JOURNAL METRICS

CiteScore 2022: 0.9 ℹCiteScore:

CiteScore is the number of citations received by a journal in one year to documents published in the three previous years, divided by the number of documents indexed in Scopus published in those same three years.

SCImago Journal Rank (SJR) 2022: 0.162 ℹSCImago Journal Rank (SJR):

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.

Source Normalized Impact per Paper (SNIP) 2022: 0.28 ℹSource Normalized Impact per Paper(SNIP):

SNIP measures a source’s contextual citation impact by weighting citations based on the total number of citations in a subject field. It helps you make a direct comparison of sources in different subject fields. SNIP takes into account characteristics of the source's subject field, which is the set of documents citing that source.

123.png

Archive

Analysis of the Giralda Tower Geotechnical Profile and Its Settlements

Emilio Romero Sánchez, Aes Esteban, María Victoria Requena García de la Cruz, Jaime Navarro Casas

https://doi.org/10.2495/CMEM-V10-N1-1-12

Page 1-12

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2852

Probabilistic Estimation of Runoff from Green Roofs

Anita Raimondi, Mariana Marchioni, Umberto Sanfilippo, Fernando Ferreira Stroppa, Gianfranco Becciu

https://doi.org/10.2495/CMEM-V10-N1-13-25

Page 13-25

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2853

Flow Regime Detection Using Gamma-Ray-Based Multiphase Flowmeter: A Machine Learning Approach

Jian Hua Zhu, Ritesh Munjal, Ani Sivaram, Santhiyapillai Rajeevan Paul, Jing Tian, Guillaume Jolivet

https://doi.org/10.2495/CMEM-V10-N1-26-37

Page 26-37

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2854

Numerical Drag and Lift Prediction Framework for Superellipsoidal Particles in Multiphase Flows

Mitja Štrakl, Jana Wedel, Paul Steinmann, Matjaž Hriberšek, Jure Ravnik

https://doi.org/10.2495/CMEM-V10-N1-38-49

Page 38-49

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2855

Modeling of the Sedimentation Process of Monodisperse Suspension

Rząsa Mariusz, Łukasiewicz Ewelina

https://doi.org/10.2495/CMEM-V10-N1-50-61

Page 50-61

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2856

Determination of Droplet Velocity in Square Microchannel

Jin-Yuan Qian, Xiao-Juan Li, Zan Wu, Zhen Cao, Bengt Sunden

https://doi.org/10.2495/CMEM-V10-N1-62-73

Page 62-73

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2857

Uncertainty Quantification of Aerodynamic and Aeroelastic Responses of A Short-Gap Twin-Box Deck Depending on the Wind Angle of Attack

Giuseppe G. Lobriglio, Antonio J. Álvarez, Felix Nieto, Santiago Hernández, José Á. Jurado

https://doi.org/10.2495/CMEM-V10-N1-74-84

Page 74-84

PDF Full-text HTML Full-text Citation

OPEN ACCESS

https://www.witpress.com/elibrary/cmem-volumes/10/1/2858