Application of micropolar plasticity to post failure analysis in geomechanics

A micropolar elastoplastic model for soils is formulated and a series of finite element analyses are employed to demonstrate the use of a micropolar continuum in overcoming the numerical difficulties encountered in application of finite element method in standard Cauchy–Boltzmann continuum. Three examples of failure analysis involving a deep excavation, shallow foundation, and a retaining wall are presented. In all these cases, it is observed that the length scale introduced in the polar continuum regularizes the incremental boundary value problem and allows the numerical simulation to be continued until a clear collapse mechanism is achieved. The issue of grain size effect is also discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

SANICLAY: simple anisotropic clay plasticity model

SANICLAY is a new simple anisotropic clay plasticity model that builds on a modification of an earlier model with an associated flow rule, in order to include simulations of softening response under undrained compression following K_o consolidation. Non‐associativity is introduced by adopting a yield surface different than the plastic potential surface. Besides, the isotropic hardening of the yield surface both surfaces evolve according to a combined distortional and rotational hardening rule, simulating the evolving anisotropy. Although built on the general premises of critical state soil mechanics, the model induces a critical state line in the void ratio–mean effective stress space, which is a function of anisotropy. To ease interpretation, the model formulation is presented firstly in the triaxial stress space and subsequently, its multiaxial generalization is developed systematically, in a form appropriate for implementation in numerical codes. The SANICLAY is shown to provide successful simulation of both undrained and drained rate‐independent behaviour of normally consolidated sensitive clays, and to a satisfactory degree of accuracy of overconsolidated clays. The new model requires merely three constants more than those of the modified Cam clay model, all of which are easily calibrated from well‐established laboratory tests following a meticulously presented procedure. Copyright © 2006 John Wiley & Sons, Ltd.     

A study of crude oil‐degrading bacteria from mangrove forests in the Persian Gulf

Mangroves are coastal ecosystems, found in tropical and subtropical regions around the world. They are found in the transitional zones between land, sea, and rivers. Petroleum hydrocarbons are the most common environmental pollutants, and oil spills pose a great hazard to mangroves forests. This research was focused on the isolation and characterization of crude oil‐degrading bacteria from mangrove ecosystems at the Persian Gulf. Sixty‐one crude oil‐degrading bacteria were isolated from mangrove samples (plant, sediment, and seawater) that enriched in ONR7a medium with crude oil as only carbon source. Some screening tests such as growth at high concentration of crude oil, bioemulsifier production, and surface hydrophobicity were done to select the most efficient strains for crude oil degradation. Molecular identification of strains was carried out by amplification of the 16S rRNA gene by PCR. The results of this study were indicated that the quantity of crude oil‐degrading bacteria was higher in the root of mangrove plants compare to other mangrove samples (sediment and seawater). Also, identification results confirmed that these isolated strains belong to Vibrio sp. strain NW4, Idiomarina sp. strain BW32, Kangiella sp. strain DP40, Marinobacter sp. strain DW44, Halomonas sp. strain BS53, and Vibrio sp. strain DS35. The application of bioremediation strategies with these bacteria can reduce crude oil pollution in this important marine environment.     

Pseudostatic approach for seismic analysis of pile group

This paper evaluates a simple approximate pseudostatic method for estimating the maximum internal forces and horizontal displacements of pile group subjected to lateral seismic excitation. The method involves two main steps: (1) computation of the free-field soil movements caused by the earthquake, and (2) the analysis of the response of the pile group based on the maximum free-field soil movements (considered as static movements) as well as a static loading at the pile head, which depends on the computed spectral acceleration of the structure being supported. The methodology takes into account the effects of group interaction and soil yielding at pile–soil interface. The applicability of this approach has been validated by a similar approach for single piles and then verified by both experimental centrifuge models of pile-supported structures and field measurements of Ohba-Ohashi Bridge in Japan. It is demonstrated that the proposed method yields reasonable estimates of the pile maximum moment, shear, and horizontal displacement for many practical cases despite of its simplicity. Limitations and reliability of the methodology are discussed and some practical conclusions on the performance of the proposed approach are presented.     

Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.