Revisiting the existence of an effective stress for wet granular soils with micromechanics

A possible effective stress variable for wet granular materials is numerically investigated based on an adapted discrete element method (DEM) model for an ideal three‐phase system. The DEM simulations consider granular materials made of nearly monodisperse spherical particles, in the pendular regime with the pore fluid mixture consisting of distinct water menisci bridging particle pairs. The contact force‐related stress contribution to the total stresses is isolated and tested as the effective stress candidate for dense or loose systems. It is first recalled that this contact stress tensor is indeed an adequate effective stress that describes stress limit states of wet samples with the same Mohr‐Coulomb criterion associated with their dry counterparts. As for constitutive relationships, it is demonstrated that the contact stress tensor used in conjunction with dry constitutive relations does describe the strains of wet samples during an initial strain regime but not beyond. Outside this so‐called quasi‐static strain regime, whose extent is much greater for dense than loose materials, dramatic changes in the contact network prevent macroscale contact stress‐strain relationships to apply in the same manner to dry and unsaturated conditions. The presented numerical results also reveal unexpected constitutive bifurcations for the loose material, related to stick‐slip macrobehavior.     

Mooring optimization of floating platforms using a genetic algorithm

This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:

• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;

• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.

Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented.     

Investigation into the effect of fault properties on wave transmission

The estimation of wave transmission across the fractured rock masses is of great importance for rock engineers to assess the stability of rock slopes in open pit mines. Presence of fault, as a major discontinuity, in the jointed rock mass can significantly impact on the peak particle velocity and transmission of blast waves, particularly where a fault contains a thick infilling with weak mechanical properties. This paper aims to study the effect of fault properties on transmission of blasting waves using the distinct element method. First, a validation study was carried out on the wave transmission across a single joint and different rock mediums through undertaking a comparative study against analytical models. Then, the transmission of blast wave across a fault with thick infilling in the Golgohar iron mine, Iran, was numerically studied, and the results were compared with the field measurements. The blast wave was numerically simulated using a hybrid finite element and finite difference code which then the outcome was used as the input for the distinct element method analysis. The measured uplift of hanging wall, as a result of wave transmission across the fault, in the numerical model agrees well with the recorded field measurement. Finally, the validated numerical model was used to study the effect of fault properties on wave transmission. It was found that the fault inclination angle is the most effective parameter on the peak particle velocity and uplift. Copyright © 2017 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.     

A probabilistic approach for computing water retention of particulate systems from statistics of grain size and tessellated pore network

The paper offers an analytical determination of the hydraulic properties of an unsaturated soil with reference to its retention curve, which describes the relationship between the volumetric water content and capillarity through matric suction. The analysis combines a particulate approach focused on the physics at the pore scale, including microstructural aspects, with a probabilistic approach where the void space and grain size are considered as random variables. In the end, the soil water characteristic curve of an unsaturated granular medium along a drying path can be derived analytically based on the sole information of particle size distribution. The analysis hinges on the tessellation of a wet granular system into an assemblage of tetrahedral unit cells revealing a pore network upon which capillary physics are computed with respect to pore throat invasion by a non-wetting fluid with evolving pendular capillary bridges. The crux of the paper is to pass from particle size probability distribution to a matching void space distribution to eventually reveal key information such as void cell and solid volume statistics. Making reasonable statistically based assumptions to render calculations tractable, the water retention curve can be readily constructed. Model predictions compare quite favourably with experimental data available for actual soils, especially in the high saturation range. Having a sound scientific basis, the model can be made amenable to address a variety of soils with a wider range of particle sizes.     

Micromechanical approach to swelling behavior of capillary-porous media with coupled physics

A detailed multiscale analysis is presented of the swelling phenomenon in unsaturated clay-rich materials in the linear regime through homogenization. Herein, the structural complexity of the material is formulated as a three-scale, triple porosity medium within which microstructural information is transmitted across the various scales, leading ultimately to an enriched stress-deformation relation at the macroscopic scale. As a side note, such derived relationship leads to a tensorial stress partitioning that is reminiscent of a Terzaghi-like effective stress measure. Otherwise, a major result that stands out from previous works is the explicit expression of swelling stress and capillary stress in terms of micromechanical interactions at the very fine scale down to the clay platelet level, along with capillary stress emerging due to interactions between fluid phases at the different scales, including surface tension, pore size, and morphology. More importantly, the swelling stress is correlated with the disjoining forces due to electrochemical effects of charged ions on clay minerals and van der Waals forces at the nanoscale. The resulting analytical expressions also elucidate the role of the various physics in the deformational behavior of clayey material. Finally, the capability of the proposed formulation in capturing salient behaviors of unsaturated expansive clays is illustrated through some numerical examples.     

Integrating cellular automata,artificial neural network,and fuzzy set theory to simulate threatened orchards: application to Maragheh,Iran

Urbanization processes challenge the growth of orchards in many cities in Iran. In Maragheh, orchards are crucial ecological, economical, and tourist sources. To explore orchards threatened by urban expansion, this study first aims to develop a new model by coupling cellular automata (CA) and artificial neural network with fuzzy set theory (CA–ANN–Fuzzy). While fuzzy set theory captures the uncertainty associated with transition rules, the ANN considers spatial and temporal nonlinearities of the driving forces underlying the urban growth processes. Second, the CA–ANN–Fuzzy model is compared with two existing approaches, namely a basic CA and a CA coupled with an ANN (CA–ANN). Third, we quantify the amount of orchard loss during the last three decades as well as for the upcoming years up to 2025. Results show that CA–ANN–Fuzzy with 83% kappa coefficient performs significantly better than conventional CA (with 51% kappa coefficient) and CA–ANN (with 79% kappa coefficient) models in simulating orchard loss. The historical data shows a considerable loss of 26% during the last three decades, while the CA–ANN–Fuzzy simulation reveals a considerable future loss of 7% of Maragheh’s orchards in 2025 due to urbanization. These areas require special attention and must be protected by the local government and decision-makers.