Most material properties exhibit random spatial fluctuations. This feature is most notable in composite materials such as new low-impact composite materials in which synthetic fibers are replaced with natural ones. Probabilistic models are needed to characterize the mechanical properties of these class of materials with highly variable features. A discrete probabilistic model is developed for the capacity of natural fibers-based products used in composite materials. Fibers are partitioned in a number of relatively small segments (links). The fiber's capacity is inferred from that of the links via an extension of the weakest link model, which accounts for the correlation among link properties. It is shown that the proposed model fitted to experimental observations of hemp ropes capacities of two different lengths, 200 and 555 mm, provides satisfactory estimates for the capacity of these ropes.

Extension of the weakest link model to describe hemp rope capacity

Pipistrelli, Maria Eleonora;Gioffre, Massimiliano
;
Grigoriu, Mircea Dan
2025

Abstract

Most material properties exhibit random spatial fluctuations. This feature is most notable in composite materials such as new low-impact composite materials in which synthetic fibers are replaced with natural ones. Probabilistic models are needed to characterize the mechanical properties of these class of materials with highly variable features. A discrete probabilistic model is developed for the capacity of natural fibers-based products used in composite materials. Fibers are partitioned in a number of relatively small segments (links). The fiber's capacity is inferred from that of the links via an extension of the weakest link model, which accounts for the correlation among link properties. It is shown that the proposed model fitted to experimental observations of hemp ropes capacities of two different lengths, 200 and 555 mm, provides satisfactory estimates for the capacity of these ropes.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1604535
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