Abstract:
The power and scope of geotechnical engineering software has accelerated. The geoprofessional’s ability to perform complex calculations rapidly, and the commercialization and accessibility of artificial intelligence (AI), have created unprecedented opportunities to evaluate engineering problems and develop solutions. However, the ease of use of these tools increases the risk of decoupling the analytical modeling from the inherent variability and complexity of the natural world. Therefore, rather that replacing the engineer, human engineering judgment is more vital than ever to manage risk and create solutions! This presentation will discuss putting analytical modeling into the context of the natural world by discussing the goals of modeling and prerequisites for effective modeling. The Conceptual Site Model will be presented as a tool for improved analytical modeling. Case studies will be presented showing the risks of insufficient site understanding and the resulting numerically correct analytical results providing incorrect engineering answers for transportation projects, as well as successful use of analytical tools to understand and predict site behavior to create effective repair solutions. Attendees will leave with a better understanding of effective modeling and methods for truing up analytical results with observed site behavior, leading to better outcomes and improved risk management.