Vaping Next to a Truck is A Lesson in Aerodynamics
An article in Discovery written by Nathanial Scharping explains why this video can be explained by physics:
As a vehicle travels, aerodynamics change. This would be true when applied to a car or any other motor vehicle, but on a smaller scale. Trucks cruising at a high speed creates high pressure in the air waves in front and on the sides of the truck. This creates something like a vacuum as the truck is next to the vapor, then after it passes the vapor floods the empty space. Small vortexes form and suck in and push back the air; like a wind tunnel The vapor is first pushed forward by a slipstream, and then pushed back by the airways.
These aerodynamics are the reason that trucks will go into another lane on the highway if there is a pedestrian on the road. Depending on the speed/velocity of the truck, a pedestrian could be sucked right onto the highway.
A diagram of these vortexes are pictured here:
The aerodynamics of a certain vehicle at a certain is difficult to calculate and requires a 6 force equation. In order to do something to this scale, many scientists will use STAR CCM+ commercial software, which is based on the two equation SST k-ω model:
These equations are also used in a turbulence model for NASA.
- Citations:
Kim, Julie, et al. “A CFD Study of Pickup Truck Aerodynamics.” Grand Valley State University: Department of Mechanical Engineering.Scharping, Nathanial. “Vaping Next to a Truck Is a Lesson in Aerodynamics.” Discovery: Science for the Curious, Discovery Magazine, 28 Aug. 2017, blogs.discovermagazine.com/d-brief/2017/08/28/vaping-next-to-truck/#.Wd-EikyZPBI.



![\frac{\partial (\rho k)}{\partial t} + \frac{\partial (\rho u_j k)}{\partial x_j}
= \cal P - \beta^* \rho \omega k + \frac{\partial}{\partial x_j}
\left[\left(\mu + \sigma_k \mu_t \right)\frac{\partial k}{\partial x_j}\right]](https://turbmodels.larc.nasa.gov/sst_eqns/img2.png)
![\frac{\partial (\rho \omega)}{\partial t} + \frac{\partial (\rho u_j \omega)}{\partial x_j}
= \frac{\gamma}{\nu_t} \cal P -
\beta \rho \omega^2 + \frac{\partial}{\partial x_j}
\left[ \left( \mu + \sigma_{\omega} \mu_t \right)
\frac{\partial \omega}{\partial x_j} \right] +
2(1-F_1) \frac{\rho \sigma_{\omega 2}}{\omega} \frac{\partial k}{\partial x_j}
\frac{\partial \omega}{\partial x_j}](https://turbmodels.larc.nasa.gov/sst_eqns/img3.png)
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