Electrical Discharge Machining Performance of Deep Cryogenically Treated Inconel 825 Superalloy: Emphasis on Surface Integrity View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Rahul, Saurav Datta

ABSTRACT

Electrical discharge machining performance of deep cryogenically treated Inconel 825 superalloy was assessed and compared to that of normal workpiece. Machining performance was evaluated in purview of surface integrity which articulated studies on morphology and topography of the EDMed surface. Severity of surface cracking was found relatively less on the machined specimen of cryogenically treated workpiece (CTW) while comparing non-treated workpiece. Moreover, machined specimen of CTW exhibited formation of tiny white layer. Other topographical measures including material migration, surface residual stress, and micro-indentation hardness of the machined specimen were analyzed. Effects of cryogenic treatment of the workpiece followed by EDM operation were discussed emphasizing on metallurgical aspects of the machined surface. Moreover, effects of cooling rate set for the cryogenic treatment cycle were also investigated on influencing EDM performance of CTW. More... »

PAGES

212-225

References to SciGraph publications

  • 2015-07. Parametric modeling and optimization for wire electrical discharge machining of Inconel 718 using response surface methodology in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2018-09. Effects of Tool Electrode on EDM Performance of Ti-6Al-4V in SILICON
  • 2009-12. Reducing electrode wear ratio using cryogenic cooling during electrical discharge machining in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2013-11. Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relational analysis in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2018-03. Surface integrity after post processing of EDM processed Inconel 718 shaft in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2017-07. Investigating surface properties of cryogenically treated titanium alloys in powder mixed electric discharge machining in JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
  • 2017-04. Surface integrity of Inconel 718 in high-speed electrical discharge machining milling using air dielectric in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2014-07. A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys in JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
  • 2017-12. Single and multiobjective optimization of Inconel 718 nickel-based superalloy in the wire electrical discharge machining in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • 2008-06. In situ high temperature XRD studies of ZnO nanopowder prepared via cost effective ultrasonic mist chemical vapour deposition in BULLETIN OF MATERIALS SCIENCE
  • 2013-05. Optimization of micro-EDM drilling of inconel 718 superalloy in THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s13632-019-00519-2

    DOI

    http://dx.doi.org/10.1007/s13632-019-00519-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111642622


    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/2008/0912", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Materials Engineering", 
            "type": "DefinedTerm"
          }, 
          {
            "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"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "KIIT University", 
              "id": "https://www.grid.ac/institutes/grid.412122.6", 
              "name": [
                "School of Mechanical Sciences, Kalinga Institute of Industrial Technology, 751024, Bhubaneswar, Odisha, India"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rahul", 
            "id": "sg:person.010565047463.32", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010565047463.32"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Department of Mechanical Engineering, National Institute of Technology, 769008, Rourkela, Odisha, India"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Datta", 
            "givenName": "Saurav", 
            "id": "sg:person.011551655057.01", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011551655057.01"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00170-012-4385-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000759574", 
              "https://doi.org/10.1007/s00170-012-4385-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s1003-6326(13)62513-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001170202"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-009-2060-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001176427", 
              "https://doi.org/10.1007/s00170-009-2060-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-009-2060-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001176427", 
              "https://doi.org/10.1007/s00170-009-2060-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-009-2060-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001176427", 
              "https://doi.org/10.1007/s00170-009-2060-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-016-9332-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001872170", 
              "https://doi.org/10.1007/s00170-016-9332-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-016-9332-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001872170", 
              "https://doi.org/10.1007/s00170-016-9332-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/09500830802380788", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002973139"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426914.2013.852213", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006081019"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426911003720862", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008031632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4236/csta.2014.31001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010888003"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.matdes.2008.11.016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010931242"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0924-0136(97)00429-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014761462"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.procir.2016.02.053", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015910769"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-013-5081-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022310714", 
              "https://doi.org/10.1007/s00170-013-5081-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426910701524626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024400458"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40430-016-0639-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027755871", 
              "https://doi.org/10.1007/s40430-016-0639-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40430-016-0639-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027755871", 
              "https://doi.org/10.1007/s40430-016-0639-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12034-008-0089-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029449660", 
              "https://doi.org/10.1007/s12034-008-0089-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cryogenics.2005.10.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031659531"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426914.2014.973579", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034444455"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12206-014-0637-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035472385", 
              "https://doi.org/10.1007/s12206-014-0637-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426910701235934", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036810721"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.msea.2009.01.061", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039433334"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/10426910903179914", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040047485"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s1644-9665(12)60180-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042286799"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apsusc.2006.04.063", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043146071"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijmachtools.2005.02.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046971856"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-015-6797-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048572351", 
              "https://doi.org/10.1007/s00170-015-6797-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.proeng.2011.11.108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051452390"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/0954408915593875", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1063886664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/0954408915593875", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1063886664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1464420714565432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064006428"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1464420714565432", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064006428"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.18052/www.scipress.com/ilcpa.41.100", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068563745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jmapro.2017.02.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084089324"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.wear.2017.01.067", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090364738"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-017-0758-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090653823", 
              "https://doi.org/10.1007/s00170-017-0758-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-017-0758-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090653823", 
              "https://doi.org/10.1007/s00170-017-0758-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1115/msec2009-84247", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092815058"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00170-017-1342-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092890104", 
              "https://doi.org/10.1007/s00170-017-1342-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.4712089", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098545741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12633-018-9760-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103763579", 
              "https://doi.org/10.1007/s12633-018-9760-0"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-04", 
        "datePublishedReg": "2019-04-01", 
        "description": "Electrical discharge machining performance of deep cryogenically treated Inconel 825 superalloy was assessed and compared to that of normal workpiece. Machining performance was evaluated in purview of surface integrity which articulated studies on morphology and topography of the EDMed surface. Severity of surface cracking was found relatively less on the machined specimen of cryogenically treated workpiece (CTW) while comparing non-treated workpiece. Moreover, machined specimen of CTW exhibited formation of tiny white layer. Other topographical measures including material migration, surface residual stress, and micro-indentation hardness of the machined specimen were analyzed. Effects of cryogenic treatment of the workpiece followed by EDM operation were discussed emphasizing on metallurgical aspects of the machined surface. Moreover, effects of cooling rate set for the cryogenic treatment cycle were also investigated on influencing EDM performance of CTW.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s13632-019-00519-2", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136434", 
            "issn": [
              "2192-9262", 
              "2192-9270"
            ], 
            "name": "Metallography, Microstructure, and Analysis", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "2", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "8"
          }
        ], 
        "name": "Electrical Discharge Machining Performance of Deep Cryogenically Treated Inconel 825 Superalloy: Emphasis on Surface Integrity", 
        "pagination": "212-225", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "646c89372ba9ad6bf3e459062ae070d0c25c283b733d04a388cb8f2620318447"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s13632-019-00519-2"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1111642622"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s13632-019-00519-2", 
          "https://app.dimensions.ai/details/publication/pub.1111642622"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:04", 
        "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/v90/0000000366_0000000366/records_112042_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs13632-019-00519-2"
      }
    ]
     

    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/s13632-019-00519-2'

    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/s13632-019-00519-2'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13632-019-00519-2'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13632-019-00519-2'


     

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

    188 TRIPLES      21 PREDICATES      63 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s13632-019-00519-2 schema:about anzsrc-for:09
    2 anzsrc-for:0912
    3 schema:author Nf2ad246b71034086849a502823edb74c
    4 schema:citation sg:pub.10.1007/s00170-009-2060-5
    5 sg:pub.10.1007/s00170-012-4385-8
    6 sg:pub.10.1007/s00170-013-5081-z
    7 sg:pub.10.1007/s00170-015-6797-8
    8 sg:pub.10.1007/s00170-016-9332-7
    9 sg:pub.10.1007/s00170-017-0758-3
    10 sg:pub.10.1007/s00170-017-1342-6
    11 sg:pub.10.1007/s12034-008-0089-y
    12 sg:pub.10.1007/s12206-014-0637-x
    13 sg:pub.10.1007/s12633-018-9760-0
    14 sg:pub.10.1007/s40430-016-0639-y
    15 https://doi.org/10.1016/j.apsusc.2006.04.063
    16 https://doi.org/10.1016/j.cryogenics.2005.10.004
    17 https://doi.org/10.1016/j.ijmachtools.2005.02.003
    18 https://doi.org/10.1016/j.jmapro.2017.02.020
    19 https://doi.org/10.1016/j.matdes.2008.11.016
    20 https://doi.org/10.1016/j.msea.2009.01.061
    21 https://doi.org/10.1016/j.procir.2016.02.053
    22 https://doi.org/10.1016/j.proeng.2011.11.108
    23 https://doi.org/10.1016/j.wear.2017.01.067
    24 https://doi.org/10.1016/s0924-0136(97)00429-9
    25 https://doi.org/10.1016/s1003-6326(13)62513-3
    26 https://doi.org/10.1016/s1644-9665(12)60180-0
    27 https://doi.org/10.1063/1.4712089
    28 https://doi.org/10.1080/09500830802380788
    29 https://doi.org/10.1080/10426910701235934
    30 https://doi.org/10.1080/10426910701524626
    31 https://doi.org/10.1080/10426910903179914
    32 https://doi.org/10.1080/10426911003720862
    33 https://doi.org/10.1080/10426914.2013.852213
    34 https://doi.org/10.1080/10426914.2014.973579
    35 https://doi.org/10.1115/msec2009-84247
    36 https://doi.org/10.1177/0954408915593875
    37 https://doi.org/10.1177/1464420714565432
    38 https://doi.org/10.18052/www.scipress.com/ilcpa.41.100
    39 https://doi.org/10.4236/csta.2014.31001
    40 schema:datePublished 2019-04
    41 schema:datePublishedReg 2019-04-01
    42 schema:description Electrical discharge machining performance of deep cryogenically treated Inconel 825 superalloy was assessed and compared to that of normal workpiece. Machining performance was evaluated in purview of surface integrity which articulated studies on morphology and topography of the EDMed surface. Severity of surface cracking was found relatively less on the machined specimen of cryogenically treated workpiece (CTW) while comparing non-treated workpiece. Moreover, machined specimen of CTW exhibited formation of tiny white layer. Other topographical measures including material migration, surface residual stress, and micro-indentation hardness of the machined specimen were analyzed. Effects of cryogenic treatment of the workpiece followed by EDM operation were discussed emphasizing on metallurgical aspects of the machined surface. Moreover, effects of cooling rate set for the cryogenic treatment cycle were also investigated on influencing EDM performance of CTW.
    43 schema:genre research_article
    44 schema:inLanguage en
    45 schema:isAccessibleForFree false
    46 schema:isPartOf N302f190df1e245b5a2daad1a24812336
    47 N8de41d1727da418d8a8b14e2dad7a982
    48 sg:journal.1136434
    49 schema:name Electrical Discharge Machining Performance of Deep Cryogenically Treated Inconel 825 Superalloy: Emphasis on Surface Integrity
    50 schema:pagination 212-225
    51 schema:productId N68f373c32ea1475ba03e5f9db024f6fd
    52 Na86e4eca572946d69429546e3b9e6a13
    53 Nf628092c0f5749ed87cb825cd815a90c
    54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111642622
    55 https://doi.org/10.1007/s13632-019-00519-2
    56 schema:sdDatePublished 2019-04-11T13:04
    57 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    58 schema:sdPublisher N5b0d72969eeb4d6b847e79893bfa2890
    59 schema:url https://link.springer.com/10.1007%2Fs13632-019-00519-2
    60 sgo:license sg:explorer/license/
    61 sgo:sdDataset articles
    62 rdf:type schema:ScholarlyArticle
    63 N050eb5e6ac4f4c1cac2d610691989079 rdf:first sg:person.011551655057.01
    64 rdf:rest rdf:nil
    65 N302f190df1e245b5a2daad1a24812336 schema:volumeNumber 8
    66 rdf:type schema:PublicationVolume
    67 N5b0d72969eeb4d6b847e79893bfa2890 schema:name Springer Nature - SN SciGraph project
    68 rdf:type schema:Organization
    69 N68f373c32ea1475ba03e5f9db024f6fd schema:name dimensions_id
    70 schema:value pub.1111642622
    71 rdf:type schema:PropertyValue
    72 N74b2b42f399240c5b06d174dc0c65baf schema:name Department of Mechanical Engineering, National Institute of Technology, 769008, Rourkela, Odisha, India
    73 rdf:type schema:Organization
    74 N8de41d1727da418d8a8b14e2dad7a982 schema:issueNumber 2
    75 rdf:type schema:PublicationIssue
    76 Na86e4eca572946d69429546e3b9e6a13 schema:name doi
    77 schema:value 10.1007/s13632-019-00519-2
    78 rdf:type schema:PropertyValue
    79 Nf2ad246b71034086849a502823edb74c rdf:first sg:person.010565047463.32
    80 rdf:rest N050eb5e6ac4f4c1cac2d610691989079
    81 Nf628092c0f5749ed87cb825cd815a90c schema:name readcube_id
    82 schema:value 646c89372ba9ad6bf3e459062ae070d0c25c283b733d04a388cb8f2620318447
    83 rdf:type schema:PropertyValue
    84 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
    85 schema:name Engineering
    86 rdf:type schema:DefinedTerm
    87 anzsrc-for:0912 schema:inDefinedTermSet anzsrc-for:
    88 schema:name Materials Engineering
    89 rdf:type schema:DefinedTerm
    90 sg:journal.1136434 schema:issn 2192-9262
    91 2192-9270
    92 schema:name Metallography, Microstructure, and Analysis
    93 rdf:type schema:Periodical
    94 sg:person.010565047463.32 schema:affiliation https://www.grid.ac/institutes/grid.412122.6
    95 schema:familyName Rahul
    96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010565047463.32
    97 rdf:type schema:Person
    98 sg:person.011551655057.01 schema:affiliation N74b2b42f399240c5b06d174dc0c65baf
    99 schema:familyName Datta
    100 schema:givenName Saurav
    101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011551655057.01
    102 rdf:type schema:Person
    103 sg:pub.10.1007/s00170-009-2060-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001176427
    104 https://doi.org/10.1007/s00170-009-2060-5
    105 rdf:type schema:CreativeWork
    106 sg:pub.10.1007/s00170-012-4385-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000759574
    107 https://doi.org/10.1007/s00170-012-4385-8
    108 rdf:type schema:CreativeWork
    109 sg:pub.10.1007/s00170-013-5081-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1022310714
    110 https://doi.org/10.1007/s00170-013-5081-z
    111 rdf:type schema:CreativeWork
    112 sg:pub.10.1007/s00170-015-6797-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048572351
    113 https://doi.org/10.1007/s00170-015-6797-8
    114 rdf:type schema:CreativeWork
    115 sg:pub.10.1007/s00170-016-9332-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001872170
    116 https://doi.org/10.1007/s00170-016-9332-7
    117 rdf:type schema:CreativeWork
    118 sg:pub.10.1007/s00170-017-0758-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090653823
    119 https://doi.org/10.1007/s00170-017-0758-3
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/s00170-017-1342-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092890104
    122 https://doi.org/10.1007/s00170-017-1342-6
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/s12034-008-0089-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1029449660
    125 https://doi.org/10.1007/s12034-008-0089-y
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/s12206-014-0637-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035472385
    128 https://doi.org/10.1007/s12206-014-0637-x
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s12633-018-9760-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103763579
    131 https://doi.org/10.1007/s12633-018-9760-0
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/s40430-016-0639-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1027755871
    134 https://doi.org/10.1007/s40430-016-0639-y
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.1016/j.apsusc.2006.04.063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043146071
    137 rdf:type schema:CreativeWork
    138 https://doi.org/10.1016/j.cryogenics.2005.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031659531
    139 rdf:type schema:CreativeWork
    140 https://doi.org/10.1016/j.ijmachtools.2005.02.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046971856
    141 rdf:type schema:CreativeWork
    142 https://doi.org/10.1016/j.jmapro.2017.02.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084089324
    143 rdf:type schema:CreativeWork
    144 https://doi.org/10.1016/j.matdes.2008.11.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010931242
    145 rdf:type schema:CreativeWork
    146 https://doi.org/10.1016/j.msea.2009.01.061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039433334
    147 rdf:type schema:CreativeWork
    148 https://doi.org/10.1016/j.procir.2016.02.053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015910769
    149 rdf:type schema:CreativeWork
    150 https://doi.org/10.1016/j.proeng.2011.11.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051452390
    151 rdf:type schema:CreativeWork
    152 https://doi.org/10.1016/j.wear.2017.01.067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090364738
    153 rdf:type schema:CreativeWork
    154 https://doi.org/10.1016/s0924-0136(97)00429-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014761462
    155 rdf:type schema:CreativeWork
    156 https://doi.org/10.1016/s1003-6326(13)62513-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001170202
    157 rdf:type schema:CreativeWork
    158 https://doi.org/10.1016/s1644-9665(12)60180-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042286799
    159 rdf:type schema:CreativeWork
    160 https://doi.org/10.1063/1.4712089 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098545741
    161 rdf:type schema:CreativeWork
    162 https://doi.org/10.1080/09500830802380788 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002973139
    163 rdf:type schema:CreativeWork
    164 https://doi.org/10.1080/10426910701235934 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036810721
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1080/10426910701524626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024400458
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1080/10426910903179914 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040047485
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1080/10426911003720862 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008031632
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1080/10426914.2013.852213 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006081019
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.1080/10426914.2014.973579 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034444455
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.1115/msec2009-84247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092815058
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.1177/0954408915593875 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063886664
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.1177/1464420714565432 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064006428
    181 rdf:type schema:CreativeWork
    182 https://doi.org/10.18052/www.scipress.com/ilcpa.41.100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068563745
    183 rdf:type schema:CreativeWork
    184 https://doi.org/10.4236/csta.2014.31001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010888003
    185 rdf:type schema:CreativeWork
    186 https://www.grid.ac/institutes/grid.412122.6 schema:alternateName KIIT University
    187 schema:name School of Mechanical Sciences, Kalinga Institute of Industrial Technology, 751024, Bhubaneswar, Odisha, India
    188 rdf:type schema:Organization
     




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


    ...