A projected Newton algorithm based on chemically allowed interval for chemical equilibrium computations
Hongbin Lu, Shaohui Tao, Xiaoyan Sun, Li Xia, Shuguang Xiang
A projected Newton algorithm based on chemically allowed interval for chemical equilibrium computations
The chemical equilibrium equations utilized in reactive transport modeling are complex and nonlinear, and are typically solved using the Newton-Raphson method. Although this algorithm is known for its quadratic convergence near the solution, it is less effective far from the solution, especially for ill-conditioned problems. In such cases, the algorithm may fail to converge or require excessive iterations. To address these limitations, a projected Newton method is introduced to incorporate the concept of projection. This method constrains the Newton step by utilizing a chemically allowed interval that generates feasible descending iterations. Moreover, we utilize the positive continuous fraction method as a preconditioning technique, providing reliable initial values for solving the algorithms. The numerical results are compared with those derived using the regular Newton-Raphson method, the Newton-Raphson method based on chemically allowed interval updating rules, and the bounded variable least squares method in six different test cases. The numerical results highlight the robustness and efficacy of the proposed algorithm.
chemical equilibrium / reactive transport modeling / numerical methods / projected Newton method
[1] |
Carrera J, Saaltink M W, Soler-Sagarra J, Wang J, Valhondo C. Reactive transport: a review of basic concepts with emphasis on biochemical processes. Energies, 2022, 15(3): 925
CrossRef
Google scholar
|
[2] |
Leal A M M, Kulik D A, Smith W R, Saar M O. An overview of computational methods for chemical equilibrium and kinetic calculations for geochemical and reactive transport modeling. Pure and Applied Chemistry, 2017, 89(5): 597–643
CrossRef
Google scholar
|
[3] |
Liang S Y, Lin W S, Chen C P, Liu C W, Fan C. A review of geochemical modeling for the performance assessment of radioactive waste disposal in a subsurface system. Applied Sciences, 2021, 11(13): 5879
CrossRef
Google scholar
|
[4] |
Yeh G T, Tripathi V S. A critical evaluation of recent developments in hydrogeochemical transport models of reactive multichemical components. Water Resources Research, 1989, 25(1): 93–108
CrossRef
Google scholar
|
[5] |
Saaltink M W, Carrera J, Ayora C. A comparison of two approaches for reactive transport modelling. Journal of Geochemical Exploration, 2000, 69–70: 97–101
CrossRef
Google scholar
|
[6] |
Steefel C, Appelo C A J, Arora B, Jacques D, Kalbacher T, Kolditz O, Lagneau V, Lichtner P C, Mayer K U, Meeussen J C L.
CrossRef
Google scholar
|
[7] |
Lu R, Nagel T, Poonoosamy J, Naumov D, Fischer T, Montoya V, Kolditz O, Shao H. A new operator-splitting finite element scheme for reactive transport modeling in saturated porous media. Computers & Geosciences, 2022, 163: 105106
CrossRef
Google scholar
|
[8] |
Carrayrou J, Hoffmann J, Knabner P, Kräutle S, de Dieuleveult C, Erhel J, Van der Lee J, Lagneau V, Mayer K U, MacQuarrie K T B. Comparison of numerical methods for simulating strongly non-linear and heterogeneous reactive transport problems—the MoMaS benchmark case. Computational Geosciences, 2010, 14(3): 483–502
CrossRef
Google scholar
|
[9] |
Carrayrou J, Mosé R, Behra P. New efficient algorithm for solving thermodynamic chemistry. AIChE Journal, 2002, 48(4): 894–904
CrossRef
Google scholar
|
[10] |
Van ZeggerenFStoreyS H. The Computation of Chemical Equilibria. Cambridge: Cambridge University Press, 1970
|
[11] |
LealA MKulik D ASaarM O. Ultra-fast reactive transport simulations when chemical reactions meet machine learning: chemical equilibrium. ArXiv:1708.04825, 2017
|
[12] |
WigleyT M L. WATSPEC: a computer program for determining the equilibrium speciation of aqueous solutions. British Geomorphological Research Group, 1977
|
[13] |
Zhadan V. Two-phase simplex method for linear semidefinite optimization. Optimization Letters, 2019, 13(8): 1969–1984
CrossRef
Google scholar
|
[14] |
Van Der LeeJ. Thermodynamic and mathematical concepts of CHESS. Technical report LHM/RD/98/39, 1998
|
[15] |
Brassard P, Bodurtha P. A feasible set for chemical speciation problems. Computers & Geosciences, 2000, 26(3): 277–291
CrossRef
Google scholar
|
[16] |
Reed M H. Calculation of multicomponent chemical equilibria and reaction processes in systems involving minerals, gases and an aqueous phase. Geochimica et Cosmochimica Acta, 1982, 46(4): 513–528
CrossRef
Google scholar
|
[17] |
Yuan Y X. Recent advances in numerical methods for nonlinear equations and nonlinear least squares. Numerical Algebra, 2011, 1(1): 15
|
[18] |
Weltin E. Are the equilibrium concentrations for a chemical reaction always uniquely determined by the initial concentrations?. Journal of Chemical Education, 1990, 67(7): 548
CrossRef
Google scholar
|
[19] |
Morel F, Morgan J. A numerical method for computing equilibria in aqueous chemical systems. Environmental Science & Technology, 1972, 6(1): 58–67
CrossRef
Google scholar
|
[20] |
BoydS PVandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2004
|
[21] |
Stark P B, Parker R L. Bounded-variable least-squares: an algorithm and applications. Computational Statistics, 1995, 10: 129
|
[22] |
SarafN. Bounded-variable least-squares methods for linear and nonlinear model predictive control. Dissertation for the Doctoral Degree. Lucca: IMT School for Advanced Studies Lucca, 2019
|
[23] |
Sagara N, Fukushima M. A hybrid method for the nonlinear least squares problem with simple bounds. Journal of Computational and Applied Mathematics, 1991, 36(2): 149–157
CrossRef
Google scholar
|
[24] |
Wei W, Dai H, Liang W. A novel projected gradient-like method for optimization problems with simple constraints. Computational & Applied Mathematics, 2020, 39(3): 1–18
CrossRef
Google scholar
|
[25] |
Bellavia S, Macconi M, Pieraccini S. Constrained Dogleg methods for nonlinear systems with simple bounds. Computational Optimization and Applications, 2012, 53(3): 771–794
CrossRef
Google scholar
|
[26] |
Valocchi A J, Street R L, Roberts P V. Transport of ion-exchanging solutes in groundwater: chromatographic theory and field simulation. Water Resources Research, 1981, 17(5): 1517–1527
CrossRef
Google scholar
|
[27] |
Carrayrou J, Bertagnolli C, Fahs M. Algorithms for activity correction models for geochemical speciation and reactive transport modeling. AIChE Journal, 2022, 68(1): e17391
CrossRef
Google scholar
|
[28] |
ÖhmanL O. Equilibrium studies of ternary aluminium(III) hydroxo complexes with ligands related to conditions in natural waters. Dissertation for the Doctoral Degree. Umeå: University of Umeå, 1983
|
[29] |
Christian J B. Simulating aqueous processes. Chemical Engineering Progress, 2003, 99: 32–39
|
[30] |
Chilakapati A, Yabusaki S, Szecsody J, MacEvoy W. Groundwater flow, multicomponent transport and biogeochemistry: development and application of a coupled process model. Journal of Contaminant Hydrology, 2000, 43(3–4): 303–325
CrossRef
Google scholar
|
[31] |
Machat H, Carrayrou J. Comparison of linear solvers for equilibrium geochemistry computations. Computational Geosciences, 2017, 21(1): 131–150
CrossRef
Google scholar
|
[32] |
Marinoni M, Carrayrou J, Lucas Y, Ackerer P. Thermodynamic equilibrium solutions through a modified Newton Raphson method. AIChE Journal, 2017, 63(4): 1246–1262
CrossRef
Google scholar
|
/
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