This book is a short yet rigorous course on a new paradigm in soil mechanics, one that holds that soil deformation occurs as a simple friction-based Poisson process in which soil particles move to their final position at random shear strains. It originates from work by Casagrande’s soil mechanics group at Harvard University that found that an aggregate of soil particles when sheared reaches a "steady-state" condition, a finding in line with the thermodynamics of dissipative systems. The book unpacks this new paradigm as it applies to soils. The theory explains fundamental, ubiquitous soil behaviors and relationships used in soils engineering daily thousands of times across the world, but whose material bases so far have been unknown. These include for example, why for one-dimensional consolidation, the e-log σ line is linear, and why Cα/Cc is a constant for a given soil. The subtext of the book is that with this paradigm, the scientific method of trying to falsify hypotheses fully drives advances in the field, i.e., that soil mechanics now strictly qualifies as a science that, in turn, informs geotechnical engineering.
The audience for the book is senior undergraduates, graduate students, academics, and researchers as well as industry professionals, particularly geotechnical engineers. It will also be useful to structural engineers, highway engineers, military engineers, persons in the construction industry, as well as planetary scientists. Because its fundamental findings hold for any mass of particles like soils, the theory applies not just to soils, but also to powders, grains etc. so long as these are under pseudo-static (no inertial effects) conditions.
2 Soil shear–the phenomenological model
3 Soil shear–the physical model (part 1)
4 Soil shear–the physical model (part 2)
5 Soil shear–strain rate effects
6 Consolidation compression–the generalized model
7 One-dimensional loading–strain rate effects
8 Finite element analysis using DSSM
Appendix 1: The Poisson process for soil deformation
Appendix 2: Analytical solution to approximated DSSM model