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Proposing an Updated AM2 Mat Performance Criteria Model
The AM2 mat system is historically one of the most deployed portable airfield mats in the military. The current AM2 airfield mat performance criteria for determining the number of coverages an AM2 mat can sustain before failure is an empirically correlated model and cannot accurately predict the num...
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Published in: | Transportation research record 2020-08, Vol.2674 (8), p.604-615 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The AM2 mat system is historically one of the most deployed portable airfield mats in the military. The current AM2 airfield mat performance criteria for determining the number of coverages an AM2 mat can sustain before failure is an empirically correlated model and cannot accurately predict the number of coverages to failure beyond lower subgrade (California bearing ration) CBR or for modern aircraft with multiple tire configurations. This paper presents a stress-based model that predicts the number of coverages to failure using the maximum deviator stress as the performance index normalized by the subgrade CBR. The proposed model addresses different aircraft tire configurations on the AM2 mat over subgrade CBR values extending up to 100. Some improvements made to current criteria include (1) the addition of more test data at higher subgrade CBR values, (2) a fitted curve that more reasonably addresses early permanent deformation failures due to loads at low CBR, (3) a reasonable “cap” to the service life of an AM2 mat due to failure from mat breakage at high CBR, (4) a consolidation of previous “families of curves” for different equivalent single wheel loads and CBR values into one single regression curve, and (5) a performance index calculated using layered elastic analysis (WinJULEA). This paper presents a comparison of the proposed model with the current performance criteria against the full-scale test data. Results show that the proposed model has a high correlation to the test data (R2 = 0.952) and performs very well with respect to the current performance criteria. |
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ISSN: | 0361-1981 2169-4052 |
DOI: | 10.1177/0361198118825123 |