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[CT148]

Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : The control of the thermal radiation influence on free convection of a multiple-port open cavity packed with water supported nanocomposite nanofluid is investigated numerically . One inlet port and two outlet ports are situated on the perpendicular walls. The remaining cavity walls are adiabatic. The heated thin baffle is located inside the cavity. The cavity is crammed with the water-supported nanodiamond–nickel nanocomposite. The governing Navier–stokes equations are written in the term of vorticity stream function transport. An ADI scheme-based finite difference process is used for discretization of the governing equations. The results are discussed graphically with the various parameters of radiation parameter, Reynolds number, Rayleigh number, solid volume fraction, widths of the opening, and locations of baffle position. It reveals that the average heat transfer rate reduces with the baffle placed far from the inlet.
Classification : 76Sxx, 76Rxx, 76Mxx
Format : Talk at Waseda University
Author(s) :
- muthtamilselvan murugan (Bharathiar university)

Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : An accurate description of reactive mass transport in porous media is of paramount importance in a multitude of environmental applications. In this talk, we will present mathematical models of gas transport in porous media for applications in contaminant removal and hydrogen storage. The models will be simplified via dimensional analysis and solved analytically in some limiting cases. Numerical solutions of the full models will also be presented. All solutions will be compared with experimental data.
Classification : 76S05, 80A19, 35B40, 76M50
Format : Talk at Waseda University
Author(s) :
- Francesc Font (Universitat Politècnica de Catalunya, CIF: Q0818003F, C. Jordi Girona, 31, 08034 Barcelona, Barcelona)
- Tim G. Myers (Centre de Recerca Matemàtica)
- Maria Aguareles (Universitat de Girona)
- Esther Barrabés (Universitat de Girona)

Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : We consider a vegetation root-soil model which couples Richards PDE in the soil domain and saturated flow in the roots domain. Scenarios when the flow depends on soil temperature is included. A mixed finite element method is applied to obtain numerical solutions, and the well-posedness for its weak formulation and error estimates are studied. We provide numerical examples using tomography data of root domains and study convergence errors to validate our theoretical results.
Classification : 76Sxx, 65Mxx
Format : Talk at Waseda University
Author(s) :
- Malgorzata Peszynska (Oregon State University)
- Nachuan Zhang (Oregon State University)

Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : Solutions to transport models of fluid in contracting/expanding porous vessels remain unknown, and the problem has been restricted to the “slow” expansion/contraction of the walls. I partially address these gaps by generating explicit solutions and improving approximations without the “slowness” dilation rate. Indeed, the homogeneous differential equation is completely solved and this exact solution may be leveraged to form more precise approximations to the flow via perturbation techniques when the Reynolds number is small.
Classification : 76S05, 34B15
Format : Online Talk on Zoom
Author(s) :
- Christopher C. Tisdell (University of New South Wales (UNSW))

Session Time & Room : 2D (Aug.22, 15:30-17:10) @D404
Type : Contributed Talk
Abstract : The outstanding computational ability of artificial neural networks (ANN) makes the deep learning (DL) branch more robust for solving various simple and complex convective models $\left(2D ~and~3D\right)$ in porous media. Moreover, it is an unsupervised learning approach in the DL that uses randomly sampled spatial and boundary collocation points as training data for ANN. A loss function according to the governing and boundary conditions is formulated and enforced to minimize at the sampled collocation points through the backpropagation algorithm using suitable optimization techniques. Eventually, a fine-tuned ANN is achieved after a sufficiently large number of training processes, and the tunned ANN is used to replicate the solution quickly.
Classification : 76S05, 68T07
Author(s) :
- Sumant Kumar (Defence Institute of Advanced Technology, Pune)
- Rathish Kumar Venkatesulu Bayya (Indian Institute of Technology Kanpur)
- Somanchi V.S.S.N.V.G. Krishna Murthy (Defence Institute of Advanced Technology, Pune)