David Mora

1.9k total citations
67 papers, 1.2k citations indexed

About

David Mora is a scholar working on Computational Mechanics, Mechanics of Materials and Computational Theory and Mathematics. According to data from OpenAlex, David Mora has authored 67 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Computational Mechanics, 40 papers in Mechanics of Materials and 22 papers in Computational Theory and Mathematics. Recurrent topics in David Mora's work include Advanced Numerical Methods in Computational Mathematics (55 papers), Numerical methods in engineering (37 papers) and Advanced Mathematical Modeling in Engineering (20 papers). David Mora is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (55 papers), Numerical methods in engineering (37 papers) and Advanced Mathematical Modeling in Engineering (20 papers). David Mora collaborates with scholars based in Chile, Italy and Colombia. David Mora's co-authors include L. Beirão da Veiga, Rodolfo Rodrı́guez, Gonzalo Rivera, Carlo Lovadina, Marco Verani, Paola F. Antonietti, Ricardo Ruíz-Baier, Giuseppe Vacca, Salim Meddahi and Ricardo Oyarzúa and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, Mathematics of Computation and Geophysical Journal International.

In The Last Decade

David Mora

60 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Mora Chile 15 1.1k 740 410 405 122 67 1.2k
Ricardo G. Durán Argentina 20 835 0.8× 559 0.8× 554 1.4× 212 0.5× 172 1.4× 47 1.2k
Zhong‐Ci Shi China 19 952 0.9× 652 0.9× 404 1.0× 296 0.7× 175 1.4× 75 1.1k
Ricardo G. Durán Argentina 18 991 0.9× 656 0.9× 494 1.2× 278 0.7× 142 1.2× 30 1.2k
Shipeng Mao China 17 816 0.8× 384 0.5× 278 0.7× 211 0.5× 189 1.5× 81 1.0k
Thomas Apel Germany 19 889 0.8× 551 0.7× 510 1.2× 205 0.5× 228 1.9× 51 1.1k
Thirupathi Gudi India 17 801 0.8× 533 0.7× 435 1.1× 194 0.5× 192 1.6× 53 911
Salim Meddahi Spain 17 729 0.7× 543 0.7× 305 0.7× 274 0.7× 40 0.3× 66 858
Franco Dassi Italy 17 757 0.7× 428 0.6× 233 0.6× 316 0.8× 61 0.5× 54 857
Sonia Fernández‐Méndez Spain 20 1.1k 1.0× 903 1.2× 117 0.3× 244 0.6× 59 0.5× 42 1.4k
So‐Hsiang Chou United States 21 1.3k 1.3× 347 0.5× 304 0.7× 525 1.3× 263 2.2× 52 1.4k

Countries citing papers authored by David Mora

Since Specialization
Citations

This map shows the geographic impact of David Mora's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Mora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Mora more than expected).

Fields of papers citing papers by David Mora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Mora. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Mora. The network helps show where David Mora may publish in the future.

Co-authorship network of co-authors of David Mora

This figure shows the co-authorship network connecting the top 25 collaborators of David Mora. A scholar is included among the top collaborators of David Mora based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Mora. David Mora is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mora, David, et al.. (2025). A virtual element method for the Biot-Brinkman equations using Nitsche’s technique. Computer Methods in Applied Mechanics and Engineering. 448. 118447–118447.
2.
Mora, David, et al.. (2024). Numerical Solution of the Biot/Elasticity Interface Problem Using Virtual Element Methods. Journal of Scientific Computing. 98(3). 1 indexed citations
3.
Mora, David, et al.. (2024). Virtual element methods for Biot–Kirchhoff poroelasticity. Mathematics of Computation.
4.
Mora, David, et al.. (2024). A finite element model for concentration polarization and osmotic effects in a membrane channel. International Journal for Numerical Methods in Fluids. 96(5). 601–625. 5 indexed citations
5.
Dassi, Franco, et al.. (2024). Mixed variational formulations of virtual elements for the polyharmonic operator (−Δ). Computers & Mathematics with Applications. 158. 150–166. 1 indexed citations
6.
Veiga, L. Beirão da, et al.. (2023). A fully-discrete virtual element method for the nonstationary Boussinesq equations in stream-function form. Computer Methods in Applied Mechanics and Engineering. 408. 115947–115947. 5 indexed citations
7.
Mora, David, et al.. (2023). The Morley-type virtual element method for the Navier–Stokes equations in stream-function form. Computer Methods in Applied Mechanics and Engineering. 419. 116573–116573. 4 indexed citations
8.
Bendahmane, Mostafa, et al.. (2023). Conforming and nonconforming virtual element methods for fourth order nonlocal reaction diffusion equation. Mathematical Models and Methods in Applied Sciences. 33(10). 2035–2083. 2 indexed citations
9.
Mora, David, et al.. (2022). Robust A Posteriori Error Analysis for Rotation-Based Formulations of the Elasticity/Poroelasticity Coupling. SIAM Journal on Scientific Computing. 44(4). B964–B995. 4 indexed citations
10.
Mora, David, et al.. (2022). Velocity‑vorticity‑pressure formulation for the Oseen problem with variable viscosity. arXiv (Cornell University). 7 indexed citations
11.
Mora, David, et al.. (2019). Incorporating variable viscosity in vorticity-based formulations for Brinkman equations. Comptes Rendus Mathématique. 357(6). 552–560. 7 indexed citations
12.
Bendahmane, Mostafa, et al.. (2018). On a vorticity-based formulation for reaction-diffusion-Brinkman systems. Networks and Heterogeneous Media. 13(1). 69–94. 9 indexed citations
13.
Mora, David, Gonzalo Rivera, & Rodolfo Rodrı́guez. (2017). A posteriori error estimates for a Virtual Element Method for the Steklov eigenvalue problem. Computers & Mathematics with Applications. 74(9). 2172–2190. 39 indexed citations
14.
Meddahi, Salim, et al.. (2017). Acoustic vibration problem for dissipative fluids. Mathematics of Computation. 88(315). 45–71. 1 indexed citations
15.
Mora, David, et al.. (2015). A finite element method for the buckling problem of simply supported Kirchhoff plates. Journal of Computational and Applied Mathematics. 286. 68–78. 12 indexed citations
16.
Gatica, Gabriel N., et al.. (2015). An augmented velocity–vorticity–pressure formulation for the Brinkman equations. International Journal for Numerical Methods in Fluids. 79(3). 109–137. 35 indexed citations
17.
Mora, David, et al.. (2014). Locking-free finite element method for a bending moment formulation of Timoshenko beams. Computers & Mathematics with Applications. 68(3). 118–131. 11 indexed citations
18.
Meddahi, Salim, David Mora, & Rodolfo Rodrı́guez. (2014). Finite element analysis for a pressure–stress formulation of a fluid–structure interaction spectral problem. Computers & Mathematics with Applications. 68(12). 1733–1750. 7 indexed citations
19.
Antonietti, Paola F., L. Beirão da Veiga, David Mora, & Marco Verani. (2014). A Stream Virtual Element Formulation of the Stokes Problem on Polygonal Meshes. SIAM Journal on Numerical Analysis. 52(1). 386–404. 190 indexed citations
20.
Veiga, L. Beirão da & David Mora. (2011). A mimetic discretization of the Reissner–Mindlin plate bending problem. Numerische Mathematik. 117(3). 425–462. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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