• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1408-1414
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• 2004

The use of flip-chip technology has many advantages over other approaches for high-density electronic packaging. ACF (anisotropic conductive film) is one of the major flip-chip technologies, which has short chip-to-chip interconnection length, high productivity, and miniaturization of package. In this study, thermal fatigue lift of ACF bonding flip-chip package has been predicted. Elastic and thermal properties of ACF were measured by using DMA and TMA. Temperature dependent nonlinear hi-thermal analysis was conducted and the result was compared with Moire interferometer experiment. Calculated displacement field was well matched with experimental result. Thermal fatigue analysis was also conducted. The maximum shear strain occurs at the outmost located bump. Shear stress-strain curve was obtained to calculate fatigue life. Fatigue model for electronic adhesives was used to predict thermal fatigue life of ACF bonding flip-chip packaging. DOE (Design of Experiment) technique was used to find important design factors. The results show that PCB CTE (Coefficient of Thermal Expansion) and elastic modulus of ACF material are important material parameters. And as important design parameters, chip width, bump pitch and bump width were chose. 2$^{nd}$ DOE was conducted to obtain RSM equation far the choose 3 design parameter. The coefficient of determination ($R^2$) for the calculated RSM equation is 0.99934. Optimum design is conducted using the RSM equation. MMFD (Modified Method for feasible Direction) algorithm is used to optimum design. The optimum value for chip width, bump pitch and bump width were 7.87mm, 430$\mu$m, and 78$\mu$m, respectively. Approximately, 1400 cycles have been expected under optimum conditions. Reliability analysis was conducted to find out guideline for control range of design parameter. Sigma value was calculated with changing standard deviation of design variable. To acquire 6 sigma level thermal fatigue reliability, the Std. Deviation of design parameter should be controlled within 3% of average value.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.716-726
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• 2010

In this research, design optimization of an aircraft wing has been performed using the fully automated Multidisciplinary Design Optimization (MDO) framework, which integrates aerodynamic and structural analysis considering nonlinear structural behavior. A computational fluid dynamics (CFD) mesh is generated automatically from parametric modeling using CATIA and Gambit, followed by an automatic flow analysis using FLUENT. A computational structure mechanics (CSM) mesh is generated automatically by the parametric method of the CATIA and visual basic script of NASTRAN-FX. The structure is analyzed by ABAQUS. Interaction between CFD and CSM is performed by a fully automated system. The Response Surface Method (RSM) is applied for optimization, helping to achieve the global optimum. The optimization design result demonstrates successful application of the fully automated MDO framework.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.229-237
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• 2008

In this research, a MDO(multi-disciplinary design optimization) framework, which integrates aerodynamic and structural analysis to design an aircraft wing, is constructed. Whole optimization process is automated by a parametric-modeling approach. A CFD mesh is generated automatically from parametric modeling of CATIA and Gridgen followed by automatic flow analysis using Fluent. Finite element mesh is generated automatically by parametric method of MSC.Patran PCL. Aerodynamic load is transferred to Finite element model by the volume spline method. RSM(Response Surface Method) is applied for optimization, which helps to achieve global optimum. As the design problem to test the current MDO framework, a wing weight minimization with constraints of lift-drag ratio and deflection of the wing is selected. Aspect ratio, taper ratio and sweepback angle are defined as design variables. The optimization result demonstrates the successful construction of the MDO framework.