New innovations in pavement materials and engineering:A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges.In the past 10 years,the pavement infrastructure strongly supports the rapid development of the global social economy.New theories,new methods,new technologies and new materials related to pavement engineering are emerging.Deterioration of pavement infrastructure is a typical multi-physics problem.Because of actual coupled behaviors of traffic and environmental conditions,predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis.In order to summarize the current and determine the future research of pavement engineering,Journal of Traffic and Transportation Engineering(English Edition)has launched a review paper on the topic of"New innovations in pavement materials and engineering:A review on pavement engineering research 2021".Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering,this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the world.The content includes asphalt binder performance and modeling,mixture performance and modeling of pavement materials,multi-scale mechanics,green and sustainable pavement,and intelligent pavement.Overall,this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering.

Molecular dynamics simulation on the rejuvenation effects of waste cooking oil on aged asphalt binder

Waste cooking oil(WCO)has received attention on rejuvenating aged asphalt binder widely in recent years.This study evaluated the rejuvenation effects of WCO on aged asphalt binder on the micro-scale using molecular dynamics(MD)simulation.First,the representative molecules of WCO and asphalt binders were selected.The molecular mixture model was then developed.The thermodynamic properties were investigated,including density,cohesive energy density,solubility parameter,and surface free energy.The results show that WCO can restore the thermodynamic properties of aged asphalt binder to some extent and WCO has different influences on electrostatic interactions and van der Waals effects.From the diffusion behavior and molecular structure of asphalt binder,WCO can improve the molecular mobility and restore the colloidal structure.Besides,the adhesion work and moisture susceptibility of asphalt binder-aggregate interfaces(calcite and quartz)were evaluated.The results show that WCO can improve adhesion work between asphalt binder and aggregates since WCO can change molecular structure of asphalt binders and certain adhesion work exists between WCO and aggregates.Also,it can mitigate the moisture susceptibility of asphalt binder-aggregate interfaces(calcite and quartz).The study demonstrates that the MD simulation can help to understand the rejuvenation effects of WCO on aged asphalt binder on the micro-scale.

Printed circuit board solder joint quality inspection based on lightweight classification network

Solder joint quality inspection is a crucial step in the qualification inspection of printed circuit board(PCB)components,and efficient and accurate inspection methods will greatly improve its production efficiency.In this paper,we propose a PCB solder joint quality detection algorithm based on a lightweight classification network.First,the Select Joint segmentation method was used to obtain the solder joint information,and colour space conversion was used to locate the solder joint.The mask method,contour detection,and box line method were combined to complete the extraction of solder joint information.Then,by combining the respective characteristics of convolutional neural network and Transformer and introducing Cross-covariance attention to reduce the computational complexity and resource consumption of the model and evenly distribute the global view mutual information in the whole training process,a new lightweight network model MobileXT is proposed to complete defect classification.Only 16.4%of the Vision Transformer computing resources used in this model can achieve an average accuracy improvement of 31%.Additionally,the network is trained and validated using a dataset of 1804 solder joint images constructed from 93 PCB images and two external datasets to evaluate MobileXT performance.The proposed method achieves more effi-cient localization of the solder joint information and more accurate classification of weld joint defects,and the lightweight model design is more appropriate for industrial edge device deployments.