On the Physical Interpretation of Complexity Criteria for Optimal System Organization in the Chemical Industry View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

V. A. Naletov

ABSTRACT

The criteria of system complexity are physically interpreted for the problem of optimal process organization in chemical engineering. To that end, optimization by means of a thermoeconomic approach using undetermined Lagrange multipliers is considered. The Lagrange multipliers obtained characterize the complexity of the system and represent the unit exergy cost of intermediate streams or product streams, which by definition must be minimized. The Lagrange multipliers obtained by applying the information approach to optimal system organization also characterize its complexity. By analogy, it may be supposed that they reflect the unit information cost of intermediate streams or the product streams similar to thermoeconomic criteria. It was shown that thermoeconomic complexity criteria cannot be used in practice on account of various fundamental limitations. Conversely, information complexity criteria are of practical value since all the characteristics present depend solely on process operating parameters. Decreasing the unit information cost is viewed as a tradeoff between the possibility of additional energy reserves in the system, on the one hand, and the costs of organizing energy production processes, on the other. Accordingly, these criteria may be regarded as hybrid, analogously to thermoeconomic criteria. More... »

PAGES

107-112

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.3103/s1068364x19030050

DOI

http://dx.doi.org/10.3103/s1068364x19030050

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117482146


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 Chemical-Technology University, Moscow, Russia", 
          "id": "http://www.grid.ac/institutes/grid.483960.0", 
          "name": [
            "Mendeleev Russian Chemical-Technology University, 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"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.3103/s1068364x15070054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037593998", 
          "https://doi.org/10.3103/s1068364x15070054"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03", 
    "datePublishedReg": "2019-03-01", 
    "description": "The criteria of system complexity are physically interpreted for the problem of optimal process organization in chemical engineering. To that end, optimization by means of a thermoeconomic approach using undetermined Lagrange multipliers is considered. The Lagrange multipliers obtained characterize the complexity of the system and represent the unit exergy cost of intermediate streams or product streams, which by definition must be minimized. The Lagrange multipliers obtained by applying the information approach to optimal system organization also characterize its complexity. By analogy, it may be supposed that they reflect the unit information cost of intermediate streams or the product streams similar to thermoeconomic criteria. It was shown that thermoeconomic complexity criteria cannot be used in practice on account of various fundamental limitations. Conversely, information complexity criteria are of practical value since all the characteristics present depend solely on process operating parameters. Decreasing the unit information cost is viewed as a tradeoff between the possibility of additional energy reserves in the system, on the one hand, and the costs of organizing energy production processes, on the other. Accordingly, these criteria may be regarded as hybrid, analogously to thermoeconomic criteria.", 
    "genre": "article", 
    "id": "sg:pub.10.3103/s1068364x19030050", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1136036", 
        "issn": [
          "1068-364X", 
          "1934-8398"
        ], 
        "name": "Coke and Chemistry", 
        "publisher": "Allerton Press", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "62"
      }
    ], 
    "keywords": [
      "unit exergy cost", 
      "thermoeconomic criterion", 
      "energy production processes", 
      "exergy cost", 
      "intermediate streams", 
      "thermoeconomic approach", 
      "Lagrange multipliers", 
      "product stream", 
      "chemical engineering", 
      "production process", 
      "chemical industry", 
      "system complexity", 
      "fundamental limitations", 
      "multipliers", 
      "physical interpretation", 
      "cost", 
      "practical value", 
      "streams", 
      "engineering", 
      "optimization", 
      "process", 
      "system", 
      "parameters", 
      "industry", 
      "process organization", 
      "characteristics", 
      "complexity", 
      "approach", 
      "tradeoff", 
      "undetermined Lagrange multipliers", 
      "complexity criteria", 
      "criteria", 
      "account", 
      "problem", 
      "products", 
      "limitations", 
      "values", 
      "means", 
      "system organization", 
      "analogy", 
      "possibility", 
      "energy reserves", 
      "hand", 
      "end", 
      "reserves", 
      "information approach", 
      "definition", 
      "interpretation", 
      "information complexity (ICOMP) criterion", 
      "practice", 
      "organization", 
      "information costs", 
      "optimal process organization", 
      "optimal system organization", 
      "unit information cost", 
      "thermoeconomic complexity criteria", 
      "additional energy reserves"
    ], 
    "name": "On the Physical Interpretation of Complexity Criteria for Optimal System Organization in the Chemical Industry", 
    "pagination": "107-112", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1117482146"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.3103/s1068364x19030050"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.3103/s1068364x19030050", 
      "https://app.dimensions.ai/details/publication/pub.1117482146"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:49", 
    "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_803.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.3103/s1068364x19030050"
  }
]
 

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.10.3103/s1068364x19030050'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.3103/s1068364x19030050'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.3103/s1068364x19030050'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.3103/s1068364x19030050'


 

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

119 TRIPLES      22 PREDICATES      84 URIs      75 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.3103/s1068364x19030050 schema:about anzsrc-for:09
2 anzsrc-for:0904
3 schema:author N440dc4a454ac4ef1a733e33992e4ee07
4 schema:citation sg:pub.10.3103/s1068364x15070054
5 schema:datePublished 2019-03
6 schema:datePublishedReg 2019-03-01
7 schema:description The criteria of system complexity are physically interpreted for the problem of optimal process organization in chemical engineering. To that end, optimization by means of a thermoeconomic approach using undetermined Lagrange multipliers is considered. The Lagrange multipliers obtained characterize the complexity of the system and represent the unit exergy cost of intermediate streams or product streams, which by definition must be minimized. The Lagrange multipliers obtained by applying the information approach to optimal system organization also characterize its complexity. By analogy, it may be supposed that they reflect the unit information cost of intermediate streams or the product streams similar to thermoeconomic criteria. It was shown that thermoeconomic complexity criteria cannot be used in practice on account of various fundamental limitations. Conversely, information complexity criteria are of practical value since all the characteristics present depend solely on process operating parameters. Decreasing the unit information cost is viewed as a tradeoff between the possibility of additional energy reserves in the system, on the one hand, and the costs of organizing energy production processes, on the other. Accordingly, these criteria may be regarded as hybrid, analogously to thermoeconomic criteria.
8 schema:genre article
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N048555df37674a72a5a09b0dc78d49d8
12 Nbe140a00fbd04bc29dfc0c245b2a8eca
13 sg:journal.1136036
14 schema:keywords Lagrange multipliers
15 account
16 additional energy reserves
17 analogy
18 approach
19 characteristics
20 chemical engineering
21 chemical industry
22 complexity
23 complexity criteria
24 cost
25 criteria
26 definition
27 end
28 energy production processes
29 energy reserves
30 engineering
31 exergy cost
32 fundamental limitations
33 hand
34 industry
35 information approach
36 information complexity (ICOMP) criterion
37 information costs
38 intermediate streams
39 interpretation
40 limitations
41 means
42 multipliers
43 optimal process organization
44 optimal system organization
45 optimization
46 organization
47 parameters
48 physical interpretation
49 possibility
50 practical value
51 practice
52 problem
53 process
54 process organization
55 product stream
56 production process
57 products
58 reserves
59 streams
60 system
61 system complexity
62 system organization
63 thermoeconomic approach
64 thermoeconomic complexity criteria
65 thermoeconomic criterion
66 tradeoff
67 undetermined Lagrange multipliers
68 unit exergy cost
69 unit information cost
70 values
71 schema:name On the Physical Interpretation of Complexity Criteria for Optimal System Organization in the Chemical Industry
72 schema:pagination 107-112
73 schema:productId N742dee6eceb24a589aa46251d0a131dd
74 N8a35b6bfe26e48cba24746a98bdc1f89
75 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117482146
76 https://doi.org/10.3103/s1068364x19030050
77 schema:sdDatePublished 2022-01-01T18:49
78 schema:sdLicense https://scigraph.springernature.com/explorer/license/
79 schema:sdPublisher Nc754d860b64f435b88f9f09a186b8b92
80 schema:url https://doi.org/10.3103/s1068364x19030050
81 sgo:license sg:explorer/license/
82 sgo:sdDataset articles
83 rdf:type schema:ScholarlyArticle
84 N048555df37674a72a5a09b0dc78d49d8 schema:issueNumber 3
85 rdf:type schema:PublicationIssue
86 N440dc4a454ac4ef1a733e33992e4ee07 rdf:first sg:person.015576745360.67
87 rdf:rest rdf:nil
88 N742dee6eceb24a589aa46251d0a131dd schema:name dimensions_id
89 schema:value pub.1117482146
90 rdf:type schema:PropertyValue
91 N8a35b6bfe26e48cba24746a98bdc1f89 schema:name doi
92 schema:value 10.3103/s1068364x19030050
93 rdf:type schema:PropertyValue
94 Nbe140a00fbd04bc29dfc0c245b2a8eca schema:volumeNumber 62
95 rdf:type schema:PublicationVolume
96 Nc754d860b64f435b88f9f09a186b8b92 schema:name Springer Nature - SN SciGraph project
97 rdf:type schema:Organization
98 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
99 schema:name Engineering
100 rdf:type schema:DefinedTerm
101 anzsrc-for:0904 schema:inDefinedTermSet anzsrc-for:
102 schema:name Chemical Engineering
103 rdf:type schema:DefinedTerm
104 sg:journal.1136036 schema:issn 1068-364X
105 1934-8398
106 schema:name Coke and Chemistry
107 schema:publisher Allerton Press
108 rdf:type schema:Periodical
109 sg:person.015576745360.67 schema:affiliation grid-institutes:grid.483960.0
110 schema:familyName Naletov
111 schema:givenName V. A.
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015576745360.67
113 rdf:type schema:Person
114 sg:pub.10.3103/s1068364x15070054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037593998
115 https://doi.org/10.3103/s1068364x15070054
116 rdf:type schema:CreativeWork
117 grid-institutes:grid.483960.0 schema:alternateName Mendeleev Russian Chemical-Technology University, Moscow, Russia
118 schema:name Mendeleev Russian Chemical-Technology University, Moscow, Russia
119 rdf:type schema:Organization
 




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


...