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Powering Performance Prediction of Low-Speed Full Ships and Container Carriers Using Statistical Approach

통계적 접근 방법을 이용한 저속비대선 및 컨테이너선의 동력 성능 추정

  • Kim, Yoo-Chul (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Kim, Gun-Do (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Kim, Myung-Soo (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Hwang, Seung-Hyun (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Kim, Kwang-Soo (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Yeon, Sung-Mo (Korea Research Institute of Ships and Ocean Engineering (KRISO)) ;
  • Lee, Young-Yeon (Korea Research Institute of Ships and Ocean Engineering (KRISO))
  • Received : 2021.04.01
  • Accepted : 2021.05.25
  • Published : 2021.08.20

Abstract

In this study, we introduce the prediction of brake power for low-speed full ships and container carriers using the linear regression and a machine learning approach. The residual resistance coefficient, wake fraction coefficient, and thrust deduction factor are predicted by regression models using the main dimensions of ship and propeller. The brake power of a ship can be calculated by these coefficients according to the 1978 ITTC performance prediction method. The mean absolute error of the predicted power was under 7%. As a result of several validation cases, it was confirmed that the machine learning model showed slightly better results than linear regression.

Keywords

Acknowledgement

본 논문은 선박해양플랜트연구소 주요사업 "극한환경상태의 선박성능 평가기술 개발"로 수행된 결과입니다. (PES3910)

References

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