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W I Newman

Publications and source records attributed to W I Newman.

6 recordsLinked to original sources

Time-dependent fiber bundles with local load sharing.

Fiber bundle models, where fibers have random lifetimes depending on their load histories, are useful tools in explaining time-dependent failure in heterogeneous materials. Such models shed light on diverse phenomena such as fatigue in structural materials and earthquakes in geophysical settings. Various asymptotic and approximate theories have been developed for bundles with various geometries and fiber load-sharing mechanisms, but numerical verification has been hampered by severe computational demands in larger bundles. To gain insight at large size scales, interest has returned to idealized fiber bundle models in 1D. Such simplified models typically assume either equal load sharing (ELS) among survivors, or local load sharing (LLS) where a failed fiber redistributes its load onto its two nearest flanking survivors. Such models can often be solved exactly or asymptotically in increasing bundle size, N, yet still capture the essence of failure in real materials. The present work focuses on 1D bundles under LLS. As in previous works, a fiber has failure rate following a power law in its load level with breakdown exponent rho. Surviving fibers under fixed loads have remaining lifetimes that are independent and exponentially distributed. We develop both new asymptotic theories and new computational algorithms that greatly increase the bundle sizes that can be treated in large replications (e.g., one million fibers in thousands of realizations). In particular we develop an algorithm that adapts several concepts and methods that are well-known among computer scientists, but relatively unknown among physicists, to dramatically increase the computational speed with no attendant loss of accuracy. We consider various regimes of rho that yield drastically different behavior as N increases. For 1/2< or =rho< or =1, ELS and LLS have remarkably similar behavior (they have identical lifetime distributions at rho=1) with approximate Gaussian bundle lifetime statistics and a finite limiting mean. For rho>1 this Gaussian behavior also applies to ELS, whereas LLS behavior diverges sharply showing brittle, weakest volume behavior in terms of characteristic elements derived from critical cluster formation. For 0<rho<1/2, ELS and LLS again behave similarly, but the bundle lifetimes are dominated by a few long-lived fibers, and show characteristics of strongest link, extreme value distributions, which apply exactly to rho=0.

Journal Article↗

Exactly soluble hierarchical clustering model: inverse cascades, self-similarity, and scaling.

We show how clustering as a general hierarchical dynamical process proceeds via a sequence of inverse cascades to produce self-similar scaling, as an intermediate asymptotic, which then truncates at the largest spatial scales. We show how this model can provide a general explanation for the behavior of several models that has been described as "self-organized critical," including forest-fire, sandpile, and slider-block models.

Journal Article↗

Networks with side branching in biology.

There are many examples of branching networks in biology. Examples include the structure of plants and trees as well as cardiovascular and bronchial systems. In many cases these networks are self-similar and exhibit fractal scaling. In this paper we introduce the Tokunaga taxonomy for the side branching of networks and his parameterization of self-similar side-branching. We introduce several examples of deterministic branching networks and show that constructions with the same fractal dimension can have different side-branching parameters. As an example of stochastic-branching in biology we consider the vein structure of a leaf. We show that the vein structure of the leaf and river networks have nearly identical side branching statistics. We introduce diffusion limited aggregation (DLA) clusters. These clusters also exhibit Tokunaga side-branching statistics. We consider several alternative explanations for why leaves, river networks, and DLA clusters have similar side-branching statistics. We also consider the allometric scaling relation between metabolic rate and the mass of species in terms of a cardiovascular system with Tokunaga statistics. We find reasonably good agreement between the observed scaling exponent, approximately 0.75, and our model for a range of values of the fractal dimension of the network and the blood flow resistance parameter.

Blood Volume↗

Symmetries in geology and geophysics.

Symmetries have played an important role in a variety of problems in geology and geophysics. A large fraction of studies in mineralogy are devoted to the symmetry properties of crystals. In this paper, however, the emphasis will be on scale-invariant (fractal) symmetries. The earth's topography is an example of both statistically self-similar and self-affine fractals. Landforms are also associated with drainage networks, which are statistical fractal trees. A universal feature of drainage networks and other growth networks is side branching. Deterministic space-filling networks with side-branching symmetries are illustrated. It is shown that naturally occurring drainage networks have symmetries similar to diffusion-limited aggregation clusters.

Journal Article↗

Time delays in age-structured populations.

A combination of analytical and computational techniques is employed to investigate age-structured populations in which the life cycle consists of two sequential demographic phases. Individuals within each phase have identical demographic rates that are functions of population size, but these rates may differ between phases. A model consisting of a system of delay ordinary differential equations is derived, and existence and stability of equilibria are discussed. Analysis reveals how equilibrium abundances depend on all demographic variables and, in particular, on the lengths of the demographic phases.

Aging↗