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RISS 인기검색어
- 검색키워드
- 저자 : Mahdi Eskandari (검색결과 3 건)
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Antenna Selection and Power Allocation for Energy Efficient MIMO Systems
Mahdi Eskandari,Ali Mohamad Doost-Hoseini,정재훈,이인규 한국통신학회 2018 Journal of communications and networks Vol.20 No.6
In this paper, we investigate a new solution for theenergy efficiency (EE) maximization and power allocation problemin point-to-point multiple-input multiple-output (MIMO) spatialmultiplexing schemes. Different from conventional energyefficientoptimization approaches that require iterative numericalalgorithms, we derive an optimal solution in a closed form, whichprovides an insight upon the relation between the optimum EE andsystem parameters such as circuit power and channel conditions. In addition, using the proposed closed form function, we present anupper bound on the optimum EE in terms of the full active transmitantennas parameters. Based on the derived upper bound, we alsopropose a new antenna selection algorithm which achieves almostthe same performance as the optimum solution with much reducedcomplexity.
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Full-scale tests of two-story RC frames retrofitted with steel plate multi-slit dampers
Mohammad Mahdi Javidan,Mohammad Seddiq Eskandari Nasab,Jinkoo Kim 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.39 No.5
There is a growing need of seismic retrofit of existing non-seismically designed structures in Korea after the 2016 Gyeongju and 2017 Pohang earthquakes, especially school buildings which experienced extensive damage during those two earthquakes. To this end, a steel multi-slit damper (MSD) was developed in this research which can be installed inside of partition walls of school buildings. Full-scale two-story RC frames were tested with and without the proposed dampers. The frames had structural details similar to school buildings constructed in the 1980s in Korea. The details of the experiments were described in detail, and the test results were validated using the analysis model. The developed seismic retrofit strategy was applied to a case study school building structure, and its seismic performance was evaluated before and after retrofit using the MSD. The results show that the developed retrofit strategy can improve the seismic performance of the structure to satisfy a given target performance level.
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Erfan Eskandari,Hasan Alimoradi,Mahdi Pourbagian,Mehrzad Shams 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.12
Subcooled flow boiling presents an enormous ability of heat transfer rate, which is extremely important inthe heat-dissipating systems of many industrial applications, such as power plants and internal combustion engines. Using an Euler-Euler-based three-dimensional numerical simulation of subcooled flow boiling in a vertical tube, weinvestigated different heat transfer quantities (average and local heat transfer coefficient, average and local vapor volumefraction, average and local wall temperature) and bubble dynamics quantities (bubble departure diameter, bubbledetachment frequency, bubble detachment waiting time, and nucleation site density) under various boundary conditions(pressure, subcooled temperature, mass flux, heat flux). Numerical results show that an increase in heat flux leadsto the increase in all of the physical quantities of interest but the bubble detachment frequency. An entirely oppositebehavior is observed when we change the mass flux and inlet subcooled temperature. Furthermore, a rise in pressurereduces all of the target quantities but the wall temperature and bubble detachment frequency. Since numerical simulationof such multiphase flow requires significant computational resources, we also present a deep learning approach,based on artificial neural networks (ANN), to predicting the physical quantities of interest. Prediction results demonstratethat the ANN model is capable of accurately predicting the target quantities with mean absolute errors less than2.5% and R-squared more than 0.93.
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