| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Earth Science | 254 | 35 | 46 | 15 |
| Engineering and Technology | 392 | 52 | 99 | 20 |
| Mathematics | 408 | 17 | 34 | 7 |
The journal investigates studies in Hydrogeology, Mathematical optimization, Algorithm, Porous medium and Mechanics. Computational Geosciences addresses concerns in Hydrogeology which are intertwined with other disciplines, such as Flow (mathematics), Grid, Finite element method and Permeability (earth sciences). It is mostly focused on Finite element method, specifically Mixed finite element method.
The concepts on Mathematical optimization presented in it can also apply to other research fields, including Uncertainty quantification, Reservoir simulation, Computation and Applied mathematics. The tackled Applied mathematics research is interrelated with Discretization which concerns subjects like Finite volume method. It explores topics in Algorithm which can be helpful for research in disciplines like Data assimilation and Ensemble Kalman filter.
Porous medium study tackled is connected to the field of Two-phase flow. The journal links adjacent topics like Mechanics with Boundary value problem. Computational Geosciences holds forums on Mathematical analysis that merges themes from other disciplines such as Discontinuous Galerkin method and Nonlinear system.
The most cited papers aim to foster the development of research in Mathematical optimization, Hydrogeology, Mathematical analysis, Flow (mathematics) and Discretization. The published papers explore topics in Mathematical optimization which can be helpful for research in disciplines like Algorithm, Grid, Reservoir simulation and Applied mathematics. While work presented in the most cited articles provide substantial information on Hydrogeology, it also covers topics in Porosity, Porous medium, Mechanics and Polygon mesh.
Computational Geosciences explores disciplines such as Hydrogeology, Applied mathematics, Algorithm, Discretization and Mechanics. The research on Hydrogeology tackled can also make contributions to studies in the areas of Data mining, Flow (psychology), Computer simulation and Artificial intelligence, Benchmark (computing). The journal focuses on Applied mathematics but the discussions also offer insight into other areas such as Flow (mathematics), Linear system, Finite element method, Iterative method and Multigrid method.
The work on Algorithm tackled in Computational Geosciences brings together disciplines like Uncertainty quantification, Hessian matrix, Data assimilation and Sensitivity (control systems). Data assimilation research in the journal involves the investigation of Function (mathematics) studies, all of which are linked to disciplines such as Mathematical optimization. The Mechanics works featured in it incorporate elements from Upwind scheme, Porosity, Porous medium, Viscosity and Fracture (geology).
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Computational Geosciences (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Computational Geosciences (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 6.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 30.70% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.04% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.04% of all publications and 41.23% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Sergi Molins;Cyprien Soulaine;Nikolaos I. Prasianakis;Aida Abbasi
(2021)Suihong Song;Suihong Song;Tapan Mukerji;Jiagen Hou
(2021)Matthew R. Sweeney;Carl W. Gable;Satish Karra;Philip H. Stauffer
(2020)Iryna Rybak;Christoph Schwarzmeier;Elissa Eggenweiler;Ulrich Rüde
(2021)Ingeborg Gåseby Gjerde;Kundan Kumar;Jan Martin Nordbotten
(2020)S. R. Zhu;S. R. Zhu;L. Z. Wu;J. Huang
(2021)Zhijun Wu;Yuan Zhou;Lei Weng;Quansheng Liu
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