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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineering-scale Modeling of High-Temperature Creep and Creep Crack Growth in Alloy 316H

This document demonstrates completion of the goals described in the technical narrative of the Department of Energy’s Industry Funding Opportunity Announcement (iFOA) project entitled “Modeling and Simulation Development Pathways to Accelerating KP-FHR Licensing,” which relates to the development and demonstration of capabilities for conducting engineering-scale simulations of Alloy 316H components under high-temperature conditions. This work encompassed two major aspects: integrating and testing constitutive models for the creep response of 316H at high temperatures, and developing tools for modeling creep crack growth (CCG) in 316H. Two classes of constitutive models were used in this effort: phenomenological models based on behavior observed at the engineering scale, and reduced-order models (ROMs) that represent the nonlinear response of mesoscale models that capture the sensitivity to material microstructure and processing. Likewise, the approaches employed for CCG modeling considered both simplified engineering approaches and detailed simulations of creep and damage ahead of the crack tip. These developments, which were performed by utilizing the Grizzly code as well as the open-source libraries it depends on, strengthen Grizzly’s ability to support licensing and safety analyses of high-temperature reactor components.

316H↗
DOE OSTI2025

Investigating the Effect of Water on the Mechanical Properties of Cellulose from Multiscale Molecular Dynamics Simulations

Classical molecular dynamics (MD) simulations provide insight into the structure and physicochemical properties of materials with atomic resolution. However, the length and time scales accessible to atomistic MD are orders of magnitude smaller than many relevant processes such as the response of a bulk material to experimentally accessible strain rates, which presents challenges when comparing models to experimental measurements. Bottom-up coarse-graining provides a means for systematically mapping atomistic information to lower resolution models to increase the length and time scales achievable by simulation. Cellulose is an abundant carbohydrate biopolymer with applications to many fields of research, such as materials science and renewable energy, due to its desirable mechanical properties and viability for conversion into biofuel. The effect of moisture content on the Young's modulus of cellulose is of special interest due to its native environment often being in the hydrated secondary plant cell wall and the grinding energy requirements for biomass feedstock preprocessing. The current work investigates the effects of water solvent on the Young's modulus of cellulose calculated from coarse-grained MD mechanical stress simulations. The coarse-grained model was parametrized from atomistic MD calculations of cellulose-cellulose potentials of mean force using umbrella sampling techniques under vacuum and solvated conditions. The Young's moduli of the coarse-grained cellulose assemblies parametrized from cellulose in vacuum or solvated in water were computed via mechanical stress simulations to highlight the importance of capturing solvent interactions for modeling the mechanical behavior of cellulose.

BASIC BIOLOGICAL SCIENCES,RADIATION PROTECTION AND↗
DOE OSTI2023

Hybrid Particle Method for Computational Shock Physics

A long-standing area of research for Eulerian shock wave physics codes has been the treatment of strength and damage for materials. Here we present a method that will aid in the analysis of strength and failure in shock physics applications where excessive diffusion of critical variables can occur and control the solution outcome. Eulerian methods excel for large deformation simulations in general but are inaccurate in capturing structural behavior. Lagrangian methods provide better structural response, but finite element meshes can become tangled. Therefore, a technique for merging Lagrangian and Eulerian treatments of material response, within a single numerical framework, was implemented in the Multiple Component computational shock physics hydrocode. The capability is a Lagrangian/Eulerian Particle Method (LEPM) that uses particles to interface a Lagrangian treatment of material strength with a more traditional Eulerian treatment of the Equation of State (EOS). Lagrangian numerical methods avoid the advection diffusion found in Eulerian methods, which typically strongly affects strength constitutive law internal variables, such as equivalent plastic strain, porosity and/or damage. The Lagrangian capability enhances existing capabilities and permits accurate predictions of high rate, large deformation and/or shock of mechanical structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer–Meshkov instability

Capturing the dynamic response of a material under high strain-rate deformation often demands challenging and time consuming experimental effort. While shock hydrodynamic simulation methods can aid in this area, a priori characterizations of the material strength under shock loading and spall failure are needed in order to parameterize constitutive models needed for these computational tools. Moreover, parameterizations of strain-rate-dependent strength models are needed to capture the full suite of Richtmyer–Meshkov instability (RMI) behavior of shock compressed metals, creating an unrealistic demand for these training data solely on experiments. Herein, we sweep a large range of geometric, crystallographic, and shock conditions within molecular dynamics (MD) simulations and demonstrate the breadth of RMI in Cu that can be captured from the atomic scale. In this work, yield strength measurements from jetted and arrested material from a sinusoidal surface perturbation were quantified as Y RMI = 0.787 ± 0.374 GPa, higher than strain-rate-independent models used in experimentally matched hydrodynamic simulations. Defect-free, single-crystal Cu samples used in MD will overestimate Y RMI , but the drastic scale difference between experiment and MD is highlighted by high confidence neighborhood clustering predictions of RMI characterizations, yielding incorrect classifications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

VERA-Grizzly Ex-Core Calculations: Watts Bar Unit 1 Cycles 1-2

The critical structures that comprise light-water reactor (LWR) nuclear power plants are subjected to operating environments that can challenge their integrity. Structures in close proximity to the reactor core, such as the reactor pressure vessel (RPV) and the biological shield wall, are subjected to high levels of radiation emanating from the core, as well as elevated temperatures. As the US fleet of operating LWRs ages, the effects of these operating environments on the integrity of these structures must be considered to ensure their continued safe operation. Extending the lifetime of commercial reactors and maintaining the aging reactor fleet require accurate prediction of the exposure of ex-core components to neutron and photon radiation. In particular, concrete degradation studies must be performed to evaluate the safety and long-term operation of reactors with lifetime extensions. The concrete reactor bioshield is important for providing radiological protection during operation and must last for the entire lifetime of the reactor. Recent interest in lifetime extensions furthers the need to accurately simulate concrete material degradation in the reactor bioshield. As a result of this need, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded this study to couple its tools, Virtual Environment for Reactor Applications (VERA) and Grizzly. VERA allows users to set up models to calculate time-dependent and fully coupled solutions (with thermal feedback) for ex-core quantities of interest such as vessel and coupon fluence and detector responses for multiple statepoints and cycles. Grizzly is a finite-element application based on the Multiphysics Object Oriented Simulation Environment (MOOSE) framework that is used to enable aging materials calculations. This report highlights the work performed to calculate the fluence in the vessel and concrete for Watts Bar Nuclear Plant Unit 1 (WBN1) Cycles 1 and 2. The fluences obtained from VERA were successfully transferred to Grizzly using a Python script. Four simulations were run with Grizzly: (1) the Mazars model with the initial Young’s modulus being the instantaneous modulus, (2) the Mazars model with the initial Young’s modulus being the delayed modulus, (3) the Mazars model with the initial Young’s modulus being the delayed modulus with the addition of the effects of micro-damage caused by irradiation, and (4) the Mazars model with the initial Young’s modulus being the instantaneous modulus, and with the addition of micro-damage and creep. Details regarding the methods used to obtain the fluence and the statistical errors associated with the VERA Monte Carlo Shift calculations are discussed in greater detail in this report. The results obtained from the four Grizzly models are also presented in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

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

Modeling brittle fracture due to anisotropic thermal expansion in polycrystalline materials

Here, this work investigated brittle fracture of polycrystalline materials due to thermal stresses arising from anisotropic thermal expansion. We used phase-field fracture simulations with the properties of alpha-uranium (α-U) and assumed a linear elastic mechanical response. Three-dimensional simulations were used to predict fracture for various conditions and crystallographic textures. We found that fracture was more pronounced during cooling than during heating because the anisotropy increased with temperature. We also found that the total crack surface area increased with increasing average misorientation, while the net shape change of the material decreased with increasing misorientation. Two-dimensional simulations in which one crystallographic coefficient of thermal expansion (CTE) was set to zero indicated that the expansion behavior in the crystallographic direction with the smallest CTE was the primary cause of fracture.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

What are the Principles Controlling Biomimetic Heteropolymer Secondary Structure? (Final Technical Report)

The goal of the project was to develop improved theories to understand how nonbiological oligomers could be designed to cooperatively fold into 3D structures. These studies would lay the groundwork for materials made of such molecules, making it possible to create controlled and ordered materials for electron transport, efficient protein-like catalysts that work under extreme conditions, and sensors with highly-specific chemical responsiveness. Two different simulation thrusts were investigated, one focused on programs to identify stable low energy folded structures at a coarse-level of description of oligomers, and another to calculate thermodynamics of such oligomers. We used these theories to answer several specific questions about what properties of oligomers lead to cooperative transitions, and to identify how oligomer knots could serve as secondary structure elements. We also carried out significant collaborative investigation with Dr. Samuel Gellman (UW-Madison, National Academy of Sciences member) on stability for foldamers of interest to them. Only one of the experimentally tested foldamers stably folded, which was indicated by simulations as being the most likely to fold. Finally, we developed new theoretical descriptions of foldamers, showing how cooperativity was determined primarily by the entropy difference between the folded and unfolded state. The research did not answer all questions laid out in the original proposal but laid the groundwork for later efforts to design folded oligomers materials with high switchability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analytical homogenization techniques applied to the Fickian diffusion: Effective diffusivity coefficient

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. In this work, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing TRISO particles. An extensive survey on effective thermal conductivity modeling was performed in our previous study, considering a random distribution of mono-sized spherical inclusions in a continuous matrix. Using the analogy between heat conduction and the simplified Fickian diffusion (or fission product species conservation), we can use the same analytical homogenization methods to obtain ETC as for the effective diffusivity coefficient (EDC). We performed several numerical experiments at varying conditions to assess the validity of our hypothesis for EDC calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗
DOE OSTI2021

Quantifying Temperature Dependence of Electronic Band Gaps and Optical Properties in SnO 2 and SnO via First-Principles Simulations

Tin metal oxides SnO x ( x = 1, 2) have gained interest as gas-sensing materials. For their applications as high-temperature sensors, however, a better understanding of their temperature dependence sensing responses is needed. Here, we comparatively quantify the temperature-dependent electronic band gaps and optical properties of SnO 2 and SnO using first-principles calculations. Without considering the temperature effect, SnO 2 and SnO are predicted to have direct and indirect band gaps of 2.18 and 1.66 eV, respectively, at the PBE + U -GGA level that we employed. The temperature effect on the electronic and optical properties is captured by taking account of the electron–phonon interaction. Band gap renormalization with temperature is calculated via the Allen–Heine–Cardona theory. For both oxides, we find a monotonic decrease in the electronic band gap such that renormalization at zero point (0 K) is ~–0.17 and ~–0.52 eV at 1000 K. These results are also analyzed by employing an analytical equation that helps characterize the band gap shift with temperature. In addition, the optical properties at finite temperatures are simulated using the frozen-phonon method that combines electron–phonon coupling with the momentum matrix. As temperature increases, the optical property spectra are smoothed because of the smearing effect, which diminishes optical constants at shorter wavelengths. Our results are of interest for high-temperature functional materials in applications of optical detection.

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

Ettringite hysteresis under sorption from molecular simulations

Highlights: • Hybrid Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations are performed. • Anisotropic large strain coefficient of crystal shrinkage of ettringite is provided. • Entropy increases when ettringite converts into metaettringite. • Sorption-induced stress may lead to columns collapse upon drying. • H-bonds involving OH groups in columns play a role in hysteresis. The response of ettringite under sorption is critical for the utilization of this mineral as an energy storage material and to understand the concrete durability problems associated with ettringite formation. We report molecular simulations directly sampling the osmotic ensemble to understand the sorption processes and structural changes in ettringite-metaettringite transition. Desorption branch and sorption-induced volume changes from simulations agree with the experiments. The structural changes at low relative humidity are analyzed, revealing for the first time details of metaettringite structure. The reversibility under sorption observed experimentally is captured by simulation in the ettringite domain. The reversibility in the conversion of metaettringite into ettringite is not captured by the direct simulations in the osmotic ensemble due to the large volume changes associated with ettringite desorption. Finally, we discuss the role of hydrogen bonds on the hysteresis in ettringite.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗
DOE OSTI2022

Quantification of the effect of uncertainty on impurity migration in PISCES-A simulated with GITR

A Bayesian inference strategy has been used to estimate uncertain inputs to global impurity transport code (GITR) modeling predictions of tungsten erosion and migration in the linear plasma device, PISCES-A. This allows quantification of GITR output uncertainty based on the uncertainties in measured PISCES-A plasma electron density and temperature profiles (n e , T e ) used as inputs to GITR. The technique has been applied for comparison to dedicated experiments performed for high (4 × 10 22 m –2 s –1 ) and low (5 × 10 21 m –2 s –1 ) flux 250 eV He–plasma exposed tungsten (W) targets designed to assess the net and gross erosion of tungsten, and corresponding W impurity transport. The W target design and orientation, impurity collector, and diagnostics, have been designed to eliminate complexities associated with tokamak divertor plasma exposures (inclined target, mixed plasma species, re-erosion, etc) to benchmark results against the trace impurity transport model simulated by GITR. The simulated results of the erosion, migration, and re-deposition of W during the experiment from the GITR code coupled to materials response models are presented. Specifically, the modeled and experimental W I emission spectroscopy data for a 429.4 nm line and net erosion through the target and collector mass difference measurements are compared. Furthermore, the methodology provides predictions of observable quantities of interest with quantified uncertainty, allowing estimation of moments, together with the sensitivities to plasma temperature and density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions

Many materials of interest to Sandia transition from fluid to solid or have regions of both phases coexisting simultaneously. Currently there are, unfortunately, no material models that can accurately predict this material response. This is relevant to applications that "birth stress" related to geoscience, nuclear safety, manufacturing, energy production and bioscience. Accurately capturing solidification and residual stress enables fully predictive simulations of the evolving front shape or final product. Accurately resolving flow of proppants or blood could reduce environmental impact or lead to better treatments for heart attacks, thrombosis, or aneurism. We will address a science question in this proposal: When does residual stress develop during the critical transition from liquid to solid and how does it affect material deformation? Our hypothesis is that these early phases of stress development are critical to predictive simulation of material performance, net shape, and aging. In this project, we use advanced constitutive models with yield stress to represent both fluid and solid behavior simultaneously. The report provides an abbreviated description of the results from our LDRD "Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions," since we have written four papers that document the work in detail and which we reference. We give highlights of the work and describe the gravitationally driven flow visualization experiment on a model yield stress fluid, Carbopol, at various concentrations and flow rates. We were able to collapse the data on a single master curve by showing it was self-similar. We also describe the Carbopol rheology and the constitutive equations of interest including the Bingham-Carreau-Yasuda model, the Saramito model, and the HB-Saramito model including parameter estimation for the shear and oscillatory rheology. We present several computational models including the 3D moving mesh simulations of both the Saramito models and Bingham-Carreau-Yasuda (BCY) model. We also show results from the BCY model using a 3D level set method and two different ways of handling reduced order Hele-Shaw modeling for generalized Newtonian fluids. We present some first ever two-dimensional results for the modified Jeffries Kamani-Donley-Rogers constitutive equation developed during this project. We include some recent results with a successful Saramito-level set coupling that allows us to tackle problems with complex geometries like mold filling in a thin gap with an obstacle, without the need for remeshing or remapping. We report on some experiments for curing systems where fluorescent particles are used to track material flow. These experiments were carried out in an oven on Sylgard 184 as a model polymerizing system. We conclude the report with a summary of accomplishments and some thoughts on follow-on work.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strain localization criteria for viscoplastic geomaterials

This report presents a viscoplastic localization criterion to detect quasi-instantaneous (i.e., load-induced) and delayed (creep-induced) strain localization in rate-dependent solids. The study is based on the theory of controllability and a viscoplastic description of the mechanical response. Analytical precursors of unstable states are defined through systems of ordinary differential equations (OEDs). The use of the proposed criteria is illustrated at the material point level through a set of strain localization analyses simulating active strain localization of a porous rock. In addition, full-field finite element simulations of compression tests conducted under various pressures are reported to demonstrate the role of local unstable viscoplasticity in the spontaneous propagation of deformation bands under stationary boundary conditions. The study shows that the viscoplastic localization criterion maintains a negative sign as long as the behavior is unstable, that is, the rate of deformation is accelerating. The sign switch coincides with the transition to decelerating deformation. The analyses revealed that pulses of overstress always emerge in correspondence with the growth of unstable behavior, and the peak matches the transition to stable behavior. The local responses recovered from full-field analyses were consistent with those observed in analyses at material point level and the predictions of the presented theory.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulation Analysis of Geometry and Material Effects for Dropkinson Bar

The reported research is motivated by the need to address a key issue affecting the Dropkinson bar apparatus. This unresolved issue is the interference of the stress wave reflected from the bar-beam boundary with the measurement of the stress-strain response of a material tested in the apparatus. The purpose of the wave beam that is currently connected to the bar is to dissipate the stress wave, but the portion of the wave reflected from the bar-beam boundary is still significant. First, we focused on understanding which parameters affect the reflected wave's arrival time at a strain gauge. Specifically, we used finite-element numerical simulations with the Sierra/SM module to study the effects of various bar-beam connection fixities, alternative wave beam materials, and alternative geometries of the Dropkinson bar system based on a monolithic design. The conclusion of this study is that a partial reflection always occurs at the bar-beam boundary (or, for a monolithic design, at a point where the bar geometry changes). Therefore, given a fixed total length of the bar, it is impossible to increase the reflected wave's arrival time by any significant amount. After reaching this conclusion, we focused instead on trying to minimize the energy of the reflected stress wave circulating up and down through the bar over a relatively long period of time (10 ms). Once again, we used numerical simulations with the Sierra/SM module to investigate the effects of various bar-beam connection fixities, alternative wave beam materials, and parameters of an asymmetric monolithic design of the bar-and-beam system. This study demonstrated that various parameters can significantly affect the energy of the wave reflections, with the difference between best and worst configurations being about one order of magnitude in terms of energy. Based on the obtained results, we conclude with concrete takeaways for Dropkinson bar users and propose potential directions for future research and optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-pressure hydrogen decompression in sulfur crosslinked elastomers

High-pressure storage and cyclic (de)pressurization of hydrogen gas is known to result in degradation and failure of gas canisters, hoses, linings, and O-rings as the relatively small hydrogen molecule can readily permeate most materials. Hence, identifying material compositions that are less susceptible to hydrogen-induced damage is of significant importance to the hydrogen energy infrastructure. Here, we use classical atomistic molecular dynamics simulations to study hydrogen exposed ethylene-propylene-diene monomer (EPDM) rubber, an elastomer typically used in O-rings. We make chemical modifications to the model by adjusting the crosslink density and report on gas solubility, diffusivity, and molecular restructuring in response to rapid decompression. Our simulations indicate that increases in crosslink density can reduce volumetric expansion during decompression and result in smaller free volume pore sizes. However, these favorable properties for sealing materials come with a tradeoff. At pressure, crosslinks introduce extra free volume, providing potential sites for gas localization, the precursor to cavitation-induced failure.

08 HYDROGEN↗