Multi-objective global optimization of a butterfly valve using genetic algorithms

Corbera, Sergio; Olazagoitia, José Luis; Lozano, José A.

doi:10.1016/j.isatra.2016.03.008

Cited by 45 publications

(16 citation statements)

References 13 publications

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“…This disc has a vertical axis of rotation whereby the closing of the valve produces a change in the fluid flow direction by diverting velocity profiles towards paths perpendicular to this axis of rotation. When the valve is completely open, it reduces the section of water way, increasing the average water velocity in the pipe [34]. This behaviour may be confirmed in other studies that used CFD techniques to simulate distortion water flow with butterfly valves with different degrees of closure [35,36].…”

Section: Computational Fluid Simulationsupporting

confidence: 66%

Numerical Analysis of Woltman Meter Accuracy under Flow Perturbations

Palau

Balbastre

Manzano

et al. 2019

Water

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One of the unknowns in the instrumentation for water measurement is what degree of influence other hydraulic elements exert on the velocity profile and, consequently, on the measurement errors. In this work, the measurement errors of a horizontal-axis Woltman meter produced by a gate valve and by a butterfly valve in different hydraulic configurations were studied using a simplified numerical model. The gate valve was installed beside the meter and three pipe diameters upstream of the meter and were operated with closures of 75%, 50% and 25%, while the butterfly valve was installed at three pipe diameters upstream of the meter with closures of 0 • (open) and 30 • . The numerical model based on the rotor's torque balance equations and Computational Fluid Dynamics (CFD) was validated by experimental tests. According to the results, it was concluded that the proposed model is valid and capable of estimating the errors caused by the hydraulic fittings arranged next to the meter. In addition, it is evident that for the analysed operating range, both valves must be installed at least three diameters of straight pipe upstream of the meter. Author Contributions: Conceptualization, C.V.P.; methodology, C.V.P., I.B. and J.M.; software, C.V.P., I.B. and J.M.; formal analysis, C.V.P., I.B. and J.M.; investigation, C.V.P., I.B.P. and J.M.; data curation, C.V.P., I.B.P. and J.M.; writing-original draft preparation, C.V.P.; writing-review and editing, C.V.P., B.M.A. and G.V.B.; visualization, C.V.P. and G.V.B.; supervision, C.V.P., B.M.A. ad J.M. Funding: This research received no external funding. Conflicts of Interest:The authors declare no conflict of interest.

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Section: Computational Fluid Simulationsupporting

confidence: 66%

Numerical Analysis of Woltman Meter Accuracy under Flow Perturbations

Palau

Balbastre

Manzano

et al. 2019

Water

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“…However, no mathematical modeling is given to the problem. In [9], authors suggest a multiobjective approach relying on Pareto dominance genetic algorithms to resolve the problem of designing butterfly valve. However, the proposed approach is based on a simple standard genetic algorithm.…”

Section: Related Work On the 2d-3d Deployment Problem Using Optimizamentioning

confidence: 99%

“…-The execution time of acMaMaPSO is high compared to other algorithms: in acMaMaPSO, we lose more execution time than acMaPSO but we gain the performance and the quality of the solution (although acMaPSO behavior is not so far from acMaMaPSO: see Figs. [6][7][8][9]. This runtime cost of acMaMaPSO is due to the time allocated to the communication between agents.…”

Section: Computational Complexity and Runtime Analysismentioning

confidence: 99%

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

et al. 2019

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h i g h l i g h t s• Proving the efficiency of optimization algorithms in solving real-world problems.• A new concept of accent birds introduced to the particle swarm optimization. • A new hybrid scheme that integrates PSO and MAS.• The hybridization improves the performance of the original tested algorithms. • A comparison between simulation and experimental validation is given. a r t i c l e i n f o Keywords: Accent based PSO Multi-agent Many-objective optimization Experimental validation 3D indoor deployment DL-IoT collection networks a b s t r a c tThe 3D indoor deployment of sensor nodes is a complex real world problem, proven to be NP-hard and difficult to resolve using classical methods. In this context, we propose a hybrid approach relying on a novel bird's accent-based many objective particle swarm optimization algorithm (named acMaPSO) to resolve the problem of 3D indoor deployment on the Internet of Things collection networks. The new concept of bird's accent is presented to assess the search ability of particles in their local areas. To conserve the diversity of the population during searching, particles are separated into different accent groups by their regional habitation and are classified into different categories of birds/particles in each cluster according to their common manner of singing. A particle in an accent-group can select other particles as its neighbors from its group or from other groups (which sing differently) if the selected particles have the same expertise in singing or are less experienced compared to this particle. To allow the search escaping from local optima, the most expert particles (parents) ''die'' and are regularly replaced by a novice (newborn) randomly generated ones. Moreover, the hybridization of the proposed acMaPSO algorithm with multi-agent systems is suggested. The new variant (named acMaMaPSO) takes advantage of the distribution and interactivity of particle agents. Experimental, numerical and statistical found results show the effectiveness of the two proposed variants compared to different other recent state-of-the-art of many-objective evolutionary algorithms.✩ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. * Correspondence to: bureau C107, Batiment C, 1 Place Georges positions and the topology of the network. In this study, we are interested in the deployment of nodes in a three-dimensional space that reflects the real topology of the RoI (region of interest) better than the two-dimensional case. We are particularly interested in improving the initial 3D indoor deployment by adding new nodes while optimizing a set of objectives such as coverage, connectivity, localization, quality of links and network utilization. These objectives will be detailed in the modeling section. To resolve the deployment problem in WSN, the topology of the network can be modeled as an identification problem in a graph as addressed in [1] and [2]. In this static case, the deployment algorithm is run off-...

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“…The population size of 110 is considered with a maximum generation number of 100. For complicated search space, the typical values for crossover probability are in the range of 0.6-0.95 and the mutation rate conventionally takes values in the range of 0.005-0.01 (33)(34)(35). Hence, the crossover probability and mutation rate are considered 0.7 and 0.01, respectively.…”

Section: Algorithmmentioning

confidence: 99%

Multi‐Objective Genetic Algorithm Assisted by an Artificial Neural Network Metamodel for Shape Optimization of a Centrifugal Blood Pump

et al. 2018

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A centrifugal blood pump is a common type of the pump used as a left ventricular assist device (LVAD) in the medical industries. The reduction of the LVADs hemolysis level to reduce the blood damage is one of the major concerns in designing of such devices. Also, the enhancement of the LVADs efficiency to decrease the battery size is another design requirement. The blood damage critically depends on the state of the blood being pumped. Besides the blood state, the blood damage also depends on the pump impeller and volute geometries. In this research, a multi-objective optimization of a centrifugal blood pump is performed. A complete 3D-optimization platform is established for both impeller and volute of a centrifugal blood pump consisting of parametric modeling, automatic mesh generation, computational fluid dynamics (CFD) simulation, and optimization strategy. A

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Multi-objective global optimization of a butterfly valve using genetic algorithms

Cited by 45 publications

References 13 publications

Numerical Analysis of Woltman Meter Accuracy under Flow Perturbations

Numerical Analysis of Woltman Meter Accuracy under Flow Perturbations

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

Multi‐Objective Genetic Algorithm Assisted by an Artificial Neural Network Metamodel for Shape Optimization of a Centrifugal Blood Pump

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