The application discloses an emulsified
asphalt wheel sticking effect evaluation method, equipment and medium, and relates to the technical field of intelligent construction, which comprises the following steps: acquiring a test parameter table, inputting the test parameter table into a
microfluidic chip tester for high-
throughput testing, and outputting a demulsification
kinetics curve and a basic
adhesion force data set; combining demulsification process parameters in the demulsification
kinetics curve with the basic
adhesion force data set to generate a demulsification adhesion
coupling data set, constructing a multi-
physical field simulation model, and using the demulsification adhesion
coupling data set for inversion and calibration to generate a calibrated digital twin model; acquiring construction environment data and inputting the construction environment data into the calibrated digital twin model for automatic multiple
simulation calculation to predict wheel sticking risk indexes of different construction schemes; and integrating a construction scheme with the lowest wheel sticking
risk index and a safe passing time window to generate an
intelligent decision suggestion. The application inverses and calibrates the interfacial
energy density through experimental data, and reduces the behavior error of the
simulation model and the real material.