فصلنامه مدل سازی در مهندسی
پیاپی 47 (زمستان 1395)

Flexural steel frames are one of the most commonly used building’s structural systems. The safety of this structural system could be affected by the uncertainties such as imperfectness in construction (especially for imperfect rigid connection), material properties and effect of unexpected loads. By considering these uncertainties and combination them with the probability theories and structural engineering, structural reliability investigates the safety level of structure. In this paper by employing the weighted simulation method, reliability and reliability-based design optimization of the flexural steel frames is investigated. For this purpose, by simultaneously using the firefly algorithm and the Radial Basis Function Meta-Model, a hybrid algorithm to approximate the failure probability and design point is proposed. The efficiency of proposed framework firstly evaluated by solving several numerical examples and then the safety and parameters sensitivity of a three-story steel frame under an artificial acceleration is investigated. The results of the safety evaluation presented good agreement with the accurate results obtained by the Monte Carlo simulation. Results of the safety evaluation and sensitivity analysis show that the imperfectness in connections rigidity highly affects the failure probability of the frame.

A variety of factors such as amount of load, velocity, wheel impact, time (loading rate), rest periods, temperature, and stress state, loading modes, aging and moisture can affect the asphalt behavior against deformation and efficiency. One of the most important factors is the effect of velocity on the tensile strain of the asphalt sub-layer, which leads to the most common type of failure (fatigue). In this study, using Abaqus, Ansys and 3D move soft wares, the desired and then a comparison between these three soft wares has been made. Dynamic modeling is conducted relying on the elastic behavior of layers. The study also includes the impact of loading speed on tensile strain of asphalt sub-layer. Results have indicated that Abaqus software compared with Ansys operates faster and more comprehensive for pavement analysis. In addition, 3D move compared with Abaqus and Ansys operates more rapidly in various model of the visco, but Abaqus has a more varied and stronger dynamic analysis. The comparisons between different velocities showed that high velocities include less fatigue failure. In general, the impact of velocity on the tensile strain in the asphalt sub-layer is more remarkable at low velocities. At low velocities, changes occur due to approaching to the static mode.

This paper presents a novel formulation for multilayer composite generation and transmission expansion planning considering the high penetration of wind farms. The proposed approach employs the so-called two-stage stochastic programming to cope with the uncertain nature of load demand and wind power and then find the optimal expansion plan among candidate generating units and transmission lines through the minimax regret criterion. Finally, the proposed approach is implemented on 24-bus reliability test system and the effect of the number of scenarios on the computational burden as well as the final optimal solution is evaluated.

Aim of this investigation is comparison of mass transfer artificial neural network (ANN) and mathematical model to prediction of carbon dioxide concentration in the exhaust air from the constructed module using glycol-amine liquid membrane. For solving of problem with ANN, command prompt function in Mathlab software was used with following instruction. First, input vector and targets are loaded in Mathlab current directory and a feed-forward tangent sigmoid transfer function in hidden layers and a linear transfer function in output layer was used. Then, the network was trained and Levenberg–Marquardt algorithm was used as training function. For this purpose, 74 input data inclusive input air pressure, input air flow rate, recovery value of CO2 in process was used. The CO2 mole fraction in output air was selected as target. Experimental data was divided in three sectors: 70% for training data, 15% for validation data and 15% for testing network. The optimum number of neurons in the hidden layer network obtained with using try and error method and the best performance of network achieved with four neurons in the hidden layer. Also, the best available models was used to predict mass transfer in liquid membranes, and exponential behavior was seen in modeling of permeating CO2 from membrane. The results of the ANN model were compared with the experimental results and this results were shown that the neural network has great ability to predict values. R-Value for mathematical model obtained 0.9839. Also, R-Value for network training, validation and testing was 0.9899, 0.9910 and 0.9975, respectively. Also, overalls R-Value was 0.9899 that proved a very good validation. Â

The main goal of total commercial banks is collect the saving of real and natural persons and allocate them in the form of facilities to industry, service and manufacturing companies. with the Non repayment of facilities from side of customers, the banks is faced with many problems such as disable in repayment of central banks, increasing the amount of facilities from customers repayment amount and disable in granted facilities. With increasing delayed demands and delaying in repayment of loans, the necessary of optimal allocation of facilities and investigation of bank credit portfolio is revealed. therefore, in current research, the modeling of predict the behavior of bank loan portfolios by using of Markov chain with limited state is investigated that includes (1) active loan or alive, (2) loan with one to three month delay in repayment, (3) delayed loan .transitional matrix between different states by historical information from the melli banks’ mortgage portfolio is achieved and then the timely prediction of payment number delays in repayment and Non repayment of facilities granted to certain portfolio is conducted. The results indicate that the proposed Markov model have the ability to accurately predict the behavior of credit bank portfolio. Key words: bank credit portfolio, Stochastic processes, discrete Markov chain.

Modeling and simulation of the bridge response during vehicle moving on it is very important in optimum bridge design. There are many researches in this field which some of them deals with studying of the structure and bridge uncertainty effects on the bridge-vehicle dynamic response. Some researchers are dealing with vehicle uncertainty that is uncertainty in mass, sprung, damping, velocity, numbers, incoming time and other mechanical parameters of the vehicles. Other researchers are considering the bridge parameters uncertainty like as module of elasticity, bearing immobility and mass of the bridge. Also in most of the researches, analytical and Monte-Carlo simulations have been used for obtaining the dynamic response of the bridge with considering mentioned uncertainty. However there isn’t any accurate and general statistical study on the bridge response with general uncertainty. In other words, the complete set of uncertainty of the vehicles or bridge has not been applied in modeling and also the exact statistical study of the dynamic response of the bridge has not been applied exactly. Therefore in this paper, after modeling of the bridge-vehicle system with coupled finite element beam and discrete vehicle model, most of the uncertainties of the vehicles have been produced with Gaussian probability distribution function and the statistical parameters of the response have been extracted by Monte-Carlo simulation. The selected model applied in this paper is a discrete model of vehicle with four degree of freedom mass sprung system. Also, the Euler-Bernoulli model was used for bridge and the coupled dynamic equation was extracted using finite element modeling of the beam with Hermitian interpolation function for suitably dividing the vehicle forces, applied on the beam elements nodes. In addition the different road surface using ISO standard was applied on the finite element beam model. One of the major contributions of this paper is considering the type of the vehicle crossing on the bridge as an additional uncertain parameter which is not mentioned in the previous literatures. In other words, three classes of the vehicle that is heavy, semi-heavy and light ones was applied in simulation as uncertain parameters. The mechanical characteristics of the vehicle were derived by CARSIM software and by Monte-Carlo simulation using uniform probability distribution function. Then mentioned parameters was produced and entered in New-Mark simulation steps. With studying on the deflection, velocity, acceleration of the bridge and also considering corresponding upper and lower limit band (confidence interval) and variance of the mentioned parameters, extended results of uncertainties effects have been obtained. It should be mentioned, in this paper an exact statistical test method was used for obtaining the statistical properties of the dynamic response. Also, in different road surface and conditions, the simulation was carried out such that four surfaces of the bridge and three type of the vehicle classes was simulated separately and finally one simulation was done in complete set of the uncertainty. Very detailed and complete results were studied and one of the important results of this paper is reporting the most effective uncertainties on the bridge response. As one of the results, it was found that with increasing the velocity of the vehicle, surface roughness and weight of the vehicle, the uncertainty of the response are increasing. As another important result is that the fundamental frequencies of the bridge is less sensitive to the uncertainties of the vehicle's parameters. Derived results of this paper can be applied in optimum designs of the bridges and also in designing the damage identification methods.

Many of the existing buildings are made and designed in according to Standard No.2800 (1st Edition). in recent years Increasing in earthquake engineering knowledge and changing in design criteria regulations and seismic evaluation has caused that the existing structures meet local or general deficiencies in seismic requirements. Therefore, the identification and development of appropriate methods is necessary for seismic rehabilitation of existing structures and providing levels of design performance. In this study, the nonlinear seismic behavior of six steel buildings with steel moment frame systems that have modeled in 4, 8 and 12 stories designed according to the criteria of the First Edition 2800 Standard and Publication 519 and has been investigated using nonlinear static analysis. The evaluation results indicate that the existing steel moment frames that are designed according to the Standard No.2800 (1st Edition) cant provide Stiffness and ductility requirements of the Standard No.2800 (3rd Edition) and FEMA356 and must be rehabilitated. The frames Improved by concentrically steel braces, increases stiffness and reduces lateral displacement however, due to buckling of the compression braces, structures suffered a sudden drop in strength and its behavior is not ductile. The use of eccentrically braces due to concentrated plastic deformation in link beams and elastic braces, structural behavior is more ductile in comparison with concentrically braced frames method. The use of buckling restrained braces, due to compressive brace is not buckling and yields in tensile, has caused increase in stiffness, strength and ductility of structure and has improved structural performance in comparison of concentrically braced frames .