Seismic Performance Testing of Anchoring Structures for Crude Oil Storage Tanks in Seismic Zones



| Product name: | Seismic Performance Testing of Anchoring Structures for Crude Oil Storage Tanks in Seismic Zones |
| Keywords: | Seismic Performance Testing of Anchoring Structures for Crude Oil Storage Tanks in Seismic Zones |
| Industry: | Petroleum, natural gas and chemical industry - Petroleum and natural gas industry |
| Process: | Sheet metal - Welding |
| Material: | Carbon steel |
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Seismic performance testing of anchoring structures for crude oil storage tanks in seismic zones must comply with GB/T 50761-2018. This standard specifies key parameters such as the seismic design response spectrum, seismic action adjustment coefficient, and structural damping ratio, requiring an anchoring coefficient ≥0.785 to resist the risk of tank bottom uplift. The testing should focus on the impulsive force (Pi) and convective component (Pc) generated by liquid sloshing. Elastic connection nodes must meet a ±15° angular displacement capacity, and the axial compressive stress on the tank wall should be lower than the allowable stress limit.
Actual case studies show that a 9m diameter storage tank using a concrete ring wall foundation, through a comparison of Chinese and American standards, reveals that the domestic anchoring coefficient calculation does not consider the influence of site category, while the sloshing wave height analysis needs to comprehensively consider the tank shape and seismic usage group factors. The testing should simultaneously monitor the bottom plate corrosion (depth ≤40%) to avoid a decrease in seismic performance due to local failure.
Performance verification needs to be combined with dynamic analysis software to simulate the structural response under seismic loads, focusing on evaluating: 1) the tensile strength of anchor bolts; 2) the critical buckling stress of the tank wall; 3) whether the liquid sloshing wave height exceeds the design limit. The test data should be compared with the digital twin model, with an error of <5%.
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