Structural optimization--past, present, and future

Presented a Paper 81-0897 at the AIAA 1981 Annual Meeting and Technical Display, Long Beach, Calif., May 12-14, 198

Cooperation and Competition Strategies in Multi-objective Shape Optimization - Application to Low-boom/Low-drag Supersonic Business Jet

International audienceCooperation and competition are natural laws that regulate the interactions between agents in numerous physical, or social phenomena. By analogy, we transpose these laws to devise e cient multi-objective algorithms applied to shape optimization problems involving two or more disciplines. Two e cient strategies are presented in this paper: a multiple gradient descent algorithm (MGDA) and a Nash game strategy based on an original split of territories between disciplines. MGDA is a multi-objective extension of the steepest descent method. The use of a gradient-based algorithm that exploits the cooperation principle aims at reducing the number of iterations required for classical multi-objective evolutionary algorithms to converge to a Pareto optimal design. On the other hand side, the Nash game strategy is well adapted to typical aeronautical optimization problems, when, after having optimized a preponderant or fragile discipline (e.g. aerodynamics), by the minimization of a primary objective-function, one then wishes to reduce a secondary objective-function, representative of another discipline, in a process that avoids degrading excessively the original optimum. Presently, the combination of the two approaches is exploited, in a method that explores the entire Pareto front. Both algorithms are rst analyzed on analytical test cases to demonstrate their main features and then applied to the optimum-shape design of a low-boom/low-drag supersonic business jet design problem. Indeed, sonic boom is one of the main limiting factors to the development of civil supersonic transportation. As the driving design for low-boom is not compliant with the low-drag one, our goal is to provide a trade-o between aerodynamics and acoustics. Thus Nash games are adopted to de ne a low-boom con guration close to aerodynamic optimality w.r.t. wave drag

ADS: A FORTRAN program for automated design synthesis, version 1.00

A new general-purpose optimization program for engineering design is described. ADS-1 (Automated Design Synthesis - Version 1) is a FORTRAN program for solution of nonlinear constrained optimization problems. The program is segmented into three levels, being strategy, optimizer, and one-dimensional search. At each level, several options are available so that a total of over 100 possible combinations can be created. Examples of available strategies are sequential unconstrained minimization, the Augmented Lagrange Multiplier method, and Sequential Linear Programming. Available optimizers include variable metric methods and the Method of Feasible Directions as examples and one-dimensional search options include polynomial interpolation and the Golden Section method as examples. Emphasis is placed on ease of use of the program. All information is transferred via a single parameter list. Default values are provided for all internal program parameters such as convergence criteria, and the user is given a simple means to over-ride these, if desired. The program is demonstrated with a simple structural design example.NASA ORDER L-9461-B; RTOP 506-53-53-07Approved for public release; distribution is unlimited

Marine Condenser Design Using Numerical Optimization

Computer codes for the analysis of marine steam condensers were coupled with a numerical optimization code to provide fully automated design. The resulting programs are excellent design tools for the conceptual design of a condenser to meet specified constraints. Examples illustrate the versatility of this method