The midterm exam in my graduate course on matrix methods of structural analysis was based on a linear-elastic, geometrically linear model of what is essentially Lee's frame. I asked the students to analyze the model using two elements and treat the point load as a member load instead of defining an additional node and applying … Continue reading Making a Point Load
Tag: Frame analysis
Results of a New Challenge
After proposing a modeling challenge for linear-elastic analysis of a strongback frame, I proposed a second challenge for linear-elastic analysis of the Ziemian frame. There were eight participants in this challenge, an increase from five for the first challenge. Due to the light gravity loads on the frame, whether or not the analysis included self-weight … Continue reading Results of a New Challenge
A New Challenge
The results from a previous modeling challenge were excellent with 100% of entries correct. But before we deep dive into the dark world of modeling nonlinear structural response, let's do one more challenge with linear analysis. The frame model shown below is UP50HA from a series of low-rise industrial structures whose reliability under gravity loading … Continue reading A New Challenge
Semi-Blind Kind of Contest Results
I proposed a simplified model of a strongback frame system as a modeling challenge and five people took the bait. I am happy to report that all five computed the expected roof displacement of 0.0128 mm, give or take 0.0001 mm. Good job, everyone! Having given this problem as an OpenSeesPy assignment for a couple … Continue reading Semi-Blind Kind of Contest Results
A Semi-Blind Kind of Contest
Contests where researchers and practitioners blindly predict the response of structural systems have produced some rather interesting results. And by "interesting", I mean "all over the place". So much so, that in an effort to protect the contestants, the contest organizers rarely make the results publicly available. Nonlinear structural analysis is hard though. Even with … Continue reading A Semi-Blind Kind of Contest
