This report summarizes design and modeling activities for the MEMS passive shock sensor. It provides a description of past design revisions, including the purposes and major differences between design revisions but with a focus on Revisions 4 through 7 and the work performed in fiscal year 2008 (FY08). This report is a reference for comparing different designs; it summarizes design parameters and analysis results, and identifies test structures. It also highlights some of the changes and or additions to models previously documented [Mitchell et al. 2006, Mitchell et al. 2008] such as the way uncertainty thresholds are analyzed and reported. It also includes dynamic simulation results used to investigate how positioning of hard stops may reduce vibration sensitivity.
This report summarizes the functional, model validation, and technology readiness testing of the Sandia MEMS Passive Shock Sensor in FY08. Functional testing of a large number of revision 4 parts showed robust and consistent performance. Model validation testing helped tune the models to match data well and identified several areas for future investigation related to high frequency sensitivity and thermal effects. Finally, technology readiness testing demonstrated the integrated elements of the sensor under realistic environments.
This report describes activities conducted in FY07 to mature the MEMS passive shock sensor. The first chapter of the report provides motivation and background on activities that are described in detail in later chapters. The second chapter discusses concepts that are important for integrating the MEMS passive shock sensor into a system. Following these two introductory chapters, the report details modeling and design efforts, packaging, failure analysis and testing and validation. At the end of FY07, the MEMS passive shock sensor was at TRL 4.
Forces generated by a static magnetic field interacting with eddy currents can provide a novel method of vibration damping. This paper discusses an experiment performed to validate modeling [3] for a case where a static magnetic field penetrates a thin sheet of conducting, non-magnetic material. When the thin sheet experiences motion, the penetrating magnetic field generates eddy currents within the sheet. These eddy currents then interact with the static field, creating magnetic forces that act on the sheet, providing damping to the sheet motion. In the presented experiment, the sheet was supported by cantilever springs attached to a frame, then excited with a vibratory shaker. The recorded motions of the sheet and the frame were used to characterize the effect of the eddy current damping.
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
Damping vibrations is important in the design of some types of inertial sensing devices. One method for adding damping to a device is to use magnetic forces generated by a static magnetic field interacting with eddy currents. In this report, we develop a 2-dimensional finite element model for the analysis of quasistatic eddy currents in a thin sheet of conducting material. The model was used for design and sensitivity analyses of a novel mechanical oscillator that consists of a shuttle mass (thin sheet of conducting material) and a set of folded spring elements. The oscillator is damped through the interaction of a static magnetic field and eddy currents in the shuttle mass. Using a prototype device and Laser Dopler Velocimetry (LDV), measurements were compared to the model in a validation study using simulation based uncertainty analyses. Measurements were found to follow the trends predicted by the model.