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John A. Trangenstein, Professor Emeritus

John A. Trangenstein

  • Adaptive mesh refinement for flow in porous media
  • Adaptive mesh refinement for reaction-diffusion problems

Contact Info:
Office Location:  24D Physics Building, Durham, NC 27708
Office Phone:  (919) 660-2824
Email Address: send me a message
Web Page:  http://www.math.duke.edu/~johnt

Office Hours:

see http://www.math.duke.edu/~johnt
Education:

Ph.D.Cornell University1975
B.S.The University of Chicago1972
Specialties:

Applied Math
Research Interests: Adaptive mesh refinement, Multigrid preconditioners

  • Adaptive mesh refinement for flow in porous media
  • Adaptive mesh refinement for reaction-diffusion problems
Keywords:

Approximation theory • Computational complexity • Equations of motion • Equations of state • Finite differences • Finite element method • Granular flow • Granular materials • Mass transfer • Mechanics • Oil wells • Plasticity • Solids

Current Ph.D. Students   (Former Students)

  • Matt Bowen  
Postdocs Mentored

  • Chisup Kim (2001/09-2003/05)  
  • Hwanho Kim (1999/09-1999/12)  
  • Zhuoxin Bi (1999/08-2002/07)  
  • Ilya Mishev (1996/09-1997/05)  
Recent Publications   (More Publications)

  1. J. Trangenstein, Numerical Solution of Hyperbolic Partial Differential Equations (May, 2008), Cambridge University Press, ISBN 052187727X (http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877275.)  [abs]
  2. with John A. Trangenstein and Chisup Kim, Operator Splitting and Adaptive Mesh Refinement for the Luo-Rudy I Model, Journal of Computational Physics, vol. 196 (2004), pp. 645-679, Elsevier  [abs]
  3. Trangenstein, JA, Multi-scale iterative techniques and adaptive mesh refinement for flow in porous media, Advances in Water Resources, vol. 25 no. 8-12 (August, 2002), pp. 1175-1213, Elsevier BV, ISSN 0309-1708 [Gateway.cgi], [doi]  [abs]
  4. Trangenstein, John A. and Bi, Zhuoxin, Multi-Scale Iterative Techniques and Adaptive Mesh Refinement for Miscible Displacement Simulation, Proceedings - SPE Symposium on Improved Oil Recovery (2002), pp. 924 - 936, Tulsa, OK, United States  [abs]
  5. Bi, Z; Higdon, D; Lee, H; Trangenstein, J, Upscaling Tensorial Permeability Fields Based on {G}Gaussian Markov Random Field Models and the Hybrid Mixed Finite Element Method, SPE Journal (2002) [ps]

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320