Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) was originally founded in 1959. The publisher of the journal is Wuhan University of Technology. JWUT first got the scopus license in the year 2001. The journal generally publishes all aspect of engineering sciences like: physics, chemistry, mathematics, and all sorts of general engineering.
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) (ISSN:2095-3844) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are in the following fields but not limited to: :
Free and forced vibrations of Z-reinforced sandwich plates stiffened by steel ribs are researched by experimental and mixed analytical–numerical techniques. A test sample of the plate is firstly manufactured and an underwater vibration test is conducted with a random white-noise force. Meanwhile, a mixed analytical–numerical method (MA-NM) is proposed, which uses an analytical homogenization for the Z-reinforced core and coupling finite element and boundary element (FE/BE) analyses for the plate. Natural frequencies given by the MA-NM are compared with ones from the detailed FE model. Forced vibration responses from the MA-NM are validated against the experimental data. Good agreements are obtained and the high accuracy of the MA-NM is demonstrated. Parameters influences are then analyzed through the MA-NM. The core material shows a larger effect on natural frequencies than the reinforcement material. Ribs at the orthotropic midlines greatly enhance the bend stiffness of the whole structure, and ribs at the surrounding sides mainly influence boundary conditions. When in-plane coordinates of the external force near the plate center, vibration responses have fewer resonance peaks and lower amplitudes, while the influence of the thickness direction coordinate could be ignored. The fluid loading reduces both natural frequencies and vibration responses.
Signal coordination is perceived by many agencies as an advantageous improvement to the community or corridor in consideration. In many cases, signal coordination techniques have proven to be successful in improving the quality of life and mobility through the area. This study determines the coordination system pattern of traffic signal for four consecutive intersections spaced at 780 m distance. Data for vehicles movement were collected using video camera during morning and evening peak hour with congested conditions. For evaluation of the possible coordination of signalized intersections a simulation model, TRANSYT7F, was used. The results show after coordinating, the amount of delay, travel time, and queue reduce.
As a convenient, economical, and eco-friendly travel mode, bike-sharing greatly improved urban mobility. However, it is often very difficult to achieve a balanced utilization of shared bikes due to the asymmetric spatio-temporal user demand distribution and the insufficient numbers of shared bikes, docks, or parking areas. If we can predict the short-run bike-sharing demand, it will help operating agencies rebalance bike-sharing systems in a timely and efficient way. Compared to the statistical methods, deep learning methods can automatically learn the relationship between the inputs and outputs, requiring less assumptions and achieving higher accuracy. This study proposes a Spatial-Temporal Graph Attentional Long Short-Term Memory (STGA-LSTM) neural network framework to predict short-run bike-sharing demand at a station level using multi-source data sets. These data sets include historical bike-sharing trip data, historical weather data, users’ personal information, and land-use data. The proposed model can extract spatio-temporal information of bike-sharing systems and predict the short-term bike-sharing rental and return demand. We use a Graph Convolutional Network (GCN) to mine spatial information and adopt a Long Short-Term Memory (LSTM) network to mine temporal information. The attention mechanism is focused on both temporal and spatial dimensions to enhance the ability of learning temporal information in LSTM and spatial information in GCN. Results indicate that the proposed model is the most accurate compared with several baseline models, the attention mechanism can help improve the model performance, and models that include exogenous variables perform better than the models that only consider historical trip data. The proposed short-term prediction model can be used to help bike-sharing users better choose routes and to help operators implement dynamic redistribution strategies.
The practice of crumb rubber derived from scrap tires to modify the mechanical properties of bituminous mixtures has become increasingly important in road engineering. In recent years, much research has been devoted to the influence of this waste material on pavement performance. This paper aims to address the influence of crumb rubber (CR) polymers on the performance of asphalt pavements. Thus, asphalt mixtures with varying percentages of CR mixed by the wet process were tested. The statistical analysis revealed that crumb rubber significantly increased the stiffness modulus, rutting resistance, and pavement resistance to moisture damage. The study concludes that an addition of 20% to 24% of crumb rubber modifiers to conventional asphalt mixture yields the most satisfactory results among other percentages of CR polymers. The study recommends the use of crumb rubber in pavement construction.
Transport activities contribute significantly to the air pollution and its impact on emissions is a key element in the evaluation of any transport policy or plan. Calculation of emissions has therefore gained institutional importance in the European Community. Recently, the scientific community has assessed evidence that exposure to outdoor air pollution causes lung cancer and increases the risk of bladder cancer. Because air pollution in urban areas is mainly caused by transportation, it is necessary to evaluate pollutant exhaust emissions from vehicles during their real-world use. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. To obtain emission factors several methods make use only of vehicle mean velocity, which can be easily obtained by vehicle flow and density in the road. Among them it is worth mentioning COPERT IV, MOBILE, INFRAS, MEET models that are widely used in the practice. In ARTEMIS FP project, a new statistical approach has been developed capable to consider more attributes than the simple mean speed to characterize driving behaviour, not only in the determination of driving cycles but also in the emission modelling. In this context, a meso scale emission model, named KEM, Kinematic Emission Model, able to calculate emission factor was developed. However, it is necessary to consider that the input to this model is, in any case, the driving cycle, and that to develop a quantitative method capable to determine the exact mix of driving cycle, on the basis of road characteristics and traffic management rules, results a very hard job. In addition a particular attention could be given to the slope variability along the streets during each journey performed by the instrumented vehicle. So in this paper we try to develop a second version of KEM model that dealt with the problem of describing and introducing same variables relative to road gradient variability in a quantitatively way. In the context of correlation study between driving cycles/emission/geographical location, we have to solve some problems for the reconstruction of GPS coordinates and altitude, during an experimental campaign realized with an instrumented car.
Bitumen supplies into Australia have become more diverse as importation of bitumen has become common and Australian refineries have been closed or reduced in their capacity. The products on which empirical links between bitumen properties and field performance were established are likely to have changed over the years. This has undermined the effectiveness of the empirical bitumen specifications used in Australia. Similar experiences in New Zealand and South Africa prompted the introduction of performance-based testing. In the USA, the multiple stress creep recovery (MSCR) test was developed as a high-temperature performance grading criterion. The MSCR test is performed using a dynamic shear rheometer. A number of these devices are already available in Australia. The test is simple and takes about 15 minutes to complete. The MSCR test was adopted by the USA for high temperature performance grading of binders because of its advantages over the traditional |G*|/sin δ. The MSCR was used to evaluate three samples of multigrade M1000 bitumen retained from a number of airport overlays. The M1000 samples assessed were found to be unsuitable at 76°C but suited to very heavy and extreme traffic loadings at 70°C and 64°C respectively. The MSCR testing of binders is recommended for high shear stress asphalt applications, such as airport surfaces.
Tunnel traffic flow has distinct microscopic characteristics compared with other road sections because of its special driving environment. Cellular automata (CA) is a method that uses cells as basic units to describe the overall behavior of complex systems. It has natural advantages for describing microscopic traffic flow characteristics. In this paper, a modified cellular automata model is established to study the characteristics and the spatial evolution mechanism of the traffic flow on a special section of the expressway such as expressway tunnel. Based on the model, the nucleation and dissolution of the traffic flow under different traffic density is simulated. It is found that the stop-and-go phenomenon becomes much more evident with the increase of the traffic density. The time takes by traffic nucleation to dissolution on high-speed lanes is less than that takes on the slow-speed lanes, and the visual blind are resulting from the drivers’ adaptation to luminosity at the entrance of a tunnel can apparently decrease the capacity of traffic flow at an expressway.
Since dwell time usually takes a large part of bus travel time, the large variability in dwell time always makes accurate prediction of arrival time\travel time difficult. On the other hand, Automatic Vehicle Location (AVL) and Automatic Passengers Counters (APC) systems are increasingly implemented for transit operation, which yield a vast amount of real time data. The emphasis of this research is to develop a bus dwell time model based on AVL and APC dynamic data, which is capable of providing real time information on bus arrival times. This model can be used for stop-based control strategies as well. The dwell time model established in this paper not only includes the number of passengers boarding and alighting, but also considers secondary factors like crowding and fare type. The number of boarding and alighting passengers is estimated by passenger arrival rate, bus headway, and capacity. Collection method, service mode, capacity restriction and occupancy of the vehicle are all taken into account in the model. Furthermore, the model is validated with the data of bus line Jiading 3 in Shanghai, China. It is compared with two previously developed models for the same route in four data sets. The results indicate that the models can be well applied in high demanded urban bus lines, especially in presence of high occupancy of vehicles. Since the effectiveness of estimation models is verified by statistical analysis methods, it will help in obtaining a reliable algorithm which can be adopted for bus arrival time/travel time prediction and assessing transit stop-based dynamic control actions.
The interest in minimising fuel consumption and greenhouse gas emissions among road specialists is increasing. Thus, methods for reducing asphalt concrete mixing and compaction tem‐ peratures by a few tens of degrees Celsius without compromising the long‐term performance has become a topic of significant interest. This study is focused on the analysis of warm mix asphalt (WMA) prepared with locally available materials in order to determine the suitable technology applicable to the specific traffic and climatic conditions of Romania. WMA was prepared using different warm mix additives (organic additives, chemical additive, and synthetic zeolite) at different mixing and compaction temperatures, and bitumen blends with these additives were analysed by carrying out the dynamic shear rheometer test and evaluating the penetration index. In conclusion it was noted that most additives did not lead to a significant change of bitumen`s characteristics, but the organic additive had a big influence on the bitumen`s properties. The characteristics of WMA are very similarto those of HMA. The mixing and compaction temperatures could be reduced by approximately 40 °C when WMA was blended with the additives without compromising the performance of the asphalt mixture, compared to hot mix asphalt.
The flexural behavioral properties of ultrahigh performance concrete (UHPC) low-profile T-beams reinforced with a combination of steel fibers and steel reinforcing bars were investigated in this paper. Five large scale T-beams were tested and analyzed regarding their defection, ductility, strain, curvature, load capacity and crack development. The experimental variables include the reinforcement ratio, the slenderness (length to diameter ratio) of the fiber reinforcements, and the fiber type. The experiments showed that all specimens exhibit flexural failure with the yielding of steel bars and excessive expansion of flexural crack, and the compression zone in the reinforced UHPC low-profile T-beam is not crushed because of the ultra high compressive strength and area of UHPC. In addition, it was concluded that using hooked-end fibers can effectively increase the specimen’s durability-based cracking load in comparison to straight fibers of same slenderness, whereas the reinforcement ratio and the slenderness of the fibers have little influence on this. Increasing the reinforcement ratio and using hooked-end instead of straight fibers increase the load capacity and bending stiffness of the specimen, as well as reduces the crack width at comparable applied load. A model was established to compute the ultimate capacity of UHPC low-profile T-beams and the prediction agrees well with the experimental results in the present and published investigations.
Copyright © 2022 All rights reserved | Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)
/Journal of Wuhan University of Technology (Transportation Science and Engineering)