Deep learning neural networks for spatially explicit prediction of flash flood probability

Flood probability maps are essential for a range of applications, including land use planning and developing mitigation strategies and early warning systems. Th...     

Innovative mitigation method for buried pipelines crossing faults

A new remediation technique is proposed to mitigate large deformations imposed on buried pipeline systems subject to permanent ground deformation. With this technique, low-density gravel(LDG) with high porosity, such as pumice,is used as backfill in the trench containing the pipe near an area susceptible to PGD. This countermeasure decreases soil resistance, soil-pipe interaction forces and strain on the pipe as the pipeline deformation mechanism changes to a more desirable shape. Expanded polys...     

Intelligent Prediction of Blasting-Induced Ground Vibration Using ANFIS Optimized by GA and PSO

Ground vibration induced by rock blasting is one of the most crucial problems in surface mines and tunneling projects. Hence, accurate prediction of ground vibration is an important prerequisite in the minimization of its environmental impacts. This study proposes hybrid intelligent models to predict ground vibration using adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) and genetic algorithms (GAs). To build prediction models using ANFIS, ANFIS–GA, and ANFIS–PSO, a database was established, consisting of 86 data samples gathered from two quarries in Iran. The input parameters of the proposed models were the burden, spacing, stemming, powder factor, maximum charge per delay (MCD), and distance from the blast points, while peak particle velocity (PPV) was considered as the output parameter. Based on the sensitivity analysis results, MCD was found as the most effective parameter of PPV. To check the applicability and efficiency of the proposed models, several traditional performance indices such as determination coefficient (R²) and root-mean-square error (RMSE) were computed. The obtained results showed that the proposed ANFIS–GA and ANFIS–PSO models were capable of statistically predicting ground vibration with excellent levels of accuracy. Compared to the ANFIS, the ANFIS–GA model showed an approximately 61% decrease in RMSE and 10% increase in R². Also, the ANFIS–PSO model showed an approximately 53% decrease in RMSE and 9% increase in R² compared to ANFIS. In other words, the ANFIS performance was optimized with the use of GA and PSO.

     

Prediction of Vibration Velocity Generated in Mine Blasting Using Support Vector Regression Improved by Optimization Algorithms

Natural Resources Research - Ground vibration generated from blasting is a detrimental side effect of the use of explosives to break the rock mass in mines. Therefore, accurately predicting ground...     

The behaviour of an artificially cemented sandy gravel

The major section of the city of Tehran, Iran has been developed on cemented coarse-grained alluvium. This deposit consists of gravely sand to sandy gravel with some cobbles and is dominantly cemented by carbonaceous materials. In order to understand the mechanical behaviour of this soil, a series of undrained triaxial compression tests and unconfined compression tests were performed on uncemented and artificially cemented samples. Portland cement type I was used as the cementation agent for preparing artificially cemented samples. Uncemented samples and lightly cemented samples (1.5% cement) tested at high confining pressure showed contractive behaviour accompanied with positive excess pore water pressure and a barrelling failure mode. However, cemented samples and uncemented samples tested at low confining pressure (25 and 50 kN/m²) showed dilative behaviour accompanied with negative excess pore water pressure. Shear zones were formed in these samples and a clear peak in excess pore water pressure and stress ratio against strain could be observed. Test results showed that the limiting stress ratio surface for cemented samples is curved and expands as the cementation and density increase. Unconfined compression strength of cemented samples increases with increases in cementation and density as well.     

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971–2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015–2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

     

A simplified stress analysis of rising salt domes

We use a simple analytical model to estimate the stress field in density‐driven, rising salt domes and adjacent sediments, and to describe the evolution of these domes. We show that the pressure exerted by the salt pushing out against its wall rocks (the salt pressure) decreases linearly up the flank of the dome, but is always greater than the overburden stress. In fact, the salt pressure normal to the dome boundary is everywhere the maximum principal stress, whereas the hoop stress parallel to the circumference of the dome is the minimum stress. In addition, we quantitatively describe the critical stages of salt dome evolution (initiation, upbuilding, and downbuilding), relating these stages to sedimentation rate and basin thickness. This analysis also shows that even the highest sedimentation rates are unlikely to accumulate enough sediments to bury downbuilding domes as long as the salt supply is unrestricted. Despite the simplicity of the model, its predictions are in good agreement with field observations near salt domes. Overall, our analytical model can provide critical insight into the stress field perturbation in and near rising salt domes and can be used to assess the accuracy of numerical models and field measurements near these domes.     

Iranian ultrapotassic volcanism at ~11 Ma signifies the initiation of post‐collisional magmatism in the Arabia–Eurasia collision zone

Ultrapotassic rocks are a common, but volumetrically minor, hallmark of post‐collisional magmatism along the Alpine–Himalayan orogenic belt. Here, we document the occurrence of ultrapotassic volcanic rocks from the Eslamy peninsula, NW Iran in the Arabia–Eurasia collision zone. Our results indicate that magma genesis involved melting of phlogopite‐ and apatite‐bearing peridotites in the sub‐continental lithospheric mantle at ~11 Ma. These peridotites likely formed by metasomatism involving components derived from subducted sediments during Neotethyan subduction. The ~11 Ma ultrapotassic volcanism was preceded by a magmatic gap of ~11 Ma after the cessation of arc magmatism in NW Iran and Armenia, thus likely representing the initiation of post‐collisional magmatism. The age coincides with the onset of collision‐related magmatic activity and topographic uplift in the Caucasus–Iran–Anatolia region, and also with other regional geological events including the closure of the eastern Tethys gateway, the end of Arabian underthrusting and the start of escape tectonics in Anatolia.     

A numerical study of the influence from pre‐existing cracks on granite rock fragmentation at percussive drilling

The aim of this study is to investigate the effect of pre‐existing, or structural, cracks on dynamic fragmentation of granite. Because of the complex behavior of rock materials, a continuum approach is employed relying upon a plasticity model with yield surface locus as a quadratic function of the mean pressure in the principal stress space coupled with an anisotropic damage model. In particular, Bohus granite rock is investigated, and the material parameters are chosen based on previous experiments. The equation of motion is discretized using a finite element approach, and the explicit time integration method is employed. The pre‐existing cracks are introduced in the model by considering sets of elements with negligible tensile strength that leads to their immediate failure when loaded in tension even though they still carry compressive loads as crack closure occurs because of compressive stresses. Previously performed edge‐on impact tests are reconsidered here to validate the numerical model. Percussive drilling is simulated, and the influence of the presence of pre‐existing cracks is studied. The results from the analysis with different crack lengths and orientations are compared in terms of penetration stiffness and fracture pattern. It is shown that pre‐existing cracks in all investigated cases facilitate the drilling process. Copyright © 2014 John Wiley & Sons, Ltd.