Details

Autor(en) / Beteiligte

• Yang, Junlong
• Wang, Jizhong
• Wang, Ziru

Titel

Behavior and modeling of CFRP nonuniformly wrapped circular seawater sea-sand concrete (SSC) columns under axial compression

Ist Teil von

• Construction & building materials, 2021-09, Vol.299, p.123887, Article 123887

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •Axial compressive behavior of nonuniformly CFRP confined circular SSC columns was investigated.•Parameters affecting the axial stress–strain performance of tested specimens were discussed.•A nonuniform confinement effective coefficient was proposed.•A new stress–strain model was developed for nonuniformly FRP confined circular concrete. An experimental study was performed in this paper to investigate the compressive behavior of carbon fiber-reinforced polymer (CFRP) nonuniformly wrapped seawater sea-sand concrete (SSC) cylinders. The effect of test variables on the mechanical performance was comprehensively discussed, including the clear spacing and thickness of external CFRP strips. The test results indicate that the failure process of tested specimens is less brittle compared with that of the fully or partially FRP-confined columns. Besides, the average ultimate stresses and strains of the specimens nonuniformly wrapped with two-layer external CFRP strips increase by 6.7%-27.4% and 5.9–41.6% respectively with the reduction of clear spacing ratio. Moreover, when the thickness of external CFRP strips double increases, the maximum increment of strength and strain at ultimate condition becomes 42.8% and 63.8% respectively. It is also shown that the FRP efficiency factor of confined specimens with nonuniform wrapping scheme is the highest among various strengthening strategies under the same FRP volumetric ratio. Finally, a new nonuniform confinement effective coefficient, as well as a analytical stress–strain model, is developed based on the available test results. Compared with several existing predicted models, the proposed model can provide more accurate and reliable predictions.