• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.3
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• pp.90-101
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• 2009

An objective of this study is to suggest a procedure to evaluate vehicle emissions regardless of the driving pattern. Field experiments using portable emission measurement system were conducted under the real world driving cycle. Standardized average for NOx, $CO_2$ emission and fuel consumption rates were calculated while the vehicle specific power distribution within each vehicle speed bin was taken into consideration. Composite emission factor and fuel economy, which were obtained based on the standardized average results and traffic statistics, showed good similarity to those acquired through the conventional chassis dynamometer tests qualitatively as well as quantitatively. Considering that a conventional method obviously has a limitation to reflect various characteristics of the real world, the new approach suggested in this study can be used as an alternative procedure to collect more specific data to establish the mobile emission factors.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.229-234
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• 2008

The new millennium has started with several innovations driven by fast evolution of the technologies in energy sector. A strong impulse towards the diffusion of new economical efficient technologies regulatory incentives related to energy production from renewable source and a small scale building trigeneration and to promotion of more sustainable environmental-friendly generation solutions, the evolution of electricity markets, more and more binding local emission constraints, and the need for improving the security of supply to reduce the energy system vulnerability. The 24 percentage energy quantify of total energy consumption consumes in commercial buildings and residential houses and the 30% portion of total $CO_2$ emissions covers also in the commercial buildings and residential houses sector. To cope with efficiently this energy sinuation in building sector, Building microgrid or building tooling, heating & power(BCHP) system has been interested in recent day due to meeting thermal and electric energy requirements efficiently and with appropriate energy quality. A multi agent system is a collective of intelligent agents that communicate with each other and work cooperatively to achieve common goals. Also, it is to medicate and coordinate communication between Control Areas and Security Coordinators for teal-time control of the BCHP system and the power pid. In this new circumstance, it is very important to integrate the power and energy delivery system and the information system(communication, networks, and intelligent equipment) that controls it. Therefore, development of smart control modules with open communication protocol and seamlessly interchange the data and information between control network and data network including extranet and intranet give a great meanings. We designed and developed the TCP/IP-CAN IED agent modules and ModBus./LonTalk/(TCP/IP) IED agent ones to configure the multi-agent system based smart energy network of commercial buildings and also intelligent algorithms for inverter fault diagnostics which ran be operated in control level or agent level network.

• Advances in environmental research
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• v.9 no.2
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• pp.97-107
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• 2020

The indiscriminate growth in global population poses a threat to the world in handling and disposal of Municipal solid waste. Rapid urban growth increases the production, consumption and generation of Municipal solid waste which leads to a drastic change in the environment. The methane produced from the Municipal Solid waste accounts for up to 11% global anthropogenic emissions, which is a major cause for global warming. This study reports the methane emission estimation using IPCC default, TNO, LandGEM, EPER and close flux chamber from open dump yards at Perungudi and Kodungaiyur in Chennai, India. The result reveals that the methane emission using close flux chamber was in the range of 8.8 Gg/yr-11.3 Gg/yr and 6.1Gg/yr to 9.1 Gg/yr at Kodungaiyur and Perungudi dump yard respectively. The per capita waste generation was estimated based on waste generation and population. The waste generation potential was projected using linear regression model for the period 2017-2050. The trend of CH₄ emission in the actual field measurement were increased every year, similarly the emission trend also increased in IPCC default method (mass balance approach), EPER Germany (zero order decay model) where as TNO and Land GEM (first order decay model) were decreased. The present study reveals that Kodungaiyur dump yard is more vulnerable to methane emission compared to Perungudi dump yard and has more potential in waste to energy conversion mechanisms than compare to Perungudi dump yard.

• Tribology and Lubricants
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• v.35 no.5
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• pp.267-273
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• 2019

Wheel bearings are important automotive parts that bear the vehicle weight and translate rotation motion; in addition, their seals are components that prevent grease leakage and foreign material from entering from the outside of the bearings. Recently, as the need for electric vehicles and eco-friendly vehicles has been emerging, the reduction in fuel consumption and $CO_2$ emissions are becoming the most important issues for automobile manufacturers. In the case of wheel bearings, seals are a key part of drag torque. In this study, we investigate the prediction of the drag torque taking into consideration the hyperelastic and viscoelastic material properties of automotive wheel bearing seals. Numerical analysis based on the finite element method is conducted for the deformation analyses of the seals. To improve the reliability of the rubber seal analysis, three types of rubber material properties are considered, and analysis is conducted using the hyperelastic material properties. Viscoelastic material property tests are also conducted. Deformation analysis considering the hyperelastic and viscoelastic material properties is performed, and the effects of the viscoelastic material properties are compared with the results obtained by the consideration of the hyperelastic material properties. As a result of these analyses, the drag torque is 0.29 Nm when the hyperelastic characteristics are taken into account, and the drag torque is 0.27 Nm when both the hyperelastic and viscoelastic characteristics are taken into account. Therefore, it is determined that the analysis considering both hyperelastic and viscoelastic characteristics must be performed because of its reliability in predicting the drag torque of the rubber seals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.289-296
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• 2021

The Korean construction industry has been implementing G-SEED, a certification system that evaluates the environmental properties of buildings for the purpose of reducing environmental burdens such as energy and resource consumption and pollutant emissions. Also, creating a pleasant environment in general is one more purpose of G-SEED certification system. However, G-SEED certification in practice is difficult and time consuming due to the complexity of the certification acquisition process coupled with little economic consideration for the materials of each certification item. Therefore, in this study, we present a model for the optimal selection of materials and economic assessment using a genetic algorithm. The development of the model involves building a material database based on life-cycle costing (LCC) targeted at "Application of Indoor Air Pollutant Low Emission Material" from G-SEED. Next, the model was validated using a real non-residential building case study. The result shows an average cost reduction rate of 74.5 % compared with the existing cost. This model is expected to be used as an economically efficient tool in G-SEED.

• Korean Journal of Culture and Social Issue
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• v.17 no.4
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• pp.381-393
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• 2011

Eco driving is a strategy to reduce energy consumption and greenhouse gas emissions from motor vehicle. However, it has not received much attention until recently. Psychological studies on this issue have been limited and the majority of existing studies have primarily been based on engineering and educational approaches. This study examined the effects of a self-management technique on two driving behaviors: speeding and putting the gears in neutral while waiting at the signal. The self-management technique consisted of three behavior interventions: goal-setting, self-monitoring, and reward. Three drivers participated in this study. An AB multiple baseline design across participants was adopted. Results showed that the self-management technique was effective in increasing both driving behaviors. Implications of the present findings and suggestions for future research were discussed.

• Journal of ILASS-Korea
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• v.28 no.1
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.267-274
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• 2022

This paper is a result of research conducted on the 800,000 m³/d capacity of A Water Treatment Plant (WTP) and 400,000 m³/d capacity of B WTP plant in operation in the Nakdong River region. We evaluated the effect of algae broom on the WTP operation based on the running data of both WTP and the data on the pre-oxidation process field test for algae control using sodium permanganate (SPM) at the B WTP. The study results showed that during the algal bloom period, the coagulant dose increased by 102% in A WTP and 58% in B WTP, respectively, and the chlorine dose also increased by 38% and 29%, respectively, which may affect Total trihalomethane (THM) production. Data such as algal populations and Chl-a, residual chlorine and THM, algal populations, and ozone dose appeared also highly correlated, confirming that algal broom affects WTP operations, including water quality and chemical dosage. As a result of the field test of B WTP, THMs appeared lower than that of the control, suggesting the possibility of the SPM pre-oxidation process as an alternative to algae-related water quality management. Furthermore, in terms of GHG emissions due to energy consumption, it was observed that the pre-oxidation process using SPM was approximately 10.8%, which is a very low ratio compared to the pre-ozonation process. Therefore, these results suggest that the SPM pre-oxidation process can be recommended as an alternative to low-carbon water purification technology.

• Journal of the Korean Institute of Rural Architecture
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• v.26 no.2
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• pp.1-8
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• 2024

Carbon neutrality refers to a state in which there is no global increase in CO₂ emissions due to human activities. In Korea, for carbon neutrality, green remodeling of existing buildings and customized support tasks for zero energy in new buildings are presented. Germany is showing fundamental changes in energy supply, such as applying renewable energy and higher energy efficiency from nuclear and fossil fuels, which were the existing energy sources. In this study, how Germany establishes policies for carbon neutrality at each state level and the cases applied to increase the energy efficiency of the actually applied residential complexes are analyzed based on this. As a result of the case complex analysis, it was found that the construction direction was being promoted as a zero-energy complex or a carbon-neutral complex by gradually reducing the energy demand in buildings and supplying additional energy with new and renewable energy in the low-energy building distribution in the 1990s. In Germany's ecological complex, energy standards have been strengthened from low-energy architecture to plus-energy architecture over time, and annual heating energy consumption standards and heat transmittance rates for each structure have been achieved at a higher level. The results of this analysis will serve as basic data and derivation of applicable items when planning residential complex development and remodeling of existing buildings for the domestic carbon-neutral goal in the future.

• Composites Research
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• v.37 no.2
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• pp.115-125
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• 2024

As global issues and interest in the environment increase, the transition to eco-friendly materials is accelerating in the automobile industry. In the automotive industry, eco-friendly composite materials are mainly used in various interior and exterior components, reducing the reliance on traditional petroleum-based materials. In particular, natural fiber composites help reduce fuel consumption and greenhouse gas emissions by making vehicles lighter. Additionally, they boast superior thermal properties and durability compared to non-recyclable composite materials, making them suitable for automotive interior parts. Furthermore, reduced production costs and sustainability are key advantages of natural fiber composites. The eco-friendly composites market is expected to grow to $86.43 billion at a CAGR of 15.3% from 2022 to 2030, and the natural fiber composites market is predicted to grow at a CAGR of 5.3% from 2023 to 2028 to $424 million. In this review paper, we explore research trends in nextgeneration natural fiber composite materials for automobiles and their application in the actual automobile industry.