Conference paper Embargoed Access

Prediction of liquefaction damage with artificial neural networks

Paolella Luca; Salvatore Erminio; Spacagna Rose Line; Modoni Giuseppe; Ochmanski Maciej


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    "embargo_date": "2020-06-30", 
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    "description": "<p>The survey of the damage occurred on land, buildings and infrastructures<br>\nextensively affected by liquefaction, coupled with a comprehensive investigation of the subsoil<br>\nproperties enables to identify the factors that determine the spatial distribution of the phenomenon.<br>\nWith this goal, a database was created in a Geographic Information platform merging<br>\nrecords of local seismicity, subsoil layering evaluated by cone penetration tests and<br>\ngroundwater level distribution for the relevant case study of San Carlo (Emilia Romagna-<br>\nItaly) struck by a severe earthquake in 2012. Here liquefaction phenomena were observed on a<br>\nportion of the village in the form of sand ejecta, lateral spreading and various damages on<br>\nbuildings and infrastructures. The location of damage allows to test possible relations with the<br>\nfactors characterizing susceptibility, triggering and severity of liquefaction. The relation<br>\namong the different variables has been herein sought by training a specifically implemented<br>\nArtificial Neural Network. A relation has thus been inferred between damage and thickness of<br>\nthe liquefiable layer and of the upper crust, seismic input and soil characteristics.</p>", 
    "language": "eng", 
    "title": "Prediction of liquefaction damage with artificial neural networks", 
    "license": {
      "id": "CC-BY-1.0"
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        }, 
        "title": "Assessment and mitigation of liquefaction potential across Europe: a holistic approach to protect structures / infrastructures for improved resilience to earthquake-induced liquefaction disasters", 
        "acronym": "LIQUEFACT", 
        "program": "H2020", 
        "funder": {
          "doi": "10.13039/501100000780", 
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          "name": "European Commission", 
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    "keywords": [
      "Liquefaction", 
      "Artificial Neural Networks"
    ], 
    "publication_date": "2019-06-23", 
    "creators": [
      {
        "affiliation": "University of Cassino and Southern Lazio", 
        "name": "Paolella Luca"
      }, 
      {
        "affiliation": "University of Cassino and Southern Lazio", 
        "name": "Salvatore Erminio"
      }, 
      {
        "affiliation": "University of Cassino and Southern Lazio", 
        "name": "Spacagna Rose Line"
      }, 
      {
        "affiliation": "University of Cassino and Southern Lazio", 
        "name": "Modoni Giuseppe"
      }, 
      {
        "affiliation": "Silesian University of Technology - Gliwice (Poland)", 
        "name": "Ochmanski Maciej"
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