Publicação
Truncated gaussian simulation to map the spatial heterogeneity of rock mass rating
| Resumo: | [Excerpt] Introduction: Mapping the intrinsic spatial variability of rock mass characteristics is an essential issue in geotechnical and geomechanical engineering, as these characteristics have a significant impact on the behavior of underground structures. Such mapping can be performed by recurrence of geostatistical models, in which the geomechanical parameters are viewed as outcomes (realizations) of spatial random fields whose properties can be inferred from the available in situ measurements and laboratory tests. In this context, several authors already applied geostatistics to predict or simulate characteristics such as lithofacies (Rosenbaum et al. 1997), rock quality designation (RQD) (Madani and Asghari 2013; Ozturk and Simdi 2014; Ozturk 2002), rock mass rating (RMR) (Ryu et al. 2003; Seokhoom et al. 2004; Stavropoulou et al. 2007; Exadaktylos and Stavropoulou 2008; Jeon et al. 2009; Egaña and Ortiz 2013) and geological strength index (GSI) (Ozturk and Simdi 2014; Deisman et al. 2013). (...) |
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| Autores principais: | Pinheiro, Marisa Mota |
| Outros Autores: | Emery, Xavier; Miranda, Tiago F. S.; Vallejos, Javier |
| Assunto: | Rock mass rating Geostatstitics Rock mechanics Geostatistical simulation Spatial heterogeneity Spatial uncertainty |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | [Excerpt] Introduction: Mapping the intrinsic spatial variability of rock mass characteristics is an essential issue in geotechnical and geomechanical engineering, as these characteristics have a significant impact on the behavior of underground structures. Such mapping can be performed by recurrence of geostatistical models, in which the geomechanical parameters are viewed as outcomes (realizations) of spatial random fields whose properties can be inferred from the available in situ measurements and laboratory tests. In this context, several authors already applied geostatistics to predict or simulate characteristics such as lithofacies (Rosenbaum et al. 1997), rock quality designation (RQD) (Madani and Asghari 2013; Ozturk and Simdi 2014; Ozturk 2002), rock mass rating (RMR) (Ryu et al. 2003; Seokhoom et al. 2004; Stavropoulou et al. 2007; Exadaktylos and Stavropoulou 2008; Jeon et al. 2009; Egaña and Ortiz 2013) and geological strength index (GSI) (Ozturk and Simdi 2014; Deisman et al. 2013). (...) |
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