Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This first volume pertains to site characterization. The opening chapter presents an in-depth analysis of site data attributes, including the establishment of a new taxonomy of site data under “4S” (site generalizations, spatial features, sampling characteristics, and smart data) to provide a novel agenda for data-driven site characterization. Type 3 machine learning methods (disruptive value) are possible as sensors become more pervasive and more intelligent. A comprehensive overview of site characterization information is also presented with a focus on its availability, coverage, value to decision making, and challenges. The remaining 13 chapters cover databases of soil and rock properties and the application of these databases to rock socket behavior, rock classification, settlement on soft marine clays, permeability of fine-grained soils, and liquefaction among others. The databases were compiled from studies undertaken in many countries including Austria, Australia, Brazil, Canada, China, France, Finland, Germany, India, Iran, Japan, Korea, Malaysia, Mexico, New Zealand, Norway, Singapore, Sweden, Thailand, the United Kingdom, and the United States.
This volume on site characterization is a companion to the volume on geotechnical structures. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.
Chapter 6 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [(CC BY)] 4.0 license.
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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