摘要
为预报某深海无动力传感器搭载装置水下运动时间,指导海上搜救人员及时回收装置,提出了一种基于Fluent计算流体力学仿真软件实现深海装置水下运动预报计算的稳态叠加算法.通过调用Fluent软件中的udf函数,链接journal和scheme两类批处理文件,解决了运动预报仿真时需要人工干预反复更新Fluent仿真参数和重复启动Fluent仿真的问题,实现了稳态叠加算法的自动化智能计算,提高了运动预报效率.最后,通过湖上试验验证了基于Fluent仿真软件实现水下装置稳态叠加智能预报的准确性.
In order to forecast the surfacing time of the unpowered deep-sea device and guide the mari-time searching personnel to recover the device in the sea trials,a steady-state superposition algorithm was proposed,which could achieve the forecast calculation of the device′s underwater motion based on the computational fluid dynamics software.To solve the problem that the simulation of motion fore-cast requires to update simulation parameters and start simulation by human intervention repeatedly, udf function of Fluent software was used,two kinds of batch files named journal file and scheme file were linked.The automated intelligent computing of the algorithm is realized,and the efficiency of motion prediction was improved.Finally,the accuracy of underwater-device′s intelligent forecast of steady-state superposition based on Fluent software was validated through the underwater experiment in the lake.
出处
《华中科技大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2015年第S1期109-112,共4页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(51209100)
高等学校博士学科点专项科研基金资助项目(20120142120045)
湖北省自然科学基金资助项目(2014CFB253)
中央高校基本科研业务费专项资金资助项目(2015TS006)
关键词
水下机器人
深海无动力装置
回收
运动预报
稳态叠加算法
水下试验
autonomous underwater vehicle
deep-sea device
recovery
motion prediction
steady-state superposition algorithm
underwater experiment