Elements of Structural Optimization

The field of structural optimization is still a relatively new field undergoing rapid changes in methods and focus. Until recently there was a severe imbalance between the enormous amount of literature on the subject, and the paucity of applications to practical design problems. This imbalance is being gradually redressed. There is still no shortage of new publications, but there are also exciting applications of the methods of structural optimizations in the automotive, aerospace, civil engineering, machine design and other engineering fields. As a result of the growing pace of applications, research into structural optimization methods is increasingly driven by real-life problems. t-.Jost engineers who design structures employ complex general-purpose software packages for structural analysis. Often they do not have any access to the source program, and even more frequently they have only scant knowledge of the details of the structural analysis algorithms used in this software packages. Therefore the major challenge faced by researchers in structural optimization is to develop methods that are suitable for use with such software packages. Another major challenge is the high computational cost associated with the analysis of many complex real-life problems. In many cases the engineer who has the task of designing a structure cannot afford to analyze it more than a handful of times.

1. Introduction.- 1.1 Function Optimization and Parameter Optimization.- 1.2 Elements of Problem Formulation.- Design Variables.- Objective Function.- Constraints.- Standard Formulation.- 1.3 The Solution Process.- 1.4 Analysis and Design Formulations.- 1.5 Specific Versus General Methods.- 1.6 Exercises.- 1.7 References.- 2. Classical Tools in Structural Optimization.- 2.1 Optimization Using Differential Calculus.- 2.2 Optimization Using Variational Calculus.- to the Calculus of Variations.- 2.3 Classical Methods for Constrained Problems.- Method of Lagrange Multipliers.- Function Subjected to an Integral Constraint.- Finite Subsidiary Conditions.- 2.4 Local Constraints and the Minmax Approach.- 2.5 Necessary and Sufficient Conditions for Optimality.- Elastic Structures of Maximum Stiffness.- Optimal Design of Euler-Bernoulli Columns.- Optimum Vibrating Euler-Bernoulli Beams.- 2.6 Use of Series Solutions in Structural Optimization.- 2.7 Exercises.- 2.8 References.- 3. Linear Programming.- 3.1 Limit Analysis and Design of Structures Formulated as LP Problems.- 3.2 Prestressed Concrete Design by Linear Programming.- 3.3 Minimum Weight Design of Statically Determinate Trusses.- 3.4 Graphical Solutions of Simple LP Problems.- 3.5 A Linear Program in a Standard Form.- Basic Solution.- 3.6 The Simplex Method.- Changing the Basis.- Improving the Objective Function.- Generating a Basic Feasible Solution―Use of Artificial Variables.- 3.7 Duality in Linear Programming.- 3.8 An Interior Method―Karmarkar’s Algorithm.- Direction of Move.- Transformation of Coordinates.- Move Distance.- 3.9 Integer Linear Programming.- Branch-and-Bound Algorithm.- 3.10 Exercises.- 3.11 References.- 4. Unconstrained Optimization.- 4.1 Minimization of Functions of One Variable.- Zeroth Order Methods.- First Order Methods.- Second Order Method.- Safeguarded Polynomial Interpolation.- 4.2 Minimization of Functions of Several Variables.- Zeroth Order Methods.- First Order Methods.- Second Order Methods.- Applications to Analysis.- 4.3 Specialized Quasi-Newton Methods.- Exploiting Sparsity.- Coercion of Hessians for Suitability with Quasi-Newton Methods.- Making Quasi-Newton Methods Globally Convergent.- 4.4 Probabilistic Search Algorithms.- Simulated Annealing.- Genetic Algorithms.- 4.5 Exercises.- 4.6 References.- 5. Constrained Optimization.- 5.1 The Kuhn-Tucker Conditions.- General Case.- Convex Problems.- 5.2 Quadratic Programming Problems.- 5.3 Computing the Lagrange Multipliers.- 5.4 Sensitivity of Optimum Solution to Problem Parameters.- 5.5 Gradient Projection and Reduced Gradient Methods.- 5.6 The Feasible Directions Method.- 5.7 Penalty Function Methods.- Exterior Penalty Function.- Interior and Extended Interior Penalty Functions.- Unconstrained Minimization with Penalty Functions.- Integer Programming with Penalty Functions.- 5.8 Multiplier Methods.- 5.9 Projected Lagrangian Methods (Sequential Quadratic Prog.).- 5.10 Exercises.- 5.11 References.- 6. Aspects of the Optimization Process in Practice.- 6.1 Generic Approximations.- Local Approximations.- Global and Midrange Approximations.- 6.2 Fast Reanalysis Techniques.- Linear Static Response.- Eigenvalue Problems.- 6.3 Sequential Linear Programming.- 6.4 Sequential Nonlinear Approximate Optimization.- 6.5 Special Problems Associated with Shape Optimization.- 6.6 Optimization Packages.- 6.7 Test Problems.- Ten-Bar Truss.- Twenty-Five-Bar Truss.- Seventy-Two-Bar Truss.- 6.8 Exercises.- 6.9 References.- 7. Sensitivity of Discrete Systems.- 7.1 Finite Difference Approximations.- Accuracy and Step Size Selection.- Iterative Methods.- Effect of Derivative Magnitude on Accuracy.- 7.2 Sensitivity Derivatives of Static Displacement and Stress Constraints.- Analytical First Derivatives.- Second Derivatives.- The Semi-Analytical Method.- Nonlinear Analysis.- Sensitivity of Limit Loads.- 7.3 Sensitivity Calculations for Eigenvalue Problems.- Sensitivity Derivatives of Vibration and Buckling Constraints.- Sensitivity Derivatives for Non-Hermitian Eigenvalue Problems.- Sensitivity Derivatives for Nonlinear Eigenvalue Problems.- 7.4 Sensitivity of Constraints on Transient Response.- Equivalent Constraints.- Derivatives of Constraints.- Linear Structural Dynamics.- 7.5 Exercises.- 7.6 References.- 8. Introduction to Variational Sensitivity Analysis.- 8.1 Linear Static Analysis.- The Direct Method.- The Adjoint Method.- Implementation Notes.- 8.2 Nonlinear Static Analysis and Limit Loads.- Static Analysis.- Limit Loads.- Implementation Notes.- 8.3 Vibration and Buckling.- The Direct Method.- The Adjoint Method.- 8.4 Static Shape Sensitivity.- The Material Derivative.- Domain Parametrization.- The Direct Method.- The Adjoint Method.- 8.5 Exercise.- 8.6 References.- 9. Dual and Optimality Criteria Methods.- 9.1 Intuitive Optimality Criteria Methods.- Fully Stressed Design.- Other Intuitive Methods.- 9.2 Dual Methods.- General Formulation.- Application to Separable Problems.- Discrete Design Variables.- Application with First Order Approximations.- 9.3 Optimality Criteria Methods for a Single Constraint.- The Reciprocal Approximation for a Displacement Constraint.- A Single Displacement Constraint.- Generalization for Other Constraints.- Scaling-based Resizing.- 9.4 Several Constraints.- Reciprocal-Approximation Based Approach.- Scaling-based Approach.- Other Formulations.- 9.5 Exercises.- 9.6 References.- 10. Decomposition and Multilevel Optimization.- 10.1 The Relation between Decomposition and Multilevel Formulation.- 10.2 Decomposition.- 10.3 Coordination and Multilevel Optimization.- 10.4 Penalty and Envelope Function Approaches.- 10.5 Narrow-Tree Multilevel Problems.- Simultaneous Analysis and Design.- Other Applications.- 10.6 Decomposition in Response and Sensitivity Calculations.- 10.7 Exercises.- 10.8 References.- 11.Optimum Design of Laminated Composite Materials.- 11.1 Mechanical Response of a Laminate.- Orthotropic Lamina.- Classical Laminated Plate Theory.- Bending, Extension, and Shear Coupling.- 11.2 Laminate Design.- Design of Laminates for In-plane Response.- Design of Laminates for Flexural Response.- 11.3 Stacking Sequence Design.- Graphical Stacking Sequence Design.- Penalty Function Formulation.- Integer Linear Programming Formulation.- Probabilistic Search Methods.- 11.4 Design Applications.- Stiffened Plate Design.- Aeroelastic Tailoring.- 11.5 Design Uncertainties.- 11.6 Exercises.- 11.7 References.- Name Index.