Traffic Load Research Articles

Hot‐spot aware multicost‐based energy‐efficient routing protocol for WBANs

SummaryWireless body area networks (WBANs) are becoming widely considered in remote healthcare monitoring applications. However, WBAN nodes have limited resources; therefore, effective and reliable routing protocols are pivotal research challenges. Furthermore, balancing the traffic load among sensor nodes is also highly required to increase network stability. In recent years, many interesting routing solutions have been proposed for WBANs; however, the significant feature in terms of stability and energy in these solutions has not been sufficiently addressed. Therefore, in this context, the Hot‐Sspot Aaware Multicost‐based Energy‐efficient Routing (H‐SAMER) protocol is proposed in this paper. The suggested protocol used multieffective cost function for next‐hop node selection based on the data type, where the patient's data are categorized into three classes: normal data, on‐demand data, and emergency data. Furthermore, the H‐SAMER protocol adds awareness to the transmission of control packets by adding the cost value to the RREQ packets. Thus, the simulation scenario shows that the H‐SAMER saves energy 8.57%, 88%, 98%, 97%, and 100% greater than E‐HARP, EH‐RCP, CO‐LAEEBA, EECBSR, and ELR‐W, respectively. Moreover, the first node death of the proposed H‐SAMER is delayed to round number 7500, which proves H‐SAMER to be a stable and reliable effective solution for WBANs.

Deep-reinforcement-learning-based RMSCA for space division multiplexing networks with multi-core fibers [Invited Tutorial

The escalating demands for network capacities catalyze the adoption of space division multiplexing (SDM) technologies. With continuous advances in multi-core fiber (MCF) fabrication, MCF-based SDM networks are positioned as a viable and promising solution to achieve higher transmission capacities in multi-dimensional optical networks. However, with the extensive network resources offered by MCF-based SDM networks comes the challenge of traditional routing, modulation, spectrum, and core allocation (RMSCA) methods to achieve appropriate performance. This paper proposes an RMSCA approach based on deep reinforcement learning (DRL) for MCF-based elastic optical networks (MCF-EONs). Within the solution, a novel state representation with essential network information and a fragmentation-aware reward function were designed to direct the agent in learning effective RMSCA policies. Additionally, we adopted a proximal policy optimization algorithm featuring an action mask to enhance the sampling efficiency of the DRL agent and speed up the training process. The performance of the proposed algorithm was evaluated with two different network topologies with varying traffic loads and fibers with different numbers of cores. The results confirmed that the proposed algorithm outperforms the heuristics and the state-of-the-art DRL-based RMSCA algorithm in reducing the service blocking probability by around 83% and 51%, respectively. Moreover, the proposed algorithm can be applied to networks with and without core switching capability and has an inference complexity compatible with real-world deployment requirements.

Quantitative analysis of asphalt concrete’s tension-compression asymmetry effects on pavement response through 3D numerical modeling with dual viscoelastic model

Asphalt concrete (AC) exhibits noticeable tension-compression (TC) asymmetry, but it is typically considered isotropic in pavement design. This study aims to quantitatively evaluate the effect of AC’s TC asymmetry on pavement response under loading through numerical modeling. To achieve this objective, a temperature-dependent dual viscoelastic constitutive model was applied to incorporate AC’s TC asymmetry into pavement modeling. Besides, three pavement structure models, including one with thick AC layers, one with thin AC layers, and one with a Portland cement concrete (PCC) base, were developed. The responses of the three pavement structures under traffic and environmental loading conditions were simulated. Modeling results showed that AC’s TC asymmetry can significantly increase the vertical strain in AC, leading to higher stress concentration and larger deformation in AC layers. Unlike the conventional understanding that tensile strain concentrates at the bottom of AC layers, high tensile strains were observed in the top AC layers, especially for the pavement with thick AC layers or a PCC base, which may lead to top-down cracking. High tensile strains were observed on the granular subbase for the pavement with thin AC layers, which may induce bottom-up cracking. Besides, AC’s TC asymmetry also significantly increases the shear strains, especially the horizontal shear strain in AC layers, which may result in debonding and shoving distresses in AC layers. It was also noticed that the pavement response highly depends on its temperature and vehicular speed. A higher temperature or lower vehicular speed leads to more significant AC’s TC asymmetry as well as its effects on asphalt pavement’s response. The outcomes of this study are expected to help enhance the design and maintenance of more durable asphalt pavement.

The Performance of Modified Asphalt Mixtures with Different Lengths of Glass Fiber

AbstractOne practical option for modifying an asphalt mixture’s performance is to use additives. This will help the mixture perform better against the damaging effects of traffic, loads, and climatic variations. In this regard, glass fiber (GF) has drawn much interest because of its positive effect. Therefore, this paper attempts to study the effect of glass fiber length and content on the performance and strength of asphalt mixtures. It also aims to determine the optimum glass fiber content and the best glass fiber length of modified asphalt mixtures. An experimental program is carried out, which includes the Marshall test, volumetric properties, freeze-thaw splitting test, immersion Marshall test, and wheel tracking test to characterize related properties of glass fiber incorporated in asphalt mixtures. Seven different percentages (0, 0.25, 0.5, 0.75, 1, 1.25, and 1.5) of glass fiber by total weight of aggregates in three various lengths are used to design 19 asphalt mixtures. Based on the results obtained, the performance of the asphalt mixture was enhanced remarkably after adding glass fiber. The use of various lengths of glass fiber led to a better-quality asphalt mixture in terms of volumetric properties, moisture damage resistance, and permanent deformation resistance. Specifically, asphalt mixtures made with (0.5%) glass fiber illustrated the highest quality, and adding (20 mm) length of glass fiber was better than (10 mm and 30 mm) glass fiber lengths. The results also show that adding (10 mm and 30 mm) lengths of glass fiber can improve the resistance of asphalt mixtures to water damage and permanent deformation compared with the control mixture (M0). The findings indicate the applicability of 20 mm glass fiber length in asphalt mixtures to achieve better resistance against moisture and reduce the chance of irreparable permanent deformation under growing traffic loads and hot climate changes. Although the inclusion of glass fiber in asphalt mixtures led to a modest increase (6%) in overall cost, the effective improvement in performance and extension of the service life of the asphalt pavement constitute a convincing argument for this approach, making it an attractive option. Finally, it was concluded that a higher amount of glass fiber (i.e., > 0.5%) and a length greater than (20 mm) could diminish the positive effect of glass fiber to improve the properties of glass fiber asphalt mixtures.

Dynamic serviceability and safety reliability analysis of aging PC girder bridges with non-prestressed reinforcement considering concrete shrinkage, creep and stochastic vehicle load flows

Prestressed concrete (PC) bridges’ service performance displays time-dependency due to several factors including concrete shrinkage, creep, resistance degradation, and stochastic vehicle load flows. These non-stationary vehicle load flows, combined with concrete shrinkage, creep, and resistance degradation, result in sequential alterations of internal forces and deformations in simply supported PC girder bridges, ultimately influencing their dynamic reliability. This study proposes a robust methodology that considers the impact of traffic loading, shrinkage, and creep to analyze the dynamic reliability of simply supported PC girder bridges through the development of a load probability model. A stochastic model for truck loads is generated using motion measurement data, which can be used to calculate bridge internal forces and subsequent quantitative analysis of structural deformation due to shrinkage and creep. Subsequently, the formula for the first exceedance probability under resistance degradation is presented and validated through Monte Carlo simulation. Reliability analysis is conducted for both serviceability and load carrying capacity limit states to assess the impact of shrinkage, creep, and increased mean vehicle load on structural reliability. The proposed method offers the theoretical foundation and practical guidance for assessing the structural health status of in-service bridges, thereby providing valuable insights into their long-term performance and maintenance requirements.

Theoretical substantiation of system for organising preventive treatment of asphalt concrete road pavements

Introduction. Over the past 20 years, the fleet of vehicles in the Republic of Belarus has increased significantly, and, consequently, the intensity of traffic on roads with a proportional increase in wear and tear of their surfaces. The need to protect asphalt concrete pavements from premature destruction dictates the search for new technological solutions. To effectively protect asphalt concrete pavements from the complex effects of water and traffic loads in the autumn-winter and spring-winter periods, the author has developed and implemented one of the options for protecting asphalt concrete pavements of a highway – treating them with a hydrophobic preventive Protekt- 01composition.Materials and methods. The research used theoretical and practical results from the implementation of the developed hydrophobic prophylactic composition.Results. The article presents an overview of the state of the problem of preventing destruction of asphalt concrete pavements abroad and in the Republic of Belarus, an analysis of the measures taken to implement the developed hydrophobic preventive Protekt-01composition at transport infrastructure facilities, and also, based on the data obtained from production testing a ‘System for organizing preventive treatment’ has been proposed, which will be aimed at preventing the beginning and future destruction of the asphalt concrete pavement of highways and will be based on monitoring the technical condition of the control object, planning, organizing, implementing and managing preventive and repair measures using navigation equipment and software that makes it possible to optimize the balance of costs and road surface defects.Originality. Thus, based on the theoretical substantiation and the results of practical implementation of the developed composition, the following are proposed:- method for ensuring the operation of a control system for liquid road-building materials which enables to eliminate overconsumption of the distributed substance;- ‘System for organizing preventive treatment’, which enables to increase the service life of asphalt concrete pavement by 1.2–1.5 times.

Multi-TA model-based conditional privacy-preserving authentication protocol for fog-enabled VANET

The rapid growth of Vehicular Ad-hoc Networks (VANET), fueled by advancements in the Internet-of-Things, cloud computing, Intelligent Transportation Systems, and fog computing, has led to the introduction of fog node-based VANET to serve resource-constrained devices. In the traditional security models of VANET, due to the use of a centralized trusted authority, there is a chance of single-point-of-failure and service unavailable with the increased service access requests. Also, there was one-to-one communication between each roadside unit and trusted authority. This may increase the system complexity and increase the traffic load. To address these issues, a novel authentication protocol for fog-enabled VANET based on multiple trusted authority model is discussed which reduces the chance of service unavailability and single-point-of-failure as the entire traffic load is distributed among multiple sub-trusted authority. Due to the incorporation of fog node, a group of roadside units can be controlled centrally, where trusted authority does not need to perform individual authentication for each roadside unit. The proposed protocol's security is rigorously examined through both informal and formal security analysis. Additionally, the protocol exhibits enhanced security features, as demonstrated in a performance comparison section, showcasing its ability to meet the security and privacy requirements while incurring relatively low communication and computation and storage costs. Thus, the proposed protocol offers a secure and efficient authentication protocol for fog-enabled VANET.

Study of the engineering performance of pipes buried in the soil

This paper investigates the response of a flexible buried pipe to traffic load using laboratory experiments and numerical analysis. A series of laboratory tests and numerical simulations were performed to examine the effect of surface pressure, loading width, pipe type, pipe thickness, and burial depth on model response. In the experiments, a load was applied to the surface of a tank in which a pipe was buried. To gain a better understanding of the pipe's behavior, numerical simulations were performed using the finite element method; PLAXIS 2-D software. The results show that there is a good agreement between numerical and experimental test results. Furthermore, experimental and numerical analysis show that increasing burial depth reduces pipe deflection, increases soil surface settlement, and decreases pipe pressure, whereas increasing surface pressure increases all of the above parameters. Finally, equations were developed based on all numerical and experimental results to predict maximum stress on the pipe crown.

Factors Influencing Suffusion-Induced Delayed Displacement of River Bridge Piers

In recent years, local scour has occurred on the pier foundations of river bridges during heavy rain and river flooding, often resulting in bridge collapse. This study focused on the characteristic displacement, called “delayed displacement”, of the river bridge pier where the critical displacement of the piers was first observed several days after the flood when the train passed and not immediately after the flood. The authors hypothesized that one of the possible reasons for the delayed displacement is the suffusion of the supporting ground during the flood, followed by a compressive behavior due to the collapse of the soil skeleton under repeated traffic loads. Accordingly, this study performed erosion tests simulating flood and cyclic loading tests simulating train passage using a triaxial test apparatus to check the validity of this hypothesis. In some test cases, suffusion without any deformation occurred in the erosion test but deformed in the cyclic loading test just after the erosion test. This behavior matches the behavior of delayed displacement. It was also suggested that the risk of the delayed displacement becomes high when the soil skeleton was assumed to primarily comprise fine particles, and the void ratio and hydraulic gradient were high.

Contact area analysis of an asphalt-concrete boundary layer with X-ray computed tomography imaging

This study focusses on the bond between asphalt and concrete. The bond is a decisive factor for the transfer of traffic loads. A lack of bond between the layers can quickly reduce the load-bearing behavior and thus lead to pavement failure. In the literature, the bond between asphalt pavements and concrete substrates is usually analyzed using mechanical test methods. With mechanical test methods, the effects of interlocking, glue adhesion and friction, which have an effect at the layer boundary, are not considered individually. Based on previous findings, the aim of this study is to carry out a precise analysis of the bonding at the layer interface between concrete and asphalt using bitumen emulsion by means of measurements with a high-resolution X-ray computer tomography (CT). To determine the effect of the surface texture of the substrate, the investigations were carried out on milled and smooth surface textures. In addition to the variation of the substrate profiles, the influence of the application quantity of the bitumen emulsions C40 B5-S and C60 BP4-S was analyzed by spraying quantities of 90 g/m² and 180 g/m² bitumen after breaking. A newly developed method was used to determine the effective degree of gluing at the layer boundary, which allowed the bonding efficiency to be determined. The results of the calculated degree of gluing for the individual variants show that the highest degree of gluing of 61.94% is achieved with the smooth texture variant and high application quantity of bitumen emulsion. The lowest degree of gluing of 17.01% was achieved with the milled texture variant without the application of bitumen emulsion. Overall, the results showed that the degree of gluing was increased for both surface textures by applying the bitumen emulsion. Compared to the smooth texture, the milled textures exhibit a lower degree of gluing for both bitumen quantities, which could be explained by the distribution of the bitumen emulsions on the substrate profiles.

Optimizing Resource Allocation in Cloud Computing Using Machine Learning

Purpose: A key component of large-scale distributed computing is the allocation of resources, as computer networks cooperate to address complex optimization problems. To get the most out of computers in general, or throughput, is the goal of resource allocation in this case. When it comes to distributed computing, there are two main varieties: grid computing and cloud computing. In grid computing, many geographically dispersed clusters are linked and made available to the general public. Materials and Methods: We looked at Monte Carlo Tree Search and Long-Short Term Memory and examined how efficient they were. By maintaining consistent traffic patterns, the simulation demonstrated that MCTS performance was improved. However, such a strategy is difficult to implement due to the potential speed with which traffic patterns may alter. A successful service level agreement (SLA) was achieved, and the issue was shown to be fixable using LSTM. We compare the suggested model to different load-balancing algorithms to find the one that best allocates resources. Findings: The results show that compared to the state-of-the-art models, the suggested model achieves an accuracy rate that is 10-15% higher. The suggested model lowers the error percentage rate of the average request blocking likelihood of traffic load by around 9.5-10.2% when compared to the predictions of existing models. Therefore, the proposed method has the potential to enhance network utilization by reducing the amount of time required by memory and the central processing unit. Implications to Theory, Practice and Policy: One advantage of the new method is a more robust forecasting strategy in comparison to earlier models. Using firefly algorithms, future research will construct a cloud data center that employs a variety of heuristics and machine learning methodologies to load balance the energy cloud (Oshawa et al., 2022).

Autonomic end-to-end quality-of-service assurance over QKD-secured optical networks

Quantum key distribution (QKD) provides future-proof security for data communications over optical networks. Currently, sophisticated QKD systems are developed and the scale of QKD-secured optical networks (QKD-ONs) becomes larger. Given the complex network conditions and dynamic end-to-end security services in QKD-ONs, autonomic management and control becomes a promising paradigm to support end-to-end quality-of-service (QoS) assurance in an efficient and stable way without requiring human intervention. Hence, to enable and utilize the autonomic functionalities over QKD-ONs for realizing the end-to-end QoS assurance becomes a challenge. This work enhances the software defined networking (SDN) technique to tackle this challenge because SDN can add programmability and flexibility for QKD-ON’s management and control. A new architecture of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance is designed, where a knowledge engine with autonomic control loops is developed in the SDN controller. We present the autonomic end-to-end QoS assurance procedure, and the cross-layer collaborative QoS assurance (CLC-QA) strategy for implementing the autonomic functionalities in the network level over QKD-ONs. We also establish an experimental testbed of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance, and perform the numerical simulation to verify our proposed approaches. Experimental results demonstrate that our presented approaches can achieve the millisecond-level overall latency of 337 ms and 618 ms, during the first and second autonomic adjustment without human intervention in case of the autonomic QoS protection. Moreover, the CLC-QA strategy is evaluated under different traffic loads by being compared with the baseline strategy without cross-layer collaboration. It can improve 22.5% protection success ratio and save 5.7% average key consumption.

The rutting performance of cold bitumen emulsion mix using ground granulated blast furnace slag and lime as fillers

Abstract Rutting is a worldwide recognized distress in bituminous pavement caused by repetitive passage of traffic loads at high temperature. High air voids and poor early strength of cold bitumen emulsion mix (CBEM) can cause rutting deformation even at lower temperatures, making it undesirable to practitioners. The CBEM can be effectively modified by using hydraulic materials as filler. The present study examines the effect of ground granulated blast furnace slag (GGBFS) and lime as fillers on rutting characteristics of CBEM at varying temperatures (i.e., 40, 50, 60oC). The conventional stone dust (SD) filler was partially replaced by GGBFS. For further modification, lime was added in CBEM containing GGBFS. Initially mix were selected for rutting test based on the results obtained by Marshall stability, indirect tensile strength, retained Marshall stability, and tensile strength ratio tests. Based on these results, 80% of GGBFS was optimized for CBEM production. Incorporating 20% lime with 80% GGBFS in CBEM further improved the properties mentioned above. Both mixes were selected for the rutting test, along with CBEM containing 100% SD and CBEM containing 20% lime, which were also selected for comparison purposes. Wheel tracking device was used for rutting test on CBEM at varying temperatures. Based on results, it was found that increasing testing temperature increases the rutting deformation. However, the CBEM containing GGBFS and lime by 80% and 20% of total weight of filler in the mix, respectively, gave better rutting resistance at each testing temperature and provide less temperature sensitivity. So, this paper introduces the blended GGBFS and lime as a new composition in CBEM that provides improved laboratory strength, moisture susceptibility resistance, and rutting resistance.

Deformation characteristics of red-mud embankment under monotonic and cyclic loads

The rapid growth in the production of the red mud has led to the shortage of land for stockpiling in recent years. Although red mud has been considered as the filling material for embankments, the deformation characteristics of a red-mud embankment under traffic loads has not yet been clarified. To promote its application in embankment construction, a series of centrifuge model tests of red-mud embankment under monotonic and cyclic loads were conducted. The deformation and failure processes of red-mud embankment under normal and overproof traffic loads were analyzed. The results show that the deformation characteristics of red-mud embankment varied significantly depending on the value of the external load. The deformation induced by monotonic load was greater than that induced by the cyclic load of the normal traffic load. The monotonic and cyclic loads of normal traffic load induced similar influential areas, and their deformation processes can be divided into rapid and slow growth parts. Shear failure occurred in the red-mud embankment under overproof traffic load. The same load increment induced more deformation of red-mud embankment after failure. Under reasonable dry density and water content, the deformation of red mud was acceptable, thus meeting the engineering requirements of embankment construction.

A numerical method for calculating the long-term settlement of three-dimensional subgrade under numerous traffic loads

Settlement problems caused by various traffic loads significantly impact infrastructure sustainability. Accurately predicting the long-term settlement of subgrade is crucial for improving infrastructure resilience. This study determined the element strain of soil using an explicit strain model, based on the bounding surface model and associated flow rules. Using the method of generalized shear strain equivalent, a cyclic cumulative factor is proposed for determining the magnitude of cumulative strain increment. The direction of plastic strain increment was determined using the bounding surface model combined with associated flow rules. A cumulative strain calculation method integrating the bounding surface and explicit strain models under general stress states was established. This computational method, combined with equivalent finite elements, can be used for calculating the long-term settlement of three-dimensional subgrade under numerous cyclic loads at general stress states through a user-defined subroutine provided by the commercial finite element modeling (FEM) software. The reliability of the method was verified through unit tests.

Influences of number of geosynthetic reinforcement layers on soil arching under cyclic loading

Geosynthetic-reinforced pile supported (GRPS) embankments have been widely used in highways and railways on soft subsoil. During the operation period, these embankments are often subjected to cyclic loading, such as traffic loading. Considering that soil arching is a key load transfer mechanism in these embankments, the development of soil arching under cyclic loading is vital important to operational safety of these embankments. Conventional trapdoor system cannot represent actual conditions of soil arching in GRPS embankments because it have a forcibly-moved trapdoor and cannot simulate load-induced subsoil settlement. Hence, this paper used a self-moving trapdoor supported by compression springs that moved up and down dependent on its overburden pressure. To investigate influences of number of geosynthetic reinforcement layers on soil arching under cyclic loading, two self-moving trapdoor tests were conducted, including a single layer and two layers, where the total reinforcement stiffness were approximately same. The trapdoor test results show that the inclusion of two reinforcement layers with a fill layer of a certain height in between reduced surface settlement of the fill and tensile forces of reinforcement, as compared with a single reinforcement layer. It also enhanced soil arching effect and improved the stability of soil arching under cyclic loading.

Rigid Pavement Acceleration-Velocity Dynamic Behavior Induced by Traffic Load

Rigid Pavement Acceleration-Velocity Dynamic Behavior Induced by Traffic Load

Effects of pavement roughness on shakedown limits under moving traffic loadings

This study proposes a lower-bound shakedown analysis method for pavement systems under moving traffic loadings considering pavement roughness. The effects of key variables, including moving speed, wavelength irregularity, and the modulus and thickness of pavements, on the shakedown limit are discussed. The calculation results indicate that pavement roughness has a considerable effect on shakedown limits, which can be overestimated in some cases when the pavement roughness is not considered. The effect of pavement roughness on the shakedown limit of a homogeneous subgrade layer gradually decreases with increasing speed. Additionally, the shakedown limit decreases with wavelength irregularity, particularly under high-speed traffic loadings. Furthermore, the effect of pavement roughness on the shakedown limit of a two-layered pavement system is more pronounced for a larger pavement modulus and thickness and a lower moving speed.

Comprehensive Evaluation of Urban Road Network Capacity Using Fractal Theory in the Context of the Internet of Things

Abstract In order to make a good assessment of road traffic status, this paper proposes a comprehensive evaluation method of urban road network capacity based on soft computing under the background of Internet of Things. The focus of the research is to use a variety of soft computing technologies such as Hausdorff dimension simplification method, branch dimension measurement algorithm, multifractal method, etc., to analyze the overall traffic load and guide the traffic channelization in an optimal way, considering various factors comprehensively. The model helps to optimize infrastructure and reduce road traffic congestion. This avoids traffic congestion, ultimately reducing the carbon footprint and promoting a green environment. This method analyzes the network capacity, network load and corresponding conversion coefficient of all levels of highway. Based on the multi-component linear regression method, this paper evaluates the urban road network capacity, and constructs the urban road network capacity planning model according to the traffic volume constraints and travel time constraints. The test results show that under the application of this method, the road capacity of the planned route exceeds 4000 pcu. The pcu is a passenger vehicle unit that measures the extent to which different types of vehicles have an impact on road capacity. When the capacity of a planned road exceeds 4000 pcu, it means that the road can carry a large number of different types of vehicles at the same time, and the average operating speed of the line can reach 42.3 km/h. After 5 years of planning, the efficiency of road use is still above 75 %. It can be proved that this method can obtain the optimal traffic path through better route planning and avoid traffic congestion and pollution.

Prediction of the axial strain development curve of soft clay under dynamic triaxial conditions based on LSTM

The dynamic triaxial test results of soft clay show that a long-term cyclic traffic load lead to significant deformation of soft clay. Considering that the dynamic triaxial test data of soft clay under cyclic loading have apparent time series characteristics, the long short-term memory (LSTM) model can be used to predict the deformation law of soft clay. Through a dynamic triaxial test of Shanghai soft clay, time series data, such as axial stress, pore water pressure, and axial strain were obtained to establish the sample data of the LSTM model. The LSTM model is then used to predict the axial strain development curve. The results showed that the LSTM model had a good fitting precision for the sample data under different dynamic stresses and frequencies, and its accuracy was above 97% in all conditions. The prediction results can reproduce the fluctuation law of the axial strain under cyclic loads and can be used to study elastic and plastic strains. The research results can provide technical support for disaster prevention and control in soft clay.