How to automate tests on a physical model without real data

In summary, the conversation discusses the desire to create an automated integrated test for a physical model of an aircraft or car. However, without real-life data to compare the results to, it is difficult to ensure the accuracy of the model. The conversation also mentions the use of different methods, such as calculating rates and accelerations, to check the reasonableness of the outputs. It is suggested to use object-oriented languages or numerical analysis libraries for this task.
  • #1
DML
1
0
I want to code up a (physical) model of an aircraft or car, and I want to create an automated integrated test to check that the code produces reasonable and realistic results. For example, I want to check that the path taken by the aircraft or car is physical and reasonable.

However, I don't have real, physical data of an aircraft or car to test my model against.

Is it possible to check the results from my code in an automated way without having real-life data to compare it against? If not, is the only viable alternative to test hundreds of permutations of the inputs to the code and manually check the output to see if the results are reasonable? If so, what is the best way to minimise time spent on checking the errors?

If it's not possible to check the model in an automated way then how to people/companies check that their physical models are as correct as possible? What methods do they use to ensure the greatest accuracy possible?
 
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  • #2
DML said:
Is it possible to check the results from my code in an automated way without having real-life data to compare it against?
No.

DML said:
If not, is the only viable alternative to test hundreds of permutations of the inputs to the code and manually check the output to see if the results are reasonable?
I don't see that that will give you any assurance at all: all it will tell you is that your model produces outputs which you think are reasonable, not that it produces outputs that bear any relation to a real aircraft or car.
 
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  • #3
For a very rough sanity check, you can calculate the rates, accelerations, and "jerk"s (the third derivative of position) and see if they stay within reasonable limits. Airplanes of certain types will have limits, depending on the types of maneuvers that they are performing. Also, remember that gravity and its direction play important roles in the limits. Anything more accurate would require more knowledge of the airplane parameters.
 
  • #4
DML said:
I want to code up a (physical) model of an aircraft or car
Well if you model your own car, you should be able to validate it pretty well, no?
 
  • #5
Depends what language to use, in general I would advice you to use OOP(object oriented) languages (since you will mostly work with object like models), or if you rather have complex or/and various mathematical formulas and this kind of stuff then you might try Python with some numerical analysis libraries... Maybe even matlab
 

1. How can I create a physical model for testing without real data?

In order to create a physical model for testing, you can use materials that closely mimic the properties of the real data. This can include using materials with similar densities, textures, and other physical characteristics. You can also use computer-aided design (CAD) software to create a 3D model that can then be printed using a 3D printer.

2. What are some methods for automating tests on a physical model?

There are several methods for automating tests on a physical model, including using sensors and actuators to collect data and control the model, creating a computer program to simulate the model, or using robotic arms to manipulate the model. It is important to carefully plan and design the automation process to ensure accurate and reliable results.

3. How do I ensure the accuracy of my automated tests on a physical model?

To ensure accuracy, it is important to calibrate your sensors and actuators to accurately measure and manipulate the physical model. Additionally, you should validate your results by comparing them to known data or conducting physical tests alongside the automated tests. Regular maintenance and monitoring of the automation equipment can also help maintain accuracy.

4. What are some challenges of automating tests on a physical model?

Some challenges of automating tests on a physical model include the cost and complexity of the equipment and software needed, as well as the potential for errors or malfunctions. Additionally, it may be difficult to accurately replicate real-world conditions in the physical model, which can affect the validity of the results.

5. How can I use the data collected from automated tests on a physical model for further analysis?

The data collected from automated tests on a physical model can be used for further analysis by importing it into a computer program or spreadsheet for visualization and manipulation. This can help identify patterns, trends, or anomalies in the data, which can inform future testing and model improvements. Additionally, the data can be used to validate computer simulations or to compare against real-world data.

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