Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios
ilustraciones, diagramas
- Autores:
-
Lozano Vargas, Germán Alberto
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/84773
- Palabra clave:
- 620 - Ingeniería y operaciones afines::624 - Ingeniería civil
Uso de la tierra -planificación
Espacios abiertos
Land use
Open spaces
Variabilidad espacial
Variabilidad inherente
Escala de fluctuación
Sabana de Bogotá
Teoría de los campos aleatorios
Modelo y función de autocorrelación
Análisis de tendencias
Spatial variability
Inherent variability
Autocorrelation function
Bogota savanna
Random field theory
Trend analysis
Scale of fluctuation
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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UNACIONAL2 |
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Universidad Nacional de Colombia |
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| dc.title.spa.fl_str_mv |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| dc.title.translated.eng.fl_str_mv |
Analysis of the inherent variability of some soil profiles of the Bogota Savanna based on random field theory |
| title |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| spellingShingle |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios 620 - Ingeniería y operaciones afines::624 - Ingeniería civil Uso de la tierra -planificación Espacios abiertos Land use Open spaces Variabilidad espacial Variabilidad inherente Escala de fluctuación Sabana de Bogotá Teoría de los campos aleatorios Modelo y función de autocorrelación Análisis de tendencias Spatial variability Inherent variability Autocorrelation function Bogota savanna Random field theory Trend analysis Scale of fluctuation |
| title_short |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| title_full |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| title_fullStr |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| title_full_unstemmed |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| title_sort |
Análisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatorios |
| dc.creator.fl_str_mv |
Lozano Vargas, Germán Alberto |
| dc.contributor.advisor.none.fl_str_mv |
Barbosa Cruz, Edgard Robert Tapias Camacho, Mauricio Alberto |
| dc.contributor.author.none.fl_str_mv |
Lozano Vargas, Germán Alberto |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines::624 - Ingeniería civil |
| topic |
620 - Ingeniería y operaciones afines::624 - Ingeniería civil Uso de la tierra -planificación Espacios abiertos Land use Open spaces Variabilidad espacial Variabilidad inherente Escala de fluctuación Sabana de Bogotá Teoría de los campos aleatorios Modelo y función de autocorrelación Análisis de tendencias Spatial variability Inherent variability Autocorrelation function Bogota savanna Random field theory Trend analysis Scale of fluctuation |
| dc.subject.lemb.spa.fl_str_mv |
Uso de la tierra -planificación Espacios abiertos |
| dc.subject.lemb.end.fl_str_mv |
Land use |
| dc.subject.lemb.eng.fl_str_mv |
Open spaces |
| dc.subject.proposal.spa.fl_str_mv |
Variabilidad espacial Variabilidad inherente Escala de fluctuación Sabana de Bogotá Teoría de los campos aleatorios Modelo y función de autocorrelación Análisis de tendencias |
| dc.subject.proposal.eng.fl_str_mv |
Spatial variability Inherent variability Autocorrelation function Bogota savanna Random field theory Trend analysis Scale of fluctuation |
| description |
ilustraciones, diagramas |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-10-05T20:15:42Z |
| dc.date.available.none.fl_str_mv |
2023-10-05T20:15:42Z |
| dc.date.issued.none.fl_str_mv |
2023 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/84773 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/84773 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.spa.fl_str_mv |
Agterberg, F.B. (1970). Autocorrelation Functions in Geology. In Geostatistics – a colloquium: Proceedings of a Colloquium on Geostatistics. University of Kansas. Alonso, E. E., Krizek, R.J (1975). Stochastic formulation of soil properties. Proceedings of the 2nd International Conference on Applications of Statistics and Probability to Soil and Structural Engineering, Vol.1, Aachen Germany, pp. 9 – 32. Baecher, G.B. (1987). Statistical Analysis of Geotechnical Data. Report No. GL-87-1, U.S. Army Engineer Waterways Experiment Station, Vicksburg, VA. Barón, M. (2021). Calibración del ensayo CPTu para el depósito lacustre de Bogotá. Maestría en Geotecnia. Universidad Nacional de Colombia. Sede Bogotá. Biswas, A., Si, B. C. (2011). Application of continuous wavelet transform in examining soil spatial variation: A review. In Mathematical Geosciences (Vol. 43, Issue 3, pp. 379–396). Stuedlein, A. & Bong, T. (2017). Effect of Spatial Variability on Static and Liquefaction-Induced Differential Settlements. 31-51. Brockwell, P.J., Davis, R.A. (1991). ITSM: An interactive time series modeling package for the PC, Springer-Verlag, New York, 104 p. Bury, K.V. (1975). Statistical Models in Applied Science. John Wiley, Hoboken Campanella, R.G., Wickremesinghe, D.S., Robertson, P.K. (1987). Statistical Treatment of Cone Penetrometer Test Data. Proceedings of the 5th International Conference on Applications of Statistics and Probability in Soil and Structural Engineering, Vancouver, BC, Canada, Vol. 2, 1011-1019. Cami, B. and Javankhoshdel, S. (2020). ARMA Models to Measure the Scale of Fluctuation from CPT Data. The Open Construction and Building Technology Journal, 14(1), pp. 230–236. Cao, Z. and Wang, Y. (2014). Bayesian model comparison and selection of spatial correlation functions for soil parameters, Structural Safety, 49, pp. 10–17 Chenari, R. Seyedeyn M.S., Faraji, S. and Kenarsari, A. (2012). Investigation on inherent variability of soil properties from cone penetration test. Chiles, J. P., y Delfiner, P. (1999). Geostatistics: Modeling spatial uncertainty (Vol. 497). John Wiley y Sons Dasaka, S.M. and Zhang, L.M. (2012). Spatial variability of in situ weathered soil. Geotechnique, 62(5). Degroot, D.J., Baecher, G.B. (1993). Estimating Autocovariances of In-Situ Soil Properties. Journal of Geotechnical Engineering, Vol. 119, No. 1, 147-166. Diaz, J., Vanmarcke E.H. (1974). Settlement of Structures on Shallow Foundations: A Probabilistic Analysis. Massachusetts Institute of Technology. Department of Civil Engineering, National Science Foundation (U.S.), United States. Díaz Méndez, L. A., Manrique, Á. (2020). Caracterización de la variabilidad espacial de la resistencia al corte no drenado del depósito lacustre “A” ubicado en la escuela colombiana de ingeniería Julio Garavito. Maestría en Ingeniería Civil. Escuela Colombiana Julio Garavito. Bogotá, Colombia. Douglas, B.J. and Olsen, R.S. (1981). Soil Classification Using Electric Cone Penetrometer. Proceedings of Conference on Cone Penetration Testing and Experience, St. Louis, 209-227. Fenton, G.A. (1999a). Estimation for Stochastic Soil Models. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 125, No. 6, 470-485. Fenton, G.A. (1999b). Random Field Modeling of CPT Data. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 125, No. 6, 486-498. Fenton, G.A., Vanmarcke, E.H. (2003). Random Field Characterization of NGES Data. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication. No. 121, 61-78. FOPAE. (2010). Zonificación de la respuesta sísmica de Bogotá para el diseño sismo resistente de edificaciones. Fondo de Prevención y Atención de Emergencias. Bogotá, Colombia. Garzón, L. X., Caicedo, B., Sánchez-Silva, M., y Phoon, K. K. (2015). Physical modelling of soil uncertainty. International Journal of Physical Modelling in Geotechnics, 15(1), 19–34. Garzón, L. X. (2019). Physical modeling of soil spatial variability: application to shallow foundation. Doctoral dissertation, Universidad de los Andes, Bogotá, Colombia. Hegazy, Y.A. and Mayne, Paul and Rouhani, Shahrok (1996). Geostatistical assessment of spatial variability in piezocone tests. Geotechnical Special Publication. 254-267. INGEOMINAS y Universidad de los Andes (1997). Microzonificacion sismica de santa fe de Bogotá. Bogotá, Colombia. Jaksa, M. B. (1995). The Influence of Spatial Variability on the Geotechnical Design Properties of a Stiff Overconsolidated Clay. Ph.D. thesis. The university of Adelaide, Australia. Jaksa, M.B., Brooker, P.I., Kaggwa, W.S. (1997). Inaccuracies Associated with Estimating Random Measurement Errors. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 123, No. 5, 393-401Jaksa, M.B., Brooker, P.I., Kaggwa, W.S. (1997). Inaccuracies Associated with Estimating Random Measurement Errors. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 123, No. 5, 393-401 Kulatilake, P.H., Ghosh, A. (1988). An Investigation Into Accuracy of Spatial Variation Estimation Using Static Cone Penetrometer Data. Proceedings of the 1st International Symposium on Penetration Testing (ISOPT-1). Orlando, FL, U.S.A. Kulatilake, P.H. (1991). Discussion on “Probabilistic Potentiometric Surface Mapping.” Journal of Geotechnical Engineering, ASCE, Vol. 117, No. 9, 1458-1459. Kulatilake, P.H., UM, J.G. (2003). Spatial Variation of Cone Tip Resistance for the Clay Site at Texas AyM University. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication No. 121, 41-60. Kulhawy, F.H., Birgisson, B., Grigoriu, M.D. (1992). Reliability-Based Foundation Design for Transmission Line Structures: Transformation Models for In-Situ Tests. Report No. EL-5507(4), Electric Power Research Institute, Palo Alto, CA. Lacasse, S., Nadim, F. (1996). Uncertainties in Characterizing Soil Properties. Uncertainty in the Geologic Environment: From Theory to Practice. ASCE Geotechnical Special Publication No. 58, Madison, WI, U.S.A., 49-75. Li, K. S. and Lee, I. K. (1991). The Assessment of Geotechnical Safety. In Selected Topics in Geotechnical Engineering - Lumb Volume, Li, K. S. (ed.), Dept. Civil and Maritime Engrg., UNSW, ADFA, Canberra, pp. 195-229. Li, K.S. (1991). Probabilistic Potentiometric Surface Mapping. Journal of Geotechnical Engineering, ASCE, Vol. 117, No. 9, 1457-1458. Spacagna, L., de Fouquet, C., y Russo, G. (2015). Interpretation of CPTU Tests with Statistical and Geostatistical Methods. Lumb. P. (1966). The variability of Natural Soils. Canadian Geotechnical Journal. 3. 74-97. Lumb, P. and Holt, J. K. (1968). The Undrained Shear Strength of a Soft Marine Clay from Hong Kong. Geotechnique, Vol. 18, pp. 25-36. Lumb, P. (1971). Precision and Accuracy of Soil Tests. Proceedings of the 1st International Conference on Applications of Statistics and Probability in Soil and Structural Engineering, Hong Kong, 329-345. Lumb, P. (1974). Application of Statistics in Soil Mechanics, chapter 3 in Soil Mechanics – New Horizons, I.K. Lee (ed.), Newnes-Butterworths, London, U.K., 44-111. Luo, Y., Ahlström, A., Allison, S. D., Batjes, N. H., Brovkin, V. (2016). Toward more realistic projections of soil carbondynamics by Earth system models, Global Biogeochem. Cy., 30,40–56. Matheron, G. (1963). Principles of Geostatistics. Economic Geology, 58, 1246-1266. Montenegro, A. (1989). La Función de Autocorrelación y su Empleo en el Análisis de Series de Tiempo. Revista Desarrollo Y Sociedad, 1(23), 117–132. Moya, J., y Rodriguez, J. (1987). El Subsuelo de Bogotá y los Problemas de Cimentaciones The Subsoil of Bogotá and the Problems in Foundations. VIII CPSIF-PCSMFE, Cartagena, Colombia. NSR-10. (marzo de 2010). Reglamento Colombiano de Construcción Sismo Resistente. Bogotá D.C. Onyejekwe, S. (2012). Characterization of soil variability for reliability-based design. Doctoral Dissertations. Missouri University of Science and Technology Onyejekwe, S. and Ge, L. (2013). Scale of Fluctuation of Geotechnical Parameters Estimated from CPTu and Laboratory Test Data. American Society of Civil Engineers (ASCE). Parra L. J. (2019). Spatial geotechnical modeling of a lacustrine deposit using functional geostatistical análisis of CPTu tests. Maestría en Geotecnia. Universidad Nacional de Colombia, Sede Bogotá Pieczyńska-Kozłowska, J. M. (2015). Comparison Between Two Methods for Estimating the Vertical Scale of Fluctuation for Modeling Random Geotechnical Problems, Studia Geotechnica et Mechanica, 37(4), pp. 95–103 Phoon, K.K., Kulhawy, F.H. (1999). Characterization of Geotechnical Variability. Canadian Geotechnical Journal, Vol. 36, No. 4, 612-624. Phoon, K.-K., Asce, M., Quek, Ser-Tong, and An, P. (2003). Identification of Statistically Homogeneous Soil Layers Using Modified Bartlett Statistics. Journal of Geotechnical and Geoenvironmental Engineering. Vol 129 Issue 7. Púa, L. M. (2020). Reproducing the inherent variability of soils using a three-dimensional printer. International Journal of Physical Modelling in Geotechnics. Universidad de los Andes, Colombia. Ripley, B.D. (1981). Spatial statistics, John Wiley y Sons, New York. Robertson, P.K., Campanella, R.G. (1983). Interpretation of Cone Penetration Tests Sands and Clays. Canadian Geotechnical Journal, 20, 719-745. Robertson, P.K., Campanella, R.G., Gillespie, D. and Greig, J. (1986) Use of Piezometer Cone Data. Proceedings of American Society of Civil Engineers, ASCE, In-Situ 86 Specialty Conference, Blacksburg, 23-25 June 1986, 1263-1280. Robertson, P.K. (1990). Soil classification using the cone penetration test. Canadian Geotechnical Journal, 27(1), 151-158. Robertson, P.K. (2010). Soil behaviour type from the CPT: an update. Geotechnical News, 28(1), 35-41. Robertson, P. K. (2013). The James K. Mitchell Lecture: Interpretation of in-situ tests some insights. En C. y. Mayne (Ed.), Geotechnical and Geophysical Site Characterization 4. London: Taylor y Francis Group. Rodriguez, J. A., y Azuaje, J. G. (2018). Determinación de perfiles de velocidad de ondas de corte en la Ciudad de Bogotá, a partir de registros acelerográficos. XVI Congreso Colombiano de Geotecnia y IV Seminario Internacional de ingeniería Sismo Geotécnica. Paipa, Colombia Schnaid, F. (2009). In Situ Testing in Geomechanics: The Main Tests. Taylor and Francis. Shinozuka, M. and Deodatis, G. (1991). Simulation of Stochastic Processes by Spectral Representation. American Society of Mechanical Engineers. Song, Y., Shen, Z., Wu, P., y Viscarra Rossel, R. A. (2021). Wavelet geographically weighted regression for spectroscopic modelling of soil properties. Scientific Reports, 11(1). Soulié, M. (1983). Geostatistical applications in geotechnics. In Geostatistics for natural resources characterisation, Part 2, NATO ASI Series: 703-730. Spry, M.J., Kulhawy, F.H., Grigoriu, M.D. (1988). Reliability-Based Foundation Design for Transmission Line Structures: Geotechnical Site Characterization Strategy. Electric Power Research Institute Rpt. EL-5507(1), EPRI, Palo Alto. Stuedlein, A., Kramer, S.,Arduino, P & Holtz, R. (2012). Geotechnical Characterization and Random Field Modeling of Desiccated Clay. Journal of Geotechnical and Geoenvironmental Engineering Stuedlein, A. and Bong, T. (2017). Effect of Spatial Variability on Static and Liquefaction-Induced Differential Settlements. 31-51. Sulikowska, I., Mlynarek, Z. and Tschuschke, W. (1991). Measurement Errors inEvaluating Relative Density of Postflotation Sediment Using the CPT Method. Proc. 6th Int. Conf. Statistics and Probability in Soil and Struct. Eng., Mexico City, pp. 676-682. Torres, V., Vandenberghe, J., Hooghiemstra, H. (2005). An environmental reconstruction of the sediment infill of the Bogotá basin (Colombia) during the last 3 million years from abiotic and biotic proxies. Palaeogeography, Palaeoclimatology, 127–148. Uzielli, M. (2004). Variability of stress-normalized CPT parameters and application to seismic liquefaction initiation analysis. Ph.D. thesis. University of Florence, Italy. Uzielli, M., Vannucchi, G. and Phoon, K.K. (2005). Random field characterisation of stress-normalised cone penetration testing parameters. Geotechnique No. 1, 55. Uzielli, Marco y Lacasse, Suzanne y Nadim, Farrokh y Phoon, Kok-Kwang. (2006). Soil variability analysis for geotechnical practice. 2nd International Workshop on Characterisation and Engineering Properties of Natural Soils. 3. 1653-1752. Vanmarcke, E. H. (1977a). Probabilistic Modeling of Soil Profiles. J. Geotech. Engrg. Div., ASCE, Vol. 103, No. GT11, pp. 1227-1246. Vanmarcke, E. H. (1977b). Reliability of Earth Slopes. J. Geotech. Engrg. Div., ASCE, Vol. 103, No. GT11, pp. 1247-1265. Vanmarcke, E.H. (1978). Probabilistic Characterization of Soil Profiles. In Site Characterization and Exploration. Proceedings of the ASCE Specialty Workshop, Nothwestern University, Evanston, Illinois, 199-216. Vanmarcke, E. H. (1983). Random Fields: Analysis and Synthesis, M.I.T. Press, Cambridge, Mass., 382 p. Vanmarcke, E. H. (1984). Random Fields: New Concepts and Engineering Applications. Proc. of 4th ASCE Specialty Conf. on Probabilistic Mechanics and Structural Reliability, ASCE, Berkeley, California, pp. 7-17. Vivatrat, V. (1978). Cone Penetration in Clays, Doctoral Dissertation, MIT, Massachussettes, USA. Webster, R. y Beckett, P.H.T. (1968). Quality and Usefulness of Soil Maps. Nature, 219: 680-682. Wickremesinghe, Damika Sampath. (1989). Statistical Characterization of Soil Profiles Using in Situ Tests. Retrospective Theses and Dissertations, 1919-2007. T, University of British Columbia. Wickremesinghe D.S. and Campanella, R.G. (1991). Statistical methods of soil layer boundary location using the cone penetration test. Proc.: 6th Int. Conf. on Application of Statistics and Probability in Civil Engineering, pp. 636-644. Wickremesinghe D.S. and Campanella, R.G. (1993). Scale of Fluctuation as a Descriptor of Soil Variability. Proceedings of the Conference on Probabilistic Methods in Geotechnical Engineering, Canberra, Australia, February 10-12, 1993, ed. K.S. Li y S.-C. Lo, Balkema, Rotterdam, 233-239. Wu, T.H. (2003). Variations in Clay Deposits of Chicago. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication No. 121, 13-28. Xiao, D., Shi, Y., Brantley, S. L., Forsythe, B., DiBiase, R. A., Davis, K. J., Li, L. (2019). Predominant control of soil properties in storage-discharge relationship and threshold behavior in catchments derived from contrasting lithologies. Water Resources Research. U.S.A. |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc/4.0/ |
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info:eu-repo/semantics/openAccess |
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xxvii, 220 + Anexos( ) |
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application/pdf |
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Bogotá |
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Colombia |
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Universidad Nacional de Colombia |
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Bogotá - Ingeniería - Maestría en Ingeniería - Geotecnia |
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Facultad de Ingeniería |
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Bogotá, Colombia |
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Universidad Nacional de Colombia - Sede Bogotá |
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Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Barbosa Cruz, Edgard Robertdac4c2e6acf210f1a8a8bc41ceddd170Tapias Camacho, Mauricio Albertoa5e78c45e55469191484a108aae2e0e9Lozano Vargas, Germán Alberto94f1bb0d4750f8698dad61fa01acd4f52023-10-05T20:15:42Z2023-10-05T20:15:42Z2023https://repositorio.unal.edu.co/handle/unal/84773Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasLa variación espacial de las propiedades medidas de los suelos se debe principalmente a tres causas: la variabilidad inherente del suelo, los errores en la medición y la incertidumbre en la transformación de los datos. El presente trabajo fue enfocado en la variabilidad espacial inherente del suelo. Para estimar esta variabilidad en algunos suelos de la Sabana de Bogotá, fue necesario recolectar y analizar datos continuos de algunas de las zonas geotécnicas existentes en Bogotá, Colombia. Uno de los ensayos in situ que permite la estimación de la variabilidad, debido a la continuidad de sus registros, es el ensayo de penetración con cono (CPT), y por esta razón se recopilaron 487 sondeos de este tipo. Mediante métodos estadísticos como el coeficiente de correlación intraclase CCI, el estadístico T y el estadístico D² se definieron unidades homogéneas de suelo (UHS) para los tres datos de salida del ensayo CPT: la resistencia por punta, la resistencia por fuste y la presión de poros. Cada UHS fue sometida a un análisis de regresión que permitió obtener la línea de tendencia óptima. A partir de los residuales generados del análisis de tendencias y por medio de la teoría de los campos aleatorios, fue posible calcular la función de autocorrelación, generar modelos de autocorrelación y posteriormente estimar la escala de fluctuación de los datos de CPT, mediante la aplicación de los métodos más usuales publicados en la literatura geotécnica. La estacionariedad de cada una de las UHS fue comprobada por medio del estadístico de Bartlett modificado y su validez fue confirmada mediante el ensayo Tau de Kendall y mediante la prueba de rachas. Se definió que la escala de fluctuación de la resistencia por punta, la resistencia por fuste y la presión de poros de CPT para algunos suelos de la Sabana de Bogotá está en un rango entre 0.10 m y 0.40 m. (Texto tomado de la fuente)The spatial variation of soil properties is mainly due to three causes: inherent soil variability, errors in data measurement, and uncertainty in data transformation. This study focused on the inherent spatial variability of soil. To estimate this variability in some soils of the Bogota Savanna (Colombia), continuous data from some of the Bogotá’s geotechnical zones were collected and assessed. One of the tests that allows the estimation of variability, due to the continuity of its records, is the cone penetration test (CPT). In consequence, 487 CPT soundings were collected. Homogeneous soil units (UHS) were defined for the output CPT data: tip resistance, sleeve friction, and pore pressure, based on statistical method such as the intraclass correlation coefficient CCI, the statistic T, and the statistic D². Employing regression analysis, the optimal trendline for each UHS was obtained. From the residuals generated from the trend analysis, using the Random Field Theory, and applying the most common methods published in geotechnical literature, it was possible to calculate the autocorrelation function, generate autocorrelation models, and subsequently estimate the scale of fluctuation of CPT data. The stationarity of each UHS was verified using the modified Bartlett statistic, and their validity was confirmed by the Kendall Tau test and by the runs test. It was determined that the scale of fluctuation of CPT tip resistance, sleeve friction, and pore pressure for some soils of the Bogota Savanna ranges from 0.10 m to 0.40 m.MaestríaMagíster en Ingeniería - GeotecniaModelación y análisis en geotecniaxxvii, 220 + Anexos( )application/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - GeotecniaFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afines::624 - Ingeniería civilUso de la tierra -planificaciónEspacios abiertosLand useOpen spacesVariabilidad espacialVariabilidad inherenteEscala de fluctuaciónSabana de BogotáTeoría de los campos aleatoriosModelo y función de autocorrelaciónAnálisis de tendenciasSpatial variabilityInherent variabilityAutocorrelation functionBogota savannaRandom field theoryTrend analysisScale of fluctuationAnálisis de la variabilidad inherente de algunos perfiles de suelo de la formación Sabana de Bogotá basado en la teoría de campos aleatoriosAnalysis of the inherent variability of some soil profiles of the Bogota Savanna based on random field theoryTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesishttp://purl.org/coar/version/c_b1a7d7d4d402bcceTexthttp://purl.org/redcol/resource_type/TMBogotáColombiaAgterberg, F.B. (1970). Autocorrelation Functions in Geology. In Geostatistics – a colloquium: Proceedings of a Colloquium on Geostatistics. University of Kansas.Alonso, E. E., Krizek, R.J (1975). Stochastic formulation of soil properties. Proceedings of the 2nd International Conference on Applications of Statistics and Probability to Soil and Structural Engineering, Vol.1, Aachen Germany, pp. 9 – 32.Baecher, G.B. (1987). Statistical Analysis of Geotechnical Data. Report No. GL-87-1, U.S. Army Engineer Waterways Experiment Station, Vicksburg, VA.Barón, M. (2021). Calibración del ensayo CPTu para el depósito lacustre de Bogotá. Maestría en Geotecnia. Universidad Nacional de Colombia. Sede Bogotá.Biswas, A., Si, B. C. (2011). Application of continuous wavelet transform in examining soil spatial variation: A review. In Mathematical Geosciences (Vol. 43, Issue 3, pp. 379–396).Stuedlein, A. & Bong, T. (2017). Effect of Spatial Variability on Static and Liquefaction-Induced Differential Settlements. 31-51.Brockwell, P.J., Davis, R.A. (1991). ITSM: An interactive time series modeling package for the PC, Springer-Verlag, New York, 104 p.Bury, K.V. (1975). Statistical Models in Applied Science. John Wiley, Hoboken Campanella, R.G., Wickremesinghe, D.S., Robertson, P.K. (1987). Statistical Treatment of Cone Penetrometer Test Data. Proceedings of the 5th International Conference on Applications of Statistics and Probability in Soil and Structural Engineering, Vancouver, BC, Canada, Vol. 2, 1011-1019.Cami, B. and Javankhoshdel, S. (2020). ARMA Models to Measure the Scale of Fluctuation from CPT Data. The Open Construction and Building Technology Journal, 14(1), pp. 230–236.Cao, Z. and Wang, Y. (2014). Bayesian model comparison and selection of spatial correlation functions for soil parameters, Structural Safety, 49, pp. 10–17Chenari, R. Seyedeyn M.S., Faraji, S. and Kenarsari, A. (2012). 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Bogotá, Colombia.Douglas, B.J. and Olsen, R.S. (1981). Soil Classification Using Electric Cone Penetrometer. Proceedings of Conference on Cone Penetration Testing and Experience, St. Louis, 209-227.Fenton, G.A. (1999a). Estimation for Stochastic Soil Models. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 125, No. 6, 470-485.Fenton, G.A. (1999b). Random Field Modeling of CPT Data. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 125, No. 6, 486-498.Fenton, G.A., Vanmarcke, E.H. (2003). Random Field Characterization of NGES Data. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication. No. 121, 61-78.FOPAE. (2010). Zonificación de la respuesta sísmica de Bogotá para el diseño sismo resistente de edificaciones. Fondo de Prevención y Atención de Emergencias. Bogotá, Colombia.Garzón, L. X., Caicedo, B., Sánchez-Silva, M., y Phoon, K. K. (2015). 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Inaccuracies Associated with Estimating Random Measurement Errors. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, Vol. 123, No. 5, 393-401Kulatilake, P.H., Ghosh, A. (1988). An Investigation Into Accuracy of Spatial Variation Estimation Using Static Cone Penetrometer Data. Proceedings of the 1st International Symposium on Penetration Testing (ISOPT-1). Orlando, FL, U.S.A.Kulatilake, P.H. (1991). Discussion on “Probabilistic Potentiometric Surface Mapping.” Journal of Geotechnical Engineering, ASCE, Vol. 117, No. 9, 1458-1459.Kulatilake, P.H., UM, J.G. (2003). Spatial Variation of Cone Tip Resistance for the Clay Site at Texas AyM University. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication No. 121, 41-60.Kulhawy, F.H., Birgisson, B., Grigoriu, M.D. (1992). Reliability-Based Foundation Design for Transmission Line Structures: Transformation Models for In-Situ Tests. Report No. EL-5507(4), Electric Power Research Institute, Palo Alto, CA.Lacasse, S., Nadim, F. (1996). Uncertainties in Characterizing Soil Properties. Uncertainty in the Geologic Environment: From Theory to Practice. ASCE Geotechnical Special Publication No. 58, Madison, WI, U.S.A., 49-75.Li, K. S. and Lee, I. K. (1991). The Assessment of Geotechnical Safety. In Selected Topics in Geotechnical Engineering - Lumb Volume, Li, K. S. (ed.), Dept. Civil and Maritime Engrg., UNSW, ADFA, Canberra, pp. 195-229.Li, K.S. (1991). Probabilistic Potentiometric Surface Mapping. Journal of Geotechnical Engineering, ASCE, Vol. 117, No. 9, 1457-1458.Spacagna, L., de Fouquet, C., y Russo, G. (2015). Interpretation of CPTU Tests with Statistical and Geostatistical Methods.Lumb. P. (1966). The variability of Natural Soils. Canadian Geotechnical Journal. 3. 74-97.Lumb, P. and Holt, J. K. (1968). 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El Subsuelo de Bogotá y los Problemas de Cimentaciones The Subsoil of Bogotá and the Problems in Foundations. VIII CPSIF-PCSMFE, Cartagena, Colombia.NSR-10. (marzo de 2010). Reglamento Colombiano de Construcción Sismo Resistente. Bogotá D.C.Onyejekwe, S. (2012). Characterization of soil variability for reliability-based design. Doctoral Dissertations. Missouri University of Science and TechnologyOnyejekwe, S. and Ge, L. (2013). Scale of Fluctuation of Geotechnical Parameters Estimated from CPTu and Laboratory Test Data. American Society of Civil Engineers (ASCE).Parra L. J. (2019). Spatial geotechnical modeling of a lacustrine deposit using functional geostatistical análisis of CPTu tests. Maestría en Geotecnia. Universidad Nacional de Colombia, Sede BogotáPieczyńska-Kozłowska, J. M. (2015). Comparison Between Two Methods for Estimating the Vertical Scale of Fluctuation for Modeling Random Geotechnical Problems, Studia Geotechnica et Mechanica, 37(4), pp. 95–103Phoon, K.K., Kulhawy, F.H. (1999). Characterization of Geotechnical Variability. Canadian Geotechnical Journal, Vol. 36, No. 4, 612-624.Phoon, K.-K., Asce, M., Quek, Ser-Tong, and An, P. (2003). Identification of Statistically Homogeneous Soil Layers Using Modified Bartlett Statistics. Journal of Geotechnical and Geoenvironmental Engineering. Vol 129 Issue 7.Púa, L. M. (2020). Reproducing the inherent variability of soils using a three-dimensional printer. International Journal of Physical Modelling in Geotechnics. Universidad de los Andes, Colombia.Ripley, B.D. (1981). Spatial statistics, John Wiley y Sons, New York.Robertson, P.K., Campanella, R.G. (1983). Interpretation of Cone Penetration Tests Sands and Clays. 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Lo, Balkema, Rotterdam, 233-239.Wu, T.H. (2003). Variations in Clay Deposits of Chicago. Probabilistic Site Characterization at the National Geotechnical Experimentation Sites, ed. G.A. Fenton and E.H. Vanmarcke, ASCE Geotechnical Special Publication No. 121, 13-28.Xiao, D., Shi, Y., Brantley, S. L., Forsythe, B., DiBiase, R. A., Davis, K. J., Li, L. (2019). Predominant control of soil properties in storage-discharge relationship and threshold behavior in catchments derived from contrasting lithologies. Water Resources Research. U.S.A.BibliotecariosEstudiantesGrupos comunitariosInvestigadoresMaestrosMedios de comunicaciónPúblico generalLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84773/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1024509332.2023.pdf1024509332.2023.pdfTesis de Maestría en Ingeniería - Geotecniaapplication/pdf9954192https://repositorio.unal.edu.co/bitstream/unal/84773/19/1024509332.2023.pdfe9b814f581f4f98356d45d58e93254a3MD519ANEXO A Recopilación de sondeos.pdfANEXO A Recopilación de sondeos.pdfAnexo A. Recopilación de sondeosapplication/pdf940909https://repositorio.unal.edu.co/bitstream/unal/84773/3/ANEXO%20A%20Recopilaci%c3%b3n%20de%20sondeos.pdf6484514366f5872940c5767df3fda19eMD53ANEXO B Registros de exploración.rarANEXO B Registros de exploración.rarAnexo B. 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