Coupled Multipoint Shape Optimization of Runner and Draft Tube of Hydraulic Turbines

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
A. E. Lyutov ◽  
D. V. Chirkov ◽  
V. A. Skorospelov ◽  
P. A. Turuk ◽  
S. G. Cherny
Keyword(s):  
Boundary Conditions ◽  
Shape Optimization ◽  
Optimization Problems ◽  
Draft Tube ◽  
Francis Turbine ◽  
Geometrical Parameters ◽  
International Electrotechnical Commission ◽  
Multi Objective ◽  
Wide Range ◽  
Hydraulic Turbines

This paper suggests a method of simultaneous multi-objective shape optimization of hydraulic turbine runner and draft tube (DT) with the objective to increase turbine efficiency in wide range of operating points (OPs). Runner and DT are the main sources of energy losses in hydraulic turbines. Coupling runner and DT in computational fluid dynamics (CFD) analysis enables correct statement of boundary conditions for efficiency evaluation, while simultaneous variation of these components allows more flexible adjustment of flow passage geometry. Detailed runner parameterization with 28 free geometrical parameters and DT parameterization with nine free parameters are given. Optimization problem is solved using multi-objective genetic algorithm (MOGA). For each variation of runner and DT shapes, flow field in wicket gate (WG), runner, and DT is simulated using steady-state Reynolds-Averaged Navier–Stokes (RANS) equations with k-e turbulence model. Energy-based boundary conditions are used for the calculations, allowing determination of efficiency of the whole turbine in correspondence with International Electrotechnical Commission (IEC) standard. Formulations of multiple OP efficiency objective functions and constraints are discussed in detail. To demonstrate the advantages of simultaneous runner and DT variation, two optimization problems are solved for a medium specific speed Francis turbine. Namely, single runner and coupled “runner–DT” optimizations are carried out. It is shown that optimized runner–DT geometry outperforms the result of single runner optimization by about 0.3% in terms of average efficiency, showing the potential of the developed approach to improve multiregime turbine characteristics in practical design optimization problems.

scholarly journals Manipulation of the swirling flow instability in hydraulic turbine diffuser by different methods of water injection

2018 ◽  
Vol 180 ◽  
pp. 02090 ◽  
Author(s):  
Pavel Rudolf ◽  
Jiří Litera ◽  
Germán Alejandro Ibarra Bolanos ◽  
David Štefan
Keyword(s):  
Swirling Flow ◽  
Flow Instability ◽  
Draft Tube ◽  
Water Injection ◽  
Hydraulic Turbine ◽  
Operating Conditions ◽  
Francis Turbine ◽  
Necessary Condition ◽  
Vortex Rope ◽  
Wide Range

Vortex rope, which induces substantial pressure pulsations, arises in the draft tube (diffuser) of Francis turbine for off-design operating conditions. Present paper focuses on mitigation of those pulsations using active water jet injection control. Several modifications of the original Susan-Resiga’s idea were proposed. All modifications are driven by manipulation of the shear layer region, which is believed to play important role in swirling flow instability. While some of the methods provide results close to the original one, none of them works in such a wide range. Series of numerical experiments support the idea that the necessary condition for vortex rope pulsation mitigation is increasing the fluid momentum along the draft tube axis.

scholarly journals Characteristic analysis of the efficiency hill chart of Francis turbine for different water heads

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769007 ◽  
Author(s):  
Pengcheng Guo ◽  
Zhaoning Wang ◽  
Longgang Sun ◽  
Xingqi Luo
Keyword(s):  
Incidence Angle ◽  
Suction Side ◽  
Francis Turbine ◽  
Small Range ◽  
Characteristic Analysis ◽  
Wide Range ◽  
Low Head ◽  
Model Efficiency ◽  
Hydraulic Turbines ◽  
High Head

According to several model test results of Francis turbines, complete model efficiency hill charts were constructed. The formation and inevitability of diversified hydraulic phenomena on model efficiency hill chart for typical head range were analyzed and the difference is compared, as well as characteristics and commonness toward the curves are discussed and summarized. Furthermore, hydraulic performance and geometric features are presented by particularly analyzing the efficiency hill charts. The inherent characteristics of Francis turbine is expressed by all kinds of curves on the model efficiency hill charts, and these curves can be adjusted and moved in a small range but cannot be removed out. Due to wide range of unit speed in terms of medium-low-head hydraulic turbines, incipient cavitation curve on suction side can be observed and it is positioned close to the operation zone; however, it fails to be visualized for the high-head turbine. The blade channel vortex curves are in the vicinity of optimum region for low-head hydraulic turbines, while high-head shows reverse trend. The interaction between zero incidence angle and zero circulation curve has a significant influence on isoefficiency circles. All comparisons and analyses could provide hydraulic design basis and retrofit references.

The Hybrid Differential Evolution with Dynamic Scaling Mutation and Wrapper Local Search for Optimization Problems

2013 ◽  
Vol 479-480 ◽  
pp. 989-995
Author(s):  
Chun Liang Lu ◽  
Shih Yuan Chiu ◽  
Chih Hsu Hsu ◽  
Shi Jim Yen
Keyword(s):  
Local Search ◽  
Differential Evolution ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Problems ◽  
Search Space ◽  
Dynamic Scaling ◽  
Multi Objective ◽  
Wide Range ◽  
Single Objective

In this paper, an improved hybrid Differential Evolution (DE) is proposed to enhance optimization performance by cooperating Dynamic Scaling Mutation (DSM) and Wrapper Local Search (WLS) schemes. When evolution speed is standstill, DSM can improve searching ability to achieve better balance between exploitation and exploration in the search space. Furthermore, WLS can disturb individuals to fine tune the searching range around and then properly find better solutions in the evolution progress. The effective particle encoding representation named Particle Segment Operation-Machine Assignment (PSOMA) that we previously published is also applied to always produce feasible candidate solutions for hybrid DE model to solve the Flexible Job-Shop Scheduling Problem (FJSP). To test the performance of the proposed hybrid method, the experiments contain five frequently used CEC 2005 numerical functions and three representative FJSP benchmarks for single-objective and multi-objective optimization verifications, respectively. Compare the proposed method with the other related published algorithms, the simulation results indicate that our proposed method exhibits better performance for solving most the test functions for single-objective problems. In addition, the wide range of Pareto-optimal solutions and the more Gantt chart diversities can be obtained for the multi-objective FJSP in practical decision-making considerations.

scholarly journals ADAPTIVE HARMONY SEARCH FOR OPTIMIZING CONSTRAINED RESOURCE ALLOCATION PROBLEM

2018 ◽  
pp. 260-269
Author(s):  
Amol C. Adamuthe ◽  
Tushar R. Nitave
Keyword(s):  
Resource Allocation ◽  
Optimization Problems ◽  
Harmony Search ◽  
Population Diversity ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Multi Objective ◽  
Wide Range ◽  
Allocation Problems ◽  
Population Based Algorithm

Resource Allocation problem is finding the optimal assignment of finite available resources to tasks or users. Resource allocation problems refer to a wide range of applications such as production, supply chain management, transportation, ICT technologies, etc. Resource allocation problems are NP-hard in nature where the objective is to find the optimal allocations satisfying given constraints. Harmony search (HS) algorithm is a meta-heuristic population based algorithm found good for solving different optimization problems. This paper presents adaptive harmony search (AHS) for solving one-dimensional bin packing problem (BPP) and multi-objective virtual machine placement problem (VMP). The proposed real coded solution representation supports partial constraint satisfaction. Adaptive pitch adjustment rate (PAR) based on population diversity improves the performance of harmony search algorithm. Results show that proposed HS gives optimal solution for 50 BPP instances with 100 % success rate. The performance reduced for large instances of BPP. The proposed weighted AHS for multi objective VMP problem gives better results than genetic algorithm.

scholarly journals Design of Experiments Applied to Francis Turbine Draft Tube to Minimize Pressure Pulsations and Energy Losses in Off-Design Conditions

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3894
Author(s):  
Arthur Favrel ◽  
Nak-Joong Lee ◽  
Tatsuya Irie ◽  
Kazuyoshi Miyagawa
Keyword(s):  
Draft Tube ◽  
Pressure Fluctuations ◽  
Internal Flow ◽  
Francis Turbine ◽  
Energy Losses ◽  
Geometrical Parameters ◽  
Cfd Simulations ◽  
Part Load ◽  
Full Load ◽  
Load Conditions

This paper proposes an original approach to investigate the influence of the geometry of Francis turbines draft tube on pressure fluctuations and energy losses in off-design conditions. It is based on Design of Experiments (DOE) of the draft tube geometry and steady/unsteady Computational Fluid Dynamics (CFD) simulations of the draft tube internal flow. The test case is a Francis turbine unit of specific speed Ns=120 m-kW which is required to operate continuously in off-design conditions, either with 45% (part-load) or 110% (full-load) of the design flow rate. Nine different draft tube geometries featuring a different set of geometrical parameters are first defined by an orthogonal array-based DOE approach. For each of them, unsteady and steady CFD simulations of the internal flow from guide vane to draft tube outlet are performed at part-load and full-load conditions, respectively. The influence of each geometrical parameter on both the flow instability and resulting pressure pulsations, as well as on energy losses in the draft tube, are investigated by applying an Analysis of Means (ANOM) to the numerical results. The whole methodology enables the identification of a set of geometrical parameters minimizing the pressure fluctuations occurring in part-load conditions as well as the energy losses in both full-load and part-load conditions while maintaining the requested pressure recovery. Finally, the results of the CFD simulations with the final draft tube geometry are compared with the results estimated by the ANOM, which demonstrates that the proposed methodology also enables a rough preliminary estimation of the draft tube losses and pressure fluctuations amplitude.

scholarly journals Multi-Objective Optimization Through Pareto Minimal Correction Subsets

2018 ◽  
Author(s):  
Miguel Terra-Neves ◽  
Inês Lynce ◽  
Vasco Manquinho
Keyword(s):  
Constrained Optimization ◽  
Optimization Problems ◽  
State Of The Art ◽  
Optimal Solution ◽  
Approximate Solutions ◽  
Pareto Optimal ◽  
Constrained Optimization Problems ◽  
Multi Objective ◽  
Wide Range ◽  
Constraint Set

A Minimal Correction Subset (MCS) of an unsatisfiable constraint set is a minimal subset of constraints that, if removed, makes the constraint set satisfiable. MCSs enjoy a wide range of applications, such as finding approximate solutions to constrained optimization problems. However, existing work on applying MCS enumeration to optimization problems focuses on the single-objective case. In this work, Pareto Minimal Correction Subsets (Pareto-MCSs) are proposed for approximating the Pareto-optimal solution set of multi-objective constrained optimization problems. We formalize and prove an equivalence relationship between Pareto-optimal solutions and Pareto-MCSs. Moreover, Pareto-MCSs and MCSs can be connected in such a way that existing state-of-the-art MCS enumeration algorithms can be used to enumerate Pareto-MCSs. Finally, experimental results on the multi-objective virtual machine consolidation problem show that the Pareto-MCS approach is competitive with state-of-the-art algorithms.

scholarly journals Multi-objective Optimization of Draft Tube in Francis Turbine Using DOE, RBF and NSGA-II

2017 ◽  
Author(s):  
Chol Nam Mun ◽  
De Chun Ba ◽  
Xiang Ji Yue ◽  
Myong Il Kim
Keyword(s):  
Draft Tube ◽  
Fluid Dynamic ◽  
Hydraulic Turbine ◽  
Optimization Method ◽  
Approximate Model ◽  
Francis Turbine ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Design Matrix ◽  
Nsga Ii

In order to improve the performance of the draft tube in hydraulic turbine, a multi–objective optimization method for the draft tube is developed by combining the design of experiment (DOE), the radial basis function (RBF) and the non–dominated sorting genetic algorithm (NSGA–II) in this paper. The geometrical design variables of the median section in the draft tube and the cross section in its exit diffuser are considered as design parameters in this optimization, which objective function is to maximize the pressure recovery factor (Cp) and minimize the energy loss coefficient (ζ). The limited numbers of design matrix required for the shape optimization of the draft tube is generated by optimal Latin hypercube (OLH) method of the DOE technique, of which performances are evaluated through computational fluid dynamic (CFD) numerical simulation. For reducing of the computational consumption, the approximate model is used based on the RBF. The Pareto optimal solutions are finally performed using the NSGA–II for obtaining the best geometrical parameters of the draft tube. The optimization result of the draft tube shows a marked performance improvement over the original, which verifies the theoretical validity and feasibility of the proposed method in this paper.

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