Structural Sensitivity Analysis and Optimization 1: Linear by Kyung K. Choi, Nam-Ho Kim

By Kyung K. Choi, Nam-Ho Kim

Structural layout sensitivity research issues the connection among layout variables on hand to the layout engineer and structural responses decided through the legislation of mechanics. The dependence of reaction measures comparable to displacement, tension, pressure, normal frequency, buckling load, acoustic reaction, frequency reaction, noise-vibration-harshness (NVH), thermo-elastic reaction, and fatigue lifestyles at the fabric estate, sizing, part form, and configuration layout variables is outlined in the course of the strength rules (governing equations) of structural mechanics. during this 2-volume set, first- and moment- order layout sensitivity analyses are offered for static and dynamics responses of either linear and nonlinear elastic structural structures, together with elasto-plastic and frictional touch problems.

Book I Linear Systems introduces structural layout techniques that come with the CAD-based layout version, layout parameterization, functionality measures, expenditures, and constraints. It additionally discusses layout sensitivity research of linear structural structures, and discrete and continuum layout sensitivity research methods.

About the Authors:

K.K. Choi is a Carver Professor of Mechanical Engineering on the college of Iowa. He teaches within the Mechanical and commercial Engineering division, and is a researcher within the heart for desktop Aided layout. His learn region is in mechanical process research, layout sensitivity research, and reliability dependent layout optimization. He has authored a number of guides and has two times received the ASME most sensible Paper Award. he's an affiliate editor for 4 nationwide and foreign journals, a fellow of ASME, and affiliate fellow of AIAA.

N.H. Kim is an Assistant Professor within the division of Mechanical and Aerospace Engineering on the collage of Florida. His learn quarter is in structural layout optimization, layout sensitivity research, nonlinear structural mechanics, structural-acoustics, and mesh-free method.

Both authors are individuals of a number of expert societies together with the yank Society of Mechanical Engineers, American Institute of Aeronautics and Astronautics, the foreign Society for Structural and Multidisciplinary Optimization, and Society of automobile Engineering.

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Extra info for Structural Sensitivity Analysis and Optimization 1: Linear Systems

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On the other hand, if approximation methods such as the finite element, boundary element, or meshfree method are used to evaluate these terms, then this procedure is called the continuumdiscrete method. The continuum-continuum method provides the exact design sensitivity of the exact model, whereas the continuum-discrete method provides an approximate design sensitivity of the exact model. When FEA is used to evaluate the structural response, then the same discretization method as structural analysis has to be used to compute the design sensitivity of performance measures in the continuum-discrete method.

Solution candidates must satisfy these conditions. 17) and Kg(u) is the positive definite in Zh, although it is not positive definite in all of R6. ” In actual computation, the global variational equation is modified to explicitly eliminate the boundary condition. However, this is not the general case. In many FEA codes, the size of Kg is retained. Instead of explicitly removing rows and columns corresponding to the boundary conditions, equivalent relations are substituted to make Kg positive definite.

Thus, the goal of the design optimization problem is to find a design that minimizes the cost function among all feasible designs. Although design sensitivity analysis is the main focus of this text, because many optimized designs will be presented, design optimization algorithms are briefly introduced in this section. However, this brief discussion is by no means a complete treatment of optimization methods. For a more detailed treatment, refer to [10] through [12]. Most gradient-based optimization algorithms are based on the mathematical programming method, which requires the function values and sensitivity information at given design variables.

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