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A new simulation method providing sh...
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Talley, Michael A.
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A new simulation method providing shock mount selection assurance.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A new simulation method providing shock mount selection assurance./
作者:
Talley, Michael A.
面頁冊數:
132 p.
附註:
Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1525.
Contained By:
Dissertation Abstracts International65-03B.
標題:
Engineering, Packaging. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3125118
ISBN:
0496724088
A new simulation method providing shock mount selection assurance.
Talley, Michael A.
A new simulation method providing shock mount selection assurance.
- 132 p.
Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1525.
Thesis (D.Sc.)--The George Washington University, 2004.
This dissertation presents the development and assessment of a practical, efficient, and easy to use six degree of freedom (6DOF) simulation tool for the selection of mounting systems for shock mitigation. The motivation for its development was to reduce the risk of equipment failures during shock tests by improving the decision tools used in assessing and designing shock isolation systems. The increased degrees of freedom over existing practical analysis methods provide engineers, analysts, equipment integrators, and others with the assurance that correct mount systems are selected. The 6DOF simulation tool, known as Shock Isolation Mount Predictions and Loading Estimates (SIMPLE), is developed to simplify the specification and implementation of the many parameters used in analyzing isolated systems. SIMPLE is validated by comparing simulation results with other analytical methods and with shock test data. The efficiency of SIMPLE is examined by applying it to assess and design over 60 different mounting systems. SIMPLE is also a tool that can easily account for uncertainties in isolated systems and their environments. Experimental results from shock tests are compared with pre-test SIMPLE sensitivity simulations and with results of post-test model calibrations. In addition, analysis of variance is performed between vendor-provided and calibrated model parameters. These comparisons show the validity of: (1) using 6DOF analysis; (2) using statically derived load-deflection data for simulations; and (3) assessing and designing isolated systems using uncertainties in model parameters.
ISBN: 0496724088Subjects--Topical Terms:
1025152
Engineering, Packaging.
A new simulation method providing shock mount selection assurance.
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This dissertation presents the development and assessment of a practical, efficient, and easy to use six degree of freedom (6DOF) simulation tool for the selection of mounting systems for shock mitigation. The motivation for its development was to reduce the risk of equipment failures during shock tests by improving the decision tools used in assessing and designing shock isolation systems. The increased degrees of freedom over existing practical analysis methods provide engineers, analysts, equipment integrators, and others with the assurance that correct mount systems are selected. The 6DOF simulation tool, known as Shock Isolation Mount Predictions and Loading Estimates (SIMPLE), is developed to simplify the specification and implementation of the many parameters used in analyzing isolated systems. SIMPLE is validated by comparing simulation results with other analytical methods and with shock test data. The efficiency of SIMPLE is examined by applying it to assess and design over 60 different mounting systems. SIMPLE is also a tool that can easily account for uncertainties in isolated systems and their environments. Experimental results from shock tests are compared with pre-test SIMPLE sensitivity simulations and with results of post-test model calibrations. In addition, analysis of variance is performed between vendor-provided and calibrated model parameters. These comparisons show the validity of: (1) using 6DOF analysis; (2) using statically derived load-deflection data for simulations; and (3) assessing and designing isolated systems using uncertainties in model parameters.
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