Learning continuum-scale models from micro-scale dynamics via Operator Regression.
Abstract not provided.
Patel, Ravi Ghanshyam↗
SEARCH · Engineering Papers
Results for “micro scale models”
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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Exploring Failure of Adhesively-Bonded Joints with Different Void Sizes at the Same Void Volume Fraction through A Micro-scale Numerical Modeling
This paper studied the effects of void sizes on the failure behavior of adhesively-bonded materials under global shear via micro-scale computational modeling. The numerical results indicate that large void sizes with increased distances between them at the same void volume fraction can alleviate the reduced joint strength of a weaker adherend-adhesive interface caused by interfacial voids. However, this is not the case for an adherend-adhesive interface with the interfacial tensile strength being sufficiently higher than the adhesive strength, showing the negligible effect on the joint strength due to various void sizes and the amount of interfacial voids. This preliminary investigation provides insightful information for scaling up the void size in the macro-scale computational modeling of joints, and enhances the understanding of the micro-mechanical adhesion in adherend-adhesive interfaces with different levels of bonding.
Qiao, Yao↗
Bridging Scales to Model Reactive Diffusive Transport in Porous Media
Published by ECS. Two novel scale-bridging algorithms to model reaction-diffusion transport in porous media are presented. The algorithms are based on direct numerical simulations and couple the information of a micro-scale model, which accounts for the large field of view provided by micro X-ray computed tomography (X-ray CT), and a nano-scale model, which locally resolves transport in the fine structure extracted from nano X-ray CT. The micro-scale model is discretized in the through-plane direction into a 1D grid, where effective properties and internal boundaries are determined based on the results from the nano-scale model. The validated algorithms are used to examine transport of oxygen in precious group metal-free electrodes considering both zero- and first-order kinetics. Unlike conventional methods, the results show that the effective diffusivity is not a passive property but increases in regions where the reaction-rate coefficient is large. The proposed algorithms account for the multiscale coupling of reaction-diffusion transport and material microstructure, thus improving the predictions compared to conventional methods.
42 ENGINEERING↗
Determination of permeability for hydrocarbon release due to excavation-induced stress redistribution in rock salt
Due to a stress redistribution after the excavation of an underground tunnel for radioactive waste disposal, an Ed/DZ (excavation disturbed/damaged zone) will be generated in the near field of the opening, resulting in significant changes in the hydraulic and mechanical properties of the rock mass in the zone. Initially more or less randomly distributed hydrocarbons at grain boundaries in rock salt, which sometimes can only be observed with ultraviolet light, can then be mobilised and migrate at a potentially significant rate towards the excavation. Within the international cooperative project DECOVALEX 2019, the migration mechanism of such fluid inclusions in rock salt is being studied intensively. Specifically, a multi-scale modelling strategy has been developed. A macroscale coupled hydro-mechanical modelling of an underground excavation was performed to determine hydraulic and time-dependent deviatoric stress conditions, by taking into account the rock salt creep behaviour. Under the obtained macro-scale constraints, micro-scale modelling of a pathway dilation along halite grain boundaries was performed using different model strategies: a) coupled hydromechanical modelling with a consideration of hydraulic pressure-induced dilatant deformation, b) nonlinear dynamic model taking account of fluid migration, stress-dependent grain boundary wetting and shear-induced dilatancy of salt, and c) phase-field modelling of flow pathway propagation. The permeability increase resulting from the pathway dilation is estimated to be as high as two orders of magnitude. Based on the permeability determined, a series of pressure buildups measured from a borehole with a high hydrocarbon release rate, a total of 430 build-ups within a monitoring time of 938 days, can be simulated with a macro-scale compressible flow model accounting for different zones around the opening.
58 GEOSCIENCES↗
Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling
Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.
Thermal Protection Systems↗
Advancing SiC clad fuel performance model: bridging micro- and macro-scale models and experimental validation
This report presents a workflow for advancing fuel performance modeling of SiC composite cladding for light-water reactors by linking microscale, experimental data-informed finite element analysis with rod-scale fuel performance codes such as BISON. The workflow uses X-ray computed tomography (XCT) to capture the actual geometry and processing-induced defects of as-fabricated SiC composite tube specimens, particularly porosity and wall-thickness variations, and converts the segmented XCT volumes into image-based finite element meshes for high fidelity structural analysis.
Koyanagi, Takaaki [Oak Ridge National Laboratory (↗
Consortium for Production of Affordable Carbon Fibers in the United States (Final Report)
Various feedstocks from coal, petroleum and bio-based acrylonitrile were investigated for their ability to produce carbon fiber within DOE strength (250 ksi), modulus (25 Msi), elongation (>1%) and cost (≤$5/lb) goals for wider utilization in light-weight vehicles for the automotive industry. The overarching approach was to chemically identify and map the various feedstocks, understand the molecular transformation to produce carbon fiber precursors (mesophase for pitch materials of polyacrylonitrile polymer) and how these impact carbon fiber quality. Predictive models were built to relate the feedstocks and precursors to carbon fiber properties using atomistic and micro-scale modeling within ±15%. Using tow-level carbon fiber epoxy composites, carbon fibers tow-level predictions of elastic components of the carbon fibers were also successfully modeled within ±15%, using finite element analysis to confirm single filament carbon fiber properties. These models were validated with tow-level epoxy composite experiments from carbon fibers produced in this study.
01 COAL, LIGNITE, AND PEAT↗
Microstructure Scale Lithium-Ion Battery Modeling: Part I. On Through-Plane Heterogeneity, Impact of Mesh Representation, and Differences between Macro- and Microscale Models
Li-ion battery performance and degradation are strongly correlated with the electrode microstructures and can be modeled at different scales, each with their own limitations. Herein, we compare predictions achieved with a macro- and a micro-scale model, that is, respectively, neglecting or considering the microstructural heterogeneity of the composite electrodes, on virtual numerically generated and real microstructures. While both models are in relative agreement at the low charge rates, differences arise for fast charging scenarios and especially for the real, highly heterogenous, microstructures. The microscale model predicts that electrolyte concentration saturation and depletion, respectively, at the back of the cathode and of the anode are exacerbated, and that lithium plating occurs earlier for real microstructures. The present work also indicates that the mesh representation significantly impacts the microscale model predictions, and consequently that microscale models should add surface area as a parameter to consider explicitly surface roughness. This article is the first of a series, with subsequent entries further investigating in-plane heterogeneities, lithium plating, and the impact of microstructure representativity on model predictions.
25 ENERGY STORAGE↗
A New Modeling Framework for Multi-Scale Simulation of Hydraulic Fracturing and Production from Unconventional Reservoirs
This paper describes a new modeling framework for microscopic to reservoir-scale simulations of hydraulic fracturing and production. The approach builds upon a fusion of two existing high-performance simulators for reservoir-scale behavior: the GEOS code for hydromechanical evolution during stimulation and the TOUGH+ code for multi-phase flow during production. The reservoir-scale simulations are informed by experimental and modeling studies at the laboratory scale to incorporate important micro-scale mechanical processes and chemical reactions occurring within the fractures, the shale matrix, and at the fracture-fluid interfaces. These processes include, among others, changes in stimulated fracture permeability as a result of proppant behavior rearrangement or embedment, or mineral scale precipitation within pores and microfractures, at µm to cm scales. In our new modeling framework, such micro-scale testing and modeling provides upscaled hydromechanical parameters for the reservoir scale models. We are currently testing the new modeling framework using field data and core samples from the Hydraulic Fracturing Field Test (HFTS), a recent field-based joint research experiment with intense monitoring of hydraulic fracturing and shale production in the Wolfcamp Formation in the Permian Basin (USA). Below, we present our approach coupling the reservoir simulators GEOS and TOUGH+ informed by upscaled parameters from micro-scale experiments and modeling. We provide a brief overview of the HFTS and the available field data, and then discuss the ongoing application of our new workflow to the HFTS data set.
58 GEOSCIENCES↗
Modeling Macro- and Micro-Scale Turbulent Mixing and Chemistry in Engine Exhaust Plumes
Simulation of turbulent mixing and chemical processes in the near-field plume and plume-vortex regimes has been successfully carried out recently using a reduced gas phase kinetics mechanism which substantially decreased the computational cost. A detailed mechanism including gas phase HOx, NOx, and SOx chemistry between the aircraft exhaust and the ambient air in near-field aircraft plumes is compiled. A reduced mechanism capturing the major chemical pathways is developed. Predictions by the reduced mechanism are found to be in good agreement with those by the detailed mechanism. With the reduced chemistry, the computer CPU time is saved by a factor of more than 3.5 for the near-field plume modeling. Distributions of major chemical species are obtained and analyzed. The computed sensitivities of major species with respect to reaction step are deduced for identification of the dominant gas phase kinetic reaction pathways in the jet plume. Both the near field plume and the plume-vortex regimes were investigated using advanced mixing models. In the near field, a stand-alone mixing model was used to investigate the impact of turbulent mixing on the micro- and macro-scale mixing processes using a reduced reaction kinetics model. The plume-vortex regime was simulated using a large-eddy simulation model. Vortex plume behind Boeing 737 and 747 aircraft was simulated along with relevant kinetics. Many features of the computed flow field show reasonable agreement with data. The entrainment of the engine plumes into the wing tip vortices and also the partial detrainment of the plume were numerically captured. The impact of fluid mechanics on the chemical processes was also studied. Results show that there are significant differences between spatial and temporal simulations especially in the predicted SO3 concentrations. This has important implications for the prediction of sulfuric acid aerosols in the wake and may partly explain the discrepancy between past numerical studies (that employed parabolic or temporal approximations) and the measured data. Finally to address the major uncertainty in the near-field plume modeling related to the plume processing of sulfur compounds and advanced model was developed to evaluate its impact on the chemical processes in the near wake. A comprehensive aerosol model is developed and it is coupled with chemical kinetics and the axisymmetric turbulent jet flow models. The integrated model is used to simulate microphysical processes in the near-field jet plume, including sulfuric acid and water binary homogeneous nucleation, coagulation, non-equilibrium heteromolecular condensation, and sulfur-induced soot activation. The formation and evolution of aerosols are computed and analyzed. The computed results show that a large number of ultra-fine (0.3--0.6 nm in radius) volatile HSO4 - HO embryos are generated in the near-field plume. These embryos further grow in size by self coagulation and condensation. Soot particles can be activated by both heterogeneous nucleation and scavenging of H2SO4-H2O aerosols. These activated soot particles can serve as water condensation nuclei for contrail formation. Conditions under which ice contrails can form behind aircrafts are studied. The sensitivities of the threshold temperature for contrail formation with respect to aircraft propulsion efficiency, relative humidity, and ambient pressure are evaluated. The computed aerosol properties for different extent of fuel sulfur conversion to S(VI) (SO3 and H2SO4) in engine are examined and the results are found to be sensitive to this conversion fraction.
Menon, Suresh↗
Analyzing the Multiscale Impacts of Implementing Energy-Efficient HVAC Improvements Through Energy Audits and Economic Input–Output Analysis
Abstract Heating, ventilation, and air-conditioning (HVAC) systems are usually an industry’s highest consumer of energy, most of which goes toward space cooling in buildings. Industrial energy-efficiency audits not only benefit manufacturers but also generate significant economic and environmental benefits to localities, states, and the nation. This article analyzes the micro- and macro scale impacts of implementing energy-efficient HVAC systems by integrating the industrial building energy data with the macroeconomic regional economic flow model. Micro-scale data include 10 years of historical energy, cost, and carbon dioxide savings achieved from energy-efficient HVAC implementation offered to manufacturers through industrial energy audits. The data were integrated into the macroeconomic modeling framework to illuminate the cascading regional economic impacts of implementing energy-efficient HVAC recommendations in manufacturing facilities. Results show that if recommendations had been implemented throughout all manufacturers in the region, $656 M energy costs would have been directly saved, 7.8 million metric tons of carbon dioxide emissions would have been avoided, and 4387 jobs could have been created, resulting in a total annual economic impact of $899 M stemming from direct, indirect, and induced impacts. The results offer insight into how industrial energy systems can be designed and provide models for how communities can accomplish a net-zero society.
Energy & Fuels↗
Physics-informed machine-learning model of temperature evolution under solid phase processes
We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.
36 MATERIALS SCIENCE↗
Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)
Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturer (OEM)s. In addition to high strength for safety requirements, superior Self-Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight, and thus improving energy efficiency. The purpose of this project is to extend and validate an existing finite element code, which is based on the Contractor developed macro-micro multi-scale modeling approach, to numerically simulate the three-point bending and clinch test and study the influences of material microstructural characteristics and phase properties on the rivetability. The macro-micro modeling approach begins with a sample scale model and identify the location, which is mostly prone to failure, the deformation history of the boundaries of that location calculated will be used to drive a microstructure-based sub-models where the material microstructure and microscale properties are considered. Using this approach, the wrap-bending failure for two Al alloys are correctly predicted for the first time. This will start with phase I effort of building a framework of macro-micro three point bending test and clinch test of Al10SiMgMn HPDC alloy in the as-cast and T7 heat treated conditions. Those results will then be validated with experimental test results. The phase II effort will involve the utilization of the knowledge learned in phase I to establish the quantitative correlation between the microstructure characteristics and the riveting performance, which will be further used to guide the optimization of HPDC Al alloy microstructure using heat treatment process to achieve sufficient rivetability to join large thin-wall HPDC alloys.
36 MATERIALS SCIENCE↗
Micro-scale Artificial Weave Generation Capabilities for Thermal Protection System Material Modeling
Thermal Protection System (TPS) modeling requires accurate representation and prediction of the thermomechanical behavior of ablative materials. State-of-the-art TPS materials such as Phenolic Impregnated Carbon Ablator (PICA) have a proven flight record and demonstrate exceptional capabilities for handling extreme aerothermal heating conditions. The constant push for lightweight materials that are flexible in their design and performance, and hence allow for a wide range of mission profiles, has led NASA over the past years to develop its Heatshield for Extreme Entry Environment Technology (HEEET). HEEET is based primarily on a dual layer woven carbon fiber architecture and the technology has successfully been tested in arc-jet facilities. These recent developments have sparked interest in the accurate micro-scale modeling of composite weave architectures, to predict the structural response of macro-scale heatshields upon atmospheric entry. This effort can be extended to incorporate in-depth failure mechanics analyses as a result of local thermal gradients or high-velocity particle impact.
Visser, Sander J.↗
Toughening of Boron Carbide Composites by Hierarchical Microstructuring
Due to a unique combination of properties including high hardness, low density, chemical and thermal stability, semi-conductivity, and high neutron absorption, boron carbide (B4C) is a potential candidate for various applications involving extreme environment. However, B4C’s current application is limited because of its low fracture toughness. In this study, a hierarchical microstructure design with features including TiB2 grains and graphite platelets was used to toughen B4C by simultaneously utilizing multiple toughening mechanisms including crack deflection, bridging, and micro-crack toughening. Using field-assisted sintering technology (FAST), B4C composites with dense and hierarchical microstructure were fabricated. Previously, the fracture toughness of fabricated B4C composites was measured at micro-scale using micro-indentation to have up to 56% improvement. In this work, the B4C composites’ fracture toughness was characterized at macro-scale using four-point bending methods and compared with previous results obtained at micro-scale. Micromechanics modeling of fracture behaviors for B4C-TiB2 composites was also performed to evaluate the contributions from experimentally observed toughening mechanisms. From four-point bending tests, B4C composites reinforced with both TiB2 grains (~15 vol%) and graphite platelets (~8.7 vol%) exhibited the highest fracture toughness enhancement from 2.38 to 3.65 MPa∙m^(1/2). The measured values were lower than those obtained using micro-indentation but maintained the general trends. The discrepancy between the indentation and four-point bending test results originated from the complex deformation behaviors triggered by the high contact load during indentation tests. Through micromechanics modeling, introduced thermal residual stress due to thermal expansion mismatch between B4C and TiB2, and weak interphases at B4C-TiB2 boundaries were identified as the main causes for experimentally observed toughness enhancement. These results proved the effectiveness of hierarchical microstructure designs for B4C toughening and can provide reference for the future design of B4C composites with optimized microstructures for further fracture toughness enhancement.
composites↗
A Micro-scale Numerical Investigation of Internal and Interfacial Void Defects in Adhesive on Failure Behavior of Adhesively-Bonded Materials with Rough Surfaces
This paper studied the effects of air void defects on the failure behavior of adhesively-bonded materials under global shear via micro-scale computational modeling. The numerical results indicated that interfacial void defects can largely facilitate interfacial debonding of a weaker adherend/adhesive interface under shear. However, this is not the case for a stronger adherend/adhesive interface, showing the reduction on the nominal shear strength of an adhesive joint is mainly due to internal void defects. The reduced bonding performance due to voids can be improved by leveraging an appropriate surface roughness. This preliminary investigation is a first step to better understand the micro-mechanics of interfacial failure in the adhesion of a roughened/patterned adherend via surface modification(s) and an adhesive, and also shows the importance of minimizing interfacial void defects in particular at a weaker adherend/adhesive interface via different techniques.
Qiao, Yao↗
Modeling Electrokinetics of Oxygen Electrodes in Solid Oxide Electrolyzer Cells
A microscale model is presented in this study to simulate electrode kinetics of the oxygen electrode in a solid oxide electrolyzer cell (SOEC). Two mixed ionic/electronic conducting structures are examined for the oxygen producing electrode in this work: single layer porous lanthanum strontium cobalt ferrite (LSCF), and bilayer LSCF/SCT (strontium cobalt tantalum oxide) structures. A yttrium-stabilized zirconia (YSZ) electrolyte separates the hydrogen and oxygen electrodes, as well as a gadolinium doped-ceria (GDC) buffer layer on the oxygen electrode side. Electrochemical reactions occurring at the two-phase boundaries (2PBs) and three-phase boundaries (3PBs) of single-layer LSCF and bilayer LSCF/SCT oxygen electrodes are modeled under various SOEC voltages with lattice oxygen stoichiometry as the key output. The results reveal that there exists a competition in electrode kinetics between 2PBs and 3PBs, but 3PBs are the primary reactive sites for single-layer LSCF oxygen electrode under high voltages. These locations experience the greatest oxygen stoichiometry variations and are therefore the most likely locations for dimensional changes. By applying an active SCT layer over LSCF, the 2PBs become activated to compete with the 3PBs, thus alleviating oxygen stoichiometry variations and reducing the likelihood of dimensional change. This strategy could reduce lattice structural expansion, proving to be valuable for electrode-electrolyte delamination prevention and will be the focus of future work.
30 DIRECT ENERGY CONVERSION↗
Electro-thermo-mechanical modelling of micro solar sails of chip scale spacecraft in space
Not provided.
Engineering↗