데이터베이스 기반 선박 성능예측방법을 활용한 해운 항로 운항 선박의 연료 소모량 추정Estimation of Ship Fuel Oil Consumption on Navigational Routes Using Database-Based Performance Prediction
- Other Titles
- Estimation of Ship Fuel Oil Consumption on Navigational Routes Using Database-Based Performance Prediction
- Authors
- 김유철; 연성모; 이영연; 황승현; 오석환; 김광수
- Issue Date
- 12월-2025
- Publisher
- 대한조선학회
- Keywords
- Fuel oil consumption(연료 소모량); Route-based estimation(항로기반 예측); Ship; performance prediction(선박 성능 추정); Regression model(회귀 모델)
- Citation
- 대한조선학회 논문집, v.62, no.6, pp 435 - 444
- Pages
- 10
- Journal Title
- 대한조선학회 논문집
- Volume
- 62
- Number
- 6
- Start Page
- 435
- End Page
- 444
- URI
- https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/11013
- DOI
- 10.3744/SNAK.2025.62.6.435
- ISSN
- 1225-1143
2287-7355
- Abstract
- The continual rise in fuel prices and increasingly stringent environmental regulations imposed by the International Maritime Organization (IMO) have made energy efficiency a critical challenge for the shipping and shipbuilding industries. Accurate prediction of ship propulsion performance and fuel consumption at the design and early operational stages is essential not only for the development of eco-friendly ships but also for establishing cost-effective operational strategies. This study aims to develop a prediction framework for predicting ship fuel consumption that can be practically applied in ship design and operational decision-making. Unlike previous approaches relying on operational data from in-service vessels, the proposed method leverages model test results and computational fluid dynamics (CFD) simulations to construct regression-based ship performance models. By incorporating ship principal particulars and route-specific environmental conditions, these models generate full-scale power curves and estimate fuel consumption. The proposed methodology provides a systematic means to support shipyards in performance guarantee evaluations and design optimization, as well as to enable ship operators to make informed economic decisions in route planning and fleet operation.
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