Travis Mikjaniec's Blog
Travis Mikjaniec's Blog RSSSmoke, Smoke, Everywhere?
Smoke, Smoke, Everywhere?
This has the possibility to be my most unpopular blog ever, which I’m ok with. The topic of this blog is smoking, specifically the second hand kind. Let me start by saying I am not a smoker. I don’t care for the smell, and am happy that it is not allowed in most building, Vegas casino’s being the main exception. My mom was for a long time though, and in general it seems to me that smokers have become the easy target. They are currently a voting minority so it’s easy to impose laws that take away some of their rights, which I think is wrong.
Let me clarify, in California, a lot of municipalities have 25 ft bans on smoking near doorways or windows. Ok, I can see that, but why 25 ft? Who came up with that distance? Did anyone study how smoke diffuses in the air and figure that after 25 ft the smoke has diffused to a concentration low enough to not cause cancer? I haven’t been able to find it. But ok, I understand that if I had an office window that happened to be by the local smokers spot, I would get annoyed by the daily smell of smoke, but would be forced to stay there so I could complete my job.
Then California in 2010 tried to ban smoking in State parks and beaches. Ok, I can understand that cigarettes may lead to forest fires and litter issues, but it was veto’ed by the Governor Schwarzenegger. Currently many municipalities in California have their own bans, like in San Jose, where smoking in public parks is completely banned. This is where I thought it would be good to analyze the problem in FloEFD, Mentor Graphics general purpose CFD software.
The purpose of this study is to see what type of 2nd hand smoke concentrations an innocent bystander might be expected to experience if someone nearby was smoking. First I needed a CAD model of the park, as FloEFD is a CAD embedded analysis software. Usually as a design engineer, the CAD is the easy part, as it has already been build. For me, that is my toughest bit as I usually don’t have CAD to start with. Being CAD lazy, I found a free CAD model of a skate park on www.grabcad.com. It isn’t the trees, grass and hills I was picturing when I started this, but it is a public park so I went with it. With that, I put in a couple CAD people, one to be the smoker, and 2 to be the potential second hand smokers.
Skate Park from grabcad.com, with 1 smoker and 2 non-smokers
Now I needed to come up with the analysis settings. I could find breathing rates and how much air a person breathes (~ 0.5 ft3/min), so I used that as boundary conditions on their nostrils. I assumed the smoker was exhaling 100% smoke, for every breath he took. This was highly unrealistic in my opinion, but as I couldn’t find a percentage number to put on this, I had to use a conservative number. Now, I wanted to capture any buoyancy effects, so I had the exhaled smoke breath coming out at 37 degC, while my outside air temperature was 20 degC. For the mesh setup, I didn’t know where the smoke would go, but knew i needed a finer mesh in the smoke cloud to get accurate concentration results. As such, I enabled FloEFD’s solution adaptive mesher, which will periodically pause the solve, go through the results, and add mesh where it’s needed. Very handy indeed.
Lastly, I modeled the wind. I also modeled a no wind condition, but then the hotter smoke just go upwards and never did get anywhere near my other park goers. See the figure below of an isosurface showing everywhere that the smoke is 1e-6 in concentration (1 part per million), and an animation of that smoke cloud vs time when he starts smoking and puffing. Basically the smoker is covered in a cloud of stinky smoke, likely why all cloths smell like smoke when you go to a Las Vegas casino or bar. It seems like being a couple feet away from him, you would be fairly safe, well maybe not your shoes, but still 25 feet away seems very arbitrary distance considering these results.
1 ppm smoke concentration Isosurface in no wind condition
Looking at the streamlines, you can see the contrast in forces on the smoke. Here, it’s clear that because the smoke was exhaled through his nose, it has a lot of downward momentum before any buoyancy forces can take over and bring the smoke back upwards. Had I analyzed using the mouth as my boundary condition, the results might be different. But, it the grand scheme of things, how often is the air completely still for an extended period of time. Not that likely, so I didn’t bother running a mouth breathing case.
Smoke Streamlines after one breath in no wind condition
For my wind cases, I didn’t want to have a really stiff breeze, because all that fresh wind air would dilute my smoke, yet I wanted to have enough wind to push it towards my non-smokers. I wanted to model the worst case wind, so I chose ~3 m/s. If you read my crawlspace moisture blog, you know that 1 m/s is the bare minimum a person could feel, so 3 m/s seemed like a reasonably average breeze.
Below are my angled wind results, where I directed the wind to make the one bystander right in the smoker’s wake. You can see he is right in the smoke area, but the concentration is very small. Again, I haven’t seen at what concentration of smoke causes cancer (like they provide for mercury or any other carcinogen), so I thought 1e-6 seemed like a very small amount (1e-6 volume fraction of smoke = 1 ppm, so very low). Also, again, I assumed 100% of the exhaled breath was smoke, so this is the worst possible 1 ppm smoke cloud and in reality would be smaller.
1 ppm smoke concentration isosurface for angled wind case
Looking at a contour plot of smoke concentration from 100 ppm to 1 ppm, you can see while he is in the smoke zone, he is in the low concentration area. How low, well I tracked the air entering his nose, and the table below shows he was getting an average of 8.9 ppm of smoke. What I see though, is the smoke zone is about 6 feet wide. I would just move out of that area to the clean air if I smelled smoke. Our other non-smoker is completely clear of any smoke. Of course, if you were “dropping in” to that bowl or doing any “ally’s” on that rail, you would be in the eye of the smoke cloud.
Smoke concentration contour plot, 1-100 ppm, for angled wind case
On the other hand, if we look at a contour plot of smoke concentration from 1000 ppm to 0 ppm, we can see that in the “smoke cloud” the concentration stays relatively high. I was surprised by this, as our skate park has a lot of ramps and things to create turbulence, which I thought would mix in a lot of fresh air and drop the concentration levels. In fact, looking at my measurement of distance from the smoker’s nose to the non-smokers nose, we can see they are about 40 feet apart, and the concentration in the smoke cloud makes it well past the non-smoker. So a 25 foot ban on smoking near doors and windows seems a little too low after looking at this (again, this is worst case with 100% of exhaled air being smoke). The smoke cloud is a local effect, but it propagates a long way down stream.
- Smoke concentration contour plot, 1000 ppm to 0 ppm, for angled wind case
To conclude, I don’t have any specific conclusions. I just saw an issue that was perfect for CFD to look into, and FloEFD helped me answer these questions in a minimum amount of time. As is usually the case when it comes to fluid dynamics, usually I have an idea of the answer at the beginning, but the results are rarely what I anticipated, even after years of doing this. In the end I think I showed both sides of the argument, smoke does travel a fair amount of distance, but it doesn’t blanket and poison the entire park. Should it be banned from all city parks and beaches? I don’t know if my results would swing the argument one way or the other. The X factor is the amount of smoke concentration that repeated exposer to would cause cancer, which medical science needs to answer first.
Next blog will be something lighter, aerodynamics of hockey pucks 
Tags: California, CFD, Computational Fluid Dynamics, Concentration, FloEFD, isosurfaces, Park, parts per million, Smoke
Cruise Ship Disaster Wind Analysis
The other day I was watching this show on the recent cruise ship sinking over in Italy. It was very interesting. They had ship experts looking over the data from the cruise ship, specifically GPS position and speed. One of the important factors that they said saved a lot of lives that night was the wind. After the ship had hit the underwater rocks and started taking on water, it continued out to deeper water. When the engines became submerged and stopped working, the ships momentum kept it moving out further from the island for a while. But, slowly the ship lost speed, and because there was an onshore wind of 25 miles per hour that night, it was first twisted/yawed to be perpendicular to the wind, then pushed back to shore.
The ship experts credit this as saving hundreds of lives that night, as people weren’t ordered to abandon ship for a long period of time. So long a time in fact that half the life boats couldn’t be used because the ship was leaning at too great an angle by the time people were told to abandon the ship. Many people ended up swimming for shore, which would not have been possible had it not been for the wind.
This made me wonder how much force it would take to move such a giant ship? I mean, this ship weighed 114,500 gross tons (256,480,000 lbs), and the wind was able to blow it a large distance in about an hour or 2? I needed to see what amount of force the air could exert on a ship this big.
I went on to grabcad.com, and found a cruise ship model. It was more for a desktop type model, but I easily scaled up the CAD to the dimensions of the real ship. Then, in FloEFD I simply defined the 25 mile/hour wind, set some goals to track the force on the ship, and the roll torque. Then I started to solve. It really was a very easy model to setup.
Here is what I saw. In this first image you get an idea of how large the wake is for a ship this big. I also displayed the mesh so you could see how it automatically adapted to the ship, and also the wake, which is very important to getting accurate results.
- Cruise Ship Wind Wake with Adaptive Mesh
Zooming in, we get more detail on the mesh local to the ship. You will also notice an area of light blue higher speed air coming out of the middle portion of the ship.
- Zoomed in View of Cruise Ship Wind Wake with Adaptive Mesh
What is happening here, is since I didn’t make this CAD myself, I missed the fact that there were no windows in this ship CAD, just holes through the ship. You can see in this image here the air moving through the ship where cabins should be. Obviously this isn’t correct, so a corrected model was run with the holes sealed.
- Wireframe Cruise Ship showing Air Flowing Through Holes
I also plotted velocity vectors with the velocity contours to see how the air was moving as it came toward the ship.
- Cruise Ship Wind Wake with Velocity Vectors
- From the top view, we can see the width of the wake downstream. Also, the mesh was plotted so we could see how the mesh adapts to adding cells in the areas of velocity changes to accurately capture the wake structure. The adaptive mesh is one of my favorite FloEFD features, as it saves so much time getting an accurate mesh.
- Cruise Ship Wind Wake and Adaptive Mesh Top View
We can get a better feel for the airflow using streamline animations, like the 3 below showing different views of the same streamlines.
Another good way of getting a feel for the extent of the low speed air is an isosurface, which is a 3D plot that connects points with the same value to make a surface. Here I’m looking at anywhere that the airspeed is 15 miles/hr, a good amount slower than the 25 miles/hr wind. You can see the extent of the air being slowed down, which gives an indication to the forces affecting the ship.
- 15 mph IsoSurface
Similarly a surface pressure plot will show where the high pressure regions, which when added up over the entire surface provide the force on that object.
- Wind Pressure Surface Plot
But of course what we really want is the actual values for the force and the torques. FloEFD can output this into excel spreadsheet tables. Below are the results from the second analysis with the cabin holes “sealed”.
| Goal Name | Unit | Value |
| Side Force | [lbf] |
264,175 |
| Rolling Torque | [lbf*ft] |
81,448 |
|
|
||
My main surprise is how low the actual force was compared to the weight of the ship. The ship weighs 256,480,000 lbs! 264,175 lbs of force is about 0.1% of the ship weight, yet it was enough to move the ship back to shore. Granted, we didn’t include any ocean current/wave effects in this analysis, which may have played a part, but as there was no data for that, I couldn’t include this into the simulation.
The more I think about it though, the more I can see that the force shouldn’t be massive. If it was, imagine how many docks would be crushed when a stiff wind blew in on a ship that was docked. Also, unlike most things that we can reference when thinking about forces, a ship isn’t on solid ground. There are no ground forces to resist this wind force. Similar to those “World’s Strongest Man” competitions where men pull airplanes or 18 wheel transport trucks, the pulling force is small compared to the size of the object being pulled, which is possible because the tires on the objects. Or how little tugboats can move ships much larger then they are.
In the end, what I take out of this analysis was that I was really surprised at the size of the wind wake behind the ship at about 1450 ft. But more then that, I was amazed at the tiny amount of wind force that moved this massive boat to shore and saved so many lives that day.
Tags: FloEFD CFD Wind Ship Cruise Boat Computational Fluid Dynamics
Is Pipe Insulation Effective?
It’s that time of the year, when the weather turns cold and people start to think about winterizing their home to reduce heating costs. Usually it takes the first winter heating bill to provide the motivation to undertake this task. With this in mind, I would like to talk about pipe insulation. Specifically, the foam wrap insulation you can find at any hardware store (http://www.homedepot.com/h_d1/N-5yc1v/R-202318552/h_d2/ProductDisplay?langId=-1&storeId=10051&catalogId=10053)
In my case, I started to look into pipe insulation for an entirely different reason. During our home inspection, we were told that much of our copper pipe was run alongside the HVAC ductwork. In some spots, the metal strapping for the duct was touching the copper, which would cause some galvanic corrosion. The simple fix would be to wrap the pipe with something to prevent this contact. When I stumbled across this foam pipe insulation for about a buck for 6 feet, I was sure I had found my answer.
Since I was going to the trouble of going into the crawlspace, I figured I should buy a bunch of these and wrap as much copper pipe as possible, because my pipe is exposed to the cold outside air in the crawlspace, so I thought there could be quite a bit of energy efficiency gained. Plus, as the master bathroom is at the opposite end of the house, I had noticed it takes a minute or two in the morning to get hot water. My new hope was to be able to shower or wash my hands in the morning without having to waste water and time waiting for it to get hot.
During the installation of these foam pipe covers, I found it difficult to get the foam insulation in different areas, whether because of T-joints, strapping or bends. I also didn’t buy enough foam, so there was still some exposed copper. This is when I started to think about running a CFD analysis on this problem. If there is some exposed copper, because of its excellent conductivity, will the heat just move to this opening, rendering all my insulation efforts moot? Did I need to make the long crawl through my crawlspace to put more pipe wrap on, or were these little portions of exposed pipe inconsequential compared to the many feet of newly insulated pipe.
For this analysis, I used our general purpose CFD tool, FloEFD. I needed some baseline numbers, so I modeled a 1 meter length of copper pipe, then I would analyze that copper pipe completely covered with the insulation (best case), then introduce a representative “gap” in that insulation for my current setup. From some research I found that hot water comes from the tank at about 50 degC, and a shower can draw about 2.5 gal/min. For the air, I wanted to simulate the worst case air temperature, which I think in the winter in my crawl space would likely be about 5 degC (above freezing for sure, though preventing pipe freezing is an added benefit of these pipe insulations).
Now we all know convection heat transfer improves with air velocity, so I wasn’t sure where to go here. From my previous crawlspace blog, where I looked at my soil water issue, I found the air speed down there was sluggish to say the least. Yet, the copper pipes running to my shower run within 1 ft of the crawl space vents, and I could feel a breeze at that location. So I decided I would need to run a no wind and a 1 m/s wind case. Below are my results.
The other main result was that the heat transfer rate was basically the same. In fact it’s slightly worse with insulation compared to without, due to the insulation having a larger surface area.
Copper Pipe, No Wind
Partial Foam Insulated Pipe, No Wind
Fully Foam Insulated Pipe, No Wind
Now, looking at the results for the with wind case, where we see a bit of a reversal on the heat loss trend. Now that forced convection is dominant, the increase in surface area for the insulated pipe doesn’t seem to be a factor. At the end of the day though, the water temperature is still pretty much the same value.
Full Foam Insulated Pipe with 1 m/s wind
It’s at this point when I started to look at this problem in a different light, as I didn’t want to have wasted money putting on insulation that isn’t effective. My new thinking is that a steady state analysis of this problem is not ideal. We will never be running the water for hours on end. My goal is to have the hot water that is in the pipe to stay hot for as long as possible so that it doesn’t take 5 minutes of running the tap to get hot water at the sink/shower. This wastes water and energy and my money, and that’s what I’m hoping gives me my ROI for my foam insulation investment.
With that, I decided I needed to simulate this as a transient analysis, starting from when the water has stopped running and timing how long it takes for the water to sufficiently cool. I figure that would be somewhere around room temperature when you would think the water isn’t “hot”.
At this point I only simulated the wind case and full/no foam, as I’m more interested in the worst case scenario (and justifying my insulation purchase).
Now this is what I’m talking about. Without insulation, the water in that pipe gets to a chilly 10 degC in about 11-12 minutes, whereas with insulation, the water doesn’t get that cold till 100 minutes. That’s a 9 times improvement for $1 per 6 feet of pipe. It’s hard to argue with that return on investment. Now, I usually shower first thing in the morning, so the water won’t stay hot throughout the night, so I’m out of luck there. For everyday washing of hands and kitchen stuff, we will definitely be wasting less water because of these pipe wraps, and that’s what matters.
Tags: CFD, FloEFD, Heat Transfer, Home Improvement, insulation, pipe