Computational analysis of INVELOX wind turbine to analyze the venturi velocity by change the parameter of diffuser

Suthagar, S.; Kumaran, T.; Gowtham, G.; Maridurai, Thirupathy; Sathish, T.; Deivanayagi, S.

doi:10.1016/j.matpr.2021.03.049

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…At the same time, all the nine samples were achieved with increasing SiC to 2 wt%, respectively. After that, nine processed AMCs specimens were utilized to the friction welding as earlier mentioned in input parameters [20]. The input parameters of friction welding are rotational speed (1,650, 1,850, and 2,050 rpm) and the forge pressure (10-20 MPa), respectively.…”

Section: Methodsmentioning

confidence: 99%

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Pushparaj¹,

Jeremiah²,

Solomon³

et al. 2023

Journal of Nanomaterials

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Nowadays, the aluminum metal matrix composites (AMCs) play an empirical role to improve the mechanical performance by various applications. Therefore, the secondary processes need to enhance the surface morphology of intermetallic phases with the appropriate reinforcing particles. In this research, Al7075- and ceramic-based nanosilicon carbide (SiC) were utilized to compose the metal matrix composites. These composites were subjected to friction welding for intermetallic surface modification with the various forging pressure and rotating speed. Initially, the AMCs were prepared with three (8–12) kinds of SiC weight proportions by the design of Taguchi L9 orthogonal array. As per the weight proportions, nine samples were prepared and then conducted the friction welding with 10–20 MPa of forge pressure and 1,650–2,050 rpm of rotational speed of spindle. Then, the entire nine specimens were allowed to conduct the tensile and microhardness test. During the mechanical test, the overall welded zone had higher mechanical properties than the base metal. Then, the artificial neural network was utilized to predict the output responses as per the designed concept of trial and error method. The overall predicted responses are nearly closed to the experimental values.

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Section: Methodsmentioning

confidence: 99%

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Pushparaj¹,

Jeremiah²,

Solomon³

et al. 2023

Journal of Nanomaterials

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“…But in this case, SiC significantly removes these minor issues during the stir casting. Figure 7 shows that the sample was accomplished with evenly dispersed SiCstrengthened particles, and mechanical characteristics also improved simultaneously [28]. Identifying the SiC particles in the micrographs is necessary for revealing the evidence.…”

Section: Microstructure On the Processed Specimen With A Maximum Frac...mentioning

confidence: 98%

Microstructure and Mechanical Characteristics of Stir-Casted AA6351 Alloy and Reinforced with Nanosilicon Carbide Particles

Thirugnanam¹,

Ananth²,

Krishnan³

et al. 2023

Journal of Nanomaterials

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The main aim of this research is to analyze the mechanical performances of the influence of silicon carbide (SiC) particles with AA6351 aluminum alloy. The aluminum metal matrix composites were prepared with liquefying stir casting to produce the metal matrix composites (MMCs). The following weight fractions are AA6351-0% SiC, AA6351-2.5% SiC, AA6351-5% SiC, and AA6351-7.5% SiC utilized to compose the MMCs. The mechanical performances like hardness, flexural, impact, compressive, and tensile studies were investigated on the processed MMCs. The scanning electron microscope (SEM) was employed to examine the strengthened particle of SiC. During the SEM examinations, uniformly dispersed SiC-strengthened particles were analyzed. The entire MMCs specimens achieve greater mechanical characteristics; the specimen fabricated with a maximum volume fraction of 7.5 wt% of SiC accumulates higher strength than the other volume fractions samples. The SiC plays a very tedious role in improving mechanical attributes. The fabricated MMCs were highly utilized in the applications of automotive and aerospace usages. This application is fully employed with lesser weight and maximum strength conditions to fulfill the mechanical performances. The stir-casting process was a highly efficient technique to compose better MMCs to achieve greater strength.

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“…The addition of more turbines did not affect the performance of the first turbine, as the flow resistance through the system remained unchanged [59]. Several numerical and experimental studies have been conducted to find the optimum design parameters of the INVELOX system such as the diffuser angle [60], the upper intake's dimensions [61,62], the guide vane's height [63], and the roof design [64]. Optimum design of the system using CFD analysis results in higher efficiency, lower losses, and maximized output power.…”

Section: Invelox Wind Systemmentioning

confidence: 99%

Techno-Economic Assessment for Installation of INVELOX Wind Turbines in Northern Iran

Taheri¹,

Taheri²

2021

Applied Engineering Letters

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This paper aims to provide a comprehensive feasibility study for the installation of a 100 MW wind power plant using the INVELOX system in Manjil, Gilan, in Northern Iran. In the first part of the paper, we provide a review of the status of wind energy installation in Iran. We then review the mathematical equations involved in wind power calculations. Afterwards, with the environmental data gathered from the corresponding authorities and open-access sources, we analyzed the INVELOX system with its benefits and drawbacks. Then, based on the derived mathematical formulations, and using simulation software packages, the average wind power density is calculated, and the turbine system is designed accordingly. Finally, the economic profitability of this project was examined using a mathematical economic analysis and the COMFAR software package. In addition to the detailed feasibility study of this specific project, this article aims to provide a comprehensive literature review of the INVELOX system.

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Computational analysis of INVELOX wind turbine to analyze the venturi velocity by change the parameter of diffuser

Cited by 4 publications

References 14 publications

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Microstructure and Mechanical Characteristics of Stir-Casted AA6351 Alloy and Reinforced with Nanosilicon Carbide Particles

Techno-Economic Assessment for Installation of INVELOX Wind Turbines in Northern Iran

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