scholarly journals Symmetry-Breaking for Airflow Control Optimization of an Oscillating-Water-Column System

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 895 ◽  
Author(s):  
Fares M’zoughi ◽  
Izaskun Garrido ◽  
Aitor J. Garrido
Keyword(s):  
Symmetry Breaking ◽  
Water Column ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Search Time ◽  
Pso Algorithm ◽  
Search Space ◽  
Oscillating Water Column ◽  
Column System ◽  
Control Optimization

Global optimization problems are mostly solved using search methods. Therefore, decreasing the search space can increase the efficiency of their solving. A widely exploited technique to reduce the search space is symmetry-breaking, which helps impose constraints on breaking existing symmetries. The present article deals with the airflow control optimization problem in an oscillating-water-column using the Particle Swarm Optimization (PSO). In an effort to ameliorate the efficiency of the PSO search, a symmetry-breaking technique has been implemented. The results of optimization showed that shrinking the search space helped to reduce the search time and ameliorate the efficiency of the PSO algorithm.

Improved Particle Swarm Optimizer with Dynamically Adjusted Search Space and Velocity Limits for Global Optimization

2015 ◽  
Vol 24 (05) ◽  
pp. 1550017 ◽  
Author(s):  
Aderemi Oluyinka Adewumi ◽  
Akugbe Martins Arasomwan
Keyword(s):  
Global Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Particle Swarm Optimizer ◽  
Search Range ◽  
Original Algorithm ◽  
Inertia Weight ◽  
And Performance

This paper presents an improved particle swarm optimization (PSO) technique for global optimization. Many variants of the technique have been proposed in literature. However, two major things characterize many of these variants namely, static search space and velocity limits, which bound their flexibilities in obtaining optimal solutions for many optimization problems. Furthermore, the problem of premature convergence persists in many variants despite the introduction of additional parameters such as inertia weight and extra computation ability. This paper proposes an improved PSO algorithm without inertia weight. The proposed algorithm dynamically adjusts the search space and velocity limits for the swarm in each iteration by picking the highest and lowest values among all the dimensions of the particles, calculates their absolute values and then uses the higher of the two values to define a new search range and velocity limits for next iteration. The efficiency and performance of the proposed algorithm was shown using popular benchmark global optimization problems with low and high dimensions. Results obtained demonstrate better convergence speed and precision, stability, robustness with better global search ability when compared with six recent variants of the original algorithm.

scholarly journals STUDI POTENSI PEMBANGKIT LISTRIK TENAGA GELOMBANG LAUT DENGAN METODA OSCILATING WATER COLUMN DI PERAIRAN KENDARI INDONESIA

2019 ◽  
Vol 4 (1) ◽  
pp. 7
Author(s):  
Faulincia Faulincia
Keyword(s):  
Water Column ◽  
Alternative Energy ◽  
Water System ◽  
Electrical Energy ◽  
Ocean Wave ◽  
Oscillating Water Column ◽  
Alternative Energy Sources ◽  
Column System ◽  
Ocean Wave Energy ◽  
Wave Conversion

<p>Referring to Law Number 30 of 2007 concerning Energy, the development of techniques the conversion of electrical energy by using alternative energy sources is interesting for followed for the past few years. This paper discusses calculation analysis power potential of ocean wave conversion using the Oscilating Water system Column (OWC) in the marine area of Indonesia. This system was chosen because it has many advantages compared to other systems and in accordance with the marine and coastal areas of Indonesia. From the calculation of power, the smallest power that can be produced is equal to 348.5838 Watts while the biggest power that can be produced is 623291.4 Watts The application of the oscillating water column system in Kendari waters with an efficiency of 11.971%.<br />Keywords. oscillating water column (OWC), ocean wave energy, electrical energy, power potential,<br />wavelength</p>

scholarly journals Computational Fluid Dynamics Model of Wells Turbine for Oscillating Water Column System: A Review

2021 ◽  
Vol 2053 (1) ◽  
pp. 012013
Author(s):  
N. Abdul Settar ◽  
S. Sarip ◽  
H.M. Kaidi
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Water Column ◽  
Cfd Simulation ◽  
Oscillating Water Column ◽  
Wells Turbine ◽  
Flow Problems ◽  
Cfd Models ◽  
Column System ◽  
Cfd Method

Abstract Wells turbine is an important component in the oscillating water column (OWC) system. Thus, many researchers tend to improve the performance via experiment or computational fluid dynamics (CFD) simulation, which is cheaper. As the CFD method becomes more popular, the lack of evidence to support the parameters used during the CFD simulation becomes a big issue. This paper aims to review the CFD models applied to the Wells turbine for the OWC system. Journal papers from the past ten years were summarized in brief critique. As a summary, the FLUENT and CFX software are mostly used to simulate the Wells turbine flow problems while SST k-ω turbulence model is the widely used model. A grid independence test is essential when doing CFD simulation. In conclusion, this review paper can show the research gap for CFD simulation and can reduce the time in selecting suitable parameters when involving simulation in the Wells turbine.

Space Contraction and Partition Algorithm for Combinatorial Optimization

2011 ◽  
Vol 421 ◽  
pp. 559-563
Author(s):  
Yong Chao Gao ◽  
Li Mei Liu ◽  
Heng Qian ◽  
Ding Wang
Keyword(s):  
Combinatorial Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Solution Space ◽  
Search Space ◽  
Small Scale ◽  
Optimal Solutions ◽  
Solution Quality ◽  
Intelligent Algorithms ◽  
Combinatorial Optimization Problems

The scale and complexity of search space are important factors deciding the solving difficulty of an optimization problem. The information of solution space may lead searching to optimal solutions. Based on this, an algorithm for combinatorial optimization is proposed. This algorithm makes use of the good solutions found by intelligent algorithms, contracts the search space and partitions it into one or several optimal regions by backbones of combinatorial optimization solutions. And optimization of small-scale problems is carried out in optimal regions. Statistical analysis is not necessary before or through the solving process in this algorithm, and solution information is used to estimate the landscape of search space, which enhances the speed of solving and solution quality. The algorithm breaks a new path for solving combinatorial optimization problems, and the results of experiments also testify its efficiency.

Evolutionary Algorithm Embedded With Bump-Hunting for Constrained Design Optimization

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Kamrul Hasan Rahi ◽  
Hemant Kumar Singh ◽  
Tapabrata Ray
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Feasible Solution ◽  
Optimization Problems ◽  
Computational Cost ◽  
Search Space ◽  
Bump Hunting ◽  
Simulation Based ◽  
Engineering Problems ◽  
Turbine Design

Abstract Real-world design optimization problems commonly entail constraints that must be satisfied for the design to be viable. Mathematically, the constraints divide the search space into feasible (where all constraints are satisfied) and infeasible (where at least one constraint is violated) regions. The presence of multiple constraints, constricted and/or disconnected feasible regions, non-linearity and multi-modality of the underlying functions could significantly slow down the convergence of evolutionary algorithms (EA). Since each design evaluation incurs some time/computational cost, it is of significant interest to improve the rate of convergence to obtain competitive solutions with relatively fewer design evaluations. In this study, we propose to accomplish this using two mechanisms: (a) more intensified search by identifying promising regions through “bump-hunting,” and (b) use of infeasibility-driven ranking to exploit the fact that optimal solutions are likely to be located on constraint boundaries. Numerical experiments are conducted on a range of mathematical benchmarks and empirically formulated engineering problems, as well as a simulation-based wind turbine design optimization problem. The proposed approach shows up to 53.48% improvement in median objective values and up to 69.23% reduction in cost of identifying a feasible solution compared with a baseline EA.

scholarly journals Effect of wall inclination on the dynamic behaviour of an oscillating water column system

2020 ◽  
Vol 307 ◽  
pp. 01021
Author(s):  
Abdelhamid El Barakaz ◽  
Abdellatif El Marjani ◽  
Hamid Mounir
Keyword(s):  
Water Column ◽  
Natural Frequency ◽  
Wave Energy ◽  
Maximum Efficiency ◽  
Oscillating Water Column ◽  
Wave Energy Converters ◽  
Column System ◽  
Resonance Domain ◽  
Pneumatic Chamber ◽  
Chamber Model

The Oscillating Water Column device (OWC) is one of the most used Wave Energy Converters (WECs) for wave energy harvesting. It consists essentially of two parts: the pneumatic chamber made of concrete and the bidirectional turbine linked to a generator group for energy production. In this study we are interested in the water motion oscillation inside the chamber resulting from the water level perturbation. This process is characterized by its own natural frequency and global damping. The vertical OWC chamber model is limited by the number of parameters defining the natural frequency and the global damping. The objective of this paper is to improve the performances obtained for the vertical OWC by considering an OWC with inclined sidewalls. For maximum efficiency, the device must operate in the resonance domain where the damping is low and the frequency of incoming waves matches with the natural frequency of the OWC. This will theoretically amplify the pneumatic energy to be converted to a mechanical one in the turbine.

scholarly journals On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Martins Akugbe Arasomwan ◽  
Aderemi Oluyinka Adewumi
Keyword(s):  
Global Optimization ◽  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Terminal Point ◽  
Simulation Experiments ◽  
Swarm Optimization ◽  
Inertia Weight

Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. Researchers have tried to address this shortcoming by modifying LDIW-PSO or proposing new PSO variants. Some of these variants have been claimed to outperform LDIW-PSO. The major goal of this paper is to experimentally establish the fact that LDIW-PSO is very much efficient if its parameters are properly set. First, an experiment was conducted to acquire a percentage value of the search space limits to compute the particle velocity limits in LDIW-PSO based on commonly used benchmark global optimization problems. Second, using the experimentally obtained values, five well-known benchmark optimization problems were used to show the outstanding performance of LDIW-PSO over some of its competitors which have in the past claimed superiority over it. Two other recent PSO variants with different inertia weight strategies were also compared with LDIW-PSO with the latter outperforming both in the simulation experiments conducted.

scholarly journals A Symmetry-Breaking Node Equivalence for Pruning the Search Space in Backtracking Algorithms

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1300
Author(s):  
Uroš Čibej ◽  
Luka Fürst ◽  
Jurij Mihelič
Keyword(s):  
Symmetry Breaking ◽  
Optimization Problem ◽  
Heuristic Method ◽  
Search Space ◽  
Search Tree ◽  
Backtracking Search ◽  
Complete Problems ◽  
Np Complete ◽  
Complexity Hierarchy ◽  
General Graphs

We introduce a new equivalence on graphs, defined by its symmetry-breaking capability. We first present a framework for various backtracking search algorithms, in which the equivalence is used to prune the search tree. Subsequently, we define the equivalence and an optimization problem with the goal of finding an equivalence partition with the highest pruning potential. We also position the optimization problem into the computational-complexity hierarchy. In particular, we show that the verifier lies between P and NP -complete problems. Striving for a practical usability of the approach, we devise a heuristic method for general graphs and optimal algorithms for trees and cycles.

Sign in / Sign up

Export Citation Format

Share Document