Difference between revisions of "Team:Aix-Marseille/Model"
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This list is not complete and we hope to test the impact on our trap's efficiency of every parameters involved in its functioning (like the diffusion coefficient,...). | This list is not complete and we hope to test the impact on our trap's efficiency of every parameters involved in its functioning (like the diffusion coefficient,...). | ||
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| − | Unfortunately, among the three parameters we firstly wanted to try, only one have been successfully ad to the program, because of | + | Unfortunately, among the three parameters we firstly wanted to try, only one have been successfully ad to the program, because of the complexity of the mathematical model and its solution, or because of (a lack of information) </p> |
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<p>Our program had to model the diffusion of pheromones through a room containing furnitures, and model the behaviour of bedbugs against the pheromones, with a model describing their deaths (caused by the fungus). This model will have to manage a lot of variables, from the diffusion to the bedbugs's moves and the interactions between all this variables. Because of the complexity of the phenomena, building the program by describing every actions occuring in our model would be too difficult. Fortunately for us, we could use the language Netlogo, which allowed us to use agent-based modeling, a type of modeling particularly efficient in term of complex system modeling. | <p>Our program had to model the diffusion of pheromones through a room containing furnitures, and model the behaviour of bedbugs against the pheromones, with a model describing their deaths (caused by the fungus). This model will have to manage a lot of variables, from the diffusion to the bedbugs's moves and the interactions between all this variables. Because of the complexity of the phenomena, building the program by describing every actions occuring in our model would be too difficult. Fortunately for us, we could use the language Netlogo, which allowed us to use agent-based modeling, a type of modeling particularly efficient in term of complex system modeling. | ||
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| + | Agent-based modeling allows us to define the behavior of the agents (the diffusing molecules, the bedbugs,...) by defining the interactions between those agents. Thanks to this, modeling of systems with multiples agents are interacting with every other agents is simpler. | ||
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Revision as of 11:40, 15 October 2018
Modeling
Modeling
Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.
Gold Medal Criterion #3
Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.
The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
Please see the 2018 Medals Page for more information.
Best Model Special Prize
To compete for the Best Model prize, please describe your work on this page and also fill out the description on the judging form. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
Inspiration
Here are a few examples from previous teams:
Why modeling ? Descriptions of our goals
As our project was growing, we understood the importance of modeling our solution. Indeed, even if we had some laboratory experiments to test our traps, it would have take time to be able to start them. A model run on a computer would have allowed us to begin those test earlyier, and make them quicker. This type of model would also have grant us more iteration of these experiments. All these advantages would have allowed us to start statistic tests earlyer, and in the end, would have helped us to build a better program. For all these reasons, modeling our project was one of our top priority.
When we begun, we various parameters to test :
- The effect of furnitures Our trap will most likely be used in a room with furnitures (like a bedroom for exemple). But even if we have a formula to model the diffusion of gases (the Fick's laws of diffusion), this model doesn't take into account the possible obstacles, which may have an impact on diffusion, and so on the efficiency of our traps.
- The effect of air flows Since we will spread our traps in an inhabited room, it may have openings to another room or even outside. Those openings could favour the creation of air-flows, which could have an impact on diffusion, and so on the efficiency of our traps
- The effect of the “packing” mode of the phermones and fungus During the development of our project, we had the opportunity to choose between two types of "packing" modes for the pheromones and the fungus. One consisted in an opened box and the other was . Since those two methods are completely different, it may have had an impact on the efficiency of our traps.
This list is not complete and we hope to test the impact on our trap's efficiency of every parameters involved in its functioning (like the diffusion coefficient,...).
Unfortunately, among the three parameters we firstly wanted to try, only one have been successfully ad to the program, because of the complexity of the mathematical model and its solution, or because of (a lack of information)
How did we model ?
Our program had to model the diffusion of pheromones through a room containing furnitures, and model the behaviour of bedbugs against the pheromones, with a model describing their deaths (caused by the fungus). This model will have to manage a lot of variables, from the diffusion to the bedbugs's moves and the interactions between all this variables. Because of the complexity of the phenomena, building the program by describing every actions occuring in our model would be too difficult. Fortunately for us, we could use the language Netlogo, which allowed us to use agent-based modeling, a type of modeling particularly efficient in term of complex system modeling.
Agent-based modeling allows us to define the behavior of the agents (the diffusing molecules, the bedbugs,...) by defining the interactions between those agents. Thanks to this, modeling of systems with multiples agents are interacting with every other agents is simpler.