Evaluation of Drying Rates of Lignite Particles in Superheated Steam Using Single-Particle Model View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-12

AUTHORS

Tsuyoshi Kiriyama, Hideaki Sasaki, Akira Hashimoto, Shozo Kaneko, Masafumi Maeda

ABSTRACT

Drying rates of lignite particle groups in superheated steam are evaluated using a single-particle model developed for Australian lignite. Size distributions of the particles are assumed to obey the Rosin–Rammler equation with the maximum particle diameters defined as 100, 50, and 6 mm. The results show the drying rate of a lignite group depends strongly on the maximum particle size, and removal of large particles prior to drying is shown to be effective to reduce the drying time. The calculation model is available for simulations of drying behaviors of lignite in various dryers when an appropriate heat transfer coefficient is given. This study simulates the drying of particles smaller than 6 mm using a heat transfer coefficient in a fluidized bed dryer reported elsewhere. The required drying time estimated from the calculation is comparable to the processing time reported in an actual fluidized bed dryer, supporting the validity of the calculation model. More... »

PAGES

308-316

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40553-016-0096-7

DOI

http://dx.doi.org/10.1007/s40553-016-0096-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041537838


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/2008/0904", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical 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": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kiriyama", 
        "givenName": "Tsuyoshi", 
        "id": "sg:person.016205404522.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016205404522.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sasaki", 
        "givenName": "Hideaki", 
        "id": "sg:person.014477263525.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014477263525.12"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hashimoto", 
        "givenName": "Akira", 
        "id": "sg:person.07574446774.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07574446774.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kaneko", 
        "givenName": "Shozo", 
        "id": "sg:person.014213066121.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014213066121.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Maeda", 
        "givenName": "Masafumi", 
        "id": "sg:person.013442640671.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013442640671.62"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.fuel.2012.09.057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000182274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-3820(80)90019-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010750442"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-3820(80)90019-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010750442"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0016-2361(81)90035-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011484539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0016-2361(81)90035-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011484539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/07373937.2010.498070", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016672341"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/en9050371", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021976948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/apj.1722", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024545561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0016-2361(78)90189-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027653303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0016-2361(78)90189-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027653303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s40553-014-0037-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033985733", 
          "https://doi.org/10.1007/s40553-014-0037-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11431-011-4414-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041538185", 
          "https://doi.org/10.1007/s11431-011-4414-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1385-8947(01)00244-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047940965"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2320/matertrans.m-m2013817", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052798189"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.fuproc.2014.12.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053431172"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ef101198k", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055477468"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ef101198k", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055477468"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ef401649j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055479723"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "Drying rates of lignite particle groups in superheated steam are evaluated using a single-particle model developed for Australian lignite. Size distributions of the particles are assumed to obey the Rosin\u2013Rammler equation with the maximum particle diameters defined as 100, 50, and 6 mm. The results show the drying rate of a lignite group depends strongly on the maximum particle size, and removal of large particles prior to drying is shown to be effective to reduce the drying time. The calculation model is available for simulations of drying behaviors of lignite in various dryers when an appropriate heat transfer coefficient is given. This study simulates the drying of particles smaller than 6 mm using a heat transfer coefficient in a fluidized bed dryer reported elsewhere. The required drying time estimated from the calculation is comparable to the processing time reported in an actual fluidized bed dryer, supporting the validity of the calculation model.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s40553-016-0096-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136641", 
        "issn": [
          "2196-2936", 
          "2196-2944"
        ], 
        "name": "Metallurgical and Materials Transactions E", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "name": "Evaluation of Drying Rates of Lignite Particles in Superheated Steam Using Single-Particle Model", 
    "pagination": "308-316", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "c5df68939a328a04321dd8bd76d1ab3685716ce8611b863fcf043fc423517533"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s40553-016-0096-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1041537838"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s40553-016-0096-7", 
      "https://app.dimensions.ai/details/publication/pub.1041537838"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:41", 
    "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/v90/0000000363_0000000363/records_70053_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs40553-016-0096-7"
  }
]
 

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/s40553-016-0096-7'

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/s40553-016-0096-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40553-016-0096-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40553-016-0096-7'


 

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

133 TRIPLES      21 PREDICATES      41 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s40553-016-0096-7 schema:about anzsrc-for:09
2 anzsrc-for:0904
3 schema:author N6b867b49ec07496eaa20286a5db7420c
4 schema:citation sg:pub.10.1007/s11431-011-4414-0
5 sg:pub.10.1007/s40553-014-0037-2
6 https://doi.org/10.1002/apj.1722
7 https://doi.org/10.1016/0016-2361(78)90189-8
8 https://doi.org/10.1016/0016-2361(81)90035-1
9 https://doi.org/10.1016/0378-3820(80)90019-3
10 https://doi.org/10.1016/j.fuel.2012.09.057
11 https://doi.org/10.1016/j.fuproc.2014.12.005
12 https://doi.org/10.1016/s1385-8947(01)00244-3
13 https://doi.org/10.1021/ef101198k
14 https://doi.org/10.1021/ef401649j
15 https://doi.org/10.1080/07373937.2010.498070
16 https://doi.org/10.2320/matertrans.m-m2013817
17 https://doi.org/10.3390/en9050371
18 schema:datePublished 2016-12
19 schema:datePublishedReg 2016-12-01
20 schema:description Drying rates of lignite particle groups in superheated steam are evaluated using a single-particle model developed for Australian lignite. Size distributions of the particles are assumed to obey the Rosin–Rammler equation with the maximum particle diameters defined as 100, 50, and 6 mm. The results show the drying rate of a lignite group depends strongly on the maximum particle size, and removal of large particles prior to drying is shown to be effective to reduce the drying time. The calculation model is available for simulations of drying behaviors of lignite in various dryers when an appropriate heat transfer coefficient is given. This study simulates the drying of particles smaller than 6 mm using a heat transfer coefficient in a fluidized bed dryer reported elsewhere. The required drying time estimated from the calculation is comparable to the processing time reported in an actual fluidized bed dryer, supporting the validity of the calculation model.
21 schema:genre research_article
22 schema:inLanguage en
23 schema:isAccessibleForFree false
24 schema:isPartOf N36fc865de3c649a9be8194323b88f132
25 Nada1f20bccef40cba41f3be740b56bb4
26 sg:journal.1136641
27 schema:name Evaluation of Drying Rates of Lignite Particles in Superheated Steam Using Single-Particle Model
28 schema:pagination 308-316
29 schema:productId N9ab7a1c59e194eb9b7472a37048134a3
30 N9fee1a6135284b0e8be087913917f5b4
31 Nfd2e89a0be9f4df287481c648dbd772d
32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041537838
33 https://doi.org/10.1007/s40553-016-0096-7
34 schema:sdDatePublished 2019-04-11T12:41
35 schema:sdLicense https://scigraph.springernature.com/explorer/license/
36 schema:sdPublisher Nb990b4ab65ca4d4aa5dc212f3e5d8258
37 schema:url https://link.springer.com/10.1007%2Fs40553-016-0096-7
38 sgo:license sg:explorer/license/
39 sgo:sdDataset articles
40 rdf:type schema:ScholarlyArticle
41 N056d5917c2944af1879161211ea48642 rdf:first sg:person.014213066121.37
42 rdf:rest Nab8de824c6f9428499110158311cc522
43 N36fc865de3c649a9be8194323b88f132 schema:volumeNumber 3
44 rdf:type schema:PublicationVolume
45 N6b867b49ec07496eaa20286a5db7420c rdf:first sg:person.016205404522.24
46 rdf:rest Nd493f68cc5c445c5b4160dbffcf44bb4
47 N9ab7a1c59e194eb9b7472a37048134a3 schema:name readcube_id
48 schema:value c5df68939a328a04321dd8bd76d1ab3685716ce8611b863fcf043fc423517533
49 rdf:type schema:PropertyValue
50 N9fee1a6135284b0e8be087913917f5b4 schema:name dimensions_id
51 schema:value pub.1041537838
52 rdf:type schema:PropertyValue
53 Nab8de824c6f9428499110158311cc522 rdf:first sg:person.013442640671.62
54 rdf:rest rdf:nil
55 Nada1f20bccef40cba41f3be740b56bb4 schema:issueNumber 4
56 rdf:type schema:PublicationIssue
57 Nb990b4ab65ca4d4aa5dc212f3e5d8258 schema:name Springer Nature - SN SciGraph project
58 rdf:type schema:Organization
59 Nd493f68cc5c445c5b4160dbffcf44bb4 rdf:first sg:person.014477263525.12
60 rdf:rest Ne2599cda6f3b442bb37a94db26aeee8f
61 Ne2599cda6f3b442bb37a94db26aeee8f rdf:first sg:person.07574446774.07
62 rdf:rest N056d5917c2944af1879161211ea48642
63 Nfd2e89a0be9f4df287481c648dbd772d schema:name doi
64 schema:value 10.1007/s40553-016-0096-7
65 rdf:type schema:PropertyValue
66 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
67 schema:name Engineering
68 rdf:type schema:DefinedTerm
69 anzsrc-for:0904 schema:inDefinedTermSet anzsrc-for:
70 schema:name Chemical Engineering
71 rdf:type schema:DefinedTerm
72 sg:journal.1136641 schema:issn 2196-2936
73 2196-2944
74 schema:name Metallurgical and Materials Transactions E
75 rdf:type schema:Periodical
76 sg:person.013442640671.62 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
77 schema:familyName Maeda
78 schema:givenName Masafumi
79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013442640671.62
80 rdf:type schema:Person
81 sg:person.014213066121.37 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
82 schema:familyName Kaneko
83 schema:givenName Shozo
84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014213066121.37
85 rdf:type schema:Person
86 sg:person.014477263525.12 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
87 schema:familyName Sasaki
88 schema:givenName Hideaki
89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014477263525.12
90 rdf:type schema:Person
91 sg:person.016205404522.24 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
92 schema:familyName Kiriyama
93 schema:givenName Tsuyoshi
94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016205404522.24
95 rdf:type schema:Person
96 sg:person.07574446774.07 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
97 schema:familyName Hashimoto
98 schema:givenName Akira
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07574446774.07
100 rdf:type schema:Person
101 sg:pub.10.1007/s11431-011-4414-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041538185
102 https://doi.org/10.1007/s11431-011-4414-0
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/s40553-014-0037-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033985733
105 https://doi.org/10.1007/s40553-014-0037-2
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1002/apj.1722 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024545561
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/0016-2361(78)90189-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027653303
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/0016-2361(81)90035-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011484539
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/0378-3820(80)90019-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010750442
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.fuel.2012.09.057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000182274
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/j.fuproc.2014.12.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053431172
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/s1385-8947(01)00244-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047940965
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1021/ef101198k schema:sameAs https://app.dimensions.ai/details/publication/pub.1055477468
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1021/ef401649j schema:sameAs https://app.dimensions.ai/details/publication/pub.1055479723
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1080/07373937.2010.498070 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016672341
126 rdf:type schema:CreativeWork
127 https://doi.org/10.2320/matertrans.m-m2013817 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052798189
128 rdf:type schema:CreativeWork
129 https://doi.org/10.3390/en9050371 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021976948
130 rdf:type schema:CreativeWork
131 https://www.grid.ac/institutes/grid.26999.3d schema:alternateName University of Tokyo
132 schema:name Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan
133 rdf:type schema:Organization
 




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


...