- author = "Pradyut Kumar Muduli",
- title = "Evaluation of liquefaction potential of soil using genetic programming",
- school = "Department of Civil Engineering, National Institute of Technology, Rourkela",
- year = "2013",
- address = "Rourkela 769008, Odisha, India",
- month = aug,
- keywords = "genetic algorithms, genetic programming, Liquefaction, Niigata, Japan and 1964 Alaska, USA, earthquakes, standard penetration test (SPT) and cone penetration test (CPT).",
-
URL = "
http://ethesis.nitrkl.ac.in/5664/",
-
URL = "
http://ethesis.nitrkl.ac.in/5664/1/509ce804-_PKMRevised100214.pdf",
- size = "251 pages",
- abstract = "Out of the various seismic hazards, soil liquefaction is a major cause of both loss of life and damage to infrastructures and lifeline systems. Soil liquefaction phenomena have been noticed in many historical earthquakes after first large scale observations of damage caused by liquefaction in the 1964 Niigata, Japan and 1964 Alaska, USA, earthquakes. Due to difficulty in obtaining high quality undisturbed samples and cost involved therein, in-situ tests, standard penetration test (SPT) and cone penetration test (CPT), are being preferred by geotechnical engineers for liquefaction potential evaluation with limited use of other in-situ tests like shear wave velocity tests and Baker penetration tests. The liquefaction evaluation in the deterministic framework is preferred by the geotechnical engineering professionals because of its simple mathematical approach with minimum requirement of data, time and effort. However, for important life line structures, there is a need of probabilistic and reliability methods for taking risk based design decisions. In recent years, soft computing techniques such as artificial neural network (ANN), support vector machine (SVM) and relevance vector machine (RVM) have been successfully implemented for evaluation liquefaction potential with better accuracy compared to available statistical methods. In the recent past, evolutionary soft computing technique genetic programming (GP) based on Darwinian theory of natural selection is being used as an alternate soft computing technique. The objective of the present research is to develop deterministic, probabilistic and reliability-based models to evaluate the liquefaction potential of soil using multi-gene genetic programming (MGGP) based on post liquefaction SPT and CPT database. Here, the liquefaction potential is evaluated and expressed in terms of liquefaction field performance indicator, referred as a liquefaction index (LI) and factor of safety against the occurrence of liquefaction (Fs). Further, the developed LIp models have been used to develop both SPT and CPT-based CRR models. These developed CRR models in conjunction with the widely used CSR7.5 model, form the proposed MGGP-based deterministic methods. The efficiency of both the developed SPT and CPT-based deterministic models has been compared with that of available statistical and ANN-based models on the basis of independent database. Two examples have been solved to show the use of developed deterministic methods to find out the extent of ground improvement works needs to be done in terms of N1,60 and qc1N using the adopted factor of safety.",
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abstract = "The probabilistic evaluation of liquefaction potential
has been performed where liquefaction potential is
expressed in terms of probability of liquefaction (PL)
and the degree of conservatism associated with
developed deterministic models are quantified in terms
of PL. Using Bayesian theory of conditional probability
the Fs is related with the PL through the developed
mapping functions. The developed SPT and CPT-based
probabilistic models have been compared in terms of the
rate of successful prediction within different limits
of PL, with that of the available statistical and
ANN-based probabilistic models. Two examples, one from
SPT and the other from CPT-based data, have been
illustrated to show the use of developed probabilistic
methods to take risk-based design decision for a site
susceptible to liquefaction.
Further reliability analysis following first order reliability method (FORM) has been carried out using high quality SPT and CPT database, which considers both model and parameter uncertainties. The uncertainties of input parameters were obtained from the database. But, a rigorous reliability analysis associated with the Bayesian mapping function approach was followed to estimate model uncertainty of the limit state, which has been represented by a lognormal random variable, and is characterized in terms of its two statistics, namely, the mean and the coefficient of variation. Four examples, two from SPT data (one liquefied and the other non-liquefied case) and the other two from CPT data (one liquefied and the other non-liquefied case), have been illustrated to show the procedure of reliability-based liquefaction potential evaluation in terms of notional probability of liquefaction (PL) considering the corresponding true model uncertainty as obtained for SPT and CPT-based limit state models in the analysis.
The development of compact and comprehensive model equation using deterministic methods based on both SPT and CPT data will enable geotechnical professional to use it with confidence and ease. The presentation of probabilistic methods in conjunction with deterministic factor of safety (Fs) value gives the measure of probability of liquefaction corresponding to particular Fs. The present works also illustrate the effect of model and parameter uncertainties while discussing the reliability analysis. Design harts have been presented and discussed with examples using both SPT and CPT data.",
- notes = "Supervisor: Sarat Kumar Das",
