OpenSees contains sophisticated solution algorithms and element and constitutive models for simulating the nonlinear response of structural and geotechnical systems to natural and human-made hazards.
But sometimes these sophisticated models are put to less than sophisticated use. I’ve been kicking this idea around in my head for a while, but what xykademiqz wrote in a recent post perfectly explains the sentiment:
… we increasingly see very sophisticated simulation tools used as blunt instruments, simulating everything but explaining nothing.
Simulating Everything but Explaining Nothing, or “Seen” if I may, using the same capitalization as “Sees” in OpenSees. The past participle to the present tense!
If you saw the Google Scholar alerts I receive every few days for new citations to OpenSees, you’d know what Seen is all about. Fragility functions for structural systems that will never be built. Optimal designs that will never be constructible. Parametric studies on properties that do not matter. High performance computing on bloated models. Machine learning algorithms that produce obvious results. The list goes on, populated with too many names to name.
And the writing that accompanies those outcomes explains nothing about either the simulations or the nothing. Nobody wants to read that sh!t.
Don’t get me wrong though. Not all of OpenSees is Seen.
But, what can we do about the Seen? Can those layers of OpenSees ever be un-Seen, i.e., generating useful and explainable insights instead of the unexplainable everything? What do you think?

Absolutely. Many research results, even outside the scope of OpenSees, are gradually becoming “SEEN”, I feel! I think, the culture of ‘Publish or Perish” is also one culprit for this scene. I often wonder nowadays, are we loosing the “physical feel” of the engineering problem being handled?
Sorry, if I have overstated.. But that’s how I feel quite a few times these days.
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These ‘Seen’ research, IMO, would probably be a great introduction/training for the graduate student that ‘mostly’ writes these paper. The optimal design they researched might never be built, but hopefully the training they receive (proper numerical modelling, optimization algorithm etc) would be beneficial for their career.
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Good point, but a paper summarizing basic training is unnecessary.
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