Aerodynamic design optimization using information extracted from analysis of unstructured surface meshes


Ontology type: sgo:Patent     


Patent Info

DATE

2017-05-23T00:00

AUTHORS

Lars Graning , Markus Olhofer , Bernhard Sendhoff

ABSTRACT

A computer-implemented method of analyzing data representing the optimization of real-world designs of physical entities according to at least one criterion. Different modifications of the design are generated by a cyclic optimization algorithm. The design data is represented by unstructured triangular surface meshes. A displacement measure representing local differences between two design modifications of the different modifications is calculated. Performance difference between the two design modifications is calculated. The performance difference is represented by at least one criterion. Sensitivity information representing correlation between the displacement measure and the performance differences is outputted. More... »

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/2008/2353", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "Lars Graning", 
        "type": "Person"
      }, 
      {
        "name": "Markus Olhofer", 
        "type": "Person"
      }, 
      {
        "name": "Bernhard Sendhoff", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.engappai.2003.10.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024809922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00500-003-0328-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025730957", 
          "https://doi.org/10.1007/s00500-003-0328-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1467-8659.00575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030386344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cma.2004.12.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048623071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg1921", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049226788", 
          "https://doi.org/10.1038/nrg1921"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrg1921", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049226788", 
          "https://doi.org/10.1038/nrg1921"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-05-23T00:00", 
    "description": "

A computer-implemented method of analyzing data representing the optimization of real-world designs of physical entities according to at least one criterion. Different modifications of the design are generated by a cyclic optimization algorithm. The design data is represented by unstructured triangular surface meshes. A displacement measure representing local differences between two design modifications of the different modifications is calculated. Performance difference between the two design modifications is calculated. The performance difference is represented by at least one criterion. Sensitivity information representing correlation between the displacement measure and the performance differences is outputted.

", "id": "sg:patent.US-9659122-B2", "keywords": [ "design optimization", "surface", "computer", "optimization", "real world", "entity", "criterion", "different modification", "optimization algorithm", "design data", "triangular", "displacement", "local difference", "design modification", "performance difference", "correlation" ], "name": "Aerodynamic design optimization using information extracted from analysis of unstructured surface meshes", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.420749.c", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-9659122-B2" ], "sdDataset": "patents", "sdDatePublished": "2019-04-18T10:20", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-uberresearch-data-patents-target-20190320-rc/data/sn-export/402f166718b70575fb5d4ffe01f064d1/0000100128-0000352499/json_export_01466.jsonl", "type": "Patent" } ]
 

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/patent.US-9659122-B2'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.US-9659122-B2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-9659122-B2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-9659122-B2'


 

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

63 TRIPLES      15 PREDICATES      35 URIs      24 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-9659122-B2 schema:about anzsrc-for:2353
2 schema:author Nd44e7c16664c4fbb8790ae9b3338f309
3 schema:citation sg:pub.10.1007/s00500-003-0328-5
4 sg:pub.10.1038/nrg1921
5 https://doi.org/10.1016/j.cma.2004.12.019
6 https://doi.org/10.1016/j.engappai.2003.10.003
7 https://doi.org/10.1111/1467-8659.00575
8 schema:datePublished 2017-05-23T00:00
9 schema:description <p id="p-0001" num="0000">A computer-implemented method of analyzing data representing the optimization of real-world designs of physical entities according to at least one criterion. Different modifications of the design are generated by a cyclic optimization algorithm. The design data is represented by unstructured triangular surface meshes. A displacement measure representing local differences between two design modifications of the different modifications is calculated. Performance difference between the two design modifications is calculated. The performance difference is represented by at least one criterion. Sensitivity information representing correlation between the displacement measure and the performance differences is outputted.</p>
10 schema:keywords computer
11 correlation
12 criterion
13 design data
14 design modification
15 design optimization
16 different modification
17 displacement
18 entity
19 local difference
20 optimization
21 optimization algorithm
22 performance difference
23 real world
24 surface
25 triangular
26 schema:name Aerodynamic design optimization using information extracted from analysis of unstructured surface meshes
27 schema:recipient https://www.grid.ac/institutes/grid.420749.c
28 schema:sameAs https://app.dimensions.ai/details/patent/US-9659122-B2
29 schema:sdDatePublished 2019-04-18T10:20
30 schema:sdLicense https://scigraph.springernature.com/explorer/license/
31 schema:sdPublisher N259fcf2fc7be4da9abdb02d200c6478f
32 sgo:license sg:explorer/license/
33 sgo:sdDataset patents
34 rdf:type sgo:Patent
35 N259fcf2fc7be4da9abdb02d200c6478f schema:name Springer Nature - SN SciGraph project
36 rdf:type schema:Organization
37 N58eff4aa0c8d4737b3ea47b218789aa4 schema:name Lars Graning
38 rdf:type schema:Person
39 N741cb79caac849eaba4a4f133ede653e schema:name Bernhard Sendhoff
40 rdf:type schema:Person
41 N9339d09d47874e848bb8c76bf332c69a rdf:first N741cb79caac849eaba4a4f133ede653e
42 rdf:rest rdf:nil
43 Ncc372fa1484443cb8d1c1a0e106ac445 rdf:first Nd8d22094c6b64c338e1c0c4f615f4641
44 rdf:rest N9339d09d47874e848bb8c76bf332c69a
45 Nd44e7c16664c4fbb8790ae9b3338f309 rdf:first N58eff4aa0c8d4737b3ea47b218789aa4
46 rdf:rest Ncc372fa1484443cb8d1c1a0e106ac445
47 Nd8d22094c6b64c338e1c0c4f615f4641 schema:name Markus Olhofer
48 rdf:type schema:Person
49 anzsrc-for:2353 schema:inDefinedTermSet anzsrc-for:
50 rdf:type schema:DefinedTerm
51 sg:pub.10.1007/s00500-003-0328-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025730957
52 https://doi.org/10.1007/s00500-003-0328-5
53 rdf:type schema:CreativeWork
54 sg:pub.10.1038/nrg1921 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049226788
55 https://doi.org/10.1038/nrg1921
56 rdf:type schema:CreativeWork
57 https://doi.org/10.1016/j.cma.2004.12.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048623071
58 rdf:type schema:CreativeWork
59 https://doi.org/10.1016/j.engappai.2003.10.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024809922
60 rdf:type schema:CreativeWork
61 https://doi.org/10.1111/1467-8659.00575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030386344
62 rdf:type schema:CreativeWork
63 https://www.grid.ac/institutes/grid.420749.c schema:Organization
 




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


...