Optimum Design of I. C. Engine Pistons

1984 ◽  
Vol 106 (2) ◽  
pp. 209-213 ◽  
Author(s):  
S. S. Rao ◽  
S. S. Srinivasa Rao
Keyword(s):  
Function Method ◽  
Optimization Problems ◽  
Interpolation Method ◽  
Unconstrained Minimization ◽  
Penalty Function Method ◽  
Minimum Volume ◽  
Constrained Optimization Problems ◽  
One Dimensional ◽  
Design Variables ◽  
Powell Method

The minimum volume design of I. C. engine pistons is considered with constraints on temperature and stresses developed in the piston. The interior penalty function method, coupled with the Davidon-Fletcher-Powell method of unconstrained minimization and the cubic interpolation method of one-dimensional search, is used for solving the constrained optimization problems. The temperature and stresses developed in the piston are determined by using the classic as well as the finite element methods of analysis. A sensitivity analysis is conducted to find the influence of changes in design variables on the objective function and the response parameters.

Reliability Based Optimization of Submarine Pressure Hulls With Inelastic Interstiffener Buckling Failure

2006 ◽  
Author(s):  
P. Radha ◽  
K. Rajagopalan
Keyword(s):  
Unconstrained Minimization ◽  
Computer Code ◽  
Correction Method ◽  
Penalty Function Method ◽  
Simulation Design ◽  
Design Variables ◽  
Minimization Technique ◽  
Buckling Failure ◽  
Optimal Values ◽  
Reliability Based Optimization

Uncertainties that exist in modelling and simulation, design variables and parameters, manufacturing processes etc., may lead to large variations in the performance characteristics of the system. Optimized deterministic designs determined without considering uncertainties can be unreliable and may lead to catastrophic failure of the structure being designed. Reliability based optimization (RBO) is a methodology that addresses these problems. In this paper the reliability based optimization of submarine pressure hulls in which the failure gets governed by inelastic interstiffener buckling has been described. The problem has been formulated to minimize the ratio of weight of shell-stiffener geometry to the weight of liquid displaced, subjected to reliability based inelastic interstiffener buckling constraint. Since the methods of analysis of inelastic buckling failure of submarine pressure hulls are inadequate, in the present study the Johnson-Ostenfeld inelastic correction method has been adopted for formulating the constraint. By considering spacing of the stiffener, thickness of the plating and depth of the stiffener as the design variables, Sequential Unconstrained Minimization Technique (SUMT) has been used to solve the design problem. RBO has been carried out to get the optimal values of these design variables for a target reliability index using Interior Penalty Function Method for which an efficient computer code in C++ has been developed.

An Adaptive Penalty Function Method for Constrained Optimization with Evolutionary Programming

2000 ◽  
Vol 4 (2) ◽  
pp. 164-170 ◽  
Author(s):  
Xinghuo Yu ◽  
◽  
Baolin Wu
Keyword(s):  
Constrained Optimization ◽  
Penalty Function ◽  
Function Method ◽  
Optimization Problems ◽  
Evolutionary Programming ◽  
Benchmark Problems ◽  
Local Optimum ◽  
Penalty Function Method ◽  
Adaptive Penalty ◽  
Adaptive Penalty Function

In this paper, we propose a novel adaptive penalty function method for constrained optimization problems using the evolutionary programming technique. This method incorporates an adaptive tuning algorithm that adjusts the penalty parameters according to the population landscape so that it allows fast escape from a local optimum and quick convergence toward a global optimum. The method is simple and computationally effective in the sense that only very few penalty parameters are needed for tuning. Simulation results of five well-known benchmark problems are presented to show the performance of the proposed method.

Evaluation of Dynamic Load-Carrying Capacity for Free-Floating Space Manipulators

2015 ◽  
Vol 713-715 ◽  
pp. 795-799 ◽  
Author(s):  
Yong Liu ◽  
Qing Xuan Jia ◽  
Gang Chen ◽  
Han Xu Sun ◽  
Jun Jie Peng
Keyword(s):  
Dynamic Load ◽  
Carrying Capacity ◽  
Function Method ◽  
Feasible Region ◽  
Penalty Function Method ◽  
Load Carrying Capacity ◽  
One Dimensional ◽  
Space Manipulators ◽  
Load Carrying ◽  
Point To Point

Two kinds of dynamic load-carrying capacity (DLCC) evaluation methods for free-floating space manipulators (FFSM) in two typical on-orbit operating missions are proposed in this paper. DLCC evaluation is transformed into nonlinear programming problem (NPP) by introducing load-carrying coefficient to measure DLCC: in point-to-point task, penalty function method is adopted to approach the boundary of feasible region rapidly, then DLCC can be obtained through following iterations; in trajectory tracking task, NPP is solved by using multiple one-dimensional search, the dynamic load-carrying coefficient in discontinuous feasible region can be quickly solved through adjusting the searching boundary constantly. The effectiveness of the mentioned methods is verified by simulations.

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