Computational Modeling of Functional Materials for Energy Applications
Presentation on Computational Modeling of Functional Materials for Energy Applications
Park, Jongwoo↗
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A High-Rate, Single-Crystal Model including Phase Transformations, Plastic Slip, and Twinning
An anisotropic, rate-dependent, single-crystal approach for modeling materials under the conditions of high strain rates and pressures is provided. The model includes the effects of large deformations, nonlinear elasticity, phase transformations, and plastic slip and twinning. It is envisioned that the model may be used to examine these coupled effects on the local deformation of materials that are subjected to ballistic impact or explosive loading. The model is formulated using a multiplicative decomposition of the deformation gradient. A plate impact experiment on a multi-crystal sample of titanium was conducted. The particle velocities at the back surface of three crystal orientations relative to the direction of impact were measured. Molecular dynamics simulations were conducted to investigate the details of the high-rate deformation and pursue issues related to the phase transformation for titanium. Simulations using the single crystal model were conducted and compared to the high-rate experimental data for the impact loaded single crystals. The model was found to capture the features of the experiments.
36 MATERIALS SCIENCE↗
Geodyn Material Library: Pseudocap models for dry porous tocks
This report describes the second edition of the Pseudocap Strength models for porous rocks implemented in GEODYN material library. The first model was developed in 2007 and calibrated for concrete. Then, the model parameters were calibrated based on triaxial tests reported for limestones and sandstones of various porosities. In these models some key parameters were chosen as functions of the reference porosity,Φ. Since then multiple modifications were implemented in the model, therefore, it has been recalibrated for some common porous materials such as limestones, sandstones, alluvium, tuffs and granite. Two types of models are described in this repot. The first type (called Pseudocap Model or PM) is for rocks from a specific location. Parameters were calibrated for several specific geologic materials. The second type (called Generic Pseudocap Model or GPM) is useful for the sites where only basic information (rock type, porosity) is available. Generic models include built-in correlations between porosities and other mechanical properties observed for certain rock types. The models of both types were validated by comparing not only to quasi-static triaxial tests for these materials but also to shock Hugoniot data and spherical explosion data for some materials. All models were derived in the frame of isotropic plasticity. They are designed to be used in explicit finite element/difference codes. Tangent stiffness tensor is not provided but can be calculated numerically for the model to be used in implicit finite element codes. For an isotropic material the stress can be decomposed into volumetric and deviatoric parts. The volumetric part is modeled using an Equation of state (EOS) which calculates the pressure and the bulk sound speed as functions of the internal specific energy and density. Here a simple, Mie-Gruneisen EOS is presented, but tabulated EOS (LEOS) provided by the library can be used as well. The stress is limited by the yield surface which depends on three invariants of the stress tensor and specific internal energy. In addition, to capture the strain-rate dependence a simple multiplier is used for the yield surface which depends on the equivalent plastic strain rate. The failure surface (the ultimate yield, Y f , defined later) is chosen in the Hoek-Brown form, commonly used in rock mechanics. It includes measurable parameters such as Unconfined Compressive Strength (UCS) as well as scale parameters characterizing the quality of the rock such as GSI (Geologic Strength Index). Thus, even though the model is calibrated for small samples it offers a way to extrapolate the strength to the field scale using geological characterization of the rock mass. The model captures effects of brittle-ductile transition in rocks by introducing a cap multiplier to the yield function. The rate of dilatancy (bulking) is proportional to the slope of the yield surface affected by the cap. Therefore, it takes place only at low confinements when the pressure is less than the brittle-ductile transition pressure, P BD . On the contrary, the porous compaction takes place at pressures higher than P BD . The cap moves as the porosity is compacted or new porosity is generated due to dilatancy. The porous compaction is modeled using an evolution equation which includes deviatoric stress so that the onset of compaction corresponds to the cap surface. The model captures effects of shear-enhanced compaction which is an important for porous rocks. Section 2 describes the modeling framework and Section 3 presents the model calibration procedure. Section 4 compares experimental data for various rocks versus model predictions. The model parameters used for this comparison are given in Appendix. The files with material constants are available with the latest GEODYN material library distribution.
58 GEOSCIENCES↗
CSP ELEMENTS: High-Temperature Thermochemical Storage with Redox-Stable Perovskites for Concentrating Solar Power
This project was motivated by the potential of reducible perovskite oxides for high-temperature, thermochemical energy storage (TCES) to provide dispatchable renewable heat for concentrating solar power (CSP) plants. This project sought to identify and characterize perovskites from earth-abundant cations with high reducibility below 1000 °C for coupling TCES of solar energy to super-critical CO2 (s-CO2) plants that operate above temperature limits (< 600 °C) of current molten-salt storage. Specific TCES > 750 kJ/kg for storage cycles between 500 and 900 °C was targeted with a system cost goal of $15/kWhth. To realize feasibility of TCES systems based on reducible perovskites, our team focused on designing and testing a lab-scale concentrating solar receiver, wherein perovskite particles capture solar energy by fast O2 release and sensible heating at a thermal efficiency of 90% and wall temperatures below 1100 °C. System-level models of the receiver and reoxidation reactor coupled to validated thermochemical materials models can assess approaches to scale-up a full TCES system based on reduction/oxidation cycles of perovskite oxides at large scales. After characterizing many Ca-based perovskites for TCES, our team identified strontium-doped calcium manganite Ca1-xSrxMnO3-δ (with x ≤ 0.1) as a composition with adequate stability and specific TCES capacity (> 750 kJ/kg for Ca0.95Sr0.05MnO3-δ) for cycling between air at 500 °C and low-PO2 (10-4 bar) N2 at 900 °C. Substantial kinetic tests demonstrated that resident times of several minutes in low-PO2 gas were needed for these materials to reach the specific TCES goals with particles of reasonable size for large-scale transport (diameter dp > 200 μm). On the other hand, fast reoxidation kinetics in air enables subsequent rapid heat release in a fluidized reoxidation reactor/ heat recovery unit for driving s-CO2 power plants. Validated material thermochemistry coupled to radiation and convective particle-gas transport models facilitated full TCES system analysis for CSP and results showed that receiver efficiencies approaching 85% were feasible with wall-to-particle heat transfer coefficients observed in laboratory experiments. Coupling these reactive particle-gas transport models to external SolTrace and CFD models drove design of a reactive-particle receiver with indirect heating through flux spreading. A lab-scale receiver using Ca0.9Sr0.1MnO3-δ was demonstrated at NREL’s High Flux Solar Furnace with particle temperatures reaching 900 °C while wall temperatures remained below 1100 °C and approximately 200 kJ/kg of chemical energy storage. These first demonstrations of on-sun perovskite reduction and the robust modeling tools from this program provide a basis for going forward with improved receiver designs to increase heat fluxes and solar-energy capture efficiencies. Measurements and modeling tools from this project provide the foundations for advancing TCES for CSP and other applications using reducible perovskite oxides from low-cost, earth-abundant elements. A perovskite composition has been identified that has the thermodynamic potential to meet the targeted TCES capacity of 750 kJ/kg over a range of temperatures amenable for integration with s-CO2 cycles. Further research needs to explore ways of accelerating effective particle kinetics through variations in composition and/or reactor/receiver design. Initial demonstrations of on-sun particle reduction for TCES show a need for testing at larger scales with reduced heat losses and improved particle-wall heat transfer. The gained insight into particle-gas transport and reactor design can launch future development of cost-effective, large-scale particle-based TCES as a technology for enabling increased renewable energy penetration.
14 SOLAR ENERGY↗
Direct measurement of storage and loss behavior in AFM force–distance experiments using the modified Fourier transformation
Force–distance curve experiments are commonly performed in atomic force microscopy (AFM) to obtain the viscoelastic characteristics of materials, such as the storage and loss moduli or compliances. The classic methods used to obtain these characteristics consist of fitting a viscoelastic material model to the experimentally obtained AFM data. Here, we demonstrate a new method that utilizes the modified discrete Fourier transform to approximate the storage and loss behavior of a material directly from the data, without the need for a fit. Additionally, one may still fit a model to the resulting storage and loss behavior if a parameterized description of the material is desired. In contrast to fitting the data to a model chosen a priori, departing from a model-free description of the material's frequency behavior guides the selection of the model, such that the user may choose the one that is most appropriate for the particular material under study. To this end, we also include modified Fourier domain descriptions of commonly used viscoelastic models.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Parallel Implicit Hydrodynamics with Material Strength for High Explosive Burn Calculations
High explosives are almost always evolving in some form of metal containment vessel. This fact requires that a materials model for the evolution of the metal containment vessel be part of any simulation of the HE. Since the actual form of the strength model to be used is an open question, we incorporate the material strength properties in a relatively agnostic fashion, which will accommodate many strength models. The only restriction is that the stress components be a function of density, specific internal energy and velocities. In addition, the timescales and rates of the chemical reactions in the HE vary between thousands of seconds and nanoseconds. A hydrodynamics capable of operating in anticipation of the eventual violent release of energy via these chemical reactions is a necessity. The central issue in creating a hydrodynamics capable of spanning these timescales is to forgo the use of a Courant time step control necessary in an explicit hydrodynamics. The Courant time-step arises because of characteristic velocities associated with the material, such as the sound speed or, in materials with strength, characteristic longitudinal and transverse speeds associated with compression and shear. The method used to circumvent the need for a Courant time-step limit is to develop an implicit calculation of the advanced particle pressure and shear modulus derived from the conservation laws of mass, momentum and specific internal energy. This process creates the implicit hydrodynamics needed for the HE calculations of interest to this study.
36 MATERIALS SCIENCE↗
LAMMPS Project Report for the Trinity KNL Open Science Period.
LAMMPS is a classical molecular dynamics code (lammps.sandia.gov) used to model materials science problems at Sandia National Laboratories and around the world. LAMMPS was one of three Sandia codes selected to participate in the Trinity KNL (TR2) Open Science period. During this period, three different problems of interest were investigated using LAMMPS. The first was benchmarking KNL performance using different force field models. The second was simulating void collapse in shocked HNS energetic material using an all-atom model. The third was simulating shock propagation through poly-crystalline RDX energetic material using a coarse-grain model, the results of which were used in an ACM Gordon Bell Prize submission. This report describes the results of these simulations, lessons learned, and some hardware issues found on Trinity KNL as part of this work.
36 MATERIALS SCIENCE↗
Scoping assessments and review of sub-scale models in support of DuraMAT Predictive Simulation Capability Area #2
The goal of the DuraMAT Predictive Simulation Capability Area is to develop a suite of modeling and simulation tools to enhance understanding of module-level thermo-mechanical-electrical effects contributing to degradation of solar photovoltaic modules. Since these effects invoke multiple physical mechanisms and take place over greatly varied time- and length- scales, developing a module-level model of sufficient resolution to capture all geometries and physics of interest was expected to be near code capability and computational resource limits. A series of sub-models and workflows were developed to assess physics and material model maturity and the necessary computational capacity for resolving degradation mechanisms of interest. Knowledge gained from these activities help to better scope future development efforts, in line with available computational and code capabilities. This memo serves as the DuraMAT Quarterly Progress Indicator (QPI) for Quarter 3 of Fiscal Year 2017 (Project Quarter 1 / Month 3), and documents completion of Milestone Subtask 2.2.1.
14 SOLAR ENERGY↗
A Theoretical Analysis on the Dynamic Behavior and Electromechanical Response of PZT
Piezoelectric materials are used as a power source in stockpile components for safety and reliability assurances. The objective of this project is to gain insights into the fundamental pressure-induced behavior and electromechanical response of lead zirconate titanate (PZT). Specifically, to establish the basis for an accurate, physics-based material model for robust model-based design to rapidly optimize PZT-based materials and components for performance studies. Established ab-initio methods are used to interrogate and understand the dynamic behavior of PZT as a function of composition (50/50, 65/35, 80/20, 95/5) and dopants (La, Nb) to overcome the costly and time-consuming experimental methodologies. New cold curves for pure and doped single-crystal PZT are obtained as the reference equation-of-state (EOS). A negligible change in the pressure responses was observed for the systems and strains studied. Dielectric and piezoelectric responses of pure and doped single-crystal PZT were also calculated as a function of pressure. For undoped PZT, there is a clear and orderly pressure and composition dependence. For doped PZT, there is a significant increase in the responses, but the behavior is very disordered and inconclusive.
36 MATERIALS SCIENCE↗
Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 6061-T651 Aluminum Alloy from Plate
Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The matters of interest here are the elastic-plastic response and ductile failure behavior of 6061-T651 aluminum alloy under the conditions described above. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of a modular $J_2$ plasticity model with isotropic hardening as well as a ductile failure model. Both included modules that accounted for temperature and strain rate dependence. The models were coupled with an adiabatic heating module to calculate the temperature rise due to the conversion of plastic work to heat. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s as well as four geometries of notched tension specimens and two tests on specimens with shear-dominated deformations. The test data collected allowed the calibration of both the plasticity and the ductile failure models. Most test specimens were extracted from a single piece of plate to maintain consistency. Notched tension tests came from a possibly different plate, but from the same lot. When using the model in structural finite element calculations, element formulations and sizes different from those used to model the test specimens in the calibration are likely to be used. A brief investigation demonstrated that the failure model can be particularly sensitive to the element selection and provided an initial guide to compensate in a specific example.
36 MATERIALS SCIENCE↗
Machine Learning Framework for Modeling Exciton-Polaritons in Molecular Materials
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Material Science↗
Numerical simulations of the Los Alamos gapstick experiment
The gapstick is a high explosive (HE) sensitivity test recently developed at Los Alamos. The experiment design was motivated by the traditional gap test and consists of a series of HE and inert pellets in a rate stick configuration. The inert pellets are made increasingly longer so that eventually the attenuated shock is unable to initiate the next HE pellet. While the gapstick is a mechanically simple experiment it poses several challenges for numerical simulation. In particular, accurately modeling the HE initiation and detonation phenomena requires a reactive burn model with sufficient mesh resolution to capture the reaction scales. In this work, the Scaled Uniform Reactive Front (SURF) and Arrhenius Wescott-Stewart-Davis (AWSD) burn models are used for simulations of a PBX 9501 (95 wt% HMX, 5% binder) gapstick. Furthermore, the material model for the inert pellet material, Polyvinylidene Fluoride (PVDF), has a direct influence on the shock propagation and a new equation of state (EOS) calibration for PVDF is developed using available Hugoniot data. Despite some challenges, the simulations are able to reasonably predict shock transit velocities and detonation failure in the gapstick.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Developing a radiation-aging model for polymeric foam cushions
Motivation: A major component of the A&L constitutive modeling effort over the last couple of years has involved developing a thermal aging model for foam cushions. Through extensive studies of uniaxial compression data, we have established that the Ogden N = 2 Hyperfoam in conjunction with the Tobolsky two-network model [Ref. 4] provides an accurate theoretical framework to describe the results, both for the traditional (stochastic) as well as the AM (3D-printed) foam pads. The results display numerical accuracy over a wide range of compression levels, from low to moderate up to slightly over 90% of lock-up. Over the last few weeks we have been exploring radiation aging data on a specific 3D printed foam, i.e., SE1700 AM FCT foam, to see if the Ogden + Tobolsky model can explain such data as well, and if so, how the various model parameters change as a function of dosage. As this report shows, the answer is indeed yes. We find that the modulus of the second (i.e., induced network) increases nearly proportionally with the radiation dosage, with a smaller sub-linear decrease in the primary shear modulus of the original network. This is consistent with the interpretation that exposure to energetic gamma-radiation is dominated by the formation of new cross-links. Significance: An important goal of A&L modeling efforts is to develop a fully age-aware materials model that can describe the joint effects of commonly present aging drivers like temperature, radiation, humidity, etc. Such a model is necessary to assess the lifetime of essential components like polymeric foams and rubber pads.
36 MATERIALS SCIENCE↗
A crystal plasticity finite element method modeling of Zircaloy with hydride phases based on scanning electron micrographs
This work developed a microstructure-based finite element model to predict the stress state of alloys with second phase inclusions. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. Generation of digital microstructure was achieved through two steps of tessellations using software Neper and Matlab. The process is demonstrated using an example of Zircaloy material with secondary phases of hydrides dispersed within and stress-strain response of Zircaloy containing hydrides was predicted. The constitutive material model for Zircaloy in this study was based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as isotropic elasto-plastic material. A parametric study had been conducted to understand the effect of volume fraction, and lamellae thickness of the hydride phase on the mechanical properties of the overall material. Results can help designers to alter the manufacturing process to obtain the enhanced mechanical properties for components used in nuclear applications made by Zircaloy material.
Kulkarni, Shank S.↗
Using Tabulated Experimental Data to Drive an Orthotropic Elasto-Plastic Three-Dimensional Model for Impact Analysis
An orthotropic elasto-plastic-damage three-dimensional model with tabulated input has been developed to analyze the impact response of composite materials. The theory has been implemented as MAT 213 into a tailored version of LS-DYNA being developed under a joint effort of the FAA and NASA and has the following features: (a) the theory addresses any composite architecture that can be experimentally characterized as an orthotropic material and includes rate and temperature sensitivities, (b) the formulation is applicable for solid as well as shell element implementations and utilizes input data in a tabulated form directly from processed experimental data, (c) deformation and damage mechanics are both accounted for within the material model, (d) failure criteria are established that are functions of strain and damage parameters, and mesh size dependence is included, and (e) the theory can be efficiently implemented into a commercial code for both sequential and parallel executions. The salient features of the theory as implemented in LS-DYNA are illustrated using a widely used composite - the T800S/3900-2B[P2352W-19] BMS8-276 Rev-H-Unitape fiber/resin unidirectional composite. First, the experimental tests to characterize the deformation, damage and failure parameters in the material behavior are discussed. Second, the MAT213 input model and implementation details are presented with particular attention given to procedures that have been incorporated to ensure that the yield surfaces in the rate and temperature dependent plasticity model are convex. Finally, the paper concludes with a validation test designed to test the stability, accuracy and efficiency of the implemented model.
Polymer Matrix Composites↗
Composite laminate failure parameter optimization through four-point flexure experimentation and analysis
Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be defined through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.
36 MATERIALS SCIENCE↗
Simultaneous three-dimensional elemental mapping of Hollandite and Pyrochlore material phases in ceramic waste form materials
In this study, differential X-ray absorption contrast tomography was performed on model ceramic composite systems to image the 3D spatial distributions of Ga and Nd containing phases. The model material systems were fabricated such that they contained two constituent phases. Ga–doped Ba hollandite (Ba 1.33 Ga 2.66 Ti 5.34 O 16 ), and pyrochlore (Nd 2 Ti 2 O 7 ) which are under consideration as nuclear waste immobilization matrices. Two complementary techniques have been used to characterize the 3D distribution of phases. The analysis suggests that the 3D spatial distributions of hollandite and pyrochlore can be readily identified through the distributions Ga and Nd, respectively. These results represent a critical development towards characterizing the complex microstructure inherent to practical materials such as multiphase ceramic composite waste forms. Furthermore, these methods can be applied to elucidate microstructural features that fundamentally determine the performance and properties of complex systems, which is central to the design of durable waste forms as well as many other real materials such fuel cells, batteries, ultra-high temperature ceramics.
36 MATERIALS SCIENCE↗
Application of a Bayesian Framework for Plasticity Model Selection
Interpretable Machine Learning (IML) has performed well when tasked with deriving constitutive material models. However, IML has been shown to prefer models that overfit noise in data, which tends to lead to bloat and a decrease in interpretability. Due to these issues, the ability of IML to reliably derive models that fit the data and are both interpretable and generalizable is limited. A method developed recently has shown promise to improve upon traditional IML by using a Bayesian fitness definition for the evolution of free-form models with non-deterministic parameters. This framework was developed for genetic-programming-based symbolic regression(GPSR) and involves model parameter estimation using Sequential Monte Carlo sampling (SMC).The method has demonstrated a reduction in bloat when dealing with noisy data in comparison to conventional GPSR. The results of this framework applied to stress-strain data for copper show models that more effectively predict the experimental data better than was previously shown with GPSR.
plasticity↗