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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Online Detection of Inter-Turn Winding Faults in Single-Phase Distribution Transformers Using Smart Meter Data

Turn-to-turn faults between primary windings due to insulation degradation are a major cause of distribution transformer failure, and occur due to high levels of stress such as overloading and overheating. An additional consequence of these faults is an increased voltage on the transformer secondary due to effective change in turns ratio. This paper develops a novel method for early detection of insulation degradation and subsequent inter-turn winding failure by monitoring the transformer secondary voltage. The algorithm is based on a cumulative sum (CUSUM) statistic and compares voltages on neighbouring transformers to flag degrading assets. Results obtained from simulation as well as experimental data show that smart meter measurements can be utilized to achieve very high detection accuracy while keeping costs low. Here, the paper also demonstrates the validity of the algorithm in the presence of measurement noise, residential solar power injection etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Pathways and Mechanism of Caffeine Binding to Human Adenosine A 2A Receptor

Caffeine (CFF) is a common antagonist to the four subtypes of adenosine G-protein-coupled receptors (GPCRs), which are critical drug targets for treating heart failure, cancer, and neurological diseases. However, the pathways and mechanism of CFF binding to the target receptors remain unclear. In this study, we have performed all-atom-enhanced sampling simulations using a robust Gaussian-accelerated molecular dynamics (GaMD) method to elucidate the binding mechanism of CFF to human adenosine A 2A receptor (A 2A AR). Multiple 500–1,000 ns GaMD simulations captured both binding and dissociation of CFF in the A 2A AR. The GaMD-predicted binding poses of CFF were highly consistent with the x-ray crystal conformations with a characteristic hydrogen bond formed between CFF and residue N6.55 in the receptor. In addition, a low-energy intermediate binding conformation was revealed for CFF at the receptor extracellular mouth between ECL2 and TM1. While the ligand-binding pathways of the A 2A AR were found similar to those of other class A GPCRs identified from previous studies, the ECL2 with high sequence divergence serves as an attractive target site for designing allosteric modulators as selective drugs of the A 2A AR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗
DOE OSTI2023

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

DEM analysis of the effect of interface transition zone on dynamic splitting tensile behavior of high-strength concrete based on multi-phase model

Highlights: • Crushable aggregates with the real geometry shape are generated by using clump-cluster method. • Flat-Joint Model is adopted as the constitutive law. • The tensile strength is almost not affected by ITZ strength when its strength exceeds 0.8 times that of mortar. • A modified formula that can reflect the functional relationship between the ITZ strength and the TDIF is proposed. The tensile strength is one of the main parameters in the design of concrete structures and has an important influence on the cracking performance and durability of concrete materials. As the weak region in concrete, the strength of the interface transition zone (ITZ) directly affects the dynamic mechanical response of concrete. Meanwhile, considering that the tensile performance of concrete is far weaker than its compressive performance, the study of the strength of ITZ is of great significance to the dynamic tensile fracture characteristics and mechanical properties of concrete. In this paper, a method combining 3D scanning technology and Clump-Cluster was proposed to generate a real geometry shape model of crushable aggregate. On this basis, the 3D discrete element model (DEM) of high-strength concrete was constructed using the Flat-Joint Model (FJM). The effects of the ITZ strength on the failure mode, number of microcracks, tensile strength and strain rate effect of high-strength concrete under strain rates from 0.01/s to 100/s were studied by splitting tensile test. The simulation results indicate that the number of microcracks generated decreases with the increase of ITZ strength, and the proportion of ITZ cracks decreases obviously. When the ITZ strength exceeds the critical value of 0.8 times that of mortar, the tensile strength is almost not affected by ITZ strength. In addition, based on the numerical simulation results, a modified formula that can reflect the functional relationship between the ITZ strength and the dynamic increasing factor of the concrete tensile strength (TDIF) is proposed, and the rationality of the TDIF modified formula is verified.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2020

Data-driven analysis of relight variability of jet fuels induced by turbulence

For safety purposes, reliable reignition of aircraft engines in the event of flame blow-out is a critical requirement. Typically, an external ignition source in the form of a spark is used to achieve a stable flame in the combustor. However, such forced turbulent ignition may not always successfully relight the combustor, mainly because the state of the combustor cannot be precisely determined. Uncertainty in the turbulent flow inside the combustor, inflow conditions, and spark discharge characteristics can lead to variability in sparking outcomes even for nominally identical operating conditions. Prior studies have shown that of all the uncertain parameters, turbulence is often dominant and can drastically alter ignition behavior. For instance, even when different fuels have similar ignition delay times, their ignition behavior in practical systems can be completely different. In practical operating conditions, it is challenging to understand why ignition fails and how much variation in outcomes can be expected. The focus of this work is to understand relight variability induced by turbulence for two different aircraft fuels, namely Jet-A and a variant named C1. A detailed, previously developed simulation approach is used to generate a large number of successful and failed ignition events. Using this data, the cause of misfire is evaluated based on a discriminant analysis that delineates the difference between turbulent initial conditions that lead to ignition or failure. From the discriminant analysis, a compressed sensing algorithm is then applied to help pinpoint the locations of relevant turbulent features. Findings from the discriminant analysis are confirmed with the time history of near kernel properties. Next, a clustering strategy is used to identify ignition and misfire modes. With this approach, it was determined that the cause of ignition failure is different for the two fuels. While it was found that Jet-A is influenced by fuel entrainment, C1 was found to be more sensitive to small scale turbulence features. Finally, a larger variability is found in the ignition modes of C1, which can be subject to extreme events induced by kernel breakdown.

42 ENGINEERING↗
DOE OSTI2023

Probabilistic Evaluation of Geomechanical Risks in CO2 Storage: An Exploration of Caprock Integrity Metrics Using a Multilaminate Model

The probabilistic uncertainty assessment of geomechanical risk—specifically, caprock failure—attributable to CO2 injection, as presented in a simplified hypothetical geological model, was the focus of this study. Our approach amalgamates the implementation of a multilaminate model, the creation of a response surface model in conjunction with the Box–Behnken sampling design, the execution of associated numerical modeling experiments, and the utilization of Monte Carlo simulations. Probability distributions to encapsulate the inherent variability (elastic and mechanical properties of the caprock and reservoir) and uncertainty in prediction estimates (vertical displacement, total strain, and F value) were employed. Our findings reveal that the Young modulus of the caprock is a key factor controlling equivalent total strain but is insufficient as a stand-alone indicator of caprock integrity. It is confirmed that the caprock can accommodate significant deformation without failure, if it possesses a low Young’s modulus and high mechanical strength properties, such as the friction angle and uniaxial compressive strength. Similarly, vertical displacement was found to be an unreliable indicator for caprock integrity, as caprock failure can occur across a broad spectrum of vertical displacements, particularly when both the Young modulus and mechanical strength properties have wide ranges. This study introduces the F value as the most dependable indicator for caprock failure, although it is a theoretical attribute (the shortest distance between the Mohr circle and the nearest failure envelope used to measure the sensitivity to failure) and not physically measurable in the field. Deviatoric stress levels were found to vary based on stress regimes, with the maximum levels observed under extensive and compressive stress regimes. In conjunction with the use of the response surface method, this study demonstrates the efficacy of the multilaminate framework and the Mohr–Coulomb constitutive model in providing a simplified, yet effective, probabilistic model of the mechanical behavior of caprock failure, reducing mathematical and computational complexities.

Energy & Fuels↗
DOE OSTI2020

Numerical Simulation and Experimental Validation of Joint Performance in Aluminum-Steel Lap Welds Formed by Friction Stir Dovetailing

Friction stir dovetailing (FSD) is a new dissimilar material joining process that simultaneously forms a mechanical interlock and metallurgical bond at the dissimilar material interface. This work presents development of a modeling and simulation approach to predict mechanical performance of FSD thick section aluminum to steel joints. A finite element analysis (FEA) was carried out in order to predict the load-carrying capacity and failure location for aluminum thicknesses between 12.7 mm and 50.8 mm with different numbers of dovetails. The numerical results and corresponding experimental investigation are in agreement and suggest that the developed methods can be used effectively for design and analysis of FSD joints using standard FEA tools.

Friction stir dovetailing, Friction stir welding, ↗
DOE OSTI2026

Multiscale study of helium diffusion in Ni-Cr alloys: Short-range trapping versus long-range channeling

Ni-Cr alloys are widely employed as structural materials in fast nuclear reactors but are vulnerable to high-temperature helium (He) embrittlement (HTHE) under fast neutron irradiation. A comprehensive understanding of He diffusion in Ni-Cr alloys, which governs the kinetics of HTHE, is therefore essential for developing resilient materials and preventing failure. In this work, we reveal the underlying mechanisms of He diffusion in pure Ni and Ni-Cr alloys by integrating density functional theory (DFT) with atomic kinetic Monte Carlo (AKMC) simulations. Our findings uncover a non-monotonic dependence of He diffusivity on Cr concentration, contradicting the monotonic trends predicted by DFT-parameterized theories. At low Cr concentrations, He diffusion is dominated by short-range trapping, characterized by multiple trapping sites and a distinct mechanism within the first nearest neighbor of Cr, differing from that in pure Ni. At high Cr concentrations, these local traps become interconnected, forming long-range fast diffusion channels that enhance He mobility. The competition between localized trapping and extended channeling results in a diffusivity that first decreases, then increases with rising Cr content. These atomic-scale insights offer critical guidance for the design of radiation-tolerant Ni-based alloys. Moreover, the combined DFT-AKMC methodology and the concept of random walker diffusion through interconnected energy basins present a broadly applicable framework for studying transport phenomena in disordered systems.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Monitoring Seismic Velocity Changes Across the San Jacinto Fault Using Train‐Generated Seismic Tremors

Abstract Microseismic noise has been used for seismic velocity monitoring. However, such signals are dominated by low‐frequency surface waves that are not ideal for detecting changes associated with small tectonic processes. Here we show that it is possible to extract stable, high‐frequency body waves using seismic tremors generated by freight trains. Such body waves allow us to focus on small velocity perturbations in the crust with high spatial resolution. We report on 10 years of seismic velocity temporal changes at the San Jacinto Fault. We observe and map a two‐month‐long episode of velocity changes with complex spatial distribution and interpret the velocity perturbation as produced by a previously undocumented slow‐slip event. We verify the hypothesis through numerical simulations and locate this event along a fault segment believed to be locked. Such a slow‐slip event stresses its surroundings and may trigger a major earthquake on a fault section approaching failure.

58 GEOSCIENCES↗
DOE OSTI2024

Limiting Rotation Rate of Neutron Stars from Crust Breaking and Gravitational Waves

Abstract Neutron stars are not observed to spin faster than about half their breakup rate. This limiting rotational frequency may be related to the strength of their crusts. As a star spins up from accretion, centrifugal forces stress the crust. We perform finite-element simulations of rotating neutron stars and find that the crust fails at rotation rates about half the breakup rate. Given uncertainties in microphysics, we have not determined the crust configuration after this failure. Instead, we argue that the crust may fail in an asymmetric way and could produce a configuration with a significant ellipticity (fractional difference in moments of inertia). If the ellipticity is large, a rotating star will radiate gravitational waves that may limit further spin-up. These stars may be promising sources for LIGO/VIRGO and next-generation gravitational-wave detectors.

Morales, J. A.↗
DOE OSTI2024

Initial Assessment of CTF for Time-at-Temperature Applications

The US nuclear industry is interested in improving the economics of their fleet of light-water reactors (LWRs) by uprating US plants. One option being considered is to regain lost margin from overly conservative fuel safety limits. The current limit requires avoidance of critical heat flux (CHF) and prevents further operation of fuel that experiences a dry-out in boiling water reactors (BWRs) or departure from nucleate boiling (DNB) in pressurized water reactors (PWRs); however, it has been shown that temporary, mild dry-out of the fuel does not necessarily increase the risk of fuel failure during its normal anticipated operating life. Such mild dry-out or DNB events may occur during a plant anticipated operational occurrence (AOO), such as a locked rotor in a PWR or a pump trip in a BWR. The time-at-temperature (TAT) approach to regulating fuel operation aims to demonstrate that the fuel rod’s integrity is not challenged during such a mild transient that leads to CHF in which the fuel operates at an elevated temperature for a brief period of time. However, implementing this approach will require extensive fuel material experimental data, as well as supporting modeling and simulation (M&S) predictions, to ensure that the predicted fuel response during AOOs, with all applicable uncertainty considered, will not threaten the safety of the fuel during the transient or the remainder of its anticipated lifecycle. To address this need, a comprehensive effort is being proposed that includes generating cladding material data under TAT conditions, assessment of available code capabilities for TAT conditions, development of new mechanistic models, and demonstration of the M&S capabilities for AOOs of interest. This will require a joint effort between the Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuels Campaign (AFC) programs, as well as close collaboration with nuclear industry stakeholders. The outcome of this collaboration will result in development and assessment of capabilities that can be used by the nuclear industry to support qualification of a TAT-based fuel failure criteria safety limit. This report focuses on the thermal hydraulics (T/H) modeling capabilities and summarizes currently available data for validating the T/H subchannel code CTF for TAT conditions, as well as preliminary assessment results of the code. The initial assessment also resulted in implementation of an alternative post-CHF heat transfer package, which has been shown to significantly improve accuracy. This report is not a final assessment and does not consider all available validation data; it is intended that a future assessment will more fully validate the code for this application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Determining Stress in Metallic Conducting Layers of Microelectronics Devices Using High Resolution Electron Backscatter Diffraction and Finite Element Analysis

Delayed failure due to stress voiding is a concern with some aging microelectronics, as these voids can grow large enough to cause an open circuit. Local measurements of stress in the metallic layers are crucial to understanding and predicting this failure, but such measurements are complicated by the fact that exposing the aluminum conducting lines will relieve most of their stress. In this study, we instead mechanically thin the device substrate and measure distortions on the thinned surface using high resolution electron backscatter diffraction (HREBSD). These measurements are then related to the stresses in the metallic layers through elastic simulations. This study found that in legacy components that had no obvious voids, the stresses were comparable to the theoretical stresses at the time of manufacture (≈300 MPa). Distortion fields in the substrate were also determined around known voids, which may be directly compared to stress voiding models. In conclusion, the technique presented here for stress determination, HREBSD coupled with finite element analysis to infer subsurface stresses, is a valuable tool for assessing failure in layered microelectronics devices.

HREBSD↗
DOE OSTI2023

Root Cause Analysis of Degradation in Protonic Ceramic Electrochemical Cell with Interfacial Electrical Sensors Using Data‐Driven Machine Learning

Abstract Protonic ceramic electrochemical cells (PCECs) offer promising paths for energy storage and conversion. Despite considerable achievements made, PCECs still face challenges such as physiochemical compatibility between componenets and suboptimal solid–solid contact at the interfaces between the electrolytes and electrodes. In this study, a novel approach is proposed that combines in situ electrochemical characterization of interfacial electrical sensor embedded PCECs and machine learning to quantify the contributions of different cell components to total degradation, as well as to predict the remaining useful life. The experimental results suggest that the overpotential induced by the oxygen electrode is 48% less than that of oxygen electrode/electrolyte interfacial contact for up to 1171 h. The data‐driven machine learning simulation predicts the RUL of up to 2132 h. The root cause of degradation is overpotential increase induced by oxygen electrode, which accounts for 82.9% of total cell degradation. The success of the failure diagnostic model is demonstrated by its consistency with degradation modes that do not manifest in electrolysis fade during early real operations. This synergistic approach provides valuable insights into practical failure diagnosis of PCECs and has the potential to revolutionize their development by enabling improved performance prediction and material selection for enhanced durability and efficiency.

25 ENERGY STORAGE↗
DOE OSTI2022

Characterization of modeling and experimental data inconsistencies from burst testing for high-burnup commercial fuel rod applications

Fuel fragmentation, relocation, and dispersal are some of the largest issues remaining in the nuclear industry before rod-average burnup can be increased beyond 62 GWd/tU. The issue is primarily related to the potential for fuel to be dispersed into the reactor primary system, which may increase public risk. One way to prevent dispersal is to avoid cladding burst. The objective of this work is to support the high burnup safety case by evaluating cladding burst under high-burnup, full-length fuel rods and to identify uncertainties that could improve model predictions. The results of this analysis will evaluate realistic, prototypic loss-of-coolant accident (LOCA) conditions; support future cladding burst test designs; and inform the development of mechanistic material models. Realistic high-burnup operating conditions were implemented in the BISON fuel performance code to simulate steady-state and LOCA transient fuel rod evolution to the point at which cladding burst occurred. Parametric studies are performed to assess code response to changes in rod internal pressures and heating rates. Results were compared with simulated LOCA experiments to identify inconsistencies between commercial fuel rod analysis and experimental validation. The representative full-length fuel rod LOCA simulation results did not agree with cladding burst tests. Cladding burst tests indicated burst occurring well below (100–150 °C) those calculated in the full-length fuel rod LOCA analysis. Further investigation indicated that the cladding burst tests do not appear to be representative for full-length fuel rods. The inconsistency investigated in this work showed that the differences between the BISON simulation and the experiment's cladding burst conditions arise from an incomplete characterization of the cladding surface temperature, detailed rodlet characterization, lack of cladding strain measurements, and uncertainty in the cladding creep and failure models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Lattice modeling of excavation damage in argillaceous clay formations: Influence of deformation and strength anisotropy

This paper presents modeling of mechanical anisotropy in argillaceous rocks using an irregular lattice modeling approach, namely the rigid-body-spring network. To represent the mechanical anisotropy, new schemes are implemented in the modeling framework. The directionality of elastic deformation is resolved by modifying the element formulation with anisotropic elastic properties. The anisotropy of strength and failure characteristics is facilitated by adopting orientation-dependent failure criteria into the failure model. The verification of the improved modeling procedures is performed against theoretical model predictions for unconfined compression tests with various bedding orientations. Furthermore, excavation damage and fracturing processes in rock formations are simulated for different geomechanical configurations, such as rock anisotropy and tectonic heterogeneity. The simulated excavation damage characteristics are realistic and comparable with the actual field observation at a tunnel located in an argillaceous clay formation. The simulation results provide insights into the excavation damage zone phenomena with an explicit representation of fracturing processes.

58 GEOSCIENCES↗