Engineering topics
Sun, Xin
Publications and source records attributed to Sun, Xin.
Multiphase flow simulations of a moving fluidized bed regenerator in a carbon capture unit
To accelerate the commercialization and deployment of carbon capture technologies, computational fluid dynamics (CFD)-based tools may be used to model and analyze the performance of carbon capture devices. This work presents multiphase CFD-based flow simulations for the regeneration device responsible for extracting CO 2 from CO 2 -loaded sorbent particles before the particles are recycled. The use of solid particle sorbents in this design is a departure from previously reported systems, where aqueous sorbents are employed. Another new feature is the inclusion of a series of perforated plates along the regenerator height. The influence of these plates on sorbent distribution is examined for varying sorbent holdup, fluidizing gas velocity, and particle size. The residence time distribution of sorbents is also measured to classify the low regime as plug flow or well-mixed flow. The purpose of this work is to better understand the sorbent flow characteristics before reaction kinetics of CO 2 desorption can be implemented.
Microstructure Based Modeling of β Phase Influence on Mechanical Response of Cast AM Series Mg Alloys
Magnesium alloys have become popular alternatives to aluminums and steels for the purpose of vehicle light-weighting. However, Mg alloys are hindered from wider application due to limited ductility as well as poor creep and corrosion performance. Understanding the impact of microstructural features on bulk response is key to improving Mg alloys for more widespread use and for moving towards truly predicting modeling capabilities. This study focuses on modeling the intrinsic features, particularly volume fraction and morphology of beta phase present, of cast Mg alloy microstructure and quantifying their impact on bulk performance. Computational results are compared to experimental measurements of cast plates of Mg alloy with varying aluminum content.
Migration of defect clusters and xenon-vacancy clusters in uranium dioxide
The possible transition states, minimum energy paths and migration mechanisms of defect clusters and xenon-vacancy defect clusters in uranium dioxide have been investigated using the dimer and the nudged elastic-band methods. The nearby O atom can easily hop into the oxygen vacancy position by overcoming a small energy barrier, which is much lower than that for the migration of a uranium vacancy. A simulation for a vacancy cluster consisting of two oxygen vacancies reveals that the energy barrier of the divacancy migration tends to decrease with increasing the separation distance of divacancy. For an oxygen interstitial, the migration barrier for the hopping mechanism is almost three times larger than that for the exchange mechanism. Xe moving between two interstitial sites is unlikely a dominant migration mechanism considering the higher energy barrier. A net migration process of a Xe-vacancy pair containing an oxygen vacancy and a xenon interstitial is identified by the NEB method. We expect the oxygen vacancy-assisted migration mechanism to possibly lead to a long distance migration of the Xe interstitials in UO2. The migration of defect clusters involving Xe substitution indicates that Xe atom migrating away from the uranium vacancy site is difficult.
Carbon Capture Simulation Initiative: A Case Study in Multi-Scale Modeling and New Challenges
Abstract: Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry and universities that is developing and deploying a suite of multi-scale modeling and simulation tools including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamic (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.
A Mechanism-based Model for Deformation Twinning in Polycrystalline FCC Steel
Deformation twinning, a common and important plastic deformation mechanism, is the key contributor to the excellent combination of strength and ductility in twinning-induced plasticity (TWIP) steel. In the open literature, a significant amount of research has been reported on the microstructural characteristics of deformation twinning and its influence on the overall deformation behavior of TWIP steel. In this study, we examine the feasibility of a mechanism-based crystal plasticity model in simulating the microstructural level deformation characteristics of TWIP steel. To this end, a model considering both double-slip and double-twin is developed to investigate the stress-strain behavior and local microstructural features related to the formation and growth of micro-twins in low stacking fault energy (SFE) TWIP steel. The twin systems are described as pseudo-slips that can be activated when their resolved shear stress reaches the corresponding critical value. A hardening law that accounts for the interaction among the slip and twin systems is also developed. Numerical simulations for dDifferent mesh sizes and single crystal patch tests under different loading modes are carried out to verify the modeling procedure. Our simulation results reveal that, despite its simple nature, the double-slip/double-twin model can capture the key deformation features of TWIP steel, including twin volume fraction evolution, continuous strain hardening, and the final fracture in the form of strain localization.
Bayesian Treed Multivariate Gaussian Process with Adaptive Design: Application to a Carbon Capture Unit
Computer experiments (numerical simulations) are widely used in scientific research to study and predict the behavior of complex systems, which usually have responses consisting of a set of distinct outputs. The computational cost of the simulations at high resolution are often expensive and become impractical for parametric studies at different input values. To overcome these difficulties we develop a Bayesian treed multivariate Gaussian process (BTMGP) as an extension of the Bayesian treed Gaussian process (BTGP) in order to model and evaluate a multivariate process. A suitable choice of covariance function and the prior distributions facilitates the different Markov chain Monte Carlo (MCMC) movements. We utilize this model to sequentially sample the input space for the most informative values, taking into account model uncertainty and expertise gained. A simulation study demonstrates the use of the proposed method and compares it with alternative approaches. We apply the sequential sampling technique and BTMGP to model the multiphase flow in a full scale regenerator of a carbon capture unit. The application presented in this paper is an important tool for research into carbon dioxide emissions from thermal power plants.
Modeling of TWIP Steel Tensile Behavior with Crystal Plasticity Finite Element Method
This is the short paper we presented at MRS 2014, and we turned it into an AMR paper.
Verification of sub-grid filtered drag models for gas-particle fluidized beds with immersed cylinder arrays
The accuracy of coarse-grid multiphase CFD simulations of fluidized beds may be improved via the inclusion of filtered constitutive models. In our previous study (Sarkar et al., Chem. Eng. Sci., 104, 399-412), we developed such a set of filtered drag relationships for beds with immersed arrays of cooling tubes. Verification of these filtered drag models is addressed in this work. Predictions from coarse-grid simulations with the sub-grid filtered corrections are compared against accurate, highly-resolved simulations of full-scale turbulent and bubbling fluidized beds. The filtered drag models offer a computationally efficient yet accurate alternative for obtaining macroscopic predictions, but the spatial resolution of meso-scale clustering heterogeneities is sacrificed.
Effects of Constituent Properties on Performance Improvement of a Quenching and Partitioning Steel
In this paper, a two-dimensional microstructure-based finite element modeling method is adopted to investigate the effects of material parameters of the constituent phases on the macroscopic tensile behavior of Q&P steel and then to do a computational materials design approach for its performance improvement. For this purpose, a model Q&P steel is first produced and various experiments are then performed to characterize the steel. Actual microstructure-based model is generated based on the information from EBSD, SEM and nano-indentation test, and the material properties for the constituent phases are determined based on the initial constituents’ properties from HEXRD test and the subsequent calibration of model prediction to tensile test results. Influence of various material parameters of the constituents on the macroscopic behaviors is then investigated by separately adjusting them by small amount. Based on the observation on the respective influence of constituents’ material parameters, a new set of material parameters are devised, which results in better performance in ductility. The results indicate that various material parameters may need to be concurrently adjusted in a cohesive way in order to improve the performance of Q&P steel. In summary, higher austenite stability, less strength difference between the phases, higher hardening exponents of the phases are generally beneficial for the performance improvement. The information from this study can be used to devise new Q&P heat-treating parameters to produce the Q&P steels with better performance.
Correlations between Nanoindentation Hardness and Macroscopic Mechanical Properties in DP980 Steels
Multiphase advanced high strength steels (AHSS) are being increasingly used in the automotive industry due to their low cost, good availability and excellent combination of strength and ductility. There is a keen interest from the automotive and steel industry for more fundamental understandings on the key microstructure features influencing the macroscopic properties, i.e., tensile properties, hole-expansion ratio and localized formability of AHSS. In this study, the micro- and macro-level properties for eight commercial DP980 steels are first characterized and quantified with various experimental methods. Correlations between macroscopic-level properties and relationships between various micro- and macro- properties for these steels are then established based on the experimental measurements. It is found that, despite their differences in their chemistry, processing parameters and sheet thickness, the eight DP980 steels do have common microstructural level properties governing their specific macroscopic properties in terms of strength, elongation and hole expansion performance.
Molecular Dynamics Simulation of Thermodynamic Properties in Uranium Dioxide
In the present study, we investigated the thermodynamic properties of uranium dioxide (UO2) by molecular dynamics (MD) simulations. As for solid UO2, the lattice parameter, density, and enthalpy obtained by MD simulations were in good agreement with existing experimental data and previous theoretical predictions. The calculated thermal conductivities matched the experiment results at the midtemperature range but were underestimated at very low and very high temperatures. The calculation results of mean square displacement represented the stability of uranium at all temperatures and the high mobility of oxygen toward 3000 K. By fitting the diffusivity constant of oxygen with the Vogel-Fulcher-Tamman law, we noticed a secondary phase transition near 2006.4 K, which can be identified as a ‘‘strong’’ to ‘‘fragile’’ supercooled liquid or glass phase transition in UO2. By fitting the oxygen diffusion constant with the Arrhenius equation, activation energies of 2.0 and 2.7 eV that we obtained were fairly close to the recommended values of 2.3 to 2.6 eV. Xiangyu Wang, Bin Wu, Fei Gao, Xin Li, Xin Sun, Mohammed A. Khaleel, Ademola V. Akinlalu and Li Liu
Predicting Tensile Stretchability of Trimmed AA6111-T4 Sheets
An integrated manufacturing process simulation framework has been developed to predict the trimmed edge tensile stretchability of AA6111-T4 sheets by incorporating the burr geometry, damage, and plastic strain from trimming simulations into subsequent tensile stretchability simulations. The influence of the trimming die clearances on the predicted tensile stretching ductility (stretchability) is studied and quantitatively compared with experimental measurements. Stretchability is found to decrease with increasing cutting clearances, and simulation results have successfully captured experimentally observed edge crack initiation and failure mode variations for different trimming clearances. Subsequent computational sensitivity studies reveal that while deburring of previously trimmed edges has little influence on tensile stretchability, removal of trimmed edge initial plastic strain may significantly enhance the subsequent trimmed edge stretchability.
Edge Fracture Prediction ofTraditional and Advanced Trimming Processes for AA6111-T4 Sheets
This work examines the traditional and advanced trimming of AA6111-T4 aluminum sheets with finite element simulations. The Rice-Tracy damage model is used for the simulation with damage parameters estimated from experimental observation of grain aspect ratio near the fracture surface of trimmed parts. Fine meshes at the shearing zone, adaptive meshing, and adaptive contact techniques are used to accurately capture the contact interactions between the sharp corner of the trimming tools and the blank to be trimmed. To the knowledge of the authors, these are the first trimming simulations that can predict the effects of shearing clearance on burr heights with quantitative accuracy for AA6111-T4 aluminum sheets. In addition, the models have also accurately reproduced the crack initiation site as well as burr and sliver formation mechanisms observed experimentally.
Mechanistic Based DEM Simulation of Particle Attrition in a Jet Cup
The attrition of particles is a major industrial concern in many fluidization systems as it can have undesired effects on the product quality and on the reliable operation of process equipment. Therefore, to accomodate the screening and selection of catalysts for a specific process in fluidized beds, risers, or cyclone applications, their attrition propensity is usually estimated through jet cup attrition testing, where the test material is subjected to high gas velocities in a jet cup. However, this method is far from perfect despite its popularity, largely due to its inconsistency in different testing set-ups. In order to better understand the jet cup testing results as well as their sensitivity to different operating conditions, a coupled computational fluid dynamic (CFD) - discrete element method (DEM) model has been developed in the current study to investigate the particle attrition in a jet cup and its dependence on various factors, e.g. jet velocity, initial particle size, particle density, and apparatus geometry.
Non-classical nuclei and growth kinetics of Cr precipitates in FeCr alloys during ageing
In this manuscript, we quantitatively calculated the thermodynamic properties of critical nuclei of Cr precipitates in FeCr alloys. The concentration profiles of the critical nuclei and nucleation energy barriers were predicted by the constrained shrinking dimer dynamics (CSDD) method. It is found that Cr concentration distribution in the critical nuclei strongly depend on the overall Cr concentration as well as temperature. The critical nuclei are non-classical because the concentration in the nuclei is smaller than the thermodynamic equilibrium value. These results are in agreement with atomic probe observation. The growth kinetics of both classical and non-classical nuclei was investigated by the phase field approach. The simulations of critical nucleus evolution showed a number of interesting phenomena: 1) a critical classical nucleus first shrinks toward its non-classical nucleus and then grows; 2) a non-classical nucleus has much slower growth kinetics at its earlier growth stage compared to the diffusion-controlled growth kinetics. 3) a critical classical nucleus grows faster at the earlier growth stage than the non-classical nucleus. All of these results demonstrate that it is critical to introduce the correct critical nuclei in order to correctly capture the kinetics of precipitation.
Precipitates of Cr at Σ3 <110> {112} GB in α-Fe
Precipitates of Cr at Σ3 <110> {112} GB in α-Fe have been studied using molecular dynamics with a two-band embedded atomic model potential. The accumulation and segregation of Cr atoms and the evolution of the GB depend on local Cr concentration and temperature. At the early stage, with the existence of vacancies, the strong attraction of Cr with the GB core provides a pathway for Cr atoms to quickly accumulate within the GB core. With the increase of Cr concentration, the size of Cr dilute precipitates increases dramatically. And the strong segregation of Cr at the GB is observed, when Cr concentration reach 20%. Also, the size of Cr precipitates increases with increasing the temperatures from 300 K to 1000 K. The accumulation and segregation of Cr atoms at the GB lead to significant deformation of the GB structure and the formation of GB steps, causing the displacement and broadening of the GB.
Predicting Flaw-Induced Resonance Spectrum Shift with Theoretical Perturbation Analysis
Resonance inspection is an emerging non-destructive evaluation (NDE) technique which uses the resonance spectra differences between the good part population and the flawed parts to identify anomalous parts. It was previously established that finite-element (FE)-based modal analysis can be used to predict the resonance spectrum for an engineering scale part with relatively good accuracy. However, FE-based simulations can be time consuming in examining the spectrum shifts induced by all possible structural flaws. This paper aims at developing a computationally efficient perturbation technique to quantify the frequency shifts induced by small structural flaws, based on the FE simulated resonance spectrum for the perfect part. A generic automotive connecting rod is used as the example part for our study. The results demonstrate that the linear perturbation theory provides a very promising way in predicting frequency changes induced by small structural flaws. As the flaw size increases, the discrepancy between the perturbation analysis and the actual FE simulation results increases due to nonlinearity, yet the perturbation analysis is still able to predict the right trend in frequency shift.