Modeling the distribution of a liquid contaminant using the diffusion equation in two dimensions

Authors

  • Roberth Cachay Torres Facultad de Ciencias Físicas y Matemáticas, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n – Ciudad Universitaria, Trujillo, Perú
  • José Roldan López Facultad de Ciencias Físicas y Matemáticas, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n – Ciudad Universitaria, Trujillo, Perú.
  • Jhenry F. Agreda-Delgado Facultad de Ciencias Físicas y Matemáticas, Universidad Nacional de Trujillo, Av. Juan Pablo II s/n – Ciudad Universitaria, Trujillo, Perú

Keywords:

Diffusion, Finite differences, Boundary conditions

Abstract

In this work, the 2D-diffusion equation is used to model the diffusion process of a pollutant in calm and shallow waters. The diffusion coefficient was considered spatially constant and only dependent on the nature of the substance. The idea and the numerical schemes (forward difference, backward difference and center difference) were applied to a domain in the XY plane of sideways 1, where the distribution of the contaminant can be seen. Neumann boundary conditions equal to zero or zero flow at the boundary have been used, in order to make a cut at said boundary for the modeling. The computational program carried out allows moving the contaminant source to any point of the domain and seeing its distribution in real time, it is also possible to add other contaminant sources and observe their diffusion. As the value of the contaminant concentration decreases over time, a slowdown in the speed of the wave is observed; the modeling allows monitoring the distribution of the contaminant for all time. Therefore, the developed numerical model can be used to predict the distribution of contaminants in liquids.

References

Andallah, L.; Khatun, M. 2020. Numerical solution of advection-diffusion equation using finite difference schemes. Bangladesh Journal of Scientific and Industrial Research, 55(1): 15-22.

Comin, D.; Nanda, R. 2019. Financial development and technology diffusion. IMF Economic Review, 67(2): 395-419.

Granik, N.; Weiss, L.; Nehme, E.; Levin, M.; Chein, M.; Perlson, E.; ... Shechtman, Y. 2019. Single-particle diffusion characterization by deep learning. Biophysical journal, 117(2): 185-192.

Habingabwa, M.; Ndahayo, F.; Berntsson, F. 2012. Air pollution tracking using pdes. Rwanda Journal, 27: 63-69.

Hutomo, G.; Kusuma, J.; Ribal, A.; Mahie, A.; Aris, N. 2019. Numerical solution of 2-d advection-diffusion equation with variable coefficient using du-fort frankel method. In Journal of Physics: Conference Series (Vol. 1180, No. 1, p. 012009). IOP Publishing.

Lax, P. 1973. Hyperbolic systems of conservation laws and the mathematical theory of shock waves. Socie-ty for Industrial and Applied Mathematics. 59 pp.

Mailler, S.; Pennel, R.; Menut, L.; Lachâtre, M. 2020. Using an antidiffusive transport scheme in the vertical direction: a promising novelty for chemistry-transport models. Geoscientific Model Development Discus-sions, 1-21.

Moin, P. 2010. Fundamentals of engineering numerical analysis. Cambridge University Press. 235 pp.

Oliveira, F.; Ferreira, R.; Lapas, L.; Vainstein, M. 2019. Anomalous diffusion: A basic mechanism for the evolution of inhomogeneous systems. Frontiers in Physics, 7: 18.

Polyanin, A.; Sorokin, V.; Vyazmin, A. 2018. Reaction-diffusion models with delay: some properties, equa-tions, problems, and solutions. Theoretical Foundations of Chemical Engineering, 52(3): 334-348.

Rubin, H. and Atkinson J. 2001. Environmental fluid mechanics. CRC Press. 721 pp.

Won, Y.; Ramkrishna, D. 2019. Revised formulation of Fick’s, Fourier’s, and Newton’s laws for spatially varying linear transport coefficients. ACS omega, 4(6): 11215-11222.

Xue, T.; Su, H.; Han, C.; Jiang, C.; Aanjaneya, M. 2020. A novel discretization and numerical solver for non-fourier diffusion. ACM Transactions on Graphics (TOG), 39(6): 1-14.

Zhang, J.; Centola, D. 2019. Social networks and health: New developments in diffusion, online and offline. Annual Review of Sociology, 45(1): 91-109.

Published

2022-12-30

How to Cite

Cachay Torres, R., Roldan López, J., & Agreda-Delgado, J. F. . (2022). Modeling the distribution of a liquid contaminant using the diffusion equation in two dimensions. Revista CIENCIA Y TECNOLOGÍA, 18(4), 31-41. Retrieved from https://revistas.unitru.edu.pe/index.php/PGM/article/view/4980

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Section

Artículos Originales