带坞舱船舶尾舱消浪装置消浪性能研究

目的 带坞舱船舶尾部具有与外界连通的自由液面,由于船舶运动会在坞舱内产生波浪,形成有害的波浪砰击,影响舱内装备的正常作业。针对这一问题,系统地对带坞舱船舶尾舱内的消浪方案进行模拟与优化,提出一套具有良好消浪性能的消浪装置方案。方法 以荷兰皇家海军两栖运输船为目标进行三维建模,使用CFD方法对其进行不同波浪下船舶响应模拟和分析,监测船舶的运动响应和舱内多个监测点的波高情况,使用多孔挡板为基础,给出一套消浪装置,并进行带有消浪装置方案的船舶响应模拟,评估该消浪装置方案的消浪性能。结果 对舱内首端和侧壁布置多孔板消浪装置,消浪效果可达40%~50%,验证了该消浪装置的可行性。结论 采用多孔介质区域模型对带有多孔介质消浪装置的整船进行数值模拟,在计算效率远高于对实际物理模型建模的同时,可以得到较好的消浪效果。     

An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

废混油钻井液资源化利用技术研究

废钻井液是钻井作业中主要污染源之一,其中含有重金属、碱、盐、油、有机物等多种污染物质,特别是废混油钻井液,油含量更高,是较难解决的问题之一,也是制约油田企业环境质量提高和可持续发展的一大难题。以废钻井液处理为代表的资源化利用技术可有效治理井场废物,将处理后的废钻井液直接用来做井场围堰和平整地面的材料,既可有效地利用废物,消除污染源,又可缓解因污染引起的工农矛盾,减少由钻井开发引发的污染赔款,实现社会效益、经济效益和环境效益的统一。