perform a consequence analysis of conditions in which through wall cracks are indeed formed. This effort consists of engineering scale modeling using the GOTHIC and MELCOR software packages along with experimental depletion and penetration tests.

spent fuel storage, aerosol deposition, Stress Cor↗