A novel optimization approach for axial turbine blade cascade via combination of a continuous-curvature parameterization method and genetic algorithm

2021 ◽  
Author(s):  
Mehrdad Nafar-Sefiddashti ◽  
Mahdi Nili-Ahmadabadi ◽  
Behnam Saeedi-Rizi ◽  
Ebrahim Shirani ◽  
Kyung Chun Kim
Keyword(s):  
Genetic Algorithm ◽  
Turbine Blade ◽  
Optimization Approach ◽  
Axial Turbine ◽  
Parameterization Method ◽  
Blade Cascade ◽  
Continuous Curvature

scholarly journals Discovering the maximum k-clique on social networks using bat optimization algorithm

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Akram Khodadadi ◽  
Shahram Saeidi
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Coding Theory ◽  
Evaluation Criteria ◽  
Convergence Speed ◽  
Optimization Approach ◽  
Computational Results ◽  
Complete Subgraph ◽  
Np Complete

AbstractThe k-clique problem is identifying the largest complete subgraph of size k on a network, and it has many applications in Social Network Analysis (SNA), coding theory, geometry, etc. Due to the NP-Complete nature of the problem, the meta-heuristic approaches have raised the interest of the researchers and some algorithms are developed. In this paper, a new algorithm based on the Bat optimization approach is developed for finding the maximum k-clique on a social network to increase the convergence speed and evaluation criteria such as Precision, Recall, and F1-score. The proposed algorithm is simulated in Matlab® software over Dolphin social network and DIMACS dataset for k = 3, 4, 5. The computational results show that the convergence speed on the former dataset is increased in comparison with the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) approaches. Besides, the evaluation criteria are also modified on the latter dataset and the F1-score is obtained as 100% for k = 5.

Optimization of Supersonic Axial Turbine Blades Based on Surrogate Models

2020 ◽  
Author(s):  
Markus Waesker ◽  
Bjoern Buelten ◽  
Norman Kienzle ◽  
Christian Doetsch
Keyword(s):  
Reynolds Number ◽  
Turbine Blade ◽  
Surrogate Model ◽  
Cfd Simulation ◽  
Turbine Blades ◽  
Energy System ◽  
Design Parameters ◽  
Blade Design ◽  
Axial Turbine ◽  
Velocity Coefficient

Abstract Due to the transition of the energy system to more decentralized sector-coupled technologies, the demand on small, highly efficient and compact turbines is steadily growing. Therefore, supersonic impulse turbines have been subject of academic research for many years because of their compact and low-cost conditions. However, specific loss models for this type of turbine are still missing. In this paper, a CFD-simulation-based surrogate model for the velocity coefficient, unique incidence as well as outflow deviation of the blade, is introduced. This surrogate model forms the basis for an exemplary efficiency optimization of the “Colclough cascade”. In a first step, an automatic and robust blade design methodology for constant-channel blades based on the supersonic turbine blade design of Stratford and Sansome is shown. The blade flow is fully described by seven geometrical and three aerodynamic design parameters. After that, an automated numerical flow simulation (CFD) workflow for supersonic turbine blades is developed. The validation of the CFD setup with a published supersonic axial turbine blade (Colclough design) shows a high consistency in the shock waves, separation zones and boundary layers as well as velocity coefficients. A design of experiments (DOE) with latin hypercube sampling and 1300 sample points is calculated. This CFD data forms the basis for a highly accurate surrogate model of supersonic turbine blade flow suitable for Mach numbers between 1.1 and 1.6. The throat-based Reynolds number is varied between 1*104 and 4*105. Additionally, an optimization is introduced, based on the surrogate model for the Reynolds number and Mach number of Colclough and no degree of reaction (equal inlet and outlet static pressure). The velocity coefficient is improved by up to 3 %.

scholarly journals Genetic algorithm hyper-parameter optimization using Taguchi design for groundwater pollution source identification

2018 ◽  
Vol 19 (1) ◽  
pp. 137-146 ◽  
Author(s):  
Xuemin Xia ◽  
Simin Jiang ◽  
Nianqing Zhou ◽  
Xianwen Li ◽  
Lichun Wang
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Parameter Tuning ◽  
Pollution Source ◽  
Heterogeneous Porous Media ◽  
Optimization Approach ◽  
Human Beings ◽  
Transient Transport ◽  
Tuning Method ◽  
Pollutant Source

Abstract Groundwater pollution has been a major concern for human beings, since it is inherently related to people's health and fitness and the ecological environment. To improve the identification of groundwater pollution, many optimization approaches have been developed. Among them, the genetic algorithm (GA) is widely used with its performance depending on the hyper-parameters. In this study, a simulation–optimization approach, i.e., a transport simulation model with a genetic optimization algorithm, was utilized to determine the pollutant source fluxes. We proposed a robust method for tuning the hyper-parameters based on Taguchi experimental design to optimize the performance of the GA. The effectiveness of the method was tested on an irregular geometry and heterogeneous porous media considering steady-state flow and transient transport conditions. Compared with traditional GA with default hyper-parameters, our proposed hyper-parameter tuning method is able to provide appropriate parameters for running the GA, and can more efficiently identify groundwater pollution.

Loss Predictions in the High-Pressure Film-Cooled Turbine Blade Cascade T120D by Mean of Wall-Resolved Large Eddy Simulation

2020 ◽  
Author(s):  
Mael Harnieh ◽  
Nicolas Odier ◽  
Jérôme Dombard ◽  
Florent Duchaine ◽  
Laurent Gicquel
Keyword(s):  
High Pressure ◽  
Large Eddy Simulation ◽  
Turbine Blade ◽  
Film Cooling ◽  
Load Prediction ◽  
Loss Assessment ◽  
Film Cooling Effectiveness ◽  
Eddy Simulation ◽  
Blade Cascade ◽  
Large Eddy

Abstract Film cooling is commonly used to protect turbine vanes and blades from the hot gases produced in the combustion chamber. The design and optimization of these systems can however only be achieved if a precise prediction of the fluid mechanics and film efficiency is guaranteed at a level where induced losses are fully mastered. Such a prerequisite induces at the numerical level to be able to identify and assess losses. In this context, the present study addresses loss assessment in a wall-resolved Large Eddy Simulation (LES) of the film-cooled high-pressure turbine blade cascade T120D from the European project AITEB II. The objectives are twofolds: (1) to evaluate the capacity of LES to predict adiabatic film cooling effectiveness in a mastered academic case; and (2) to investigate loss generation mechanisms in a fully anisothermal configuration. When it comes to LES predictions of T120D, the flow structure around the blade and the coolant jet organization are coherent with literature findings. Satisfactory agreements are furthermore retrieved for the pressure load prediction as well as the adiabatic film effectiveness if compared to the experiment. Loss generation is then investigated illustrating the fact that aerodynamics losses dominate mixing losses which are mainly located in the coolant film. This is in line with the temperature difference between the hot and coolant flows that is low for this experimental condition. Distinct contributions can however be made available by studying the local loss generation maps by means of Second Law Analysis if recast in the specific context of anisothermal flows when simulated by LES.

The best angle of hot steam injection holes in the 3D steam turbine blade cascade

2022 ◽  
Vol 173 ◽  
pp. 107387
Author(s):  
Amir Kafaei ◽  
Fahime Salmani ◽  
Esmail Lakzian ◽  
Włodzimierz Wróblewski ◽  
Mikhail S. Vlaskin ◽  
...  
Keyword(s):  
Steam Turbine ◽  
Turbine Blade ◽  
Steam Injection ◽  
Blade Cascade ◽  
Steam Turbine Blade
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