Fully coupled elastoplastic hydro-mechanical analysis of unsaturated porous media using a meshfree method

This paper presents the first application of an advanced meshfree method, ie, the edge-based smoothed point interpolation method (ESPIM), in simulation of the coupled hydro-mechanical behaviour of unsaturated porous media. In the proposed technique, the problem domain is spatially discretised using a triangular background mesh, and the polynomial point interpolation method combined with a simple node selection scheme is adopted for creating nodal shape functions. Smoothing domains are formed on top of the background mesh, and a constant smoothed strain, created by applying the smoothing operation over the smoothing domains, is assigned to each smoothing domain. The deformation and flow models are developed based on the equilibrium equation of the mixture, and linear momentum and mass balance equations of the fluid phases, respectively. The effective stress approach is followed to account for the coupling between the flow and deformation models. Further coupling among the phases is captured through a hysteretic soil water retention model that evolves with changes in void ratio. An advanced elastoplastic constitutive model within the context of the bounding surface plasticity theory is employed for predicting the nonlinear behaviour of soil skeleton. Time discretisation is performed by adopting a three-point discretisation method with growing time steps to avoid temporal instabilities. A modified Newton-Raphson framework is designed for dealing with nonlinearities of the discretised system of equations. The performance of the numerical model is examined through a number of numerical examples. The state-of-the-art computational scheme developed is useful for simulation of geotechnical engineering problems involving unsaturated soils.     

A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping

In this paper, we evaluate the predictive performance of an adaptive neuro-fuzzy inference system (ANFIS) using six different membership functions (MF). In combination with a geographic information system (GIS), ANFIS was used for land subsidence susceptibility mapping (LSSM) in the Marand plain, northwest Iran. This area is prone to droughts and low groundwater levels and subsequent land subsidence damages. Therefore, a land subsidence inventory database was created from an extensive field survey. Areas of land subsidence or areas showing initial signs of subsidence were used for training, while one-third of inventory database were reserved for testing and validation. The inventory database randomly divided into three different folds of the same size. One of the folds was chosen for testing and validation. Other two folds was used for training. This process repeated for every fold in the inventory dataset. Thereafter, land subsidence related factors, such as hydrological and topographical factors, were prepared as GIS layers. Areas susceptible to land subsidence were then analyzed using the ANFIS approach, and land subsidence susceptibility maps were created, whereby six different MFs were applied. Lastly, the results derived from each MF were validated with those areas of the land subsidence database that were not used for training. Receiver operating characteristics (ROC) curves were drawn for all LSSMs, and the areas under the curves were calculated. The ROC analyses for the six LSSMs yielded very high prediction values for two out of the six methods, namely the difference of DsigMF (0.958) and GaussMF (0.951). The integration of ANFIS and GIS generally led to high LSSM prediction accuracies. This study demonstrated that the choice of training dataset and the MF significantly affects the results.     

Risk assessment of polycyclic aromatic hydrocarbons in the West Port semi-enclosed basin (Malaysia)

Sediment samples collected from the West Port, the west coastal waters of Malaysia, were analyzed by standard methods to determine the degree of hydrocarbon contamination and identify the sources of polyaromatic hydrocarbons (PAHs). Concentrations of PAHs in the port sediments ranged from 100.3 to 3,446.9 μg/kg dw. The highest concentrations were observed in stations close to the coastline, locations affected by intensive shipping activities and industrial input. These were dominated by high-molecular-weight PAHs (4–6 rings). Source identification showed that PAHs originated mostly pyrogenically, from the combustion of fossil fuels, grass, wood, and coal or from petroleum combustion. Regarding ecological risk estimation, only station 7 was moderately polluted, the rest of the stations suffered rare or slight adverse biological effects with PAH exposure in surface sediment, suggesting that PAHs are not considered as contaminants of concern in the West Port.     

Improved performance‐based seismic assessment of buildings by utilizing Bayesian statistics

This paper addresses two important issues of concern to practicing engineers and researchers alike in application of performance‐based seismic assessment (PBSA) methodology on buildings: (i) the number of ground motion records required to exercise PBSA—current practice (FEMA P‐58‐1) requires eleven or more pairs of motions for this purpose, and (ii) the time and effort associated with performing the number of nonlinear response history analyses required to exercise PBSA. We present a method for exercising of PBSA that employs classical linear modal analysis to develop a first estimate (i.e., a priori) of probability distribution of loss, followed by utilizing Bayesian statistics to update this estimate using estimates of loss obtained by utilizing a small number of nonlinear response history analyses of a detailed model of the building (i.e., posterior). The proposed technique is used to assess the distribution of monetary loss of two case studies, a 4‐story reinforced concrete moment‐resisting frame building and a 20‐story steel moment‐resisting frame building, both located in Los Angeles, for a ground motion hazard with 10% probability of exceedance in 50 years. The efficiency of the proposed PBSA method is demonstrated by showing the similarity between the distribution of monetary loss at each story of case study buildings obtained from the traditional/sophisticated PBSA methodology and the proposed PBSA method in this study. Copyright © 2015 John Wiley & Sons, Ltd.     

Landslide detection using deep learning and object-based image analysis

Landslides - Recent landslide detection studies have focused on pixel-based deep learning (DL) approaches. In contrast, intuitive annotation of landslides from satellite imagery is based on...     

Using constrained inversion of gravity and magnetic field to produce a 3D litho‐prediction model

Geologically constrained inversion of gravity and magnetic field data of the Victoria property (located in Sudbury, Canada) was undertaken in order to update the present three‐dimensional geological model. The initial and reference model was constructed based on geological information from over 950 drillholes to constrain the inversion. In addition, downhole density and magnetic susceptibility measured in six holes were statistically analysed to derive lower and upper bounds on the physical properties attributed to the lithological units in the reference model. Constrained inversion of the ground gravity and the airborne magnetic data collected at the Victoria property were performed using GRAV3D and MAG3D, respectively. A neural network was trained to predict lithological units from the physical properties measured in six holes. Then, the trained network was applied on the three‐dimensional distribution of physical properties derived from the inversion models to produce a three‐dimensional litho‐prediction model. Some of the features evident in the lithological model are remnants of the constraints, where the data did not demand a significant change in the model from the initial constraining model (e.g., the thin pair of diabase dykes). However, some important changes away from the initial model are evident; for example, a larger body was predicted for quartz diorite, which may be related to the prospective offset dykes; a new zone was predicted as sulfide, which may represent potential mineralisation; and a geophysical subcategory of metabasalt was identified with high magnetic susceptibility and high density. The litho‐prediction model agrees with the geological expectation for the three‐dimensional structure at Victoria and is consistent with the geophysical data, which results in a more holistic understanding of the subsurface lithology.     

Earthquake response of concrete arch dams: a plastic–damage approach

There are several alternatives to evaluate seismic damage‐cracking behavior of concrete arch dams, among which damage theory is the most popular. A more recent option introduced for this purpose is plastic–damage (PD) approach. In this study, a special finite element program coded in 3‐D space is developed on the basis of a well‐established PD model successfully applied to gravity dams in 2‐D plane stress state. The model originally proposed by Lee and Fenves in 1998 relies on isotropic damaged elasticity in combination with isotropic tensile and compressive plasticity to capture inelastic behaviors of concrete in cyclic or dynamic loadings. The present implementation is based on the rate‐dependent version of the model, including large crack opening/closing possibilities. Moreover, with utilizing the Hilber–Hughes–Taylor time integration scheme, an incremental–iterative solution strategy is detailed for the coupled dam–reservoir equations while the damage–dependent damping stress is included. The program is initially validated, and then, it is employed for the main analyses of the Koyna gravity dam in a 3‐D modeling as well as a typical concrete arch dam. The former is a major verification for the further examination on the arch dam. The application of the PD model to an arch dam is more challenging because the governing stress condition is multiaxial, causing shear damage to become more important than uniaxial states dominated in gravity dams. In fact, the softening and strength loss in compression for the damaged regions under multiaxial cyclic loadings affect its seismic safety. Copyright © 2013 John Wiley & Sons, Ltd.     

Climate change outlook for water resources management in a semiarid river basin: the effect of the environmental water demand

Iran is a developing country with arid and semiarid regions. Poor management of water resources combined with the effects of climate change is leading to the drying of several rivers and wetlands. Several planned water development projects, primarily for agricultural expansion, will be implemented in the coming years which could worsen impacts on vulnerable aquatic ecosystems. Proper water resources management is essential to meet present and future residential, environmental, industrial, and agricultural demands in semiarid regions. This paper presents projections of how the availability of water resources will change in the Karkheh river basin of Iran for the period 2010–2059 employing sustainability criteria in the form of time-based reliability, volumetric reliability, resiliency, and vulnerability. This paper’s results show that consideration of environmental receptors as a stakeholder of water use places limitations on agricultural development within the Karkheh river basin.