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受高寒地区极端天气影响和换热管换热作用,氧化槽内的温度分布不均、复杂多变,甚至影响细菌氧化的效率。为探究氧化槽温度动态分布和实时变化,融合DDDAS思想提出离线—在线分离法对氧化槽温度进行实时动态精准仿真预测。首先建立氧化槽内部热量传递模型;其次针对系统参数空间高维问题,离线阶段采用POD方法确定氧化槽温度变化的主导模态,降低系统参数维度;为了解决传感器测量有效信息难的问题,在线阶段采用贪婪算法优化传感器测量位置;最后通过RKF将测量信息注入到仿真中以提高氧化槽温度的预测精度。结果表明,离线—在线分离法能够对氧化槽温度进行实时精准预测。
Abstract：Affected by extreme weather in cold area and heat transfer of heat exchanger pipeline,temperature distribution in oxidation tank is uneven,complex and changeable,thus affecting efficiency of bacterial oxidation.In order to study temperature dynamic distribution and real-time change of oxidation tank,an offline-online splitting methodology is proposed based on DDDAS to predict temperature of oxidation tank by real-time dynamic accurate simulation.Heat transfer model of oxidation tank is established.In order to solve problem of high dimension of system parameter space,POD method is used to find POD basis of temperature change of oxidation tank in order to reduce system parameter dimensions at offline stage.To address sensor measurement problem,greedy algorithm is used to optimize sensor position in online phase.Finally,RKF is used to inject measurement information into simulation to improve prediction accuracy of oxidation trough temperature.The experimental results show that offlineonline splitting methodology can accurately predict temperature of oxidation tank.
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基本信息:
中图分类号:TF831
引用信息:
[1]赵威振,南新元,孙明.氧化槽温度实时动态精准预测仿真研究[J].有色金属(冶炼部分),2018(07):25-30.
基金信息:
国家自然科学基金资助项目(61463047)
2018-07-12
2018-07-12