Study on the erosion mechanism and service life prediction of tailings recycled concrete based on a grey forecasting model in a salt spray environment

To explore the erosion mechanism and service life of tailings recycled concrete in salt-spray environment, the evolution laws of compressive strength corrosion resistance coefficient ( K f ), relative quality evaluation coefficient(ξ 1 ), and dynamic elastic modulus evaluation coefficient (ξ 2 ) of concrete with different iron ore tailings dosages were investigated through accelerated salt spray erosion tests. A grey forecasting model incorporating full-order time power terms (FOTP-GM(1,1)) was proposed. The results indicated that the FTOP-GM(1,1) model, constructed by reconstructing background values, overcame the limitations of the traditional GM (1,1) model in predicting nonlinear degraded sequences, with relative errors between the predicted and original values within 2%. A competitive failure threshold was established, forming a multi-index competitive failure model of "strength-mass-elastic modulus." The service life was defined by the earliest threshold parameter, revealing the dominant failure path influenced by iron ore tailings dosage: K f when the dosage was ≤30%, and ξ 1 when the dosage exceeded 30%. If ξ 2 were chosen as the evaluation parameter, the predicted service life would generally be longer. Compared to natural aggregate concrete (NAC) and recycled aggregate concrete (RAC), the optimal iron ore tailings dosage of 30% increased the predicted service life by 13.76% and 37.29%, respectively. This study provides a high-precision, efficient method for predicting the service life of tailings recycled concrete in salt-spray environments, offering a lightweight tool for durability design of iron ore tailings based concrete in marine and inland salt-lake regions.