David Zorío

According to our database, David Zorío authored at least 11 papers between 2016 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Lax-Wendroff Approximate Taylor Methods with Fast and Optimized Weighted Essentially Non-oscillatory Reconstructions.

Hugo Carrillo, Carlos Parés, David Zorío

J. Sci. Comput., 2021

An order-adaptive compact approximation Taylor method for systems of conservation laws.

Hugo Carrillo, Emanuele Macca, Carlos Parés Madroñal, Giovanni Russo, David Zorío

J. Comput. Phys., 2021

2020

An Efficient Third-Order WENO Scheme with Unconditionally Optimal Accuracy.

Antonio Baeza, Raimund Bürger, Pep Mulet, David Zorío

SIAM J. Sci. Comput., 2020

On approximate implicit Taylor methods for ordinary differential equations.

Antonio Baeza, Raimund Bürger, María Carmen Martí, Pep Mulet, David Zorío

Comput. Appl. Math., 2020

2019

WENO Reconstructions of Unconditionally Optimal High Order.

Antonio Baeza, Raimund Bürger, Pep Mulet, David Zorío

SIAM J. Numer. Anal., 2019

On the Efficient Computation of Smoothness Indicators for a Class of WENO Reconstructions.

Antonio Baeza, Raimund Bürger, Pep Mulet, David Zorío

J. Sci. Comput., 2019

Central WENO Schemes Through a Global Average Weight.

Antonio Baeza, Raimund Bürger, Pep Mulet, David Zorío

J. Sci. Comput., 2019

2017

An Approximate Lax-Wendroff-Type Procedure for High Order Accurate Schemes for Hyperbolic Conservation Laws.

David Zorío, Antonio Baeza, Pep Mulet

J. Sci. Comput., 2017

Approximate Lax-Wendroff discontinuous Galerkin methods for hyperbolic conservation laws.

Raimund Bürger, Kenettinkara Sudarshan Kumar, David Zorío

Comput. Math. Appl., 2017

2016

High Order Weighted Extrapolation for Boundary Conditions for Finite Difference Methods on Complex Domains with Cartesian Meshes.

Antonio Baeza, Pep Mulet, David Zorío

J. Sci. Comput., 2016

High Order Boundary Extrapolation Technique for Finite Difference Methods on Complex Domains with Cartesian Meshes.

Antonio Baeza, Pep Mulet, David Zorío

J. Sci. Comput., 2016