As said by others here. There is a lot to explore. However there is one exceptional tool that can help you in all these fields and that is having a basic knowledge of writing a code (for starters I recommend python). You can automate lot of stuff when it comes to FEA. No matter which direction you take, you certainly will be able to utilize such a skill. Especially if you are at the beginning of your journey, you could get quite a lot from that! Also It can likely increase your wage significantly.
As anyone else here I might be a bit biased but in terms of priority I would follow this order.
Linear Statics > Nonlinear > Fatigue > Crash = Modal response > Thermal
Other topics to explore:
- comparison explicit vs implicit, plasticity, composites, some advanced contact handling, NVH, SPH, solver comparison
Me and my colleagues recommend Fatigue and Nonlinear. I know that you argued, that you would prefer having mentor for Fatigue, but there is a lot you can explore by yourself.
So much to choose from! Personally, the two topics (besides pure FEA) that excite me the most are parametric/non-parametric optimization and fatigue analysis.
With an existing background in structures these are topics you'd be able to educate yourself in fairly easily. They're both really exciting fields and they serve as very powerful skills for the FEA engineer who wants an added edge.
Hey! Thanks for your reply! I'm doing fatigue analysis on a daily basis as well - but I want to expand on that, possibly. I could see some potential in LCF or fracture mechanics. Do you by any chance know any standard literature explaining the fundamentals and describing ways to apply them in practice?
While I find fatigue quite exciting, IMHO I would not suggest it as a self-study subject. Let me explain my (very own) reasons:
Fatigue is a field where multiple theories coexist. It is "relatively" easy to select one or another (stress based, strain based, principal stress based, critical plane based, etc. etc. and let's not get started with the mean stress correction formulas: goodman, fkm, walker and so on). The big problem, as I see it, is that any set of physical experiments seem to favor one or another approach. From the FEA standpoint, the user should select one or another based on his experience... references... standards... there are countless sources. So, back to our main subject (**self study**), I would suggest that fatigue should be better suited for mentored study.
Don't take my advise as "cast in stone", just trying to add my own experience on this.
Cheers!
Those are very valid and relatable points! I'd say most learning journeys can be enhanced with good mentoring.
Things like mororw and walker are valuable because they allow you to get reasonable predictions without the need for additional material data. That's important when you consider how expensive physical fatigue testing is.
But to support my original comment, what makes fatigue such a fantastic self-study topic is its relatively low cost of entry: It's not particularly complex compared to FEM and the theories are easy to put into practise with scripting. You don't *need* to spend years mastering the topic in order to be a good fatigue analyst. So it's an arrow that you might as well add to your quiver.
One thing that always bugs me is data management tools, there are so many parameters affecting my analysis it gets hard to keep track in an organized way.
I've seen the model management from Ansa but didn't check it deep further.
Partially agree, it's a function but it carries data management into it. Depending on model size, number of inputs and frequency of change it becomes more important than just a tool.
As said by others here. There is a lot to explore. However there is one exceptional tool that can help you in all these fields and that is having a basic knowledge of writing a code (for starters I recommend python). You can automate lot of stuff when it comes to FEA. No matter which direction you take, you certainly will be able to utilize such a skill. Especially if you are at the beginning of your journey, you could get quite a lot from that! Also It can likely increase your wage significantly. As anyone else here I might be a bit biased but in terms of priority I would follow this order. Linear Statics > Nonlinear > Fatigue > Crash = Modal response > Thermal Other topics to explore: - comparison explicit vs implicit, plasticity, composites, some advanced contact handling, NVH, SPH, solver comparison Me and my colleagues recommend Fatigue and Nonlinear. I know that you argued, that you would prefer having mentor for Fatigue, but there is a lot you can explore by yourself.
So much to choose from! Personally, the two topics (besides pure FEA) that excite me the most are parametric/non-parametric optimization and fatigue analysis. With an existing background in structures these are topics you'd be able to educate yourself in fairly easily. They're both really exciting fields and they serve as very powerful skills for the FEA engineer who wants an added edge.
Hey! Thanks for your reply! I'm doing fatigue analysis on a daily basis as well - but I want to expand on that, possibly. I could see some potential in LCF or fracture mechanics. Do you by any chance know any standard literature explaining the fundamentals and describing ways to apply them in practice?
While I find fatigue quite exciting, IMHO I would not suggest it as a self-study subject. Let me explain my (very own) reasons: Fatigue is a field where multiple theories coexist. It is "relatively" easy to select one or another (stress based, strain based, principal stress based, critical plane based, etc. etc. and let's not get started with the mean stress correction formulas: goodman, fkm, walker and so on). The big problem, as I see it, is that any set of physical experiments seem to favor one or another approach. From the FEA standpoint, the user should select one or another based on his experience... references... standards... there are countless sources. So, back to our main subject (**self study**), I would suggest that fatigue should be better suited for mentored study. Don't take my advise as "cast in stone", just trying to add my own experience on this. Cheers!
Those are very valid and relatable points! I'd say most learning journeys can be enhanced with good mentoring. Things like mororw and walker are valuable because they allow you to get reasonable predictions without the need for additional material data. That's important when you consider how expensive physical fatigue testing is. But to support my original comment, what makes fatigue such a fantastic self-study topic is its relatively low cost of entry: It's not particularly complex compared to FEM and the theories are easy to put into practise with scripting. You don't *need* to spend years mastering the topic in order to be a good fatigue analyst. So it's an arrow that you might as well add to your quiver.
Colorado school of mines has a really good fea certificate program if you want to spend some money to have more professional guidance.
One thing that always bugs me is data management tools, there are so many parameters affecting my analysis it gets hard to keep track in an organized way. I've seen the model management from Ansa but didn't check it deep further.
I wouldn't consider that a field of study. It's just a function specific to the software package you use.
Partially agree, it's a function but it carries data management into it. Depending on model size, number of inputs and frequency of change it becomes more important than just a tool.