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Title: Electrodynamic Shaker Capability Estimation Through Experimental Dynamic Substructuring [Thesis]

Technical Report ·
DOI:https://doi.org/10.2172/1958984· OSTI ID:1958984
ORCiD logo [1]
  1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Univ. of California, San Diego, CA (United States)

Electrodynamic shaker systems are an essential tool in shock and vibration testing of dynamic environments. However, the specific performance capability of these systems is difficult to characterize. The dynamics of the shaker itself, the device under test and the specific test configuration used all couple to create a dynamic response unique to each test. Poorly predicted limitations in shaker capability affect the ability to achieve test specifications, delay testing schedules, and create difficulties for choosing test equipment. To predict shaker capability for a specific test configuration prior to setup, a lumped parameter model of the shaker system and a modal model of a device under test was developed. These models were then analytically coupled using LaGrange multiplier frequency based substructuring to estimate their coupled frequency response functions. The coupled frequency response functions were used to predict electrical inputs required to meet a given test specification. These input requirements were finally compared to a validation test using the specification and setup. Input requirements estimated using the substructuring estimated frequency response functions showed significant error. However, results using an ideal frequency response function showed very little error. These results indicate that with a better method of experimental dynamic substructuring employed it would be possible to accurately predict shaker capability for a given test configuration prior to setup.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Univ. of California, San Diego, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
89233218CNA000001
OSTI ID:
1958984
Report Number(s):
LA-UR-23-20025; TRN: US2403107
Country of Publication:
United States
Language:
English

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