0045-7825
Published by: Elsevier
https://www.journals.elsevier.com/computer-methods-in-applied-mechanics-and-engineering
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mechanical and Aerospace Engineering | 9 | 232 | 798 | 62 |
| Mathematics | 9 | 108 | 310 | 37 |
| Engineering and Technology | 45 | 282 | 768 | 59 |
The main research concerns discussed in Computer Methods in Applied Mechanics and Engineering are Finite element method, Mathematical analysis, Applied mathematics, Numerical analysis and Mathematical optimization. The journal holds forums on Finite element method that merges themes from other disciplines such as Discretization, Algorithm, Geometry and Nonlinear system. The Mathematical analysis works featured in it incorporate elements from Boundary (topology), Galerkin method and Classical mechanics.
The studies on Applied mathematics discussed can also contribute to research in the domains of Polygon mesh, A priori and a posteriori, Estimator, Isogeometric analysis and Calculus. It dives deep in exploring the relationship between the study of Numerical analysis and Mechanics. Most of the works presented in the journal deals with Mechanics but it intersects with the subject of Structural engineering.
It investigates Mathematical optimization research which frequently intersects with Topology optimization. The research on Mixed finite element method discussed in the journal draws on the closely related field of Extended finite element method.
The journal papers facilitate discussions on Finite element method, Mathematical analysis, Applied mathematics, Numerical analysis and Mathematical optimization. Geometry, Classical mechanics and Nonlinear system are some topics wherein Finite element method research discussed in the most cited papers has an impact. The works on Mathematical analysis tackled in the published articles bring together disciplines like Navier–Stokes equations, Galerkin method and Discontinuous Galerkin method.
Computer Methods in Applied Mechanics and Engineering is mainly concerned with subjects like Applied mathematics, Field (physics), Mechanics, Finite element method and Algorithm. The journal addresses concerns in Applied mathematics which are intertwined with other disciplines, such as Partial differential equation, Biot number, Benchmark (computing), Nonlinear system and Acceleration. The work on Field (physics) tackled in it brings together disciplines like Phase (waves), Isogeometric analysis, Phase (matter) and Composite material.
Computer Methods in Applied Mechanics and Engineering centers on topics in Finite element method, with a focus on Mortar methods. In addition to Algorithm research, the journal aims to explore topics under Conditional random field, Measure (mathematics), Multivariate statistics, Random field and Cholesky decomposition. The presented research on Discretization deals specifically with Optimization problem but it also addresses topics in Mathematical analysis and Boundary (topology).
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 Computer Methods in Applied Mechanics and Engineering (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 Computer Methods in Applied Mechanics and Engineering (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 2022 edition, 20.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 41.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 8.33% 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.
E. Samaniego;C. Anitescu;S. Goswami;V.M. Nguyen-Thanh
(2020)Zhiping Mao;Ameya D. Jagtap;George Em Karniadakis
(2020)Ehsan Haghighat;Maziar Raissi;Adrian Moure;Hector Gomez
(2021)Ameya D. Jagtap;Ehsan Kharazmi;George Em Karniadakis;George Em Karniadakis
(2020)Georgios Kissas;Yibo Yang;Eileen Hwuang;Walter R. Witschey
(2020)Xuhui Meng;Zhen Li;Dongkun Zhang;George Em Karniadakis
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