Comparison Between Two Methods for Estimating the Vertical Scale of Fluctuation for Modeling Random Geotechnical Problems

Open access

Abstract

The design process in geotechnical engineering requires the most accurate mapping of soil. The difficulty lies in the spatial variability of soil parameters, which has been a site of investigation of many researches for many years. This study analyses the soil-modeling problem by suggesting two effective methods of acquiring information for modeling that consists of variability from cone penetration test (CPT). The first method has been used in geotechnical engineering, but the second one has not been associated with geotechnics so far. Both methods are applied to a case study in which the parameters of changes are estimated. The knowledge of the variability of parameters allows in a long term more effective estimation, for example, bearing capacity probability of failure.

[1] Alonso E., Krizek R.J., Stochastic formulation of soil properties, Proc. 2nd Int. Conf. on Appl. of Statistics and Probability in Soil and Struct. Eng., Aachen; 1975, Vol. II, 9–32.

[2] Baecher G.B., Christian J.T., Reliability and Statistics in Geotechnical Engineering, West Sussex, John Wiley & Sons; 2003.

[3] Bagińska I., Kupis R., Pochrań Z., Badania sonda statyczna CPTU gruntu nasypowego oraz rodzimego celem analizy stanu i odkształacalności nasypu, Politechnika Wrocławska, Instytut Geotechniki i Hydroechniki, Raport Serii U 18/12, 2012.

[4] Campanella R.G., Wickremesinghe D., Robertson P.K., Statistical Treatment of Cone Penetration Test Data, Proceedings of the 5th International Conference on Application of Statistics and Probability in Soil and Structure, Vancouver, edited by DL. Blochley, 1011–1019, Vancouver, BC. 1987.

[5] Cao Z., Wang Y., Bayesian model comparison and selection of spatial correlation functions for soil parameters, Structural Safety, 10.1016/j.strusafe.2013.06.003, 10-17.

[6] Degroot D.J., Baecher G.B., Estimating Autocovariance of In-situ Soil Properties, Journal of the Geotechnical Engineering Division, ASCE 1993; 119(1): 147–166. DOI: 10.1061/(ASCE)0733-9410(1993)119:1(147).

[7] Fenton G.A., Estimation for Stochastic Soil Models, Journal of the Geotechnical Engineering Division, ASCE 1999, 125(6), 470–485. DOI: 10.1061/(ASCE)1090-0241(1999)125:6(470).

[8] Fenton G.A., Griffiths D.V., Risk assessment in geotechnical engineering, John Wiley & Sons, Hoboken, N.J., 2008.

[9] Hicks M.A., Onisiphorou C., Stochastic Evaluation of Static Liquefaction in a Predominantly Dilative Sand Fill, Geotechnique, 2005, 55(2), 123–133. DOI: 10.1680/GEOT.2005.55.2.123.

[10] Jaksa M.B., Kaggwa W.S., Brooker P.I., Geostatistical Modeling of the Undrained Shear Stength of Stiff, Overconsolidated, Clay, Proceedings of Conference on Probabilistic Methods in Geotechnical Engineering, Canberra, eddited by KS. Li and SCR. Lo, Rotterdam, Brookfield, A.A. Balkema, 1993, 185–194.

[11] Lloret M.M.A., Hicks M.A., Wong S.Y., Soil Characterisation of an Artificial Island Accounting for Heterogeneity, Proceedings of GeoCongress 2012, San Francisco, ed. by Hryciw R.D., Athanastopoulos-Zekkos A. and Yesiller N., 2816–2825. Reston: ASCE.

[12] Lloret-Cabot M.M.A., Hicks M.A., Nuttall J.D., Investigating the Scales of Fluctuation of an Artificial Sand Island, Proceedings of the International Conference, Geotechnical Installations in Geotechnical Engineering, 2013, Rotterdam, edited by M.A. Hicks, J. Dijkstra, M. Lloret-Cabot, and M. Karstunen, 192–197. Rotterdam: CRC Press Taylor and Francis Group.

[13] Lloret-Cabot M.M.A., Fenton G.A., Hicks M.A., On the estimation of scale of fluctuation in geostatistics, Georisk: 2014 Assessment and Management of Risk for Engineered Systems and Geohazards, DOI: 10.1080/17499518.2013.871189.

[14] Lumb P., The variability of natural soils, Canadian Geotechnical Journal, 1966, 3(2), 74–97.

[15] Lumb P., Safety factors and the probability distributions of soil strength, Canadian Geotechnical Journal, 1970, 7(3), 225–242.

[16] Lumb P., Spatial variability of soil properties, Proc. 2nd Int. Conf. on Appl. of Statistics and Probability in Soil and Struct. Eng. (ICASP) Aachen, 1975, Vol. II, 397–422.

[17] Puła W., Zastosowanie teorii niezawodności konstrukcji do oceny bezpieczeństwa fundamentów, Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 2004.

[18] Rice S., Matematical Analysis of Random Noise, Bell System Technical Journal, 1944, 25 (3–4).

[19] Schultze E., Frequency distributions and correlations of soil properties, [in:] P. Lumb (ed.), Proc. 1st Int. Conf. on Appl. of Statistics and Probability in Soil and Struct. Eng. (ICASP), Hong-Kong. University Press, Hong-Kong 1972, 372–387.

[20] Stuedlein A.W., Kramer S.L., Arduino P., Holtz R.D., Geotechnical Characterization and Random Field Modeling of Desiccated Clay, Journal of Geotechnical and Geoenvironmental Engineering, ASCE 2012, 1301-1313. DOI: 10.1061/(ASCE)GT.1943-5606.0000723.

[21] Uzielli M., Vannucchi G., Phoon K.-K., Random Field Characterisation of Stress-normalised Cone Penetration Testing Parameters, Geotechnique, 2005, 55(1), 3–20, DOI: 10.1680/geot.2005.55.1.3.

[22] Vanmarcke E.H., Probabilistic Modeling of Soil Profiles, Journal of the Geotechnical Engineering Division, ASCE 1977a, 103(GT11), 1227–1246.

[23] Vanmarcke E.H., Reliability of earth slopes, Journal of Geotechnical Division, ASCE 1977b; 103(GT11), 1247–1265.

[24] Vanmarcke E.H., Random FieldsAnalysis and Synthesis, Cambridge, MIT Press, 1983.

[25] Vessia G., Casini F., Springman S., Mechanical characterisation of lacustrine clay by interpreting spatial variability in CPTU measurements, Proc. 11th Int. Conf. on Appl. of Statistics and Probability in Soil and Struct. Eng. (ICASP), Zurich 2011.

[26] Wackernagel H., Multivariate Geostatistics: An Introduction with Applications, Germany, Springer, 2003.

[27] Wickremesinghe D., Camapanella R.G., Scale of Fluctuation as a Descriptor of Soil Variability, Proceedings of Conference on Probabilistic Methods in Geotechnical Engineering, Canberra, K.S. Li, S.-C.R. Lo (eds.), 233–239, A.A. Balkema, Rotterdam 1993.

Studia Geotechnica et Mechanica

The Journal of Wrocław University of Science and Technology and AGH University of Science and Technology

Journal Information

CiteScore 2018: 1.03

SCImago Journal Rank (SJR) 2018: 0.213
Source Normalized Impact per Paper (SNIP) 2018: 1.106

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 155 119 15
PDF Downloads 62 56 3