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Showing 29 results for Simulation

M. H. Shojaeefard, F. A. Boyaghchi , M. B. Ehghaghi ,
Volume 17, Issue 4 (11-2006)
Abstract

In this paper the centrifugal pump performances are tested when handling water and viscous oils as Newtonian fluids. Also, this paper shows a numerical simulation of the three-dimensional fluid flow inside a centrifugal pump. For these numerical simulations the SIMPLEC algorithm is used for solving governing equations of incompressible viscous/turbulent flows through the pump. The k-ε turbulence model is adopted to describe the turbulent flow process. These simulations have been made with a steady calculation using the multiple reference frames (MRF) technique to take into account the impeller- volute interaction. Numerical results are compared with the experimental characteristic curve for each viscous fluid. The data obtained allow the analysis of the main phenomena existent in this pump, such as: head, efficiency and power changes for different operating conditions. Also, the correction factors for oils are obtained from the experiment for part loading (PL), best efficiency point (BEP) and over loading (OL). These results are compared with proposed factors by American Hydraulic Institute (HIS) and Soviet :::union::: (USSR). The comparisons between the numerical and experimental results show good agreement.


J. Fathikalajahi, M. Baniadam , R. Rahimpour ,
Volume 19, Issue 3 (7-2008)
Abstract

 An equation-oriented approach was developed for steady state flowsheeting of a commercial methanol plant. The loop consists of fixed bed reactor, flash separator, preheater, coolers, and compressor. For steady sate flowsheeting of the plant mathematical model of reactor and other units are needed. Reactor used in loop is a Lurgi type and its configuration is rather complex. Previously reactor and flash separator are modeled as two important units of plant. The model is based on mass and energy balances in each equipment and utilizing some auxiliary equations such as rate of reaction and thermodynamics model for activity coefficients of liquid. In order to validate the mathematical model for the synthesis loop, some simulation data were performed using operating conditions and characteristics of the commercial plant. The good agreement between the steady state simulation results and the plant data shows the validity of the model.
H.r. Khakdaman, M. Abedinzadegan Abdi, H.a. Ghadirian, A.t. Zoghi,
Volume 19, Issue 3 (7-2008)
Abstract

Abstract: The use of mixed amine system in gas treating processes is increasing today. For natural gas sweetening purposes, mixed amines are typically mixtures of MDEA and DEA or MEA that enhance CO2 removal while retaining desirable characteristics of MDEA such as reduced corrosion problems and low heats of reaction. In this work, a process simulator was used to predict the performance of an Iranian gas sweetening plant with a sour gas feed containing 6.41% CO2 and 3.85% H2S on molar basis. Various mixtures of diethanolamine (DEA) and Methyl diethanolamine (MDEA) were used to investigate the potential for an increase in plant capacity. It was noticed that the process simulator is quite capable in predicting the existing plant performance and can potentially guide in selecting the optimum blend composition. It was also noticed that a substantial increase in plant capacity is quite possible by just adding MDEA to the existing solvent and keeping the solvent flow rate and stripper reboiler heat duty. In another word, it is possible to increase the plant capacity from 293 to 357 MMSCFD using a mixed amine system.
A. Nicknam, S. Yaghmaei Sabegh, A. Yazdani,
Volume 19, Issue 3 (7-2008)
Abstract

  Abstract : The main objective of this study is estimating the strong motion for the Bam region using the stochastically based seismological models. The two widely used synthetic techniques namely point-source and finite-fault were utilized incorporating the source-path and site parameters into simple function. The decay factor kappa was estimated based on the data obtained from recorded strong motions to be used as an appropriate factor for the region. The results were validated against those of the recorded data during the destructive 26 December 2003 Bam earthquake in south east of Iran. The efficiency of these methods and estimating the appropriate regional model parameters are the main objectives of this study. The results of the synthesized ground motion, such as acceleration time history, PGA and elastic response spectra were compared /assessed with those of observed data. The Bias model (MB) is used to assess the validation of the simulated earthquakes against recorded horizontal acceleration time histories. The %90 confidence interval of the means averaged over the whole stations using t-student distribution was evaluated and it was shown to be in an acceptable range. The elastic response spectra of the simulated strong motion are showed to be in a good agreement between the recorded waveforms confirming the acceptability of the selected/evaluated source-path-site model parameters. The sensitivity of the simulated PGA and response spectra against kappa factor as well as the path-averaged frequency-dependent quality factor Q, is studied and discussed.


K. Shahanaghi, V.r. Ghezavati,
Volume 19, Issue 4 (12-2008)
Abstract

  In this paper, we present the stochastic version of Maximal Covering Location Problem which optimizes both location and allocation decisions, concurrently. It’s assumed that traveling time between customers and distribution centers (DCs) is uncertain and described by normal distribution function and if this time is less than coverage time, the customer can be allocated to DC. In classical models, traveling time between customers and facilities is assumed to be in a deterministic way and a customer is assumed to be covered completely if located within the critical coverage of the facility and not covered at all outside of the critical coverage. Indeed, solutions obtained are so sensitive to the determined traveling time. Therefore, we consider covering or not covering for customers in a probabilistic way and not certain which yields more flexibility and practicability for results and model. Considering this assumption, we maximize the total expected demand which is covered. To solve such a stochastic nonlinear model efficiently, simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.


H. Arabi, M.t Salehi, B. Mirzakhani, M.r. Aboutalebi , S.h. Seyedein , S. Khoddam,
Volume 19, Issue 5 (7-2008)
Abstract

Hot torsion test (HTT) has extensively been used to analysis and physically model flow behavior and microstructure evolution of materials and alloys during hot deformation processes. In this test, the specimen geometry has a great influence in obtaining reliable test results. In this paper, the interaction of thermal-mechanical conditions and geometry of the HTT specimen was studied. The commercial finite element package ANSYS was utilized for prediction of temperature distribution during reheating treatment and a thermo-rigid viscoplastic FE code, THORAX.FOR, was used to predict thermo-mechanical parameters during the test for API-X70 micro alloyed steel. Simulation results show that no proper geometry and dimension selection result in non uniform temperature within specimen and predicted to have effects on the consequence assessment of material behavior during hot deformation. Recommendations on finding proper specimen geometry for reducing temperature gradient along the gauge part of specimen will be given to create homogeneous temperature as much as possible in order to avoid uncertainty in consequent results of HTT.


F. Bazdidi Tehrani, H. Feizollahi ,
Volume 19, Issue 5 (7-2008)
Abstract

The mixing characteristics of coolant air jets with the hot gas exiting the gas turbine combustor’s primary zone is of major importance to the combustor exit temperature profile. In the present work, a three dimensional numerical simulation on the basis of the finite volume method was developed. The aim was to investigate the penetration and mixing characteristics of directly opposed rows of coolant jets injected normally into a heated confined cross stream. The ability of the standard and the realizable κ-ε turbulence models in the prediction of formation of dimensionless temperature profiles, downstream of jets, was evaluated. The effect of jet-to-mainstream momentum flux ratio, in the lower and upper limits of 25.0 and 60.0, at a fixed channel height-to-hole diameter ratio of 12.5 and a periodic distance of adjacent jets of 2 cm, was investigated. Also the effect of periodic distance in the range of 1-3 cm on the temperature profile was studied. Comparisons between the present numerical results on the temperature profiles and the experimental data of Wittig et al. [13] demonstrated reasonable agreement.

 

Keywords:  
Morteza Montazeri-Gh, Mahdi Soleymani ,
Volume 19, Issue 5 (7-2008)
Abstract

In previous studies, active suspension system in conventional powertrain systems was investigated. This paper presents the application of active suspension system in parallel hybrid electric vehicles as a novel idea. The main motivation for this study is investigation of the potential advantages of this application over the conventional one. For this purpose, a simultaneous simulation is developed that integrates the powertrain and active suspension systems in a unified media where the power and input data between two systems are exchanged. Using this concurrent simulation tool, the impact of the active suspension load on the internal combustion engine response is studied for both conventional and hybrid electric configurations. The simulation results presented in this study show that there are quite remarkable advantages for application of the active suspension in parallel hybrid electric vehicles in comparison with the conventional one.


Kamran Shahanaghi, Hamid Babaei , Arash Bakhsha,
Volume 20, Issue 1 (5-2009)
Abstract

In this paper we focus on a continuously deteriorating two units series equipment which its failure can not be measured by cost criterion. For these types of systems avoiding failure during the actual operation of the system is extremely important. In this paper we determine inspection periods and maintenance policy in such a way that failure probability is limited to a pre-specified value and then optimum policy and inspection period are obtained to minimize long-run cost per time unit. The inspection periods and maintenance policy are found in two phases. Failure probability is limited to a pre-specified value In the first phase, and in the second phase optimum maintenance thresholds and inspection periods are obtained in such a way that minimize long-run expected.
A. Shariat Mohaymany , S.m.mahdi Amiripour,
Volume 20, Issue 3 (9-2009)
Abstract

Local bus network is the most popular transit mode and the only available transit mode in the majority of cities of the world. Increasing the utility of this mode which increases its share from urban trips is an important goal for city planners. Timetable setting as the second component of bus network design problem (network route design timetable setting vehicle assignment crew assignment) have a great impact on total travel time of transit passengers. The total travel time would effect on transit utility and transit share of urban trips. One of the most important issues in timetable setting is the temporal coverage of service during the day. The coverage of demand is an objective for setting timetables which has not been well studied in the literature. In this paper a model is developed in order to maximize the temporal coverage of bus network. The model considers demand variation during the day as well as the stochastic nature of demand. A distribution function is used instead of a deterministic value for demand. The model is then implemented to an imaginary case.
M. Ebrahimi, R. Farnoosh,
Volume 20, Issue 4 (4-2010)
Abstract

This paper is intended to provide a numerical algorithm based on random sampling for solving the linear Volterra integral equations of the second kind. This method is a Monte Carlo (MC) method based on the simulation of a continuous Markov chain. To illustrate the usefulness of this technique we apply it to a test problem. Numerical results are performed in order to show the efficiency and accuracy of the present method.
Rasoul Haji, Mohammadmohsen Moarefdoost, Seyed Babak Ebrahimi,
Volume 21, Issue 4 (12-2010)
Abstract

  This paper aims to evaluate inventory cost of a Two-echelon serial supply chain system under vendor managed inventory program with stochastic demand, and examine the effect of environmental factors on the cost of overall system. For this purpose, we consider a two-echelon serial supply chain with a manufacturer and a retailer. Under Vendor managed inventory program, the decision on inventory levels are made by manufacturer centrally. In this paper, we assume that the manufacturer monitors inventory levels at the retailer location and replenishes retailer's stock under (r, n, q) policy moreover, the manufacturer follows make-to-order strategy in order to respond retailer's orders. In the other word, when the inventory position at the retailer reaches reorder point, r, the manufacturer initiates production of Q=nq units with finite production rate, p. The manufacturer replenishes the retailer's stock with replenishment frequency n, and the complete batch of q units to the retailer during the production time. We develop a renewal reward model for the case of Poisson demand, and drive the mathematical formula of the long run average total inventory cost of system under VMI. Then, by using Monte Carlo simulation, we examine the effect of environmental factors on the cost of overall system under VMI .


F Etebari, M. Abedzadeh , F. Khoshalhan,
Volume 22, Issue 1 (3-2011)
Abstract

Improvement in supply chain performance is one of the major issues in the current world. Lack of coordination in the supply chain is the main drawback of supply chain that many researchers have proposed different methodologies to overcome it. VMI (Vendor-managed inventory) is one of these methodologies that implementing it has some obstacles. This paper proposes new model that is agent-managed SC. This paper is trying to use intelligent agent technology in the supply chain. In this paper supply chain assessment performance measure indicators have been divided into three categories cost, flexibility and customer responsiveness indicators. In the first category we use holding and backordered inventory costs, for second category, bullwhip effect are used and for the last one customer responsiveness indicator has been applied. Bullwhip effect is one of the main phenomena’s that has been tried to reduce it with the agent-based systems.
Yahia Zare Mehrjerdi, Maryam Dehghan,
Volume 24, Issue 1 (2-2013)
Abstract

Abstract In the dynamic and competitive market, managers seek to find effective strategies for new products development. Since There has not been a thorough research in this field, this study is based on a review on the risks exist in the NPD process and an analysis of risks through FMEA approach to prioritize the existent risks and a modeling behavior of the NPD process and main risks using system dynamics. First, we present new product development concepts and definition. We then based our study on a literature review on the NPD risks and then provide an FMEA approach to define risks priority. Using the obtained main risks, we model the NPD process risks applying system dynamics to analyze the system and the risks effect on. A safety clothing manufacturer is considered as a case study.
Mostafa Khanzadi, Farnad Nasirzadeh, Mahdi Rezaie,
Volume 24, Issue 3 (9-2013)
Abstract

Allocation of construction risks between clients and their contractors has a significant impact on the total construction costs. This paper presents a system dynamics (SD)-based approach for quantitative risk allocation. Using the proposed SD based approach, all the factors affecting the risk allocation process are modeled. The contractor’s defensive strategies against the one-sided risk allocation are simulated using governing feedback loops. The full-impact of different risk allocation strategies may efficiently be modeled, simulated and quantified in terms of time and cost by the proposed object-oriented simulation methodology. The project cost is simulated at different percentages of risk allocation and the optimum percentage of risk allocation is determined as a point in which the project cost is minimized. To evaluate the performance of the proposed method, it has been implemented in a pipe-line project. The optimal risk allocation strategy is determined for the inflation risk as one of the most important identified risks.
M. Reza Peyghami, Abdollah Aghaie, Hadi Mokhtari,
Volume 24, Issue 3 (9-2013)
Abstract

In this paper, we consider a stochastic Time-Cost Tradeoff Problem (TCTP) in PERT networks for project management, in which all activities are subjected to a linear cost function and assumed to be exponentially distributed. The aim of this problem is to maximize the project completion probability with a pre-known deadline to a predefined probability such that the required additional cost is minimized. A single path TCTP is constructed as an optimization problem with decision variables of activity mean durations. We then reformulate the single path TCTP as a cone quadratic program in order to apply polynomial time interior point methods to solve the reformulation. Finally, we develop an iterative algorithm based on Monte Carlo simulation technique and conic optimization to solve general TCTP. The proposed approach has been tested on some randomly generated test problems. The results illustrate the good performance of our new approach.
Yahia Zare Mehrjerdi, Ali Nadizadeh,
Volume 27, Issue 1 (3-2016)
Abstract

Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customersthat have fuzzy demands. To model the CLRP_FD, a fuzzy chance constrained program is designed, based on fuzzy credibility theory. To solve the CLRP_FD, a greedy clustering method (GCM) including the stochastic simulation is proposed. Finally, to obtain the best value of the preference index of the model and analysis its influence on the final solutions of the problem, numerical experiments are carried out. Keywords: Capacitated location routing problem, Fuzzy demand, Credibility theory, Stochastic simulation, Ant colony system.


Parham Azimi, Naeim Azouji,
Volume 28, Issue 4 (11-2017)
Abstract

In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization via simulation (OvS) approach has been developed which is the main contribution of the current research. In this approach, the mathematical model of the main problem is relaxed and solved then the optimum solutions were used in the corresponding simulation model to produce several random feasible solutions for the main problem. Finally, the most promising solutions were selected as the initial population of a genetic Algorithm (GA). To test the efficiency of the problem, several test problems were solved by the proposed approach and according to the results, the proposed concept has a very good performance to solve such a complex combinatoral problem. Also, the concept could be easily applied for other similar combinatorics. 


Mahdieh Akhbari,
Volume 29, Issue 2 (6-2018)
Abstract

The aim of this study is to present a new method to predict project time and cost under uncertainty. Assuming that what happens in projects implementation which is expressed in the form of Earned Value Management (EVM) indicators is primarily related to the nature of randomness or unreliability, in this study, by using Monte Carlo simulation, and assuming a specific distribution for the time and cost of project activities, a significant number of predicting scenarios will be simulated. According to the data, an artificial neural network is used as efficient data mining methods to estimate the project time and cost at completion.
Arezoo Jahani, Parastoo Mohammadi, Hamid Mashreghi,
Volume 29, Issue 2 (6-2018)
Abstract

Innovation & Prosperity Fund (IPfund) in Iran as a governmental organization aims to develop new technology-based firms (NTBF) by its available resources through financing these firms. The innovative projects which refer to IPfund for financing are in a stage which can receive both fixed rate facilities and partnership in the projects, i.e. profit loss sharing (PLS). Since this fund must protect its initial and real value of its capital against inflation rate, therefore, this study aims to examine the suitable financing methods with considering risk. For this purpose we study on risk assessment models to see how to use risk adjusted net present value for knowledge based projects. On this basis, the NPV of a project has been analyzed by taking into account the risk variables (sales revenue and the cost of fixed investment) and using Monte Carlo simulation. The results indicate that in most cases for a project, the risk adjusted NPV in partnership scenario is more than the other scenario. In addition to, partnership in projects which demand for industrial production facilities is preferable for the IPfund than projects calling for working capital.

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