Experimental Study on Static Performance of Deployable Bridge Based on Cable-Strengthened Scissor Structures
The deployable bridge based on scissor structures is one of the effective methods to quickly restore traffic after natural and man-made disasters. Scissor structures have the advantages of high storage rate, lightweight, and convenient storage and transportation. However, when scissor structures are...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/4373486 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The deployable bridge based on scissor structures is one of the effective methods to quickly restore traffic after natural and man-made disasters. Scissor structures have the advantages of high storage rate, lightweight, and convenient storage and transportation. However, when scissor structures are used as load-bearing structures, their stiffness and bearing capacity are low. In this study, a three-dimensional deployable bridge based on the cable-strengthened scissor structures was proposed. In addition to rapid expansion, steel cables were used to strengthen scissor structures to improve the stiffness and bearing capacity. Besides, the static loading comparative tests on cable-strengthened scissor structures and traditional scissor structures (cable-free scissor structures) were performed. The results show that the stiffness of the cable-free scissor structure is small, the bending moment of members is large, and the stress distribution is uneven. The stiffness of cable-strengthened scissor structure is significantly improved; the bending moment of members is significantly reduced; and the stress distribution in the member section is more uniform. It is proved that cables can be used to improve the stiffness and load-bearing capacity of scissor structures without affecting the deployability. |
|---|---|
| ISSN: | 1687-8094 |