0266-8920
Published by: Elsevier
https://www.journals.elsevier.com/probabilistic-engineering-mechanics
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mechanical and Aerospace Engineering | 349 | 12 | 15 | 6 |
| Engineering and Technology | 520 | 38 | 92 | 16 |
The main points discussed in Probabilistic Engineering Mechanics deals with Applied mathematics, Mathematical analysis, Monte Carlo method, Nonlinear system and Stochastic process. Probabilistic Engineering Mechanics focuses on Applied mathematics but the discussions also offer insight into other areas such as Random field, Mathematical optimization, Random variable and Calculus. While work presented in it provided substantial information on Mathematical optimization, it also covered topics in Reliability (statistics) and Probabilistic logic.
Probabilistic Engineering Mechanics investigates Random variable research which frequently intersects with Probability distribution. The concepts on Mathematical analysis presented in the journal can also apply to other research fields, including Classical mechanics, Probability density function, White noise and Random vibration. The study on Random vibration presented in Probabilistic Engineering Mechanics intersects with subjects under the field of Linear system.
It facilitates discussions on Monte Carlo method that incorporate concepts from other fields like Algorithm and Structural engineering, Finite element method. It explores the study of Nonlinear system to improve our understanding of the broader topic of Control theory. The Stochastic process works featured in it incorporate elements from Statistical physics and Spectral density.
The journal articles are organized to reinforce research efforts on Algorithm, Applied mathematics, Monte Carlo method, Mathematical optimization and Mathematical analysis. The most cited papers explore topics in Applied mathematics which can be helpful for research in disciplines like Stochastic process, Linear system and Calculus. While work presented in the journal articles provide substantial information on Mathematical analysis, it also covers topics in Random vibration, Probability density function and Nonlinear system.
Probabilistic Engineering Mechanics mainly deals with areas of study such as Applied mathematics, Algorithm, Probability density function, Monte Carlo method and Random field. The studies on Applied mathematics discussed can also contribute to research in the domains of Random variable, Marginal distribution, Nonlinear system, Skewness and Numerical analysis. Algorithm research featured in Probabilistic Engineering Mechanics incorporates concerns from various other topics such as Spectral density, Structural failure, White noise and Linear filter.
The studies in Probability density function featured incorporate elements of Probabilistic logic, Equations of motion, Randomness, Viscoelasticity and Mechanical equilibrium. It addresses concerns in the field of Monte Carlo method by exploring it in line with topics in Reliability (statistics) which intersect with Importance sampling, Kriging and Importance sampling method subjects. Topics in Random field were tackled in line with various other fields like Finite element method, Statistical physics, Random variate and Curse of dimensionality.
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 Probabilistic Engineering 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 Probabilistic Engineering 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, 7.69% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.89% of all publications and 52.78% 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.
Ehsan Adeli;Bojana Rosić;Hermann G. Matthies;Sven Reinstädler
(2020)Pol D. Spanos;Giovanni Malara
(2020)Omid Sedehi;Omid Sedehi;Costas Papadimitriou;Lambros S. Katafygiotis
(2020)T.J. Dodwell;T.J. Dodwell;S. Kynaston;R. Butler;R.T. Haftka
(2021)M. Ciano;M. Gioffrè;M. Grigoriu
(2020)For those interested in Mechanical and Aerospace Engineering, exploring 2 year accelerated bachelor degrees online offers a fast-tracked option to earn a degree without compromising quality. Accelerated programs help students enter the workforce sooner while maintaining rigorous academic standards.
Many students are motivated by potential earnings, so considering 4 year degrees that pay well can guide informed decisions. Mechanical and Aerospace Engineering often rank among these, leading to lucrative opportunities once graduated.
Understanding highest paying jobs associated with engineering degrees can help clarify career goals. Common paths include aerospace design, systems engineering, and robotics, all offering competitive salaries and growth potential.
For budget-conscious students, affordable options matter. Exploring cheap online bachelor degree programs supports financial feasibility while ensuring access to quality education, which is vital in fields demanding technical expertise.
