Learn Python For Mechanical Engineers – Posted by IIMT College Group on Jul 8, 2022 Why is Python important for mechanical engineering students?
It is a common myth that mechanical engineering does not involve any kind of computer interface. Even mechanical engineers hate computer programming and miss a lot of opportunities. As we move toward a future of electric cars, autonomous vehicles, and automation, the next era of mechanical, aerospace, and automotive engineering requires an understanding of how to integrate mechanical engineering concepts into computer languages to simulate ideas. or it can be made faster automatically. Python is a very simple and efficient programming language. Can solve complex problems in seconds. Even if you are a mechanical/automotive engineer, you will still need Python in most cases. Areas where Python is used include, but are not limited to, mechanical engineering.
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The most popular python program for quantitative analysis. If it is linear math problems with ODE/PDE, it takes more time to solve the problem analytically. In mechanical engineering, there are often boundary conditions that make solving numerical analysis problems difficult.
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Let’s say you’re trying to find the pressure difference across a pipe where a liquid is flowing. It will just take forever to solve the problem, but it will be very difficult to find the exact value or determine the difference on the graph. With a programming language, you can solve such a problem in seconds and get a simulation of the image at the same time.
Python can be used to solve old thermodynamics problems. Whether your problem is related to chemical kinetics or fluid dynamics, you can write code to solve the problem and save time in the field of computational fluid dynamics, Python has a great program. To simulate problems in CFD software, you will need to write your scripts in a programming language such as MATLAB/Python.
Python is used in other areas of mechanical engineering such as vibration, dynamic motion, simulation and model engineering. The automotive and automotive industries use Python to automate tasks. Even if the text is written in another programming language, rewrite it in Python before automation, because it is the most common language and communication between branches and code.
If you look at the job boards of companies like Tesla, Mercedes-Benz, Boeing, they hire and hire mechanical engineers who can code.
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In today’s era of competitive market, the customer is almost aware of their basic requirements and luxury needs. The automation of mechanical and industrial production is gaining significant changes. Read more… There is a stereotype that mechanical engineers (MEs) try to avoid programming as much as possible. If we can’t automate it in Excel, let’s avoid it altogether. Programming often takes a back seat (or no seat) to the main focus of the ME during day-to-day work. Much of ME thinking is focused on machine design, dynamics, and material science, not programming.
However, what we often don’t realize is that learning to code can help us work smarter instead of harder, especially in the world of IoT development. Avoiding programming because you don’t like programming or because you’re afraid you’re not good enough will hurt you in the long run.
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Fortunately, programming languages are accessible enough that you can learn the basics very quickly. Python is one of them, and for me it has become an invaluable tool for various mechanical engineering tasks.
So why would an ME want to learn to program, or more specifically, learn to program in Python?
In 2019, Paul Krill of InfoWorld magazine wrote that Python “received the highest score on the monthly Tiobe index of programming language popularity”.
“On its current trajectory, Python could overtake Java and C to become the most popular indexing language in the next three to four years,” notes Tiobe.
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Given this explosion in popularity, more and more employers are adding Python to their list of required skills. However, that is the only reason to learn this skill. Python is easy to learn. Another important reason is the limitless possibilities that a programming language like Python can give you.
Python opens the door to faster and more streamlined workflows, can simulate large amounts of data, and most importantly, automate tedious and tedious tasks to complete in seconds.
What exactly can you do with Python as a mechanical engineer? One of the most useful things you can do is perform quantitative analysis.
With the many packages that come with Python, such as NumPy and SciPy, you can use built-in functions to perform numerical analysis faster and easier than ever before. With SciPy, you can integrate, plot, and even dilute without doing manual calculations. It saves a lot of time.
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With a little initial setup, you can use Python to perform all the calculations you need in an instant.
Another example you can do is simple finite element analysis. Numerical analysis of thermodynamics is a great example; With the PYro tool, we can easily calculate “the most common thermodynamic properties from temperature and pressure, such as density, enthalpy, entropy, internal energy, molecular weight, specific heat, specific heat ratio, and specific volume.”
Computational fluid dynamics lends itself well to Python programming. PyCFD uses the boundary element method to write and solve partial differential equations, calculate the volume of fluids using the Navier-Stokes equation, and solve partial differential equations with boundary values.
Overall, this provides three main advantages to the mechanical engineers in your organization. First, remember that just as you can use your co-workers’ code, other people in the company can use your script after you’ve written it. This will save everyone time and allow for more effective teamwork.
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Second, we can further enhance automation by building custom features in a platform like Onshape. Essentially, it allows us to quickly and easily create custom functions to use in our projects. This includes custom beams, airfoils, spur gears, beam drivers and wires.
Finally, Python allows us to automate large calculations that are too complex or time-consuming. The language is very good at floating point arithmetic and can handle up to 17 digits. Not surprisingly, Python forms the basis of math-intensive machine learning (ML) frameworks such as PyTorch.
There is a reason why Excel and Google Sheets are so widely used by businesses. Spreadsheets have many easy-to-use features, and new users are quick to implement large projects in these programs.
However, Excel and other programs have their limitations. Excel suffers when the data is large. Python, on the other hand, is a scientific tool for big data work.
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Python’s high-level features not only speed up code development and make problem-solving more intuitive, but the scientific community already has rich libraries ready to use.
These include science packages like NumPy and SciPy, which we mentioned earlier, but this is only the tip of the iceberg.
Matplotlib is a 2D graphics library ideal for scientific and engineering work, while SymPy is specifically designed for symbolic computing tasks, from calculus to quantum physics.
When we compare MATLAB with Python, the difference also becomes clear. Both are translation languages, but there are technical and philosophical differences between them.
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Aside from subtleties like MATLAB and Python syntax changes, Python has a much more flexible and active support community than MATLAB, and has much of the same functionality. An exception is MATLAB’s Simulink for model-based simulation and modeling.
These technical details are largely due to different development approaches: MATLAB is proprietary and closed-source software, while Python is an open-source project supported by hundreds of developers.
This ultimately boils down to several key advantages in favor of Python. First, Python’s versatility allows us to do more with less. The same application integrates functions from multiple libraries, simplifying workflows and requiring less user input. We all know what happens when a business has too many spreadsheets. Programming in Python reduces this complexity by allowing us to integrate much of this work into a single, unified platform.
Computer programming may not be our primary focus as mechanical engineers, but in today’s digital world, these skills are critical. Learning a friendly language like Python can pay huge dividends.