Seonho Cho

Design sensitivity analysis and topology optimization of displacement–loaded non-linear structures

Abstract A continuum-based design sensitivity analysis (DSA) method for geometrically nonlinear systems with nonhomogeneous boundary conditions is developed to topologically optimize the displacement–loaded nonlinear structures. In the adjoint variable method, the solution space requires just homogeneous boundary conditions even if the original system has nonhomogeneous ones. A design sensitivity expression for the instantaneous rigidity functional is derived for the displacement–loaded nonlinear topology optimization. The tangent stiffness is obtained at the end of the equilibrium iterations in the nonlinear analysis of the original system; this stiffness is used in the DSA so that no iteration would be necessary to evaluate the design sensitivity expressions. In force–loaded systems, the solution dose not converge easily because the material distributes sparsely sometimes during optimization. However, when the displacement–loaded system is used, there is no convergence difficulty.

Topological Shape Optimization of Heat Conduction Problems using Level Set Approach

ABSTRACT A topological shape optimization method for heat conduction problems is developed using a level set method. The level set function obtained from the “Hamilton-Jacobi type” equation is embedded into a fixed initial domain to implicitly represent thermal boundaries and obtain the finite-element response and adjoint sensitivity. The developed method minimizes the thermal compliance, satisfying the constraint of allowable volume by varying the implicit boundary. During optimization, the boundary velocity to integrate the Hamilton-Jacobi equation is obtained from the optimality condition. The newly developed method shows no numerical instability and makes it easy to represent topological shape variations.

Green synthesis of gold nanoparticles using chlorogenic acid and their enhanced performance for inflammation.

UNLABELLED Here we developed a novel green synthesis method for gold nanoparticles (CGA-AuNPs) using chlorogenic acid (CGA) as reductants without the use of other chemicals and validated the anti-inflammatory efficacy of CGA-AuNPs in vitro and in vivo. The resulting CGA-AuNPs appeared predominantly spherical in shape with an average diameter of 22.25±4.78nm. The crystalline nature of the CGA-AuNPs was confirmed by high-resolution X-ray diffraction and by selected-area electron diffraction analyses. High-resolution liquid chromatography/electrospray ionization mass spectrometry revealed that the caffeic acid moiety of CGA forms quinone structure through a two-electron oxidation causing the reduction of Au(3+) to Au(0). When compared to CGA, CGA-AuNPs exhibited enhanced anti-inflammatory effects on NF-κB-mediated inflammatory network, as well as cell adhesion. Collectively, green synthesis of CGA-AuNPs using bioactive reductants and mechanistic studies based on mass spectrometry may open up new directions in nanomedicine and CGA-AuNPs can be an anti-inflammatory nanomedicine for future applications. FROM THE CLINICAL EDITOR Gold nanoparticles (Au NPs) have been shown to be very useful in many applications due to their easy functionalization capability. In this article, the authors demonstrated a novel method for the synthesis of gold nanoparticles using chlorogenic acid (CGA) as reductants. In-vitro experiments also confirmed biological activity of the resultant gold nanoparticles. Further in-vivo studies are awaited.

Level Set-Based Topological Shape Optimization of Nonlinear Heat Conduction Problems Using Topological Derivatives

Abstract A level set-based topological shape-optimization method is developed to relieve the well-known convergence difficulty in nonlinear heat-conduction problems. While minimizing the objective function of instantaneous thermal compliance and satisfying the constraint of allowable volume, the solution of the Hamilton–Jacobi equation leads the initial implicit boundary to an optimal one according to the normal velocity determined from the descent direction of the Lagrangian. Topological derivatives are incorporated into the level set-based framework to improve convergence of the optimization process as well as to avoid the local minimum resulting from the intrinsic nature of the shape-design approach.

Antibacterial nanocarriers of resveratrol with gold and silver nanoparticles

This study focused on the preparation of resveratrol nanocarrier systems and the evaluation of their in vitro antibacterial activities. Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) for resveratrol nanocarrier systems were synthesized using green synthetic routes. During the synthesis steps, resveratrol was utilized as a reducing agent to chemically reduce gold and silver ions to AuNPs and AgNPs. This system provides green and eco-friendly synthesis routes that do not involve additional chemical reducing agents. Resveratrol nanocarriers with AuNPs (Res-AuNPs) and AgNPs (Res-AgNPs) were observed to be spherical and to exhibit characteristic surface plasmon resonance at 547 nm and at 412-417 nm, respectively. The mean size of the nanoparticles ranged from 8.32 to 21.84 nm, as determined by high-resolution transmission electron microscopy. The face-centered cubic structure of the Res-AuNPs was confirmed by high-resolution X-ray diffraction. Fourier-transform infrared spectra indicated that the hydroxyl groups and C=C in the aromatic ring of resveratrol were involved in the reduction reaction. Res-AuNPs retained excellent colloidal stability during ultracentrifugation and re-dispersion, suggesting that resveratrol also played a role as a capping agent. Zeta potentials of Res-AuNPs and Res-AgNPs were in the range of -20.58 to -48.54 mV. Generally, against Gram-positive and Gram-negative bacteria, the Res-AuNPs and Res-AgNPs exhibited greater antibacterial activity compared to that of resveratrol alone. Among the tested strains, the highest antibacterial activity of the Res-AuNPs was observed against Streptococcus pneumoniae. The addition of sodium dodecyl sulfate during the synthesis of Res-AgNPs slightly increased their antibacterial activity. These results suggest that the newly developed resveratrol nanocarrier systems with metallic nanoparticles show potential for application as nano-antibacterial agents with enhanced activities.

An efficient global-local hybrid optimisation method using design sensitivity analysis

An efficient global-local hybrid optimisation method is developed combining a genetic algorithm (GA) as a global optimiser and a method of feasible direction (MFD) as a local optimiser. During the global iteration using the GA, the design sensitivity information with respect to design variables is used to perform a what-if study for efficient crossover. After the final global iteration, a local optimisation can be followed to further improve the solution obtained from the GA. The developed global-local hybrid optimisation method is applied to simple mathematical problems to compare the efficiency and accuracy of the proposed method with that of the conventional genetic algorithm. The application of the developed method is also extended to the practical engineering problems, which shows very good and efficient results.

Level Set–Based Topological Shape Optimization of Heat Conduction Problems Considering Design-Dependent Convection Boundary

A level set–based topological shape optimization method considering design-dependent convection boundaries is developed for steady-state heat conduction problems. We embed the level set function obtained from a Hamilton-Jacobi type of equation into a fixed initial domain to implicitly represent thermal boundaries. The effects of the implicit convection boundary obtained from topological shape variations are represented by numerical Dirac delta and Heaviside functions. The method minimizes the thermal compliance of systems by varying the implicit boundary, satisfying the constraint of allowable material volume. During design optimization, the boundary velocity to integrate the Hamilton-Jacobi equation is derived from an optimality condition.

Concentration Effect of Reducing Agents on Green Synthesis of Gold Nanoparticles: Size, Morphology, and Growth Mechanism

Under various concentration conditions of reducing agents during the green synthesis of gold nanoparticles (AuNPs), we obtain the various geometry (morphology and size) of AuNPs that play a crucial role in their catalytic properties. Through both theoretical and experimental approaches, we studied the relationship between the concentration of reducing agent (caffeic acid) and the geometry of AuNPs. As the concentration of caffeic acid increases, the sizes of AuNPs were decreased due to the adsorption and stabilizing effect of oxidized caffeic acids (OXCAs). Thus, it turns out that optimal concentration exists for the desired geometry of AuNPs. Furthermore, we investigated the growth mechanism for the green synthesis of AuNPs. As the caffeic acid is added and adsorbed on the surface of AuNPs, the aggregation mechanism and surface free energy are changed and consequently resulted in the AuNPs of various geometry.

Level Set-based Topological Shape Optimization of Nonlinear Heat Conduction Problems

A level set-based topological shape optimization method is developed for nonlinear heat conduction problems. While minimizing the objective function of instantaneous thermal compliance and satisfying the constraint of allowable volume, solution of the Hamilton-Jacobi equation leads the initial boundary to an optimal one according to the normal velocity field determined from the descent direction of the Lagrangian. To overcome the convergence difficulty in nonlinear problems resulting from introduction of an approximate boundary, an actual boundary is identified by tracking the level set functions and remeshing using Delaunay triangulation. The velocity field outside the actual domain is determined through a velocity extension scheme.

Configuration and sizing design optimisation of powertrain mounting systems

A configuration and sizing design optimisation problem for powertrain mounting systems is formulated. The objective function is to decouple and maximise the component modal kinetic energy of the powertrain subsystem. Natural frequencies and collinear roll vector condition are used as the constraints. Cartesian coordinates and spring rates of the mounts are selected as the design parameters. An automated design optimisation procedure is developed using an optimisation code based on the method of feasible direction (MFD) and MSC/NASTRAN as a finite clement solver. The necessary gradient information is obtained using the central finite difference method. For the obtained optimum model, forced response analyses are performed in engine idling and wheel unbalancing conditions to show that overall accelerations are greatly reduced at the response positions.