You’re on an airplane when you feel a sudden jolt. Outside your window nothing seems to be happening, yet the plane continues to rattle you and your fellow passengers as it passes through turbulent air in the atmosphere.
你在飛機上, 突然感覺到一陣顛簸。 在你旁邊的窗外似乎 沒有發生任何事, 但飛機持續震動讓你 和其他乘客感到不安, 此時它正在穿過大氣中的亂流。
Although it may not comfort you to hear it, this phenomenon is one of the prevailing mysteries of physics. After more than a century of studying turbulence, we’ve only come up with a few answers for how it works and affects the world around us.
雖然知道這點可能 也無法讓你欣慰一點, 但這個現象是物理中 主要的謎題之一。 在研究亂流至少一個世紀之後, 我們只能提出幾個答案, 說明它怎麼運作, 怎麼影響我們周圍的世界。
And yet, turbulence is ubiquitous, springing up in virtually any system that has moving fluids. That includes the airflow in your respiratory tract. The blood moving through your arteries. And the coffee in your cup, as you stir it. Clouds are governed by turbulence, as are waves crashing along the shore and the gusts of plasma in our sun. Understanding precisely how this phenomenon works would have a bearing on so many aspects of our lives.
但,亂流無所不在, 它會突然出現在差不多 任何有流體的系統中。 包括你呼吸道中的氣流。 在你血管中流動的血液。 當你攪拌時你杯子裡的咖啡。 雲朵是被亂流所支配的, 拍打海岸的海浪 以及太陽電漿也都是。 若能清楚了解這個現象 是怎麼運作的, 對我們生活的許多方面都會有影響。
Here’s what we do know. Liquids and gases usually have two types of motion: a laminar flow, which is stable and smooth; and a turbulent flow, which is composed of seemingly unorganized swirls. Imagine an incense stick. The laminar flow of unruffled smoke at the base is steady and easy to predict. Closer to the top, however, the smoke accelerates, becomes unstable, and the pattern of movement changes to something chaotic. That’s turbulence in action, and turbulent flows have certain characteristics in common.
以下是我們確實知道的。 液體和氣體通常有兩種移動方式: 「層流」這種方式很穩定且平順; 以及「亂流」,它是由 看似很亂的漩渦組成。 想像一支香。 在基部的煙很平靜, 它的層流很穩定,很容易預測。 然而,在更接近上端處, 煙會加速,變得不穩定, 移動的模式會改變,變得很混亂。 那就是正在發生的亂流, 亂流有某些共同的特徵。
Firstly, turbulence is always chaotic. That’s different from being random. Rather, this means that turbulence is very sensitive to disruptions. A little nudge one way or the other will eventually turn into completely different results. That makes it nearly impossible to predict what will happen, even with a lot of information about the current state of a system.
首先,亂流總是很混亂的。 和隨機有所不同, 亂流容易被擾亂。 朝某個方向輕輕推一下, 最終會變成完全不同的結果。 因此幾乎完全不可能 預測會發生什麼狀況, 即使知道很多系統的現況也一樣。
Another important characteristic of turbulence is the different scales of motion that these flows display. Turbulent flows have many differently-sized whirls called eddies, which are like vortices of different sizes and shapes. All those differently-sized eddies interact with each other, breaking up to become smaller and smaller until all that movement is transformed into heat, in a process called the “energy cascade."
亂流還有另一項重要特徵, 就是亂流會展現出 不同規模的運動。 亂流有許多不同 大小的旋渦,叫做「渦流」, 也就是不同形狀和大小的渦旋渦。 各種大小的渦流 會彼此產生交互作用, 因而被打散而變得越來越小, 直到所有的運動都被轉換為熱能, 這個過程叫做「能量串跌」。
So that’s how we recognize turbulence– but why does it happen? In every flowing liquid or gas there are two opposing forces: inertia and viscosity. Inertia is the tendency of fluids to keep moving, which causes instability. Viscosity works against disruption, making the flow laminar instead. In thick fluids such as honey, viscosity almost always wins. Less viscous substances like water or air are more prone to inertia, which creates instabilities that develop into turbulence.
這就是我們辨識出亂流的方式—— 但,為什麼會發生亂流? 在所有的流動液體或氣體中, 都有兩股相反的力量: 「慣性」和「黏性」。 慣性是流體持續流動的傾向, 會造成不穩定。 黏性則是在對抗擾亂, 讓流動變成層流。 在很濃稠的流體中,比如蜂蜜, 黏性幾乎永遠勝出。 比較不黏稠的物質,像水或空氣, 就比較容易受慣性影響, 慣性會造成不穩定, 進而發展成亂流。
We measure where a flow falls on that spectrum with something called the Reynolds number, which is the ratio between a flow’s inertia and its viscosity. The higher the Reynolds number, the more likely it is that turbulence will occur. Honey being poured into a cup, for example, has a Reynolds number of about 1. The same set up with water has a Reynolds number that’s closer to 10,000.
若要測量流動將會落在何處, 會採用所謂的「雷諾數」, 它是流動的慣性對黏性的比率。 雷諾數越高, 亂流發生的可能性就越高。 比如,把蜂蜜倒入一個杯子中, 雷諾數大約是 1。 同樣的狀況換成水,
The Reynolds number is useful for understanding simple scenarios, but it’s ineffective in many situations. For example, the motion of the atmosphere is significantly influenced by factors including gravity and the earth’s rotation. Or take relatively simple things like the drag on buildings and cars. We can model those thanks to many experiments and empirical evidence. But physicists want to be able to predict them through physical laws and equations as well as we can model the orbits of planets or electromagnetic fields.
雷諾數就接近 10,000。 若要了解簡單的情境, 雷諾數很有用, 但在許多情況下則不太有效。 比如,大氣的活動會大大受到 重力及地球轉動等因子的影響。 或者,用相對簡單的事物為例, 如大樓和汽車上方的阻力。 託許多實驗和實證證據的福, 我們能建立對應的模型。 但物理學家想透過物理定律 和方程式來預測它們, 希望能做到像我們能針對 星球軌道的電磁場來建模一樣。
Most scientists think that getting there will rely on statistics and increased computing power. Extremely high-speed computer simulations of turbulent flows could help us identify patterns that could lead to a theory that organizes and unifies predictions across different situations. Other scientists think that the phenomenon is so complex that such a full-fledged theory isn’t ever going to be possible.
大部分的科學家認為, 要達到這個目標就要仰賴統計, 以及越來越強的運算能力。 針對亂流做非常高速的電腦模擬, 能夠協助我們辨識出一些模式, 也許可以創造出一個理論, 組織和統合各種不同情況中的預測。 其他科學家認為, 這個現象太複雜了, 不可能會有這種 成熟完整的理論存在。
Hopefully we’ll reach a breakthrough, because a true understanding of turbulence could have huge positive impacts. That would include more efficient wind farms; the ability to better prepare for catastrophic weather events; or even the power to manipulate hurricanes away. And, of course, smoother rides for millions of airline passengers.
希望我們能夠突破瓶頸, 因為若有亂流有真正的了解, 會帶來很大的正面影響, 包括效能更高的風場, 對災難性天氣事件做更好的準備, 或甚至操控颶風讓它轉向。 當然也能為數百萬航空公司乘客 提供更順暢的旅程。