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Ship Energy Consumption Prediction with Gaussian Process Metamodel

机译:船舶能耗预测与高斯过程元模型

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Shipping is a major contributor to the global CO2 emissions.It is important to improve the ship energy efficiency and reduce the ship emissions.Various emission reduction measures have been proposed to reduce the ship emissions.In order to evaluate the efficiency of these emission reduction measures,it is necessary to evaluate the reduction of fuel consumption for these measures.However,due to the complex of ship energy system,it is difficult to assess the ship fuel consumption under different scenarios considering both operational and weather conditions through physical systems or simulation models.In this paper,a Gaussian process metamodel is developed to predict the ship fuel consumption for different scenarios.This model not only considers the effects of operational conditions such as speed and trim,but also takes into account the impacts of weather conditions such as wind and wave effects.The effects of these factors on ship fuel consumption are further evaluated.The case study indicates the accuracy and efficiency of using Gaussian process metamodel for ship energy consumption prediction.
机译:航运是全球二氧化碳排放的主要贡献者。提高船舶能源效率并减少船舶排放是重要的。提出了令人减少减排措施,以减少船舶排放。为了评估这些减排措施的效率,有必要评估这些措施的燃料消耗的降低。然而,由于船舶能量系统的复杂,难以通过物理系统或仿真模型来评估不同场景的船舶燃料消耗。在本文中,开发了高斯工艺元模型,以预测不同场景的船舶燃料消耗。本型不仅考虑了速度和修剪的运行条件的影响,还考虑了风的影响波浪效应。进一步评估了这些因素对船舶燃料消耗的影响。案例研究利用高斯工艺元模型进行船舶能耗预测的准确性和效率。

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