Towards CFD-based optimization of urban wind conditions: Comparison of Genetic algorithm, Particle Swarm Optimization, and a hybrid algorithm

Kaseb, Z.; Rahbar, Morteza

doi:10.1016/j.scs.2021.103565

Cited by 32 publications

(5 citation statements)

References 42 publications

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“…These studies and the conclusion in [36] strengthened the application of GA and CFD in this study. In this context, GA shows potential for finding the best solution to optimization problems when combined with other methods.…”

Section: Relevant Studies Using Cfd and Gasupporting

confidence: 75%

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

et al. 2022

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In the event of a typhoon, the majority of houses suffer from large amounts of damage because they were not built with typhoon resilience in mind. For instance, the Philippines is one of the world’s most vulnerable countries to typhoons. Often, roof structures are ripped off during typhoons with average or more vigorous wind gustiness, and houses are easily ruined. This situation led us to search for the appropriate building orientation and roof angle of single-family residential houses through simulations using MATLAB’s genetic algorithm (GA) and SolidWorks’ computational fluid dynamics (CFD). The GA provides the set of design points, while CFD generates a fitness score for each design point. The goal of the optimization is to determine the orientation and roof angle while minimizing the drag force along the direction of a constant wind speed (315 km/h). The lower and upper bounds for house orientation are 0∘ and 90∘, respectively; the roof angle is between 3∘ and 60∘. After 100 generations, the GA converged to values equal to an 80∘ orientation and 11∘ roof angle. The final results provide a good standpoint for future experiments on physical structures.

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Section: Relevant Studies Using Cfd and Gasupporting

confidence: 75%

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

et al. 2022

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“…Rahmatian et al [9] illustrate the prowess of RSM in optimising various aspects of wind energy systems, including turbine energy recovery and control parameter optimisation. The authors of [39] recognise RSM's broad applicability, but they also acknowledge its limitations when dealing with nonlinear outputs. The work described in [40] introduces response surface optimisation (RSO) through the use of surrogate models, providing insights into the intricate impact of design parameters on vertical axis wind turbine performance.…”

Section: Introductionmentioning

confidence: 99%

Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology

Shambira,

Makaka,

Mukumba

2024

Sustainability

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Wind energy, renowned for cost-effectiveness and eco-friendliness, addresses global energy needs amid fossil fuel scarcity and environmental concerns. In low-wind speed regions, optimising wind turbine performance becomes vital and achievable by augmenting wind velocity at the turbine rotor using augmentation systems such as concentrators and diffusers. This study focuses on developing a velocity augmentation model that correctly predicts the throat velocity in an empty concentrator-diffuser-augmented wind turbine (CDaugWT) design and determines optimal geometrical parameters. Utilising response surface methodology (RSM) in Design Expert 13 and computational fluid dynamics (CFD) in ANSYS Fluent, 86 runs were analysed, optimising parameters such as diffuser and concentrator angles and lengths, throat length, and flange height. The ANOVA analysis confirmed the model’s significance (p < 0.05). Notably, the interaction between the concentrator’s length and the diffuser’s length had the highest impact on the throat velocity. The model showed a strong correlation (R2 = 0.9581) and adequate precision (ratio value of 49.655). A low coefficient of variation (C.V.% = 0.1149) highlighted the model’s reliability. The findings revealed a 1.953-fold increase in inlet wind speed at the throat position. Optimal geometrical parameters for the CDaugWT included a diffuser angle of 10°, concentrator angle of 20°, concentrator length of 375 mm (0.62Rth), diffuser length of 975 mm (1.61Rth), throat length of 70 mm (0.12Rth), and flange height of 100 mm (0.17Rth) where Rth is the throat radius. A desirability value of 0.9, close to 1, showed a successful optimisation. CFD simulations and RSM reduced calculation cost and time when determining optimal geometrical parameters for the CDaugWT design.

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“…Xue et al [24] gave a strategy pool consisting of four strategies in solving high-dimensional feature selection problems. In addition, the introduction of other intelligent algorithm's features can result in hybrid algorithms with better performance: Kaseb et al [25] added the crossover and mutation operators of GA to PSO, which further balanced the exploration and exploitation capability of the algorithm, and improved its ability to deal with wind conditions in cities. Shams et al [26] proposed a hybrid Dipper-Throated Optimization and Particle Swarm Optimization (DTPSO), combining the advantages of the Dipper-Throated Optimization algorithm and PSO for hepatocellular carcinoma prediction.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application

Wang,

Gao,

2024

Mathematics

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Particle Swarm Optimization (PSO) is facing more challenges in solving high-dimensional global optimization problems. In order to overcome this difficulty, this paper proposes a novel PSO variant of the hybrid Sine Cosine Algorithm (SCA) strategy, named Velocity Four Sine Cosine Particle Swarm Optimization (VFSCPSO). The introduction of the SCA strategy in the velocity formulation ensures that the global optimal solution is found accurately. It increases the flexibility of PSO. A series of experiments are conducted on the CEC2005 test suite with compositional algorithms, algorithmic variants, and good intelligent algorithms. The experimental results show that the algorithm effectively improves the overall performance of compositional algorithms; the Friedman test proves that the algorithm has good competitiveness. The algorithm also performs better in PID parameter tuning. Therefore, the VFSCPSO is able to solve the high-dimensional global optimization problems in a better way.

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Towards CFD-based optimization of urban wind conditions: Comparison of Genetic algorithm, Particle Swarm Optimization, and a hybrid algorithm

Cited by 32 publications

References 42 publications

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology

Hybrid Sine Cosine and Particle Swarm Optimization Algorithm for High-Dimensional Global Optimization Problem and Its Application

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