Scientia Iranica
Volume:16 Issue: 4, 2009

This paper presents an application of the Max-Min Ant System for optimal operation of reservoirs using three di erent formulations. Ant colony optimization algorithms are a meta-heuristic approach initially inspired by the observation that ants can nd the shortest path between food sources and their nest. The basic algorithm of Ant Colony Optimization is the Ant System. Many other algorithms, such as the Max-Min Ant System, have been introduced to improve the performance of the Ant System. The rst step for solving problems using ant algorithms is to de ne the graph of the problem under consideration. The problem graph is related to the decision variables of problems. In this paper, the problem of optimal operation of reservoirs is formulated using two di erent sets of decision variable, i.e. storage volumes and releases. It is also shown that the problem can be formulated in two di erent graph forms when the reservoir storages are taken as the decision variables, while only one graph representation is available when the releases are taken as the decision variables. The advantages and disadvantages of these formulation are discussed when an ant algorithm, such as the Max-Min Ant System, is attempted to solve the underlying problem. The proposed formulations are then used to solve the problem of water supply and the hydropower operation of the \Dez" reservoir. The results are then compared with each other and those of other methods such as the Ant Colony System, Genetic Algorithms, Honey Bee Mating Optimization and the results obtained by Lingo software. The results indicate the ability of the proposed formulation and, in particular, the third formulation to optimally solve reservoir operation problems.

The Ant Colony Optimization Algorithm (ACOA) is a new class of stochastic search algorithm proposed for the solution of combinatorial optimisation problems. Di erent versions of ACOA are developed and used with varying degrees of success. The Max-Min Ant System (MMAS) is recently proposed as a remedy for the premature convergence problem often encountered with ACOAs using elitist strategies. The basic concept behind MMAS is to provide a logical balance between exploitation and exploration. The method, however, introduces some additional parameters to the original algorithm, which should be tuned for the best performance of the method adding to the computational requirement of the algorithm. An alternative method to MMAS is proposed in this paper and applied to pipe network optimization problem. The method uses a simple but e ective mechanism, namely Pheromone Trail Replacement (PTR), to make sure that the global best solution path has always the maximum trail intensity. This mechanism introduces enough exploitation into the method and more importantly enables one to exactly predict the number of global best solutions at each iteration of the algorithm without requiring calculation of the cost of the solutions created. The sub-colony of repeated global best solutions of the iterations is then mutated, such that a prede ned number of solutions survive the mutation process. Two di erent mutation mechanisms, namely deterministic and stochastic mutation processes, are introduced and used. The rst one uses a one bit mutation with a probability of one on some members of the sub-colony, while the second one uses a uniform mutation on the whole sub-colony. The probability of mutation in the second mutation process is adjusted at each iteration, so that the required number of globalbest solutions survives the mutation. The method is shown to produce results comparable to the MMAS algorithm, while requiring less free parameter tuning. The application of the method to a benchmark example in the pipe network optimization discipline is presented and the results are compared..

The nature of High Strength Concrete, HSC, is brittle failure and although the behavior of reinforced concrete beams heavily steel reinforced are increased in strength, the ductility, which is important in seismic regions, is in question. In other words, such beams, while consisting of HSC, are more brittle. In this paper, the exural ductility of such members, with a variation in compressive reinforcement, is investigated. Six heavily reinforced High Strength Concrete, HSC, beams, with di erent percentages of  and 0, were cast and incrementally loaded under bending. During the test, the strain on the concrete middle face and on the tension and compression bars as well as the de ection at di erent points of the span length were measured up to failure. Based on the results obtained, the curvature, displacement and rotation ductility of the HSC members are more deeply reviewed. A comparison between theoretical and experimental results are also reported here. Generally, it was concluded that for heavily steel reinforced HSC beams, the displacement ductility for singly reinforced beams is too close to the doubly reinforced beams.

New penalty functions, which have better convergence properties, as compared to the commonly used exterior and interior penalty functions, have been proposed in this paper. The convergence behavior and accuracy of ordinary penalty functions depend on the selection of appropriate penalty parameters. The optimization of ordinary penalty functions is accomplished after several rounds of optimization where, at each round a di erent but xed value of penalty parameter is used. While some useful hints and rules for the selection of suitable penalty parameter values have been provided by di erent authors, the objective of this paper has been to improve this procedure by including the penalty parameter in the design vector, so that it can be modi ed during the optimization, automatically, in order to improve the convergence characteristics. This can also help accomplish optimization in only one round, which is of considerable importance when it is desired to solve a constrained problem by using genetic algorithms. The proof of convergence to the optimum solution of the proposed functions is also included in the paper. Ten-bar and three-bar truss examples are used for illustration through which the convergence of ordinary and new functions are evaluated and compared. The results show that the new penalty functions can outperform the ordinary functions, especially in combination with genetic algorithms..

An experimental investigation of the strengthening of the torsional resistance of High- Strength Concrete (HSC) beams using Carbon-Fiber-Reinforced-Polymers (CFRP) is conducted. A total of seven beams are tested. Three beams are designated as reference specimens and four beams are strengthened using CFRP wrapping of di erent con guration and then tested. The variables considered in the experimental study include di erent wrap con gurations such as: U-wrapping, full and strip wrapping, the e ect of the number of CFRP plies and the in uence of anchors in U-wrapped test beams. The reference and the strengthened beams are subjected to pure torsional moment. The load, the twist angle of the beams and the strains at longitudinal, transverse re-bars and CFRP are recorded to failure. In the current study, the ductility ratios and their increased percentage are investigated using two rather di erent methods. In further study, increasing the cracking, yield and ultimate torsional capacity of the strengthened beams is evaluated. Finally, experimental results are compared to several analytical results. The ultimate torsional strengths that are obtained by one of the analytical methods are in good agreement with the experimental results.

The liquefaction phenomenon is usually accompanied by a large amount of settlement. Based on the observations made in past earthquakes, ground improvement by densi cation is one of the most useful approaches to reduce the liquefaction-induced settlement. Currently, there is no analytical solution for evaluation of the amount of settlement and tilting of footings that are constructed on densi ed ground surrounded by lique able soil. A number of factors, such as underlying soil properties, dimensions of the footing and earthquake loading characteristics, cause the problem to become complicated. In this paper, the dynamic response of shallow foundations on both lique able and non-lique able (densi ed) soils is studied using a 3D fully-coupled dynamic analysis. A well-calibrated critical state two-surface plasticity model has been used in the numerical analysis, which is capable of accounting for the volumetric/shear response of the soil skeleton at a wide range of densities (void ratios) and con ning pressures. The OpenSEES platform is used to conduct the numerical simulations. The proposed numerical model has been applied in simulating a series of centrifuge experiments. Comparison of the numerical results and the centrifuge experiment measurements reveals that the numerical model is capable of capturing the important aspects of the dynamic response of footings on lique able and densi ed subsoils, and can be used as a valuable tool for investigating the amount of liquefaction-induced settlement, tilting of footings and their reduction due to densi cation.

The numerical solution of incompressible Navier-Stokes equations for ows involving complex geometries is greatly a ected by mesh resolution. In these ows, some regions may need ner mesh than others. Adaptive Mesh Re nement (AMR) techniques enable the mesh to be locally re ned, based on error distribution in the previous analysis. In this paper, three adaptive re nement methods, namely, Superconvergent Patch Recovery (SPR) based re nement, gradient based re nement and curvature (2nd derivative) based re nement are used in conjunction with the characteristic based split nite element method to solve a benchmark problem of a lid-driven cavity. The results of the proposed adaptive re nement methods are presented and their eciencies are compared. The results show the e ectiveness of the adaptive re nement method for the ecient and accurate simulation of ow problems.