Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

The compaction quality of subgrade filler strongly affects subgrade settlement.The main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse particles.First,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade filler.Shape indexes of 2D subgrade filler are then computed and statistically analyzed.Finally,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine particles.Moreover,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle shapes.The dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine particles.Under the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the sample.This study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

Prediction of high-embankment settlement combining joint denoising technique and enhanced GWO-v-SVR method

Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure safety.This study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)method.High-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet transform.Furthermore,high-embankment settlements were predicted using the EGWO-n-SVR method.In this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model hyperparameters.The proposed NHM was then tested in two case studies.Finally,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were investigated.The results indicate that the NHM suppresses noise and restores details in high-embankment field measurements.Simultaneously,the NHM out-performs other alternative prediction methods in prediction accuracy and robustness.This demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field mea-surements.Moreover,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.

Physical modeling of long-term dynamic characteristics of the subgrade for medium-low-speed maglevs

To investigate the dynamic characteristics and long-term dynamic stability of the new subgrade structure of medium-low-speed(MLS)maglevs,cyclic vibration tests were performed under natural and rainfall conditions,and the dynamic response of the subgrade structure was monitored.The dynamic response attenuation characteristics along the depth direction of the subgrade were compared,and the distribution characteristics of the dynamic stress on the surface of the subgrade along the longitudinal direction of the line were analyzed.The critical dynamic stress and cumulative deformation were used as indicators to evaluate the long-term dynamic stability of the subgrade.Results show that water has a certain effect on the dynamic characteristics of the subgrade,and the dynamic stress and acceleration increase with the water content.With the dowel steel structure set between the rail-bearing beams,stress concentration at the end of the loaded beam can be prevented,and the diffusion distance of the dynamic stress along the longitudinal direction increases.The dynamic stress measured in the subgrade bed range is less than 1/5 of the critical dynamic stress.The postconstruction settlement of the subgrade after similarity ratio conversion is 3.94 mm and 7.72 mm under natural and rainfall conditions,respectively,and both values are less than the 30 mm limit,indicating that the MLS maglev subgrade structure has good long-term dynamic stability.