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        <name>
          <family>Briggs</family>
          <given>Kevin</given>
        </name>
        <id>k.m.briggs@bath.ac.uk</id>
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          <family>Trinidad González</family>
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    <title>Dataset for Quantifying CPT cone factors in clays derived from weathered mudstone</title>
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    <keywords>Mudstone, Lias Group, Cone penetration test, Undrained shear strength, Cone factors</keywords>
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    <abstract>This dataset contains data from a ground investigation in weathered, stiff, fissured clays of the Lias Group. In the paper, &quot;Quantifying CPT cone factors in clays derived from weathered mudstone&quot;, these data are used to evaluate the performance of cone penetration test (CPT) profiles for predicting the undrained shear strength of these clays.

The dataset consists of a table including 94 pairs of corrected CPT cone factors (N_{kt,UU}), derived from a one-to-one comparison of 94 pairs of triaxial shear strength data from unconsolidated, undrained triaxial tests and CPT cone tip resistance data from equivalent depths.</abstract>
    <date>2023-10-03</date>
    <publisher>University of Bath</publisher>
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        <funder_name>Royal Academy of Engineering</funder_name>
        <funder_id>https://doi.org/10.13039/501100000287</funder_id>
        <grant_id>RCSRF1920\10\65</grant_id>
        <project_name>RAEng Senior Research Fellowship in High Speed Rail</project_name>
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        <funder_name>Engineering and Physical Sciences Research Council</funder_name>
        <funder_id>https://doi.org/10.13039/501100000266</funder_id>
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        <project_name>Assessment, Costing and enhancement of long life, Long Linear assets</project_name>
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    <collection_method>This data was collected as part of a commercial ground investigation by multiple contractors in Oxfordshire, UK. The data was provided by HS2 Ltd in the AGS4 Data Format. Full details of the methodology may be found in the &quot;Materials and method&quot; section of the associated paper.</collection_method>
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