Hakan Basarir

Support capacity estimation of a diversion tunnel in weak rock

Abstract This paper presents the results of the support capacity estimation for the diversion tunnel of the Urus dam site in highly weathered tuff and weak zone. Tunneling in weak rock requires some special considerations, since misjudgment in support design results in costly failures. There are several ways of estimating rock support pressure and selecting support. However, all systems suffer from their characteristic limitations in achieving objectives. Thus, it is more useful to use different methods for estimating support pressure and type of support. The support pressure pi was established by three different methods. These methods are the (1) empirical methods based on rock mass rating (RMR) and rock mass quality index (Q-classification systems), (2) ground support interaction analysis (GSIA) and (3) numerical methods, namely, Phase2 finite element (FEM) program. Rock masses were characterized in terms of RSR, RMR, Q-system and GSI. Drill-core samples were tested in the rock mechanics laboratory to determine physico-mechanical properties. Rock mass strength was estimated by empirical methods. Finally, the required support system is proposed and evaluated by different methods in the highly weathered tuff and weak zone of the diversion tunnel.

Analysis of rock–support interaction using numerical and multiple regression modeling

This paper presents the results of performance analysis on the support systems recommended by the RMR (rock mass rating) rock mass classification system. Rock–support interaction is analyzed by means of both numerical and multiple regression modeling. Five different rock mass conditions were assumed from very poor to very good, each representing varied RMR. Extensive computer simulations were conducted to investigate the stresses, displacements, and yielded zones around a circular opening excavated at different depths, and under different rock conditions. The performances of the RMR recommended support systems were analyzed and the stability of excavation was evaluated. Multiple regression modeling was conducted to assess the relationship between support pressure, depth, and tunnel deformation for different rock conditions. Regression models were derived and the response surfaces were constructed, showing the interaction between tunnel depth, support pressure, and tunnel displacement. Using the derived mo...

Preliminary estimation of rock mass strength using diamond bit drilling operational parameters

In many mining engineering applications such as prospecting, development, production and grouting, diamond bit drilling is widely used due to high penetration rate, core recovery and its ability to drill with less deviation. It has been well known that the operational parameters of diamond bit drilling are closely related with rock mass strength properties. One of the most widely discussed subjects in drilling is the possibility of using diamond drill bit operational parameters for preliminary estimation of rock mass strength and deformability properties used in many mining engineering design projects. Once such rock properties are estimated, it will be possible to make tactical planning decisions as mining progresses. In this study two different techniques, multiple regression and adaptive neuro-fuzzy inference system (ANFIS) were used to develop the models for preliminary estimation of rock mass strength. The variables used in the models are widely known and recorded operational parameters of diamond bit drilling such as bit load, bit rotation and penetration rate. To develop the models, a database covering the rock properties and the machine operational parameters collected from seven different drill holes in Turkey was constructed. Results indicate that both regression and ANFIS-based models can successfully be used to predict the rock mass strength. Adaptive neuro-fuzzy inference model exhibits better performance according to statistical performance indicators. By means of the developed models it is possible to estimate the strength of rock mass during drilling operation, especially in weak and highly fractured rock masses. The estimated strength parameters can be related to further mining engineering applications such as the assessment of excavatability, blast design and even mine design studies.

Green Concrete with High-Volume Fly Ash and Slag with Recycled Aggregate and Recycled Water to Build Future Sustainable Cities

AbstractBuilding sustainable green cities for the future can be difficult or highly challenging as such cities need to reduce their environmental footprint through eco-friendly materials, resource and energy conservation, as well as renewable energy generation. A recent paper by the first author has proposed sustainable concrete with 80% ground granulated blast furnace slag (GGBFS) to build Masdar City in the UAE with a 153  kg/m3 carbon footprint. This paper proposes three new types of sustainable concretes in an attempt to further reduce the carbon footprint. In Type I, a total of 4 concrete mixes were made with a high volume GGBFS with 60, 70, 80, and 90% replacement of ordinary portland cement (OPC), 100% recycled water (RW), and 100% recycled aggregate (RA). The same replacement ratios were used in Type II but with only 100% RA. In Type III, a total of four concrete mixes made with a high volume fly ash (FA) cement with 40, 50, 60, and 70% replacement of OPC. The paper provides information on the mix...

Assessment of slope stability using fuzzy sets and systems

To assess the stability of slopes, mining and geotechnical engineers frequently use empirical rock mass classification and characterisation systems. These methods are practical and often very useful in the preliminary design stage. Slope mass rating (SMR) system is one of the commonly used empirical methods to assess the stability of slopes. The SMR is obtained correcting basic rock mass rating (RMR) using four joint adjustment factors that consider the geomechanical relationship between the slope face and the joint affecting rock mass as well as the excavation method used. The factors included in the SMR system such as basic RMR, and correction factors involve some drawbacks such as uncertainties sourced from qualitative criteria, sharp class boundaries and fixed rating scales. These drawbacks are sourced from the complex nature of rock mass. To deal with these uncertainties, the fuzzy set theory is applied in this study to reliably determine basic RMR and adjustment factors. It was seen that fuzzy set theory can sufficiently cope with the common drawbacks in the determination of factors included in the SMR system.

Prediction of rock mass P wave velocity using blasthole drilling information

Abstract In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.

Lattice Finite Strain Theory for Non-hydrostatically Compressed Materials

The purpose of this paper is to describe the nonlinear behaviour of geomaterials within the principles of thermodynamics. The main components of this contribution are (1) a new method to estimate the properties of minerals subjected to the non-hydrostatic compression in diamond anvil cell using the finite strain theory is introduced and (2) a proper measure of deformation that applies to a wide range of minerals is identified. This research work shows that the logarithmic (Hencky) strain produces a good agreement with experiments for a wide range of materials.

Energy Dissipation and Storage in Underground Mining Operations

In this paper, we focus on the energy alteration during longwall mining in an attempt to mimic the conditions of a coal mine in Western Turkey. We verify the proposed model using existing analytical and numerical solutions in terms of stress components. Based on the verified numerical model, the energy balance during longwall retreat is studied rigorously. It is found that excavation-induced increment of external work increases linearly with time, while the stored strain energy increment is quadratic. Meanwhile, the strain energy increment rate gradually decreases with longwall progress because of excavation-induced higher stored energy within the adjacent coal block. The energy dissipation process during lonwall mining, corresponding to crack propagation, is divided into four stages, namely initiation stage, steady growth stage, sharp increment stage, and stabilisation stage. Our results provide new insights into energy evolution during longwall mining both from the reversible and irreversible points of view. The current paper shows, for the first time, that the extended finite element method is suitable to describe the crack propagation during longwall mining. The excavation induced crack propagation in the roof strata predicted by the model is in agreement with the “arch-shaped” patterns obtained using laboratory tests and Discrete Element numerical simulations.

The prediction of ultimate pure bending moment of concrete-filled steel tubes by adaptive neuro-fuzzy inference system (ANFIS)

Abstract In this study, different modelling techniques such as multiple regression and adaptive neuro-fuzzy inference system (ANFIS) are used for predicting the ultimate pure bending of concrete-filled steel tubes (CFTs). The behaviour of CFT under pure bending is complex and highly nonlinear; therefore, forward modelling techniques can have considerable limitations in practical situations where fast and reliable solutions are required. Linear multiple regression (LMR), nonlinear multiple regression (NLMR) and ANFIS models were trained and checked using a large database that was constructed and populated from the literature. The database comprises 72 pure bending tests conducted on fabricated and cold-formed tubes filled with concrete. Out of 72 tests, 48 tests were conducted by the second author. Input variables for the models are the same with those used by existing codes and practices such as the tube thickness, tube outside diameter, steel yield strength, strength of concrete and shear span. A practical application example, showing the translation of constructed ANFIS model into design equations suitable for hand calculations, was provided. A sensitivity analysis was conducted on ANFIS and multiple regression models. It was found that the ANFIS model is more sensitive to change in input variables than LMR and NLMR models. Predictions from ANFIS models were compared with those obtained from LMR, NLMR, existing theory and a number of available codes and standards. The results indicate that the ANFIS model is capable of predicting the ultimate pure bending of CFT with a high degree of accuracy and outperforms other common methods.