Thursday, 13 July 2017

Wallis (flooding) Correlation - notes

Wallis Correlation notes from Lockett, MJ. 1995. Flooding of rotating structured packing and its application to conventional packed columns. Chemical Engineering Research & Design, 73(4). pp 379-384.
- Lockett argues structured packing have a higher capacity (at same surface area) compared to random packing. He used a corrugated sheet packing.
- for flooding:
- He did not see a sharp increase in pressure drop as the onset of flooding. In contrast to a  conventional (1G) column.
- Determined flooding from peak pressure drop at constant gas & liquid flow with increasing RPM. He found the peak of the curve matched observations better than the 500Pa/100RPM condition used by Singh et al.
Wallis correlation:
- developed for counter-current two-phase flows in tubes.

Equation is in the form of a straight line. So you can plot the capacity factors and find ‘m’ and ‘C’. Lockett found the lines were parallel (m = 2.14) and that the dependence of C through Ng0.25  (from a log-log plot) fitted his data well. He used literature data from conventional (1G) columns to get a flooding-predicting equation for RPBs in the form of Equation 1. He converts it to a Sherwood correlation also using algerbra, but he argues the Wallis correlation is better because it’s simpler.

Tuesday, 4 July 2017

F1 air boxes

The air box on a formula one car sits above the driver's head. It's purpose is to provide an air supply for burning fuel in the engine. A formula one car's air box may also be referred to as a "scoop" or a "roll hoop" or "air intake". Somewhat intuitively, reason it is sometimes called a roll hoop is because it also serves to protect the driver's head when the car is flipped, and regulations require it to also contain a roll cage structure for this purpose. You may also see them referred to as an "intake manifold" - the intake manifold is actually the part that immediately follows the air intake, which distributes the air into the cylinders of the engine. The air intake and the intake manifold are two separate parts in everyday cars, but in F1 cars the air is immediately directed into the engine to increase the power it supplies so the lines between the two are somewhat blurred. 
A air box acts like a turbocharger. It takes air from outside the car, from a point on the bodywork where the airflow stagnates, and therefore has a high pressure. Ramming this high pressure air into the engine increases the power output because more oxygen and therefore fuel can be burnt inside the engine. 
Boy-racers and the like may fit their cars with NACA ducts, basic scoops, and other simple designs in an effort to achieve similar effects. But for an F1 air box, design is much more complicated. Many factors must be accounted for during the design:

1. drag from the airbox, which slows the car down. 
2. uniform air distribution into the cylinders, non-uniform distribution can starve cylinders of air which makes the car slower.
3. resonance effects between the engine and the air intake. In state-of-the-art CFD modelling, the CFD model of the air intake is combined with a 1D model of the engine to try to address this problem. 
4. Preventing detached/recirculating flow inside the air box. immediately after entering the airbox, the flow turns a 90 degree bend into the engine. If the flow recirculates in this region it will case a higher pressure drop and non-uniform distribution of air into the cylinders.  
5. In most modern formula one cars, the air box is segmented into multiple inlets, and supplies air for many other applications in addition to engine air supply. It may be used for cooling flow. It can be redirected over the rear wing, stalling the rear wing, which provides the driver with a means of controlling the cars down force. 
6. you may also see air boxes which have a vertical ridge that seems to stick out after the duct:(http://www.racecar-engineering.com/wp-content/uploads/2010/05/mercbox.jpg). This may be another drag-reducing measure. similar modifications to crossflow over a cylinder serve to dampen the wake, reducing drag due to vortex shedding etc.
7. when the engine is not running at 100%, less air is going into the airbox, so more air must flow around the airbow. This can disturb the airflow over the car, affecting the rear wing, which can reduce downforce, for example, if the driver is slowing down to enter a corner - just when he/she would need the downforce !

The design of a modern F1 car's air intake has to take into account lots of factors and as a result the first (drag reduction) may be compromised to serve the others better. As I've been researching this, I was surprised to find there's actually isn't that much information available in open literature. This is probably because the various teams want details of their designs to stay secret to give them the competitive edge. This post serves a basic summary of what I've found in my short search. 

Thursday, 5 January 2017

wall functions and near-wall behaviour

Wall functions and near-wall behaviour
The standard k-e model cannot be integrated down to the wall. (Versteeg and Malalasekera (p77) say that k = 0 and e = 0 at the wall, so eddy viscosity values become indeterminate. Wilcox (p.181) says that when integrated without dampening functions, most turbulence models give false values for C (the additive constant in the log law)).The standard k-e model solves this issue using a wall function. The wall function applies the law of the wall to find the near-wall behaviour. The law of the wall applies to the turbulent boundary layer in scenarios such as pipe flow and flat plate boundary layers. When describing the law of the wall it is generally split into four layers.
The laminar (a.k.a. viscous, linear) sublayer is directly next to the wall. In this layer the velocity profile is linear resembling couette flow. On the wall, the no-slip condition applies and the velocity is zero, outwards from this point the shear stress is roughly constant, and therefore roughly equal to the wall shear stress. u+ = y+ in this region. The real laminar sublayer is very thin (it extends to y = +5 or so).
Between this and the next region is the ‘buffer layer’; The buffer layer is the name for the region between the laminar sublayer and the log-law layer, where experimental data doesn’t quite fit either layers. If it’s to be modelled, it’s usually fitted with a smoothing function.
The next region is the log layer. The velocity profile in the log layer can be described using the law of the wall, , where the Von-Karman constant and C+ = 5 for smooth walls. The log layer extends from about y+ = 30 to y+ = 300, but in some cases (such as turbulent pipe flow) it can give a good approximation of the whole velocity profile.
Beyond this region, the outer layer or “law of the wake” is valid. This region is inertia-dominated core flow far from the wall and free of viscous effects.  The law of the wake is:
This is based on the velocity defect law and the names are sometimes used interchangeably.
The aim of the wall function in the standard k-e model is to use these laws to define the velocity in the near wall cell. So the standard wall function uses the log law to define u in the mesh cell nearest the wall, this is why it requires a mesh of between y+ = 30 and y+= 500. So the main advantage of the wall function is that it allows a coarse-grid solution. Measurements of turbulent kinetic energy budgets indicate production equals dissipation. Using these assumptions plus the eddy viscosity formula the wall function is:
This is applicable at high Reynolds numbers. Fluent contains various variations on this, covered in the theory guide. (I believe ‘scalable wall functions’ <- intended for use with dense meshes, ‘non equilibrium wall functions’ <- a bit of a grey area between the two. Uses log-law with press. grad. correction for velocity & two-layer approach for k)
At low Reynolds numbers the log-law is not valid. Models such as the ‘Low-Re k-e turbulence model’ use wall dampening functions. These can also be referred to as ‘two-layer k-e model’. Fluent calls it ‘enhanced wall treatment’ (Fluent’s ‘enhanced wall treatment’ switches between this and the wall function depending on the y+ of the mesh, using a blending function. The idea is to make the turbulence model robust to coarse mesh regions in the model).
In the theory guide, it defines the enhanced wall treatment as follows. The domain is divided into fully-turbulent and viscosity-affected regions based on wall-distance-turbulent-Reynolds number is the cutoff point. In the fully-turbulent region, the turbulence model (k-e model or whatever) is solved as per. In the viscosity-affected region, the one-equation Wolfstien (1969) model is used instead, expect for momentum & k, which still follow the k-e model. Turbulent viscosity is found from:
The length scale is found from:
This definition of turbulent visc. is blended with the turbulence model definition (k-e model)
Blending:     
In the viscosity-affected region, turbulent dissipation is found from: The length scale is found from .
This is again blended with the bulk values similar to turbulent viscosity above. In simulations where Rey is less than 200 everywhere, e is found algebraically from the above and not from the turbulence model (k-e model or whatever).
For momentum, a blending function is applied. This covers the buffer layer, and allows for including other effects easily (such as pressure gradient effects).
The enhanced wall treatment calculates u+turb as follows, in order to include pressure gradient and heat transfer effects. (I think this and the equation above are all for calculating u in the first cell only? i.e. this is how it switches between a wall function approach and a low-Re approach?):
Solving the above is an ODE that Fluent solves analytically. If all three constants equal zero, then this becomes the log-law. For u+lam:
(the manual then covers a thermal boundary layer equation, which I will leave out).
(I think there’s two issues going on: I think wall dampening functions are needed to control turbulence values (k etc) near to the wall, but a value for the boundary condition (the first cell) also needs to be defined.?  )
Trying to shed some light on the k-w model behaviour in the near-wall region:
Quotes on k-ω:
Versteeg and malalasekera, p 91:
“the k-ω model initially attracted attention because integration to the wall did not require wall dampening functions in low Reynolds number applications”
Not the most academic reference! forum post:
“the k-omega based models were designed originally for the near wall region and therefore does not require dampening functions, hence hybrid wall functions (blending of near wall and log law function) were implemented directly and same is true for SA model”
Ansys Fluent theory Guide, p114, p 126:
“y+ independent formulations are the default for all ω-equation based turbulence models… …for the ω-equation based models, use the default – EWT(enhanced wall treatment)- ω … (p126) EWT-ω: Unlike the standard ε-equation, the ω-equation can be integrated through the viscous sublayer without the need for a two-layer approach…”
CFD online Wiki:
“the SST k- ω model can be used as a low-Re turbulence model without any damping functions”
(Section afterwards says fluent uses wall functions unless “transitional flows option” is enabled. I think the author could be getting “transition-SST” and “Low-Re” options in Fluent confused ?)
Wilcox, p 181:
“the k-ω model is, in fact, unique because viscous modifications to its closure coefficients are not needed to achieve a satisfactory value of C”
(does not mean that corrections are not used at all !!)
Boundary conditions, SST k-w Model, Fluent Theory guide:
For the k-w model at the wall boundary condition, a switching function (not given in fluent guide, CFD online suggest route-mean-square type belnding function) blends between these two values depending on the grid density.
According to Versteeg and Malalasekera (p 91), this is the hyperbolic variation of w at the near-wall grid point. it is more commonly seen as elsewhere. Fluent’s equation looks different but is actually the same if you do the algebra subbing in the dimensionless no’s.
Boundary condition for k are “as for enhanced-wall treatment” in the k-e model. Not really clear what this is in actuality. Closest is page 118 in Fluent theory guide:
where ‘n’ = local coordinate relative to cell wall. Versteeg and Malalasekera state “k at the wall is set to zero” for the k-w model. This stems from the no-slip condition, according to Wilcox (p.176).
k = 0 and ω as table supported by NASA website. also gives “farfield values” (I think this is recommended inlet & outlet conditions?)
low-Re SST in fluent theory guide:
The low-Re correction is nothing to do with the transition-SST model. The low-Re correction acts on μt and is available in the k-ω models:
Sources:
Versteeg, HK. Malalasekera, W. (2007) An introduction to computational fluid dynamics. 2nd ed. Prentice-hall.
Wilcox, DC. (2006). turbulence modelling for CFD. 3rd ed. DCW industries.
Wolfstien (1969). The velocity and temperature distribution in one-dimensional flow with turbulence augmentation and pressure gradient. International journal of heat and mass trans 12(3). can’t access requires ILL?
NASA website: https://turbmodels.larc.nasa.gov/sst.html