The sand-driven flow is studied from the continuum viewpoint in this paper. The crux of this work is how to model the stresses of the particle phase properly. By analysing the two-fluid model which usually, works in s...The sand-driven flow is studied from the continuum viewpoint in this paper. The crux of this work is how to model the stresses of the particle phase properly. By analysing the two-fluid model which usually, works in solving gas-particle two-phase .flow,. we find that this model has many. deficiencies for studying the sand-driven flow,even for the simplest case- the steady, two-dimensional fully-developed flow.Considering this, we have proposed the three-fluid model in which the upward particles and the downward-particles ore regarded as two kinds of fluids respectively.It is shown that the three-fluid model is better than the two-fluid model in reflecting the internal structure of the flow, region and the influence of the boundary situations on the flow. and it is advantageous to find an approximate solution in that the main components of the particle-phase stresses can be explicitly expressed by those variables in the three-fluid model.In the end, the governing equations as well as the boundary. conditions for the three-fluid model are provided with a discussion.展开更多
可再生能源的高渗透率给电网供需匹配带来严峻挑战的同时,燃煤机组需要承担着大量的调峰调频任务,这对过热汽温系统的安全稳定运行造成了一定威胁,因此有必要建立面向热工控制的汽温数学模型。考虑到迟延型扩张状态观测器(time-delayed ...可再生能源的高渗透率给电网供需匹配带来严峻挑战的同时,燃煤机组需要承担着大量的调峰调频任务,这对过热汽温系统的安全稳定运行造成了一定威胁,因此有必要建立面向热工控制的汽温数学模型。考虑到迟延型扩张状态观测器(time-delayed extended state observer,TD-ESO)的总扰动信号中含有大量模型信息,提出一种基于ESO补偿模型的参数智能优化和信息提取方法,即以总扰动中未知信息量最小为目标,采用改进沙丘猫算法对模型参数优化并提取总扰动中已知模型信息补偿至ESO的输入端。在仿真算例方面,线性和非线性系统的测试结果表明,所提辨识方法对有无输入迟延的两种系统均有良好的适用性和较高的精度;在实际应用方面,基于超超临界二次再热机组的过热汽温系统数据进行模型辨识与验证,同样表明该建模方法是合理、准确的。因此,该文所建立的模型能够为汽温系统的控制策略设计和性能优化等方面提供有价值的参考。展开更多
文摘The sand-driven flow is studied from the continuum viewpoint in this paper. The crux of this work is how to model the stresses of the particle phase properly. By analysing the two-fluid model which usually, works in solving gas-particle two-phase .flow,. we find that this model has many. deficiencies for studying the sand-driven flow,even for the simplest case- the steady, two-dimensional fully-developed flow.Considering this, we have proposed the three-fluid model in which the upward particles and the downward-particles ore regarded as two kinds of fluids respectively.It is shown that the three-fluid model is better than the two-fluid model in reflecting the internal structure of the flow, region and the influence of the boundary situations on the flow. and it is advantageous to find an approximate solution in that the main components of the particle-phase stresses can be explicitly expressed by those variables in the three-fluid model.In the end, the governing equations as well as the boundary. conditions for the three-fluid model are provided with a discussion.
文摘可再生能源的高渗透率给电网供需匹配带来严峻挑战的同时,燃煤机组需要承担着大量的调峰调频任务,这对过热汽温系统的安全稳定运行造成了一定威胁,因此有必要建立面向热工控制的汽温数学模型。考虑到迟延型扩张状态观测器(time-delayed extended state observer,TD-ESO)的总扰动信号中含有大量模型信息,提出一种基于ESO补偿模型的参数智能优化和信息提取方法,即以总扰动中未知信息量最小为目标,采用改进沙丘猫算法对模型参数优化并提取总扰动中已知模型信息补偿至ESO的输入端。在仿真算例方面,线性和非线性系统的测试结果表明,所提辨识方法对有无输入迟延的两种系统均有良好的适用性和较高的精度;在实际应用方面,基于超超临界二次再热机组的过热汽温系统数据进行模型辨识与验证,同样表明该建模方法是合理、准确的。因此,该文所建立的模型能够为汽温系统的控制策略设计和性能优化等方面提供有价值的参考。
