Posts Tagged ‘CFD’

Scanning radiation flux with moving sensors in Energy2D

July 13th, 2014 by Charles Xie
Figure 1: Moving sensors facing a rectangular radiator.
The heat flux sensor in Energy2D can be used to measure radiative heat flux, as well as conductive and convective heat fluxes. Radiative heat flux depends on not only the temperature of the object the sensor measures but also the angle at which it faces the object. The latter is known as the view factor.

In radiative heat transfer, a view factor between two surfaces A and B is the proportion of the radiation which leaves surface A that strikes surface B. If the two surfaces face each other directly, the view factor is greater than the case in which they do not. If the two surfaces are closer, the view factor is greater.

Figure 2: Rotating sensors inside and outside a ring radiator.
To conveniently visualize the effect of a view factor, Energy2D allows you to attach a heat flux sensor to a moving or rotating particle, with a settable linear or angular velocity. In this way, we can set up sensors to automatically "scan" the field of radiation heat flux like a radar.

Figure 1 shows a moving sensor and a rotating sensor, as well as the data they record. A third sensor is also placed to the right of an object that is being heated by the radiator. This object has an emissivity of one so it also radiates. Its radiation flux is recorded by the third sensor whose data shows a slowly increasing heat flux as the object slowly warms up.

As an interesting test case, Figure 2 shows two rotating sensors, one placed precisely at the center of a ring radiator and the other outside. The almost steady line recorded by the first sensor suggests that the view factor at the center does not change, which makes sense. The small sawtooth shape is due to the limitation of discretization in our numerical simulation.

Multiphysics simulations of inelastic collisions with Energy2D

July 4th, 2014 by Charles Xie
Figure 1. Mechano-thermal simulation of inelastic collision.
Many existing simulations of inelastic collisions show the changes of speeds and energy of the colliding objects without showing what happens to the lost energy, which is often converted into thermal energy that spreads out through heat transfer. With the new multiphysics modeling capabilities, the Energy2D software can show the complete picture of energy transfer from the mechanical form to the thermal form in a single simulation.

Figure 2. Thermal marks left by collisions.
Figure 1 shows the collisions of three identical balls (mass = 10 kg, speed = 1 m/s) with three fixed objects that have different elasticities (0, 0.5, and 1). The results show that, in the case of the completely inelastic collision, all the kinetic energy of the ball (5 J) is converted into thermal energy of the rectangular hit object (at this point, the particles in Energy2D do not hold thermal energy, but this will be changed in a future version), whereas in the case of completely elastic collision, the ball B1 does not lose any kinetic energy to the hit object. In the cases of inelastic collisions, you can see the thermal marks created by the collisions. The thermometers placed in the objects also register a rise of temperatures. This view resembles infrared images of floors taken immediately after being hit by tennis balls.

Figure 3. Collisions in Energy2D.
Energy2D supports particle collisions with all the 2D shapes that it provides: rectangles, ellipses, polygons, and blobs. Figure 2 shows the thermal marks on two blobs created by a few bouncing particles. And Figure 3 shows another simulation of collision dynamics with a lot of particles bouncing off complex shapes (boy, it took me quite a while in this July 4 weekend to hunt down most of the bugs in the collision code).

The multiphysics functionality of Energy2D is an exciting new feature as it allows more realistic modeling of natural phenomena. Even in science classrooms, realism of simulations is not just something that is nice to have. If computer simulations are to rival real experiments, it must produce not only the expected effects but also the unexpected side effects. Capable of achieving just that, a multiphysics simulation can create a deep and wide learning space just like real experiments. For engineering design, this depth and breadth are not options -- there is no open-endedness without this depth and breadth and there is no engineering without open-endedness.

Fireplaces at odd with energy efficiency? An Energy2D simulation

January 18th, 2014 by Charles Xie
In the winter, a fireplace is the coziest place in the house when we need some thermal comfort. It is probably something hard to remove from our living standards and our culture (it is supposed to be the only way Santa comes into your house). But is the concept of fireplace -- an ancient way of warming up a house -- really a good idea today when the entire house is heated by a modern distributed heating system? In terms of energy efficiency, the advice from science is that it probably isn't.

Figure 1. A fire is lit in the fireplace.
When the wood burns, a fireplace creates an updraft force that draws the warm air from the house to the outside through the chimney. This creates a "negative pressure" that draws the cold air from the outside into the house through small cracks in the building envelope. This is called the stack effect. So while you are getting radiation heat from the fireplace, you are also losing heat in the house at a faster rate through convection. As a result, your furnace has to work harder to keep other parts of your house warm.

Figure 2. No fire.
Our Energy2D tool can be used to investigate this because it can simulate both the stack effect and thermostats. Let's just create a house heated by a heating board on the floor as shown in the figures in this article. The heating board is controlled by a thermostat whose temperature sensor is positioned in the middle of the house. A few cracks were purposely created in the wall on the right side to let the cold air from the outside in. Their sizes were exaggerated in this simulation.

Figure 1 shows the duty cycles of the heating board within two hours when the house was heated from 0 °C to 20 °C with a fire lit in the fireplace. A heating run is a segment of the temperature curve in which the temperature increases, indicating the house is being heated. In our simulation, the duration of a heating run is approximately the same under different conditions. The difference is in the durations of the cooling runs. A more drafty house tends to have shorter cooling runs as it loses energy more quickly. Let's just count those heating runs. Figure 1 shows that 15 heating runs were recorded in this case.

Figure 2 shows the case when there was no fire in the fireplace and the fireplace door was closed. 13 heating runs were recorded in this case.

What does this result mean? This means that, in order to keep the house at 20 °C, you actually need to spend a bit more on your energy bill when the fireplace is burning. This is kind of counter-intuitive, but it may be true, especially when you have a large drafty house.

Figure 3. In a house without cracks...
How do we know that the increased energy loss is due to the cracks? Easy. We can just nudge the window and the wall on the right to close the gaps. Now we have a tight house. Re-run the simulation shows that  only 11 heating runs were recorded (Figure 3). In this case, you can see in Figure 3 that the cooling runs lasted longer, indicating that the rate of heat loss decreased.

Note that this Energy2D simulation is only an approximation. It does not consider the radiation heat gain from the fireplace. And it assumes that the fire would burn irrespective of air supply. But still, it illustrates the point.

This example demonstrates how useful Energy2D may be for all precollege students. In creating this simulation, all I did is to drag and drop, change some parameters, run the simulation, and then count the heating runs. As simple as that, this tool could be a game changer in science and engineering education in high schools or even middle schools. It really creates an abundance of learning opportunities for students to experiment with concepts and designs that would otherwise be inaccessible. Similar experiences are currently only possible at college level with expensive professional software that typically cost hundreds or even thousands of dollars for just a single license. Yet, according to some of our users, our Energy2D rivals those expensive tools to some extent (I would never claim that myself, though).

Season’s greetings from Energy2D

December 14th, 2013 by Charles Xie
I have been so swamped in fund raising these days that I haven't been able to update this blog for more than two months. Since it is the time of the year again, I thought I should just share a holiday video made by Matthew d'Alessio, a professor at California State University Northridge, using our signature software Energy2D.

The simulator currently attracts more than 5,000 unique visitors each month, a number that probably represents a sizable portion of engineering students studying the subject of heat transfer on the planet. Over the past year, I have received a lot of encouraging emails from Energy2D's worldwide users. Some of them even compared it with well-known engineering programs. Franco Landriscina at the University of Trieste has written Energy2D into his recent Springer book "Simulation and Learning: A Model-Centered Approach."

I am truly grateful for these positive reactions. I want to say "Thank You" for all your nice words. There is nothing more rewarding than hearing from you on this fascinating subject of fluid dynamics and heat transfer. Rest assured that the development of this program will resume irrespective of its funding. In 2014, I hope to come up with a better radiation solver, which I have been thinking for quite a long time. It turns out that simulating radiation is much more difficult than simulating convection!

Here is a tutorial video in Spanish made by Gabriel Concha.