Structural and Multidisciplinary Optimization View Homepage


Ontology type: schema:Periodical     


Journal Info

START YEAR

1989

PUBLISHER

Springer Berlin Heidelberg

LANGUAGE

en

HOMEPAGE

https://link.springer.com/journal/158

Recent publications latest 20 shown

  • 2022-07-27 Multi-fidelity surrogate model ensemble based on feasible intervals
  • 2022-07-14 Optimal sensor placement based on dynamic condensation using multi-objective optimization algorithm
  • 2022-07-14 Concurrent shape optimization of a multiscale structure for controlling macrostructural stiffness
  • 2022-07-11 Parameter identification of airfoil systems using an elite-based clustering Jaya algorithm and incremental vibration responses
  • 2022-07-09 Toward multiphysics multiscale concurrent topology optimization for lightweight structures with high heat conductivity and high stiffness using MATLAB
  • 2022-07-09 A surrogate model to accelerate non-intrusive global–local simulations of cracked steel structures
  • 2022-07-07 Size, shape and layout optimization of mono-mast guyed transmission line towers
  • 2022-07-07 Optimized reinforcement distribution in reinforced concrete structures under plane stress state
  • 2022-07-07 A multi-objective optimization design method of shift manipulator for robot driver using SA-PSA
  • 2022-07-07 An expected uncertainty reduction of reliability: adaptive sampling convergence criterion for Kriging-based reliability analysis
  • 2022-07-07 Improving the diversity of topology-optimized designs by swarm intelligence
  • 2022-07-07 BIOS: an object-oriented framework for Surrogate-Based Optimization using bio-inspired algorithms
  • 2022-07-06 Latest developments in node-based shape optimization using Vertex Morphing parameterization
  • 2022-07-06 Topology optimization of non-linear viscous dampers for energy-dissipating structures subjected to non-stationary random seismic excitation
  • 2022-07-06 Proximal-exploration multi-objective Bayesian optimization for inverse identification of cyclic constitutive law of structural steels
  • 2022-06-30 Topology optimization for polymeric stent
  • 2022-06-30 Layout optimization of long-span structures subject to self-weight and multiple load-cases
  • 2022-06-30 Rapid aerodynamic shape optimization under uncertainty using a stochastic gradient approach
  • 2022-06-30 Importance sampling-based algorithms for efficiently estimating failure chance index under two-fold random uncertainty
  • 2022-06-28 An enhanced variable-fidelity optimization approach for constrained optimization problems and its parallelization
  • 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", 
        "contentRating": [
          {
            "author": "snip", 
            "ratingValue": "1.7100000381469727", 
            "type": "Rating"
          }, 
          {
            "author": "sjr", 
            "ratingValue": "1.4019999504089355", 
            "type": "Rating"
          }
        ], 
        "description": "

    Structural and Multidisciplinary Optimization is at the converging frontier of design, engineering, simulation, additive manufacturing, AI and digital-twins. The field has become increasingly important for improving environmental sustainability and combating climate change through enhancing efficiency of engineering products.
    \nThe journal  
    \n• explores a wide range of topics dealing with optimization involving at least one major engineering discipline such as solid (structural), fluid, thermal, electric and electronics, electromagnetics etc.
    \n• covers multidisciplinary optimization when one discipline deals with a major physical performance listed above.
    \n• examines closely related fields that are relevant to design optimization.
    \n• is the official journal of the International Society of Structural and Multidisciplinary Optimization (ISSMO)
    \n
    \nThe journal’s scope ranges from mathematical foundations of the field to algorithm and software development, and from benchmark examples to case studies of practical applications in a wide range of industries including automotive, aerospace, rail, AEC (architecture, engineering and construction), mechanical, electrical, chemical, naval and bio-medical. Articles that provide broad educational value are also encouraged.
    \nFields such as computer-aided design and manufacturing, additive manufacturing, digital-twins, AI, system identification and modeling, inverse processes, computer simulation, bio-mechanics, biomedical applications, nanotechnology, electric and electronics systems, MEMS, optics, chemical processes, computational biology, uncertainty quantification, meta-modeling, DOE and active control of engineering products are covered when the topic is closely related to the optimization of structures, fluids or another major physics.
    \n 
    \n 

    \n", "editor": [ { "familyName": "Cheng", "givenName": "Gengdong", "type": "Person" } ], "id": "sg:journal.1050630", "inLanguage": [ "en" ], "isAccessibleForFree": false, "issn": [ "1615-147X", "1615-1488" ], "license": "Hybrid", "name": "Structural and Multidisciplinary Optimization", "productId": [ { "name": "dimensions_id", "type": "PropertyValue", "value": [ "50630" ] }, { "name": "lccn_id", "type": "PropertyValue", "value": [ "00227119" ] }, { "name": "nlm_unique_id", "type": "PropertyValue", "value": [ "101639455" ] }, { "name": "nsd_ids_id", "type": "PropertyValue", "value": [ "447200" ] }, { "name": "era_ids_id", "type": "PropertyValue", "value": [ "3820" ] } ], "publisher": { "name": "Springer Berlin Heidelberg", "type": "Organization" }, "publisherImprint": "Springer", "sameAs": [ "https://app.dimensions.ai/discover/publication?and_facet_source_title=jour.1050630" ], "sdDataset": "journals", "sdDatePublished": "2022-08-04T17:25", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/journal/journal_0.jsonl", "startYear": "1989", "type": "Periodical", "url": "https://link.springer.com/journal/158" } ]
     

    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/journal.1050630'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/journal.1050630'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/journal.1050630'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/journal.1050630'


     

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

    60 TRIPLES      20 PREDICATES      27 URIs      23 LITERALS      10 BLANK NODES

    Subject Predicate Object
    1 sg:journal.1050630 schema:contentRating N301419bfe127498bb0bba8e60d4b82a3
    2 N6b6e3a4218b84be1818451b01e0ef325
    3 schema:description <p>Structural and Multidisciplinary Optimization is at the converging frontier of design, engineering, simulation, additive manufacturing, AI and digital-twins. The field has become increasingly important for <strong>improving environmental sustainability</strong><strong> </strong>and combating climate change through enhancing efficiency of engineering products.<br /> The journal &nbsp;<br /> &bull; explores a wide range of topics dealing with optimization involving at least one major engineering discipline such as solid (structural), fluid, thermal, electric and electronics, electromagnetics etc.<br /> &bull; covers multidisciplinary optimization when one discipline deals with a major physical<u> </u>performance listed above.<br /> &bull; examines closely related fields that are relevant to design optimization.<br /> &bull; is the official journal of the International Society of Structural and Multidisciplinary Optimization (ISSMO)<br /> <br /> The journal&rsquo;s scope ranges from mathematical foundations of the field to algorithm and software development, and from benchmark examples to case studies of practical applications in a wide range of industries including automotive, aerospace, rail, AEC (architecture, engineering and construction), mechanical, electrical, chemical, naval and bio-medical. Articles that provide broad educational value are also encouraged.<br /> Fields such as computer-aided design and manufacturing, additive manufacturing, digital-twins, AI, system identification and modeling, inverse processes, computer simulation, bio-mechanics, biomedical applications, nanotechnology, electric and electronics systems, MEMS, optics, chemical processes, computational biology, uncertainty quantification, meta-modeling, DOE and active control of engineering products are covered when the topic is closely related to the optimization of structures, fluids or another major physics.<br /> &nbsp;<br /> &nbsp;</p>
    4 schema:editor Ne403cebcd1d346f4922c9acd7bb7feae
    5 schema:inLanguage en
    6 schema:isAccessibleForFree false
    7 schema:issn 1615-147X
    8 1615-1488
    9 schema:license Hybrid
    10 schema:name Structural and Multidisciplinary Optimization
    11 schema:productId N1fbdfd6b687a475ba99c14976940315b
    12 N3f88989a74f246928492577f98cbb47a
    13 N8cf888a65d9240f08de1f9be249989cf
    14 N9b59df41cb084a02bf5dfab0c542abb2
    15 Nb7801c00d9fd429388ee6ee31e80f58c
    16 schema:publisher N5666533a946f4a9ebd4f5cd5b3409576
    17 schema:publisherImprint Springer
    18 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_source_title=jour.1050630
    19 schema:sdDatePublished 2022-08-04T17:25
    20 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    21 schema:sdPublisher N7201631077654025b147f4d0ccda627a
    22 schema:startYear 1989
    23 schema:url https://link.springer.com/journal/158
    24 sgo:license sg:explorer/license/
    25 sgo:sdDataset journals
    26 rdf:type schema:Periodical
    27 N1fbdfd6b687a475ba99c14976940315b schema:name era_ids_id
    28 schema:value 3820
    29 rdf:type schema:PropertyValue
    30 N301419bfe127498bb0bba8e60d4b82a3 schema:author Nd51ca122b9554859b7af6eef01b82483
    31 schema:ratingValue 1.7100000381469727
    32 rdf:type schema:Rating
    33 N3f88989a74f246928492577f98cbb47a schema:name dimensions_id
    34 schema:value 50630
    35 rdf:type schema:PropertyValue
    36 N480f1908206540998f0b78941a6148b7 rdf:first sjr
    37 rdf:rest rdf:nil
    38 N5666533a946f4a9ebd4f5cd5b3409576 schema:name Springer Berlin Heidelberg
    39 rdf:type schema:Organization
    40 N6b6e3a4218b84be1818451b01e0ef325 schema:author N480f1908206540998f0b78941a6148b7
    41 schema:ratingValue 1.4019999504089355
    42 rdf:type schema:Rating
    43 N7201631077654025b147f4d0ccda627a schema:name Springer Nature - SN SciGraph project
    44 rdf:type schema:Organization
    45 N8cf888a65d9240f08de1f9be249989cf schema:name lccn_id
    46 schema:value 00227119
    47 rdf:type schema:PropertyValue
    48 N9b59df41cb084a02bf5dfab0c542abb2 schema:name nsd_ids_id
    49 schema:value 447200
    50 rdf:type schema:PropertyValue
    51 Nb7801c00d9fd429388ee6ee31e80f58c schema:name nlm_unique_id
    52 schema:value 101639455
    53 rdf:type schema:PropertyValue
    54 Nd51ca122b9554859b7af6eef01b82483 rdf:first snip
    55 rdf:rest rdf:nil
    56 Ne403cebcd1d346f4922c9acd7bb7feae rdf:first Nf3716c40f04444aaa541a1906c967c4e
    57 rdf:rest rdf:nil
    58 Nf3716c40f04444aaa541a1906c967c4e schema:familyName Cheng
    59 schema:givenName Gengdong
    60 rdf:type schema:Person
     




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


    ...