| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mechanical and Aerospace Engineering | 41 | 116 | 268 | 36 |
| Mathematics | 221 | 18 | 24 | 12 |
| Engineering and Technology | 293 | 80 | 145 | 25 |
The scientific interests tackled in Computational Mechanics are Finite element method, Mathematical analysis, Numerical analysis, Mechanics and Applied mathematics. The research on Finite element method featured in Computational Mechanics combines topics in other fields like Discretization and Nonlinear system. Mathematical analysis research featured in the journal incorporates concerns from various other topics such as Boundary element method, Singular boundary method, Geometry and Boundary (topology).
The work tackled in the journal goes beyond the discipline of Singular boundary method as it also encompasses Boundary knot method. Specifically, studies on Method of fundamental solutions are prevalent in the Boundary knot method works discussed. The in-depth study on Numerical analysis also explores topics in the intersecting field of Algorithm.
Mechanics study tackled is connected to the field of Classical mechanics. The work tackled in it goes beyond the discipline of Applied mathematics as it also encompasses Mathematical optimization. Research on Structural engineering presented in Computational Mechanics focuses, in particular, on Fracture mechanics and Constitutive equation.
The journal papers investigate areas of study like Finite element method, Mathematical analysis, Numerical analysis, Applied mathematics and Structural engineering. The most cited articles explore topics in Finite element method which can be helpful for research in disciplines like Mechanics and Nonlinear system. The published articles explore issues in Mathematical analysis which can be linked to other research areas like Boundary element method, Geometry and Boundary (topology).
Computational Mechanics is organized to address concerns in the fields of Finite element method, Mathematical analysis, Applied mathematics, Mechanics and Discretization. The close relationship between Algorithm and Artificial neural network and Computational mechanics is one of the points of interest dissected in Finite element method research. The study of Mathematical analysis encompasses disciplines such as Finite strain theory, as well as fields such as Constitutive equation, all of which overlap with one another.
The Applied mathematics works featured in it incorporate elements from Polygon mesh, Quadrature (mathematics), Collocation method, Multiphysics and Nonlinear system. While work presented in it provided substantial information on Mechanics, it also covered topics in Isotropy, Stress (mechanics), Anisotropy and Plasticity. It explores issues in Discretization which can be linked to other research areas like Flow (mathematics), Boundary (topology), Isogeometric analysis and Computational science.
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 Mechanics (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 Mechanics (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, 7.18% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.64% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.52% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.83% of all publications and 50.00% 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.
Kevin Linka;Mathias Peirlinck;Ellen Kuhl
(2020)Karlo Seleš;Fadi Aldakheel;Zdenko Tonković;Jurica Sorić
(2021)Tao Wang;Xuan Ye;Zhanli Liu;Xiaoming Liu
(2020)Alex Viguerie;Alessandro Veneziani;Guillermo Lorenzo;Davide Baroli
(2020)Takuya Terahara;Kenji Takizawa;Tayfun E. Tezduyar;Tayfun E. Tezduyar;Yuri Bazilevs
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