Literature DB >> 12445757

An efficient numerical method for distributed-loop models of the urine concentrating mechanism.

Anita T Layton1, Harold E Layton.   

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.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12445757     DOI: 10.1016/s0025-5564(02)00176-1

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  2 in total

1.  Countercurrent multiplication may not explain the axial osmolality gradient in the outer medulla of the rat kidney.

Authors:  Anita T Layton; Harold E Layton
Journal:  Am J Physiol Renal Physiol       Date:  2011-07-13

2.  Maximum urine concentrating capability in a mathematical model of the inner medulla of the rat kidney.

Authors:  Mariano Marcano; Anita T Layton; Harold E Layton
Journal:  Bull Math Biol       Date:  2010-02       Impact factor: 1.758

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.