Seongmin Chang

A Study on the Sequential Multiscale Homogenization Method to Predict the Thermal Conductivity of Polymer Nanocomposites with Kapitza Thermal Resistance

In this study, a sequential multiscale homogenization method to characterize the effective thermal conductivity of nano particulate polymer nanocomposites is proposed through a molecular dynamics(MD) simulations and a finite element-based homogenization method. The thermal conductivity of the nanocomposites embedding different-sized nanoparticles at a fixed volume fraction of 5.8% are obtained from MD simulations. Due to the Kapitza thermal resistance, the thermal conductivity of the nanocomposites decreases as the size of the embedded nanoparticle decreases. In order to describe the nanoparticle size effect using the homogenization method with accuracy, the Kapitza interface in which the temperature discontinuity condition appears and the effective interphase zone formed by highly densified matrix polymer are modeled as independent phases that constitutes the nanocomposites microstructure, thus, the overall nanocomposites domain is modeled as a four-phase structure consists of the nanoparticle, Kapitza interface, effective interphase, and polymer matrix. The thermal conductivity of the effective interphase is inversely predicted from the thermal conductivity of the nanocomposites through the multiscale homogenization method, then, exponentially fitted to a function of the particle radius. Using the multiscale homogenization method, the thermal conductivities of the nanocomposites at various particle radii and volume fractions are obtained, and parametric studies are conducted to examine the effect of the effective interphase on the overall thermal conductivity of the nanocomposites.

An efficient method for fluid/structure interaction analysis considering nonlinear structural behavior

Fluid/structure interaction (FSI) analysis is necessary to predict the response of a system in which aerodynamic pressure causes deformation of the structure, and vice versa. In dealing with a nonlinear behavior of the structure, however, a simple iterative algorithm of aerodynamic analysis with structural analysis yields no accurate results since aerodynamic pressure need to be changed in accordance with the deformation of structures. In this study, we explore an efficient and accurate method for integrating FSI analysis into structural nonlinear systems. During the course of nonlinear structural analysis, loading conditions are periodically updated by aerodynamic analysis. The accuracy and efficiency of the method is demonstrated with a high-aspect-ratio flexible wing of Global Hawk.

Hierarchical strategies of optimization for structural system identification based on the condensation method

In the system identification using finite element method (FEM), system responses of overall degree of freedoms (DOFs) are necessary. Because of the limitation of sensor and other experiment equipment, the responses of unspecified DOFs have to be contained in the design variables. This increase of the design variable makes difficult to solve the inverse problem. It is one of the solutions about the problem of limited responses that the responses of unspecified DOFs are represented by the responses of specified DOFs, using the condensation method. In the previous study, we applied iterative inverse perturbation method (IIPM) to enhance the efficiency and the solution convergence of the structural system identification problems using the condensation method. So we efficiently identify structural system through solving the optimization problem with design variables which have the same number of elements. However, if the size of problem developed to analyze practical model is increased, the number of design variables which had to be considered in solving process is extremely increased. To identify large structural system, optimization strategy to efficiently change design variables during the iteration of optimization is required. In this study, we suggest two optimization strategies which are adaptive sub-domain method and genetic concept method. Numerical examples are presented to verify the efficiency of the proposed methods and to compare with those methods.

Experimental Examples for Identification of Structural Systems Using Degree of Freedom-Based Reduction Method

Identification method on various structural system has been introduced in many numerical ways to validate complex structures by FEM using experimentally measured data. The objection of this study is to figure out how to identify a perturbed structure model by comparing with measured data based on original FEM data. Identified structure will improve the accuracy and reality to the numerical model by minimizing those differences between two models. Base-line model (original model) is constructed by FEM and will be compared with perturbed model (real model) by IPM (Inverse Perturbation Method). Measured dynamic responses, which is eigenvalues and eigenvectors, will be applied to satisfy the equilibrium and minimize the difference of dynamic responses between base-line model and perturbed model. In experimental examples, due to lack of number of sensor locations which will be located on the model, condensation method is used to restore full model. The equilibrium equation is expressed in terms of measured (primary) and unmeasured (secondary) degree of freedom. In the present study, influence of selection of sensor location and the convergence are considered and selection of sensor algorithm is applied to identification method. Experimental examples demonstrate that the proposed method improves accuracy of identifying perturbed structure model.

Multiscale analysis of polymer nanocomposites considering hyperelasto-plastic behavior

ecently, polymer nanocomposites receive attention in various fields such as academic field and manufacturing field [1]. Merits of polymer nanocomposites come from the interface effect between nanoparticle and polymer matrix. As the particle radius decreases, the interface effect becomes remarkable due to surface-to-volume ratio of nanoparticles. The mechanical behaviors of polymer nanocomposites are enhanced by interface effect. In order to characterize the mechanical properties of interphase, sequential multiscale bridging method is studied by many researchers. There are some studies on the plastic deformation of polymer nanocomposites through the molecular dynamics simulation. Yield point and hardening parameters could be obtained through molecular dynamics simulation, and interphase characteristics could be also obtained through multiscale framework with micromechanics based on Eshelby’s solution [2]. For carbon materials, weakened interface effect could be considered in multiscale model as well. However, a study on the hyperelasto-plastic behavior of polymer nanocomposites is not achieved enough. Nonlinear elastic behavior and plastic behavior of polymer nanocomposites with respect to various filler size are critical factor in view of mechanical design. Especially, in order to handle mechanics of structures with periodic microstructures subjected to large deformation with rotation, macroscopic constitutive equation obtained from twoscale homogenization method should be preceded. In this study, hyperelasto-plastic behavior of polymer nanocomposites are investigated through molecular dynamics simulation. Authors try to elucidate plastic mechanism of polymer matrix and polymer nanocomposites explicitly. With this motivation, unloading simulations and dihedral angle distribution change are conducted as well. Many molecular dynamics results show that change of dihedral conformation of molecules cause the plastic strain of thermoplastic structures [3]. For example, D. Hossain states that dihedral angle change from Gauche state to Trans state is main reason of plastic deformation of amorphous polyethylene in free volume [4]. However, there is no research considering both unloading simulation and plastic mechanism in molecular dynamics simulation. In this study, irreversible characteristics of dihedral angle change under loading and unloading process are identified. More studies to consider plastic mechanism in microscopic viewpoint will be included in future work. The hyperelasto-plastic model about polymer matrix and interphase are not completed in this study. In hyperelastic range, the generalized Mooney-Rivlin model is employed to describe the hyperelastic behavior of Nylon6 polymer matrix. In order to define plastic behavior of polymer matrix, hardening function is constructed by

Stress-diffusion Full Coupled Multiscale Simulation Method for Battery Electrode Design

In this paper, we device stress-diffusion full coupling multiscale analysis method for battery electrode simulation. In proposed method, the diffusive and mechanical properties of electrode material depend on Li concentration are estimated using density function theory(DFT) simulation. Then, stress-diffusion full coupling continuum formulation based on finite element method(FEM) is constructed with the diffusive and mechanical properties calculated from DFT simulation. Finally, silicon nanowire anode charge and discharge simulations are performed using the proposed method. Through numerical examples, the stress-diffusion full coupling method shows more resonable results than previous one way continuum analysis.

A Simulation Study of Artificial Cochlea Based on Artificial Basilar Membrane for Improving the Performance of Frequency Separation

The basilar membrane (BM), one of organs of cochlea, has the specific positions of the maximum amplitude at each of related frequencies. This phenomenon is due to the geometry of BM. In this study, as the part of the research for the development of fully implantable artificial cochlea which is based on polymer membrane, parametric studies are performed to suggest the desirable artificial basilar membrane model which can detect wider range of frequency separation. The vibro-acoustic characteristics of the artificial basilar membrane are predicted through finite element analysis using commercial software Abaqus. Simulation results are verified by comparing with experimental results. Various geometric shapes of the BM and residual stress effects on the BM are investigated through the parametric study to enable a wider detectable frequency separation range.

Structural system identification considering the noise of system response using the optimization strategy

In this paper, the optimization strategy of structural system identification is proposed considering the noise of system responses. In the formulated optimization problem for the system identification, a huge amount of computational resources and time are required to identify the large scale structural system due to the increased design variables in proportion to the number of elements. Moreover, added design variables are necessary to consider the noise of system response obtained from experimental observations. Owing to the many design variables presenting the noise and the large area without structural change, the convergence of solution is deteriorated. In order to overcome these issues, we devise the optimization strategy that selects the significant design variables and reduces the number of design variables. The proposed method reduce required computational resources and calculation time and improve the solution convergence through the discarding the design variables that disturb the solution convergence. The efficiency of the proposed method is verified through numerical examples with pre- assumed noise.