فصلنامه مدل سازی در مهندسی
پیاپی 19 (زمستان 1388)

Recently, identification of dynamic properties of structures such as bridges, towers and building, which are not easy to excite, is possible by measuring only the output responses. Due to measuring only the responses when the structure is excited only by ambient or operational forces, these methods are referred as output-only modal analysis or operational modal analysis (OMA). One drawback of OMA is that the mode shapes are not scaled. However the scaled mode shapes are required for some important applications such as damage detection or model updating. In this paper, a procedure is proposed for precise scaling of the operational mode shapes. The method is based on the sensitivity analysis of the effective parameters in the accuracy of scaling. The finite element model of a ten storey building is used to present the capability of the method. The natural frequencies and unscaled mode shapes have been estimated using FDD method and the mass change method is applied for scaling the mode shapes. The sensitivity of the results to the amount, location and the number of added masses and the number of modes under investigation have been evaluated. It is shown that the amount of added masses can be estimated by try and error of the FE model of structure and the masses should be distributed all over the structure to decrease the scaling error.

Dynamic analyses require many seismic data such as design acceleration and spectra of the site and earthquake records. This paper aims to predict peak ground acceleration, speed, and displacement using Artificial Neural Network (ANN). The proposed method of estimating PGA, PGV and PGD from earthquake parameters via a neural network has been applied to the database of the Next Generation Attenuation (NGA) project which includes 1950 recorded earthquake accelerograms classified into three sets according to the faulting mechanism for the training of the neural networks. The number of earthquake accelerograms for each mechanism (the strike-slip, reverse and reverse-oblique) is 650. Earthquake records have moment magnitudes between 4.5 and 7.9 Richter, distances from the recording site to epicentre ranging from 2.3 to 195 kilometres, hypocenter depths between 0.5 to 29 kilometres, and average shear-wave velocities in the top 30m ranging from 116 to 2016 m/sec. In the selected learning algorithm, the average speed of the shear wave in the top 30 metres, focal depth, magnitude and distance to source are the input variables, and Peak Ground Acceleration, Velocity and Displacement (PGA, PGV and PGD) values are used as output. Close match between the predicted values of the deployed method with the observed values and its ability to reduce or even eliminate the uncertainties in the attenuation relationships show that this method can be used as a reliable method for predicting the main parameters of strong ground motions. The results indicate successful performance for the artificial neural network algorithm in predicting the expected results.

Today, in Third-world countries such as Iran tendency the population growth and width of transportation and high rank of needed increase the number of cars and travels, that thi is increasing of the unreasonable of travel time and high rate of accidents. So the expection the density of passing traffic for a street and capacity analysis to extence and improvement of road network is too important. In this essay, we inspect truly the passing traffic of highway between Semnan-Garmsar simulating CORSIM software. Then with changeable geometric matters we analyse the changes of the density of passing traffic and the race of passing traffic. This highway is one of the important roadway in our country for transferring passengers and stuffs and is apart of road connectivity between west-east. CORSIM is a through going simulated software in science traffic engineering, which has the high capability in analysis of road network. As a result of lacking acquaince with this software, its used is limited in our country and until now it is uselessness about urban highway network. Geometritic and traffic information was received through real observation so that they have great accuracy.

In the process of effective and optimized planning and control, in order to manage the project, it is necessary to consider all the project aspects. Common techniques of project scheduling and control such as CPM and PERT assume unlimited resource availability in project network analysis; Developed networks due to theory derived of this techniques are networks that deal with time optimization of the activities. Consequently in this schedule and control methods, it is possible that during the project performance in some time periods, requirement to one or more resources is higher than the availability level or include more resource fluctuations. It can finally convert the project into an uneconomical project by a negative time and cost trade off or cause considerable deliveries in project performance time. This paper presents a technical method for controlling and optimizing resource allocation to project activities; This technique as an extension to the basic CPM and PERT approach presents a simple method for controlling the project schedule of resource allocation by considering their constraints and causes the optimized and efficient distribution of tasks to project levels; Finally by avoiding the simultaneous unnecessary use of several activates of a critical resource and by generating efficient levels of resource availability, it optimizes the project approaches.

According to the restrictive rules of pollution and vehicle's fuel consumption, extensive researches have been done for reduction them. These parameters not only depend on vehicle's characteristics, but also depend on driving in cities. These parameters are explained by driving city cycles. It is too difficult to obtain the results of cycle in experiment. So we innovate a new algorithm which estimates fuel consumption and pollution amount in standard cycles, having vehicle's characteristics and engine test results on dynamometer. A program was developed in MATLAB. Results of program for a typical vehicle has been compared and confirmed with experimental data and then we studied the effects of cycle that contains changing in accelerating duration, amount of accelerating speed, gear changing speed and duration of stopping vehicle in city cycle on fuel consumption.

Labyrinth spillways were considered as one of the appropriate options to pass PMF discharge where the system had difficulties. In a certain width in similar head these spillways with nonlinear crest can pass greater discharges compare to spillways with frontal crest. Since they pass large discharge under low hydraulic heads and need to smaller place in plane compare to other types of spillways, they are considered as economical structures. Therefore it is essential to apply optimum geometry with maximum passing discharge under specific hydraulic conditions with minimum construction cost. For this purpose in this research fuzzy inference system and genetic algorithms to optimize the spillway's geometry which satisfy the hydraulic conditions were used. To apply fuzzy inference system and to evaluate the coefficient based on available input - output pattern, from it ANFIS was employed. In this section in ANFIS model using experimental data input data such as angle of spillway walls along the flow (α), ratio of total head to spillway height (Ht/p), and discharge coefficient (Cd) were trained. Finally, using genetic algorithm and ANFIS model output, optimum geometry was found with defining the minimum cost function to satisfy appropriate hydraulic conditions.

Application of near-surface mounted (NSM) fiber reinforced polymer (FRP) is emerging as a promising technology for increasing shear strength of reinforced concrete (RC) members. However, most of studies in this field, have been performed experimentally and only very limited research is available on the numerical modeling of such beams using finite element (FE) method. This paper presents the results of a recent study in which a FE procedure was proposed to investigate the effects of conventional numerical modeling assumptions. In such methods, interfaces between concrete and steel stirrups and between concrete and FRP are not considered to predict the behavior of RC beams shear-strengthened with NSM-FRP. Despite the widespread use of these assumptions in numerical modeling of RC beams, their deficiencies and limitations have not been investigated in depth yet. Therefore, this paper presents a critical study on the FE modeling of NSM-FRP shear strengthened RC beams. For this aim, numerical modeling was carried out for two major groups of test beams. In the first group, specimens were selected from available experimental programs published in literature. For the second group, modeling was performed on three rectangular beams, built and tested in structural laboratory by cooperating of authors. Numerical results were compared by experimental findings. The load deflection response obtained from the proposed numerical method showed good agreement with the experimental plots. In some cases, such as cracking pattern and strain distribution in FRP and steel reinforcement, undesirable discrepancies were observed between FE and experiments. Maximum strain ratio between FE and experiments was reported in 0.66 to 0.89 for FRP and in 0.25 to 0.60 for steel stirrups.