scholarly journals Theoretical Model of the Physical System: Optimization by the Genetic Algorithm

10.5772/14860 ◽  
2011 ◽  
Author(s):  
Stanislav Jureka
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Model ◽  
Physical System ◽  
System Optimization

Wave Energy Converter Array Optimization: A Review of Current Work and Preliminary Results of a Genetic Algorithm Approach Introducing Cost Factors

2015 ◽  
Author(s):  
Chris Sharp ◽  
Bryony DuPont
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Wave Energy ◽  
Reference Model ◽  
A Priori ◽  
System Optimization ◽  
Primary Energy ◽  
Close Relative ◽  
Cost Information ◽  
Multiple Test

Currently, ocean wave energy is a novel means of electricity generation that is projected to potentially serve as a primary energy source in coastal areas. However, for wave energy converters (WECs) to be applicable on a scale that allows for grid implementation, these devices will need to be placed in close relative proximity to each other. From what’s been learned in the wind industry of the U.S., the placement of these devices will require optimization considering both cost and power. However, current research regarding optimized WEC layouts only considers the power produced. This work explores the development of a genetic algorithm (GA) that will create optimized WEC layouts where the objective function considers both the economics involved in the array’s development as well as the power generated. The WEC optimization algorithm enables the user to either constrain the number of WECs to be included in the array, or allow the algorithm to define this number. To calculate the objective function, potential arrays are evaluated using cost information from Sandia National Labs Reference Model Project, and power development is calculated such that WEC interaction affects are considered. Results are presented for multiple test scenarios and are compared to previous literature, and the implications of a priori system optimization for offshore renewables are discussed.

Optimum Selection of Hydraulic Devices for Water Hammer Control in the Pipeline Systems Using Genetic Algorithm

2003 ◽  
Author(s):  
Bong Seong Jung ◽  
Bryan W. Karney
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Optimization Problems ◽  
System Optimization ◽  
Water Hammer ◽  
Pipeline System ◽  
Optimal Size ◽  
Protection Strategy ◽  
Hydraulic Devices ◽  
Selection Of

Genetic algorithms have been used to solve many water distribution system optimization problems, but have generally been limited to steady state or quasi-steady state optimization. However, transient events within pipe system are inevitable and the effect of water hammer should not be overlooked. The purpose of this paper is to optimize the selection, sizing and placement of hydraulic devices in a pipeline system considering its transient response. A global optimal solution using genetic algorithm suggests optimal size, location and number of hydraulic devices to cope with water hammer. This study shows that the integration of a genetic algorithm code with a transient simulator can improve both the design and the response of a pipe network. This study also shows that the selection of optimum protection strategy is an integrated problem, involving consideration of loading condition, device and system characteristics, and protection strategy. Simpler transient control systems are often found to outperform more complex ones.

scholarly journals Onset of natural selection in auto-catalytic heteropolymers

2017 ◽  
Author(s):  
Alexei V. Tkachenko ◽  
Sergei Maslov
Keyword(s):  
Natural Selection ◽  
Theoretical Model ◽  
Information Entropy ◽  
Physical System ◽  
Driving Forces ◽  
Darwinian Evolution ◽  
Living Matter ◽  
Spontaneous Reduction ◽  
Nano Structures ◽  
Opening Up

Reduction of information entropy along with ever-increasing complexity are among the key signatures of living matter. Understanding the onset of such behavior in early prebiotic world is essential for solving the problem of origins of life. To elucidate this transition, we study a theoretical model of information-storing heteropolymers capable of template-assisted ligation and subjected to cyclic non-equilibrium driving forces. We discover that this simple physical system undergoes a spontaneous reduction of the information entropy due to the competition of chains for constituent monomers. This natural-selection-like process ultimately results in the survival of a limited subset of polymer sequences. Importantly, the number of surviving sequences remains exponentially large, thus opening up the possibility of further increase in complexity due to Darwinian evolution. We also propose potential experimental implementations of our model using either biopolymers or artificial nano-structures.

scholarly journals Heating, Ventilation, and Air Conditioning System Optimization Control Strategy Involving Fan Coil Unit Temperature Control

2019 ◽  
Vol 9 (11) ◽  
pp. 2391 ◽  
Author(s):  
Chang-Ming Lin ◽  
Hsin-Yu Liu ◽  
Ko-Ying Tseng ◽  
Sheng-Fuu Lin
Keyword(s):  
Genetic Algorithm ◽  
Energy Conservation ◽  
Temperature Control ◽  
Control Strategy ◽  
Air Conditioning ◽  
Minimum Energy ◽  
System Optimization ◽  
Hvac System ◽  
Minimum Energy Consumption ◽  
Optimization Control

The objective of this study was to develop a heating, ventilation, and air conditioning (HVAC) system optimization control strategy involving fan coil unit (FCU) temperature control for energy conservation in chilled water systems to enhance the operating efficiency of HVAC systems. The proposed control strategy involves three techniques, which are described as follows. The first technique is an algorithm for dynamic FCU temperature setting, which enables the FCU temperature to be set in accordance with changes in the outdoor temperature to satisfy the indoor thermal comfort for occupants. The second technique is an approach for determining the indoor cold air demand, which collects the set FCU temperature and converts it to the refrigeration ton required for the chilled water system; this serves as the control target for ensuring optimal HVAC operation. The third technique is a genetic algorithm for calculating the minimum energy consumption for an HVAC system. The genetic algorithm determines the pump operating frequency associated with minimum energy consumption per refrigeration ton to control energy conservation. To demonstrate the effectiveness of the proposed HVAC system optimization control strategy combining FCU temperature control, this study conducted a field experiment. The results revealed that the proposed strategy enabled an HVAC system to achieve 39.71% energy conservation compared with an HVAC system operating at full load.

Design of Docking Probe Based on Dynamics Model of Flexible Beam Impact

2011 ◽  
Vol 120 ◽  
pp. 371-374
Author(s):  
Xiang Zhang ◽  
Yi Yong Huang ◽  
Wei Han ◽  
Xiao Qian Chen
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Model ◽  
Impact Dynamics ◽  
Flexible Beam ◽  
Analytical Mechanics ◽  
Space Probe ◽  
Dynamics Model ◽  
Docking Mechanism

The issue considered in this paper is a flexible beam based on space probe-cone docking mechanism, which aims to buffer impact effects replacing buffering mechanism. The theoretical model of docking impact dynamics based on flexible beam is built according to the Lagrange Analytical Mechanics theory. The shape of docking probe is optimized by using genetic algorithm.

Ramjet Powered Missile Design Using a Genetic Algorithm

2007 ◽  
Vol 7 (2) ◽  
pp. 167-173 ◽  
Author(s):  
Roy J. Hartfield ◽  
Rhonald M. Jenkins ◽  
John E. Burkhalter
Keyword(s):  
Genetic Algorithm ◽  
Performance Prediction ◽  
Design Space ◽  
System Optimization ◽  
Design Strategy ◽  
Optimization Process ◽  
Preliminary Design ◽  
Efficient Exploration ◽  
Typical Design ◽  
Design Scenario

A methodology for developing optimized designs for symmetric-centerbody ramjet powered missiles, using a genetic algorithm as the driver for the system optimization process, has been developed. The methodology described in this paper allows for a comprehensive but efficient exploration of the design space. This global optimization process is made possible by performance prediction codes, which can provide preliminary design-level accuracy very efficiently. This work demonstrates the first truly comprehensive design strategy for this type of device. The paper contains a discussion of the methodology and shows results for a typical design scenario.

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