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Biodegradability of bioplastics in different aquatic environments:A systematic review

Journal of environmental Sciences 2024年第8期142卷 169-181页

作者： Maria Cristina Lavagnolo Valentina Poli Anna Maria Zampini Valentina Grossule department of civil Environmental and Architectural Engineering-Laboratory of Environmental EngineeringUniversity of PadovaLungargine Rovetta 8Padova 35100Italy

Bioplastics were first introduced as environmentally friendly materials,with properties similar to those of conventional plastics.A bioplastic is defined as biodegradable if it can be decomposed into carbon dioxide under aerobic degradation,or methane and CO_(2)under anaerobic conditions,inorganic compounds,and new cellular biomass,by the action of naturally occurring *** definition however does not provide any information on the environmental conditions,timescale and extent at which decomposition processes should *** regard to the aquatic environment,recognized standards have been established to assess the ability of plastics to undergo biodegradation;however,these standards fail to provide clear targets to be met to allow labelling of a bioplastic as ***,these standards grant the user an extensive leeway in the choice of process *** these reasons,the comparison of results deriving from different studies is *** authors analysed and discussed the degree of biodegradability of a series of biodegradable bioplastics in aquatic environments(both fresh and salt water)using the results obtained in the laboratory and from on-site testing in the context of different research *** Oxygen Demand(BOD),CO_(2)evolution,surface erosion and weight loss were the main parameters used by researchers to describe the percentage of *** results showed a large variability both in weight loss and BOD,even when evaluating the same type of *** confirms the need for a reference range of values to be established with regard to parameters applied in defining the biodegradability of bioplastics.

关键词： Biodegradation Bioplastic Plastic Natural environment Plastic waste

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Evaluation of the coefficient of lateral stress at rest of granular materials under repetitive loading conditions

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Journal of Rock Mechanics and Geotechnical engineering 2024年第5期16卷 1709-1721页

作者： Heerym Han Hyunwook Choo Junghee Park department of civil and environmental engineering Hanyang UniversitySeoul04763South Korea department of civil and environmental engineering Incheon National UniversityIncheon22012South Korea

Although the internal stress state of soils can be affected by repetitive loading,there are few studies evaluating the lateral stress(or K_(0))of soils under repetitive *** study investigates the changes in K_(0) and directional shear wave velocity(V_(s))in samples of two granular materials with different particle shapes during repetitive loading.A modified oedometer cell equipped with bender elements and a diaphragm transducer was developed to measure the variations in the lateral stress and the shear wave velocity,under repetitive loading on the loading and unloading *** study produced the following results:(1)Repetitive loading on the loading path resulted in an increase in the K_(0) of test samples as a function of cyclic loading number(i),and(2)Repetitive loading on the unloading path resulted in a decrease in K_(0) according to *** shear wave velocity ratio(i.e.V_(s)(HH)/V_(s)(VH),where the first and second letters in parentheses corresponds to the directions of wave propagation and particle motion,respectively,and V and H corresponds to the vertical and horizontal directions,respectively)according to i supports the experimental observations of this ***,when the tested material was in lightly over-consolidated state,there was an increase in K_(0) during repetitive loading,indicating that it was the initial K_(0),rather than the loading path,which is responsible for the change in K_(0).The power model can capture the variation in the K_(0) of samples according to ***,the K_(0)=1 line acts as the boundary between the increase and decrease in K_(0) under repetitive loading.

关键词： Coefficient of lateral stress at rest Repetitive loading Granular materials Shear wave velocity Stiffness anisotropy

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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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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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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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Evaluation of the seismic behavior of reinforced concrete structures with flat slab-column gravity frame and shear walls through nonlinear analysis methods

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Earthquake engineering and engineering Vibration 2024年第3期23卷 713-726页

作者： M.A.Najafgholipour S.Heidarian Radbakhsh E.Erfani department of civil and environmental engineering Shiraz University of TechnologyShiraz ***Iran department of Building Civiland Environmental EngineeringConcordia UniversityMontréal H3G 1M8Canada

This paper presents an investigation of the seismic behavior of reinforced concrete(RC)structures in which shear walls are the main lateral load-resisting elements and the participation of flat slab floor systems is not considered in the seismic design *** this regard,the behavior of six prototype structures(with different heights and plan layouts)is investigated through nonlinear static and time history analyses,implemented in the OpenSees *** results of the analyses are presented in terms of the behavior of the slab-column connections and their mode of failure at different loading ***,the global response of the buildings is discussed in terms of some parameters,such as lateral overstrength due to the gravity flat slab-column *** to the nonlinear static analyses,in structures in which the slab-column connections were designed only for gravity loads,the slab-column connections exhibited a punching mode of failure even in the early stages of ***,the punching failure was eliminated in structures in which a minimum transverse reinforcement recommended in ACI 318(2019)was provided in the slabs at joint ***,despite neglecting the contribution of gravity flat slab-column frames in the lateral load resistance of the structures,a relatively significant overstrength was imposed on the structures by the gravity frames.

关键词： RC flat slab-column frames seismic behavior nonlinear analysis time history analysis

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Online learning-based model predictive trajectory control forconnected and autonomous vehicles: Modeling and physical tests

Journal of Intelligent and Connected Vehicles

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Journal of Intelligent and Connected Vehicles 2024年第2期7卷 86-96页

作者： Qianwen Li Peng Zhang Handong Yao Zhiwei Chen Xiaopeng Li School of environmental CivilAgricultural and Mechanical EngineeringUniversity of GeorgiaAthens 30602USA department of civil and environmental engineering University of Wisconsin–MadisonMadison 53706USA department of civil Architecturaland Environmental EngineeringDrexel UniversityPhiladelphia 19104USA

Motivated by the promising benefits of connected and autonomous vehicles (CAVs) in improving fuelefficiency, mitigating congestion, and enhancing safety, numerous theoretical models have been proposed to plan CAVmultiple-step trajectories (time–specific speed/location trajectories) to accomplish various operations. However, limitedefforts have been made to develop proper trajectory control techniques to regulate vehicle movements to follow multiplesteptrajectories and test the performance of theoretical trajectory planning models with field experiments. Without aneffective control method, the benefits of theoretical models for CAV trajectory planning can be difficult to harvest. This studyproposes an online learning-based model predictive vehicle trajectory control structure to follow time–specific speed andlocation profiles. Unlike single-step controllers that are dominantly used in the literature, a multiple-step model predictivecontroller is adopted to control the vehicle’s longitudinal movements for higher accuracy. The model predictive controlleroutput (speed) cannot be interpreted by vehicles. A reinforcement learning agent is used to convert the speed value to thevehicle’s direct control variable (i.e., throttle/brake). The reinforcement learning agent captures real-time changes in theoperating environment. This is valuable in saving parameter calibration resources and improving trajectory control accuracy.A line tracking controller keeps vehicles on track. The proposed control structure is tested using reduced-scale robot *** adaptivity of the proposed control structure is demonstrated by changing the vehicle load. Then, experiments on twofundamental CAV platoon operations (i.e., platooning and split) show the effectiveness of the proposed trajectory controlstructure in regulating robot movements to follow time-specific reference trajectories.

关键词： connected and autonomous vehicles(CAVs) reinforcement learning physical tests time-specific speed and location longitudinal and lateral control

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Evaluation of slope stability through rock mass classification and kinematic analysis of some major slopes along NH-1A from Ramban to Banihal, North Western Himalayas

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Journal of Rock Mechanics and Geotechnical engineering 2024年第1期16卷 167-182页

作者： Amit Jaiswal A.K.Verma T.N.Singh department of civil and environmental engineering Indian Institute of Technology PatnaPatna801106India

The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India’s socio-economic *** to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few *** of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the *** rock mass classification methods are generally used to assess the strength and deformability of rock *** study assesses slope stability along the NH-1A of Ramban district of North Western *** structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 *** evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present *** SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely *** stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1%gives two slopes as stable *** slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the *** value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR&SSR and RMR&GSI with correlation coefficient(R 2)value of 0.815 and 0.6866,***,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.

关键词： Rock mass classification Kinematic analysis Slope stability Himalayan road Static and dynamic conditions

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Estimating the frequency of traffic overloading on road bridges

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Journal of Traffic and Transportation engineering(English Edition) 2024年第4期11卷 776-796页

作者： Roberto Ventura Benedetto Barabino Giulio Maternini department of civil EnvironmentalArchitectural Engineering and MathematicsUniversity of BresciaBrescia 25123Italy

Load limits,which appear to be routinely exceeded by trucks,occasionally result in road bridge ***,predicting failures is crucial for safeguarding road *** studies have largely focused on forecasting bridge failure event probability using the reliability analysis method,whilst occasionally accounting for vehicular overloading *** recently,a study has investigated design traffic overloading event frequency using generalised linear regression models(GLRMs),including a power component and negative binomial regressions(NBRs).However,as far as the authors know,artificial neural network models(ANNMs)have never been applied to this *** paper is an attempt to fill in these *** a frequencybased metric of traffic overloading was adopted as a driver of failure ***,two alternative‘frequency'models were specified,calibrated,and *** former was based on a GLRM,the latter on ***,these models were compared using regression plots(RPs),measures of errors(Mo Es)and the ratio between the number of observed vs predicted design load overcoming events to evaluate their *** models analysed more than 2 million weigh-in-motion(WIM)data records from a pilot station on a bridge on a heavily used ring road in Brescia(Italy).Results showed that ANNMs outperformed *** have a higher correlation coefficient(between predicted and target frequencies),lower Mo Es,and a closer-to-unity ratio(between predicted and target frequencies).These findings may increase prediction accuracy of design traffic overloading events and give road authorities more effective traffic management to protect bridges from load hazards.

关键词： Road bridges Traffic load hazard Econometry Machine learning Weigh-in-motion Big-data analysis

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Automated,economical,and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

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Journal of Traffic and Transportation engineering(English Edition) 2024年第3期11卷 381-405页

作者： Jian Liu Fangyu Liu Linbing Wang department of civil and environmental engineering Virginia Polytechnic Institute and State UniversityBlacksburgVA 24061USA School of environmental CivilAgricultural and Mechanical EngineeringUniversity of GeorgiaAthensGA 30602USA Illinois Center for Transportation Department of Civil and Environmental EngineeringUniversity of Illinois Urbana-ChampaignUrbanaIL 61801USA

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO_(2)emissions during pavement construction and ***,the laboratory mix design process,which involves selecting aggregate gradation and binder content,is time-consuming and *** accelerate the traditional mix design procedure,this study presented a mix design procedure that can automatically determine gradation and binder content based on machine learning(ML)and a meta-heuristic ***,ML approaches were employed to model the relationship between volumetric properties(mixture bulk specific gravity(Gmb)and air void(VV))and both mixture component properties and mixture proportion,based on a dataset collected from literature with 660 mixture *** with the prediction of ML models and the modified multi-objective grey wolf optimization(MOGWO)algorithm,an automatic asphalt mix design was proposed to pursue three goals,including VV,cost,and CO_(2)*** results indicated that least squares support vector regression(LSSVR)and e Xtreme gradient boosting(XGBoost)achieved the highest prediction accuracies(correlation coefficient:0.92 for VV and 0.96 for Gmb).The MOGWO algorithm successfully found the 26 optimal mix designs for the case of VV *** ***_(2)*** to the traditional laboratory design,the optimal mixture with VV of4%achieves a cost saving of 2.46%and a reduction of 4.03%in carbon *** volumetric properties of the mixtures output by the approach also align closely with values measured in a laboratory.

关键词： Asphalt mix design Machine learning MOGWO CO_(2)emission Volumetric properties

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