Modeling in Engineering
Year:2017 | Volume:14 | Issue:47 |Papers Count:20

Flexural steel frames are one of the most commonly used buildings 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.

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.

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 isnt 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 vehicles' 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) can' t 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.

Turbine rotor unbalance leads to reduction in performance, wear of the parts and damage. Departure of the mass and center of mass of the blades from their ideal values, manufacturing errors in the wheel and uneven distribution of other parts like shims, are considered as the main sources of unbalance in rotors. Before dynamic balancing of rotor, an optimum distribution of the blades and other parts is needed to be found, such that there remains minimum static unbalance in a stage. To achieve such distribution, the weight moment of the individual blades and other parts are measured in advance. There have been several algorithms in the literature for finding the optimum distribution, however they do not take into account the initial unbalance of the wheel and uneven distribution of the shims. In this paper, a method is proposed to find a distribution of the blades and spacer shims, if any, such that the initial unbalance of the wheel is canceled and the unbalance of the stage is minimized. The results of the proposed method is compared with those obtained from other algorithms and two cases worked out by active companies in this area. The residual unbalances obtained from the proposed method are up to 10 times lower than the minimum values that can be achieved by the other method and, shows an improvement of up to 108 times for the two cases mentioned.

In this investigation, a numerical method based on potential flow for aerodynamic analysis of BWB aircrafts has been developed. At first, results of this method are validated with experimental data and then, three current BWB planforms have been chosen and analyzed to determine suitable planform for BWB aircrafts. The results show that aerodynamic characteristics of (A) and (B) planforms are better than (C) planform. On the other hand, the (A) planform has better a uniform lift distribution along the span, less induced drag, more space and less noise than (B) planform. Finally, the (A) planform is a suitable configuration for BWB aircrafts.

Dynamical stability of mobile robots becomes important and it should be discussed when there is a need of high speed motions. This problem can be solved by appropriate design of control signal with stability constraints. But, actually this is, in many cases, impossible or at least unbearable. In this paper, we have noticed balancing approach for this problem to significant reduction of control effort. Based on fixed-point approach the values of counterweights are computed and finally this iterative method drives the mobile robot through a stable trajectory. This novel method is called iterative balancing of mobile robots and final stable trajectory has very low pay-off in compare of unbalanced constrained one. The results are investigated by simulating of open loop control of mobile robot.

Blowdown Supersonic Wind Tunnels (SWTs) are generally operated with a constant stagnation pressure in the settling chamber, with control usually provided by one or more pressure regulators or control valves. In this paper, first, a Simulink block diagram code was developed to solve the nonlinear mathematical model of the special BSWT consisting of a set of ordinary differential and algebraic equation that derived from mass and energy conservation equations. At the second step, a Proportional-Integral (PI) controller system was developed in Matlab/Simulink software environment to control the stagnation pressure in the settling chamber and Mach number in the test section. Next, the PI controller parameter is optimized by an intelligent approach such as using Genetic Algorithm (GA). At last, experimental verification has been carried out for supersonic conditions to show the system robustness. Also the system simulation results with the optimized controller for a Mach 3 blowdown run is presented. The results illustrate a great performance of the BSWT model and its controller.

In this research, a multi-objective mix integer programming for supply chain is proposed in which forward and reverse logistic is considered, simultaneously. In addition to cost, minimization of the environmental influences such as carbon dioxide emission and water consumption and also the social issues such as generated jobs and their equitable distributionis considered. Moreover, it is assumed that the demand is uncertain and the problem has been modeled using robust optimization. Proposed model determines the type of technology and capacity of facilities other than optimal location and flows between them. Eventually, the efficiency of robust model is investigated by applying it on steel industry as a case study.

In this paper, a mathematical modeling of nested hierarchical p-center problem is presented. In this model there are two levels of hierarchies and the first one should be passed to achieve the second level. The second level facility can provide both services of the first and the second level. This model is a linear integer mathematical programming model. To provide an application of the model, some simulated cases are investigated and resolved, the results show that using this model reduces the initial construction cost while the main objective which is maximum servicing distance will not be changed basically.for the large size problem using of metaheuristic algorithms is necessary so in this paper an algorithm based on the Particle swarm intelligence is proposed to solve the problem. Numerical results confirm efficiency of the algorithm.

Today, the most important risk and challenge addressed in e-commerce and e-banking is the risk of online fraud and phishing attacks. Phishing attacks have been one of widely used tools for attackers to steal passwords and electronic codes of users in e-exchanges in cyberspace. In this type of fraud, fraudulent orphisher sends emails with various claimsto the victim and directs the victim to his fake pages by several different techniques. Then, he attempts to steal sensitive information of users such as passwords. Web pages, emails and phishing addresses have features that can be used to detect these attacks. In this paper, an approach will be presented to identify and predict phishing web sites using classification algorithms based on web page features which has less error rate than other techniques to deal with phishing attacks, especially the similar techniques based on data mining algorithms. In the proposed approach, the usable features in the detection of phishing pages are weighted basedon the effect to detect these attacks and then a pattern will be elicited to identify these attacks by applying classification algorithms on the relevant datasets. our approach can detect journal phishing attacks and has low error rate than previous approaches.

The scattering and uncertainty of the Ore grades data, are the important parameters in the design of open pit mines, as they have considerable effect in estimating the economic value of the extraction process. Because the purpose of any economic activity is to achieve maximum benefit, the uncertainty as a negative value, which is considered as equivalent costs, have negative effect on the other economic parameters in mining operations. In this paper, to investigating the impact of grades uncertainty on the push-backs designing of Chadormalu Iron Mine, the Gholamnejad Heuristic algorithm (2005) is described at first, then considering the difference between the mean grades in the each block to the mining cut-off grade, the algorithm is corrected and a new economic relation, proposed. In the new relationship, economic value of the the blocks can estimated more logically. Then, using a three-dimensional floating cone in the PLP macro, the results of economic calculations for the net values, shows the two major designs for the mine cavity. Based on these results, for certainty up to 81 percent the the cavity has single set of designs, and from 81 to 100 percent of certainty another set of mining advanced planing is achived. The results indicate that the mine cavity design using the new relationship, considering the difference of the average grade of the block to the mining cut-off grade, In addition to the impact of scattering of the data, have positive impact on the economic calculations and can estimate values more real.

Query expansion as one of query adaptation approaches, improves retrieval effectiveness of information retrieval. Pseudo-relevance feedback (PRF) is a query expansion approach that supposes top-ranked documents are relevant to the query concept, and selects expansion terms from top-ranked documents. However, Existing of irrelevant document in top-ranked documents is possible. Many approaches have been proposed for selecting relevant documents and ignoring irrelevant ones, which use clustering or classification of documents. Important issue in query expansion approaches is using relevant documents for selecting expansion terms. In this paper, we propose clustering of pseudo-relevant documents based on query sensitive similarity, which is efficient for placing similar documents together. Query sensitive similarity obtained good results in document retrieval rather than term-based similarity, is the reason for using in this paper. Clusters are ranked based on inner similarity, and some top ranked ones are selected for query expansion. Then, we extract expansion terms from documents of selected clusters based on Term Frequency- Inverse document frequency (TF-IDF) scoring function. Conducted experiments over Medicine dataset (MED) shows that retrieval results for expanded queries with selected documents from clusters is better than basic retrieval (VSM) and Pseudo-relevance feedback. In addition, the effectiveness of retrieval is raised.

Since railway transportation is one of the greenest and safest ways for carrying passengers and freight, investigation on improving the performance of its sub-systems can be in line with requirements of industry. One of the most important sub-systems of each vehicles is its driving part. Due to smoothness of wheel and rail, comparing moving car on road, moving on rail needs more less energy. But this low friction can cause wheel slip and wheelspin. Rising the wheel slip more than a certain value, will cause decrement in acceleration and damages wheel and rail, so the control of wheel slip has a special importance. Therefore having a model of trainâ s speed control system equipped with wheel slip control can be useful. In this paper after literature survey of wheel slip control, by combining the movement equation and using an adhesion observer the mechanical part of system is obtained. For driving the induction motor of drive system, field oriented control is choose. By combining the mechanical part, induction motor and its drive the complete model is presented. By simulation in different operation points the performance of presented model is validated.

One of the most common systems to collect the suspended particles from the air is fibrous filters. An important parameter to evaluate the filters performance is pressure drop. In this work the influence of the arrangement of the fibers at the fibrous media on the pressure drop is studied. Three different parallel, staggered and random arrangements are considered to model the fibrous media. The effects of these arrangements are investigated at different solid volume fractions. The results are compared and discussed with existing empirical and semi analytical relations. It is observed that using regular arrangement results in larger pressure drop than random one or which is predicted by empirical tests.