Study on mechanical behavior of limestone and simulation using neural network model under different water-chemical environment

Based on triaxial compression tests of saturated limestone soaked by water-chemical solution, main factors affecting mechanical characteristics of limestone such as pH value, ion concentration and confining pressure are analyzed. The tests show that the elastic modulus and the peak strength of saturated limestone trend to decrease with the increase of acidity-alkalinity for the same solution with the same mol concentration; strength of limestone soaked in Na2SO4 solution, distilled water and CaCl2 solution with the same pH value decreases according to priority; the axial strain when the peak strength reaches, the strength of limestone and plastic deformation increase markedly with the increase of confining pressure. Considering the effect of the chemical solution and the stress path for mechanical property of limestone, an implicit modeling method describing mechanical property of limestone using evolutionary neural network is proposed. The neural network constitutive model trained by learning samples, tested by testing samples, and whose structure are searched by genetic algorithm, can well describe the mechanical properties of the limestone and can be used to simulate the mechanical tests in the similar condition. Correction of simulation is proved by 5 mechanical tests under different lab conditions.