Experimental Investigation into Dynamic and Static Stiffness Relationships in Rubber-Metal Springs
Source abstract
Abstract
Abstract Rubber-metal springs are widely utilized in industrial applications, particularly as vibration absorbers, due to their ability to mitigate dynamic loads. The dynamic stiffness of rubber-metal springs plays a crucial role in determining the natural frequency of a system, as natural frequency is directly linked to dynamic stiffness. Therefore, the accurate determination of dynamic stiffness is essential when selecting an appropriate rubber-metal spring for a given application. However, the assessment of dynamic stiffness presents a significant challenge due to the complex interaction between rubber and metal components, particularly when considering the viscoelastic properties of rubber and the geometric properties of the spring. Rubber’s viscoelastic response and how it changes under different strain rates is fundamentally rooted in the micro- and meso-scale configuration of polymer chains, filler particles, and their bonding to metal components. Consequently, dynamic stiffness is often approximated using static stiffness measurements, which simplifies the problem but may lead to inaccuracies in predicting the true dynamic behaviour of the spring. In this paper, we present an experimental method for dynamic stiffness assessment using an electrodynamic shaker, which allows for a more accurate characterization of the spring’s response to dynamic loading. This method is compared to an analytical approach based on static stiffness, highlighting the limitations of the latter approach. Furthermore, we propose an improved range for calculating dynamic stiffness from static stiffness, enhancing the predictive accuracy for dynamic behaviour.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Elasticity and Material Modeling · Vibration Control and Rheological Fluids · Mechanical Engineering and Vibrations Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (30)
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