Back to Search
Start Over
Shape optimization of bi-directional flow passage components based on a genetic algorithm and computational fluid dynamics
- Source :
- Engineering Optimization. 50:1287-1303
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- The inlet/outlet is an important part of a water conveyance system in a pumped storage power station (PSPS). Its hydraulic characteristics are directly related to the operation and economic benefit of the PSPS. Frequent changes between inflow and outflow operations pose significant challenges in the design of the inlet/outlet diffusion segment shape. In this study, an effective optimization method, including three-dimensional parametric modelling, computational fluid dynamics and a genetic algorithm, is introduced and coupled to the design of the diffusion segment shape. The hydraulic characteristics of bi-directional flow, including the head loss, velocity uneven distribution and uneven discharge distribution, are selected as the objective function in the optimization method. Using this method, the recommended shape of the inlet/outlet is studied and its hydraulic characteristics are discussed. The results indicate that the optimized inlet/outlet has better performance.
- Subjects :
- geography
Control and Optimization
geography.geographical_feature_category
business.industry
020209 energy
Applied Mathematics
Flow (psychology)
02 engineering and technology
Inflow
Mechanics
Management Science and Operations Research
Computational fluid dynamics
Inlet
Industrial and Manufacturing Engineering
Computer Science Applications
Hydraulic head
020303 mechanical engineering & transports
0203 mechanical engineering
Genetic algorithm
0202 electrical engineering, electronic engineering, information engineering
Environmental science
Shape optimization
Outflow
business
Subjects
Details
- ISSN :
- 10290273 and 0305215X
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- Engineering Optimization
- Accession number :
- edsair.doi...........8041944489614048fb0b3f40a16af482
- Full Text :
- https://doi.org/10.1080/0305215x.2017.1400543