• Computers and Concrete
• /
• 제20권4호
• /
• pp.429-437
• /
• 2017

In this study, the effect of the tensile strength and ratio of disc spacing to penetration depth on the efficiency of tunnel boring machine (TBM) is investigated using Particle flow code (PFC) in two dimensions. Models with dimensions of $150{\times}70mm$ made of rocks with four different tensile strength values of 5 MPa, 10 MPa, 15 MPa and 20 MPa were separately analyzed and two "U" shape cutters with width of 10 mm were penetrated into the rock model by velocity rate of 0.1 mm/s. The spacing between cutters was also varied in this study. Failure patterns for 5 different penetration depths of 3 mm, 4 mm, 5 mm, 6 mm, and 7 mm were registered. Totally 100 indentation test were performed to study the optimal tool-rock interaction. An equation relating mechanical rock properties with geometric characteristics for the optimal TBM performance is proposed. The results of numerical simulations show that the effective rock-cutting condition corresponding to the minimum specific energy can be estimated by an optimized disc spacing to penetration depth, which, in fact, is found to be proportional to the rock's tensile strength.

• Structural Engineering and Mechanics
• /
• 제86권6호
• /
• pp.765-778
• /
• 2023

This study investigates the free vibration and buckling analyses of isotropic curved plate structures fixed at all ends. The Kirchhoff-Love Plate Theory (KLPT) and Finite Element Method (FEM) are employed to model the curved structure. In order to perform the finite element analysis, a four-node quadrilateral element with 5 degrees of freedom (DOF) at each node is utilized. Additionally, the drilling effect (θ_z) is considered as minimal to satisfy the DOF of the structure. Lagrange's equation of motion is used in order to obtain the first ten natural frequencies and the critical buckling values of the structure. The effects of various radii of curvatures and aspect ratio on the natural frequency and critical buckling load values for the single-bay and two-bay curved frames are investigated within this scope. A computer code based on finite element analysis is developed to perform free vibration and buckling analysis of curved plate frames. The natural frequency and critical buckling load values of the present study are compared with ANSYS R18.2 results. It has been concluded that the results of the present study are in good agreement with ANSYS results for different radii of curvatures and aspect ratio values of both single-bay and two-bay structures.

• Geomechanics and Engineering
• /
• 제34권5호
• /
• pp.507-527
• /
• 2023

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

• Interaction and multiscale mechanics
• /
• 제2권2호
• /
• pp.177-187
• /
• 2009

Machine or structural members subjected to fatigue loading will have a crack initiated during early part of their life. Therefore analysis of members with cracks and other discontinuities is very important. Finite element method has enjoyed widespread use in engineering, but it is not convenient for crack problems as the region very close to crack tip is to be discretized with very fine mesh. However, as the body force method (BFM), requires only the boundary of the discontinuity (crack or hole) to be discretized it is easy versatile technique to analyze such problems. In the present work fundamental solution for concentrated load x + iy acting in the semi-infinite plate at an arbitrary point $z_0=x_0+iy_0$ is considered. These fundamental solutions are in complex form ${\phi}(z)$ and ${\psi}(z)$ (England 1971). These potentials are known as Melan potentials (Ramakrishna 1994). A crack in the semi-infinite plate as shown in Fig. 1 is considered. This crack is divided into number of divisions. By applying pair of body forces on a division, the resultant forces on the remaining 'N'divisions are to be found for which ${\phi}_1(z)$ and ${\psi}_1(z)$ are derived. Body force method is applied to calculate stress intensity factor for crack in semi-infinite plate. Also for the case of crack emanating from circular hole in semi-infinite plate radial stress, hoop stress and shear stress are calculated around the hole and crack. Convergent results are obtained by body force method. These results are compared with FEM results.

• Advances in nano research
• /
• 제10권1호
• /
• pp.59-69
• /
• 2021

Electrospinning is a cost-effective and versatile method for producing submicron fibers. Although this method is relatively simple, at the theoretical level the interactions between process parameters and their influence on the fiber morphology are not yet fully understood. In this paper, the aim was finding optimal electrospinning parameters in order to obtain the smallest fiber diameter by using Taguchi's methodology. The nanofibers produced by electrospinning a solution of Thermoplastic Polyurethane (TPU) in Dimethylformamide (DMF). Polymer concentration and process parameters were considered as the effective factors. Taguchi's L9 orthogonal design (4 parameters, 3 levels) was applied to the experiential design. Optimal electrospinning conditions were determined using the signal-to-noise (S/N) ratio with Minitab 17 software. The morphology of the nanofibers was studied by a Scanning Electron Microscope (SEM). Thereafter, a tensile tester machine was used to assess mechanical properties of nanofibrous scaffolds. The analysis of DoE experiments showed that TPU concentration was the most significant parameter. An optimum combination to reach smallest diameters was yielded at 12 wt% polymer concentration, 16 kV of the supply voltage, 0.1 ml/h feed rate and 15 cm tip-to-distance. An empirical model was extracted and verified using confirmation test. The average diameter of nanofibers at the optimum conditions was in the range of 242.10 to 257.92 nm at a confidence level 95% which was in close agreement with the predicted value by the Taguchi technique. Also, the mechanical properties increased with decreasing fibers diameter. This study demonstrated Taguchi method was successfully applied to the optimization of electrospinning conditions for TPU nanofibers and the presented scaffold can mimic the structure of Extracellular Matrix (ECM).

• Structural Engineering and Mechanics
• /
• 제71권1호
• /
• pp.57-63
• /
• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.

• Advances in nano research
• /
• 제12권6호
• /
• pp.549-566
• /
• 2022

Mining of ore minerals (sfalerite, cinnabar, and chalcopyrite) from the old mine has led in significant environmental effects as contamination of soils and plants and acidification of water. Also, nanoparticles (NP) have obtained global importance because of their widespread usage in daily life, unique properties, and rapid development in the field of nanotechnology. Regarding their usage in various fields, it is suggested that soil is the final environmental sink for NPs. Nanoparticles with excessive reactivity and deliverability may be carried out as amendments to enhance soil quality, mitigate soil contaminations, make certain secure land-software of the traditional change substances and enhance soil erosion control. Meanwhile, there's no record on the usage of Nano superior substances for mine soil reclamation. In this study, five soil specimens have been tested at 4 sites inside the region of mine (<100 m) to study zeolites, and iron sulfide nanoparticles. Also, through using Artificial Neural Network (ANN) and Extreme Learning Machine (ELM), this study has tried to appropriately estimate the mechanical properties of soil under the effect of these Nano particles. Considering the RMSE and R2 values, Zeolite Nano materials could enhance the mine soil fine through increasing the clay-silt fractions, increasing the water holding capacity, removing toxins and improving nutrient levels. Also, adding iron sulfide minerals to the soils would possibly exacerbate the soil acidity problems at a mining site.

• Advances in nano research
• /
• 제12권1호
• /
• pp.81-99
• /
• 2022

The aim of current work is to evaluate thermo-electrical characteristics of graphene nanoplatelets Reinforced Composite (GNPRC) coupled with magneto-electro-elastic (MEE) face sheet. In this regard, a cylindrical smart nanocomposite made of GNPRC with an external MEE layer is considered. The bonding between the layers are assumed to be perfect. Because of the layer nature of the structure, the material characteristics of the whole structure is regarded as graded. Both mechanical and thermal boundary conditions are applied to this structure. The main objective of this work is to determine critical temperature and critical voltage as a function of thermal condition, support type, GNP weight fraction, and MEE thickness. The governing equation of the multilayer nanocomposites cylindrical shell is derived. The generalized differential quadrature method (GDQM) is employed to numerically solve the differential equations. This method is integrated with Deep Learning Network (DNN) with ADADELTA optimizer to determine the critical conditions of the current sandwich structure. This the first time that effects of several conditions including surrounding temperature, MEE layer thickness, and pattern of the layers of the GNPRC is investigated on two main parameters critical temperature and critical voltage of the nanostructure. Furthermore, Maxwell equation is derived for modeling of the MEE. The outcome reveals that MEE layer, temperature change, GNP weight function, and GNP distribution patterns GNP weight function have significant influence on the critical temperature and voltage of cylindrical shell made from GNP nanocomposites core with MEE face sheet on outer of the shell.

• Geomechanics and Engineering
• /
• 제28권6호
• /
• pp.599-611
• /
• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Computers and Concrete
• /
• 제32권5호
• /
• pp.465-474
• /
• 2023

The point load test (PLT) is a widely-used alternative method in the field to determine the uniaxial compressive strength due to its simple testing machine and procedure. The point load test index can estimate the uniaxial compressive strength through conversion factors based on the rock types. However, the mechanism correlating these two parameters and the influence of the mechanical properties on PLT results are still not well understood. This study proposed a theoretical model to understand the mechanism of PLT serving as an alternative to the UCS test based on laboratory observation and literature survey. This model found that the point load test is a self-confined compression test. There is a compressive ellipsoid near the loading axis, whose dilation forms a tensile ring that provides confinement on this ellipsoid. The peak load of a point load test is linearly positive correlated to the tensile strength and negatively correlated to the Poisson ratio. The model was then verified using numerical and experimental approaches. In numerical verification, the PLT discs were simulated using flat-joint BPM of PFC3D to model the force distribution, crack propagation and BPM properties' effect with calibrated micro-parameters from laboratory UCS test and point load test of Berea sandstones. It further verified the mechanism experimentally by conducting a uniaxial compressive test, Brazilian test, and point load test on four different rocks. The findings from this study can explain the mechanism and improve the understanding of point load in determining uniaxial compressive strength.