Karsten Urban

Computational Mechanics · 2008–2019

A researcher in the Science corpus: 5 papers; trusts 3 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Karsten Urban trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Gianluigi Rozza
  2. Dinh Bao Phuong Huynh
  3. Anthony T. Patera
  4. Bernard Haasdonk
  5. David J. Knezevic
  6. Ngoc Cuong Nguyen

Who trusts Karsten Urban overall

  1. Benjamin Peherstorfer
  2. Bernhard Wieland
  3. Bernard Haasdonk
  4. Karen E. Willcox
  5. Martin Gubisch
  6. Rob P. Stevenson
  7. Paolo Pacciarini
  8. Max D. Gunzburger
  9. Tiantian Guo

Papers from Karsten Urban's perspective

Ordered by how strongly the researchers Karsten Urban trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics (SIAM Journal on Numerical Analysis)
  2. Reduced basis approximation and a posteriori error estimation for the time-dependent viscous Burgers’ equation
  3. A Successive Constraint Linear Optimization Method for Lower Bounds of Parametric Coercivity and Inf-Sup Stability Constants
  4. REDUCED BASIS APPROXIMATION AND A POSTERIORI ERROR ESTIMATION FOR THE PARAMETRIZED UNSTEADY BOUSSINESQ EQUATIONS
  5. Reduced Basis Approximation and a Posteriori Error Estimation for Affinely Parametrized Elliptic Coercive Partial Differential Equations
  6. Methods of Modern Mathematical Physics. I: Functional Analysis
  7. An ‘empirical interpolation’ method: application to efficient reduced-basis discretization of partial differential equations
  8. Certified real‐time solution of the parametrized steady incompressible Navier–Stokes equations: rigorous reduced‐basis a posteriori error bounds
  9. EFFICIENT REDUCED-BASIS TREATMENT OF NONAFFINE AND NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS
  10. A posteriori error bounds for reduced-basis approximations of parametrized parabolic partial differential equations

Their papers