Research Article Open Access

THE IMPROVEMENT OF THE COMPUTATIONAL PERFORMANCE OF THE ZONAL MODEL POMA USING PARALLEL TECHNIQUES

Yao Yu1, Ahmed Cherif Megri1, Kenneth M. Flurchick1 and Dukka Bahadur K.C.1
  • 1 North Carolina A and T State University, USA
American Journal of Engineering and Applied Sciences
Volume 7 No. 1, 2014, 185-193

DOI: https://doi.org/10.3844/ajeassp.2014.185.193

Submitted On: 31 January 2014 Published On: 12 April 2014

How to Cite: Yu, Y., Megri, A. C., Flurchick, K. M. & K.C., D. B. (2014). THE IMPROVEMENT OF THE COMPUTATIONAL PERFORMANCE OF THE ZONAL MODEL POMA USING PARALLEL TECHNIQUES. American Journal of Engineering and Applied Sciences, 7(1), 185-193. https://doi.org/10.3844/ajeassp.2014.185.193

Abstract

The zonal modeling approach is a new simplified computational method used to predict temperature distribution, energy in multi-zone building and indoor airflow thermal behaviors of building. Although this approach is known to use less computer resource than CFD models, the computational time is still an issue especially when buildings are characterized by complicated geometry and indoor layout of furnishings. Therefore, using a new computing technique to the current zonal models in order to reduce the computational time is a promising way to further improve the model performance and promote the wide application of zonal models. Parallel computing techniques provide a way to accomplish these purposes. Unlike the serial computations that are commonly used in the current zonal models, these parallel techniques decompose the serial program into several discrete instructions which can be executed simultaneously on different processors/threads. As a result, the computational time of the parallelized program can be significantly reduced, compared to that of the traditional serial program. In this article, a parallel computing technique, Open Multi-Processing (OpenMP), is used into the zonal model, Pressurized zOnal Model with the Air diffuser (POMA), in order to improve the model computational performance, including the reduction of computational time and the investigation of the model scalability.

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Keywords

  • Zonal Model
  • POMA
  • OpenMP
  • Computational Time
  • Computing Parallelization