Developing the Rule of Thumb for Evaluating Penetration Rate of TBM,Using Binary Classification

Geotechnical and Geological Engineering - Using the tunnel boring machine (TBM) in tunneling projects contributes significantly to increased efficiency and reducing the time of project...     

Application of Leeb Hardness Test in Prediction of Dynamic Elastic Constants of Sedimentary and Igneous Rocks

Geotechnical and Geological Engineering - The Leeb hardness test is a non-destructive and portable technique that can be used both in the laboratory and in-field applications. The main purpose of...     

Formation and growth of multiple,distinct ice lenses in frost heave

This paper presents a fully coupled thermo-hydro-mechanical (THM) model which simulates frost heave in fully saturated soils. The model is able to simulate the formation and growth of multiple distinct ice lenses. The basic equations of the system were derived using the continuum theory of mixtures, nonequilibrium thermodynamics, and fracture mechanics, considering skeleton deformation, water flow and heat transport. Central to this model is the coupled transport of mass due to the temperature gradient across the frozen fringe, which acts as the main driving force of the phenomenon. The model is formulated in terms of measurable physical properties and thus no ad hoc parametrization is required. In an ice-lens-free state, the system is solved as a continuum using the finite element method (FEM). It is then locally treated as a discontinuous system upon the formation of ice lens, by enriching the elements carrying the embedded ice lens(es) using the extended finite element method (X-FEM). The accuracy and efficiency of the proposed model has been verified using several laboratory tests on Devon silt samples at different overburden pressures and thermal boundary conditions. Shut-off pressures have been also estimated and compared with the experimental results.     

Superiority of neural networks for pillar stress prediction in bord and pillar method

Estimation of pillar stress is a crucial task in underground mining. This is used to determine pillar dimensions, room width, roof conditions, and general mine layout. There are several methods for estimating induced stresses due to underground excavations, i.e., empirical methods, numerical solutions, and currently artificial intelligence (AI). AI based techniques are gradually gaining popularity especially for problems involving uncertainty. In this paper, an attempt has been made to predict stresses developed in the pillars of bord and pillar mining using artificial neural network. A comparison has also been done to compare the obtained results with the boundary element method as well as measured field values. For this purpose, a multilayer perceptron neural network model was developed. A number of architectures with different hidden layers and neurons were tried to get the best solution, and the architecture 5-20-8-1 was found to be an optimum solution. Sensitivity analysis was also carried out to understand the influence of important input parameters on pillar stress concentration.     

Petrogenesis of granitic unit of Naqadeh complex, Sanandaj–Sirjan Zone, NW Iran

The granitic unit is a component of the Naqadeh plutonic complex, NW of Sanandaj–Sirjan Zone (NW Iran). This unit is composed of high-K calc-alkaline, slightly peraluminous (ASI?=?1.12–1.17) evolved monzogranites. These monzogranites have 41.85?±?0.81 Ma (zircon U–Pb sensitive, high-resolution ion microprobe (SHRIMP) age) with two inherited zircon ages of 98.5?±?1.7 and 586.6?±?13.1 Ma, respectively. The only enclave type consists of quartz-amphibolite enclaves indicating residual parental rocks. Chemical and isotopic (⁸⁷Sr/⁸⁶Sr_40Ma?=?0.708638; εNd_40Ma?=??4.26) characteristics of monzogranites suggest that they could be derived by partial melting of crustal mafic rocks followed by some assimilation of metasedimentary rocks. With regards to inherited zircon age and quartz-amphibolite composition of Naqadeh granite, the old mafic rocks of this complex (Naqadeh dioritic rocks with ~100 Ma) can be considered as parental rocks, and their partial melting under high water content, and assimilation of produced melt by metasedimentary rocks, would lead to the generation of a Naqadeh granitic unit.     

Clustering of mineral prospectivity area as an unsupervised classification approach to explore copper deposit

This paper describes the usage of clustering methods including self-organizing map (SOM) and fuzzy c-means (FCM) which are applied to prepare mineral prospectivity map. Different evidential layers, including geological, geophysical, and geochemical, to evaluate Now Chun copper deposit located in the Kerman province of Iran are used. Clustering approaches are used to reduce the dimension of 13 feature vectors derived from different layers. At first, Geospatial Information Systems (GIS) is employed to analyze and integrate different layers, and the area under study is prioritized to five classes. Then, the SOM as an unsupervised classification method is carried out to classify this area into five clusters. Produced clusters are compared with GIS prospect map, while the SOM results are matched with the GIS output. The main reason to use the FCM is that a vector belongs simultaneously to more than one cluster so that membership values of each cluster can be mapped. As a consequence, clusters generated by the SOM and FCM are considerably matched with five-class-map of the GIS approach. The chosen cluster as a high potential location to additional drilling is matched to the main alteration and faults zone. To validate generated clusters for mineral potential mapping, geological matching of study area and selected proper cluster can be a satisfactory way. Finally, clustering methods can be a very fast approach to interpret the area under study.     

Designing an integrated urban growth prediction model: a scenario-based approach for preserving scenic landscapes

Abstract

This study demonstrates the integration of landscape aesthetic quality and probable urban growth patterns in urban landscape modelling. This was performed using SLEUTH as a scenario-based urban growth model in Gorgan City of Iran. Future urbanization was predicted under developing three different scenarios including historical, managed and aesthetically sound urban growth up to the year 2030. Multi-Layer Perceptron neural network model was conducted for mapping the aesthetic suitability of the study area. The aesthetic suitability layer was used in the third scenario of SLEUTH model as the excluded layer to protect the scenic patches in future. The results showed that by correct implementation of urban growth policies, 323 ha in the second scenario and 650 ha in the third scenario would be saved. This integrated model would help the planners for a better management of urban landscapes as a Spatial Decision Support System.     

Fusing remote sensing with sparse demographic data for synthetic population generation: an algorithm and application to rural Afghanistan

We develop a new algorithm for population synthesis that fuses remote-sensing data with partial and sparse demographic surveys. The algorithm addresses non-binding constraints and complex sampling designs by translating population synthesis into a computationally efficient procedure for constrained network growth. As a case, we synthesize the rural population of Afghanistan, validate the algorithm with in-sample and out-of-sample tests, examine the variability of algorithm outputs over k-nearest neighbor manifolds, and show the responsiveness of our algorithm to additional data as a constraint on marginal population counts.     

Load‐displacement and bearing capacity of foundations on granular soils using a multi‐surface kinematic constitutive soil model

A finite element approach based on an advanced multi‐surface kinematic constitutive model is used to evaluate the bearing capacity of footings resting on granular soils. Unlike simple elastic‐perfectly plastic models, often applied to granular foundation problems, the present model realistically accounts for stress dependency of the friction angle, strain softening–hardening and non‐associativity. After the model and its implementation into a finite element code are briefly discussed, the numerical difficulty due to the singularity at the footing edge is addressed. The bearing capacity factor N_γ is then calculated for different granular materials. The effect of footing size, shape, relative density and roughness on the ultimate bearing capacity are studied and the computed results compare very favourably with the general experimental trends. In addition, it is shown that the finite element solution can clearly represent counteracting mechanisms of progressive failure which have an important effect on the bearing capacity of granular foundations. Copyright © 2006 John Wiley & Sons, Ltd.     

Assessment of a spatial multi-criteria evaluation to site selection underground dams in the Alborz Province,Iran

Most part of Iran is arid and semi-arid; thus in most parts of the region, groundwater is the only source of water. This research presents a method based on a spatial multi-criterion evaluation (SMCE) for designing possible sites of underground dams and ranks them according to their suitability. The method was tested for siting underground dams in the Alborz Province, Iran. At first, screening algorithm was applied using exclusionary criteria, and thirty-one potential areas were recognized in the study area. In the next step, a suitable gorge or valley was recognized using the combination of basic maps and extensive field surveys (long axis of tank level) in each potential area. Subsequently, the analytical hierarchy process was used as a powerful tool for decision-making in the SMCE in order to evaluate different criteria for underground dam sites. SMCE techniques were then applied to combine the criteria, and obtain a suitability map in the study area. These sites were then compared and ranked according to their main criteria such as water, storage, axis and socio-economics. All these criteria were assessed through geographical information system modelling. This method shows passable results and could be used for site selection of underground dams in other regions of Iran.