Geometric Optimization of Radiant Enclosures Containing Specular Surfaces

2003 ◽  
Vol 125 (5) ◽  
pp. 845-851 ◽  
Author(s):  
K. J. Daun ◽  
D. P. Morton ◽  
J. R. Howell
Keyword(s):  
Design Methodology ◽  
Optimization Design ◽  
Numerical Algorithms ◽  
Geometric Optimization ◽  
Trial And Error ◽  
Design Problems ◽  
Design Iteration ◽  
Optimization Methodology ◽  
Reflecting Surfaces ◽  
Specular Surfaces

This paper presents an optimization methodology for designing radiant enclosures containing specularly-reflecting surfaces. The optimization process works by making intelligent perturbations to the enclosure geometry at each design iteration using specialized numerical algorithms. This procedure requires far less time than the forward “trial-and-error” design methodology, and the final solution is near optimal. The radiant enclosure is analyzed using a Monte Carlo technique based on exchange factors, and the design is optimized using the Kiefer-Wolfowitz method. The optimization design methodology is demonstrated by solving two industrially-relevant design problems involving two-dimensional enclosures that contain specular surfaces.

Geometric Optimization of Radiant Enclosures Containing Specular Surfaces, Through Non-Linear Programming

2002 ◽  
Author(s):  
K. J. Daun ◽  
D. P. Morton ◽  
J. R. Howell
Keyword(s):  
Design Methodology ◽  
Numerical Algorithms ◽  
Geometric Optimization ◽  
Trial And Error ◽  
Design Problems ◽  
Non Linear Programming ◽  
Design Iteration ◽  
Optimization Methodology ◽  
Reflecting Surfaces ◽  
Specular Surfaces

This paper presents an optimization methodology for designing radiant enclosures containing specularly-reflecting surfaces. The optimization process works by making intelligent perturbations to the enclosure geometry at each design iteration using specialized numerical algorithms. This requires far less time than the forward “trial-and-error” design methodology, and the final solution is near optimal. In this application, the radiant enclosure is analyzed using a Monte Carlo technique based on exchange factors, and the design is optimized using the Kiefer-Wolfowitz method. This design methodology is demonstrated by solving two industrially-relevant design problems involving two-dimensional enclosures that contain specular surfaces.

Geometric Optimization of Concentrating Solar Collectors Using Monte Carlo Simulation

2009 ◽  
Author(s):  
A. J. Marston ◽  
K. J. Daun ◽  
M. R. Collins
Keyword(s):  
Monte Carlo ◽  
Intelligent Design ◽  
Numerical Algorithms ◽  
Optimal Solution ◽  
Geometric Optimization ◽  
Trial And Error ◽  
Solar Collectors ◽  
Surface Geometry ◽  
Step Size ◽  
Optimization Methodology

This paper presents an optimization methodology for designing linear concentrating solar collectors. The proposed algorithm makes intelligent design updates to the collector surface geometry according to specialized numerical algorithms. The process is much more efficient than traditional “trial-and-error” methods, producing a final solution that is near-optimal. A Monte Carlo technique is used to quantify the performance of the collector design in terms of an objective function, which is then minimized using a modified Kiefer-Wolfowitz algorithm that uses sample size and step size controls. The methodology is applied to the design of a linear parabolic concentrating collector, successfully arriving at the known optimal solution.

Optimization Design of Electromagnetic Devices Using an Enhanced Salp Swarm Algorithm

2021 ◽  
Vol 35 (12) ◽  
pp. 1471-1476
Author(s):  
Houssem Bouchekara ◽  
Mostafa Smail ◽  
Mohamed Javaid ◽  
Sami Shamsah
Keyword(s):  
Optimization Design ◽  
Upper Bounds ◽  
Lower And Upper Bounds ◽  
Design Problems ◽  
Salp Swarm Algorithm ◽  
Electromagnetic Devices ◽  
Swarm Algorithm ◽  
Better Than

An Enhanced version of the Salp Swarm Algorithm (SSA) referred to as (ESSA) is proposed in this paper for the optimization design of electromagnetic devices. The ESSA has the same structure as of the SSA with some modifications in order to enhance its performance for the optimization design of EMDs. In the ESSA, the leader salp does not move around the best position with a fraction of the distance between the lower and upper bounds as in the SAA; rather, a modified mechanism is used. The performance of the proposed algorithm is tested on the widely used Loney’s solenoid and TEAM Workshop Problem 22 design problems. The obtained results show that the proposed algorithm is much better than the initial one. Furthermore, a comparison with other well-known algorithms revealed that the proposed algorithm is very competitive for the optimization design of electromagnetic devices.

Geometric Optimization of Concentrating Solar Collectors using Monte Carlo Simulation

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
A. J. Marston ◽  
K. J. Daun ◽  
M. R. Collins
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stochastic Programming ◽  
Objective Function ◽  
Sample Size ◽  
Optimization Algorithm ◽  
Geometric Optimization ◽  
Trial And Error ◽  
Solar Collectors ◽  
Step Size

This paper presents an optimization algorithm for designing linear concentrating solar collectors using stochastic programming. A Monte Carlo technique is used to quantify the performance of the collector design in terms of an objective function, which is then minimized using a modified Kiefer–Wolfowitz algorithm that uses sample size and step size controls. This process is more efficient than traditional “trial-and-error” methods and can be applied more generally than techniques based on geometric optics. The method is validated through application to the design of three different configurations of linear concentrating collector.

Optimal Design Methodology of Point-to-Point Servo Systems for Minimization of Energy Consumption

1992 ◽  
Vol 206 (1) ◽  
pp. 35-43
Author(s):  
S W Kim ◽  
J S Park
Keyword(s):  
Design Methodology ◽  
Design Problems ◽  
Servo Systems ◽  
Speed Reduction ◽  
Point Motion ◽  
Actual Design ◽  
Profile Optimization ◽  
Point To Point ◽  
Selection Of

An optimum design methodology is presented for point-to-point motion control servo systems in which d.c. permanent magnetic motors are used as the main actuators. Emphasis is focused on establishing a series of comprehensive decision-making practices in dealing with three major design subjects: determination of the velocity profile, optimization of the speed reduction ratio, and selection of the motor. Finally, a practical design example is discussed to illustrate how the suggested design methodology may be applied to actual design problems.

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