A Fast Explicit Operator Splitting Method for Passive Scalar Advection View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-10

AUTHORS

Alina Chertock, Charles R. Doering, Eugene Kashdan, Alexander Kurganov

ABSTRACT

The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples. More... »

PAGES

200-214

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10915-010-9381-2

DOI

http://dx.doi.org/10.1007/s10915-010-9381-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040254502


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0101", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Pure Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "North Carolina State University", 
          "id": "https://www.grid.ac/institutes/grid.40803.3f", 
          "name": [
            "Department of Mathematics, North Carolina State University, 27695, Raleigh, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chertock", 
        "givenName": "Alina", 
        "id": "sg:person.010773240620.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010773240620.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Michigan\u2013Ann Arbor", 
          "id": "https://www.grid.ac/institutes/grid.214458.e", 
          "name": [
            "Departments of Mathematics & Physics, University of Michigan, 48109-1043, Ann Arbor, MI, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Doering", 
        "givenName": "Charles R.", 
        "id": "sg:person.01161117310.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161117310.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tel Aviv University", 
          "id": "https://www.grid.ac/institutes/grid.12136.37", 
          "name": [
            "Department of Applied Mathematics, Tel Aviv University, 69978, Tel Aviv, Ramat Aviv, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kashdan", 
        "givenName": "Eugene", 
        "id": "sg:person.0643561524.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0643561524.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tulane University", 
          "id": "https://www.grid.ac/institutes/grid.265219.b", 
          "name": [
            "Department of Mathematics, Tulane University, 70118, New Orleans, LA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kurganov", 
        "givenName": "Alexander", 
        "id": "sg:person.011515614245.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011515614245.51"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1103/physreve.74.025301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000954959"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.74.025301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000954959"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1010146231", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-0713-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010146231", 
          "https://doi.org/10.1007/978-1-4612-0713-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-0713-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010146231", 
          "https://doi.org/10.1007/978-1-4612-0713-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-0427(03)00484-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015152680"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-0427(03)00484-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015152680"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-75712-2_33", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023066781", 
          "https://doi.org/10.1007/978-3-540-75712-2_33"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/num.10025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023436063"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physd.2007.05.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023507492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02512373", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025582758", 
          "https://doi.org/10.1007/bf02512373"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02512373", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025582758", 
          "https://doi.org/10.1007/bf02512373"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/fld.1355", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027873504"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1028924986", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1028924986", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1033434289", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-09017-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033434289", 
          "https://doi.org/10.1007/978-3-662-09017-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-09017-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033434289", 
          "https://doi.org/10.1007/978-3-662-09017-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0375-9601(90)90092-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036177237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0375-9601(90)90092-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036177237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0370-1573(98)00083-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037715182"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jcph.2000.6459", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039729347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9991(90)90260-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044769524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1570-8659(05)80035-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047927182"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112006008639", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053841680"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s002211208200295x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054033857"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/0705041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062850730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/0721062", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062853049"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s003614450036757x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062877731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s1064827500373413", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062883810"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s1064827501392880", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062883923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511791253", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098709967"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2010-10", 
    "datePublishedReg": "2010-10-01", 
    "description": "The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309\u2013332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10915-010-9381-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1126163", 
        "issn": [
          "0885-7474", 
          "1573-7691"
        ], 
        "name": "Journal of Scientific Computing", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1-3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "45"
      }
    ], 
    "name": "A Fast Explicit Operator Splitting Method for Passive Scalar Advection", 
    "pagination": "200-214", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bfc1d1cc15125d39021960c659016b30557beaced3cec10e263eb6a4e20fca4f"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10915-010-9381-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1040254502"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10915-010-9381-2", 
      "https://app.dimensions.ai/details/publication/pub.1040254502"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T10:31", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000349_0000000349/records_113650_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10915-010-9381-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10915-010-9381-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10915-010-9381-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10915-010-9381-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10915-010-9381-2'


 

This table displays all metadata directly associated to this object as RDF triples.

167 TRIPLES      21 PREDICATES      52 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10915-010-9381-2 schema:about anzsrc-for:01
2 anzsrc-for:0101
3 schema:author N86d4738d3e374c70975874bd0e34adc0
4 schema:citation sg:pub.10.1007/978-1-4612-0713-9
5 sg:pub.10.1007/978-3-540-75712-2_33
6 sg:pub.10.1007/978-3-662-09017-6
7 sg:pub.10.1007/bf02512373
8 https://app.dimensions.ai/details/publication/pub.1010146231
9 https://app.dimensions.ai/details/publication/pub.1028924986
10 https://app.dimensions.ai/details/publication/pub.1033434289
11 https://doi.org/10.1002/fld.1355
12 https://doi.org/10.1002/num.10025
13 https://doi.org/10.1006/jcph.2000.6459
14 https://doi.org/10.1016/0021-9991(90)90260-8
15 https://doi.org/10.1016/0375-9601(90)90092-3
16 https://doi.org/10.1016/j.physd.2007.05.001
17 https://doi.org/10.1016/s0370-1573(98)00083-0
18 https://doi.org/10.1016/s0377-0427(03)00484-9
19 https://doi.org/10.1016/s1570-8659(05)80035-3
20 https://doi.org/10.1017/cbo9780511791253
21 https://doi.org/10.1017/s0022112006008639
22 https://doi.org/10.1017/s002211208200295x
23 https://doi.org/10.1103/physreve.74.025301
24 https://doi.org/10.1137/0705041
25 https://doi.org/10.1137/0721062
26 https://doi.org/10.1137/s003614450036757x
27 https://doi.org/10.1137/s1064827500373413
28 https://doi.org/10.1137/s1064827501392880
29 schema:datePublished 2010-10
30 schema:datePublishedReg 2010-10-01
31 schema:description The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.
32 schema:genre research_article
33 schema:inLanguage en
34 schema:isAccessibleForFree true
35 schema:isPartOf N165c33f7444e4fd0abf3f4942135f885
36 N26cbc27db9a54cd180a46938a2eb9abc
37 sg:journal.1126163
38 schema:name A Fast Explicit Operator Splitting Method for Passive Scalar Advection
39 schema:pagination 200-214
40 schema:productId N720b68aab0e5471da4043de94b8ffc1a
41 Na6f8ce8a7b574e2ca0260b05084166d9
42 Ne445cea60e1647f287b518da3883ff98
43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040254502
44 https://doi.org/10.1007/s10915-010-9381-2
45 schema:sdDatePublished 2019-04-11T10:31
46 schema:sdLicense https://scigraph.springernature.com/explorer/license/
47 schema:sdPublisher N1b2e2faa5ae440c4aa4a2ad9fc86ad77
48 schema:url http://link.springer.com/10.1007%2Fs10915-010-9381-2
49 sgo:license sg:explorer/license/
50 sgo:sdDataset articles
51 rdf:type schema:ScholarlyArticle
52 N05bf1105591a4c95bbd8662de556eaed rdf:first sg:person.01161117310.79
53 rdf:rest Na9608cdae0a54c3ca0e8b4ee95a874b8
54 N165c33f7444e4fd0abf3f4942135f885 schema:issueNumber 1-3
55 rdf:type schema:PublicationIssue
56 N1b2e2faa5ae440c4aa4a2ad9fc86ad77 schema:name Springer Nature - SN SciGraph project
57 rdf:type schema:Organization
58 N26cbc27db9a54cd180a46938a2eb9abc schema:volumeNumber 45
59 rdf:type schema:PublicationVolume
60 N720b68aab0e5471da4043de94b8ffc1a schema:name doi
61 schema:value 10.1007/s10915-010-9381-2
62 rdf:type schema:PropertyValue
63 N86d4738d3e374c70975874bd0e34adc0 rdf:first sg:person.010773240620.18
64 rdf:rest N05bf1105591a4c95bbd8662de556eaed
65 Na6f8ce8a7b574e2ca0260b05084166d9 schema:name dimensions_id
66 schema:value pub.1040254502
67 rdf:type schema:PropertyValue
68 Na9608cdae0a54c3ca0e8b4ee95a874b8 rdf:first sg:person.0643561524.00
69 rdf:rest Nde77cdd378de4277bc13831b6c419b5d
70 Nde77cdd378de4277bc13831b6c419b5d rdf:first sg:person.011515614245.51
71 rdf:rest rdf:nil
72 Ne445cea60e1647f287b518da3883ff98 schema:name readcube_id
73 schema:value bfc1d1cc15125d39021960c659016b30557beaced3cec10e263eb6a4e20fca4f
74 rdf:type schema:PropertyValue
75 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
76 schema:name Mathematical Sciences
77 rdf:type schema:DefinedTerm
78 anzsrc-for:0101 schema:inDefinedTermSet anzsrc-for:
79 schema:name Pure Mathematics
80 rdf:type schema:DefinedTerm
81 sg:journal.1126163 schema:issn 0885-7474
82 1573-7691
83 schema:name Journal of Scientific Computing
84 rdf:type schema:Periodical
85 sg:person.010773240620.18 schema:affiliation https://www.grid.ac/institutes/grid.40803.3f
86 schema:familyName Chertock
87 schema:givenName Alina
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010773240620.18
89 rdf:type schema:Person
90 sg:person.011515614245.51 schema:affiliation https://www.grid.ac/institutes/grid.265219.b
91 schema:familyName Kurganov
92 schema:givenName Alexander
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011515614245.51
94 rdf:type schema:Person
95 sg:person.01161117310.79 schema:affiliation https://www.grid.ac/institutes/grid.214458.e
96 schema:familyName Doering
97 schema:givenName Charles R.
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161117310.79
99 rdf:type schema:Person
100 sg:person.0643561524.00 schema:affiliation https://www.grid.ac/institutes/grid.12136.37
101 schema:familyName Kashdan
102 schema:givenName Eugene
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0643561524.00
104 rdf:type schema:Person
105 sg:pub.10.1007/978-1-4612-0713-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010146231
106 https://doi.org/10.1007/978-1-4612-0713-9
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/978-3-540-75712-2_33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023066781
109 https://doi.org/10.1007/978-3-540-75712-2_33
110 rdf:type schema:CreativeWork
111 sg:pub.10.1007/978-3-662-09017-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033434289
112 https://doi.org/10.1007/978-3-662-09017-6
113 rdf:type schema:CreativeWork
114 sg:pub.10.1007/bf02512373 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025582758
115 https://doi.org/10.1007/bf02512373
116 rdf:type schema:CreativeWork
117 https://app.dimensions.ai/details/publication/pub.1010146231 schema:CreativeWork
118 https://app.dimensions.ai/details/publication/pub.1028924986 schema:CreativeWork
119 https://app.dimensions.ai/details/publication/pub.1033434289 schema:CreativeWork
120 https://doi.org/10.1002/fld.1355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027873504
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1002/num.10025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023436063
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1006/jcph.2000.6459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039729347
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/0021-9991(90)90260-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044769524
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/0375-9601(90)90092-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036177237
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.physd.2007.05.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023507492
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/s0370-1573(98)00083-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037715182
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/s0377-0427(03)00484-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015152680
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/s1570-8659(05)80035-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047927182
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1017/cbo9780511791253 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098709967
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1017/s0022112006008639 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053841680
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1017/s002211208200295x schema:sameAs https://app.dimensions.ai/details/publication/pub.1054033857
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1103/physreve.74.025301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000954959
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1137/0705041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062850730
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1137/0721062 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062853049
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1137/s003614450036757x schema:sameAs https://app.dimensions.ai/details/publication/pub.1062877731
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1137/s1064827500373413 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062883810
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1137/s1064827501392880 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062883923
155 rdf:type schema:CreativeWork
156 https://www.grid.ac/institutes/grid.12136.37 schema:alternateName Tel Aviv University
157 schema:name Department of Applied Mathematics, Tel Aviv University, 69978, Tel Aviv, Ramat Aviv, Israel
158 rdf:type schema:Organization
159 https://www.grid.ac/institutes/grid.214458.e schema:alternateName University of Michigan–Ann Arbor
160 schema:name Departments of Mathematics & Physics, University of Michigan, 48109-1043, Ann Arbor, MI, USA
161 rdf:type schema:Organization
162 https://www.grid.ac/institutes/grid.265219.b schema:alternateName Tulane University
163 schema:name Department of Mathematics, Tulane University, 70118, New Orleans, LA, USA
164 rdf:type schema:Organization
165 https://www.grid.ac/institutes/grid.40803.3f schema:alternateName North Carolina State University
166 schema:name Department of Mathematics, North Carolina State University, 27695, Raleigh, NC, USA
167 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...