The Importance of Physical Modeling in Engineering: Insights from an EE Student

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SUMMARY

The discussion emphasizes the critical role of physical modeling in engineering, particularly in electrical engineering (EE) and mechanical systems. Participants highlighted that while theoretical modeling is essential, empirical testing and physical prototypes are vital for ensuring design safety and performance. The importance of physical models varies by system complexity, with simpler models often sufficing for less critical applications. Ultimately, effective physical modeling enhances project outcomes and aligns with industry standards.

PREREQUISITES
  • Understanding of empirical testing methodologies in engineering
  • Familiarity with theoretical modeling concepts
  • Knowledge of design standards in engineering
  • Experience with prototype development and testing
NEXT STEPS
  • Research best practices for empirical testing in engineering design
  • Explore advanced theoretical modeling techniques in electrical engineering
  • Learn about design standards and safety regulations in engineering projects
  • Investigate the use of simulation software for physical modeling
USEFUL FOR

Engineering students, electrical engineers, mechanical engineers, and professionals involved in design and prototyping processes will benefit from this discussion.

Number2Pencil
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I was hoping to get some input from someone in an engineering field about how important physical modeling is to you.

for example: how long do you spend on it, how closely does the model resemble the final project, do you think it's vital or a waste of time, or does your place of business even do it?

I'm asking because I'm in an EE class that is supposed to resemble an actual job. We're making a autonomous robot and he was VERY displeased with our physical model...so it got me wondering
 
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Number2Pencil said:
I was hoping to get some input from someone in an engineering field about how important physical modeling is to you.

for example: how long do you spend on it, how closely does the model resemble the final project, do you think it's vital or a waste of time, or does your place of business even do it?

I'm asking because I'm in an EE class that is supposed to resemble an actual job. We're making a autonomous robot and he was VERY displeased with our physical model...so it got me wondering

I spend a significant amount of time theoretically modeling systems for either operational capabilities or design specifications but none on physical models. However we do verify the theoretical model by empirical testing once the system is built.

I suppose it would depend on what system you are modelling though.

CS
 
IMO physical model is important to make a system works better. If one just want the system works, then sometimes very simple model reduces the design time. Empirical testing on prototype can be a quick way to tune the performance of a system. But it would be hard to tune if the system has many parameters and optimal performance is required. Anyway it depends on what specific system you are modeling.
 
luben said:
Empirical testing on prototype can be a quick way to tune the performance of a system. But it would be hard to tune if the system has many parameters and optimal performance is required.

Empirical testing is required by most design standards to ensure the design is appropriate (safe) - not to fine tune it. However, fine tuning may be a coincidental benefit.

CS
 
We spend a lot of time and effort on our engine models. They are first used to get the thermodynamic cycle operational and make sure it is even feasible. Once the actual engine is being worked, we update the model based on test results. Once that is done, we use those models to help potential customers determine if the engine will suit their needs from an aircraft performance standpoint. They are also used to answer a myriad of other questions that eventually pop up. These models are very important to our company.

As far as component models and subsystems, I guess it all depends on the criticality of the model. A lot of times a simple model is sufficient.
 

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