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Investigation of material composition,design,and performance of open-graded asphalt mixtures for semi-flexible pavement:A comprehensive experimental study

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Journal of Traffic and transportation engineering(English Edition) 2024年第1期11卷 92-116页

作者： Mohammad Taghipoor Abolfazl Hassani Mohammad M.Karimi department of civil and Environmental engineering Tarbiat Modares UniversityTehranIran

The primary goal of this study is the design and construction of semi-flexible pavement(SFP)mixture in accordance with the engineering and mechanical *** study involves the use of a range of gradation curves,air void contents,cellulose and synthesized fibers,and neat and modified asphalt binders to prepare the open-graded asphalt(OGA)*** analyze the characteristics of these mixtures,a variety of test,namely binder drainage,semi-circular bending(SCB),Cantabro,wheel tracking,indirect tensile strength(ITS),and permeability tests were ***,to analyze the prepared grouting material,flexural strength,compressive strength,and fluidity tests were *** the final stage,SFP was compared to HMA in terms of engineering characteristics and *** to the results,SFP was more resistant to skid,rutting,fire,and moisture damage,while HMA had a better performance in fracture tests,including SCB *** to the results of the mechanical performance tests conducted on OGA mixtures,the highest and lowest values for air void content to achieve the highest mechanical performance level were 30%-35%and 25%,***,based on the laboratory results,it was determined that the required void ratio for constructing OGA mixtures was 24%-26%based on the bitumen type and fibers amount in the ***,SFP mixture can be regarded as a viable alternative to common pavements thanks to its high resistance to rutting and moisture damage,long freezing-thawing fatigue life,and adequate fire and skid resistance.

关键词： Semi-flexible pavement mixture Open-graded asphalt mixture engineering properties Cantabro test Hot mix asphalt

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Biotransformation of 6:2 fluorotelomer sulfonate(6:2 FTS)in sulfur-rich media by Trametopsis cervina

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Frontiers of Environmental Science & engineering 2024年第9期18卷 17-26页

作者： Felix Grimberg Thomas M Holsen Sujan Fernando Siwen Wang department of civil and Environmental engineering Clarkson UniversityPotsdamNew York 13699USA

Biotransformation of 6:2 fluorotelomer sulfonate(6:2 FTS)by two species of white-rot fungi,Pleurotus ostreatus(***)and Trametopsis cervina(***),was investigated in a sulfurrich medium designed to stimulate production of lignin-degrading *** of 6:2 FTS was observed by *** over the study period of 30 d,but not by *** rates were comparable to those found in other studies investigating mixed culture degradation in nonsulfur limiting media,with approximately 50 mol%of applied 6:2 FTS removed after 30 *** transformation products were short-chain perfluorocarboxylic acids(PFCAs),including PFHxA(2.27 mol%),PFPeA(0.24 mol%),and PFBA(0.28 mol%).The main intermediate products include 5:2 sFTOH(16.3 mol%)and 5:3 FTCA(2.99 mol%),while 6:2 FTCA,6:2 FTuCA,and 5:2 ketone were also identified at low *** 60 mol%of detected products were assigned to the major pathway to 5:2 ketone,and 40 mol%were assigned to the minor pathway to 5:3 *** overall molar balance was found to decrease to 75 mol%by Day 30,however,was closed to near 95 mol%with a theoretical estimation for the volatile intermediates in the headspace,5:2 ketone and 5:2 *** different capabilities of the two white-rot fungal species for 6:2 FTS biotransformation in sulfur-rich media suggest that the enzyme processes of *** to de-sulfonate 6:2 FTS may be unrelated to sulfur metabolism.

关键词： White-rot fungus 6:2 fluorotelomer sulfonate(6:2 FTS) Biotransformation Sulfur-rich medium Intermediate products

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Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

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Journal of Mountain Science 2024年第2期21卷 690-717页

作者： Furquan AHMAD Pijush SAMUI S.S.MISHRA department of civil engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** SS approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO *** ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo Simulation Subset Simulation Machine Learning Seismic coefficient

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Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

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Earthquake engineering and engineering Vibration 2024年第2期23卷 345-358页

作者： Zan Zhou Thomas Man-Hoi Lok Wan-Huan Zhou department of civil and Environmental engineering Faculty of Science and TechnologyUniversity of MacaoMacaoChina

Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization ***,an improper selection of the number of layers may lead to an incorrect shear wave velocity *** this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil ***,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer ***,the shear-wave velocity profile is determined by a genetic algorithm with the known layer *** applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

关键词： surface wave inversion analysis shear-wave velocity profile deep neural network genetic algorithm

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Study on a conical bearing for acceleration-sensitive equipment

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Earthquake engineering and engineering Vibration 2024年第1期23卷 103-128页

作者： Pang Hui Xu Wen Dai Junwu Jiang Tao Key Laboratory of Earthquake engineering and engineering Vibration Institute of Engineering MechanicsChina Earthquake AdministrationHarbin 150080China Key Laboratory of Earthquake Disaster Mitigation Ministry of Emergency ManagementHarbin 150080China School of civil engineering and transportation Beihua UniversityJilin 132013China

Seismic isolation effectively reduces seismic demands on building structures by isolating the superstructure from ground vibrations during ***,isolation strategies give less attention to acceleration-sensitive systems or ***,as the isolation layer’s displacement grows,the stiffness and frequency of traditional rolling and sliding isolation bearings increases,potentially causing self-centering and resonance *** a result,a new conical pendulum bearing has been selected for acceleration-sensitive equipment to increase self-centering capacity,and additional viscous dampers are incorporated to enhance system ***,the theoretical formula for conical pendulum bearings is supplied to analyze the device’s dynamic parameters,and shake table experiments are used to determine the proposed device’s isolation efficiency under various *** to the test results,the newly proposed devices have remarkable isolation performance in terms of minimizing both acceleration and displacement ***,a numerical model of the isolation system is provided for further research,and the accuracy is demonstrated by the aforementioned experiments.

关键词： seismic isolation acceleration-sensitive equipment the conical pendulum bearing shake table tests isolation performance,numerical model

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High-resolution photogrammetry to measure physical aperture of two separated rock fracture surfaces

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Journal of Rock Mechanics and Geotechnical engineering 2024年第8期16卷 2922-2934页

作者： Masoud Torkan Mateusz Janiszewski Lauri Uotinen Alireza Baghbanan Mikael Rinne department of civil engineering Aalto UniversityEspooFinland department of Mining engineering Isfahan University of TechnologyIsfahanIran

Photogrammetry,reconstructing three-dimensional(3D)models from overlapping two-dimensional(2D)photos,finds application in rock mechanics and rock engineering to extract geometrical details of reconstructed objects,for example rock *** properties are important for determining the mechanical stability,permeability,strength,and shear behavior of the rock *** can be used to reconstruct detailed 3D models of two separated rock fracture surfaces to characterize fracture roughness and physical aperture,which controls the fluid flow,hydromechanical and shear behavior of the rock *** research aimed to determine the optimal number of scale bars required to produce high-precision 3D models of a fracture surface.A workflow has been developed to define the physical aperture of a fracture using *** blocks of Kuru granite(25 cm×25 cm×10 cm)with an artificially induced fracture,were *** scaling 3D models,321 markers were used as ground control points(GCPs)with predefined distances on each *** the samples were wellmatched in their original positions,the entire block was *** data of the GCPs were extracted from the 3D model of the *** half was surveyed separately and georeferenced by GCPs and merged into the same coordinate *** fracture surfaces were extracted from the 3D models and the vertical distance between the two surfaces was digitally calculated as physical *** assessment of the photogrammetric reconstruction showed a 20-30 mm digital control distance accuracy when compared to known distances defined between *** attain this accuracy,the study found that at least 200 scale bars were ***,photogrammetry was employed to measure changes in aperture under normal *** results obtained from this approach were found to be in good agreement with those obtained using linear variable displacement transducers(LVDTs),with differences ran

关键词： Photogrammetry Physical aperture Rock fracture Predefined distances Markers

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Short-term prediction of on-street parking occupancy using multivariate variable based on deep learning

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Journal of Traffic and transportation engineering(English Edition) 2024年第1期11卷 28-40页

作者： Mengqi Lyu Yanjie Ji Chenchen Kuai Shuichao Zhang School of transportation Southeast UniversityNanjing 211189China Shandong Provincial Communications Planning and Design Institute Group Co. Ltd.Jinan 250101China School of civil and transportation engineering Ningbo University of TechnologyNingbo 315211China

Short-term prediction of on-street parking occupancy is essential to the ITS system,which can guide drivers in finding vacant parking *** the spatial dependencies and exogenous dependencies need to be considered simultaneously,which makes short-term prediction of on-street parking occupancy ***,this paper proposes a deep learning model for predicting block-level parking ***,the importance of multiple points of interest(POI)in different buffers is sorted by Boruta,used for feature *** results show that different types of POI data should consider different buffer *** based on the real on-street parking data,long short-term memory(LSTM)that can address the time dependencies is applied to predict the parking *** results demonstrate that LSTM considering POI data after Boruta selection(LSTM(+BORUTA))outperforms other baseline methods,including LSTM,with an average testing MAPE of 11.78%.The selection process of POI data helps LSTM reduce training time and slightly improve the prediction performance,which indicates that complex correlations among the same type of POI data in different buffer zones will also affect the prediction accuracy of *** there are more restaurants on both sides of the street,the prediction performance of LSTM(+BORUTA)is significantly better than that of LSTM.

关键词： Smart parking Parking occupancy Short-term prediction Long short-term memory Boruta

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Hydrodynamic Assessment of A New Nature-Based Armour Unit on Rubble Mound Breakwater for Coastal Protection

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China Ocean engineering 2024年第3期38卷 439-452页

作者： Ehsan SAFA Alireza MOJTAHEDI Abdolmajid MOHAMMADIAN Mohamad Ali Lotfollahi YAGHIN department of Water Resources engineering Faculty of Civil EngineeringUniversity of TabrizTabriz ***Iran Faculty of civil engineering University of OttawaOttawa K1H 8M5Canada

This research proposes a novel nature-based design of a new concrete armour unit for the cover layer of a rubblemoundbreakwater. Armour units are versatile with respect to shape, orientation, surface condition details, and ***, a detailed analysis is required to investigate the exact state of their hydraulic interactions and structuralresponses. In this regard, the performance results of several traditional armour units, including the Antifer cube,Tetrapod, X-block and natural stone, are considered for the first step of this study. Then, the related observed resultsare compared with those obtained for a newly designed (artificial coral) armour unit. The research methodology utilizesthe common wave flume test procedure. Furthermore, several verified numerical models in OpenFOAM code areused to gain the extra required data. The proposed armour is configured to provide an effective shore protection as anenvironmental-friendly coastal structure. Thus it is designed with a main trunk including deep grooves to imitate thetypical geometry of a coral type configuration, so as to attain desirable performance. The observed results and ananalytic hierarchy process (AHP) concept are used to compare the hydraulic performance of the studied traditionaland newly proposed (artificial coral) armour units. The results indicate that the artificial coral armour unit demonstratesacceptable performance. The widely used traditional armour units might be replaced by newer designs for betterwave energy dissipation, and more importantly, for fewer adverse effects on the marine environment.

关键词： rubble mound breakwater hydraulic interaction armour unit analytic hierarchy process numerical model

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Prediction of fracture initiation in cohesive soils based on data mining modelling and large-scale laboratory verification

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Underground Space 2024年第6期19卷 279-300页

作者： Weiping Luo Dajun Yuan Yannick Choy Hing Ng Dalong Jin Ping Lu Teng Wang department of Geotechnical engineering College of Civil EngineeringTongji UniversityShanghai 200092China Key Laboratory of the Ministry of Education for Urban Underground engineering Beijing Jiaotong UniversityBeijing 100044China department of civil and Environmental engineering National University of SingaporeSingapore 119077Singapore

Many empirical and analytical methods have been proposed to predict fracturing pressure in cohesive *** of them take into account three to four specific influencing factors and rely on the assumption of a failure *** this study,a novel data-mining approach based on the XGBoost algorithm is investigated for predicting fracture initiation in cohesive *** has the advantage of handling multiple influencing factors simultaneously,without pre-determining a failure mode.A dataset of 416 samples consisting of 14 distinct features was herein collected from past studies,and used for developing a regressor and a classifier model for fracturing pressure prediction and failure mode classification *** results show that the intrinsic characteristics of the soil govern the failure mode while the fracturing pressure is more sensitive to the stress *** XGBoost-based model was also tested against conventional approaches,as well as a similar machine learning algorithm namely random forest ***,several large-scale triaxial fracturing tests and an in-situ case study were carried out to further verify the generalization ability and applicability of the proposed data mining approach,and the results indicate a superior performance of the XGBoost model.

关键词： Fracturing pressure Failure mode Cohesive soil Data-mining Large-scale tests

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Incorporating mitigation strategies in machine learning for landslide susceptibility prediction

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Geoscience Frontiers 2024年第5期15卷 399-414页

作者： Hai-Min Lyu Zhen-Yu Yin Pierre-Yves Hicher Farid Laouafa Key Laboratory for Resilient Infrastructures of Coastal Cities(MOE) College of Civil and Transportation EngineeringShenzhen UniversityShenzhenChina department of civil and Environmental engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Research Institute of civil engineering and Mechanics(GeM) UMR CNRS 6183Ecole Centrale de NantesFrance National Institute for Industrial Environment and Risks(INERIS) Verneuil-en-HalatteFrance

This study proposes an approach that considers mitigation strategies in predicting landslide susceptibility through machine learning(ML)and geographic information system(GIS)*** models,such as random forest(RF),logistic regression(LR),and support vector classification(SVC)are incorporated into GIS to predict landslide susceptibilities in Hong *** consider the effect of mitigation strategies on landslide susceptibility,non-landslide samples were produced in the upgraded area and added to randomly created samples to serve as ML models in training *** scenarios were created to compare and demonstrate the efficiency of the proposed approach;Scenario I does not considering landslide control while Scenario II considers mitigation strategies for landslide *** largest landslide susceptibilities are 0.967(from RF),followed by 0.936(from LR)and 0.902(from SVC)in Scenario II;in Scenario I,they are 0.986(from RF),0.955(from LR)and 0.947(from SVC).This proves that the ML models considering mitigation strategies can decrease the current landslide *** comparison between the different ML models shows that RF performed better than LR and SVC,and provides the best prediction of the spatial distribution of landslide susceptibilities.

关键词： Machine learning Landslide susceptibility Spatial prediction Mitigation strategies

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