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Smarter Geotech Starts With Digital Twins
Over the past year, I’ve come across the term “digital twin” quite a bit, a term I really like because it sounds pretty cool! So I started gathering information to see how it could be applied in geotechnical engineering. This week’s article is all about that. I’ve never applied it myself, but I hope this…
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More Data, Better Model? Not Always!
At the GeoCongress 2023 conference in LA, I had an interesting conversation with a geotechnical engineer about a Bayesian correlation model we developed. The model correlated cone penetration tip resistance with standard penetration test (SPT) blow counts in sandy soils, using 220 high-quality data points from previous research. His reaction? “Wait, just 220 points? And…
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Your Geotechnical Machine Learning Model is Probably Unusable – Here’s Why
Over the past three years, I’ve had a great opportunity to review tens of research papers applying machine learning to geotechnical problems: slope stability, soil classification, predictive modeling, you name it. And while I genuinely appreciate the effort researchers put into these studies, I’ve noticed a pattern: Many of them are just chasing the AI/ML…
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MUSIC-3X: A Simple Way to Summarize Geotechnical Data Challenges
Data quality is everything when it comes to machine learning or data-driven applications in geotechnical engineering (or any field, actually). No matter how advanced your model is, if the data isn’t solid, the results won’t be either. That’s why I believe the first step in applying AI to geotechnical problems is to truly understand the…
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Will AI Replace Geotechnical Engineers?
It was August 2021 when I first joined the PhD program at UC. Apart from face masks, all grad students were talking about Python, programming, and machine learning—and I had no idea what they meant. Coming from traditional geotechnical field work with a heavily experimental research background, I thought civil engineering was purely classical science.…