- Rock Mechanics and Modeling
- Geotechnical Engineering and Underground Structures
- Geotechnical Engineering and Analysis
- Geomechanics and Mining Engineering
- Grouting, Rheology, and Soil Mechanics
- Tunneling and Rock Mechanics
- Geoscience and Mining Technology
- Geotechnical and Geomechanical Engineering
- Mineral Processing and Grinding
- Drilling and Well Engineering
- Hydraulic Fracturing and Reservoir Analysis
- Dam Engineering and Safety
- Landslides and related hazards
- Hydrocarbon exploration and reservoir analysis
- Railway Engineering and Dynamics
- Geophysical Methods and Applications
- Mining and Gasification Technologies
- Metal Extraction and Bioleaching
- Civil and Geotechnical Engineering Research
- Geotechnical Engineering and Soil Stabilization
- Mining Techniques and Economics
- Geochemistry and Geologic Mapping
- NMR spectroscopy and applications
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Reservoir Engineering and Simulation Methods
University of Tehran
2016-2025
Health Affairs
2019
Institución Universitaria Salazar y Herrera
2017
McGill University
1989
Generally, longwall mining-induced stress results from the relaxation due to destressed zone that occurs above mined panel. Knowledge of induced is very important for accurate design adjacent gateroads and intervening pillars which helps raise safety productivity mining operations. This study presents a novel time-dependent analytical model determination investigates coefficient concentration over gates pillars. The developed based on strain energy balance in incorporated rheological...
Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining structures. In this paper, two predictive models including Mamdani fuzzy system (MFS) multivariable regression (MVRA) were developed to predict deformation based on data obtained from dilatometer tests carried out Bakhtiary dam site additional collected longwall coal mines. Models inputs considered be rock quality designation, overburden height, weathering, unconfined compressive strength,...
The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent combined caved and fractured zones above mined panel in longwall mining. For this, suitable datasets have been collected from literatures prepared for modeling. data were used construct a multilayer perceptron (MLP) approximate unknown nonlinear relationship between input parameters HDZ. MLP proposed predicted values enough agreements with measured ones...
Accurate settlement forecasting is essential for preventing severe structural and infrastructure damage. This paper investigates predicting tunneling-induced ground settlements using machine learning models. Empirical methods estimating are often imprecise site-specific. Developing novel, accurate prediction critical to avoid catastrophic The umbrella arch method constrains deformations initial stability before installing primary support. study develops models forecast solely from...
Assessment of the roof behavior in longwall gob and estimation occurrence caving fracturing zones above mined panels are main factors used evaluating abutment stresses, ground subsidence, face support adjacent structures design. The combined height is taken as equivalent to destressed zone (HDZ) this study. long-term plays a key role accurate determination maximum surface subsidence amount transferred loads towards neighboring solid sections. In paper, has been studied condition. For...
To examine the effect of pressure on pore structure and petrophysical properties carbonate rock, porosity, permeability, CT scanning, SEM elastic wave velocity two core plug samples from an oilfield in Southwest Iran were analyzed under cyclic pressure. One plugs was calcite other dolomite with anhydrite nodules. The exerted increased 13.79 MPa to 27.58 six steps, variations at different loading unloading steps counted analyzed. results show that sample decreases porosity permeability...
The paper describes an artificial neural network method(ANNM) to predict the stresses executed on segmental tunnellining. An ANN using multi-layer perceptron (MLP) is developed.At first, database resulted from numerical analyses wasprepared. This includes; depth of cover (H), horizontal verticalstress ratio (K), thickness segment (t), Young modulus ofsegment (E) and key position in each ring (θ) thetunnel perimeter as input variables. Different types stressesand extreme values displacement...