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Sarhan Karray,Zied Driss,Hedi Kchaou,Mohamed Salah Abid 대한기계학회 2011 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.25 No.7
A coupling algorithm is used to compute the equilibrium of a flexible anchor impeller in a stirred vessel. This coupling algorithm is based on a partitioned approach, which consists of three relatively independent modules: the computational fluid dynamics (CFD), the computational structure dynamics (CSD) and the interface. In the CFD module, the Euler formulation was used to account for the moving boundary. In the CSD module, the updated Lagrangian formulation for solving the motion of non-linear structure was used and a static study was adopted. In the interface module, an exchange of the forces and displacements was allowed. The numerical results, such as the velocity field, the turbulent kinetic energy, its dissipation rate, the turbulent viscosity and the mechanical deformation, have been presented. Particularly, we are interested in the study of the static behavior of the anchor impeller and the evolution of the displacement field of the arms during various iterations of our coupling algorithm. Accordingly, if the anchor impeller undergoes a deformation due to the flexion of the arms of the anchor impeller, the numerical results changes slightly from iteration to another. At the end of certain iteration,the anchor impeller becomes deformed and the velocity field is preserved. These results confirm that the fluid has a significant effect on the deformation of the arms of the anchor impeller during mixing depending on the velocity of the anchor impeller and the fluid flow. The numerical results were validated by a comparison with literature data.
Personal Rapid Transit Network Design Using Genetic Algorithm and Ant Colony System Hybridization
Jin-Myung Won,Fakhreddine Karray 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
This study proposes a new hybrid meta-heuristic to address the Guideway Network (GN) design problem of Personal Rapid Transit (PRT). PRT is a novel transportation paradigm, which operates a number of driverless vehicles over an elevated GN. Since the GN interconnects many stations, designing an efficient GN is a challenging problem even for a moderate-sized PRT system. To solve the GN design problem effectively, we propose a hybrid meta-heuristic of a Genetic Algorithm (GA) and a local search Ant Colony System (ACS). The proposed hybrid meta-heuristic uses a special representation technique named cycle representation, which encodes a GN candidate as an aggregation of cycles (circulators). The GA searches for the best combination of the cycles via special genetic operators dedicated to the cycle representation. On the other hand, the local search ACS accelerates the search by fine-tuning the cycles using the pheromone matrix maintaining past search history. The empirical tests performed for realistic GN design problems verify the effectiveness and efficiency of the proposed hybrid meta-heuristic.
Experimental Study of Steel Fiber Concrete Slabs Part I: Behavior under Uniformly Distributed Loads
Ellouze, Ali,Ouezdou, Mongi Ben,Karray, Mohammed Ali Korea Concrete Institute 2010 International Journal of Concrete Structures and M Vol.4 No.2
This article aims to study the effects of adding steel fibers to concrete on the mechanical behavior of steel fiber concrete (SFC) slabs. After formulating the SFC, an experimental work was, first, conducted on $160\;{\times}\;320$ mm cylindrical specimens and $70\;{\times}\;70\;{\times}\;280$ mm prisms. Then, this study was carried out on 20 rectangular $1,100\;{\times}\;1,100\;{\times}\;60$ mm small slabs submitted to a distributed load. Two types of fibers with hooked ends were used: long fibers (LF) of a length of 50 mm and short fibers (SF) of a length of 35 mm. The studied parameters are compressive and tensile strengths and Young's modulus. Plain concrete (PC) small slabs were also prepared to be compared to the SFC specimens. The results showed that the compressive strength of SFC increased up to 25% while the splitting tests showed an improvement of the SFC reaching 45%. Tests on SFC small slabs also showed that a smaller deflection is obtained with respect to PC, which indicates an improvement in strength (up to 100%), in ductility and in resistance to cracking. The LF gives a better improvement in strength than the SF for a 70% $kg/m^3$ of steel proportioning.
Experimental Study of Steel Fiber Concrete Slabs Part I
Ali Ellouze,Mongi Ben Ouezdou,Mohammed Ali Karray 한국콘크리트학회 2010 International Journal of Concrete Structures and M Vol.4 No.2
This article aims to study the effects of adding steel fibers to concrete on the mechanical behavior of steel fiber concrete (SFC) slabs. After formulating the SFC, an experimental work was, first, conducted on 160 × 320 mm cylindrical specimens and 70 × 70 × 280 mm prisms. Then, this study was carried out on 20 rectangular 1,100 × 1,100 × 60 mm small slabs submitted to a distributed load. Two types of fibers with hooked ends were used: long fibers (LF) of a length of 50 mm and short fibers (SF) of a length of 35 mm. The studied parameters are compressive and tensile strengths and Young"s modulus. Plain concrete (PC) small slabs were also prepared to be compared to the SFC specimens. The results showed that the compressive strength of SFC increased up to 25% while the splitting tests showed an improvement of the SFC reaching 45%. Tests on SFC small slabs also showed that a smaller deflection is obtained with respect to PC, which indicates an improvement in strength (up to 100%), in ductility and in resistance to cracking. The LF gives a better improvement in strength than the SF for a 70% kg/m³ of steel proportioning.
Data Clustering Using Multi-Objective Hybrid Evolutionary Algorithm
Jin-Myung Won,Sami Ullah,Fakhreddine Karray 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
This paper proposes a multi-objective evolution strategy (ES) hybridized with a k-means algorithm to address a data clustering problem whose objective is minimizing both clustering error and cluster number. Contrary to the conventional data clustering problem with a predetermined number of clusters, the bi-objective problem considered in this study has a set of clustering solutions whose cluster numbers are different from one another. This enables to secure the best clustering result that fits specific needs without restricting the cluster number. To find the solution set, the hybrid ES evolves a population of solution candidates each of which represents a variable number of cluster centroids. While evolving the population, special ES operators dedicated to the bi-objective clustering problem are used. Whenever the hybrid ES creates a new set of cluster centroids, it is fine-tuned by the k-means algorithm. The experiment results show that the hybrid ES outperforms the conventional ES and KMA.