Motion based design : solution algorithms to the inverse problem with applications to seismic design
A general solution algorithm to the inverse equilibrium problem is derived. The algorithm finds stiffness coefficients for a given loading and a given set of displacment constraints. Optimization techniques are employed for the statically indeterminate case and for the case of partial displacement specification. The applicability of the method to seismic design of buildings is demonstrated. An inverse eigen-problem is solved for a stiffness distribution that produces a desired fundamental mode shape. The stiffness is then scaled based on the magnitude of the excitation with the use of response spectra. Emphasis is placed on stiffness proportional damping, which can be generated from the physical placement of dampers. Thesis Supervisor: Jerome J. Connor Title: Professor of Civil and Environmental Engineering Acknowledgments I would like to take this opportunity to thank the people to whom I am indebted for this thesis. First of all, I would like to thank my father and mother, Wilfred and Lorraine Gallegos. I would not have had the opportunity to write this thesis, were it not for your financial and emotional support. You have been very supportive of all my efforts without trying to influence any of the decisions I have made. A very heartfelt thanks to my brother and sister, Wilfred Jr. and Anita. You have always been, and will continue to be excellent role models. A special thanks to my advisor Professor Jerome J. Connor for an extremely interesting and challenging research topic. But more importantly, I thank you for helping me find a new direction in life. It was a pleasure working with you. Thanks to Miguel Licona for providing a state space simulator which was used to analyze the designs. I dedicate this thesis to my grandmothers, Corina V. Duran and Lucia Lopez. You provided me with a stable cultural environment and a unique perspective on life. I have always drawn and will continue to draw upon your wise words of wisdom in times of need.
Linear and Nonlinear Programming
I* Basics 1 Optimization Models 2 Fundamentals of Optimization 3 Representation of Linear Constraints II Linear Programming 4 Geometry of Linear Programming 5 The Simplex Method Introduction 6 Duality and Sensitivity 7 Enhancements of the Simplex Method 8 Network Problems 9 Computational Complexity of Computer Programming III Unconstained Nonlinear Optimization 10 Basics of Unconstrained Optimization 11 Methods for Unconstrained Optimization 12 Low-Storage Methods 13 Nonlinear Least-Squares IV *Nonlinear Programming 14 Optimality Conditions for Constrained Problems 15 Feasible-Point Methods 16 Penalty and Barrier Methods 17 Interior Point Methods Appendixes
Structural optimization in the dynamics response regime - A computational approach
Structural optimization of designs with requirements including restrictions on structure dynamic response and characteristics