International Journal of Optimization in Civil Engineering
http://ijoce.iust.ac.ir
Iran University of Science & Technology - Journal articles for year 2016, Volume 6, Number 1Yektaweb Collection - https://yektaweb.comen2016/1/11INVERSE FREQUENCY RESPONSE ANALYSIS FOR PIPELINES LEAK DETECTION USING THE PARTICLE SWARM OPTIMIZATION
http://www.iust.ac.ir/ijoce/browse.php?a_id=234&sid=1&slc_lang=en
Inverse Transient Analysis (ITA) is a powerful approach for leak detection of pipelines. When the pipe transient flow is analyzed in frequency domain the ITA is called Inverse Frequency Response Analysis (IFRA). To implement an IFRA for leak detection, a transient state is initiated in the pipe by fast closure of the downstream end valve. Then, the pressure time history at the valve location is measured. Using the Fast Fourier Transform (FFT) the measured signal is transferred into the frequency domain. Besides, using the transfer matrix method, a frequency response analysis model for the pipeline is developed as a function of the leak parameters including the number, location and size of leaks. This model predicts the frequency responses of the pipe in return for any random set of leak parameters. Then, a nonlinear inverse problem is defined to minimize the discrepancies between the observed and predicted responses at the valve location. To find the pipeline leaks the method of Particle Swarm Optimization (PSO) is coupled to the transient analysis model while, the leak parameters are the optimization decision variables. The model is successfully applied against an example pipeline and in both terms of efficiency and reliability the results are satisfactory.A. HaghighiOPTIMUM DESIGN OF SKELETAL STRUCTURES USING ANT LION OPTIMIZER
http://www.iust.ac.ir/ijoce/browse.php?a_id=235&sid=1&slc_lang=en
This paper utilizes recent optimization algorithm called Ant Lion Optimizer (ALO) for optimal design of skeletal structures. The ALO is based on the hunting mechanism of Antlions in nature. The random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps are main steps for this algorithm. The new algorithm is examined by designing three truss and frame design optimization problems and its performance is further compared with various classical and advanced algorithms.S. TalatahariDETERMINATION OF OPTIMAL HEDGING RULE USING FUZZY SET THEORY FOR MULTI-RESERVOIR OPERATION
http://www.iust.ac.ir/ijoce/browse.php?a_id=236&sid=1&slc_lang=en
To deal with severe drought when water supply is insufficient hedging rule, based on hedging rule curve, is proposed. In general, in discrete hedging rules, the rationing factors have changed from a zone to another zone at once. Accordingly, this paper is an attempt to improve the conventional hedging rule to control the changes of rationing factors. In this regard, the simulation model has employed a fuzzy approach, and this causes rationing factor changing during a long term simulation gradually. To optimize different parameters of the purposed hedging a Multi-objective Particle Swarm Optimization (MOPSO) algorithm has been considered. The minimum of two objectives Modified Shortage Index (MSI) involving water supply of minimum flow and agriculture demands can be taken as the optimization objectives. The results of the proposed hedging rule indicate long term and annual MSI values have considerably improved compared to the conventional hedging rule. This determines that the proposed method is promising and efficient to mitigate the water shortage problem.I. AhmadianfarCOMPARISON ABILITY OF GA AND DP METHODS FOR OPTIMIZATION OF RELEASED WATER FROM RESERVOIR DAM BASED ON PRODUCED DIFFERENT SCENARIOS BY MARKOV CHAIN METHOD
http://www.iust.ac.ir/ijoce/browse.php?a_id=237&sid=1&slc_lang=en
Planning for supply water demands (drinkable and irrigation water demands) is a necessary problem. For this purpose, three subjects must be considered (optimization of water supply systems such as volume of reservoir dams, optimization of released water from reservoir and prediction of next droughts). For optimization of volume of reservoir dams, yield model is applied. Reliability of yield model is more than perfect model and cost of solution of this model is less than other methods. For optimization of released water from reservoir dams, different methods can be applied. In this research, dynamic programming method (a discrete method for optimization) and genetic algorithm (a searcher method for optimization) are considered for optimization of released water from the Karaj reservoir dam. The Karaj dam locates in west of Tehran. This research shows that reliability and resiliency of GA method is more than DP method and vulnerability of GA method is less than DP method. For improving of results of GA method, mutation rate of GA method is considered from 0.005 to 0.3 for different generations. For prediction extreme droughts in future, the Markov chain method is used. Based on generated data by Markov chain method, optimum volume of reservoir dam is determined by yield model. Then optimum released water from reservoir dam is determined by DP and GA methods for different scenarios that produced by Markov chain method. The Markov chain and yield model show that volume of reservoir Karaj dam should increase 123 MCM for overcoming to next droughts.A. Adib A HYBRID SUPPORT VECTOR REGRESSION WITH ANT COLONY OPTIMIZATION ALGORITHM IN ESTIMATION OF SAFETY FACTOR FOR CIRCULAR FAILURE SLOPE
http://www.iust.ac.ir/ijoce/browse.php?a_id=238&sid=1&slc_lang=en
Slope stability is one of the most complex and essential issues for civil and geotechnical engineers, mainly due to life and high economical losses resulting from these failures. In this paper, a new approach is presented for estimating the Safety Factor (SF) for circular failure slope using hybrid support vector regression (SVR) and Ant Colony Optimization (ACO). The ACO is combined with the SVR for determining the optimal value of its user-defined parameters. The optimization implementation by the ACO significantly improves the generalization ability of the SVR. In this research, the input data for the SF estimation consists of the values of geometrical and geotechnical input parameters. As an output, the model estimates the SF that can be modeled as a function approximation problem. A data set that includes 46 data points is applied in current study, while 32 data points are used for constructing the model, and the remainder data points (14 data points) are used for assessment of the degree of accuracy and robustness. The results obtained show that the hybrid SVR with ACO model can be used successfully for estimation of the SF.H. FattahiOPTIMUM DESIGN OF GRILLAGE SYSTEMS USING CBO AND ECBO ALGORITHMS
http://www.iust.ac.ir/ijoce/browse.php?a_id=239&sid=1&slc_lang=en
Grillages are widely used in various structures. In this research, the Colliding Bodies Optimization (CBO) and Enhanced Colliding Bodies Optimization (ECBO) algorithms are used to obtain the optimum design of irregular grillage systems. The purpose of this research is to minimize the weight of the structure while satisfying the design constraints. The design variables are considered to be the cross-sectional properties of the beams and the design constraints are employed from LRFD-AISC. In addition, optimum design of grillages is performed for two cases: (i) without considering the warping effect, and (ii) with considering the warping effect. Also, several examples are presented to show the effect of different spacing and various boundary conditions. Finally, the results show that warping effect, beam spacing and boundary conditions have significant effects on the optimum design of grillages.A. KavehA FAST GA-BASED METHOD FOR SOLVING TRUSS OPTIMIZATION PROBLEMS
http://www.iust.ac.ir/ijoce/browse.php?a_id=240&sid=1&slc_lang=en
<p class="MsoNormal" style="text-indent: 0cm">Due to the complex structural issues and
increasing number of design variables, a rather fast optimization algorithm to
lead to a global swift convergence history without multiple attempts may be of
major concern. Genetic Algorithm (GA) includes random numerical technique that
is inspired by nature and is used to solve optimization problems. In this
study, a novel GA method based on self-adaptive operators is presented. Results
show that this proposed method is faster than many other defined GA-based
conventional algorithms. To investigate the efficiency of the proposed method,
several famous optimization truss problems with semi-discrete variables are
studied. The results reflect the good performance of the algorithm where
relatively a less number of analyses is required for the global optimum
solution.<o:p /></p>
M. R. Ghasemi SHAPE OPTIMIZATION OF CONCRETE GRAVITY DAMS CONSIDERING DAM–WATER–FOUNDATION INTERACTION AND NONLINEAR EFFECTS
http://www.iust.ac.ir/ijoce/browse.php?a_id=241&sid=1&slc_lang=en
This study focuses on the shape optimization of concrete gravity dams considering dam–water–foundation interaction and nonlinear effects subject to earthquake. The concrete gravity dam is considered as a two–dimensional structure involving the geometry and material nonlinearity effects. For the description of the nonlinear behavior of concrete material under earthquake loads, the Drucker–Prager model based on the associated flow rule is adopted in this study. The optimum design of concrete gravity dams is achieved by the hybrid of an improved gravitational search algorithm (IGSA) and the orthogonal crossover (OC), called IGSA–OC. In order to reduce the computational cost of optimization process, the support vector machine approach is employed to approximate the dam response instead of directly evaluating it by a time–consuming finite element analysis. To demonstrate the nonlinear behavior of concrete material in the optimum design of concrete gravity dams, the shape optimization of a real dam is presented and compared with that of dam considering linear effect.M. KhatibiniaCRITICAL INCIDENT ANGLE FOR THE MINIMUM COST DESIGN OF LOW, MID AND HIGH-RISE STEEL AND REINFORCED CONCRETE-COMPOSITE BUILDINGS
http://www.iust.ac.ir/ijoce/browse.php?a_id=242&sid=1&slc_lang=en
One of the main tasks of engineers is to design structural systems light and economic as possible, yet resistant enough to withstand all possible loads arising during their service life and to absorb the induced seismic energy in a controlled and predictable fashion. The traditional trial-and-error design approach is not capable to determine an economical design satisfying also the code requirements. Structural design optimization, on the other hand, provides a numerical procedure that can replace the traditional design approach with an automated one. The objective of this work is to propose a performance-based seismic design procedure, formulated as a structural design optimization problem, for designing steel and steel-concrete composite buildings subject to interstorey drift limitations. In particular a straightforward design procedure is proposed where the influence on both record and incident angle is considered. For this purpose six test examples are considered, in particular three steel and three steel-concrete composite buildings are optimally designed for minimum initial cost.N.D. Lagaros