• Proceedings of the KSME Conference
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• 2001.06c
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• pp.543-547
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• 2001

CAE has been settled down to an indispensable tool for the simulation of a mechanical system according to the development of computer-aided analysis rapidly. Particularly finite element programs have advanced to the one of most valuable things in the filed of CAE due to the remarkable progress in the implementation. But since this analysis tool mostly provides the result of the analysis, it cannot satisfy designers who are seeking for information to improve their designs. Therefore, design sensitivity analysis or optimization module has been incorporated into commercial FEA programs to satisfy the desire of designers since 1990s. Design sensitivity analysis is to compute the rate of change of response with respected to design variable. Design sensitivity analysis is classfied into static design sensitivity analysis, Eigenvalue design sensitivity analysis and dynamic design sensitivity analysis. In this research, it will be presented to nonlinear static design sensitivity analysis formulation and nonlinear static design sensitivity analysis external module based ANSYS have been developed and illustrated an example to verify the developed module.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1248-1253
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• 2003

Sensitivity information has been used for linearization of nonlinear functions in optimization. Basically, sensitivity is a derivative of a function with respect to a design variable. Design sensitivity is repeatedly calculated in optimization. Since sensitivity calculation is extremely expensive, there are studies to directly use the sensitivity in the design process. When a small design change is required, an engineer makes design changes by considering the sensitivity information. Generally, the current process is performed one-by-one for design variables. Methods to exploit the sensitivity information are developed. When a designer wants to change multiple variables with some relationship, the directional derivative can be utilized. In this case, the first derivative can be calculated. Only small design changes can be made from the first derivatives. Orthogonal arrays can be used for moderate changes of multiple variables. Analysis of Variance is carried out to find out the regional influence of variables. A flow is developed for efficient use of the methods. The sensitivity information is calculated by finite difference method. Various examples are solved to evaluate the proposed algorithm.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.492-497
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• 2004

Three methods for design sensitivity such as numerical differentiation, analytical method and semi-analytical method have been developed for the last three decades. Although analytical design sensitivity analysis is exact, it is hard to implement for practical design problems. Therefore, numerical method such as finite difference method is widely used to simply obtain the design sensitivity in most cases. The numerical differentiation is sufficiently accurate and reliable for most linear problems. However, it turns out that the numerical differentiation is inefficient and inaccurate because its computational cost depends on the number of design variables and large numerical errors can be included especially in nonlinear design sensitivity analysis. Thus semi-analytical method is more suitable for complicated design problems. Moreover semi-analytical method is easy to be performed in design procedure, which can be coupled with an analysis solver such as commercial finite element package. In this paper, implementation procedure for the semi-analytical design sensitivity analysis outside of the commercial finite element package is studied and computational technique is proposed, which evaluates the pseudo-load for design sensitivity analysis easily by using the design variation of corresponding internal nodal forces. Errors in semi-analytical design sensitivity analysis are examined and numerical examples are illustrated to confirm the reduction of numerical error considerably.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.12
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• pp.2092-2100
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• 2003

Sensitivity information has been used for linearization of nonlinear functions in optimization. Basically, sensitivity is a derivative of a function with respect to a design variable. Design sensitivity is repeatedly calculated in optimization. Since sensitivity calculation is extremely expensive, there are studies to directly use the sensitivity in the design process. When a small design change is required, an engineer makes design changes by considering the sensitivity information. Generally, the current process is performed one-by-one for design variables. Methods to exploit the sensitivity information are developed. When a designer wants to change multiple variables with some relationship, the directional derivative can be utilized. In this case, the first derivative can be calculated. Only small design changes can be made from the first derivatives. Orthogonal arrays can be used for moderate changes of multiple variables. Analysis of Variance is carried out to find out the regional influence of variables. A flow is developed for efficient use of the methods. A software system with the flow has been developed. The system can be easily interfaced with existing commercial systems through a file wrapping technique. The sensitivity information is calculated by finite difference method. Various examples are solved to evaluate the proposed algorithm and the software system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.508-512
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• 1997

Design sensitivity analysis of Eigen Problem give systematic design improvement information for noise and vibration of a system. Based on reliable results form commercial FE code(UAI/NASTRAN), three computational procedures for design sensitivity analysis of eigen problem are suggested. Those methods are finite difference,design sensitivity analysis using external module and design sensitivity analysis running with NASTRAN. To verify the suggested methods, a numerical example is given and these results are compared with the results from UAI/NASTRAN eigen sensitivity option. We can conclude that design sensitivity coefficient of eigen proplems can be computed outside of the FE code as easy as inside of the FE code.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.149-154
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• 2004

The design sensitivity analysis of Zwicker's loudness with respect to structural sizing design variables is developed. The loudness sensitivity in the critical band is composed of two equations, the derivative of main specific loudness with respect to 1/3-oct band level and global acoustic design sensitivities. The main specific loudness is calculated by using FEM, BEM tools. i.e. MSC/NASTRAN and SYSNOISE. And global acoustic sensitivity is calculated by combining acoustic and structural sensitivity using the chain rule. Structural sensitivity is obtained by using semi-analytical method and acoustic sensitivity is implemented numerically using the boundary element method. For sensitivity calculation, sensitivity analyzer of loudness (SOLO), in-house program is developed. A 1/4 scale car cavity model is optimized to show the effectiveness of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1590-1597
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• 2004

Three methods of design sensitivity analysis for structures such as numerical method, analytical method and semi-analytical method have been developed for the last three decades. Although analytical design sensitivity analysis can provide very exact result, it is difficult to implement into practical design problems. Therefore, numerical method such as finite difference method is widely used to simply obtain the design sensitivity in most cases. The numerical differentiation is sufficiently accurate and reliable fur most linear problems. However, it turns out that the numerical differentiation is inefficient and inaccurate in nonlinear design sensitivity analysis because its computational cost depends on the number of design variables and large numerical errors can be included. Thus the semi-analytical method is more suitable for complicated design problems. Moreover, semi-analytical method is easy to be performed in design procedure, which can be coupled with an analysis solver such as commercial finite element package. In this paper, implementation procedure fur the semi-analytical design sensitivity analysis outside of the commercial finite element package is studied and the computational technique is proposed for evaluating the partial differentiation of internal nodal force, so called pseudo-load. Numerical examples coupled with commercial finite element package are shown to verify usefulness of proposed semi-analytical sensitivity analysis procedure and computational technique for pseudo-load.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.299-306
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• 1998

Design sensitivity analysis of a mechanical system is an essential tool for design optimization and trade-off studies. This paper presents an efficient algorithm for the design sensitivity analysis of railway vehicle systems, using the direct differentiation method. The cartesian coordinate is employed as the generalized coordinate. The governing equations of the design sensitivity analysis are formulated as the differential equations. Design sensitivity analysis of railway vehicle systems is performed to show the validity and efficiency of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.491-496
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• 2010

The direct design modification of problematic component is disallowed in order to sacrifice other major factors such as a stability or a major performance. So, the best design policy is to risvise the immature structural medchanism under the minimal design change as soon as possible. For this paper presents a new design sensitivity analysis based on transmissibility rtio (TR) of response acceleration to find a proper candidate for the minimal design modification. The new sensitivity analysis is based on the fact that the sensitivity of TR over a small design change is inversly proportinal to the magnitude of TR. The theory of proposed design sensitivity analysis is simulated with the variance of TR over a dynamic change. Then, new methodology is appplied for a linear elastic specimen to detect the most sensitive node over a design change using measured accleration data during uni-axial vibration test, The physical verification of the sensitivity method is conducted on the CAE model of a linear elastic specimen by adding concentration mass and the vibration fatigue of the simple specimen is analyzed to estimate the relationship between fatigue behaviors and sensitivity consequences.