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Engineering Optimization

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Introduction

 

Maple lets you minimize or maximize objective functions with respect to constraints.

 

(1)

 

The objective function can be a sum-of-squares error for parameter estimation, or the

 

• 

weight of a mechanical device

• 

cost of production

• 

or energy required for a process

 

The constraints can be limits on the

 

• 

dimensions of a mechanical device, or the allowable stresses

• 

minimum and maximum process temperatures

• 

or amount of base materials

 

Units can be employed in the objective function or the constraints.

 

You can use Maple's built-in linear, nonlinear, and quadratic optimizers, or the optional Global Optimization Toolbox.

Example - Fuel Pod Design Optimization

 

You are designing a fuel pod with a hemispherical cap, cylindrical mid-section and conical cap.

 

 

What are values of L, H and R that minimize the surface area while maintaining the volume V at 3 m3?

 

Objective function - surface area of pod

Constraint on the volume area of pod


All dimensions must be greater than 0


Hence the optimized dimensions are

(2)


Check that the constraint on the pod volume is satisfied

(3)

Applications

Welded Beam Design Optimization

Helical Spring

Optimize a Rankine Cycle

Chemical Kinetics Parameter Estimation

PV Diode Parameter Estimation


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