Menampilkan 20 dari ~9524826 hasil · dari DOAJ, CrossRef, Semantic Scholar
T. Baumeister, L. S. Marks, E. Avallone
Babin Manandhar, Kayode Dunkel Vance, Danda B. Rawat et al.
Public transportation systems face numerous challenges like traffic congestion, inconsistent schedules, and variable passenger demand. These issues lead to delays, overcrowding, and reduced patron satisfaction. Digital twin (DT) technology is a promising innovation for improving public transportation systems by offering real-time virtual representations of physical systems. By integrating real-time data from various sources, digital twins can enable predictive analytics, optimize operations, and improve the overall performance of public transportation networks. This work explores the potential of digital twins to optimize operational efficiency, enhance passenger experiences, and support sustainable urban mobility. A comprehensive review of the existing literature was conducted by analyzing case studies, theoretical models, and practical implementations to assess the effectiveness of DTs in transit systems. While the benefits of DTs are significant, their successful implementation in bus transportation systems is impeded by several challenges like scalability limitations, interoperability issues, and technical complexities involving data integration and IT infrastructure. This paper discusses ways to overcome these challenges, which include using modular designs, microservices, blockchain for security, and standardized communication for better integration. It emphasizes the importance of collaboration in research and practice to effectively apply digital twin technology to public transit systems.
Zain Ul Abideen Tariq, Emna Baccour, Aiman Erbad et al.
Rapid growth in wireless data traffic and the increasing demand for secure, low-latency communication have driven research toward next-generation (6G) technology, which aims to provide ubiquitous, secure wireless connectivity. Reconfigurable Intelligent Surfaces (RIS) have emerged as a promising technology in 6G, offering a means of combating increasing physical layer security threats by smartly managing wireless channel conditions. This survey offers an in-depth review of RIS-assisted anti-jamming strategies in next-generation wireless communication networks, encompassing threats, solutions, and research challenges. We start by presenting the analysis of existing surveys and their research gaps in the area of the use of RIS for the security of wireless communications. Following this, we present core concepts of jamming, and the threats they pose across various wireless networks, challenges of state-of-the-art anti-jamming techniques, motivation for using RIS for anti-jamming, and its potential applications. The survey also examines state-of-the-art RIS-assisted countermeasures against jamming threats in wireless networks, some key lessons learned, and gaps identified. In conclusion, we identify key technical challenges and propose future research directions for RIS-assisted anti-jamming in next-generation wireless communication networks, underscoring the potential of RIS technology to enhance security and resilience in future wireless systems.
O. A. Bubnova, V. A. Miroshnyk, R. V. Markul et al.
Purpose. The aim of this study is to develop mathematical models for predicting the processes of contamination of the aeration zone and groundwater in the event of leachate leakage from a solid waste landfill. The mathematical models take into account typical hydrological parameters: porosity of the aeration zone, aquifer, filtration coefficient of the aeration zone, filtration coefficient of the underground aquifer, intensity of leachate infiltration into the aeration zone and underground aquifer. Methodology. A one-dimensional filtration equation and a one-dimensional mass transfer equation were used to model the process of infiltrate migration in the aeration zone. The modeling of the process of contamination of the underground aquifer, which receives infiltrate from the landfill, was carried out on the basis of a two-dimensional equation (planned model) of geomigration. For the numerical integration of the model equations, a variable-triangular finite-difference splitting scheme was used. The numerical integration of the two-dimensional geomigration equation is performed using the splitting scheme. The peculiarity of the proposed numerical models is that the value of the unknown function can be determined by an explicit formula. Findings. Numerical models have been developed to solve the complex problem of predicting the contamination of the aeration zone and underground flow in the case of infiltration of an impurity from a solid waste landfill. Originality. Numerical models of filtration and mass transfer of impurities in the case of migration of infiltrate from a municipal solid waste landfill through the aeration zone and into groundwater are proposed. To apply these mathematical models, standard hydrological information is required. The models are aimed at solving complex problems in the field of environmental safety and protection. They make it possible to determine the negative impact of landfills on the environment at the stage of justifying the location of future landfills and their size. Practical value. The proposed mathematical models use standard hydrological information, which is important for serial calculations in design organizations, and can be useful for assessing the impact of landfills on environmental pollution.
Deepty Jain, Smriti Bhatnagar, Vanshika Rathi et al.
Abstract Air pollution will likely increase as cities continue to intensify urban activities and expand their infrastructure. Delhi is one of the most polluted cities in the world. Yet, there is a lack of understanding of how the built environment (BE) strategies can address local air quality levels for the city. Additionally, the existing studies use the land use regression (LUR) technique, assuming independence between BE variables. We assessed the impact of BE variables measured at various spatial scales on Delhi's air pollutants (PM2.5, PM10, CO, NO2 and O3). This study used the Principal Component Regression (PCR) approach to account for the multicollinearity between BE variables. As per the analysis, PCR provided better estimates for PM10, PM2.5, and CO concentrations. LUR was found better for modelling NO2 and O3. The findings show that as built-up percentage and the metro station density increases the PM10 and CO levels are also likely to increase, while increasing green percentage is likely to result in decreasing pollutant concentrations. We also identify BE variables that affect a particular pollutant. Percentage institutional within 700 m buffer radii affects PM10, distance to CBD affects CO levels, and distance to the bus depot is affects both CO and NO2 levels. The PCR helped measure the joint effect of BE variables on pollutant concentrations in Delhi. Simultaneously modelling multiple air pollutants can help develop a better urban development strategy for addressing air pollution.
Jian-Yu Fu, Xiao Ge, Lei Chen et al.
To investigate the fatigue behaviour of stainless steel (SS) reinforcement, monotonic tensile and cyclic fatigue loading tests on 1.4362 duplex SS bars with diameters of 12 mm, 16 mm, and 20 mm are conducted. To keep the characteristics of reinforcement used in engineering construction, the specimens remain unprocessed. Two loading schemes for cyclic tests are considered in this work: (i) constant strain-amplitude, and (ii) variable strain-amplitude. The Ramberg-Osgood model was used to fit the experimental results. The strain-based and energy-based fatigue life equations are obtained. The strain-based fatigue life equation is compared with the present fatigue life estimation equations. Moreover, the ReinforcingSteel material model in OpenSees is calibrated with the experimental data. The results show that SS bars under cyclic experience hardening followed by softening. The bar diameter does not significantly affect the fatigue life prediction. The modified fatigue life equation suggests that SS bars have better fatigue resistance than conventional steel (CS) bars. The numerical analysis indicates that the calibrated steel material model (i.e. ReinforcingSteel) can produce a good simulation of SS bars under cyclic loading. It can improve the accuracy of numerical models of concrete components reinforced by SS bars.
Fei Dai, Yawen Chen, Zhiyi Huang et al.
In the realm of parallel and distributed computation, All-gather operation, a process where each node in a distributed system gathers data from all others, is pivotal. This operation underpins various high-performance computing (HPC) applications, notably in distributed deep learning (DL), by enabling model and hybrid parallelisms. Although optical interconnection networks promise unmatched bandwidth and reliability for data transfers between distributed nodes, most current All-gather algorithms remain optimized for electrical interconnects, leading to suboptimal performance in optical contexts. This paper proposes “OpTree”, an advanced scheme distinctly designed for All-gather operation in optical interconnect systems. OpTree constructs an optimal <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-ary tree that minimizes communication time by determining the optimal number of communication stages. A comprehensive comparison between OpTree’s communication steps and existing All-gather algorithms is provided. Theoretical insights reveal that OpTree substantially curtails communication steps within optical interconnects. Constraints imposed by OpTree on optical communication are also elaborated. Empirical evaluations, through rigorous simulations, establish that: 1) OpTree is effective in generating an optimal m-ary tree for minimizing communication time. 2) For a 1024-node optical ring system, OpTree cuts communication time by 72.97%, 93.15%, and 86.32% against WRHT, Ring, and Neighbor Exchange (NE) schemes, respectively, tested over different message sizes. 3) With varying node counts, the reductions stand at 42.27%, 92.74%, and 85.49% against the same counterparts. 4) As the number of wavelengths increases, communication time further diminishes.
Amr E. Aboeleneen, Alaa A. Abdellatif, Aiman M. Erbad et al.
Recent advancements in Software Defined Networks (SDN), Open Radio Access Network (O-RAN), and 5G technology have significantly expanded the capabilities of wireless networks, extending beyond mere data transmission. This progression has led to the emergence of Virtual Networks (VN) and Network Slicing, enabling industries to enhance their services and applications by establishing virtual networks that utilize shared physical infrastructure. Many works in the literature have considered optimizing the allocation of on-demand slices, assuming the absolute availability of resources and their accurate load. However, accurately allocating future network slices remains challenging due to the error in load prediction, diverse Key Performance Indicators (KPIs), resource price variations, and the potential for over- or under-provisioning. This study presents a two-phase intelligent approach to address these challenges. The framework proactively predicts different slice loads while considering prediction errors in optimizing future slices with varied KPIs in a cost-efficient manner. Specifically, our method utilizes historical load data per service and employs AI-based forecasts for service load prediction. Subsequently, it employs a Deep Reinforcement Learning (DRL) agent on O-RAN’s virtual Control Unit (vCU) and virtual Distributed unit (vDU) to correct errors in prediction and optimize the cost of slice allocation based on service KPI requirements, ultimately pre-allocating future network slices at reduced costs. Through experimental validation against various baselines and state-of-the-art solutions, we demonstrate the efficacy of our proposed solution, achieving a notable reduction (37-51%) in the average cost of allocated slices while inquiring about (1.5-7%) of additional resources compared to the state-of-the-art..
Luke Pollock, Graham Wild
Guoxuan Han, Jingbin Zhang, Haojie Sun et al.
Rock-filled concrete (RFC) has good performance in terms of energy savings, cost reduction, and CO<sub>2</sub> emissions as a novel massive concrete construction technology. There have been studies into replacing natural rocks in RFC with large blocks of solid waste, and this method has been used on several construction sites. However, the granular and powdery solid waste utilized in RFC is limited, as a consequence of the special requirement of self-compacting concrete (SCC) in RFC. The goal of this paper is to increase the amount of granular and powdery solid waste in RFC. Iron ore tailing (IOT) and phosphogypsum (PG) were used separately as granular and powdery solid waste. The modified PG, ground blast-furnace slag (GBFS), steel slag, and cement clinker are combined to form parathion gypsum slag cement in a specific proportion, with the ratio of PG, GBFS, steel slag, and cement being 47:47:2:2. To replace the natural rocks in RFC, artificial rockfills made of IOT and parathion gypsum slag cement are used to increase the dosage of solid waste. The artificial rockfills were formed using three methods: compressing, roller compacting, and normal vibrating. When the compressive strength and material costs of the three types of artificial rockfills are compared, the compressing method is the best for maximizing the IOT. In artificial rockfills, the mass fraction of granular solid waste is 83.3%, and the mass fraction of total solid waste is 99.3%.
YANG Guang-qing 1, 2, WANG Xin 1, 3, WANG Xi Zhao 4, JIN Jin Zhao 5, ZHANG Chao 5
Based on the field tests, the influences of pile spacing and reinforcement form on the mechanical behavior of pile-supported reinforced embankment are studied. The soil pressures at the top of the pile, the soil stresses between the piles and the deformations of the geogrid at the center line of embankment, 10 m to the right of the center line and shoulder vertical line, are monitored. The variation of stresses of piles and soil, the variation of loads on cross section of subgrade and the deformation laws of geogrid of cross section of subgrade are analyzed. The results show that the critical height of embankment is 1~1.5 times the net spacing of piles. From the embankment center line to the shoulder direction, the stress reduction coefficient increases gradually, and the stress concentration effect decreases gradually. From the embankment center line to the shoulder direction, the deformation of geogrid decreases gradually. The load transfer of pile-supported embankment is mainly based on soil arching effect and supplemented by membrane effect. The test results are compared with the calculated ones of five theoretical methods to evaluate the applicability of the five methods.
Wen Li, Hongying Zhang, Zhaoguo Huang et al.
The purpose of this research is to find a traffic light timing optimization scheme. During the research, an intersection between Xi’an Mingguang road and the Fourth FengCheng road was chosen to analyze the crossing time distribution of pedestrians who were separated from west-to-the-right-turn vehicles during which the method of breaking off both ends of pedestrian green light signals was used. The VISSIM software was used for traffic simulation, aimed at improving traffic volume and right-turning vehicle average speed for less vehicle queuing delays, less human-vehicle conflicts, and better security for pedestrians without excessive interruption on their street crossing efficiency. The optimal scheme is obtained and the result shows that (1) the number of passing vehicles remains unchanged, with the queuing delay reduced by 5.78% and crosswalk passing speed increased by 19.01% compared with the original one. (2) As the scheme effect is positively correlated with the increase of right turn vehicle numbers, the scheme could be adopted for urban traffic management based on the local situation, which is not only in peak traffic hours but also in the flat peak time to ensure vehicle efficiency and pedestrian safety in the light of “vehicle yielding to pedestrians” regulation. (3) The scheme could also be adopted in cities with no “vehicle yielding to pedestrians” policy for both people-vehicle separation and pedestrian safety when crossing streets.
Hongwei Liu
In order to analyze the application effect of bridge pile foundation in Yushu permafrost area, this paper uses the research methods of theoretical analysis, model testing, and numerical simulation to collect soil samples in the Yushu area, study various indicators of frozen soil, simulate different frozen soil foundations in the Yushu area, and study different seismic waves under the influence of different temperatures. The seismic response mechanism of bridge pile foundations in the Yushu permafrost region under the influence of loading mode, soil material, and single pile in different permafrost regions is analyzed, and the dynamic response and mechanical nonlinear characteristics of displacement and deformation under different seismic forces are obtained. The simulation results show that under the influence of different temperatures, different seismic wave loading methods, and different soil quality single piles, the bridge pile foundation in the Yushu permafrost area has obvious seismic response laws and obvious mechanical nonlinear characteristics. Under the influence of permafrost material, most single piles have response coefficients of between 0 and 1.
Fayiz Alfaverh, M. Denaï, Yichuang Sun
© 2021 The Authors. IET Electrical Systems in Transportation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/
Bingzhe Zhang, Kehai Wang, Guanya Lu et al.
Laminated rubber bearings are commonly adopted in small‐to‐medium span highway bridges in earthquake‐prone areas. The accurate establishment of the mechanical model of laminated rubber bearings is one of most critical steps for the bridge seismic response analysis. A new constitutive model of bearing based on the artificial neural network (ANN) technique is established through the static cyclic test of laminated rubber bearings, considering the bearing initial stiffness, friction coefficient, and other parameters such as the bearing sectional area, height, loading velocity, vertical load, and aging time. Combined with the ANN method, the ANN‐based bridge seismic demand model is built and applied to the rapid evaluation of the bridge seismic damage. The importance of the bearing affecting design factors in the bridge seismic demands are ranked. The results demonstrated that the dimensions of the bearing and vertical load are the main factors affecting the bearings constitutive model. Based on the partial dependency analysis with the ANN‐based bridge seismic demand model, it is concluded that the height of bearing is the key design parameter which affects the bridge seismic response the most. The ANN seismic demands model can fit the complex function relationship between various factors and bridge seismic response with high precision, so as to achieve the rapid evaluation of bridge seismic damage.
Jing Li, Yingluo Zhou, Weibing Wang et al.
Abstract Simple methods for the collection and transportation of water droplets can solve complex problems, but developing technologies to achieve this is a challenge. To this end, widespread attention in recent years has focused on the preparation and application of superhydrophobic surfaces. Inspired by the structures of trichomes (hairs) of Sarracenia, a genus of carnivorous pitcher plants, we report a bionic high-low rib-like microstructure with superhydrophobic and directional water transport properties. At the same time, we can accelerate fog-collection efficiency by preparing a surface enabling directional slip of liquid. This work provides a good strategy for liquid transportation and fog collection, which has broad application prospects in the collection of rainwater in desert areas and the transmission of microfluidics in mechanical engineering.
T. Holstein, G. Dodig-Crnkovic, Patrizio Pelliccione
As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.
Valentin Ivanov, Klaus Augsburg, Carlos Bernad et al.
The presented paper introduces a new methodology of experimental testing procedures required by the complex systems of electric vehicles (EV). This methodology is based on real-time connection of test setups and platforms, which may be situated in different geographical locations, belong to various cyber-physical domains, and are united in a global X-in-the-loop (XIL) experimental environment. The proposed concept, called XILforEV, allows exploring interdependencies between various physical processes that can be identified or investigated in the process of EV development. The paper discusses the following relevant topics: global XILforEV architecture; realization of required high-confidence models using dynamic data driven application systems (DDDAS) and multi fidelity models (MFM) approaches; and formulation of case studies to illustrate XILforEV applications.
Yanan Dong, Jing Wang, Zhengfang Wang et al.
Diagnosing tunnel lining structural damages is vital to ensure safe tunnel operations. However, the detection of multiple defect is challenging task due to the size imbalance between cracks, spalling, and backgrounds. Currently, deep-learning-based methods for multiple defect are dependent on multiple-stage networks, which have limited their scalability and complex frame working processes. To accurately recognize the multiple defect at the pixel-level using only one-stage networks, a new method was proposed, which integrated the basic SegNet with a focal loss function, and was referred to as an FL-SegNet method. The focal loss function was adopted to address the problem of the size imbalance by down-weighing the losses assigned to the well-classified samples, and then the training was focused on the hard samples. Furthermore, comparative experiments were performed to evaluate the performances of the different methods. The experimental results demonstrated that FL-SegNet method was capable of accurately predicting the profiles of small-sized cracks and overlapping damages even under various noise conditions, and successfully outperformed the two-stream method and the basic SegNet method in this regard. The performance metrics (MPA and MIoU) of the FL-SegNet method were significantly higher than those of other multiple defect detection approaches in different scenarios (images with small-sized damages attained to 81.53% and 69.86%, increased by 11.99 % and 4.88% compared with two-stream method, and increased by 17.78% and 7.69% compared with basic SegNet). Therefore, this paper provides an effective solution for the future detection of multiple defect in tunnel linings.
J. Ni, Yu Jiang, Xuanxuan Bi et al.
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