Evaluation of liquefaction potential of soil using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@PhdThesis{Muduli:thesis,
  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.",
  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",
}

Genetic Programming entries for Pradyut Kumar Muduli

Citations