For the past 3 years, I've been actively sharing my insights/experiences on LinkedIn and many of these posts have gained significant traction. (over 100k views!)
Interestingly, a common theme among these posts is their focus on CAE and Engineering basics. With this in mind, I've gathered all of my best posts into this well-structured, value-adding article AKA - 8 Valuable Lessons in CAE.
This compilation aims to provide engineers with tips to overcome technical challenges, doubts and myths while working in the field of CAE.
Let’s begin..
Do you ever find complex CAE terms overwhelming?
Well, the solution is simple: break them down into parts & try to grasp what each term means. (Divide & rule)
Take Crash analysis, for example.
👉 We call it dynamic because it deals with moving objects where inertial effects come into play.
👉 Next, we label it as nonlinear because we capture the nonlinearity in material, geometry or contact.
👉 Lastly, we tag it as explicit because we rely on a specialized (explicit) solver to solve it.
So crash analysis is the art of tackling Nonlinear-Explicit-Dynamic problems or a way of predicting how things behave during a crash!
A strong foundation in Engineering basics is the key to addressing majority of technical problems.
Frequently, many individuals around us tend to associate CAE with software tools.
However, the reality is different.
👉 Solving real-world problems requires application of engineering basics with the help of FEA software.
👉 We use software as a medium (like calculator) to address or model complex real-world challenges.
Based on the above statements, we can define CAE in simple words as,
👉 To solve industrial problems using principles of physics with the help of FEA tools (like Hypermesh, Ansys, etc).
Many industries have started recognizing the value of CAE due to its multifaceted benefits rather than a single factor.
👉 Projections indicate that the market is estimated to reach $19.2 billion by 2031 with an estimated Compound Annual Growth Rate (CAGR) of 9.4% from 2022 to 2031. (Source: Research and Markets)
Various industries including shipbuilding, automation, space exploration, agriculture & aviation are employing it due to key benefits like:
👉 Minimize physical prototyping.
👉 Reduces development costs.
👉 Accelerate product improvement.
making CAE a valuable tool for staying competitive in today's constantly evolving world.
Recent years have witnessed a rise in partnerships, mergers & acquisitions among original CAE providers which is expected to boost its growth further. 📈
What's your opinion on the above projections? Let me know in comments.
Tools can change, develop, or upgrade over time.
New software packages emerge, offering enhanced functionalities & user experiences. 💻
As a result, #CAE professionals must continually adapt & familiarize themselves with these tools.
👉🏼 However, the true essence lies in the understanding of the underlying principles & industry-specific challenges.
This is where domain expertise shines through.
👉🏼 When we possess deep knowledge of a particular domain, we can effectively utilize FEA tools as a means to solve real-world problems.
Agree?
Time to debunk another very common misconception! 👊
CAE is not a magic wand that instantly solves everything, it's a #tool that amplifies our problem-solving capabilities.
👉 Human being’s expertise, creativity & critical thinking are essential elements that breathe life into simulations.
#CAE, at its core, empowers engineers to navigate intricate challenges, unravel design complexities & optimize solutions.
👉 It's our profound understanding of engineering principles, our ability to interpret results & our innovative thinking that turn data into actionable insights!
Remember, computers are incredible assistants, but they're only as brilliant as the minds behind them. 😎
CAE is a tool for reducing the reliance on physical prototypes, NOT eliminating physical tests entirely. 🌐🛠️
The strength of #CAE lies in its ability to provide insights & predictions about product behavior under various conditions by reducing costly iterations.
However, it can't capture every aspect of real-world complexity, making physical tests indispensable!
Physical tests, on the other hand, #validate & verify the accuracy of CAE results, ensuring that our digital models align with reality.
👉 Remember, it's not about choosing between CAE & physical tests. It's about leveraging the strengths of both to drive product design & innovation.
It's true that Simulation is a crucial aspect of CAE, but it is only a piece of the puzzle.
#CAE is a comprehensive process consisting of modeling, solving & post-processing.
👉🏼 Modeling involves creating a virtual representation of the system.
👉🏼 Solving involves applying mathematical equations to determine the system's behavior &
👉🏼 Post-processing involves analyzing the results where simulation plays an important role.
Moral of the story: Don't believe everything you hear & see.
👉🏼 Be prepared to understand the entire process rather than just a fragment of it.
🚀 Let's debunk a myth that may be holding you back!
Do you think that one needs to know a lot of #math to excel in CAE?
🔍 Well, It's time to shift the perspective!
It’s true that math is foundational to #FEA, focusing solely on complex equations & advanced calculations can often distract us from actual problem solving. 🛠️
It's all about leveraging your basic #engineering skills.
By understanding the #fundamental principles & concepts, we can efficiently analyze structural behavior, evaluate performance or optimize designs.
#CAE helps predict product behavior under different conditions, uncovering design flaws early on & streamlining the iterative process.
Ultimately, it's about making informed decisions & not getting lost in the intricacies of complex mathematics.
I hope you enjoyed this article and gained some valuable lessons along the way.
Checkout CAEPic - An eBook with Graphs, Flowcharts & Infographics that help simplify complex CAE ideas into manageable steps.
Very well written...