Example of Numerical Methods for Partial Differential Equations format
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Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format
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Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format Example of Numerical Methods for Partial Differential Equations format
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Numerical Methods for Partial Differential Equations — Template for authors

Publisher: Wiley
Categories Rank Trend in last 3 yrs
Analysis #17 of 164 up up by 15 ranks
Numerical Analysis #12 of 66 up up by 5 ranks
Applied Mathematics #100 of 548 up up by 73 ranks
Computational Mathematics #31 of 152 up up by 30 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 407 Published Papers | 1569 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 07/07/2020
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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.

2.236

37% from 2018

Impact factor for Numerical Methods for Partial Differential Equations from 2016 - 2019
Year Value
2019 2.236
2018 1.633
2017 1.305
2016 1.079
graph view Graph view
table view Table view

3.9

39% from 2019

CiteRatio for Numerical Methods for Partial Differential Equations from 2016 - 2020
Year Value
2020 3.9
2019 2.8
2018 2.5
2017 2.1
2016 2.1
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 37% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 39% 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.

0.901

9% from 2019

SJR for Numerical Methods for Partial Differential Equations from 2016 - 2020
Year Value
2020 0.901
2019 0.993
2018 0.998
2017 1.059
2016 1.029
graph view Graph view
table view Table view

1.212

10% from 2019

SNIP for Numerical Methods for Partial Differential Equations from 2016 - 2020
Year Value
2020 1.212
2019 1.099
2018 1.069
2017 0.995
2016 0.841
graph view Graph view
table view Table view

insights Insights

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

insights Insights

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

Numerical Methods for Partial Differential Equations

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Wiley

Numerical Methods for Partial Differential Equations

An international journal that aims to cover research into the development and analysis of new methods for the numerical solution of partial differential equations, it is intended that it be readily readable by and directed to a broad spectrum of researchers into numerical meth...... Read More

Mathematics

i
Last updated on
07 Jul 2020
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ISSN
0749-159X
i
Impact Factor
High - 1.096
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
apa
i
Citation Type
Numbered
[25]
i
Bibliography Example
Beenakker, C.W.J. (2006) Specular andreev reflection in graphene.Phys. Rev. Lett., 97 (6), 067 007. URL 10.1103/PhysRevLett.97.067007.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1002/NUM.20112
Variational formulation for the stationary fractional advection dispersion equation
Vincent J. Ervin1, John Paul Roop2

Abstract:

In this article a theoretical framework for the Galerkin finite element approximation to the steady state fractional advection dispersion equation is presented. Appropriate fractional derivative spaces are defined and shown to be equivalent to the usual fractional dimension Sobolev spaces Hs. Existence and uniqueness results ... In this article a theoretical framework for the Galerkin finite element approximation to the steady state fractional advection dispersion equation is presented. Appropriate fractional derivative spaces are defined and shown to be equivalent to the usual fractional dimension Sobolev spaces Hs. Existence and uniqueness results are proven, and error estimates for the Galerkin approximation derived. Numerical results are included that confirm the theoretical estimates. © 2005 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2005 read more read less

Topics:

Fractional calculus (63%)63% related to the paper, Galerkin method (56%)56% related to the paper, Sobolev space (53%)53% related to the paper, Finite element method (51%)51% related to the paper, Uniqueness (51%)51% related to the paper
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707 Citations
Journal Article DOI: 10.1002/NUM.1690080202
Simple nonconforming quadrilateral Stokes element
Rolf Rannacher1, Stefan Turek1

Abstract:

A simple nonconforming quadrilateral Stokes element based on “rotated” multi-linear shape functions is analyzed. On strongly nonuniform meshes the usual parametric version of this element suffers from a lack of consistency, while its nonparametric counterpart turns out to be convergent with optimal orders. This theoretical re... A simple nonconforming quadrilateral Stokes element based on “rotated” multi-linear shape functions is analyzed. On strongly nonuniform meshes the usual parametric version of this element suffers from a lack of consistency, while its nonparametric counterpart turns out to be convergent with optimal orders. This theoretical result is confirmed by numerical tests. read more read less

Topics:

Quadrilateral (58%)58% related to the paper
591 Citations
Journal Article DOI: 10.1002/NUM.20460
Solving nonlinear fractional partial differential equations using the homotopy analysis method
Mehdi Dehghan1, Jalil Manafian1, Abbas Saadatmandi2

Abstract:

In this article, the homotopy analysis method is applied to solve nonlinear fractional partial differential equations. On the basis of the homotopy analysis method, a scheme is developed to obtain the approximate solution of the fractional KdV, K(2,2), Burgers, BBM-Burgers, cubic Boussinesq, coupled KdV, and Boussinesq-like B... In this article, the homotopy analysis method is applied to solve nonlinear fractional partial differential equations. On the basis of the homotopy analysis method, a scheme is developed to obtain the approximate solution of the fractional KdV, K(2,2), Burgers, BBM-Burgers, cubic Boussinesq, coupled KdV, and Boussinesq-like B(m,n) equations with initial conditions, which are introduced by replacing some integer-order time derivatives by fractional derivatives. The homotopy analysis method for partial differential equations of integer-order is directly extended to derive explicit and numerical solutions of the fractional partial differential equations. The solutions of the studied models are calculated in the form of convergent series with easily computable components. The results of applying this procedure to the studied cases show the high accuracy and efficiency of the new technique. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2010 read more read less

Topics:

Homotopy analysis method (74%)74% related to the paper, Numerical partial differential equations (68%)68% related to the paper, Stochastic partial differential equation (66%)66% related to the paper, First-order partial differential equation (66%)66% related to the paper, Adomian decomposition method (64%)64% related to the paper
554 Citations
H‐p clouds—an h‐p meshless method
C. Armando Duarte1, J. Tinsley Oden1

Abstract:

A new methodology to build discrete models of boundary-value problems is presented. The h-pcloud method is applicable to arbitrary domains and employs only a scattered set of nodes to build approximate solutions to BVPs. This new method uses radial basis functions of varying size of supports and with polynomialreproducing pro... A new methodology to build discrete models of boundary-value problems is presented. The h-pcloud method is applicable to arbitrary domains and employs only a scattered set of nodes to build approximate solutions to BVPs. This new method uses radial basis functions of varying size of supports and with polynomialreproducing properties of arbitrary order. The approximating properties of the h-p cloud functions are investigated in this article and a several theorems concerning these properties are presented. Moving least squares interpolants are used to build a partition of unity on the domain of interest. These functions are then used to construct, at a very low cost, trial and test functions for Galerkin approximations. The method exhibits a very high rate of convergence and has a greater -exibility than traditional h-p finite element methods. Several numerical experiments in I-D and 2-D are also presented. @ 1996 John Wiley & Sons, Inc. In most large-scale numerical simulations of physical phenomena, a large percentage of the overall computational effort is expended on technical details connected with meshing. These details include, in particular, grid generation, mesh adaptation to domain geometry, element or cell connectivity, grid motion and separation to model fracture, fragmentation, free surfaces, etc. Moreover, in most computer-aided design work, the generation of an appropriate mesh constitutes, by far, the costliest portion of the computer-aided analysis of products and processes. These are among the reasons that interest in so-called meshless methods has grown rapidly in recent years. Most meshless methods require a scattered set of nodal points in the domain of interest. In these methods, there may be no fixed connectivities between the nodes, unlike the finite element or finite difference methods. This feature has significant implications in modeling some physical phenomena that are characterized by a continuous change in the geometry of the domain under analysis. The analysis of problems such as crack propagation, penetration, and large deformations, can, in principle, be greatly simplified by the use of meshless methods. A growing crack, for example, can be modeled by simply extending the free surfaces that correspond to the crack [ 11. The analysis of large deformation problems by, e.g., finite element methods, may require the continuous remeshing of the domain to avoid the breakdown of the calculation due to read more read less

Topics:

Regularized meshless method (65%)65% related to the paper, Meshfree methods (61%)61% related to the paper, Mesh generation (60%)60% related to the paper, Finite element method (57%)57% related to the paper, Moving least squares (55%)55% related to the paper
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540 Citations
Journal Article DOI: 10.1002/NUM.10062
Exponential convergence and H‐c multiquadric collocation method for partial differential equations
Alexander H.-D. Cheng1, M. A. Golberg, E.J. Kansa2, G. Zammito3

Abstract:

The radial basis function (RBF) collocation method uses global shape functions to interpolate and collocatethe approximate solution of PDEs. It is a truly meshless method as compared to some of the so-calledmeshless or element-free finite element methods. For the multiquadric and Gaussian RBFs, there are twoways to make the so... The radial basis function (RBF) collocation method uses global shape functions to interpolate and collocatethe approximate solution of PDEs. It is a truly meshless method as compared to some of the so-calledmeshless or element-free finite element methods. For the multiquadric and Gaussian RBFs, there are twoways to make the solution converge—either by refining the mesh size read more read less

Topics:

Regularized meshless method (64%)64% related to the paper, Collocation method (63%)63% related to the paper, Orthogonal collocation (63%)63% related to the paper, Singular boundary method (59%)59% related to the paper, Partial differential equation (52%)52% related to the paper
395 Citations
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13. What is Sherpa RoMEO Archiving Policy for Numerical Methods for Partial Differential Equations?

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 Numerical Methods for Partial Differential Equations. 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 Numerical Methods for Partial Differential Equations?

The 5 most common citation types in order of usage for Numerical Methods for Partial Differential Equations are:.

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

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