Scientia Iranica
Volume:20 Issue: 2, 2013

Tuned Mass Dampers (TMDs) are a well-accepted control device widely used by the civil engineering community. The main purpose of this study is the robust multi-objective optimization design of this device using Genetic Algorithms (GAs) to control the structural vibrations against earthquakes. To enhance the performance of the TMD system, its parameters, including mass, stiffness, and damping ratio, have been optimally designed using multi-objective genetic algorithms. For doing this, three non-commensurable objective functions, namely: maximum displacement, maximum velocity, and maximum acceleration of each floor, are considered, which are to be minimized simultaneously. For this purpose, a fast and elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. Moreover, in order to take into account the uncertainties existing in the system, a robust design optimization procedure is performed using the Hammersley sequence sampling approach. In this study, the example building is modeled as a 3-D frame, and its responses are evaluated using coupled multi-mode analysis. From the numerical results of the study, it is found that the robust TMD system is capable of providing a reduction of about 28% on maximum displacement of the building.

The step-pool spillway is inspired by rhythmic sequences of steps and pools in steep mountain streams. By mixing the hydraulic process of stepped spillways and mountainous river step-pool systems, a new kind of stepped spillway, called the step-pool spillway, was designed for a noticeable increase in energy dissipation. The step-pool spillway has increasingly turned into an effective energy dissipator. However, until now, most studies on step-pool spillway overflow have been based on the model test. In this study, the two-phase flow over two types of step-pool spillway was investigated using two-phase schemes (Volume Of Fluid (VOF) and mixture) and various turbulence modeling. Numerical simulation of two-phase flow was carried out on two types of step-pool spillway with various slopes. Comparison of the energy dissipation rates and flow field variables of the present simulation with those of experimental models is presented. Results show that the mixture model with the Reynolds Stress turbulence Model (RSM) is suitable for simulation of two-phase flow over spillways.

There are many parameters utilized to obtain a more reasonable performance for structures under earthquake excitations in seismic provisions. General considered parameters in seismic provisions are: PGA, importance factor (I) and typical inherent overstrength and global ductility capacity (R). It is well recognized that the main characteristic of the design of structures under seismic excitation is probabilistic rather than deterministic; therefore, it should be determined if whether the probability of structural damage decreases when such parameters change in the design of structures. In this paper, fragility curves are developed in order to evaluate these parameters. Fragility curves are employed for various probability parameters. These diagrams are utilized to demonstrate when a coefficient or a number of parameters are used to improve the performance level of a structure. Moreover, it guarantees that the probability of exceedance of the damage limit state decreases, as expected. These diagrams can further illustrate the effect of uncertainty of design parameters. After introducing fragility curves and the application procedure, the effect of the uncertainty of the PGA is displayed and discussed. The results reveal that by increasing the global ductility capacity (R), the probability of damage exceedance is decreased; however, an increase in importance factor (I) for hospital buildings versus office buildings, cannot guarantee a decrease in the probability of damage exceedance. The PGA randomness results reveal that considering PGA uncertainty does not mean that the probability of damage exceedance will be increased in general cases.

Lateral spreading and flow failure are amongst the most destructive effects of liquefaction. Estimation of the hazard of lateral spreading requires characterization of subsurface conditions, principally soil density, fine content, groundwater conditions, site topography and seismic characteristics. However, inaccuracies in the measurement or estimation of the influencing parameters have always been a major concern and, thus, various statistical approaches have been improvised to subdue the effect of such inaccuracies in the prediction of future events.Very few empirical correlations consider the effect of uncertainties in predicting the extent of lateral movement. Hence, in this article, an innovative approach, based on robust optimization, has been utilized to enumerate the effect of such uncertainties. In order to assess the merits of the proposed approach, a database containing 526 data points of liquefaction-induced lateral ground spreading case histories from eighteen different earthquakes, is used.The identification technique used in this article is based on the robust counterpart of the least squares problem, which is a second order cone problem, and is efficiently solved by the interior point method. A definition of uncertainty, based on the Frobenius norm of the data, is introduced and examined against the correlation coefficients for various empirical models, including a new linear model, and, thereby, optimum values are determined.The results suggest that in comparison with Al Bawwab models, the robust method is a better pattern recognition tool for datasets with degrees of uncertainty. It is further shown that logarithmic correlations perform better in deterministic valuation, whereas, considering uncertainty, they give similar degrees of accuracy to the new linear model.

Free surface vortex and air entrainment are not favorable experiences in hydropower and pumping projects. While complete omission of vortex and air entrainment is not always cost effective, partially weakened free-surface vortex flow is more economical and practical. Hence, in this study, a comprehensive set of experiments were conducted to partially reduce vortex strength and air entrainment at vertical pipe intakes, using rectangular anti-vortex plates. This phenomenon results in increasing water discharge compared with a corresponding free-surface vortex for the same water depth, i.e. in cases of shaft spillway. The plates were used as singles and in pairs and placed symmetrically and asymmetrically, with respect to the pipe axis. Accordingly, the results of partially entrained air using anti-vortex plates were presented as graphs and practical equations. Finally, design guides and recommendations were provided to predict the effects of plate geometries and positions on free-surface vortex strength.

A methodology for the design of a rain gauge network is developed in this study. To the best of the authors’ knowledge, this is the first time a combination of geostatistical tools and factor analysis, along with a clustering technique, has been used to prioritize rain gauge stations in terms of information content over the study area. The whole study area is divided into homogeneous subregions and a conventional variance-based approach is implemented in each subregion to rank rain gauge stations. For this purpose, factor analysis coupled with ordinary block kriging is used to identify the number of homogeneous subregions, and then, ordinary point kriging is used to assign rain gauge stations to each subregion. The developed scheme is quite time-efficient as it is not sensitive to initial guesses on cluster centers, there is no need to specify the number of clusters in advance and, above all, it is highly relevant to the overall objective stipulated in rain gauge network design. The proposed methodology is implemented on real data set in the south west of Iran. The results show that the proposed approach compares well with existing paradigms in rain gauge network design and only six rain gauge stations are required to provide the necessary information. In particular, the measure of network accuracy lies somewhere in between the so called time consuming and more simplified approaches used in rain gauge network design.

This paper presents the results of parametric analyses of the yielding moment (image) of Bolted Flush Endplate Beam (BFEB) splice connections using Finite Element Modeling (FEM) tools. The connection components were modeled using three-dimensional brick elements, while contact between the endplates was modeled using Coulomb friction. Materials for beam, endplate and bolts were considered to behave non-linearly. Finite element results with three experimental and numerical studies were compared, and all indicated good agreement, which is also briefly reviewed in this paper. Using verified FEM, fairly large parametric studies, based on the practical configuration of BFEB connections, were carried out to investigate the yielding moments with variations in size of beam flange, beam web, thickness of endplate, and diameter, as well as vertical and horizontal pitch, of bolts. Finally, the investigation results are summarized to access the prediction equations for image as functions of geometric variables of the BFEB connections. Due to the multitude of influencing parameters, the objective parameters have been normalized by using the prediction of theoretical models, which is established upon the component method presented. The method for accuracy in predicting values, regarding the image of a BFEB connection, is also discussed.

The fundamental goal of a pipeline utility is to serve its customers with a low cost water supply of acceptable quality. The number, type, size, and location of transient protective devices play a direct role in the pipeline system reliability and expenditure. The purpose of this study is to optimize the design of these devices to prevent water column separation after source pump power failure. The minimum pressures along the pipeline are assumed to be higher than “−10 m” to avoid water column separation. A rational, systematic, and efficient optimization algorithm is constructed by combining the Fuzzy Inference System (FIS) and the Genetic Algorithm (GA). The FIS representing expert knowledge is incorporated into the GA approach to improve its fitness evaluation process. Three cases are presented to demonstrate the effectiveness and efficiency of the proposed hybrid approach

This paper describes the development of a car driving cycle for the city of Tehran and its suburbs using a new approach based on driving data clustering. In this study, driving data gathering is performed under real traffic conditions using Advanced Vehicle Location (AVL) devices installed on private cars. The recorded driving data is then analyzed, based on “micro-trip” definition. Two driving features including “average speed” and “idle time percentage” are calculated for all micro-trips. The micro-trips are then clustered into four groups in driving feature space using the image-means clustering method. For development of the driving cycle, the nearest micro-trips to the cluster centers are selected as representative micro-trips. The new method for driving cycle development needs less computation compared to the SAPM method. In addition, it benefits the capability of the image-means clustering method for traffic condition grouping. The developed driving cycle contains a 1533 s speed time series, with an average speed of 33.83 km/h and a distance of 14.41 km. Finally, the characteristics of the developed driving cycle are compared with some other light vehicle driving cycles used in other countries, including FTP-75, ECE, EUDC and J10-15 Mode.

Numerical investigations have been carried out on bed load sediment transport in a river with uniform steady flow. The Lagrangian method is applied to develop the numerical model. The numerical method is a modified and improved version of the latest introduced Smoothed Particle Hydrodynamic scheme for incompressible fluid, which was named I-SPH. The model is applied to calculate the bed load sediment transportation rate, as well as the moving pattern, of granular and non-cohesive sediments located on the bed of a river. The presented numerical scheme, which is improved to be applicable for Multi-Phase fluids, is named MPM-I-SPH. It is concluded that the developed model is reliable for prediction of the moving pattern of sediments, including velocity and location, near to the bed.