OPTIMUM DESIGN OF SPACE FRAMES UNDER SEISMIC LOADING

2001 ◽  
Vol 01 (01) ◽  
pp. 105-123 ◽  
Author(s):  
MANOLIS PAPADRAKAKIS ◽  
NIKOS D. LAGAROS ◽  
VAGELIS PLEVRIS
Keyword(s):  
Structural Optimization ◽  
Optimum Design ◽  
Large Scale ◽  
Optimization Problems ◽  
Response Spectrum ◽  
Minimum Weight ◽  
Optimization Procedure ◽  
Seismic Loading ◽  
Approximate Design ◽  
Design Response Spectrum

The objective of this paper is to perform structural optimization under seismic loading. Combinatorial optimization methods and in particular algorithms based on Evolution Strategies are implemented for the solution of large-scale structural optimization problems under seismic loading. In this work the efficiency of a rigorous approach in treating dynamic loading is investigated and compared with a simplified dynamic analysis in the framework of finding the optimum design of structures with minimum weight. In this context a number of accelerograms are produced from the elastic design response spectrum of the region. These accelerograms constitute the multiple loading conditions under which the structures are optimally designed. This approach is compared with an approximate design approach based on simplifications adopted by the seismic codes. The results obtained for a characteristic test problem indicate a substantial improvement in the final design when the proposed optimization procedure is implemented.

Large Scale Structural Optimization With Linear Goal Programming

1990 ◽  
Author(s):  
Mohamed E. M. El-Sayed ◽  
T. S. Jang
Keyword(s):  
Structural Optimization ◽  
Goal Programming ◽  
Large Scale ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Minimum Weight ◽  
Design Tool ◽  
Linear Goal Programming ◽  
Programming Techniques ◽  
Structural Optimization Problem

Abstract This paper presents a method for solving large scale structural optimization problems using linear goal programming techniques. The method can be used as a multicriteria optimization tool since goal programming removes the difficulty of having to define an objective function and constraints. It also has the capacity of handling rank ordered design objectives or goals. The method uses finite element analysis, linear goal programming techniques and successive linearization to obtain the solution for the nonlinear goal optimization problems. The general formulation of the structural optimization problem into a nonlinear goal programming form is presented. The successive linearization method for the nonlinear goal optimization problem is discussed. To demonstrate the validity of the method, as a design tool, the solution of the minimum weight structural optimization problem with stress constraints for 10, 25 and 200 truss problems are included.

scholarly journals Analysis of Offshore Structures Based on Response Spectrum of Ice Force

2019 ◽  
Vol 7 (11) ◽  
pp. 417 ◽  
Author(s):  
Liu ◽  
Li ◽  
Zhang
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Response Spectrum ◽  
Time History ◽  
Offshore Structures ◽  
Potential Threat ◽  
Influence Coefficients ◽  
Design Response Spectrum ◽  
Ice Force ◽  
Bending Failure

With the development of large-scale offshore projects, sea ice is a potential threat to the safety of offshore structures. The main forms of damage to bottom-fixed offshore structures under sea ice are crushing failure and bending failure. Referred to as the concept of seismic response spectrums, the design response spectrum of offshore structures induced by the crushing and bending ice failure is presented. Selecting the Bohai Sea in China as an example, the sea areas were divided into different ice zones due to the different sea ice parameters. Based on the crushing and bending failure power spectral densities of ice force, a large amount of ice force time-history samples are firstly generated for each ice zone. The time-history of the maximum responses of a series of single degree of freedom systems with different natural frequencies under the ice force are calculated and subsequently, a response spectrum curve is obtained. Finally, by fitting all the response spectrum curves from different samples, the design response spectrum is generated for each ice zone. The ice force influence coefficients for crushing and bending failure are obtained, which can be used to estimate the stochastic sea ice force acting on a structure conveniently in a static way. A comparison of the proposed response spectrum method with the Monte Carlo method by a numerical example shows good agreement.

scholarly journals Distribution Endpoint Estimation Assessment for the use in Metaheuristic Optimization Procedure

MENDEL ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 93-100
Author(s):  
Jan Holesovky
Keyword(s):  
Extreme Value Theory ◽  
Large Scale ◽  
Optimization Problems ◽  
Random Search ◽  
Optimization Procedure ◽  
Short Review ◽  
Value Theory ◽  
Extreme Value ◽  
Mixed Integer ◽  
Endpoint Estimation

Metaheuristic algorithms are often applied to numerous optimization problems, involving large-scale and mixed-integer instances, specifically. In this contribution we discuss some refinements from the extreme value theory to the lately proposed modification of partition-based random search. The partition-based approach performs iterative random sampling at given feasible subspaces in order to exclude the less favourable regions. The quality of particular regions is evaluated according to the promising index of a region. From statistical perspective, determining the promising index is equivalent to the endpoint estimation of a probability distribution induced by the objective function at the sampling subspace. In the following paper, we give a short review of the recent endpoint estimators derived on the basis of extreme value theory, and compare them by simulations. We discuss also the difficulties in their application and suitability of the estimators for various optimization instances.

An Efficient Genetic Algorithm for Large Scale Built-Up Structural Optimization

1993 ◽  
Author(s):  
Shigang Wang ◽  
Xindu Cheng ◽  
Ji Zhou ◽  
Jun Yu
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Stress Constraints ◽  
Plate Structures ◽  
Dynamic Source ◽  
Complex Structural

Abstract In this paper, a new zigzag method for plate structures and a genetic algorithm (GA) of dynamic source seed spaces are developed and a combination of them is used to deal with large scale built-up structural optimization. The new GA combined with the zigzag method can work efficiently to cope with large scale structural optimization with displacement and stress constraints. Examples show that this GA is robust and can be used for many complex structural optimization problems.

Optimization Design of a Walkable Fixture Mechanism

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Xiao-Jin Wan ◽  
Hanjie Zhang
Keyword(s):  
Performance Optimization ◽  
Error Propagation ◽  
Optimization Design ◽  
Large Scale ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Singular Values ◽  
Legged Robot ◽  
Nsga Ii ◽  
Propagation Matrix

In this paper, a novel fixture mechanism with combining a mobility of the legged robot and advantages of parallel mechanism is designed to hold the different size and shape, large-scale workpiece. The proposed mobile fixture mechanism holds the workpiece as a parallel manipulator while it walks as a legged robot. This kind of robotized fixtures can possess high self-configurable ability to accommodate a wider variety of products. In order to obtain the best kinematic dexterity and accuracy characteristics, comprehensive performance optimization is performed by non-dominated-genetic algorithm (NSGA-II). In the optimization procedure, a conventional kinematic transformation matrix (Jacobian matrix) and error propagation matrix are obtained through derivation and differential motion operations. The singular values and condition number based on velocity Jacobians and error amplification factors based on error propagation matrix are derived; in addition, relative pose error range of end effector is also derived. On the basis of the above measure indices, three kinds of nonlinear optimization problems are defined to obtain the optimal architecture parameters for better kinematic accuracy and dexterity in workspace. Comparison analyses of the optimized results are performed.

Optimal Structural Design in the USSR

1989 ◽  
Vol 42 (2) ◽  
pp. 27-37 ◽  
Author(s):  
Mark I. Reitman
Keyword(s):  
Structural Optimization ◽  
Optimum Design ◽  
Structural Design ◽  
Optimization Problems ◽  
Moving Loads ◽  
Mathematical Methods ◽  
3D Structures ◽  
Optimal Structural Design ◽  
Academic Researchers ◽  
Rigid Frames

Studies in structural optimization in Russia began more than a century ago and initially satisfied the needs of railroad engineering. Later Soviet academic researchers and engineers considered the optimum design of compressed and twisted bars, beams, arches, rigid frames, plates, shells, and various 3D structures under single and multiple statical, dynamical, and moving loads. Some new formulations of the optimization problems have been introduced and solved using classical and new mathematical methods. Several hundred contributions are briefly covered with references to 50 bibliographical sources.

A New Hybrid Simulated Annealing Algorithm for Large Scale Global Optimization

2015 ◽  
Vol 5 (3) ◽  
pp. 24-36
Author(s):  
Seifedine N. Kadry ◽  
Abdelkhalak El Hami
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Structural Optimization ◽  
Stochastic Approximation ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Optimization Problems ◽  
Simultaneous Perturbation Stochastic Approximation ◽  
Hybrid Simulated Annealing ◽  
Annealing Algorithm

The present paper focus on the improvement of the efficiency of structural optimization, in typical structural optimization problems there may be many locally minimum configurations. For that reason, the application of a global method, which may escape from the locally minimum points, remain essential. In this paper, a new hybrid simulated annealing algorithm for large scale global optimization problems with constraints is proposed. The authors have developed a stochastic algorithm called SAPSPSA that uses Simulated Annealing algorithm (SA). In addition, the Simultaneous Perturbation Stochastic Approximation method (SPSA) is used to refine the solution. Commonly, structural analysis problems are constrained. For the reason that SPSA method involves penalizing constraints a penalty method is used to design a new method, called Penalty SPSA (PSPSA) method. The combination of both methods (Simulated Annealing algorithm and Penalty Simultaneous Perturbation Stochastic Approximation algorithm) provides a powerful hybrid stochastic optimization method (SAPSPSA), the proposed method is applicable for any problem where the topology of the structure is not fixed. It is simple and capable of handling problems subject to any number of constraints which may not be necessarily linear. Numerical results demonstrate the applicability, accuracy and efficiency of the suggested method for structural optimization. It is found that the best results are obtained by SAPSPSA compared to the results provided by the commercial software ANSYS.

Multilevel Parallelization Concepts for Structural Optimization Using Transputer Systems

1993 ◽  
Author(s):  
Dietrich Hartmann ◽  
Karl R. Leimbach
Keyword(s):  
Structural Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Optimization Criterion ◽  
Structural Systems ◽  
Large Set ◽  
Computer Implementation ◽  
Actual Computer

Abstract Multilevel parallelization concepts for structural optimization provide potential to significantly improve the productivity in CAE. In particular, if large scale structural systems are to be designed with respect to a specified optimization criterion subject to a large set of constraints substantial speedup factors are achievable. This contribution is discussing generic as well as specific parallelization concepts of large structural optimization problems. Based upon these concepts transputer systems are applied as a platform for the transition from concepts to actual computer implementation.

Optimum Design of Damage Resistant Reinforced Composite Panels

2019 ◽  
Vol 827 ◽  
pp. 37-42
Author(s):  
Andrea Sellitto
Keyword(s):  
Optimum Design ◽  
Impact Force ◽  
Minimum Weight ◽  
Optimization Procedure ◽  
Stacking Sequence ◽  
Multi Objective Optimization ◽  
Low Velocity ◽  
Reinforced Composite ◽  
Design Variables ◽  
The Impact

In this work, an optimization procedure able to determine the optimum design of a stiffened aeronautical panel subjected to low velocity impacts is presented. As design variables, the number of plies and the stacking sequence of the panel have been considered. The optimization is based on a genetic algorithm, while the onset of the impact induced damage is predicted by means of an approach based on the critical impact force threshold. A multi-objective optimization has been carried out to determine, among the configurations able to withstand the low velocity impacts, the ones characterized by the maximum buckling load and the minimum weight.

Solving Very Large-Scale Structural Optimization Problems

AIAA Journal ◽  
2007 ◽  
Vol 45 (11) ◽  
pp. 2729-2736
Author(s):  
F. Hüttner ◽  
M. Grosspietsch
Keyword(s):  
Structural Optimization ◽  
Large Scale ◽  
Optimization Problems
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