Detail publikace

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

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"
}