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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A thermodynamics-based damage model for the non-linear mechanical behavior of SiC/SiC ceramic matrix composites in irradiation and thermal environments

A damage model is developed and validated with experimental data for the non-linear mechanical behavior of SiC/SiC composite materials in nuclear applications. Cyclic thermal and mechanical loading associated with neutron irradiation effects of these composites leads to wide-spread and progressive micro-cracking that leads to loss of thermal conductivity and further enhancement of thermo-mechanical damage. A physics-based model of wide-spread micro-cracking is developed within the thermodynamic framework of continuum damage mechanics. Evolution equations for damage parameters that describe the growth of continuum damage are developed, where the material variables are obtained from experiments. The model novelty is in coupling mechanical, thermal, and irradiation damage through a consistent thermodynamic framework, including loss of thermal conductivity due to the evolution of mechanically induced micro-cracks. A number of thermo-mechanical experiments were conducted to confirm model assumptions. The model is shown to be validated with out-of-pile experiments, and then implemented using commercial finite element code COMSOL to the fuel cladding problem with normal and high radiation dose cases.

Materials Science↗
DOE OSTI2020

Very massive tracers and higher derivative biases

Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. Herein we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, highly massive tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement with the prediction: at $z$ = 0, for all tracers, we are able to match the power spectra up to $k ≃$ 0.28$h$ Mpc -1 , as well as a small set of about 10 2 bispectra triangles up to $k ≃$ 0.17$h$ Mpc -1 . We also discuss the limitations of our study and some avenues to pursue to further establish these findings.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Numerical simulation of compressible fluid-dynamics in the chamber of inertial fusion energy systems

Here, this paper aims to establish new and innovative modeling capabilities for analyzing chambers in Inertial Fusion Energy (IFE) systems. IFE is emerging as a promising method to achieve fusion power production, but several challenges must be overcome to develop an IFE pilot plant or deploy commercial IFE systems. These challenges are both theoretical and technical, encompassing a deeper understanding of the underlying physical phenomena and the development of new technologies and materials. One of the needs is to develop mathematical models to describe IFE systems and numerical tools to simulate them. This paper contributes to this endeavor by presenting a new OpenFOAM solver for IFE systems, focusing on gas dynamics in their chambers. The analysis and development of chamber designs will play a significant role in the transition from single-shot experiments to high-repetition rates, as there is a need to protect the chamber walls from the intense radiation fields produced by fusion reactions. A promising design option, normally referred to as thick wall chamber design, consists in using lithium or molten salt jet arrays within the chamber. A critical phenomenon is the venting of high-pressure gases from the center to the external part of the chamber, passing through the blanket array. This process involves the propagation and attenuation of strong pressure waves, requiring suitable modeling approaches for compressible fluid-dynamics. The solver proposed in this work implements a multi-material hydrodynamics model tailored to accurately describe the non-linear propagation of pressure waves while avoiding numerical oscillation issues typical of high-velocity compressible simulation. This solver is verified against numerical test cases, validated against experimental data, and applied to the analysis of the High-Yield Lithium-Injection Fusion-Energy (HYLIFE-I) concept. The relevance of this paper is threefold. Firstly, it contributes to developing and testing modeling approaches for compressible fluid-dynamics phenomena, with specific focus on the new and unexplored topic of IFE thick-liquid-wall blanket modeling. Secondly, it marks one of the first applications of the OpenFOAM library in the research field of IFE systems. Finally, the investigated problem is of practical interest for IFE developers, as it provides useful indications about relevant phenomena in pressure wave propagation in the chamber of these systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Emission line predictions for mock galaxy catalogues: a new differentiable and empirical mapping from DESI

ABSTRACT We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii], and [O iii]) from a galaxy’s rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman’s rank correlation coefficient ρs > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo-z’s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Life cycle assessment of railway ties fabricated with ductile cementitious composites and carbonation curing

This paper evaluates the lifecycle economic and environmental benefits of implementing CO 2 utilization and storage within advanced engineered cementitious composite (ECC) railway ties. Using CO 2 -treated ECC ties can yield lifecycle benefits primarily due to enhanced material properties – increased lifespan in this case – instead of due to the stored CO 2 that would otherwise enter the atmosphere. Sequestration-based policies such as 45Q in the United States would therefore not incentivize deployment of ECC railway ties, despite their considerable CO 2 avoidance opportunities. To reach these conclusions, cradle-to-grave lifecycle models were developed for ECC ties and conventional concrete ties and evaluated under 1000 possible use-phase scenarios. The models incorporated premature tie failures – consistent with real-world observations – that were used to study a wide range of non-linear impacts arising from the random nature of tie failures and replacements. The results show that past studies that neglected premature failure of ties may have underestimated lifecycle greenhouse gas (GHG) emissions of concrete rail ties by nearly three times. Overall, servicing a track with ECC ties instead of concrete ties can reduce the lifecycle costs and GHG emissions by 12% and 21% respectively, based on median values of 1000 model run results. The expected benefits would be larger for entities like Amtrak that plan to expand concrete tie infrastructure despite significant challenges with premature concrete tie failures. Furthermore, the results of this study suggest that the lifespan of ECC ties needs to be at least 25% longer than concrete ties to achieve net lifecycle benefits. The possibility of this should be tested and confirmed under real-world conditions.

42 ENGINEERING↗
DOE OSTI2024

Scale-Bridging Optimization Framework for Desalination Integrated Produced Water Networks

In this work, we develop a Pyomo-based non-linear optimization strategy that includes rigorous MVR models. The detailed desalination unit is integrated into the multiperiod produced water network problem using the trust region filter (TRF) method. TRF decomposes the integrated problem into a master problem consisting of the network variables and a simplified surrogate model for the detailed desalination unit. The surrogate is updated using zero and first-order corrections from the optimal solution of the detailed models at every iteration. This framework allows us to co-optimize the design of the desalination units and operating policy for the multiperiod network. A common design is ensured across all periods using global capacity constraints. We validate the solution obtained using the TRF method by solving the full integrated problem for small network instances and show our results on real case studies on produced water networks from the Permian and Appalachian basins. In this work, we describe our TRF formulation, give details on our implementation in Pyomo, and analyze the results obtained by solving the optimization problem using IPOPT. We also present a discussion on the computational efficiency and scaling using the TRF approach against a full-scale integration of the rigorous models within the water network.

Naik, Sakshi↗
DOE OSTI2018

Evaluation of non-invasive biomonitoring of 2,4-Dichlorophenoxyacetic acid (2,4-D) in saliva

The objective of this study was to evaluate the potential for noninvasive biomonitoring of 2,4-dichlorophenoxyacetic acid (2,4-D) in saliva. Using an in vitro rat salivary gland epithelial cell (SGEC) system, a collection of experiments investigating chemical protein binding, temporal and directional transport, as well as competitive transport with para-aminohippuric acid (PAH), a substrate for renal organic anion transporters, was conducted to identify cellular transport parameters required to computationally model salivary transport of 2,4-D. Additionally, a physiological protein gradient was implemented to mimic physiologically relevant concentrations of protein in rat plasma and saliva, and under these conditions the transfer of 2,4-D was markedly slower, driven by increased protein binding (i.e. reduced free 2,4-D species available to cross salivary barrier). The rate of transfer was directly proportional to the amount of unbound 2,4-D and demonstrated no indication of active transport. An in vivo assessment of 2,4-D exposure in rats revealed a non-linear protein binding response in plasma, indicating saturated protein binding and increased levels of free 2,4-D species at higher doses. A strong correlation between concentrations in saliva and free unbound species in plasma was observed (Pearson correlation coefficient = 0.95). Saliva:plasma 2,4-D ratios measured in vivo (0.0079) were comparable over dose, but significantly different than ratios measured in vitro (physiological conditions) (0.034), possibly due to 2,4-D concentrations in saliva not being at equilibrium with 2,4-D concentrations in blood, as well as physiological features absent in in vitro settings (e.g. blood flow). We demonstrated that 2,4-D is consistently transported into saliva using both in vitro and in vivo models, making 2,4-D a potential candidate for human non-invasive salivary biomonitoring. Further work is needed to understand whether current sensor limits of detection are sufficient to measure occupationally relevant exposures.

Carver, Zana A.↗
DOE OSTI2023

Improving initialization and evolution accuracy of cosmological neutrino simulations

Neutrino mass constraints are a primary focus of current and future large-scale structure (LSS) surveys. Non-linear LSS models rely heavily on cosmological simulations — the impact of massive neutrinos should therefore be included in these simulations in a realistic, computationally tractable, and controlled manner. Here, a recent proposal to reduce the related computational cost employs a symmetric neutrino momentum sampling strategy in the initial conditions. We implement a modified version of this strategy into the Hardware/Hybrid Accelerated Cosmology Code (HACC) and perform convergence tests on its internal parameters. We illustrate that this method can impart Script $\mathcal{O}$(1%) numerical artifacts on the total matter field on small scales, similar to previous findings, and present a method to remove these artifacts using Fourier-space filtering of the neutrino density field. Moreover, we show that the converged neutrino power spectrum does not follow linear theory predictions on relatively large scales at early times at the 15% level, prompting a more careful study of systematics in particle-based neutrino simulations. We also present an improved method for backscaling linear transfer functions for initial conditions in massive neutrino cosmologies that is based on achieving the same relative neutrino growth as computed with Boltzmann solvers. Our self-consistent backscaling method yields sub-percent accuracy in the total matter growth function. Comparisons for the non-linear power spectrum with the Mira-Titan emulator at a neutrino mass of m ν = 0.15 eV are in very good agreement with the expected level of errors in the emulator and in the direct N-body simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone

Prolonged contact between a corrosive liquid and metal alloys can cause progressive dealloying. For one such process as liquid-metal dealloying (LMD), phase field models have been developed to understand the mechanisms leading to complex morphologies. However, the LMD governing equations in these models often involve coupled non-linear partial differential equations (PDE), which are challenging to solve numerically. In particular, numerical stiffness in the PDEs requires an extremely refined time step size (on the order of 10 -12 s or smaller). This computational bottleneck is especially problematic when running LMD simulation until a late time horizon is required. This motivates the development of surrogate models capable of leaping forward in time, by skipping several consecutive time steps at-once. In this paper, we propose a U-shaped adaptive Fourier neural operator (U-AFNO), a machine learning (ML) based model inspired by recent advances in neural operator learning. U-AFNO employs U-Nets for extracting and reconstructing local features within the physical fields, and passes the latent space through a vision transformer (ViT) implemented in the Fourier space (AFNO). We use U-AFNOs to learn the dynamics of mapping the field at a current time step into a later time step. We also identify global quantities of interest (QoI) describing the corrosion process (e.g., the deformation of the liquid-metal interface, lost metal, etc.) and show that our proposed U-AFNO model is able to accurately predict the field dynamics, in spite of the chaotic nature of LMD. Most notably, our model reproduces the key microstructure statistics and QoIs with a level of accuracy on par with the high-fidelity numerical solver, while achieving a significant 11, 200 × speed-up on a high-resolution grid when comparing the computational expense per time step. Finally, we also investigate the opportunity of using hybrid simulations, in which we alternate forward leaps in time using the U-AFNO with high-fidelity time stepping. We demonstrate that while advantageous for some surrogate model design choices, our proposed U-AFNO model in fully auto-regressive settings consistently outperforms hybrid schemes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

This study aims to implement a hybrid ensemble surrogate machine learning technique in predicting the compressive strength (CS) of concrete, an important parameter used for durability design and service life prediction of concrete structures in civil engineering projects. For this purpose, an experimental database consisting of 1030 records has been compiled from the machine learning repository of the University of California, Irvine. The database was used to train and validate four conventional machine learning (CML) models, namely Artificial Neural Network (ANN), Linear and Non-Linear Multivariate Adaptive Regression Splines (MARS-L and MARS-C), Gaussian Process Regression (GPR), and Minimax Probability Machine Regression (MPMR). Subsequently, the predicted outputs of CML models were combined and trained using ANN to construct the Hybrid Ensemble Model (HENSM). It is observed that the proposed HENSM produces higher predictive accuracy compared to the CML models used in the present study. The predictive performance of all models for CS prediction was compared using the testing dataset and it is found that the HENSM model attained the highest predictive accuracy in both phases. Based on the experimental results, the newly constructed HENSM model is very potential to be a new alternative in handling the overfitting issues of CML models and hence, can be used to predict the concrete CS, including the design of less polluting and more sustainable concrete constructions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Estimating the Electric Fields Driving Lightning Dart Leader Development With BIMAP‐3D Observations

Abstract In this paper, a numerical dart leader model has been implemented to understand the leader's development and the corresponding electric field changes observed by the 3D broadband mapping and polarization (BIMAP‐3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre‐dart‐leader channel has a significant temperature of 3,000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well‐defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

3D lightning mapping↗
DOE OSTI2023

Using the Gerchberg-Saxton algorithm to reconstruct nonmodulated pyramid wavefront sensor measurements

Adaptive optics (AO) is a technique to improve the resolution of ground-based telescopes by correcting, in real-time, optical aberrations due to atmospheric turbulence and the telescope itself. With the rise of Giant Segmented Mirror Telescopes (GSMT), AO is needed more than ever to reach the full potential of these future observatories. One of the main performance drivers of an AO system is the wavefront sensing operation, consisting of measuring the shape of the above mentioned optical aberrations. Aims. The non-modulated pyramid wavefront sensor (nPWFS) is a wavefront sensor with high sensitivity, allowing the limits of AO systems to be pushed. The high sensitivity comes at the expense of its dynamic range, which makes it a highly non-linear sensor. We propose here a novel way to invert nPWFS signals by using the principle of reciprocity of light propagation and the Gerchberg-Saxton (GS) algorithm. We test the performance of this reconstructor in two steps: the technique is first implemented in simulations, where some of its basic properties are studied. Then, the GS reconstructor is tested on the Santa Cruz Extreme Adaptive optics Laboratory (SEAL) testbed located at the University of California Santa Cruz. This new way to invert the nPWFS measurements allows us to drastically increase the dynamic range of the reconstruction for the nPWFS, pushing the dynamics close to a modulated PWFS. The reconstructor is an iterative algorithm requiring heavy computational burden, which could be an issue for real-time purposes in its current implementation. However, this new reconstructor could still be helpful in the case of many wavefront control operations. In conclusion, this reconstruction technique has also been successfully tested on the Santa Cruz Extreme AO Laboratory (SEAL) bench where it is now used as the standard way to invert nPWFS signal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A mixed, unified forward/inverse framework for earthquake problems: fault implementation and coseismic slip estimate

SUMMARY We introduce a new finite-element (FE) based computational framework to solve forward and inverse elastic deformation problems for earthquake faulting via the adjoint method. Based on two advanced computational libraries, FEniCS and hIPPYlib for the forward and inverse problems, respectively, this framework is flexible, transparent and easily extensible. We represent a fault discontinuity through a mixed FE elasticity formulation, which approximates the stress with higher order accuracy and exposes the prescribed slip explicitly in the variational form without using conventional split node and decomposition discrete approaches. This also allows the first order optimality condition, that is the vanishing of the gradient, to be expressed in continuous form, which leads to consistent discretizations of all field variables, including the slip. We show comparisons with the standard, pure displacement formulation and a model containing an in-plane mode II crack, whose slip is prescribed via the split node technique. We demonstrate the potential of this new computational framework by performing a linear coseismic slip inversion through adjoint-based optimization methods, without requiring computation of elastic Green’s functions. Specifically, we consider a penalized least squares formulation, which in a Bayesian setting—under the assumption of Gaussian noise and prior—reflects the negative log of the posterior distribution. The comparison of the inversion results with a standard, linear inverse theory approach based on Okada’s solutions shows analogous results. Preliminary uncertainties are estimated via eigenvalue analysis of the Hessian of the penalized least squares objective function. Our implementation is fully open-source and Jupyter notebooks to reproduce our results are provided. The extension to a fully Bayesian framework for detailed uncertainty quantification and non-linear inversions, including for heterogeneous media earthquake problems, will be analysed in a forthcoming paper.

58 GEOSCIENCES↗
DOE OSTI2019

Energy occupation of waves and structures in 3D compressive MHD turbulence

Abstract Structures and propagating waves are often observed in solar wind turbulence. Their origins and features remain to be uncovered. In this work, we use 3D driven, compressible MHD turbulence simulations to investigate the global signatures of the driven fluctuations in whole spatial and temporal domain. With four-dimensional spatial-temporal (x, y, z, t) Fourier transformations implemented, we have identified two distinct main populations: waves, which satisfy the $\omega -\boldsymbol {k}$ dispersion relations and are propagating; and structures, which satisfy the polarization relations but non-propagating (ω = 0). Whereas the overall turbulent energy spectrum is still consistent with k−5/3, the contributions from waves and structures show very different behaviour in $\boldsymbol {k}$ space, with structures dominating at small k but waves becomes comparable to structures at large k. Overall, the fluctuations in the directions perpendicular to the large-scale mean field $\boldsymbol {B_0}$ are a manifestation of structures, while along the parallel direction, the fluctuations are dominated by waves. Also, a significant portion of the incompressible structures are the Alfvénic nature, and with imbalanced increased, the waves predominantly propagate in one direction and nearly perpendicular to $\boldsymbol {B_0}$. Differentiating the relative contributions from waves and structures could have important implications for understanding the non-linear cascade processes in the inertial range as well as particle-fluctuation interactions at small scales.

Yang, L. P.↗
DOE OSTI2018

Mechanical Behavior of UO 2 at Sub-grain Length Scales: Quantification of Elastic, Plastic and Creep Properties via Microscale Testing

Techniques were developed to measure properties at sub-grain scales using depleted Uranium Oxide (d-UO2) samples heat-treated to obtain different grain sizes and oxygen stoichiometries, through three main tasks: 1) sample processing and characterization, 2) microscale and conventional testing and 3) modeling. Grain size and crystallography were characterized using Scanning Electron Microscopy (SEM), in conjunction with Electron Backscattering Diffraction (EBSD) and Electron Channeling Contrast Imaging (ECCI). Grains were then carefully selected based on their crystallographic orientations to perform ex-situ micromechanical tests with samples machined via Focused Ion Beam (FIB), with emphasis on micro-cantilever bending. These experiments were performed under controlled atmospheres, to insure stoichiometry control, at temperatures up to 700 °C and allowed measurements involving elastic (effective Young’s modulus), plastic (critical resolved shear stresses) and creep (creep strain rates) behavior. Conventional compression experiments were performed simultaneously to compare with the ex-situ measurements and study potential size effects. Modeling was implemented using anisotropic elasticity and inelastic constitutive relations for plasticity and creep based on kinematics and kinetics of dislocation glide that account for the effects of crystal orientation, and stress. The models will be calibrated and validated using the experimental data. This project provided insight on correlations among stoichiometry, crystallography and mechanical behavior in advanced oxide fuels, provided valuable experimental data to validate and calibrate mesoscale fuel performance codes and also a framework to measure sub-grain scale mechanical properties that should be suitable for use with irradiated samples due to small volumes required. The goals and metrics of the ongoing study of thermo-mechanical behavior in depleted uranium dioxide (d-UO 2 ) outlined in this project have been concluded successfully, resulting in: 1) the successful fabrication, processing, and characterization of large-grained samples with various orientations (up to and including single crystals) having stoichiometric and hyper-stoichiometric O/U ratios; 2) formulation, calibration, and validation of a crystal plasticity constitutive model to describe the creep deformation of UO 2 at the sub-grain length scale (single crystal level) at intermediate temperatures; 3) the successful calibration of a crystal plasticity constitutive model to describe the elasto-plastic deformation of microcantilever beams, also at moderate temperatures. Samples were prepared from natural uranium oxide powder of production-quality provided by Areva. The powder was pressed in a die to a pressure of 100 MPa to produce green pellets with no sintering aids, lubricants, or any other additives. The green pellets were then heated up to 1700 °C under ultra-high purity argon atmosphere (~1 ppm O2). The atmosphere was then changed to 79% Argon, 21% O 2 and the temperature was held at 1700 °C for 2 hours to sinter the pellets under oxidative conditions [1] that are known to increase grain growth kinetics in UO 2 [2]. Samples were then cooled down under Ar-4%H2 atmosphere to reduce the samples back to stoichiometric UO 2 . For macro-scale procedures, testing of UO 2 samples with large grains was performed at 1200 °C using a modified load frame capable of applying dead-weight loads to ensure constant stress conditions, while displacement of the sample produced by the applied load was measured with high precision micrometers to obtain strains. Stress steps were used during testing and the strains were monitored to measured creep strain rates under steady state for each level of stress used, so that stress exponents could be obtained. The results of the mechanical testing, along with sample geometry and crystal orientation of the grains in the samples, as well as post-test sample characterization were used to formulate a viscoplastic model to account for steady state (stage II) creep behavior, along with basic assumptions from crystal plasticity and kinematic constraints due to testing fixtures. In the micro-scale, testing of microcantilever beams at temperatures ranging from 25 to 570 °C was performed in-situ with a scanning electron microscope with a special attachment to apply load and measure displacement while the samples were at temperature. The load-displacement curves obtained showed linear behavior before fracture for all temperatures attempted except 570 °C, where clear deviations from non-linearity were observed before fracture. These deviations were consistently observed for all samples tested for a given orientation. A viscoplastic model was used to account for the presence of inelastic strain, along with basic assumptions from crystal plasticity and beam theory. These models were kept as simple as possible, and results from tests performed in a set of samples with a given crystal orientation were used to calibrate the material constants for the model, while results from a different sample set were then used for validation, thus satisfying the conditions of all main tasks within the parameters of this project. Details of these efforts are outlined in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High- temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes ad- vantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗