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    <responseDate>2026-10-12T06:47:19Z</responseDate>
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    <identifier>10.57760/sciencedb.31518</identifier>
    <datestamp>2026-04-08T13:59:03Z</datestamp>
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  <dc:date>2026-04-08</dc:date>
  <dc:title>Strain Energy Density Dataset of Crustal Rock Mass in Pakistan</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.31518</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>To support seismic hazard analysis and disaster prevention and mitigation in Pakistan, this study uses the Crust 1.0 global crustal model and the Central Asia Fault Database as basic data, constrained by the regional GNSS velocity field. A three-dimensional finite element model is established to numerically calculate and generate a millennial-scale 3D strain energy density distribution dataset for the crustal rock mass in Pakistan. The dataset presents strain energy density distributions of the regional crust under eight loading time scales (5, 10, 30, 50, 100, 300, 500, and 1000 years), and includes medium information of fault nodes and strata nodes. The 3D coordinates (km) and strain energy density values (J/m&amp;sup3;) of nodes are provided in .xls format. The reliability of the dataset is effectively verified through model boundary condition validation and matching analysis with historical strong earthquake distributions. This dataset can serve regional seismic potential hazard assessment, seismic hazard zoning, and research on the preparation mechanism of strong earthquakes, providing fundamental and critical data support for seismic disaster prevention, risk management and mitigation in Pakistan.</dc:description>
  <dc:subject>Pakistan; seismic disaster; GNSS velocity field; strain energy density; numerical calculation</dc:subject>
  <dc:creator>Wang Ziqing</dc:creator>
  <dc:creator>Mao Wenfei</dc:creator>
  <dc:creator>L ü Changju</dc:creator>
  <dc:creator>Wu Lixin</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.11922/11-6035.csd.2026.0046.zh</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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