Search arXiv⌕ Search

arXiv · cond-mat/0006061

Pattern formation and selection in quasi-static fracture

Abstract

Fracture in quasi-statically driven systems is studied by means of a discrete spring-block model. Developed from close comparison with desiccation experiments, it describes crack formation induced by friction on a substrate. The model produces cellular, hierarchical patterns of cracks, characterized by a mean fragment size linear in the layer thickness, in agreement with experiments. The selection of a stationary fragment size is explained by exploiting the correlations prior to cracking. A scaling behavior associated with the thickness and substrate coupling, derived and confirmed by simulations, suggests why patterns have similar morphology despite their disparity in scales.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kwan-tai Leung, Zoltan Neda. 2000-06-05. Pattern formation and selection in quasi-static fracture. https://doi.org/10.1103/physrevlett.85.662

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Nonuniform asymmetric exclusion process: Stationary densities and domain walls

We compute the stationary densities in totally asymmetric exclusion processes (TASEP) with open boundary conditions and spatially nonuniform hopping rates. The stationary densities in the low and and high density phases can be discontinuous, only when the space-dependent hopping rate is spatially discontinuous. In contrast, the stationary density profile in the maximal current phase can be discontinuous, even when the space-dependent hopping rate is continuous. We further investigate the domain walls, which are delocalised with complex shapes. In striking contrast to a delocalised domain wall (DDW) in an open, uniform TASEP, these DDWs can also form at the transitions between the low or high density phases and maximal current phase, and can cover the entire TASEP channel or a part of it, depending upon the specific forms of the site-dependence of the hopping rates and the associated phase transitions. We calculate their envelopes, which are curved lines, revealing their dependence on the spatial nonuniformity of the hopping rates. The phase diagrams in the plane of the control parameters show universal topology. The associated phase transitions are explored, which can be different from their counterparts in an open uniform TASEP.

cond-mat.stat-mech↗

A Human-AI Theorem Connecting Spontaneous and Field-Induced Mechanisms of Collective Behavior in One Dimension

Can an artificial intelligence (AI) generate a scientific hypothesis outside a human collaborator's active hypothesis space (AHS), and can human-AI research be organized to make such breakthroughs more likely? We document such a case while proving a theorem that connects two basic organizing mechanisms of statistical physics: collective behavior arising in zero field from competing interactions and that induced or controlled by an external field. A zero-field $O(n)$-vector open chain with arbitrary inhomogeneous nearest- and next-nearest-neighbor interaction functions $U_i(S_i\cdot{S}_{i+1})$ and $V_i(S_i\cdot{S}_{i+2})$ is microscopically, via a temperature-independent mapping at the Hamiltonian level, equivalent to a simpler $O(n)$ open chain with nearest-neighbor interaction $V_i(\boldsymbolσ_i\cdot\boldsymbolσ_{i+1})$ and axial single-spin potential $U_i(σ_i^z)$ for every integer $n\ge1$ and every system size $L\ge1$. The homogeneous linear specialization maps the foundational frustrated $J_1$-$J_2$ model onto the canonical $J$-$h$ field model---with $n=1,2,3$ being the Ising, XY, and Heisenberg classical spin models, respectively; the theorem resolved a longstanding challenge for $n=3$ published in 1990. Its proof was done with an AI-synthesized recursive Householder moving frame and understood via a human-recognized hidden reciprocity. An analogous theorem holds when the continuous $O(n)$ spins are replaced by the $q$-state Potts spins, implying a closed-form exact solution of the $J_1$-$J_2$ standard Potts open chain for every $q\ge2$ and every $L\ge1$. The emergence of these theorems from a human-AI co-development framework suggests that sustained AI involvement throughout a systematic research program may incubate autonomous scientific breakthroughs and make aspects of the discovery process experimentally testable.

cond-mat.stat-mech↗

Intermittency in Wind-Driven Fires

We construct a wind-driven forest-fire model in one dimension in which a fire can jump gaps between trees to ignite disjoint downwind forests. The size of a gap that a fire can jump depends on the fire intensity, which increases as the fire propagates through trees and diminishes as the fire jumps gaps. Trees grow on empty sites at rate $r$ and lightning strikes each site with rate $f$. When $f\ll r/L$, where $L$ is the system length, lightning is sufficiently rare that quasi-deterministic dynamics arises where all trees are consumed when a lightning-induced fire occurs. For $f\gg L^{-μ}$ with $μ\approx 0.8$, lightning is sufficiently frequent that a steady state is reached, but with unexpected behaviors for the forest- and gap-size distributions. Intermittency arises in between these regimes, with coexisting temporal domains of deterministic and chaotic dynamics.

cond-mat.stat-mech↗