Journal ArticleDOI
Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows
Asif Afzal,Abdul Aabid,Ambareen Khan,Sher Afghan Khan,Upendra Rajak,Tikendra Nath Verma,Rajesh Kumar +6 more
TLDR
In this article, the authors performed an experimental analysis of base pressure in suddenly expanded compressible flow from nozzles at different Mach numbers and found that microjets are efficient when the flow is under the influence of a favorable pressure gradient.About:
This article is published in Aerospace Science and Technology.The article was published on 2020-12-01. It has received 66 citations till now. The article focuses on the topics: Adverse pressure gradient & Mach number.read more
Citations
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Back propagation modeling of shear stress and viscosity of aqueous Ionic-MXene nanofluids
Asif Afzal,Kyathanahalli Marigowda Yashawantha,Navid Aslfattahi,Navid Aslfattahi,Rahman Saidur,Rahman Saidur,R. K. Abdul Razak,Ram Subbiah +7 more
TL;DR: In this paper, back-propagation modeling of viscosity and shear stress of Ionic-MXene nanofluid is carried out in order to obtain better performance.
Journal ArticleDOI
Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks.
Ballupete Nagaraju Sharath,Channarayapattana Venkataramaiah Venkatesh,Asif Afzal,Navid Aslfattahi,Abdul Aabid,Muneer Baig,B. Saleh +6 more
TL;DR: In this paper, the authors recognized the inclusion of ceramics such as Gr and B4C in manufacturing AMMCs through stir casting, and tested the composites for hardness and wear behaviour.
Journal ArticleDOI
A novel hybrid method for flight departure delay prediction using Random Forest Regression and Maximal Information Coefficient
TL;DR: The proposed RFR-MIC model exhibits good performance compared with linear regression, k-nearest neighbors, artificial neural network, and standard Random Forest Regression, and the results show that flight information on multiple air routes can certainly improve the accuracy of flight departure delay prediction.
Journal ArticleDOI
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
TL;DR: In this paper, a combined cycle power plant (CCPP) was modeled using different algorithms, including Ridge, Linear Regression (LR), Support Vector Regressor (SVR), and Upport vector Regressor(SVR).
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Finding the optimal design of a Cantor fractal-based AC electric micromixer with film heating sheet by a three-objective optimization approach
TL;DR: In this article , a three-objective optimization process for an Alternating Current (AC) electrothermal theory-based micromixer is presented, in which the width-to-length ratio (a/b) of the AC electrode based on the Cantor fractal, the inlet velocity (U), the voltage amplitude (V), and the heat of the film heating sheet (Q) are design variables.
References
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Physics-informed neural networks for high-speed flows
TL;DR: In this article, a physics-informed neural network (PINN) was used to approximate the Euler equations that model high-speed aerodynamic flows in one-dimensional and two-dimensional domains.
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Aircraft viscous drag reduction using riblets
TL;DR: In this paper, the performance of 3 M riblets on airfoils, wings and wing-body or aircraft configurations at different speed regimes are reviewed; these applications bring in additional effects like pressure gradients and three dimensionality.
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Machine learning methods for turbulence modeling in subsonic flows around airfoils
TL;DR: In this article, a high Reynolds number turbulent flows around the airfoils and the results calculated by the computational fluid dynamics solver with the Spallart-Allmaras (SA) model were used as training data to construct a high-dimensional data-driven network model based on machine learning.
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Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows
TL;DR: The objective of the work presented in this paper was to assess the online application and resulting benefits of an artificial intelligence system for detection of leaks/bursts at district meter area (DMA) level.
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Computational Fluid Dynamics in Turbomachinery: A Review of State of the Art
TL;DR: In this article, the authors reviewed the state of the art work carried out in the field of turbomachinery using computational fluid dynamics (CFD) and highlighted the prevailing merits and demerits of CFD in turbomachines.