A5081309509- Fractional Differential Equations Solutions
- Differential Equations and Numerical Methods
- Nanofluid Flow and Heat Transfer
- Nonlinear Differential Equations Analysis
- Numerical methods in engineering
- Numerical methods for differential equations
- Rheology and Fluid Dynamics Studies
- Fluid Dynamics and Vibration Analysis
- Fluid Dynamics and Turbulent Flows
- Lattice Boltzmann Simulation Studies
- Iterative Methods for Nonlinear Equations
- Electromagnetic Simulation and Numerical Methods
- Heat Transfer Mechanisms
- Advanced Mathematical Modeling in Engineering
- Vibration and Dynamic Analysis
- Numerical methods in inverse problems
- Thermoelastic and Magnetoelastic Phenomena
- Heat and Mass Transfer in Porous Media
- Heat Transfer and Optimization
- Gear and Bearing Dynamics Analysis
- Tribology and Lubrication Engineering
- Magnetic Bearings and Levitation Dynamics
- Neural Networks and Applications
- Nonlinear Photonic Systems
- Polysaccharides and Plant Cell Walls
Queensland University of Technology
2016-2025
Hunan University
2023
University of Oxford
2023
Australian Research Council
2023
ARC Centre of Excellence for Mathematical and Statistical Frontiers
2023
Jinhua Polytechnic
2021
Xiamen University
2015-2016
In this work, the unsteady magnetohydrodynamics boundary layer flow and heat transfer of novel generalized Kelvin–Voigt viscoelastic nanofluids over a moving plate are investigated. The classical constitutive relation is to incorporate time-fractional derivative characterize fluid behavior, which proved be significance physically justified. newly developed fractional correlation dual-phase-lagging equation applied momentum energy equations, respectively, for nanofluid model plate. formulated...
Analytical solutions of space–time fractional partial differential equations (fPDEs) are crucial for understanding dynamics features in complex systems and their applications. In this paper, sub-equation neural networks (fSENNs) first proposed to construct exact fPDEs. The fSENNs embed the Riccati equation into (NNs). NNs a multi-layer computational models that composed weights activation functions between neurons input, hidden, output layers. fSENNs, every neuron hidden layer is assigned...
Abstract Due to the influence of various factors on bridge sensors, signals obtained often contain multiple signal components, including temperature and vehicle induced effect. It is necessary separate analyze individual in health detection. In order response components from complex signals, this article proposes an improved VMD algorithm based recursive methods, which takes mean value each block as eigenvalue, fits eigenvalues using least squares method, separates first intrinsic mode...
A comb structure consists of a one-dimensional backbone with lateral branches. These structures have widespread application in medicine and biology. Such promotes an anomalous diffusion process along the (x-direction), classical branches (y-direction). In this work, we propose distributed-order time- space-fractional diffusion-wave equation to model more general setting. The is firstly formulated study subject irregular convex domain motivation that time-fractional derivative considers...