论文标题
热活动拉格朗日示踪剂维持的大规模对流流
Large-scale convective flow sustained by thermally active Lagrangian tracers
论文作者
论文摘要
悬浮在流体中的非等温粒子会导致复杂的相互作用 - 这些颗粒会响应流体流动的变化,而流体流的变化又通过其温度异常而改变。在这里,我们基于热耦合到流体的示踪剂颗粒进行新的概念证明数值研究。我们认为颗粒可以调整其内部温度对某些局部流体特性的反应,并遵循简单的,硬接线的主动控制方案。我们研究了通过将颗粒温度从热变为冷的情况,具体取决于流动中的上升还是下降来引起不稳定性。根据活动颗粒的数量及其过量的负/正温度,可以实现从稳定到不稳定对流流量的宏观转变。稳定状态的特征是流量低,湍流动能,温度较高,没有大规模特征。对流状态的特征是湍流动能,自我维持的大规模对流和弱稳定的温度梯度。颗粒单独促进稳定温度梯度的形成,而它们的综合作用会引起大规模的对流。当拉格朗日温度尺度很小时,形成了弱对流的层流系统。还将拉格朗日方法与均匀的欧拉体积加热进行比较,平均注射曲线相同,并且没有观察到这种过渡。我们的经验方法表明,热对流可以通过纯lagrangian强迫控制,并为其他基于数据驱动的粒子方案开辟了道路,以增强或耗尽热流中的大规模运动。
Non-isothermal particles suspended in a fluid lead to complex interactions -- the particles respond to changes in the fluid flow, which in turn is modified by their temperature anomaly. Here, we perform a novel proof-of-concept numerical study based on tracer particles that are thermally coupled to the fluid. We imagine that particles can adjust their internal temperature reacting to some local fluid properties and follow simple, hard-wired active control protocols. We study the case where instabilities are induced by switching the particle temperature from hot to cold depending on whether it is ascending or descending in the flow. A macroscopic transition from a stable to unstable convective flow is achieved, depending on the number of active particles and their excess negative/positive temperature. The stable state is characterized by a flow with low turbulent kinetic energy, strongly stable temperature gradient, and no large-scale features. The convective state is characterized by higher turbulent kinetic energy, self-sustaining large-scale convection, and weakly stable temperature gradients. The particles individually promote the formation of stable temperature gradients, while their aggregated effect induces large-scale convection. When the Lagrangian temperature scale is small, a weakly convective laminar system forms. The Lagrangian approach is also compared to a uniform Eulerian bulk heating with the same mean injection profile and no such transition is observed. Our empirical approach shows that thermal convection can be controlled by pure Lagrangian forcing and opens the way for other data-driven particle-based protocols to enhance or deplete large-scale motion in thermal flows.