relation: https://khub.utp.edu.my/scholars/17487/
title: Heat Transfer Modelling with Physics-Informed Neural Network (PINN)
creator: Dhamirah Mohamad, N.Z.
creator: Yousif, A.
creator: Shaari, N.A.B.
creator: Mustafa, H.I.
creator: Abdul Karim, S.A.
creator: Shafie, A.
creator: Izzatullah, M.
description: The numerical simulations of partial differential equations aid us in studying the nanofluid flow in the porous media, the analysis of the dispersion of pollutants, and many other physical phenomena. However, to simulate such phenomena requires tremendous computational power, and it increases with the number of parameters. In this chapter, we will explore the application of the Physics-Informed Neural Network (PINN) in solving heat equation with distinct types of materials. To leverage the GPU performance and cloud computing, we perform the simulations on the Google Cloud Platform. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022
type: Article
type: PeerReviewed
identifier:   Dhamirah Mohamad, N.Z. and Yousif, A. and Shaari, N.A.B. and Mustafa, H.I. and Abdul Karim, S.A. and Shafie, A. and Izzatullah, M.  (2022) Heat Transfer Modelling with Physics-Informed Neural Network (PINN).  Studies in Systems, Decision and Control, 444.  pp. 25-35.  ISSN 21984182     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140231783&doi=10.1007%2f978-3-031-04028-3_3&partnerID=40&md5=6dda30d6c6fb1d7efa59ee36502b4c34
relation: 10.1007/978-3-031-04028-3₃
identifier: 10.1007/978-3-031-04028-3₃