TY - JOUR
T1 - A database of saturated hydraulic conductivity of fine-grained soils
T2 - probability density functions
AU - Feng, Shuyin
AU - Vardanega, Paul J.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Saturated hydraulic conductivity is a key soil mechanics parameter which has widespread use in many geotechnical applications. In order to set up stochastic analyses, geotechnical modellers require databases to calibrate the parameter ranges and distributions employed. This letter uses a recently compiled database of saturated hydraulic conductivity measurements called FG/KSAT-1358 and reports on the fitting of various probability density functions to the data of void ratio, liquid limit, water content ratio and the negative natural logarithm of ksat. It is shown that the best fit distribution is the lognormal for void ratio, while the loglogistic distribution is most favoured for liquid limit and water content ratio, and the best fit distribution for -ln[ksat(m/s)] is the logistic function. The data of -ln[ksat(m/s)] is then subdivided according to liquid limit level, silt or clay classification, type of hydraulic conductivity test used and sample preparation/condition. When some subdivisions of the database are analysed, the best fit distribution is more variable with GEV and logistic being the most favoured for most of the studied subsets.
AB - Saturated hydraulic conductivity is a key soil mechanics parameter which has widespread use in many geotechnical applications. In order to set up stochastic analyses, geotechnical modellers require databases to calibrate the parameter ranges and distributions employed. This letter uses a recently compiled database of saturated hydraulic conductivity measurements called FG/KSAT-1358 and reports on the fitting of various probability density functions to the data of void ratio, liquid limit, water content ratio and the negative natural logarithm of ksat. It is shown that the best fit distribution is the lognormal for void ratio, while the loglogistic distribution is most favoured for liquid limit and water content ratio, and the best fit distribution for -ln[ksat(m/s)] is the logistic function. The data of -ln[ksat(m/s)] is then subdivided according to liquid limit level, silt or clay classification, type of hydraulic conductivity test used and sample preparation/condition. When some subdivisions of the database are analysed, the best fit distribution is more variable with GEV and logistic being the most favoured for most of the studied subsets.
KW - Saturated Hydraulic Conductivity
KW - Probability Density Functions
KW - Database
KW - Fine-grained soils
KW - Akaike information criterion
KW - corrected Akaike information criterion
UR - http://www.scopus.com/inward/record.url?scp=85070869346&partnerID=8YFLogxK
U2 - 10.1080/17499518.2019.1652919
DO - 10.1080/17499518.2019.1652919
M3 - Article (Academic Journal)
AN - SCOPUS:85070869346
SN - 1749-9518
VL - 13
SP - 255
EP - 261
JO - Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
JF - Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
IS - 4
ER -