Posts by Nicolae Suciu

Abstract

This article presents numerical investigations on accuracy and convergence properties of several numerical approaches for simulating steady state flows in heterogeneous aquifers.

Finite difference, finite element, discontinuous Galerkin, spectral, and random walk methods are tested on one- and two-dimensional benchmark flow problems.

Realizations of log-normal hydraulic conductivity fields are generated by Kraichnan algorithms in closed form as finite sums of random periodic modes, which allow direct code verification by comparisons with manufactured reference solutions. The quality of the methods is assessed for increasing number of random modes and for increasing variance of the log-hydraulic conductivity fields with Gaussian and exponential correlation. Experimental orders of convergence are calculated from successive refinements of the grid.

The numerical methods are further validated by comparisons between statistical inferences obtained from Monte Carlo ensembles of numerical solutions and theoretical first-order perturbation results.

It is found that while for Gaussian correlation of the log-conductivity field all the methods perform well, in the exponential case their accuracy deteriorates and, for large variance and number of modes, the benchmark problems are practically not tractable with reasonably large computing resources, for all the methods considered in this study.

Authors

Cristian D. Alecsa
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy

Imre Boros
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy
Department of Mathematics, Babes-Bolyai University, Mihail Kogalniceanu, 1, 400084 Cluj-Napoca, Romania

Florian Frank
Mathematics Department, Friedrich-Alexander University of Erlangen-Nuremberg, Cauerstraße. 11, 91058 Erlangen, Germany

Peter Knabner,
Mathematics Department, Friedrich-Alexander University of Erlangen-Nuremberg, Cauerstraße. 11, 91058 Erlangen, Germany

Mihai Nechita
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy
Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, United Kingdom

Alexander Prechtel
Mathematics Department, Friedrich-Alexander University of Erlangen-Nuremberg, Cauerstraße. 11, 91058 Erlangen, Germany

Andreas Rupp
Mathematics Department, Friedrich-Alexander University of Erlangen-Nuremberg, Cauerstraße. 11, 91058 Erlangen, Germany
Interdisciplinary Center for Scientific Computing, Ruprecht-Karls-University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany

Nicolae Suciu
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy

Keywords

flow; accuracy; convergence; computational tractability; finite difference; finite elements; discontinuous Galerkin; spectral methods; global random walk

Paper coordinates:

This is the extended, complete version of the following paper published in Adv. Water Res.

C. D. Alecsa, I. Boros, F. Frank, P. Knabner, M. Nechita, A. Prechtel, A. Rupp, N. Suciu, Numerical benchmark study for flow in highly heterogeneous aquifers, Adv. Water Res. (2020).
doi: 10.1016/j.advwatres.2020.103558

The coordinates of the extended preprint are:

C. D. Alecsa, I. Boros, F. Frank, P. Knabner, M. Nechita, A. Prechtel, A. Rupp, N. Suciu, Benchmark for numerical solutions of flow in heterogeneous groundwater formations, arxiv 1911.10774.

References

see the expanding block below

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[1] Ababou, R., McLaughlin, D., Gelhar, L.W., Tompson, A.F., 1989. Numerical simulation of threedimensional saturated flow in randomly heterogeneous porous media. Transp. Porous Media 4(6), 549–565. https://doi.org/10.1007/BF00223627

[2] Alnæs, M.S., Blechta, J., Hake, J., Johansson, A., Kehlet B., Logg, A., Richardson, C., Ring J., Rognes, M.E., Wells, G.N., 2015. The FEniCS Project Version 1.5. Archive of Numerical Software 3(100), 9–23. https://doi.org/10.11588/ans.2015.100.20553

[3] Arbogast, T., Wheeler, M.F., Zhang, N.-Y., 1996. A nonlinear mixed finite element method for a degenerate parabolic equation arising in flow in porous media. SIAM J. Numer. Anal., 33(4), 1669–1687. https://doi.org/10.1137/S0036142994266728

[4] Aurentz, J.L., Trefethen, L.N., 2017. Chopping a Chebyshev series. ACM Transactions on Mathematical Software (TOMS), 43(4),33. https://doi.org/10.1145/2998442

[5] Attinger, S., 2003. Generalized coarse graining procedures for flow in porous media. Comput. Geosci. 7(4), 253–273.
http://dx.doi.org/10.1023/B:COMG.0000005243.73381.e3

[6] Bakr, A.A., Gelhar, L.W., Gutjahr, A.L., MacMillan, J.R., 1978. Stochastic analysis of spatial variability in subsurface flows: 1. Comparison of one-and three-dimensional flows. Water Resour. Res. 14(2), 263–271. https://doi.org/10.1029/WR014i002p00263

[7] Bellin, A., Salandin, P., Rinaldo, A., 1992. Simulation of dispersion in heterogeneous porous formations: Statistics, first-order theories, convergence of computations. Water Resour. Res. 28(9), 2211–2227. https://doi.org/10.1029/92WR00578

[8] Bellin, A., Rubin, Y., 1996. HYDRO GEN: A spatially distributed random field generator for correlated properties. Stoch. Hydrol. Hydraul. 10(4), 253–78. https://doi.org/10.1007/BF01581869

[9] Bohling, G. C., Liu, G., Dietrich, P., Butler, J. J., 2016. Reassessing the MADE direct-push hydraulic conductivity data using a revised calibration procedure. Water Resour. Res. 52(11), 8970–8985. https://doi.org/10.1002/2016WR019008

[10] Brunner, F., Radu, F.A., Bause, M., Knabner, P., 2012. Optimal order convergence of a modified BDM1 mixed finite element scheme for reactive transport in porous media. Adv. Water Resour. 35, 163–171. http://dx.doi.org/10.1016/j.advwatres.2011.10.001

[11] Carrayrou, J., Kern, M., Knabner, P., 2010. Reactive transport benchmark of MoMaS. Comput. Geosci. 14(3), 385–392. https://doi.org/10.1007/s10596-009-9157-7

[12] Carrayrou, J., Hoffmann, J., Knabner, P., Krautle, S., De Dieuleveult, C., Erhel, J., Van Der Lee, J., Lagneau, V., Mayer, K.U., Macquarrie, K.T., 2010. Comparison of numerical methods for simulating strongly nonlinear and heterogeneous reactive transport problems–the MoMaS benchmark case. Comput. Geosci. 14(3), 483–502. https://doi.org/10.1007/s10596-010-9178-2

[13] Celik, I., Karatekin O., 1997. Numerical experiments on application of Richardson extrapolation with nonuniform grids. J. Fluids Eng. 119(3), 584–590.

[14] Cramer, H., Leadbetter, M.R., 1967. Stationary and Related Stochastic Processes. John Wiley & Sons, New York.

[15] Dagan, G., 1989. Flow and Transport in Porous Formations. Springer, Berlin.

[16] de Dreuzy, J.-R., Beaudoin, A., Erhel, J., 2007. Asymptotic dispersion in 2D heterogeneous porous media determined by parallel numerical simulations. Water Resour. Res. 43, W10439. https://doi.org/10.1029/2006WR005394

[17] de Dreuzy, J.-R., Pichot, G., Poirriez, B., Erhel, J., 2013. Synthetic benchmark for modeling flow in 3D fractured media. Comput. Geosci. 50, 59–71. http://dx.doi.org/10.1016/j.cageo.2012.07.025

[18] Deng, F.W., Cushman, J.H., 1995. On Higher-Order Corrections to the Flow Velocity Covariance Tensor. Water Resour. Res. 31(7), 1659-1672. https://doi.org/10.1029/94WR02974

[19] Di Federico, V., Neuman, S.P., 1997. Scaling of random fields by means of truncated power variograms and associated spectra. Water Resour. Res. 33, 1075–1085 ()
https://doi.org/10.1029/97WR00299

[20] Di Pietro, D.A., Ern, A., 2012, Mathematical Aspects of Discontinuous Galerkin Methods. Springer, Heidelberg.

[21] Eberhard, J.P., Suciu, N., Vamos, C., 2007. On the self-averaging of dispersion for transport in quasiperiodic random media. J. Phys. A 40(4), 597–610.
http://dx.doi.org/10.1088/1751-8113/40/4/002

[22] Flemisch, B., Berre, I., Boon, W., Fumagalli, A., Schwenck, N., Scotti, A., Stefansson, I., Tatomir, A., 2018. Benchmarks for single-phase flow in fractured porous media. Adv. Water Resour. 111, 239–58. https://doi.org/10.1016/j.advwatres.2017.10.036

[23] Frank F., Reuter B., Aizinger V., Knabner, P., 2015. FESTUNG: A MATLAB/GNU Octave toolbox for the discontinuous Galerkin method, Part I: Diffusion operator. Comput. Math. Appl. 70(1), 11– 46. https://doi.org/10.1016/j.camwa.2015.04.013

[24] Gelhar, L.W., 1986. Stochastic subsurface hydrology from theory to applications. Water Resour. Res., 22(9S) S135S–145S. https://doi.org/10.1029/WR022i09Sp0135S

[25] Gelhar, L.W., Axness, C., 1983. Three-dimensional stochastic analysis of macrodispersion in aquifers. Water Resour. Res. 19(1), 161–180. https://doi.org/10.1029/WR019i001p00161

[26] Gotovac, H., Andricevicc, R., Gotovac, B., 2007. Multi resolution adaptive modeling of groundwater flow and transport. Adv. Water Resour. 30(5), 1105–1126. https://doi.org/10.1016/j.advwatres.2006.10.007

[27] Gotovac, H., Cvetkovic, V., Andricevicc, R., 2009. Adaptive Fup multi-resolution approach to flow and advective transport in highly heterogeneous porous media: Methodology, accuracy and convergence. Adv. Water Resour. 32(6), 885–905. https://doi.org/10.1016/j.advwatres.2009.02.013

[28] Grenier, C., Anbergen, H., Bense, V., Chanzy, Q., Coon, E., Collier, N., Costard, F., Ferry, M., Frampton, A., Frederick, J., Gon¸calves, J., Holmen, J., Jost, A., Kokh, S., Kurylyk, B., McKenzie, J., Molson, J., Mouche, E., Orgogozo, L., Pannetier, R., Riviere, A., Roux, N., Ruhaak, W., Scheidegger, J., Selroos, J.-O., Therrien, R., Vidstrand, P., Voss, C. 2018. Groundwater flow and heat transport for systems undergoing freeze-thaw: Intercomparison of numerical simulators for 2D test cases. Advances in water resources, 114, 196-218. https://doi.org/10.1016/j.advwatres.2018.02.001

[29] Hoepffner, J., 2007. Implementation of Boundary Conditions. http://www.lmm.jussieu.fr/ hoepffner/boundarycondition.pdf

[30] Hou, T., Wu, X.H., Cai, Z., 1999. Convergence of a multiscale finite element method for elliptic problems with rapidly oscillating coefficients. Math. Comput. 68(227), 913–943. https://doi.org/10.1090/S0025-5718-99-01077-7

[31] Kelley, C. T., 1995. Iterative Methods for Linear and Nonlinear Equations (Vol. 16). Siam, Philadelphia.

[32] Knabner, P., Angermann, L., 2003. Numerical Methods for Elliptic and Parabolic Partial Differential Equations. Springer, New York.

[33] Kornhuber, R., Peterseim, D., Yserentant, H., 2018. An analysis of a class of variational multiscale methods based on subspace decomposition. Math. Comput. 87(314), 2765–2774. https://doi.org/10.1090/mcom/3302

[34] Kraichnan, R.H., 1970. Diffusion by a random velocity field. Phys Fluids 13(1), 22–31. http://dx.doi.org/10.1063/1.1692799

[35] Kramer, P.R., Kurbanmuradov, O., Sabelfeld, K., 2007. Comparative analysis of multiscale Gaussian random field simulation algorithms. J. Comp. Phys. 226, 897–924. https://doi.org/10.1016/j.jcp.2007.05.002

[36] Kurbanmuradov, O.A., Sabelfeld, K.K., 2010. Stochastic flow simulation and particle transport in a 2D Layer of random porous medium. Transp. Porous Media 85, 347 373. http://dx.doi.org/10.1007/s11242-010-9567-y

[37] Larsson, S., Thomee, V., (2009). Partial Differential Equations with Numerical Methods. Springer, Berlin Heidelberg. http://dx.doi.org/10.1007/978-3-540-88706-5

[38] LeVeque, R., 2007. Finite Difference Methods for Ordinary and Partial Differential Equations: Steady-State and Time-Dependent Problems. SIAM, Philadelphia.

[39] Li, H., Zhang, D., 2007. Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods. Water Resour. Res. 43, W09409.
http://dx.doi.org/doi:10.1029/2006WR005673

[40] Li, S., McLaughlin, D. B., 1991. A nonstationary spectral method for solving stochastic groundwater problems: unconditional analysis. Water Resour. Res. 27(7), 1589–1605. https://doi.org/10.1029/91WR00881

[41] Li, W., Lu, Z., Zhang, D., 2009. Stochastic analysis of unsaturated flow with probabilistic collocation method. Water Resour. Res. 45, W08425. https://doi.org/doi:10.1029/2008WR007530

[42] Li, Z., Qiao, Z., Tang, T., 2017. Numerical Solution of Differential Equations: Introduction to Finite Difference and Finite Element Methods. Cambridge University Press. http://dx.doi.org/10.1017/9781316678725

[43] Liu, H.A., Molz, F.J., 1997. Multifractal analyses of hydraulic conductivity distributions. Water Resour. Res. 33(11), 2483–2488. https://doi.org/10.1029/97WR02188

[44] Lord, G.J., Powell, C.E., Shardlow, T., 2014. An Introduction to Computational Stochastic PDEs. Cambridge University Press.

[45] Mantoglou, A., Wilson, J.L., 1982. The turning bands method for simulation of random fields using line generation by a spectral method. Water Resour. Res. 18(5), 1379–1394. https://doi.org/10.1029/WR018i005p01379

[46] Mizell, S.A., Gutjahr, A.L., Gelhar, L.W., 1982. Stochastic analysis of spatial variability in twodimensional steady groundwater flow assuming stationary and nonstationary heads.Water Resources Research, 18(4), 1053–1067. https://doi.org/10.1029/WR018i004p01053

[47] Molz, F.J., Boman, G.K., 1995. Further evidence of fractal structure in hydraulic conductivity distributions. Geophys. Res. Lett. 22(18), 2545–2548. https://doi.org/10.1029/95GL02548

[48] Molz, F.J., Liu, H.H., Szulga, J., 1997. Fractional Brownian motion and fractional Gaussian noise in subsurface hydrology: A review, presentation of fundamental properties, and extensions. Water Resour. Res. 33(10), 2273–2286. https://doi.org/10.1029/97WR01982

[49] Nochetto, R.H., Verdi, C., 1988. Approximation of degenerate parabolic problems using numerical integration. SIAM J. Numer. Anal., 25(4), 784–814. https://doi.org/10.1137/0725046

[50] Oberkampf, W.L, Blottner F G., 1998. Issues in computational fluid dynamics code verification and validation. AIAA J. 36 (5), 687–695. https://doi.org/10.2514/2.456

[51] Radu, F., Pop, I.S., Knabner, P., 2004. Order of convergence estimates for an Euler implicit, mixed finite element discretization of Richards’ equation. SIAM J. Numer. Anal., 42(4), 1452–1478. https://doi.org/10.1137/S0036142902405229

[52] Radu, F.A., Suciu, N., Hoffmann, J., Vogel, A., Kolditz, O., Park, C.-H., Attinger, S., 2011. Accuracy of numerical simulations of contaminant transport in heterogeneous aquifers: a comparative study. Adv. Water Resour. 34, 47–61. http://dx.doi.org/10.1016/j.advwatres.2010.09.012

[53] Rajaram, H., Gelhar, L. W., 1991. Three-dimensional spatial moments analysis of the Borden tracer test. Water Resour. Res. 27(6), 1239–1251. https://doi.org/10.1029/91WR00326

[54] Rehfeldt, K.R., Boggs, J.M., Gelhar, L.W., 1992. Field study of dispersion in a heterogeneous aquifer: 3. Geostatistical analysis of hydraulic conductivity. Water Resour. Res. 28(12), 3309–3324. https://doi.org/10.1029/92WR01758

[55] Ritzi Jr, R.W., Soltanian, M.R., 2015. What have we learned from deterministic geostatistics at highly resolved field sites, as relevant to mass transport processes in sedimentary aquifers?. J. Hydrol. 531, 31–39. https://doi.org/10.1016/j.jhydrol.2015.07.049

[56] Riviere, B., 2008. Discontinuous Galerkin Methods for Solving Elliptic and Parabolic Equations: Theory and Implementation. Frontiers in Applied Mathematics, Philadelphia.

[57] Roache, P.J., 2002. Code verification by the method of manufactured solutions. J. Fluids Eng. 124 (1):4–10. http://dx.doi.org/10.1115/1.1436090

[58] Roache, P.J., 1998. Verification and Validation in Computational Science and Engineering. Hermosa Publishers, New Mexico.

[59] Roy, C.J., 2003. Grid convergence error analysis for mixed-order numerical schemes. AIAA Journal 41(4), 595–604. https://doi.org/10.2514/2.2013

[60] Roy, C.J., 2005. Review of code and solution verification procedures for computational simulation. J. Comput. Phys. 205, 131–156. http://dx.doi.org/10.1016/j.jcp.2004.10.036

[61] Rupp, A., 2019. Simulating Structure Formation in Soils Across Scales Using Discontinuous Galerkin Methods. Shaker, Duren.

[62] Salandin, P., Fiorotto, V., 1998. Solute transport in highly heterogeneous aquifers. Water Resour. Res. 34(5), 949–961. https://doi.org/10.1029/98WR00219

[63] Shen, J., Wang, Y., Xia, J., 2016. Fast structured direct spectral methods for differential equations with variable coefficients, I. The one-dimensional case. SIAM J. Sci. Comput. 38(1), A28–A54. https://doi.org/10.1137/140986815

[64] Srzic, V., Cvetkovic, V., Andricevic, R., Gotovac, H., 2013). Impact of aquifer heterogeneity structure and local-scale dispersion on solute concentration uncertainty. Water Resour. Res. 49(6), 3712- 3728. https://doi.org/10.1002/wrcr.20314

[65] Suciu, N., 2010. Spatially inhomogeneous transition probabilities as memory effects for diffusion in statistically homogeneous random velocity fields. Phys. Rev. E 81, 056301. http://dx.doi.org/10.1103/PhysRevE.81.056301

[66] Suciu, N., 2014. Diffusion in random velocity fields with applications to contaminant transport in groundwater. Adv. Water. Resour. 69, 114–133. http://dx.doi.org/10.1016/j.advwatres.2014.04.002

[67] Suciu, N., 2019. Diffusion in Random Fields. Applications to Transport in Groundwater. Birkhauser, Cham. https://doi.org/10.1007/978-3-030-15081-5

[68] Suciu, N., Vamos, C., Vanderborght, J., Hardelauf, H., Vereecken, H., 2006. Numerical investigations on ergodicity of solute transport in heterogeneous aquifers. Water. Resour. Res. 42, W04409. http://dx.doi.org/10.1029/2005WR004546

[69] Suciu, N., Radu, F.A., Prechtel, A., Knabner, P., 2013. A coupled finite element – global random walk approach to advection – dominated transport in porous media with random hydraulic conductivity. J. Comput. Appl. Math. 246, 27–37. http://dx.doi.org/10.1016/j.cam.2012.06.027

[70] Suciu, N., Attinger, S., Radu, F. A., Vamos, C., Vanderborght, J., Vereecken, H., Knabner, P. (2015). Solute transport in aquifers with evolving scale heterogeneity. An. Sti.U. Ovid. Co-Mat. 23(3), 167–186. http://dx.doi.org/doi:10.1515/auom-2015-0054

[71] Suciu, N., Schuler, L., Attinger, S., Knabner, P., 2016. Towards a filtered density function approach for reactive transport in groundwater. Adv. Water Resour. 90, 83–98. http://dx.doi.org/10.1016/j.advwatres.2016.02.016

[72] Trefry, M.G., Ruan, F.P., McLaughlin, D., 2003. Numerical simulations of preasimptotic transport in hetoregenous porous media: departures from the Gaussian limit. Water Resour. Res. 39(3), 1063– 1077. https://doi.org/10.1029/2001WR001101

[73] Vamos, C., Suciu, N., Vereecken, H., 2003. Generalized random walk algorithm for the numerical modeling of complex diffusion processes. J. Comput. Phys., 186, 527 544. https://doi.org/10.1016/S0021-9991(03)00073-1.

[74] Weideman, J.A., Reddy, S.C., 2000. A MATLAB differentiation matrix suite. ACM Trans. Math. Software 26(4), 465–519. https://doi.org/10.1145/365723.365727

[75] Zhang, Y., Person, M., Gable, C.W., 2007. Representative hydraulic conductivity of hydrogeologic units: Insights from an experimental stratigraphy. J. Hydrol. 339, 65 78. https://doi.org/10.1016/j.jhydrol.2007.03.007

[76] Yaglom, A.M., 1987. Correlation Theory of Stationary and Related Random Functions, Volume II: Supplementary Notes and References. Springer, New York.

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