• Journal of the Korean Institute of Gas
• /
• v.19 no.6
• /
• pp.8-14
• /
• 2015

Synthetic natural gas(SNG), acquired from coal, is regarded as an alternative to natural gas since a rise in natural gas due to high oil price can be coped with it. In the present study, 11-liter heavy duty compressed natural gas(CNG) engine was employed in order to examine the combustion and emission characteristics of SNG. The simulated SNG, made up 90.95% of methane, 6.05% propane and 3% hydrogen was used in the experiment. Power output, thermal efficiency, combustion stability and emission characteristics were compared to those with CNG at the same engine operating conditions. Knocking phenomenon was also analyzed at 1260 rpm, full load condition. Combustion with SNG was more stable than CNG. Nitrogen oxides emissions increased while Carbon dioxides emissions decreased. Anti-knocking characteristics were improved with SNG.

• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.4
• /
• pp.455-462
• /
• 2006

Natural gas is a promising alternative fuel to meet strict engine emission regulations in many countries. Natural gas engines can operate at lean burn and stoichiometric burn conditions with different combustion and emission characteristics. In this paper, the fuel economy, emissions, misfire, knock and cycle-to-cycle variations in indicated mean effective pressure of lean burn natural gas engines are highlighted. Stoichiometric burn natural gas engines are briefly reviewed. To keep the output power and torque of natural gas engines comparable to that of gasoline engines, high boosting pressure should be used. High activity catalyst for methane oxidation and lean deNOx system or three way catalyst with precisely control strategies should be developed to meet stringent emission standards.

• Journal of Integrative Natural Science
• /
• v.13 no.4
• /
• pp.147-151
• /
• 2020

In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.864-869
• /
• 2004

A novel concept of feedback loop design for modal test and model updating is proposed. This method uses the closed -loop natural frequency information for parameter modification to overcome the problems associated with the conventional method employing the modal sensitivity matrix. To obtain new modal information from closed-loop system, controllers should be effective in changing modal data while guaranteeing the stability of closed-loop system. It is very hard to guarantee the stability of the closed-loop system with non-collocated sensor and actuator set. Ill this research, we proposed a controller called mode-decoupling controller that can change a target mode as much as the designer wants guaranteeing the stability of closed-loop system. This controller can be computed just using measured open-loop modeshape matrix. A simulation based on time domain input/output data is performed to check the feasibility of proposed control method.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.14 no.10
• /
• pp.955-961
• /
• 2004

A novel concept of feedback loop design for modal test and model updating is proposed. This method uses the closed-loop natural frequency information for parameter modification to overcome the problems associated with the conventional method employing the modal sensitivity matrix. To obtain new modal information from closed-loop system, controllers should be effective in changing modal data while guaranteeing the stability of closed-loop system. But it is very hard to guarantee the stability of the closed-loop system with non-collocated sensor and actuator set. In this research, we proposed a controller called mode-decoupling controller that can change a target mode as much as the designer wants guaranteeing the stability of closed-loop system. This controller can be computed Just using measured open-loop modeshape matrix. A simulation based on time domain input/output data is performed to check the feasibility of proposed control method.

• Progress in Superconductivity and Cryogenics
• /
• v.1 no.1
• /
• pp.48-55
• /
• 1999

thermodynamic cycle analysis has been performed for the power generation systems to utilize the cold energy of liquefied natural gas (LNG). The power cycle used the air or water at room temperature as a heat source and the LNG at cryogenic temperature as a heat sink. Among manypossible configurations of the cycle. the open Rankine cycle. and the closed Brayton cycle, and the closed Rankine cycle are selected for the basic analysis because of their practical importance. The power output per unit mass of LNG has been analytically calculated for various design parameters such as the pressure ratio. the mass flow rate. the adiabatic efficiency. the heat exchanger effectiveness. or the working fluid. The optimal conditions for the parameters are presented to maximize the power output and the design considerations are discussed. It is concluded that the open Rankine cycle is the most recormmendable both in thermodynamic efficency and in practice.

• Journal of Powder Materials
• /
• v.30 no.6
• /
• pp.528-535
• /
• 2023

Since their initial development in 2012, triboelectric nanogenerators (TENGs) have gained popularity worldwide as a desired option for harnessing energy. The urgent demand for TENGs is attributed to their novel structural design, low cost, and use of large-scale materials. The output performance of a TENG depends on the surface charge density of the friction layers. Several recycled and biowaste materials have been explored as friction layers to enhance the output performance of TENGs. Natural and oceanic biomaterials have also been investigated as alternatives for improving the performance of TENG devices. Moreover, structural innovations have been made in TENGs to develop highly efficient devices. This review summarizes the recent developments in recycling and biowaste materials for TENG devices. The potential of natural and oceanic biowaste materials is also discussed. Finally, future outlooks for the structural developments in TENG devices are presented.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.2 no.2
• /
• pp.60-66
• /
• 2003

For the estimation of chatter lobe boundary it is very important to calculate the natural mode of cutting process. There are many time series algorithms for getting the natural mode of structural endmilling dynamics considering the cutting process. In this study, we have compared several time series methods such as AR algorithm, ARX, ARMAX, ARMA, Box Jenkins, Output Error, Recursive ARX, Recursive ARMAX considering the sampling frequency. As a results, the ARX, ARMAX and IV 4 are more desirable algorithms for the calculation of modal parameters such as natural frequency and damping ratio In endmilling operation. Also these algorithms may be adopted for the natural mode estimation of endmilling operation for chatter lobe prediction.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.537-555
• /
• 2021

Many researchers have carried out studies related to programming languages since the beginning of computer science. Besides programming with traditional programming languages (i.e., procedural, object-oriented, functional programming language, etc.), a new paradigm of programming is being carried out. It is programming with natural language. By programming with natural language, we expect that it will free our expressiveness in contrast to programming languages which have strong constraints in syntax. This paper surveys the approaches that generate source code automatically from a natural language description. We also categorize the approaches by their forms of input and output. Finally, we analyze the current trend of approaches and suggest the future direction of this research domain to improve automatic code generation with natural language. From the analysis, we state that researchers should work on customizing language models in the domain of source code and explore better representations of source code such as embedding techniques and pre-trained models which have been proved to work well on natural language processing tasks.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
• /
• 1999.02a
• /
• pp.165-168
• /
• 1999

Thermodynamic cycle analysis has been performed for the power generation systems to utilize the cold energy of liquefied natural gas (LNG). Among many possible configurations of the cycle, the open Rankine cycle, the closed Rankine cycle, and the closed Brayton cycle are selecte for the analysis because of their practical importance. The power output per unit mass of LNG has been analytically calculated for various design parameters. The optimal conditions for the parameters to maximize the power output are presented and some of the design considerations are discussed.