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RISS 인기검색어
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- 저자 : Mohammad Ehteram (검색결과 2 건)
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Taguchi optimization of micron sized lubricant oil droplet deposition on a hot plate
Mohammad Hassan Shojaeefard,Vahid Mousapour Khaneshan,Mohammad Ali Ehteram,Mostafa Akbari,Ehsan Allymehr 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.8
The deposition of micron sized lubricant oil droplets similar to oil droplets in blow-by gases of Internal combustion (IC) engines on ahot flat plate was studied using a round impinging jet configuration. Five parameters which simulate the different operational conditionsin IC engines were chosen: The impaction nozzle’s outlet diameter, additional air flow rate, plate angle, plate temperature, and nozzle tothe plate distance. An Experimental test-rig was constructed to acquire deposit weight with different parameter values. To find the conditionsof minimum deposition, the deposit’s weight was optimized using the Taguchi design of experiment method with respect to thedesign parameters. Using the experimental data, the predicted optimal value of the deposit weight was confirmed. Analysis of varianceshowed that plate angle is the most influential factor in deposition of fine oil droplets. Scanning electron microscopy (SEM) was used toinvestigate the mechanism of deposition.
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Optimization of Reservoir Operation using New Hybrid Algorithm
Zaher Mundher Yaseen,Hojat Karami,Mohammad Ehteram,Nuruol Syuhadaa Mohd,Sayed Farhad Mousavi,Lai Sai Hin,Ozgur Kisi,Saeed Farzin,김성원,Ahmed El-Shafie 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.11
Due to the scarcity of fresh water resources, exploiting dams’ reservoirs, based on their optimal operation, obviates construction of extra dams and high costs and satisfies downstream consumers’ water needs with high reliability. In this research, a new hybrid approach of Artificial Fish Swarm Algorithm (AFSA) and Particle Swarm Optimization Algorithm (PSOA) is used to optimize Karun-4 reservoir, increase energy production and minimize downstream water shortages. This Hybrid Algorithm (HA) brings about diversity of responses in PSOA, prevents entrapment of AFSA in local optimum traps and increases convergence speed and balances between the abilities to scan and make profit in the AFSA. This method was assessed based on reliability, vulnerability and resilience indices. In addition, based on a multi-criteria decision-making model, it was evaluated by comparing it with other evolutionary algorithms. To verify the HA, it was tested on few mathematical functions. Results indicated that the HA features performed higher reliability, lower vulnerability and resiliency, as compared with AFSA and PSOA. In addition, HA is ranked first according to the multi criteria decision making model. Further, among all the tested evolutionary methods, this new algorithm yielded the best answer for dam power plant’s objective function.
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