Example of Communications in Computational Physics format
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Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format
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Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format Example of Communications in Computational Physics format
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Communications in Computational Physics — Template for authors

Categories Rank Trend in last 3 yrs
Physics and Astronomy (miscellaneous) #23 of 58 down down by 9 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 325 Published Papers | 1049 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 04/07/2020
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Related Journals

open access Open Access

IOP Publishing

Quality:  
High
CiteRatio: 3.9
SJR: 0.59
SNIP: 0.826
open access Open Access

Springer

Quality:  
High
CiteRatio: 2.5
SJR: 0.337
SNIP: 0.719
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 4.1
SJR: 1.099
SNIP: 1.093

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

2.607

44% from 2018

Impact factor for Communications in Computational Physics from 2016 - 2019
Year Value
2019 2.607
2018 1.813
2017 1.762
2016 2.004
graph view Graph view
table view Table view

3.2

9% from 2019

CiteRatio for Communications in Computational Physics from 2016 - 2020
Year Value
2020 3.2
2019 3.5
2018 3.4
2017 2.7
2016 2.8
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 44% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has decreased by 9% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.217

27% from 2019

SJR for Communications in Computational Physics from 2016 - 2020
Year Value
2020 1.217
2019 0.959
2018 0.855
2017 1.048
2016 0.969
graph view Graph view
table view Table view

1.266

39% from 2019

SNIP for Communications in Computational Physics from 2016 - 2020
Year Value
2020 1.266
2019 0.913
2018 1.103
2017 1.022
2016 0.888
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 27% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 39% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Communications in Computational Physics

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Cambridge University Press

Communications in Computational Physics

Communications in Computational Physics (CiCP) publishes original research and survey papers of high scientific value in computational modeling of physical problems. Results in multi-physics and multi-scale innovative computational methods and modeling in all physical sciences...... Read More

Physics and Astronomy

i
Last updated on
04 Jul 2020
i
ISSN
1815-2406
i
Impact Factor
High - 1.087
i
Open Access
No
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
unsrt
i
Citation Type
Numbered
[25]
i
Bibliography Example
G E Blonder, M Tinkham, and T M Klapwijk. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B, 25(7):4515–4532, 1982. 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article
Heterogeneous multiscale methods: A review
Weinan E1, Björn Engquist2, Xiantao Li, Weiqing Ren3, Eric Vanden-Eijnden3

Abstract:

This paper gives a systematic introduction to HMM, the heterogeneous multiscale methods, including the fundamental design principles behind the HMM philosophy and the main obstacles that have to be ... This paper gives a systematic introduction to HMM, the heterogeneous multiscale methods, including the fundamental design principles behind the HMM philosophy and the main obstacles that have to be ... read more read less

Topics:

Multiscale modeling (60%)60% related to the paper, Information and Computer Science (53%)53% related to the paper
774 Citations
open accessOpen access Journal Article
Fast numerical methods for stochastic computations: A review
Dongbin Xiu1

Abstract:

This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along w... This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along with its Galerkin and collocation approaches for solving stochastic equations. Properties of these methods are summarized by using results from literature. This paper also attempts to present the gPC based methods in a unified framework based on an extension of the classical spectral methods into multi-dimensional random spaces. AMS subject classifications: 41A10, 60H35, 65C30, 65C50 read more read less

Topics:

Stochastic optimization (60%)60% related to the paper, Polynomial chaos (54%)54% related to the paper, Stochastic partial differential equation (52%)52% related to the paper, Stochastic differential equation (52%)52% related to the paper, Spectral method (51%)51% related to the paper
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665 Citations
open accessOpen access Journal Article DOI: 10.4208/CICP.291210.290411S
Numerical Methods for Fluid-Structure Interaction — A Review
Gene Hou, Jin Wang, Anita T. Layton

Abstract:

The interactions between incompressible fluid flows and immersed struc- tures are nonlinear multi-physics phenomena that have applications to a wide range of scientific and engineering disciplines In this article, we review representative numeri- cal methods based onconforming and non-conforming meshes that arecurrentlyavail-... The interactions between incompressible fluid flows and immersed struc- tures are nonlinear multi-physics phenomena that have applications to a wide range of scientific and engineering disciplines In this article, we review representative numeri- cal methods based onconforming and non-conforming meshes that arecurrentlyavail- able for computing fluid-structure interaction problems, with an emphasis on some of the recent developments in the field A goal is to categorize the selected methods and assess their accuracy and efficiency We discuss challenges faced by researchers in this field, and we emphasize the importance of interdisciplinary effort for advancing the study in fluid-structure interactions read more read less
View PDF
555 Citations
open accessOpen access Journal Article
Efficient collocational approach for parametric uncertainty analysis
Dongbin Xiu1

Abstract:

A numerical algorithm for effective incorporation of parametric uncertainty into mathematical models is presented. The uncertain parameters are modeled as random variables, and the governing equations are treated as stochastic. The solutions, or quantities of interests, are expressed as convergent series of orthogonal polynom... A numerical algorithm for effective incorporation of parametric uncertainty into mathematical models is presented. The uncertain parameters are modeled as random variables, and the governing equations are treated as stochastic. The solutions, or quantities of interests, are expressed as convergent series of orthogonal polynomial expansions in terms of the input random parameters. A high-order stochastic collocation method is employed to solve the solution statistics, and more importantly, to reconstruct the polynomial expansion. While retaining the high accuracy by polynomial expansion, the resulting “pseudo-spectral” type algorithm is straightforward to implement as it requires only repetitive deterministic simulations. An estimate on error bounded is presented, along with numerical examples for problems with relatively complicated forms of governing equations. read more read less

Topics:

Deterministic simulation (60%)60% related to the paper, Polynomial expansion (59%)59% related to the paper, Collocation method (57%)57% related to the paper, Parametric statistics (56%)56% related to the paper, Uncertainty analysis (54%)54% related to the paper
441 Citations
open accessOpen access Journal Article DOI: 10.4208/CICP.301110.040811A
Phase-Field Models for Multi-Component Fluid Flows

Abstract:

In this paper, we review the recent development of phase-field models and their numerical methods for multi-component fluid flows with interfacial phenomena. The models consist of a Navier-Stokes system coupled with a multi-component Cahn-Hilliard system through a phase-field dependent surface tension force, variable density ... In this paper, we review the recent development of phase-field models and their numerical methods for multi-component fluid flows with interfacial phenomena. The models consist of a Navier-Stokes system coupled with a multi-component Cahn-Hilliard system through a phase-field dependent surface tension force, variable density and viscosity, and the advection term. The classical infinitely thin boundary of separation between two immiscible fluids is replaced by a transition region of a small but finite width, across which the composition of the mixture changes continuously. A constant level set of the phase-field is used to capture the interface between two immiscible fluids. Phase-field methods are capable of computing topological changes such as splitting and merging, and thus have been applied successfully to multi-component fluid flows involving large interface deformations. Practical applications are provided to illustrate the usefulness of using a phase-field method. Computational results of various experiments show the accuracy and effectiveness of phase-field models. read more read less

Topics:

Phase field models (51%)51% related to the paper, Viscosity (51%)51% related to the paper, Boundary (topology) (50%)50% related to the paper
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433 Citations
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Communications in Computational Physics format uses unsrt citation style.

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Frequently asked questions

1. Can I write Communications in Computational Physics in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Communications in Computational Physics guidelines and auto format it.

2. Do you follow the Communications in Computational Physics guidelines?

Yes, the template is compliant with the Communications in Computational Physics guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Communications in Computational Physics?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Communications in Computational Physics citation style.

4. Can I use the Communications in Computational Physics templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Communications in Computational Physics.

5. Can I use a manuscript in Communications in Computational Physics that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Communications in Computational Physics that you can download at the end.

6. How long does it usually take you to format my papers in Communications in Computational Physics?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Communications in Computational Physics.

7. Where can I find the template for the Communications in Computational Physics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Communications in Computational Physics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Communications in Computational Physics's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Communications in Computational Physics an online tool or is there a desktop version?

SciSpace's Communications in Computational Physics is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Communications in Computational Physics?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Communications in Computational Physics?”

11. What is the output that I would get after using Communications in Computational Physics?

After writing your paper autoformatting in Communications in Computational Physics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Communications in Computational Physics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Communications in Computational Physics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Communications in Computational Physics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Communications in Computational Physics?

The 5 most common citation types in order of usage for Communications in Computational Physics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Communications in Computational Physics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Communications in Computational Physics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Communications in Computational Physics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Communications in Computational Physics Endnote style according to Elsevier guidelines.

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