title: An efficient numerical method for distributed-loop models of the urine concentrating mechanism.
abstract: In this study we describe an efficient numerical method, based on the semi-Lagrangian (SL) semi-implicit (SI) method and Newton's method, for obtaining steady-state (SS) solutions of equations arising in distributed-loop models of the urine concentrating mechanism. Dynamic formulations of these models contain large systems of coupled hyperbolic partial differential equations (PDEs). The SL method advances the solutions of these PDEs in time by integrating backward along flow trajectories, thus allowing large time steps while maintaining stability. The SI approach controls stiffness arising from transtubular transport terms by averaging these terms in time along flow trajectories. An approximate SS solution of a dynamic formulation obtained via the SLSI method can be used as an initial guess for a Newton-type solver, which rapidly converges to a highly accurate numerical approximation to the solution of the ordinary differential equations that arise in the corresponding SS model formulation. In general, it is difficult to specify a priori for a Newton-type solver an initial guess that falls within the radius of convergence; however, the initial guess generated by solving the dynamic formulation via the SLSI method can be made sufficiently close to the SS solution to avoid numerical instability. The combination of the SLSI method and the Newton-type solver generates stable and accurate solutions with substantially reduced computation times, when compared to previously applied dynamic methods.
authors.affiliation: Department of Mathematics, University of North Carolina, Phillips Hall, Campus Box 3250, Chapel Hill, NC 27599, USA. layton@amath.unc.edu
authors.forename: Anita T
authors.initials: AT
authors.lastname: Layton
authors.forename: Harold E
authors.initials: HE
authors.lastname: Layton
mesh_terms: D000818:Animals; D002463:Cell Membrane Permeability / Q000502:physiology; D006801:Humans; D007671:Kidney Concentrating Ability / Q000502:physiology*; D007679:Kidney Medulla / Q000378:metabolism; D008138:Loop of Henle / Q000378:metabolism*; D008954:Models, Biological; D017711:Nonlinear Dynamics; D009997:Osmotic Pressure; D012964:Sodium / Q000493:pharmacokinetics; D014867:Water / Q000378:metabolism
chemical_list: D014867:Water; D012964:Sodium