Modeling in Engineering
Year:2011 | Volume:9 | Issue:24|Papers Count:7

Pounding of adjacent building have been seen in the moderate and strong earthquakes. There are different methods to model the impact. One of these methods is contact elements. Contact elements include linear and nonlinear elastic and viscoelastic and Hertz-damp elements. Investigators have generally studied on contact elements in elastic structures. In this study, the ability of different contact modelings is added to Opensees software. Validation of modeling is achieved by comparing the numerical result of this study with other investigations' numerical studies. Simulations between analytical modeling and experimental studies show that to conquer displacement, results of different contact elements are the same, but velocity and contact force results of elements with and without damping have more accuracy. Finally these elements are used to model the contact of 5-story building under 6 records, in two left to right and right to left states. As regards, Hertz-damp has the least uncertainty of modeling; therefore results of other elements are compared with this element. Results generally show that accuracy of nonlinear elements is more than linear elements. This is more obvious in the maximum contact forces.

In this paper, in order to determine optimal bidding strategy of GENCOs, considering uncertainty of market price, a stochastic model is presented. For this purpose, a two-stage stochastic model is proposed in which energy prices are considered as uncertain parameters. Furthermore, for taking into account the practical conditions, the producers have been granted the opportunity to sell their productions both through bilateral contracts and participating in energy auctions. The producer's financial risk is also evaluated using the well-known CVaR criterion. The proposed model is implemented on a test system and the obtained results are analyzed. The simulation results show that the proposed model can simulate market behavior effectively, obtain optimal bidding strategy and propose proper market selection with the aim of profit maximization.

Poly lactic acid polymers are biodegradable, having long and strong strands of polymer, when water reaches them they decompose to acids exist in the human body. These polymers, instead of platinum, are used as holding for broken bones. After the bones repair, the polymer decomposes and excreted from the body as water and carbon dioxide, so it is no need for surgery re-operation. The main goal of this study was investigation of degradation mechanism, decomposition time and its effective factors. In this paper decomposition kinetic of biodegradable polymers in human body was studied, which is complicated due to its autocatalytic nature. The governing equations with boundary and initial conditions were solved numerically. Variation of product concentration, concentration of polymer bands and water were presented against exposure time. The time needed for complete decomposition was calculated equal to 11 months. Diffusion coefficients, water concentration and geometry affect the degradation process. Finally, recommendations for optimum use of these materials were presented.

Dynamic relaxation method is an iterative procedure for solving the simultaneous system of equations. This technique is used in the static and dynamic nonlinear structural analysis. One of the most important parameters in this approach is fictitious damping factor. If this factor is selected more accurately, convergence rate will rise. In this paper, inverse vector iteration method is utilized to find the damping factor in the dynamic relaxation iterations, and a new formulation is proposed. The geometric nonlinear analysis of several plane and space trusses and also structural frames are performed using the suggested method. The numerical results indicate that the convergence rate improves compared with the conventional dynamic relaxation procedure so that the number of iterations and the analysis time decrease significantly. Consequently, the authors' technique makes the solving process faster and more capable.

In this paper, the results of study on seismic isolated buildings and effects of seismic gaps between such buildings and adjacent buildings during earthquake have been presented. The importance of this study can be explained as, the results can be used to evaluate the effects of seismic gap between structures which are subject to earthquake. Statistic information has been obtained by analyzing buildings with three, five and seven stories that were subjected to 20 earthquake records. Gaps among buildings changed based on characteristic of them with base isolation system; it can give us a better point. Each of structures was analyzed under the selected records and it was investigated effect of impact between them during earthquake on seismic demands. In addition for studying effects of pounding on seismic demand in structures with base isolated system, 540 nonlinear time history analysis was performed. At the end we suggested a simple and effective equation that can reduce effects of pounding on adjacent buildings.

Bearing capacity prediction of shallow strip foundations is one of the most important issues in geotechnical engineering. There are some bearing capacity equations and design charts proposed by researchers for this purpose. Most of the methods are for homogeneous and up to two layered subsoil. Recently, predicting bearing capacity of shallow foundations on multi layered soils have been interested. In this study, an artificial neural network is developed for bearing capacity prediction of shallow strip foundation based on cohesive multi layered subsoil. Training process of ANN needs a wide range of input data. In this study, a FEM is used for generating data for ANN. ANN has been trained for both kind of layered subsoil. Finally a multiple regression analysis which can generate a relationship between input parameters and target data is defined. Validation of neural network shows that an AAN can predict the ultimate bearing capacity of shallow strip foundation on cohesive layered subsoil with an acceptable accuracy. Effect of each parameter on ultimate bearing capacity of foundation using ANN is investigated. The results are compared with FEM and indicate that an ANN can evaluate the effect of input parameters with an acceptable accuracy. Validation of equations proposed for predicting bearing capacity of shallow foundations using multiple regression analysis indicates that this method can fit our purposes.

In most of the chemical engineering processes, the phenomena of mass and heat transfer are among their inseparable parts. In the present paper, simultaneous heat and mass transfer has been studied experimentally by a laboratory set up. In this apparatus, the existence of condensation and evaporation created due to heat transfer causes mass transfer and finally influences the coefficient of heat transfer. Also, mass transfer changes heat distribution in heat transfer phenomena that causes total change in heat flux. Thus, in this apparatus, some experiments have been carried out through changing different parameters such as temperature and flow rate for two fluids, water and air. Comparing the results obtained from these experiments and the ones gained from the process modeling, the existence of wall effect and its influence on the temperature of output water from the system were realized and process modeling was corrected again through applying wall effect. The studies conducted in the present research paper indicate that if the temperature and flow rate of air rises, the influence of wall effect increases and the change of wall effect has no significant change due to rise of the water temperature and flow rate, therefore, it is not an influential parameter.