journal article·2017-05-01Open access

Using Mason number to predict MR damper performance from limited test data

Andrew C. Becnel, Norman M. Wereley

AIP Advances· Volume 7· Issue 5

Abstract

The Mason number can be used to produce a single master curve which relates MR fluid stress versus strain rate behavior across a wide range of shear rates, temperatures, and applied magnetic fields. As applications of MR fluid energy absorbers expand to a variety of industries and operating environments, Mason number analysis offers a path to designing devices with desired performance from a minimal set of preliminary test data. Temperature strongly affects the off-state viscosity of the fluid, as the passive viscous force drops considerably at higher temperatures. Yield stress is not similarly affected, and stays relatively constant with changing temperature. In this study, a small model-scale MR fluid rotary energy absorber is used to measure the temperature correction factor of a commercially-available MR fluid from LORD Corporation. This temperature correction factor is identified from shear stress vs. shear rate data collected at four different temperatures. Measurements of the MR fluid yield stress are also obtained and related to a standard empirical formula. From these two MR fluid properties – temperature-dependent viscosity and yield stress – the temperature-corrected Mason number is shown to predict the force vs. velocity performance of a full-scale rotary MR fluid energy absorber. This analysis technique expands the design space of MR devices to high shear rates and allows for comprehensive predictions of overall performance across a wide range of operating conditions from knowledge only of the yield stress vs. applied magnetic field and a temperature-dependent viscosity correction factor.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Vibration Control and Rheological Fluids · Hydraulic and Pneumatic Systems · Fluid Dynamics and Vibration Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

University of Maryland Department of Aerospace Engineering, , College Park, Maryland 20742, USA

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