5.8 Models and Simulations

5.8 Models and Simulations

By Klea h

• Identify the purpose and advantages of using models and simulations.

• Recognize how abstraction is used to simplify real-world phenomena in simulations.

• Formulate, test, and refine hypotheses using models and simulations.

​Vocabulary:
models: physical or virtual representations of an object.
simulations: test a hypothesis of a situation using a model.

OBJECTIVES

Poll

"Would you rather crash a real plane to test engine failure or simulate it on a computer? Why?"

• Real plane

• Simulate it on a computer

​https://www.youtube.com/watch?v=CuPmambJU5Q

​Models allow us to create a physical or virtual representation of an object. The concept for the Etihad Towers in Abu Dhabi began as a computer-generated model using a CAD (Computer Aided Design). As the architect refines the model, they can test strength, stress, and other important factors before beginning construction.

Models can also be physical representations of real-world objects such as a scaled version of the Rotherhithe Bridge. Ultimately, models (digital or physical) enable us to represent real-world phenomena in a way that can be studied and enhanced.

​Simulations

Simulations are simplified versions of real-world systems used to test ideas or hypotheses. They help us study complex situations without the risks, costs, or time required in real life.

​Since including every real-world detail is impossible, simulations use abstractions—removing less important details—to focus on what matters most. Scientists choose which parts to include carefully to avoid bias and often use random number generators to mimic unpredictable events.

​Simulations
An example of a situation where a simulation may be useful would be to determine what would happen if an object (like a bird) flew into a jet plane mid-flight? Instead of throwing birds into jet engines, companies simulate the impact to test safety. Simulations like these allow safer, faster, and cheaper testing.

They are valuable for making decisions, refining hypotheses, and improving designs—whether you're testing planes, predicting floods, or programming robots.

​Saving Time and Money

Jet engine companies, like Rolls Royce or General Electric, can heave virtual birds into virtual engines without ruining a $35 million product or removing the “no animals were harmed” stickers from planes to iteratively design the best possible fowl-free engine.

The time required for simulations is impacted by the level of detail and quality of the models and the software and hardware used for the simulation. The time and detail it takes to create a program that models a jet engine exploding would be significantly more than a running simulation created in Scratch.

​On the Horizon

Computer scientists use information about conditions to create and study a wide range of complex systems. Analysis from the results of simulations is usually able to generate new knowledge and new hypotheses related to the phenomena being modeled. According to the National Institute of Biomedical Imaging and Bioengineering (NIBIB) (Links to an external site.), computational modeling has benefited society in many ways. Like weather forecasting and earthquake predictions, the following are just some of the examples related to computational modeling that the NIBIB is busy researching:

• Improving healing of chronic wounds

• Reducing osteoarthritis following knee surgery

• Multiscale modeling of microbial biofilms for improved treatment of antibiotic resistant infections

With continued advancement in computational models, one day you could be flying to work!