• Journal of Hydrogen and New Energy
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• v.31 no.5
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• pp.405-410
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• 2020

In this literature, we are introduce a basic design of multi energy hub based on natural gas governor station. Multi energy hub consists of turbo expender generator, phosphoric acid fuel cell, pressure swing adsorption, H₂ charging station, utilities and etc. We design a hybrid energy hub system that provides energy using these complex energies, and calculates the amount of electricity that can be produced and the amount of hydrogen charged through the process analysis. TEG and phosphoric acid fuel cell produce 2,290 to 2,380 kW and can supply electricity to 500 houses. In addition, By-product H₂ gas is refined to H₂ vehicle fuel. This will help maximize the balance of energy demand and supply and improve national energy efficiency by integrating unused decompression energy power generation technology and various power generation/heat source technologies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.1011-1019
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• 2015

Insulated-gate bipolar transistors (IGBTs) are the predominantly used power semiconductors for high-current applications, and are used in trains, airplanes, electrical, and hybrid vehicles. IGBT power modules generate a considerable amount of heat from the dissipation of electric power. This heat generation causes several reliability problems and deteriorates the performances of the IGBT devices. Therefore, thermal management is critical for IGBT modules. In particular, realizing a proper thermal design for which the device temperature does not exceed a specified limit has been a key factor in developing IGBT modules. In this study, we investigate the thermal behavior of the 1200 A, 3.3 kV IGBT module package using finite-element numerical simulation. In order to minimize the temperature of IGBT devices, we analyze the effects of various packaging materials and different thickness values on the thermal characteristics of IGBT modules, and we also perform a design-of-experiment (DOE) optimization

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.10
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• pp.819-825
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• 2006

In a SOFC/GT (solid oxide fuel cell/gas turbine) hybrid power generation system, the recuperator is an indispensible component to enhance system performance. Since the expansion ratio to the recuperator core is very large, generally, the effective header design to distribute the flow uniformly before entering the core is crucial to guarantee the required performance. In the present study, we focus on the design of a diffuser type recuperator header with a 90 degree turn inlet port. To reduce the flow separation and recirculation flows, multiple horizontal vanes are used. The number of horizontal vanes is varied from 0 to 24. The air flow velocity is measured at 40 points just behind the core outlet by using a hot wire anemometer. Then, the flow non-uniformity is evaluated from the measured flow velocity. The experimental results showed that inlet air velocity did not effect on relative flow non-uniformity. According to increasing the number of horizontal vanes, flow non-uniformity reduced about $40{\sim}50%$ than without using horizontal vanes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.589-597
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• 2015

Wave energy harvesting system using OWC(Oscillating Water Column) and MB (Movable Body) attached at the caisson breakwater was studied. This system was suggested to maximize wave energy extraction using resonant phenomena of oscillating water column and buoy in wave channel (Park et al., 2014). Not only incident waves but also reflected waves from the breakwater can be used as sources of exciting force for harvesting wave energy efficiently. Using Galerkin finite model based on the linear wave theory (Park, 1991), the performance of the system was evaluated for various damping ratios of power take off system. Numerical results show that the proposed system is excellent in efficiency compared with that of conventional system and the performance of the system is governed by the resonance of oscillating water column in the wave channel. In addition, the additional efforts to minimize viscous damping was found to be necessary because viscous damping occurring in the channel and around the moving buoy is significant in generation efficiency.

• Advances in Energy Research
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• v.5 no.2
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• pp.107-128
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• 2017

Energy is a major component of almost all economic, production, and service activities, and rapid population growth, urbanization and industrialization have led to ever growing demand for energy. Limited energy resources and increasingly evident environmental effects of fossil fuel consumption has led to a growing awareness about the importance of further use of renewable energy sources in the countries energy portfolio. Renewable hydrogen production is a convenient method for storage of unstable renewable energy sources such as wind and solar energy for use in other place or time. In this study, suitability of 25 cities located in Iran's western region for renewable hydrogen production are evaluated by multi-criteria decision making techniques including TOPSIS, VIKOR, ELECTRE, SAW, Fuzzy TOPSIS, and also hybrid ranking techniques. The choice of suitable location for the centralized renewable hydrogen production is associated with various technical, economic, social, geographic, and political criteria. This paper describes the criteria affecting the hydrogen production potential in the study region. Determined criteria are weighted with Shannon entropy method, and Angstrom model and wind power model are used to estimate respectively the solar and wind energy production potential in each city and each month. Assuming the use of proton exchange membrane electrolyzer for hydrogen production, the renewable hydrogen production potential of each city is then estimated based on the obtained wind and solar energy generation potentials. The rankings obtained with MCDMs show that Kermanshah is the best option for renewable hydrogen production, and evaluation of renewable hydrogen production capacities show that Gilangharb has the highest capacity among the studied cities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.817-824
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• 2000

This paper presents circuit DQ modeling and analysis of operating characteristics of hybrid cascade multilevel PWM rectifier, especially five-level, without isolation transformers. The circuit DQ transformation changes the original three-phase time varying circuit to stationary equivalent one by employing the synchronously rotating transformation matrix. As a result of circuit DQ modeling, the operating characteristics and some useful design relationships for the system are obtained with ease. That is, the analytic equations for DC voltages and active/reactive power supplied by source with respect to control variables are Presented. Moreover, the DC voltages for the multilevel output generation may be directly built up from AC utility source and the important control equation ensuring 5-level output voltage is obtained. Finally, to confirm the validity of the analysis, MATLAB simulations are carried out and the simulation results show good agreements between analytic predictions and the simulated waveforms.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.5
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• pp.95-101
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• 2012

An electric water pump for engine cooling system has an advantage which particularly in the cold start, the use of the electric water pump saves fuel and leads to a corresponding reduction in emissions. The canned type electric water pump without mechanical sealing elements was selected to meet the requirements for operational reliability and life. However, the electric water pump for internal combustion engine generates much more heat loss than for hybrid electric vehicle since it is operated by the electric power of high current and low voltage. In this study, the fluid flow and thermal characteristics of the canned type electric water pump as an inverter integrated water pump has been investigated under the effects of heat generation. The analysis conditions such as outdoor air temperature of $125^{\circ}C$, water pump speed of 6000 rpm, coolant temperature of $106^{\circ}C$ and coolant flow rate of 120 L/min was used as a standard condition. Therefore, flow fields and temperature distribution inside the water pump were obtained. Also, we checked the feasibility of the canned type for the electric water pump in comparison with the mechanical seal type.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2516-2533
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• 2023

Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.