Numerical simulation of asphalt mixture based on three-dimensional heterogeneous specimen

In order to verify the validity of finite element numerical simulation method for asphalt mixture, which consists of aggregates, mastic （where mastic is a kind of fine mixture composed of asphalt binder mixed with fines and fine aggregates） and air voids, based on three-dimensional （3D） heterogeneous specimen, X-ray computerized tomography （X-ray CT） was used to scan the asphalt specimens to obtain the real internal microstrnctures of asphalt mixture. CT images were reconstructed to build up 3D digital specimen, and the viscoelastic properties of mastic were described with Burgers model The uniaxial creep numerical simulations of three different levels of aggregate gradation were conducted. The simulation results agree well with the experimental results. The numerical simulation of asphalt mixture incorporated with real 3D microstructure based on finite element method is a promising application to conduct research of asphalt concrete. Additionally, this method can increase the mechanistic understanding of global viscoelastic properties of asphalt mixtures by linking the real 3D microstructure.

Smoothed response spectra including soil-structure interaction effects

Elastic response spectra that take into account the effects of soil-structure interaction on soft soils are developed. The response spectra are calculated utilizing a 3 DOF system including deformations of the superstructure and foundation. The equations of motion of the system are solved using direct integration under normalized earthquake records. Statistical processing of the results is implemented resulting in response spectra for "short and dense buildings with low interaction", "short and dense buildings with high interaction", "tall and light buildings with low interaction" and "tall and light buildings with high interaction". The resulting response spectra are smoothed and discussed.

A Comparative Analysis of Performance-Based Resilience Metrics via a Quantitative-Qualitative Combined Approach: Are We Measuring the Same Thing?

Since the proposal of the pioneering“resilience triangle”paradigm,various time-series performance-based metrics have been devised for resilience quantification.The numerous choices diversify the toolbox for measuring this compound system concept;however,this multiplicity causes intractable questions for applications,including“Do these metrics measure the same resilience?”and“Which one to pick under what circumstance?”In this study,we attempted to address these two fundamental issues using a comprehensive comparative investigation.Through a quantitative-qualitative combined approach,12 popular performance-based resilience metrics are compared using empirical data from China’s aviation system under the disturbance of COVID-19.Quantitative results indicate that only 12 of the 66 metric pairs are strongly positively correlated and with no significant differences in quantification outcomes;qualitative results indicate that the majority of the metrics are based on different definition interpretations,basic components,and expression forms,and thus essentially measure different resilience.The advantages and disadvantages of each metric are comparatively discussed,and a“how to choose”guideline for metric users is proposed.This study is an introspective investigation of resilience quantification studies,aiming to offer a new perspective to scrutinize those benchmarking metrics.

Two-level vehicle path planning model for multi-warehouse robots with conflict solution strategies and improved ACO

With the rapid development of warehouse robots in logistics and other industries,research on their path planning has become increasingly important.Based on the analysis of various conflicts that occur when the warehouse robot travels,this study proposes a two-level vehicle path planning model for multi-warehouse robots,which integrates static and dynamic planning to improve operational efficiency and reduce operating costs.In the static phase,the blockage factor is introduced to enhance the ant colony optimization(ACO)algorithm as a negative feedback mechanism to effectively avoid the blockage nodes during movement.In the dynamic stage,a dynamic priority mechanism is designed to adjust the routing strategy in real time and give the optimal path according to the real situation.To evaluate the model’s effectiveness,simulations were performed under different operating environments and application strategies based on an actual grid environment map.The simulation results confirm that the proposed model outperforms other methods in terms of average running distance,number of blocked nodes,percentage of replanned paths,and average running time,showing great potential in optimizing warehouse operations.