Scientia Iranica
Volume:25 Issue: 2, Mar - Apr 2018

Although several analytical and numerical approaches have been devoted to investigate the shakedown behavior of pavements, shakedown limit of reinforced pavements in particular geocell-reinforced pavements have not been explored yet by load-displacement numerical means. Bahaviour of a typical three layer pavement reinforced with geocell has been investigated under repeated vertical trafic loads by three dimensional finite element elasto-plastic analysis based on shakedown failure and servicability criteria. Three different cases of unreinforced, base layer reinforced and subgrade reinforced pavement were taken into consideratation and subjected to a variety of vehicle loads. Shakedow limit which is is the multiplication of initial load to shakedown coefficient for each pavement under each load was determined through a trial and error process. Results indicate that reinforcement of subgarde by geocell significantly improves the shakedown coefficients of pavements. Reinforcement of base by geocell increases the shakedown coefficient of pavements as well as but not as much as subgrade reinforcement. Results also indicate the sensitivity of shakedown coefficient and shakedown bearing capacity to intensity and shape of the contact area of different loads so that the most extreme case was observed for P=22 ton. Variation of accumulated plastic displacement prior to shakedown state has also been presented and discussed.

Monitoring embankment dams is of crucial importance. In earth dams, the pore pressures, earth pressures, and displacements occurring during construction and function, are measured at the time of the first impounding and exploitation by installing essential instruments and so the dam’s performance is evaluated and analyzed. Scope of the present research is the evaluation of the performance of Siah-Sang dam through using the results of instruments and back analysis which has been conducted by FLAC software.
The Mohr-Coulomb elastic-plastic model has been considered as the behavioral model of the dam and the effect of the upstream shell’s materials deformation has been modeled at the time of the initial impounding. Following that, comparing the results of the numerical analysis with the measured values, indicates that there is a proper consistency between these two values. Moreover, it was observed that the dam’s performance was suitable regarding the created pore water pressure, displacements and stresses in the construction period as well as during the first impounding. In addition, susceptibility of the hydraulic fracturing was assessed by calculating the arching ratio and it was concluded that this dam is secure in comparison with the behavior of other similar dams in Iran and the world.

Suction caissons are extensively used as anchors for offshore foundation structures. The uplift capacity of suction caisson is an important factor from effective design point of view. In this paper, two recently developed AI techniques, functional network (FN) and multivariate adaptive regression spline (MARS), have been used to predict the uplift capacity of suction caisson in clay. The performances of the developed models are compared with other AI techniques; artificial neural network, support vector machine, relevance vector machine, genetic programming, extreme learning machine and group method of data handling with harmony search (GMDH-HS). The model inputs include the aspect ratio of the caisson, undrained shear strength of soil at the depth of the caisson tip, relative depth of the lug at which the caisson force is applied, load inclination angle and load rate parameter. Comparative analyses are made with the results of the above AI techniques, using different statistical performances criteria; correlation coefficient (R), root mean square error, Nash-Sutcliffe coefficient of efficiency, log-normal distribution of ratio of predicted to observed load capacity, with a ranking system to find out the best predictive model. The FN and MARS models are found to be comparably efficient and they outperform other AI techniques.

Stepped spillways are employed to reduce excess energy encountered with exiting flow from high hydraulic structures. Study of local scour evolution downstream of stepped spillways wilt therefore, provide information to required get benefits from these structures to minimizes the scour hole dimensions. This paper provides the results of 67 experiments downstream of some stepped spillways subjected to different Froude numbers, basin lengths, tail-water depths, sediment sizes and two different sloped spillways. The experiments were continued for 6, 8, 12 and 24 hours from which 824 profiles and 85000 data points were recorded and analyzed. The results show that in certain circumstances the dimensions of scour hole increase in accordance with particle Froude number. It was also observed that increase in the slope of spillway would result in reduction in the geometries of scour hole. At certain conditions, as the tail-water increases, the depth of scour hole increases and elongate the hole. The relationships for duration of scour evolution downstream of stepped spillway are presented in this paper. Finally, it was observed that the stepped spillway would considerably decrease the dimensions of scour hole compared with Ogee spillways which is reflects the excess energy loss downstream of stepped spillway.

In the room and pillar mining method is of fundamental importance the dimensioning of the pillars. The area of influence method is typically used today for dimensioning of the pillars, but an overdimensioning or critical stability conditions can happen with this method.
A parametric analysis with tri-dimensional numerical modelling was carried out to study in the detail the stress conditions in the rock pillars. This made it possible to identify a critical point, where the minimum local safety factor is reached, at the corners of the pillar close to the roof of the mining room.
Through the estimation of the major principal stress at the critical point it was possible to evaluate the minimum local safety factor in function of the geometric and geomechanical parameters of the problem.
The dimensioning of the pillars through the local safety factor at the critical point makes it possible to avoid overdimensioning and static problems, which instead can occur when simplified calculation methods are used.
The use of proposed figures can allow a fast pre-dimensioning of the pillar, leaving the more detailed numerical modelling only to the found geometric configuration.

Concrete is widely used for many practices in Civil Engineering. Therefore, an understanding of its behavior helps engineers and researchers to perform more accurate and cost-effective analyses and designs. In this order, several models have been proposed to predict the behavior of concrete that most of which are satisfactory accurate. However, by increasing the accuracy of the models their computational cost increases as well. In this study, a model with the least computational cost is proposed to predict the behavior of various concretes and confinement conditions. This model does not require any experimental tests to determine its parameters. It was able to predict the behavior of various concretes including normal-weight concrete (NWC) and light-weight concrete (LWC) from other researchers. This model can also be applied to two- and three-dimensional problems. Moreover, the confinement conditions of concretes were considered. The predictions were in good accordance with the experimental results.

A Mixed formulation of Discrete Least Squares Meshless (MDLSM) as a truly meshfree method is presented in this paper for solving both linear and non-linear propagation problems. In DLSM method, the irreducible formulation was deployed which needs to calculate the costly second derivatives of the MLS shape functions. In the proposed MDLSM method, the complex and costly second derivatives of shape functions are not required. Furthermore, using the mixed formulation, both unknown parameters and their gradients are simultaneously obtained circumventing the need for post-processing procedure performed in irreducible formulation to calculate the gradients. Therefore, the accuracy of gradients of unknown parameters is increased. In MDLSM method, the set of simultaneous algebraic equations are built by minimizing a least squares functional with respect to the nodal parameters. The least squares functional defined as the sum of squared residuals of the differential equation and its boundary condition. The proposed method automatically leads to symmetric and positive-definite system of equations and, therefore, is not subject to the Ladyzenskaja-Babuska-Brezzi (LBB) condition. The proposed MDLSM method is validated and verified by a set of benchmark problems. The results indicate the ability of proposed method to efficiently and effectively solve the linear and non-linear propagation problems.

Current study deals with strength and seismic ductility assessment of reinforced high strength concrete (HSC) columns. We have studied the nonlinear response of HSC columns with various reinforcement and axial force ratios subjected to cyclic loading. Study consists of primary verification of mathematical nonlinear model and further calibration to ensure accuracy. An existing experimental work is assumed as verification pilot that consists of four columns. Column members differ in the strength and axial force. Concrete has 63.1 MPa mean strength and 0.3% crushing strain. The longitudinal and transverse reinforcements are according to ACI 318 regulations in experiment. We used the nonlinear fiber-element code in OpenSees environment for modeling and analysis of models. The existing proposed stress-strain curve is modified to ensure validity of assessment. Calibration procedure led to conclusion that the post-yield slope needs to be modified in HSC model as the average value of ACI 363 reference. We have developed twelve extra models to estimate the interaction of concrete strength, rebar ratio and the axial force effect on the seismic performance. Parametric study of calibrated models reveals that the seismic energy dissipation in HSC members is function of the provided longitudinal reinforcement ratio and lateral confining stirrup amount.

Accurate outlier detection is an important matter to consider prior to data applied to predict flow pattern. Identifying these outliers and reducing their impact in measurements could be effective in presenting the authentic flow pattern. This paper aims to detect outliers in flow pattern experiments along a 180 degree sharp bend channel with and without a T-shaped spur dike. Velocity components have been collected using 3D velocimeter called Vectrino in order to determine flow pattern. Some of outlier detection methods employed in the paper, such as Z-score test, sum of sine curve fitting, Mahalanobis distance, hierarchical clustering, LSC-Mine, Self-organizing map, Fuzzy C-Means Clustering, and voting. Considering the experiments carried out, the methods were efficient in outlier detection, however, the voting method appeared to be the most efficient one. Briefly, this paper has calculated different hydraulic parameters in the sharp bend and made comparison between them for the sake of studying how effective running the voting method are on mean and turbulent flow pattern variations. The results indicated that developing the voting method in flow pattern experiment in the bend would cause a decrease in Reynolds shear stress, by 36%, while the mean velocities were not significantly influenced by the method.

A procedure for updating the Park-Ang damage index of reinforced concrete building under near-fault ground motion is proposed. Rather than developing a new damage model, a correction term is added to the existing damage model within the Bayesian framework. The correction term is described as a linear function of the variation of stiffness of structures which is a more consistent indicator in predicting the level of damage. The Bayesian method is an effective approach when new data become available. The reinforced concrete building damage data during past near-fault pulse-like earthquakes were used in updating the damage model. The proposed damage index is conceptually simple and realistic.

In recent years, controlled blasting has turned into an efficient method for evaluation of soil liquefaction in real scale and evaluation of ground improvement techniques. Predicting blast-induced soil liquefaction by using collected information can be an effective step in the[a1] study of blast-induced liquefaction. In this study, to estimate residual pore pressure ratio, first, multi- layer perceptron neural network is used in which error (RMS) for the network was calculated as 0.105. Next, neuro-fuzzy network, ANFIS was used for modeling. Different ANFIS models are created using Grid partitioning (GP), Subtractive Clustering (SCM), and Fuzzy C-means Clustering (FCM). Minimum error is obtained using by FCM at about 0.081. Finally, radial basis function (RBF) network is used. Error of this method was about 0.06. Accordingly, RBF network has better performance. Variables including fine-content, relative density, effective overburden pressure and SPT value are considered as input components and the Ru, residual[a2] pore pressure ratio was used as the only output component for designing prediction models. In the next stage the network output is compared with the results of a regression analysis. Finally, sensitivity analysis for RBF network is tested, its results reveal that and SPT are the most effective factors in determining Ru.

In this study, a regional flood frequency analysis (RFFA) was applied to 33 stream gauging stations in the Eastern Black Sea Basin, Turkey. Homogeneity of the region was determined by discordancy (Di) and heterogeneity measures (Hi) based on L-moments. Generalized extreme-value, lognormal, Pearson type III, and generalized logistic distributions were fitted to the flood data of the homogeneous region. Based on the appreciate distribution for the region, flood quantiles were estimated for return periods of T=5, 10, 25, 50, 100, and 500 years. A non linear regression model was then developed to determine the relationship between flood discharges and meteorological and hydrological characteristics of the catchment. In order to compare with regression analysis, artificial bee colony algorithm (ABC) and teaching-learning based optimization (TLBO) models were developed. The equations were obtained by using the ABC and TLBO algorithms for the estimation of flood discharges for different return periods. The analysis showed that the TLBO and ABC results were superior to the regression analysis. Error values indicated that TLBO method yielded better results for estimation of flood quantiles for different independent variables.

Delays and disruptions reduce the reliability and stability of the rail operations. Railway traffic rescheduling includes ways to manage the operations during and after the occurrences of such disturbances. In this study, we consider the simultaneous presence of large disruptions (temporary full or partial blockage of tracks) as well as stochastic variation of operations, as a source of disturbance. The occurrence time of blockage and its recovery time are given. We designed a simulation-based optimization model that incorporates dynamic dispatch priority rules with the objective of minimizing the total delay time of trains. We moreover design a variable neighborhood search meta-heuristic scheme for handling traffic under the limited capacity close to the blockage. The new plan includes a set of new departure times; dwell times, train running times. We evaluate the proposed model on a set of disruption scenarios covering a large part of the Iranian rail network. The result indicates that the developed simulation-based optimization approach has substantial advantages in producing practical solution quickly, when compared to commercial optimization software. In addition, the solutions have a lower average and smaller standard deviation than currently accepted solutions, determined by human dispatcher or by standard software packages.

To explore the mechanisms concerning adfreezing strengths at the interface between frozen fine sand and structures, a series of experiments were conducted using a direct shear apparatus. The main results were as follows: All adfreezing strengths increased with decreasing temperature and increasing normal stress and surface roughness. Peak adfreezing strength (peak shear stress at failure) had a linear relationship with temperature, its relationship with normal stress was in line with the Mohr–Coulomb criterion, and its relationship with roughness satisfied a logarithmic function. Residual adfreezing strength (post-peak shear stress) varied with temperature and normal stress and presented three typical regular patterns—sustained stable, first stable and then fluctuating, and circularly fluctuating. The fluctuation cycle about strength curves increased with increasing roughness. An empirical formula on adfreezing strengths incorporating temperatures, normal stress, and roughness was constructed.