Project Details
Description
The tensile strength of nacre is amazing—it is about 15-times higher than the strength of its main constituent (CaCO3). The reasons have recently become well understood: 1) the nanoscale thickness of nacre's building blocks, the aragonite lamellae (or platelets), and 2) their imbricated, or staggered, nanoscale architecture. Therefore, biomimetic materials inspired by nacre are of major interest. However, their recent studies have all been deterministic, while most engineering structures and devices must be designed for the maximum failure probability one in a million (1.E-6) per lifetime, This is what must be used to set the safety factor, instead of the coefficient of variation (CoV), since a material with superior mean strength and a lower CoV can have an inferior safety at 1.E-6, depending on the shape of the probability density function (pdf) (this point has mostly been overlooked by material scientists and engineers). The 1.E-6 probability level is a challenge---it can be determined neither by histogram testing (as one would need hundred million tests!) nor by stochastic finite element methods (which can deliver only the CoV). Therefore, the complete pdf of strength must be established by a new theory, which must then be verified experiments by other than repeated tests (i.e., histogram testing).
Only two analytical models for the pdf of material strength now exist—the weakest-link chain or series coupling (yielding Weibull pdf, 1939) and the fiber bundle or parallel coupling (yielding Gaussian or normal pdf, Daniels 1945). Their extrapolations from the mean to 1.E-6 differ enormously, almost as 2:1. The proposed new idea is to approximate the nanoscale nacreous architecture by a diagonally pulled fishnet with brittle or quasibrittle links, which promises to be the third ever pdf model solvable analytically. For a brittle fishnet, the pdf is obtained as a sum of probabilities that 0, 1, 2, … links have failed prior to maximum load. For a fishnet wi
Status | Finished |
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Effective start/end date | 1/7/19 → 1/6/23 |
Funding
- Army Research Office (W911NF1910039 P00007)
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