Publication detail

Challenges in numerical modelling of continuous steel casting - very fast GPU dynamic solidification model and its use in continuous casting control

KLIMEŠ, L. ŠTĚTINA, J.

Original Title

Challenges in numerical modelling of continuous steel casting - very fast GPU dynamic solidification model and its use in continuous casting control

English Title

Challenges in numerical modelling of continuous steel casting - very fast GPU dynamic solidification model and its use in continuous casting control

Type

conference paper

Language

en

Original Abstract

The paper describes the development of the parallel GPU dynamic solidification model with the use of CUDA computing architecture and NVIDIA Tesla GPU. Its computing performance is then compared with commonly used non-parallel models. Consequently, the GPU model is used for model-based predictive control with an emphasis on violent changes in the casting speed. This approach utilizes the GPU model for real-time prediction of the temperature field for various control strategies. The proper control strategy is then chosen according to the evaluation of the thermal behaviour of cast blank and other criteria. The results show that parallel computing and GPUs are great tools to enhance the computing performance of dynamic solidification models. Due to the significant speed up in order of tens, new opportunities for real-time control of casting have become available.

English abstract

The paper describes the development of the parallel GPU dynamic solidification model with the use of CUDA computing architecture and NVIDIA Tesla GPU. Its computing performance is then compared with commonly used non-parallel models. Consequently, the GPU model is used for model-based predictive control with an emphasis on violent changes in the casting speed. This approach utilizes the GPU model for real-time prediction of the temperature field for various control strategies. The proper control strategy is then chosen according to the evaluation of the thermal behaviour of cast blank and other criteria. The results show that parallel computing and GPUs are great tools to enhance the computing performance of dynamic solidification models. Due to the significant speed up in order of tens, new opportunities for real-time control of casting have become available.

Keywords

continuous casting of steel, dynamic solidification model, GPU computing, parallel computing, model-based predictive control

RIV year

2014

Released

23.06.2014

Publisher

Austrian Society for Metallurgy and Materials (ASMET)

Location

Leoben, Austria

ISBN

978-3-200-03664-2

Book

Proceedings of the 8th European Continuous Casting Conference ECCC 2014

Pages from

266

Pages to

275

Pages count

10

Documents

BibTex


@inproceedings{BUT108135,
  author="Lubomír {Klimeš} and Josef {Štětina}",
  title="Challenges in numerical modelling of continuous steel casting - very fast GPU dynamic solidification model and its use in continuous casting control",
  annote="The paper describes the development of the parallel GPU dynamic solidification model with the use of CUDA computing architecture and NVIDIA Tesla GPU. Its computing performance is then compared with commonly used non-parallel models. Consequently, the GPU model is used for model-based predictive control with an emphasis on violent changes in the casting speed. This approach utilizes the GPU model for real-time prediction of the temperature field for various control strategies. The proper control strategy is then chosen according to the evaluation of the thermal behaviour of cast blank and other criteria. The results show that parallel computing and GPUs are great tools to enhance the computing performance of dynamic solidification models. Due to the significant speed up in order of tens, new opportunities for real-time control of casting have become available.",
  address="Austrian Society for Metallurgy and Materials (ASMET)",
  booktitle="Proceedings of the 8th European Continuous Casting Conference ECCC 2014",
  chapter="108135",
  howpublished="electronic, physical medium",
  institution="Austrian Society for Metallurgy and Materials (ASMET)",
  year="2014",
  month="june",
  pages="266--275",
  publisher="Austrian Society for Metallurgy and Materials (ASMET)",
  type="conference paper"
}