Case-Study Inverse Thermal Analyses of Al2139 Laser Welds View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-05-18

AUTHORS

A. D. Zervaki, G. N. Haidemenopoulos, D. P. Vriami, S. G. Lambrakos

ABSTRACT

Case study inverse thermal analyses of A12139 laser welds are presented. These analyses employ a numerical methodology that is in terms of analytic and numerical basis functions for inverse thermal analysis of steady state energy deposition in plate structures. The results of the case studies presented provide parametric representations of weld temperature histories that can be adopted as input data to various types of computational procedures, such as those for prediction of solid-state phase transformations and their associated software implementations. In addition, these weld temperature histories will be useful for construction of numerical basis functions that can be adopted for inverse analysis of welds corresponding to other process parameters or welding processes whose process conditions are within similar regimes. More... »

PAGES

777-785

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11665-011-9968-2

DOI

http://dx.doi.org/10.1007/s11665-011-9968-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028331124


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/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0910", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Manufacturing Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece", 
          "id": "http://www.grid.ac/institutes/grid.410558.d", 
          "name": [
            "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zervaki", 
        "givenName": "A. D.", 
        "id": "sg:person.07420163560.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07420163560.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece", 
          "id": "http://www.grid.ac/institutes/grid.410558.d", 
          "name": [
            "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Haidemenopoulos", 
        "givenName": "G. N.", 
        "id": "sg:person.015521222033.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015521222033.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece", 
          "id": "http://www.grid.ac/institutes/grid.410558.d", 
          "name": [
            "Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vriami", 
        "givenName": "D. P.", 
        "id": "sg:person.012344701671.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012344701671.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Center for Computational Materials, Code 6390, Materials Science and Technology Division, Naval Research Laboratory, Washington, DC, USA", 
          "id": "http://www.grid.ac/institutes/grid.89170.37", 
          "name": [
            "Center for Computational Materials, Code 6390, Materials Science and Technology Division, Naval Research Laboratory, Washington, DC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lambrakos", 
        "givenName": "S. G.", 
        "id": "sg:person.015722475453.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015722475453.27"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2011-05-18", 
    "datePublishedReg": "2011-05-18", 
    "description": "Case study inverse thermal analyses of A12139 laser welds are presented. These analyses employ a numerical methodology that is in terms of analytic and numerical basis functions for inverse thermal analysis of steady state energy deposition in plate structures. The results of the case studies presented provide parametric representations of weld temperature histories that can be adopted as input data to various types of computational procedures, such as those for prediction of solid-state phase transformations and their associated software implementations. In addition, these weld temperature histories will be useful for construction of numerical basis functions that can be adopted for inverse analysis of welds corresponding to other process parameters or welding processes whose process conditions are within similar regimes.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s11665-011-9968-2", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1042007", 
        "issn": [
          "1059-9495", 
          "1544-1024"
        ], 
        "name": "Journal of Materials Engineering and Performance", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "21"
      }
    ], 
    "keywords": [
      "inverse thermal analysis", 
      "Case study inverse thermal analyses", 
      "weld temperature histories", 
      "laser welds", 
      "thermal analysis", 
      "temperature history", 
      "steady-state energy deposition", 
      "solid-state phase transformation", 
      "welding process", 
      "process parameters", 
      "numerical methodology", 
      "plate structures", 
      "process conditions", 
      "inverse analysis", 
      "welds", 
      "phase transformation", 
      "energy deposition", 
      "basis functions", 
      "computational procedure", 
      "numerical basis functions", 
      "input data", 
      "parametric representation", 
      "similar regimes", 
      "deposition", 
      "software implementation", 
      "case study", 
      "parameters", 
      "prediction", 
      "analysis", 
      "structure", 
      "regime", 
      "process", 
      "conditions", 
      "construction", 
      "methodology", 
      "implementation", 
      "results", 
      "addition", 
      "terms", 
      "transformation", 
      "function", 
      "procedure", 
      "types", 
      "data", 
      "study", 
      "representation", 
      "history"
    ], 
    "name": "Case-Study Inverse Thermal Analyses of Al2139 Laser Welds", 
    "pagination": "777-785", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1028331124"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11665-011-9968-2"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11665-011-9968-2", 
      "https://app.dimensions.ai/details/publication/pub.1028331124"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-11-24T20:54", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/article/article_540.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s11665-011-9968-2"
  }
]
 

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/s11665-011-9968-2'

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/s11665-011-9968-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11665-011-9968-2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11665-011-9968-2'


 

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

128 TRIPLES      20 PREDICATES      71 URIs      63 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11665-011-9968-2 schema:about anzsrc-for:09
2 anzsrc-for:0910
3 schema:author N603a33001bc04c1fb04421834173ba6e
4 schema:datePublished 2011-05-18
5 schema:datePublishedReg 2011-05-18
6 schema:description Case study inverse thermal analyses of A12139 laser welds are presented. These analyses employ a numerical methodology that is in terms of analytic and numerical basis functions for inverse thermal analysis of steady state energy deposition in plate structures. The results of the case studies presented provide parametric representations of weld temperature histories that can be adopted as input data to various types of computational procedures, such as those for prediction of solid-state phase transformations and their associated software implementations. In addition, these weld temperature histories will be useful for construction of numerical basis functions that can be adopted for inverse analysis of welds corresponding to other process parameters or welding processes whose process conditions are within similar regimes.
7 schema:genre article
8 schema:isAccessibleForFree false
9 schema:isPartOf N350799cf51b1436687e4ce18ebf22b6d
10 N38da9bd4f76948ff8d7ae2eb40bb09c7
11 sg:journal.1042007
12 schema:keywords Case study inverse thermal analyses
13 addition
14 analysis
15 basis functions
16 case study
17 computational procedure
18 conditions
19 construction
20 data
21 deposition
22 energy deposition
23 function
24 history
25 implementation
26 input data
27 inverse analysis
28 inverse thermal analysis
29 laser welds
30 methodology
31 numerical basis functions
32 numerical methodology
33 parameters
34 parametric representation
35 phase transformation
36 plate structures
37 prediction
38 procedure
39 process
40 process conditions
41 process parameters
42 regime
43 representation
44 results
45 similar regimes
46 software implementation
47 solid-state phase transformation
48 steady-state energy deposition
49 structure
50 study
51 temperature history
52 terms
53 thermal analysis
54 transformation
55 types
56 weld temperature histories
57 welding process
58 welds
59 schema:name Case-Study Inverse Thermal Analyses of Al2139 Laser Welds
60 schema:pagination 777-785
61 schema:productId N74aef05a806b447192f5342377811df1
62 Nc061630f0b9344ffb7b4356913a76153
63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028331124
64 https://doi.org/10.1007/s11665-011-9968-2
65 schema:sdDatePublished 2022-11-24T20:54
66 schema:sdLicense https://scigraph.springernature.com/explorer/license/
67 schema:sdPublisher Nac778a00c3554ac8956442174989bce6
68 schema:url https://doi.org/10.1007/s11665-011-9968-2
69 sgo:license sg:explorer/license/
70 sgo:sdDataset articles
71 rdf:type schema:ScholarlyArticle
72 N0a7f5b958b5f4574a84dd04c1c2ddc78 rdf:first sg:person.015722475453.27
73 rdf:rest rdf:nil
74 N2a6236aee5a64b7baf5e819dcb10db0f rdf:first sg:person.015521222033.93
75 rdf:rest N5f5c282bec4d47208ad54a2fefdef34d
76 N350799cf51b1436687e4ce18ebf22b6d schema:issueNumber 6
77 rdf:type schema:PublicationIssue
78 N38da9bd4f76948ff8d7ae2eb40bb09c7 schema:volumeNumber 21
79 rdf:type schema:PublicationVolume
80 N5f5c282bec4d47208ad54a2fefdef34d rdf:first sg:person.012344701671.92
81 rdf:rest N0a7f5b958b5f4574a84dd04c1c2ddc78
82 N603a33001bc04c1fb04421834173ba6e rdf:first sg:person.07420163560.19
83 rdf:rest N2a6236aee5a64b7baf5e819dcb10db0f
84 N74aef05a806b447192f5342377811df1 schema:name dimensions_id
85 schema:value pub.1028331124
86 rdf:type schema:PropertyValue
87 Nac778a00c3554ac8956442174989bce6 schema:name Springer Nature - SN SciGraph project
88 rdf:type schema:Organization
89 Nc061630f0b9344ffb7b4356913a76153 schema:name doi
90 schema:value 10.1007/s11665-011-9968-2
91 rdf:type schema:PropertyValue
92 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
93 schema:name Engineering
94 rdf:type schema:DefinedTerm
95 anzsrc-for:0910 schema:inDefinedTermSet anzsrc-for:
96 schema:name Manufacturing Engineering
97 rdf:type schema:DefinedTerm
98 sg:journal.1042007 schema:issn 1059-9495
99 1544-1024
100 schema:name Journal of Materials Engineering and Performance
101 schema:publisher Springer Nature
102 rdf:type schema:Periodical
103 sg:person.012344701671.92 schema:affiliation grid-institutes:grid.410558.d
104 schema:familyName Vriami
105 schema:givenName D. P.
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012344701671.92
107 rdf:type schema:Person
108 sg:person.015521222033.93 schema:affiliation grid-institutes:grid.410558.d
109 schema:familyName Haidemenopoulos
110 schema:givenName G. N.
111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015521222033.93
112 rdf:type schema:Person
113 sg:person.015722475453.27 schema:affiliation grid-institutes:grid.89170.37
114 schema:familyName Lambrakos
115 schema:givenName S. G.
116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015722475453.27
117 rdf:type schema:Person
118 sg:person.07420163560.19 schema:affiliation grid-institutes:grid.410558.d
119 schema:familyName Zervaki
120 schema:givenName A. D.
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07420163560.19
122 rdf:type schema:Person
123 grid-institutes:grid.410558.d schema:alternateName Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece
124 schema:name Department of Mechanical Engineering, University of Thessaly, 38334, Volos, Greece
125 rdf:type schema:Organization
126 grid-institutes:grid.89170.37 schema:alternateName Center for Computational Materials, Code 6390, Materials Science and Technology Division, Naval Research Laboratory, Washington, DC, USA
127 schema:name Center for Computational Materials, Code 6390, Materials Science and Technology Division, Naval Research Laboratory, Washington, DC, USA
128 rdf:type schema:Organization
 




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


...