본 연구는 친환경 선박의 연료 특성 분석, 사고 사례분석, FRAM(Functional Resonance Analysis Method) 분석을 통하여 사고의 원인과 선박 운항시 발생 가능한 다양한 변동성을 분석하였다. LNG, 메탄올, 암모니아, 액화수소 등 다양한 친환경 선박연료는 각각의 물리적, 화학적 특성으로 인해 누출, 화재, 폭발 등의 위험을 내포하고 있으며, 특히 벙커링 과정이 관련된 사고가 빈번하게 발생하였 다. 사고 사례분석과 FRAM 분석을 통해 인적, 기술적, 환경적 변동성이 친환경 선박의 사고원인으로 도출됨을 확인하였다. 사고를 예 방하고 줄이기 위해서는 변동성을 최소화하고, 인적/기술적 오류를 없애고 환경적 변화에 최적화된 대응이 필요하다. 연구내용을 기반 으로 친환경 선박 운항에서 다양한 오류와 변동성을 최소화 하기 위한 연구가 지속적으로 필요할 것으로 보이며, 이에 따른 체계적인 사고 대응 시스템이 구축되어야 할 것이다.

The several experiments of Diesel vehicles using EFT were completed. The experiments were performed on chassis dynamometer and road driving test using test mode such as FTP-75 and LA-4. The experiments were employed to measure the effect eco-friendly EFT additives on exhaust emissions and fuel consumption efficiency. In this experiment, the following results are obtained by analyzing the data relativity between exhaust emissions and EFT additives. The value of exhaust emissions such as NOX, SOX, CO2 and PM were improved as Diesel mixed EFT additives at th ratio of 200:1. The improvement of resulting data value was best PM, NOX, SOX, CO₂and fuel consumption rate in the order named.

The two experiments of gasoline vehicle using eco-friendly treatment(Ecoburn) were completed. The experiments was done on traveling using the performance testing mode for chassis dynamometer and road driving test. The experiments were employed to measure exhaust emissions and fuel consumption. In this experiment, the correlation between CO₂and fuel consumption were found in gasoline vehicle. The following results are obtained by analyzing the data relativity between exhaust emissions and additives. 1) If the value of exhaust emissions such as CO, HC, NOX, CO₂were improved as gasoline mixed additives at th ratio of 300:1. The value of fuel consumption were worse compare to those of exhaust emission. The improvement of resulting data value was best CO, HC, NOX and fuel consumption in the order named. 2) The value of CO₂ were to be nearly proportional to the fuel consumption value.