Signaling properties of asymmetric spider webs

Abstract

Spiders rely on vibrations transmitted through their webs to mlocate and classify prey, and spider will adjust their behavior according to the gained information. Yet, the cues spiders use to interpret these signals, especially from the initial impact, remain poorly understood. These webs are lightweight, mechanically nonlinear structures that serve as extended sensory systems. Understanding how the design of such systems affects signaling can offer insight into sensing in engineering sensing systems, in the field of for example structural health monitoring, feedback control systems, and optimal sensor placement. This dissertation investigates how specific vibrational cues—those that spiders can realistically measure—contribute to prey localization and classification. A central question is whether structural irregularities, such as eccentricity and narrowness, enhance these cues. The study also examines whether such cues remain reliable despite changes in web design and external parameters like prey mass and impact location, which is critical for robust sensing in systems operating with limited information, like spider webs. Previous research on spider web dynamics has primarily focused on idealized circular webs and local geometric features, overlooking how global web shape and prey mass influence vibrational behavior. While several promising mechanisms for prey detection and localization have been proposed, it remains unknown whether these cues remain reliable across the diverse range of web shapes seen in nature and under varying prey sizes. Critically, spiders must act based on limited local information, measured only at their leg positions, so any effective cue must be robust to changes in design and external conditions without relying on global knowledge of the web dynamics or prey. The study combines a numerical and experimental investigations to explore how spider webs design affects vibrational cues. Spiderweb-like structures were fabricated with biologically accurate tension gradients and tested under dynamic loading to analyze their vibrational behavior, enables with high speed cameras. These experiments were complemented by numerical simulations using the Finite Element method. This dissertation presents three main discoveries. First, a robust pitching mode was identified that allows spiders to localize prey using directional vibrations, independent of web irregularities. Second, a specific cue was found to reflect prey mass through system dynamics. However, ambiguity arises due to overlap between the effects of prey mass and distance to impact, and introducing geometric irregularities actually increases this ambiguity. Still, these cues support robust classification of prey type based on mass. Third, building on these biological insights, the thesis introduces a design method for 3D-printed networks with programmable tension gradients and develops Directional Digital Image Correlation (D-DIC), a displacement measurement technique for optical methods that enables full-field experimental modal analysis from a single impact. This includes tracking edges, not just at intersections, as was possible with DIC. Engineering sensing systems are typically designed for structures with known geometry and dynamics. Sensors can be placed with flexibility, and external perturbations are often treated as non-intrusive to the system's behavior. In contrast, spiders must sense and interpret vibrations in webs with unknown and variable properties. They are limited to sensing vibrations near the web's center, and must rely on cues that remain informative despite variation in design, prey mass, and impact location. Moreover, in spider webs, an impact event significantly alters the system's dynamics, making sensing inherently more challenging. This work shows that spiders overcome these limitations by relying on robust structural cues. These findings offer a foundation for designing sensing systems that perform reliably in uncertain and constrained environments, where full modeling is not feasible and disturbances cannot be ignored.