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Parallel Implementation of a Simplified Semi-physical Wildland Fire Spread Model Using OpenMP

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Book cover Hybrid Artificial Intelligent Systems (HAIS 2017)

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Abstract

We present a parallel 2D version of a simplified semi-physical wildland fire spread model based on conservation equations, with convection and radiation as the main heat transfer mechanisms. This version includes some 3D effects. The OpenMP framework allows distributing the prediction operations among the available threads in a multicore architecture, thereby reducing the computational time and obtaining the prediction results much more quickly. The results from the experiments using data from a real fire in Galicia (Spain) confirm the benefits of using the parallel version.

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References

  1. Amdahl, G.M.: Validity of the single processor approach to achieving large scale computing capabilities. In: Proceedings of the April 18–20, 1967, Spring Joint Computer Conference, AFIPS 1967 (Spring), pp. 483–485, New York, NY, USA. ACM (1967)

    Google Scholar 

  2. Anderson, H.E.: Aids to determining fuel models for estimating fire behavior. General Technical Report INT-122, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station (1982)

    Google Scholar 

  3. Andrews, P.L.: BEHAVE: fire behavior prediction and fuel modeling system-BURN subsystem, Part 1. U.S. Department of Agriculture, Forest Service, Intermountain Research Station Ogden, UT (1986)

    Google Scholar 

  4. Arca, B., Ghisu, T., Spataro, W., Trunfio, G.A.: GPU-accelerated optimization of fuel treatments for mitigating wildfire hazard. Procedia Comput. Sci. 18, 966–975 (2013)

    Article  Google Scholar 

  5. Asensio, M.I., Ferragut, L., Simon, J.: A convection model for fire spread simulation. Appl. Math. Lett. 18(6), 673–677 (2005). Special issue on the occasion of MEGA 2003

    Article  MATH  MathSciNet  Google Scholar 

  6. Cascón, J.M., Engdahl, Y.A., Ferragut, L., Hernández, E.: A reduced basis for a local high definition wind model. Comput. Methods Appl. Mech. Eng. 311, 438–456 (2016)

    Article  MathSciNet  Google Scholar 

  7. Cencerrado, A., Artés, T., Cortés, A., Margalef, T.: Relieving uncertainty in forest fire spread prediction by exploiting multicore architectures. Procedia Comput. Sci. 51, 1752–1761 (2015)

    Article  Google Scholar 

  8. Esvensen, G.: Data Assimilation, The Ensemble Kalman Filter. Springer, Heidelberg (2009)

    Google Scholar 

  9. Ferragut, L., Asensio, M.I., Cascón, J.M., Prieto, D.: A simplified wildland fire model applied to a real case. In: Casas, F., Martinez, V. (eds.) Advances in Differential Equations and Applications, pp. 155–167. Springer International Publishing, Cham (2014)

    Google Scholar 

  10. Ferragut, L., Asensio, M.I., Cascón, J.M., Prieto, D.: A wildland fire physical model well suited to data assimilation. Pure Appl. Geophys. 172(1), 121–139 (2015)

    Article  MATH  Google Scholar 

  11. Ferragut, L., Asensio, M.I., Monedero, S.: Modelling radiation and moisture content in fire spread. Commun. Numer. Methods Eng. 23(9), 819–833 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  12. Ferragut, L., Asensio, M.I., Simon, J.: High definition local adjustment model of 3D wind fields performing only 2D computations. Int. J. Numer. Methods Biomed. Eng. 27(4), 510–523 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  13. Graham, S.L., Kessler, P.B., Mckusick, M.K.: Gprof: a call graph execution profiler. In: SIGPLAN Notices, vol. 17, no. 6, pp. 120–126 (1982)

    Google Scholar 

  14. Innocenti, E., Silvani, X., Muzy, A., Hill, D.R.C.: A software framework for fine grain parallelization of cellular models with OpenMP: application to fire spread. Environ. Model. Softw. 24(7), 819–831 (2009)

    Article  Google Scholar 

  15. Itzkowitz, M., Mazurov, O., Copty, N., Lin, Y.: An OpenMP runtime API for profiling. Sun Microsystems, Inc., OpenMP ARB White Paper. http://www.compunity.org/futures/omp-api.html

  16. Mandel, J., Bennethum, L.S., Beezley, J.D., Coen, J.L., Douglas, C.C., Kim, M., Vodacek, A.: A wildfire model with data assimilation. Math. Comput. Simul. 79, 584–606 (2008)

    Article  MATH  Google Scholar 

  17. MPI Forum. Message Passing Interface (MPI) Forum Home Page, December 2009. http://www.mpi-forum.org/

  18. Pastor, E., Zárate, L., Planas, E., Arnaldos, J.: Mathematical models and calculation systems for the study of wildland fire behaviour. Prog. Energy Combust. Sci. 29(2), 139–153 (2003)

    Article  Google Scholar 

  19. Perry, G.L.W.: Current approaches to modelling the spread of wildland fire: a review. Prog. Phys. Geogr. 22(2), 222–245 (1998)

    Article  Google Scholar 

  20. Prieto, D., Asensio, M.I., Ferragut, L., Cascón, J.M.: Sensitivity analysis and parameter adjustment in a simplified physical wildland fire model. Adv. Eng. Softw. 90, 98–106 (2015)

    Article  MATH  Google Scholar 

  21. Scott, J.H., Burgan, R.E.: Models, standard fire behavior Fuel : a comprehensive set for use with Rothermel’s surface fire spread model. General Technical Report RMRS-GTR-153, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station (2005)

    Google Scholar 

  22. Sullivan, A.L.: Wildland surface fire spread modelling, 1990–2007. 1: physical and quasi-physical models. Int. J. Wildland Fire 18(4), 349–368 (2009)

    Article  Google Scholar 

  23. Sullivan, A.L.: Wildland surface fire spread modelling, 1990–2007. 2: empirical and quasi-empirical models. Int. J. Wildland Fire 18(4), 369–386 (2009)

    Article  Google Scholar 

  24. Sullivan, A.L.: Wildland surface fire spread modelling, 1990–2007. 3: simulation and mathematical analogue models. Int. J. Wildland Fire 18(4), 387–403 (2009)

    Article  Google Scholar 

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Acknowledgement

This work has been partially supported by the Department of Education of the regional government, the Junta of Castilla y León, Grant contract: SA020U16. The authors are also grateful to Arsenio Morillo Rodríguez chief of the forest prevention and valorization area of the regional government, the Xunta de Galicia, for his technical support providing all the necessary information about the Osoño fire.

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Authors and Affiliations

  1. Departamento de Matemática Aplicada, Universidad de Salamanca, Casas del Parque 2, 37008, Salamanca, Spain

    D. Álvarez, D. Prieto, M. I. Asensio & L. Ferragut

  2. I. U. de Física Fundamental y Matemáticas, Universidad de Salamanca, Casas del Parque 1, 37008, Salamanca, Spain

    M. I. Asensio, J. M. Cascón & L. Ferragut

  3. Departamento de Economía e Historia Económica, Universidad de Salamanca, Edificio FES, Campus Miguel de Unamuno, 37007, Salamanca, Spain

    J. M. Cascón

Authors
  1. D. Álvarez
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  2. D. Prieto
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  3. M. I. Asensio
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  4. J. M. Cascón
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  5. L. Ferragut
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Corresponding author

Correspondence to D. Álvarez .

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Editors and Affiliations

  1. University of La Rioja , Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  2. University of La Rioja , Logroño, La Rioja, Spain

    Rubén Urraca

  3. University of A Coruña , Ferrol, La Coruña, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Álvarez, D., Prieto, D., Asensio, M.I., Cascón, J.M., Ferragut, L. (2017). Parallel Implementation of a Simplified Semi-physical Wildland Fire Spread Model Using OpenMP. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_22

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  • DOI: https://doi.org/10.1007/978-3-319-59650-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59649-5

  • Online ISBN: 978-3-319-59650-1

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