Example of Journal of Computational Physics format
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Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format
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Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format Example of Journal of Computational Physics format
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open access Open Access
recommended Recommended

Journal of Computational Physics — Template for authors

Publisher: Elsevier
Categories Rank Trend in last 3 yrs
Applied Mathematics #33 of 548 down down by None rank
Numerical Analysis #5 of 66 down down by None rank
Computational Mathematics #13 of 152 down down by None rank
Modeling and Simulation #31 of 290 down down by None rank
Physics and Astronomy (all) #31 of 233 down down by None rank
Physics and Astronomy (miscellaneous) #10 of 58 down down by 3 ranks
Computer Science Applications #134 of 693 down down by 49 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 2706 Published Papers | 16515 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 15/06/2020
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FAQ

Related Journals

open access Open Access

Elsevier

Quality:  
High
CiteRatio: 3.4
SJR: 0.531
SNIP: 0.961
open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 1.4
SJR: 0.214
SNIP: 0.992
open access Open Access

Springer

Quality:  
High
CiteRatio: 3.4
SJR: 0.291
SNIP: 0.951
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 7.9
SJR: 1.159
SNIP: 1.775

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.

2.985

5% from 2018

Impact factor for Journal of Computational Physics from 2016 - 2019
Year Value
2019 2.985
2018 2.845
2017 2.864
2016 2.744
graph view Graph view
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6.1

5% from 2019

CiteRatio for Journal of Computational Physics from 2016 - 2020
Year Value
2020 6.1
2019 5.8
2018 5.5
2017 5.4
2016 5.2
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 5% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 5% 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.

1.882

3% from 2019

SJR for Journal of Computational Physics from 2016 - 2020
Year Value
2020 1.882
2019 1.936
2018 1.643
2017 2.047
2016 2.049
graph view Graph view
table view Table view

1.743

5% from 2019

SNIP for Journal of Computational Physics from 2016 - 2020
Year Value
2020 1.743
2019 1.836
2018 1.777
2017 1.838
2016 1.799
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 3% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 5% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Computational Physics

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Elsevier

Journal of Computational Physics

Journal of Computational Physics thoroughly treats the computational aspects of physical problems, presenting techniques for the numerical solution of mathematical equations arising in all areas of physics. The journal seeks to emphasize methods that cross disciplinary boundar...... Read More

Physics and Astronomy

i
Last updated on
14 Jun 2020
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ISSN
0021-9991
i
Impact Factor
High - 2.464
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
elsarticle-num
i
Citation Type
Numbered
[25]
i
Bibliography Example
G. E. Blonder, M. Tinkham, T. M. Klapwijk, Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion, Phys. Rev. B 25 (7) (1982) 4515–4532. URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1006/JCPH.1995.1039
Fast parallel algorithms for short-range molecular dynamics
Steven J. Plimpton1

Abstract:

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be dif... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed. read more read less

Topics:

Intel Paragon (64%)64% related to the paper, Intel iPSC (62%)62% related to the paper, Parallel algorithm (58%)58% related to the paper, Parallel processing (DSP implementation) (54%)54% related to the paper
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26,738 Citations
open accessOpen access Journal Article DOI: 10.1016/0021-9991(77)90098-5
Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes
Jean-Paul Ryckaert1, Giovanni Ciccotti1, Herman J. C. Berendsen1

Abstract:

A numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated. The relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration. The method is applied to a molecular d... A numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated. The relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration. The method is applied to a molecular dynamics simulation of a liquid of 64 n-butane molecules and compared to a simulation using generalized coordinates. The method should be useful for molecular dynamics calculations on large molecules with internal degrees of freedom. read more read less

Topics:

Generalized coordinates (62%)62% related to the paper, Holonomic constraints (58%)58% related to the paper, Verlet integration (58%)58% related to the paper, Equations of motion (55%)55% related to the paper, Cartesian coordinate system (55%)55% related to the paper
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16,572 Citations
Journal Article DOI: 10.1016/0021-9991(88)90002-2
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Stanley Osher1, James A. Sethian2

Abstract:

New numerical algorithms are devised (PSC algorithms) for following fronts propagating with curvature-dependent speed. The speed may be an arbitrary function of curvature, and the front can also be passively advected by an underlying flow. These algorithms approximate the equations of motion, which resemble Hamilton-Jacobi eq... New numerical algorithms are devised (PSC algorithms) for following fronts propagating with curvature-dependent speed. The speed may be an arbitrary function of curvature, and the front can also be passively advected by an underlying flow. These algorithms approximate the equations of motion, which resemble Hamilton-Jacobi equations with parabolic right-hand-sides, by using techniques from the hyperbolic conservation laws. Non-oscillatory schemes of various orders of accuracy are used to solve the equations, providing methods that accurately capture the formation of sharp gradients and cusps in the moving fronts. The algorithms handle topological merging and breaking naturally, work in any number of space dimensions, and do not require that the moving surface be written as a function. The methods can be used also for more general Hamilton-Jacobi-type problems. The algorithms are demonstrated by computing the solution to a variety of surface motion problems. read more read less

Topics:

Equations of motion (55%)55% related to the paper, Curvature (54%)54% related to the paper, Hamilton–Jacobi equation (53%)53% related to the paper, Hyperbolic function (52%)52% related to the paper, Conservation law (51%)51% related to the paper
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12,372 Citations
Journal Article DOI: 10.1016/0021-9991(81)90145-5
Volume of fluid (VOF) method for the dynamics of free boundaries
C.W Hirt1, B. D. Nichols1

Abstract:

Several methods have been previously used to approximate free boundaries in finite-difference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efficient than other methods for treating complicated... Several methods have been previously used to approximate free boundaries in finite-difference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efficient than other methods for treating complicated free boundary configurations. To illustrate the method, a description is given for an incompressible hydrodynamics code, SOLA-VOF, that uses the VOF technique to track free fluid surfaces. read more read less

Topics:

Volume of fluid method (60%)60% related to the paper, Compressibility (50%)50% related to the paper
9,793 Citations
Journal Article DOI: 10.1006/JCPH.1994.1159
A perfectly matched layer for the absorption of electromagnetic waves

Abstract:

A new technique of free-space simulation has been developed for solving unbounded electromagnetic problems with the finite-difference time-domain method. Referred to as PML, the new technique is based on the use of an absorbing layer especially designed to absorb without reflection the electromagnetic waves. The first part of... A new technique of free-space simulation has been developed for solving unbounded electromagnetic problems with the finite-difference time-domain method. Referred to as PML, the new technique is based on the use of an absorbing layer especially designed to absorb without reflection the electromagnetic waves. The first part of the paper presents the theory of the PML technique. The second part is devoted to numerical experiments and to numerical comparisons with the previously used techniques of free-space simulation. These comparisons show that the PML technique works better than the others in all cases; using it allows us to obtain a higher accuracy in some problems and a release of computational requirements in some others. read more read less

Topics:

Perfectly matched layer (70%)70% related to the paper
9,340 Citations
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Journal of Computational Physics format uses elsarticle-num citation style.

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Frequently asked questions

1. Can I write Journal of 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 Journal of Computational Physics guidelines and auto format it.

2. Do you follow the Journal of Computational Physics guidelines?

Yes, the template is compliant with the Journal of 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 Journal of 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 Journal of Computational Physics citation style.

4. Can I use the Journal of 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 Journal of Computational Physics.

5. Can I use a manuscript in Journal of 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 Journal of Computational Physics that you can download at the end.

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

7. Where can I find the template for the Journal of 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 Journal of 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 Journal of 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. Journal of Computational Physics an online tool or is there a desktop version?

SciSpace's Journal of 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 Journal of 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 Journal of Computational Physics?”

11. What is the output that I would get after using Journal of Computational Physics?

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

12. Is Journal of 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 Journal of 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 Journal of 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 Journal of Computational Physics?

The 5 most common citation types in order of usage for Journal of 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 Journal of 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 Journal of Computational Physics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of 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 Journal of Computational Physics Endnote style according to Elsevier guidelines.

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