Information-Probabilistic Approach to the Organization of a Binary Distillation Process View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-05

AUTHORS

V. A. Naletov, V. A. Kolesnikov, M. B. Glebov, A. Yu. Naletov

ABSTRACT

A systematic approach to the optimal organization of a binary distillation process based on information theory is presented. This approach allows to formulate conditions for optimal function distribution for a complex process, when the feed stream is separated into several product streams. The results of computational experiments based on this approach and known thermodynamic approaches that involve the minimization of exergy losses and entropy production are compared using a numerical example that models the separation process for a methanol–water mixture. The results of computational experiments based on the information-probabilistic approach to the optimal organization of a binary distillation process agree with results obtained by using thermodynamic approaches, evidencing the applicability of the information approach in the context of its integration into the general algorithm of chemical engineering system design based on the information approach. More... »

PAGES

410-418

References to SciGraph publications

  • 2011-10-13. Information-thermodynamic principle of the organization of chemical engineering systems in THEORETICAL FOUNDATIONS OF CHEMICAL ENGINEERING
  • 2008-08-10. Optimal organization of binary distillation in THEORETICAL FOUNDATIONS OF CHEMICAL ENGINEERING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1134/s004057951902012x

    DOI

    http://dx.doi.org/10.1134/s004057951902012x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1117484969


    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/2008/0904", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Chemical Engineering", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia", 
              "id": "http://www.grid.ac/institutes/grid.39572.3a", 
              "name": [
                "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Naletov", 
            "givenName": "V. A.", 
            "id": "sg:person.015576745360.67", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015576745360.67"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia", 
              "id": "http://www.grid.ac/institutes/grid.39572.3a", 
              "name": [
                "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kolesnikov", 
            "givenName": "V. A.", 
            "id": "sg:person.011667347513.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011667347513.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia", 
              "id": "http://www.grid.ac/institutes/grid.39572.3a", 
              "name": [
                "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Glebov", 
            "givenName": "M. B.", 
            "id": "sg:person.016025443041.98", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016025443041.98"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia", 
              "id": "http://www.grid.ac/institutes/grid.39572.3a", 
              "name": [
                "Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Naletov", 
            "givenName": "A. Yu.", 
            "id": "sg:person.014507624441.79", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014507624441.79"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1134/s0040579511050289", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044456607", 
              "https://doi.org/10.1134/s0040579511050289"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1134/s0040579508040106", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018179773", 
              "https://doi.org/10.1134/s0040579508040106"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-05", 
        "datePublishedReg": "2019-05-01", 
        "description": "A systematic approach to the optimal organization of a binary distillation process based on information theory is presented. This approach allows to formulate conditions for optimal function distribution for a complex process, when the feed stream is separated into several product streams. The results of computational experiments based on this approach and known thermodynamic approaches that involve the minimization of exergy losses and entropy production are compared using a numerical example that models the separation process for a methanol\u2013water mixture. The results of computational experiments based on the information-probabilistic approach to the optimal organization of a binary distillation process agree with results obtained by using thermodynamic approaches, evidencing the applicability of the information approach in the context of its integration into the general algorithm of chemical engineering system design based on the information approach.", 
        "genre": "article", 
        "id": "sg:pub.10.1134/s004057951902012x", 
        "inLanguage": "en", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136110", 
            "issn": [
              "0040-5795", 
              "1608-3431"
            ], 
            "name": "Theoretical Foundations of Chemical Engineering", 
            "publisher": "Pleiades Publishing", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "53"
          }
        ], 
        "keywords": [
          "binary distillation process", 
          "computational experiments", 
          "information approach", 
          "engineering systems design", 
          "system design", 
          "optimal organization", 
          "information theory", 
          "general algorithm", 
          "systematic approach", 
          "streams", 
          "algorithm", 
          "organization", 
          "complex process", 
          "integration", 
          "process", 
          "function distribution", 
          "experiments", 
          "minimization", 
          "design", 
          "applicability", 
          "results", 
          "numerical examples", 
          "example", 
          "context", 
          "distillation process", 
          "theory", 
          "exergy loss", 
          "feed stream", 
          "product stream", 
          "thermodynamic approach", 
          "separation process", 
          "distribution", 
          "methanol-water mixtures", 
          "loss", 
          "entropy production", 
          "conditions", 
          "approach", 
          "mixture", 
          "production", 
          "optimal function distribution", 
          "information-probabilistic approach", 
          "chemical engineering system design"
        ], 
        "name": "Information-Probabilistic Approach to the Organization of a Binary Distillation Process", 
        "pagination": "410-418", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1117484969"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1134/s004057951902012x"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1134/s004057951902012x", 
          "https://app.dimensions.ai/details/publication/pub.1117484969"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-01-01T18:54", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_823.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1134/s004057951902012x"
      }
    ]
     

    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.10.1134/s004057951902012x'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1134/s004057951902012x'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1134/s004057951902012x'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1134/s004057951902012x'


     

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

    129 TRIPLES      22 PREDICATES      70 URIs      60 LITERALS      6 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1134/s004057951902012x schema:about anzsrc-for:09
    2 anzsrc-for:0904
    3 schema:author Nad0561f6da5f4867a916994616aa6f2d
    4 schema:citation sg:pub.10.1134/s0040579508040106
    5 sg:pub.10.1134/s0040579511050289
    6 schema:datePublished 2019-05
    7 schema:datePublishedReg 2019-05-01
    8 schema:description A systematic approach to the optimal organization of a binary distillation process based on information theory is presented. This approach allows to formulate conditions for optimal function distribution for a complex process, when the feed stream is separated into several product streams. The results of computational experiments based on this approach and known thermodynamic approaches that involve the minimization of exergy losses and entropy production are compared using a numerical example that models the separation process for a methanol–water mixture. The results of computational experiments based on the information-probabilistic approach to the optimal organization of a binary distillation process agree with results obtained by using thermodynamic approaches, evidencing the applicability of the information approach in the context of its integration into the general algorithm of chemical engineering system design based on the information approach.
    9 schema:genre article
    10 schema:inLanguage en
    11 schema:isAccessibleForFree false
    12 schema:isPartOf N02b5db1a058346dd97131e1794e58d03
    13 N2df3767f3b3840e9af4cb70cec0007b9
    14 sg:journal.1136110
    15 schema:keywords algorithm
    16 applicability
    17 approach
    18 binary distillation process
    19 chemical engineering system design
    20 complex process
    21 computational experiments
    22 conditions
    23 context
    24 design
    25 distillation process
    26 distribution
    27 engineering systems design
    28 entropy production
    29 example
    30 exergy loss
    31 experiments
    32 feed stream
    33 function distribution
    34 general algorithm
    35 information approach
    36 information theory
    37 information-probabilistic approach
    38 integration
    39 loss
    40 methanol-water mixtures
    41 minimization
    42 mixture
    43 numerical examples
    44 optimal function distribution
    45 optimal organization
    46 organization
    47 process
    48 product stream
    49 production
    50 results
    51 separation process
    52 streams
    53 system design
    54 systematic approach
    55 theory
    56 thermodynamic approach
    57 schema:name Information-Probabilistic Approach to the Organization of a Binary Distillation Process
    58 schema:pagination 410-418
    59 schema:productId N2ca94edb8d5a404080106a55ae145290
    60 Na5c7944e7fda4c7bb75f381ee7481d3d
    61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117484969
    62 https://doi.org/10.1134/s004057951902012x
    63 schema:sdDatePublished 2022-01-01T18:54
    64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    65 schema:sdPublisher N0053d8a1cef34c53986f169b40055ec1
    66 schema:url https://doi.org/10.1134/s004057951902012x
    67 sgo:license sg:explorer/license/
    68 sgo:sdDataset articles
    69 rdf:type schema:ScholarlyArticle
    70 N0053d8a1cef34c53986f169b40055ec1 schema:name Springer Nature - SN SciGraph project
    71 rdf:type schema:Organization
    72 N02b5db1a058346dd97131e1794e58d03 schema:issueNumber 3
    73 rdf:type schema:PublicationIssue
    74 N2ca94edb8d5a404080106a55ae145290 schema:name doi
    75 schema:value 10.1134/s004057951902012x
    76 rdf:type schema:PropertyValue
    77 N2df3767f3b3840e9af4cb70cec0007b9 schema:volumeNumber 53
    78 rdf:type schema:PublicationVolume
    79 N8dd97f6c8fe3491a91eedf620074e2bc rdf:first sg:person.011667347513.40
    80 rdf:rest Na28df41039cd47bab9bdd5d8b42587b0
    81 Na28df41039cd47bab9bdd5d8b42587b0 rdf:first sg:person.016025443041.98
    82 rdf:rest Nf9d04edad6f0481fb0d415e73145569b
    83 Na5c7944e7fda4c7bb75f381ee7481d3d schema:name dimensions_id
    84 schema:value pub.1117484969
    85 rdf:type schema:PropertyValue
    86 Nad0561f6da5f4867a916994616aa6f2d rdf:first sg:person.015576745360.67
    87 rdf:rest N8dd97f6c8fe3491a91eedf620074e2bc
    88 Nf9d04edad6f0481fb0d415e73145569b rdf:first sg:person.014507624441.79
    89 rdf:rest rdf:nil
    90 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
    91 schema:name Engineering
    92 rdf:type schema:DefinedTerm
    93 anzsrc-for:0904 schema:inDefinedTermSet anzsrc-for:
    94 schema:name Chemical Engineering
    95 rdf:type schema:DefinedTerm
    96 sg:journal.1136110 schema:issn 0040-5795
    97 1608-3431
    98 schema:name Theoretical Foundations of Chemical Engineering
    99 schema:publisher Pleiades Publishing
    100 rdf:type schema:Periodical
    101 sg:person.011667347513.40 schema:affiliation grid-institutes:grid.39572.3a
    102 schema:familyName Kolesnikov
    103 schema:givenName V. A.
    104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011667347513.40
    105 rdf:type schema:Person
    106 sg:person.014507624441.79 schema:affiliation grid-institutes:grid.39572.3a
    107 schema:familyName Naletov
    108 schema:givenName A. Yu.
    109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014507624441.79
    110 rdf:type schema:Person
    111 sg:person.015576745360.67 schema:affiliation grid-institutes:grid.39572.3a
    112 schema:familyName Naletov
    113 schema:givenName V. A.
    114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015576745360.67
    115 rdf:type schema:Person
    116 sg:person.016025443041.98 schema:affiliation grid-institutes:grid.39572.3a
    117 schema:familyName Glebov
    118 schema:givenName M. B.
    119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016025443041.98
    120 rdf:type schema:Person
    121 sg:pub.10.1134/s0040579508040106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018179773
    122 https://doi.org/10.1134/s0040579508040106
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1134/s0040579511050289 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044456607
    125 https://doi.org/10.1134/s0040579511050289
    126 rdf:type schema:CreativeWork
    127 grid-institutes:grid.39572.3a schema:alternateName Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia
    128 schema:name Mendeleev Russian University of Chemical Technology, Miusskaya pl. 9, 125047, Moscow, Russia
    129 rdf:type schema:Organization
     




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


    ...