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易流态固体散货海运液化风险预测

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为有效控制海运环境下易流态固体散货因液化而导致的船舶倾覆事故风险,基于船舶运动学及波能理论,采用AWQA水动力计算软件,模拟分析全球固体散货海运主力船型在各典型海域航行过程中所遭遇的外界环境载荷,并根据土动力学理论及三轴试验结果对相关外界环境载荷进行货物液化风险的等效分析,在此基础上,构建货物液化风险评估模型.基于风险评估模型及其数值计算样本,采用BP神经网络算法完成货物液化风险快速预测,实现了货物海运液化风险的快速智能预测,并通过模型的权值矩阵及阈值矩阵得到BP快速预测模型的显性表述.运用该预测模型,对4种典型易流态固体散货海运环境下的液化风险进行快速预测,预测结果与评估模型结果具有很好的一致性.该预测模型可基于船型和海况等参数快速、有效预测易流态固体散货海运液化风险,为一线海事监管提供了安全方法,同时对IMSBC规则的发展也起到良好的促进作用.
Risk prediction of liquefiable solid bulk cargoes during sea transportation
In order to effectively control the ship capsizing risk caused by liquefaction of liquefiable solid bulk cargo during sea transport,based on ship kinematics and wave energy theo-ry,AWQA hydrodynamic analysis software was used to simu-late and analyze the external environmental loads encountered by ships while sailing in various typical sea areas,and the e-quivalent analysis of the liquefaction risk of the cargo and the related assessment model was carried out according to the the-ory of soil dynamics and results of triaxial tests,and on this basis,the risk assessment model for cargo liquefaction was constructed.Based on the risk assessment model and its nu-merical calculation samples,a fast prediction model for cargo liquefaction risk was completed by using the BP neural net-work algorithm,thereby achieving fast and intelligent predic-tion of cargo maritime liquefaction risk,and the explicit ex-pression of the BP fast prediction model was obtained by the weight matrix and threshold matrix of the model.The predic-tion model was used to quickly predict the liquefaction risk of four typical liquid solid bulk cargo shipping environments,and the prediction results were consistent with the evaluation model results.This prediction model can quickly and effec-tively predict the liquefaction risk of liquid solid bulk cargo in marine transportation based on parameters such as ship type and sea conditions,providing a safety method for frontline maritime supervision and promoting the development of IMS-BC rules.

liquefiable solid bulk cargosea transportlique-faction riskintelligent algorithmquick prediction

吴宛青、白兆傲、赵子豪、郑庆功、封星、杜嘉立、张春龙、吉海龙

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大连海事大学轮机工程学院,辽宁大连 116026

大连海事大学航海学院,辽宁大连 116026

中华人民共和国辽宁海事局大连危险货物运输研究中心,辽宁大连 116001

易流态固体散货 海上运输 液化风险 智能算法 快速预测

国家自然科学基金面上项目国家自然科学基金面上项目

5187902552271358

2024

大连海事大学学报
大连海事大学

大连海事大学学报

CSTPCD北大核心
影响因子:0.469
ISSN:1006-7736
年,卷(期):2024.50(1)
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