skip to main content
10.1145/3361821.3361826acmotherconferencesArticle/Chapter ViewAbstractPublication PagescciotConference Proceedingsconference-collections
research-article

Development and HPC Preliminary Testing of a TRM Reactive-transport Model for Solving Potential Environmental Issues

Authors Info & Claims
Published:20 September 2019Publication History

ABSTRACT

The main objective of the study is to develop a reactive-transport model able to utilize HPC resources. The primary purpose is constructing a mathematical representation of a proposed reactivetransport system in order to simulate the potential risk of environmental contamination. Additionally, the contribution of the study is not only associated with HPC usage but also with new model features implemented during the developing phase. Overall, the Transport-Reaction Model (TRM) was developed to include complex functionality that is necessary in order to solve specific transport-reaction issues. TRM is based on coupling the PhreeqcRM geochemical library with 2D solute species transport in water on a regular rectangular network of elements. Compared to the other similar models, our model offers a unique feature that is associated with the 2D mesh. This feature represents an innovative component that improved our modelling results. Testing revealed that TRM provides conditions for simulation acceleration up to 16 threads. The further addition of resources to 20 or 24 also speeds up the calculation but decreases the efficiency of the parallel solution. Generally, the TRM is optimally run on 16 threads.

References

  1. Zhang, A., Li, T., Si, Y., Liu, R., Shi, H., Li, J., Li, J. and Wu, X. 2016. Double-layer parallelization for hydrological model calibration on HPC systems. J Hydrol. 535, 737--747. DOI= https://doi.org/10.1016/j.jhydrol.2016.01.024.Google ScholarGoogle ScholarCross RefCross Ref
  2. Cruz, de la R., Folch, A., Farré, P., Cabezas, J., Navarro, N. and Cela, J.M. 2016. Optimization of atmospheric transport models on HPC platforms. Comput Geosci 97, 30--39. DOI= https://doi.org/10.1016/j.cageo.2016.08.019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Sharma, T., Glynn, J., Panos, E., Deane, P., Gargiulo, M., Rogan, F. and Gallachóir, B. Ó. 2019. High performance computing for energy systém optimization models: Enhancing the energy policy tool kit. Energ Policy. 128, 66--74. DOI= https://doi.org/10.1016/j.enpol.2018.12.055.Google ScholarGoogle ScholarCross RefCross Ref
  4. Pijanowski, B.C., Tayyebi, A., Doucette, J., Pekin, B.K., Braun, D. and Plourde, J. 2014. A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment. Environ Modell Softw Sci. 51, 250--268. DOI= https://doi.org/10.1016/j.envsoft.2013.09.015.Google ScholarGoogle ScholarCross RefCross Ref
  5. Reuther, A., Byun, Ch., Arcand, W., Bestor, D., Bergeron, B., Hubbell, M., Jones, M., Michaleas, P., Prout, A., Rosa, A. and Kepner, J. 2018. Scalable system scheduling for HPC and big data. J Parallel Distr Com. 111, 76--92. DOI= https://doi.org/10.1016/j.jpdc.2017.06.009.Google ScholarGoogle ScholarCross RefCross Ref
  6. Usgs.gov. (2017). PHREEQC Version 3. [online] Available at: https://www.usgs.gov/software/phreeqc-version-3/ [Accessed 28 Jun. 2019].Google ScholarGoogle Scholar
  7. Arma. Armadillo C++ library for linear algebra & scientific computing. [online] Available at: http://arma.sourceforge.net/ [Accessed 28 Jun. 2019].Google ScholarGoogle Scholar
  8. Vojáček, L., Podhoranyi, M. Hpc based smart remote execution solution for modelling environmental issues.(2018) Proceedings - 2018 1st International Cognitive Cities Conference, IC3 2018, art. no. 8567214, pp. 242--245.Google ScholarGoogle Scholar

Index Terms

  1. Development and HPC Preliminary Testing of a TRM Reactive-transport Model for Solving Potential Environmental Issues

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      CCIOT '19: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things
      September 2019
      134 pages
      ISBN:9781450372411
      DOI:10.1145/3361821

      Copyright © 2019 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 September 2019

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited
    • Article Metrics

      • Downloads (Last 12 months)3
      • Downloads (Last 6 weeks)2

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader