Application of deep learning to study aggregative and non-aggregative nanofluid flow within the nozzle of a liquid rocket engine
Abstract We have used Bayesian Regularization Back Propagation based deep neural
networks to analyze the flow and heat transfer behavior for the flow of a nanofluid (aluminum …
networks to analyze the flow and heat transfer behavior for the flow of a nanofluid (aluminum …
[HTML][HTML] Design of integrated evolutionary finite differences for nonlinear electrohydrodynamics ion drag flow in cylindrical conduit model
This research implements an evolutionary optimized finite differences scheme (FDS) for
nonlinear electrohydrodynamics ion drag flow dynamics in a cylindrical conduit (EHD …
nonlinear electrohydrodynamics ion drag flow dynamics in a cylindrical conduit (EHD …
Novel polynomial Abet data augmentation algorithm with GRU paradigm for nuclear power prediction
In current study innovative approach is presented to improve the accuracy and efficiency of
machine learning models on the dataset for each of the 31 US states, solely comprising a …
machine learning models on the dataset for each of the 31 US states, solely comprising a …
Numerical treatment for double diffusion phenomenon with generalized heat flux effects in 3d nanomaterial flow over bi-directional stretched wall
Current study aims to numerically investigate the bi-directional flow of nanofluids in the
presence of Cattaneo–Christov double diffusion for two heat sources, namely, prescribed …
presence of Cattaneo–Christov double diffusion for two heat sources, namely, prescribed …
Electro osmotic flow of nanofluids within a porous symmetric tapered ciliated channel
A Imran, M Abbas, SE Awan, M Shoaib… - ZAMM‐Journal of …, 2024 - Wiley Online Library
In this investigation, a comprehensive study has been made to reveal electro osmosis flow
through a tapered ciliated symmetric porous channel. The flow is initiated due to …
through a tapered ciliated symmetric porous channel. The flow is initiated due to …
Evaluation of aircraft engine performance during takeoff phase with machine learning methods
B Kurt - Neural Computing and Applications, 2024 - Springer
During the takeoff phase, aircraft engines reach maximum speed and temperature to
achieve the required thrust. Due to these harsh operating conditions, the performance of …
achieve the required thrust. Due to these harsh operating conditions, the performance of …
Generating Mathematical Expressions for Estimation of Atomic Coordinates of Carbon Nanotubes Using Genetic Programming Symbolic Regression
N Anđelić, S Baressi Šegota - Technologies, 2023 - mdpi.com
The study addresses the formidable challenge of calculating atomic coordinates for carbon
nanotubes (CNTs) using density functional theory (DFT), a process that can endure for days …
nanotubes (CNTs) using density functional theory (DFT), a process that can endure for days …
A stochastic scale conjugate neural network procedure for the SIRC epidemic delay differential system
In this study, a stochastic computing structure is provided for the numerical solutions of the
SIRC epidemic delay differential model, ie SIRC-EDDM using the dynamics of the COVID …
SIRC epidemic delay differential model, ie SIRC-EDDM using the dynamics of the COVID …