Size-dependent analysis of functionally graded carbon nanotube-reinforced composite nanoshells with double curvature based on nonlocal strain gradient theory View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-11-03

AUTHORS

Pham Toan Thang, Dieu T. T. Do, Jaehong Lee, T. Nguyen-Thoi

ABSTRACT

As initial endeavors, this paper presents an in-depth study to investigate the influence of nanoscale parameters on bending and free vibration responses of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) nanoshells with double curvature. Carbon nanotubes (CNTs) are considered as reinforcements that are distributed across the shell thickness with two different distributions, namely the UD and FG-X. First of all, the mathematical formulas are built on the nonlocal strain gradient theory which, as a critical point of this study, considers both nonlocal and strain gradient parameters simultaneously. Additionally, toward using the Navier solution, the simply supported boundary condition is established to obtain the deflection and natural frequency of FG-CNTRC nanoshells. Furthermore, some specific numerical results are shown and compared with the results reported in the literature. Most importantly, the new findings are given and discussed deeply to show the effect of nanoscale parameters and material property and shape of shells on the deflection and fundamental frequency parameters of the FG-CNTRC nanoshells. From the obtained results, it is shown that the small length-scale has a significant effect on frequencies and deflection of FG-CNTRC nanoshells. More... »

PAGES

1-20

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00366-021-01517-1

DOI

http://dx.doi.org/10.1007/s00366-021-01517-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1142390968


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/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0802", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Computation Theory and Mathematics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam", 
          "id": "http://www.grid.ac/institutes/grid.444812.f", 
          "name": [
            "Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam", 
            "Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Thang", 
        "givenName": "Pham Toan", 
        "id": "sg:person.012700323451.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012700323451.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duy Tan Research Institute for Computational Engineering (DTRice), Duy Tan University, 550000, Da Nang, Vietnam", 
          "id": "http://www.grid.ac/institutes/grid.444918.4", 
          "name": [
            "Duy Tan Research Institute for Computational Engineering (DTRice), Duy Tan University, 550000, Da Nang, Vietnam"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Do", 
        "givenName": "Dieu T. T.", 
        "id": "sg:person.010016625754.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010016625754.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Deep Learning Architecture Research Center, Sejong University, 209 Neungdong-ro, Gwangjin-gu, 143-747, Seoul, Republic of Korea", 
          "id": "http://www.grid.ac/institutes/grid.263333.4", 
          "name": [
            "Deep Learning Architecture Research Center, Sejong University, 209 Neungdong-ro, Gwangjin-gu, 143-747, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Jaehong", 
        "id": "sg:person.013544506437.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013544506437.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam", 
          "id": "http://www.grid.ac/institutes/grid.444812.f", 
          "name": [
            "Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam", 
            "Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nguyen-Thoi", 
        "givenName": "T.", 
        "id": "sg:person.07354764215.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07354764215.20"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00366-021-01353-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1136366091", 
          "https://doi.org/10.1007/s00366-021-01353-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00366-021-01413-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1138068493", 
          "https://doi.org/10.1007/s00366-021-01413-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep06479", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017443789", 
          "https://doi.org/10.1038/srep06479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00366-020-01098-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1128973275", 
          "https://doi.org/10.1007/s00366-020-01098-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00707-016-1647-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039427543", 
          "https://doi.org/10.1007/s00707-016-1647-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00253945", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031046763", 
          "https://doi.org/10.1007/bf00253945"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s40430-016-0551-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013794937", 
          "https://doi.org/10.1007/s40430-016-0551-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/381678a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036830729", 
          "https://doi.org/10.1038/381678a0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2021-11-03", 
    "datePublishedReg": "2021-11-03", 
    "description": "As initial endeavors, this paper presents an in-depth study to investigate the influence of nanoscale parameters on bending and free vibration responses of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) nanoshells with double curvature. Carbon nanotubes (CNTs) are considered as reinforcements that are distributed across the shell thickness with two different distributions, namely the UD and FG-X. First of all, the mathematical formulas are built on the nonlocal strain gradient theory which, as a critical point of this study, considers both nonlocal and strain gradient parameters simultaneously. Additionally, toward using the Navier solution, the simply supported boundary condition is established to obtain the deflection and natural frequency of FG-CNTRC nanoshells. Furthermore, some specific numerical results are shown and compared with the results reported in the literature. Most importantly, the new findings are given and discussed deeply to show the effect of nanoscale parameters and material property and shape of shells on the deflection and fundamental frequency parameters of the FG-CNTRC nanoshells. From the obtained results, it is shown that the small length-scale has a significant effect on frequencies and deflection of FG-CNTRC nanoshells.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00366-021-01517-1", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1041785", 
        "issn": [
          "0177-0667", 
          "1435-5663"
        ], 
        "name": "Engineering with Computers", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }
    ], 
    "keywords": [
      "nonlocal strain gradient theory", 
      "strain gradient theory", 
      "gradient theory", 
      "nanoscale parameters", 
      "carbon nanotube-reinforced composites", 
      "double curvature", 
      "nanotube-reinforced composites", 
      "free vibration response", 
      "carbon nanotubes", 
      "size-dependent analysis", 
      "composite nanoshells", 
      "fundamental frequency parameters", 
      "vibration response", 
      "Navier solution", 
      "natural frequencies", 
      "material properties", 
      "gradient parameter", 
      "specific numerical results", 
      "boundary conditions", 
      "deflection", 
      "frequency parameters", 
      "numerical results", 
      "shell thickness", 
      "shape of shells", 
      "nanoshells", 
      "composites", 
      "parameters", 
      "nanotubes", 
      "reinforcement", 
      "thickness", 
      "curvature", 
      "mathematical formula", 
      "critical point", 
      "frequency", 
      "shell", 
      "properties", 
      "results", 
      "shape", 
      "solution", 
      "significant effect", 
      "depth study", 
      "influence", 
      "UD", 
      "conditions", 
      "effect", 
      "different distributions", 
      "distribution", 
      "theory", 
      "FG", 
      "point", 
      "formula", 
      "analysis", 
      "study", 
      "new findings", 
      "response", 
      "literature", 
      "initial endeavors", 
      "endeavor", 
      "findings", 
      "paper"
    ], 
    "name": "Size-dependent analysis of functionally graded carbon nanotube-reinforced composite nanoshells with double curvature based on nonlocal strain gradient theory", 
    "pagination": "1-20", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1142390968"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00366-021-01517-1"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00366-021-01517-1", 
      "https://app.dimensions.ai/details/publication/pub.1142390968"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-10T10:33", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/article/article_910.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00366-021-01517-1"
  }
]
 

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/s00366-021-01517-1'

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/s00366-021-01517-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00366-021-01517-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00366-021-01517-1'


 

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

184 TRIPLES      22 PREDICATES      94 URIs      75 LITERALS      4 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00366-021-01517-1 schema:about anzsrc-for:01
2 anzsrc-for:0102
3 anzsrc-for:08
4 anzsrc-for:0801
5 anzsrc-for:0802
6 schema:author N4cf2dfadc0b742cb891e9db15bc95f54
7 schema:citation sg:pub.10.1007/bf00253945
8 sg:pub.10.1007/s00366-020-01098-5
9 sg:pub.10.1007/s00366-021-01353-3
10 sg:pub.10.1007/s00366-021-01413-8
11 sg:pub.10.1007/s00707-016-1647-9
12 sg:pub.10.1007/s40430-016-0551-5
13 sg:pub.10.1038/381678a0
14 sg:pub.10.1038/srep06479
15 schema:datePublished 2021-11-03
16 schema:datePublishedReg 2021-11-03
17 schema:description As initial endeavors, this paper presents an in-depth study to investigate the influence of nanoscale parameters on bending and free vibration responses of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) nanoshells with double curvature. Carbon nanotubes (CNTs) are considered as reinforcements that are distributed across the shell thickness with two different distributions, namely the UD and FG-X. First of all, the mathematical formulas are built on the nonlocal strain gradient theory which, as a critical point of this study, considers both nonlocal and strain gradient parameters simultaneously. Additionally, toward using the Navier solution, the simply supported boundary condition is established to obtain the deflection and natural frequency of FG-CNTRC nanoshells. Furthermore, some specific numerical results are shown and compared with the results reported in the literature. Most importantly, the new findings are given and discussed deeply to show the effect of nanoscale parameters and material property and shape of shells on the deflection and fundamental frequency parameters of the FG-CNTRC nanoshells. From the obtained results, it is shown that the small length-scale has a significant effect on frequencies and deflection of FG-CNTRC nanoshells.
18 schema:genre article
19 schema:inLanguage en
20 schema:isAccessibleForFree false
21 schema:isPartOf sg:journal.1041785
22 schema:keywords FG
23 Navier solution
24 UD
25 analysis
26 boundary conditions
27 carbon nanotube-reinforced composites
28 carbon nanotubes
29 composite nanoshells
30 composites
31 conditions
32 critical point
33 curvature
34 deflection
35 depth study
36 different distributions
37 distribution
38 double curvature
39 effect
40 endeavor
41 findings
42 formula
43 free vibration response
44 frequency
45 frequency parameters
46 fundamental frequency parameters
47 gradient parameter
48 gradient theory
49 influence
50 initial endeavors
51 literature
52 material properties
53 mathematical formula
54 nanoscale parameters
55 nanoshells
56 nanotube-reinforced composites
57 nanotubes
58 natural frequencies
59 new findings
60 nonlocal strain gradient theory
61 numerical results
62 paper
63 parameters
64 point
65 properties
66 reinforcement
67 response
68 results
69 shape
70 shape of shells
71 shell
72 shell thickness
73 significant effect
74 size-dependent analysis
75 solution
76 specific numerical results
77 strain gradient theory
78 study
79 theory
80 thickness
81 vibration response
82 schema:name Size-dependent analysis of functionally graded carbon nanotube-reinforced composite nanoshells with double curvature based on nonlocal strain gradient theory
83 schema:pagination 1-20
84 schema:productId Nc52f9857a8c04a078414908c150cf88e
85 Ndca31568408540518a86f4eef1ff9436
86 schema:sameAs https://app.dimensions.ai/details/publication/pub.1142390968
87 https://doi.org/10.1007/s00366-021-01517-1
88 schema:sdDatePublished 2022-05-10T10:33
89 schema:sdLicense https://scigraph.springernature.com/explorer/license/
90 schema:sdPublisher N37def4743cc84a538847615f893b392e
91 schema:url https://doi.org/10.1007/s00366-021-01517-1
92 sgo:license sg:explorer/license/
93 sgo:sdDataset articles
94 rdf:type schema:ScholarlyArticle
95 N076694447ff3468ab688231da326ab8d rdf:first sg:person.013544506437.00
96 rdf:rest N463a78e58aae4d0888702fd43279abd7
97 N37def4743cc84a538847615f893b392e schema:name Springer Nature - SN SciGraph project
98 rdf:type schema:Organization
99 N463a78e58aae4d0888702fd43279abd7 rdf:first sg:person.07354764215.20
100 rdf:rest rdf:nil
101 N4cf2dfadc0b742cb891e9db15bc95f54 rdf:first sg:person.012700323451.29
102 rdf:rest N857efff2394a4cc9b02a6420fe93e208
103 N857efff2394a4cc9b02a6420fe93e208 rdf:first sg:person.010016625754.56
104 rdf:rest N076694447ff3468ab688231da326ab8d
105 Nc52f9857a8c04a078414908c150cf88e schema:name dimensions_id
106 schema:value pub.1142390968
107 rdf:type schema:PropertyValue
108 Ndca31568408540518a86f4eef1ff9436 schema:name doi
109 schema:value 10.1007/s00366-021-01517-1
110 rdf:type schema:PropertyValue
111 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
112 schema:name Mathematical Sciences
113 rdf:type schema:DefinedTerm
114 anzsrc-for:0102 schema:inDefinedTermSet anzsrc-for:
115 schema:name Applied Mathematics
116 rdf:type schema:DefinedTerm
117 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
118 schema:name Information and Computing Sciences
119 rdf:type schema:DefinedTerm
120 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
121 schema:name Artificial Intelligence and Image Processing
122 rdf:type schema:DefinedTerm
123 anzsrc-for:0802 schema:inDefinedTermSet anzsrc-for:
124 schema:name Computation Theory and Mathematics
125 rdf:type schema:DefinedTerm
126 sg:journal.1041785 schema:issn 0177-0667
127 1435-5663
128 schema:name Engineering with Computers
129 schema:publisher Springer Nature
130 rdf:type schema:Periodical
131 sg:person.010016625754.56 schema:affiliation grid-institutes:grid.444918.4
132 schema:familyName Do
133 schema:givenName Dieu T. T.
134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010016625754.56
135 rdf:type schema:Person
136 sg:person.012700323451.29 schema:affiliation grid-institutes:grid.444812.f
137 schema:familyName Thang
138 schema:givenName Pham Toan
139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012700323451.29
140 rdf:type schema:Person
141 sg:person.013544506437.00 schema:affiliation grid-institutes:grid.263333.4
142 schema:familyName Lee
143 schema:givenName Jaehong
144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013544506437.00
145 rdf:type schema:Person
146 sg:person.07354764215.20 schema:affiliation grid-institutes:grid.444812.f
147 schema:familyName Nguyen-Thoi
148 schema:givenName T.
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07354764215.20
150 rdf:type schema:Person
151 sg:pub.10.1007/bf00253945 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031046763
152 https://doi.org/10.1007/bf00253945
153 rdf:type schema:CreativeWork
154 sg:pub.10.1007/s00366-020-01098-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1128973275
155 https://doi.org/10.1007/s00366-020-01098-5
156 rdf:type schema:CreativeWork
157 sg:pub.10.1007/s00366-021-01353-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1136366091
158 https://doi.org/10.1007/s00366-021-01353-3
159 rdf:type schema:CreativeWork
160 sg:pub.10.1007/s00366-021-01413-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1138068493
161 https://doi.org/10.1007/s00366-021-01413-8
162 rdf:type schema:CreativeWork
163 sg:pub.10.1007/s00707-016-1647-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039427543
164 https://doi.org/10.1007/s00707-016-1647-9
165 rdf:type schema:CreativeWork
166 sg:pub.10.1007/s40430-016-0551-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013794937
167 https://doi.org/10.1007/s40430-016-0551-5
168 rdf:type schema:CreativeWork
169 sg:pub.10.1038/381678a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036830729
170 https://doi.org/10.1038/381678a0
171 rdf:type schema:CreativeWork
172 sg:pub.10.1038/srep06479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017443789
173 https://doi.org/10.1038/srep06479
174 rdf:type schema:CreativeWork
175 grid-institutes:grid.263333.4 schema:alternateName Deep Learning Architecture Research Center, Sejong University, 209 Neungdong-ro, Gwangjin-gu, 143-747, Seoul, Republic of Korea
176 schema:name Deep Learning Architecture Research Center, Sejong University, 209 Neungdong-ro, Gwangjin-gu, 143-747, Seoul, Republic of Korea
177 rdf:type schema:Organization
178 grid-institutes:grid.444812.f schema:alternateName Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
179 schema:name Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
180 Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
181 rdf:type schema:Organization
182 grid-institutes:grid.444918.4 schema:alternateName Duy Tan Research Institute for Computational Engineering (DTRice), Duy Tan University, 550000, Da Nang, Vietnam
183 schema:name Duy Tan Research Institute for Computational Engineering (DTRice), Duy Tan University, 550000, Da Nang, Vietnam
184 rdf:type schema:Organization
 




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


...