Abstract: A ballastless track roadbed damage forewarning method considering uncertainty includes the following steps. Step 1: counting roadbed material parameters and precipitation; Step 2: establishing a FLAC-PFC model of a ballastless track roadbed and calibrating mesoscopic parameters of a roadbed surface layer; Step 3: generating a lognormal random field of particle contact friction coefficients and assigning it to particle contact nodes of the roadbed surface layer; Step 4: perform sampling on the precipitation and adjusting a fluid domain of the roadbed surface layer; Step 5: determining a worst spatial correlation distance in the random field; and Step 6: calculating a damage probability pf of the roadbed surface layer under the worst spatial correlation distance; outputting alarm information when pf exceeds an alarm threshold, otherwise, quitting. The method monitors and gives early warning of damage to the roadbed surface layer under dynamic loads, ensuring driving safety.

Abstract: A ballastless track roadbed damage forewarning method considering uncertainty includes the following steps. Step 1: counting roadbed material parameters and precipitation; Step 2: establishing a FLAC-PFC model of a ballastless track roadbed and calibrating mesoscopic parameters of a roadbed surface layer; Step 3: generating a lognormal random field of particle contact friction coefficients and assigning it to particle contact nodes of the roadbed surface layer; Step 4: perform sampling on the precipitation and adjusting a fluid domain of the roadbed surface layer; Step 5: determining a worst spatial correlation distance in the random field; and Step 6: calculating a damage probability pf of the roadbed surface layer under the worst spatial correlation distance; outputting alarm information when pf exceeds an alarm threshold, otherwise, quitting. The method monitors and gives early warning of damage to the roadbed surface layer under dynamic loads, ensuring driving safety.

Abstract: Disclosed is detection apparatus for flow deformation of foundation layer in horizontal direction including: housing, rotation assembly rotatably disposed within accommodation cavity of the housing, and measurement assembly including first optical fiber lead wire, first optical fiber sensor disposed on first optical fiber lead wire, second optical fiber lead wire, and second optical fiber sensor disposed on second optical fiber lead wire, and disposed within the accommodation cavity. First optical fiber sensor is configured to measure tensile strain of first optical fiber lead wire and first optical fiber sensor before and after the rotation assembly rotates; second optical fiber sensor is configured to measure tensile strain of second optical fiber lead wire and second optical fiber sensor before and after the rotation assembly rotates, to obtain strain amount and displacement change amount, and further to obtain flow deformation degree and flow deformation direction of soil mass of the foundation layer.

Abstract: Disclosed is detection apparatus for flow deformation of foundation layer in horizontal direction including: housing, rotation assembly rotatably disposed within accommodation cavity of the housing, and measurement assembly including first optical fiber lead wire, first optical fiber sensor disposed on first optical fiber lead wire, second optical fiber lead wire, and second optical fiber sensor disposed on second optical fiber lead wire, and disposed within the accommodation cavity. First optical fiber sensor is configured to measure tensile strain of first optical fiber lead wire and first optical fiber sensor before and after the rotation assembly rotates; second optical fiber sensor is configured to measure tensile strain of second optical fiber lead wire and second optical fiber sensor before and after the rotation assembly rotates, to obtain strain amount and displacement change amount, and further to obtain flow deformation degree and flow deformation direction of soil mass of the foundation layer.