Transactions of Nanjing University of Aeronautics & Astronautics
Volume 37,Issue 2,2020 Table of Contents
2020, 37(2):175-186.
DOI: 10.16356/j.1005-1120.2020.02.001
Abstract:
Based on ADS-B surveillance data, this paper proposes a multi-unmanned aerial vehicle(multi-UAV) collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution, thus to provide early warning of possible conflicts. To address the problem of multi-UAV conflict, the basic ant colony algorithm is introduced. The conflict simplification model of the traditional basic ant colony algorithm is optimized by adding a speed regulation strategy. A multi-UAV conflict resolution scheme is presented based on speed regulation and heading strategies. The ant colony algorithm is improved by adding angle information and a queuing system. The results show that the improved ant colony algorithm can provide multi-UAV joint escape routes for a multi-UAV conflict situation in airspace. Unlike the traditional ant colony algorithm, our approach converges to the optimization target. The time required for the calculation is reduced by 43.9%, and the total delay distance caused by conflict resolution is reduced by 58.4%.
Based on ADS-B surveillance data, this paper proposes a multi-unmanned aerial vehicle(multi-UAV) collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution, thus to provide early warning of possible conflicts. To address the problem of multi-UAV conflict, the basic ant colony algorithm is introduced. The conflict simplification model of the traditional basic ant colony algorithm is optimized by adding a speed regulation strategy. A multi-UAV conflict resolution scheme is presented based on speed regulation and heading strategies. The ant colony algorithm is improved by adding angle information and a queuing system. The results show that the improved ant colony algorithm can provide multi-UAV joint escape routes for a multi-UAV conflict situation in airspace. Unlike the traditional ant colony algorithm, our approach converges to the optimization target. The time required for the calculation is reduced by 43.9%, and the total delay distance caused by conflict resolution is reduced by 58.4%.
2020, 37(2):187-196.
DOI: 10.16356/j.1005-1120.2020.02.002
Abstract:
In a large-volume, high-density traffic background, air traffic manifests fluid-like microscopical characteristics. The characteristics are formed by the micro tailing actions between individual aircraft. Aircraft headway refers to the time interval between successive flying aircraft in air traffic flow, which is one of the most important characteristics of air traffic flow. The variation in aircraft headway reveals the air traffic control behaviour. In this paper, we study the characteristics of air traffic control behaviours by analyzing radar tracks in a terminal maneuvering area. The headway in arrival traffic flow is measured after the determination of aircraft trailing relationships. The headway evolutionary characteristics for different control decisions and the headway evolutionary characteristics in different phase-states are discussed, and some interesting findings are gotten. This work may be helpful for scholars and managers in understanding the intrinsic nature of air traffic flow and in the development of intelligent assistant decision systems for air traffic management.
In a large-volume, high-density traffic background, air traffic manifests fluid-like microscopical characteristics. The characteristics are formed by the micro tailing actions between individual aircraft. Aircraft headway refers to the time interval between successive flying aircraft in air traffic flow, which is one of the most important characteristics of air traffic flow. The variation in aircraft headway reveals the air traffic control behaviour. In this paper, we study the characteristics of air traffic control behaviours by analyzing radar tracks in a terminal maneuvering area. The headway in arrival traffic flow is measured after the determination of aircraft trailing relationships. The headway evolutionary characteristics for different control decisions and the headway evolutionary characteristics in different phase-states are discussed, and some interesting findings are gotten. This work may be helpful for scholars and managers in understanding the intrinsic nature of air traffic flow and in the development of intelligent assistant decision systems for air traffic management.
2020, 37(2):197-208.
DOI: 10.16356/j.1005-1120.2020.02.003
Abstract:
A new meta-heuristic approach is proposed in this paper based on a new composite dispatching rule to tackle the aircraft landing problem (ALP). First, the ALP is modeled as a machine scheduling problem with the objective of minimizing the total penalty, i.e., total weighted earliness plus total weighted tardiness. Second, a composite dispatching rule, minimized penalty with due dates and set-ups (MPDS), is presented to determine the landing sequence. Then, an efficient heuristic approach is proposed to solve the problem by integrating the MPDS rule and CPLEX solver. In the first stage, the landing sequence is established based on the proposed MPDS rule. In the second stage, landing time is optimized using CPLEX solver. Next, a new meta-heuristic strategy is introduced into the heuristic approach by conducting the local search from the potential landing sequences, which are generated by the proposed MPDS rule. Finally, the performance of the proposed approach is evaluated using a set of benchmark instances taken from the OR library. The results demonstrate the effectiveness and efficiency of the proposed approaches.
A new meta-heuristic approach is proposed in this paper based on a new composite dispatching rule to tackle the aircraft landing problem (ALP). First, the ALP is modeled as a machine scheduling problem with the objective of minimizing the total penalty, i.e., total weighted earliness plus total weighted tardiness. Second, a composite dispatching rule, minimized penalty with due dates and set-ups (MPDS), is presented to determine the landing sequence. Then, an efficient heuristic approach is proposed to solve the problem by integrating the MPDS rule and CPLEX solver. In the first stage, the landing sequence is established based on the proposed MPDS rule. In the second stage, landing time is optimized using CPLEX solver. Next, a new meta-heuristic strategy is introduced into the heuristic approach by conducting the local search from the potential landing sequences, which are generated by the proposed MPDS rule. Finally, the performance of the proposed approach is evaluated using a set of benchmark instances taken from the OR library. The results demonstrate the effectiveness and efficiency of the proposed approaches.
2020, 37(2):209-222.
DOI: 10.16356/j.1005-1120.2020.02.004
Abstract:
Four-dimensional trajectory based operation (4D-TBO) is believed to enhance the planning and execution of efficient flights, reduce potential conflicts and resolve upcoming tremendous flight demand. Most of the 4D trajectory planning related studies have focused on manned aircraft instead of unmanned aerial vehicles (UAVs). This paper focuses on planning conflict-free 4D trajectories for fixed-wing UAVs before the departure or during the flight planning. A 4D trajectory generation technique based on Tau theory is developed， which can incorporate the time constraints over the waypoint sequence in the flight plan. Then the 4D trajectory is optimized by the particle swarm optimization (PSO) algorithm. Further simulations are performed to demonstrate the effectiveness of the proposed method, which would offer a good chance for integrating UAV into civil airspace in the future.
Four-dimensional trajectory based operation (4D-TBO) is believed to enhance the planning and execution of efficient flights, reduce potential conflicts and resolve upcoming tremendous flight demand. Most of the 4D trajectory planning related studies have focused on manned aircraft instead of unmanned aerial vehicles (UAVs). This paper focuses on planning conflict-free 4D trajectories for fixed-wing UAVs before the departure or during the flight planning. A 4D trajectory generation technique based on Tau theory is developed， which can incorporate the time constraints over the waypoint sequence in the flight plan. Then the 4D trajectory is optimized by the particle swarm optimization (PSO) algorithm. Further simulations are performed to demonstrate the effectiveness of the proposed method, which would offer a good chance for integrating UAV into civil airspace in the future.
2020, 37(2):223-231.
DOI: 10.16356/j.1005-1120.2020.02.005
Abstract:
Air route network is the carrier of air traffic flow, and traffic assignment is a method to verify the rationality of air route network structure. Therefore, air route network generation based on traffic assignment has been becoming the research focus of airspace programming technology. Based on link prediction technology and optimization theory, a bi-level programming model is established in the paper. The model includes an upper level of air route network generation model and a lower level of traffic assignment model. The air route network structure generation incorporates network topology generation algorithm based on link prediction technology and optimal path search algorithm based on preference, and the traffic assignment adopts NSGA-III algorithm. Based on the Python platform NetworkX complex network analysis library, a network of 57 airports, 383 nodes, and 635 segments within China Airspace Beijing and Shanghai Flight Information Regions and 187 975 sorties of traffic are used to simulate the bi-level model. Compared with the existing air route network, the proposed air route network can decrease the cost by 50.624%, lower the flight conflict coefficient by 33.564%, and reduce dynamic non-linear coefficient by 7.830%.
Air route network is the carrier of air traffic flow, and traffic assignment is a method to verify the rationality of air route network structure. Therefore, air route network generation based on traffic assignment has been becoming the research focus of airspace programming technology. Based on link prediction technology and optimization theory, a bi-level programming model is established in the paper. The model includes an upper level of air route network generation model and a lower level of traffic assignment model. The air route network structure generation incorporates network topology generation algorithm based on link prediction technology and optimal path search algorithm based on preference, and the traffic assignment adopts NSGA-III algorithm. Based on the Python platform NetworkX complex network analysis library, a network of 57 airports, 383 nodes, and 635 segments within China Airspace Beijing and Shanghai Flight Information Regions and 187 975 sorties of traffic are used to simulate the bi-level model. Compared with the existing air route network, the proposed air route network can decrease the cost by 50.624%, lower the flight conflict coefficient by 33.564%, and reduce dynamic non-linear coefficient by 7.830%.
2020, 37(2):232-241.
DOI: 10.16356/j.1005-1120.2020.02.006
Abstract:
With the continuous increase in the number of flights, the use of airport collaborative decision-making（A-CDM） systems has been more and more widely spread. The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft block-out. The spatial-temporal-environment deep learning (STEDL) model is presented to improve the prediction accuracy of departure aircraft taxi-out time. The model is composed of time-flow sub-model (airport capacity, number of taxiing aircraft, and different time periods), spatial sub-model (taxiing distance) and environmental sub-model (weather, air traffic control, runway configuration, and aircraft category). The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%. The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.
With the continuous increase in the number of flights, the use of airport collaborative decision-making（A-CDM） systems has been more and more widely spread. The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft block-out. The spatial-temporal-environment deep learning (STEDL) model is presented to improve the prediction accuracy of departure aircraft taxi-out time. The model is composed of time-flow sub-model (airport capacity, number of taxiing aircraft, and different time periods), spatial sub-model (taxiing distance) and environmental sub-model (weather, air traffic control, runway configuration, and aircraft category). The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%. The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.
2020, 37(2):242-262.
DOI: 10.16356/j.1005-1120.2020.02.007
Abstract:
Airway networks are the basic carriers of air traffic. Characterizing airway networks will significantly improve the operating efficiency of aviation. This study is targeted at the airway network composed of 1 479 waypoints in 2018 of China. Together with spatial structures, traffic flow characteristics, and the dominating traffic flow, four airway network models are constructed from the perspective of complex networks, including physical airway network, airway traffic network, directed airway traffic network, and dominance-based directed airway traffic network. Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices, and the differences of these indices among different networks are investigated. Thereby, composite indices are proposed. Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship, and the distributions of indices among different networks are significantly different. Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes; some waypoints display large results in multiple composite indices but low traffic flows, and other waypoints only perform well in certain composite indices. The importance levels of waypoints are divided, by the K-means method based on degree composite index, betweenness composite index and closeness composite index, into three levels, and the reasonableness of clustering results is validated by the statistical results of traffic flows, airport number, and flight delay.
Airway networks are the basic carriers of air traffic. Characterizing airway networks will significantly improve the operating efficiency of aviation. This study is targeted at the airway network composed of 1 479 waypoints in 2018 of China. Together with spatial structures, traffic flow characteristics, and the dominating traffic flow, four airway network models are constructed from the perspective of complex networks, including physical airway network, airway traffic network, directed airway traffic network, and dominance-based directed airway traffic network. Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices, and the differences of these indices among different networks are investigated. Thereby, composite indices are proposed. Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship, and the distributions of indices among different networks are significantly different. Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes; some waypoints display large results in multiple composite indices but low traffic flows, and other waypoints only perform well in certain composite indices. The importance levels of waypoints are divided, by the K-means method based on degree composite index, betweenness composite index and closeness composite index, into three levels, and the reasonableness of clustering results is validated by the statistical results of traffic flows, airport number, and flight delay.
2020, 37(2):263-273.
DOI: 10.16356/j.1005-1120.2020.02.008
Abstract:
To quantify unmanned aerial vehicle (UAV) flight risks in low-altitude airspace, we analyze the factors of UAV flight risks from three aspects: flight conflict, flight environment, and traffic characteristics. The aerial risk index and ground risk index of the UAV are constructed, the index screening model and the UAV flight risk assessment model are established, and a UAV flight risk assessment model based on K-means clustering has been proposed. Meanwhile, numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively, but also provide technical support for UAV risk management and control.
To quantify unmanned aerial vehicle (UAV) flight risks in low-altitude airspace, we analyze the factors of UAV flight risks from three aspects: flight conflict, flight environment, and traffic characteristics. The aerial risk index and ground risk index of the UAV are constructed, the index screening model and the UAV flight risk assessment model are established, and a UAV flight risk assessment model based on K-means clustering has been proposed. Meanwhile, numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively, but also provide technical support for UAV risk management and control.
2020, 37(2):274-287.
DOI: 10.16356/j.1005-1120.2020.02.009
Abstract:
With the increasing civil aviation passengers and the rapid development of aviation logistics, the study on remotely piloted operation (RPO) mode has received extensive attention. RPO mode constructs the piloting decision-making mode which involves the tripartite collaboration among airborne automatic/autonomous system, remote ground-based crews and air traffic control. In this paper, we describe the organizing architecture for commercial remotely piloted aircraft (CRPA) system and its components. Compared with the current operation mode, the new air-ground collaborative decision-making mode has been established with six different situations based on the type of the flight and the condition of the remote pilot. Taking airport surface operation as an experimental example, we model the airport surface operation process and compare the advantages and disadvantages between RPO mode and the current dual-pilot mode from the perspectives of time and operation coverage, and draw conclusions that RPO mode can basically cover the flight operations of the dual-pilot, improve the accuracy of pilot operations and greatly reduce response time by 48% in pre-flight inspection. The above research would be the foundation for the RPO development of commercial aircraft in China.
With the increasing civil aviation passengers and the rapid development of aviation logistics, the study on remotely piloted operation (RPO) mode has received extensive attention. RPO mode constructs the piloting decision-making mode which involves the tripartite collaboration among airborne automatic/autonomous system, remote ground-based crews and air traffic control. In this paper, we describe the organizing architecture for commercial remotely piloted aircraft (CRPA) system and its components. Compared with the current operation mode, the new air-ground collaborative decision-making mode has been established with six different situations based on the type of the flight and the condition of the remote pilot. Taking airport surface operation as an experimental example, we model the airport surface operation process and compare the advantages and disadvantages between RPO mode and the current dual-pilot mode from the perspectives of time and operation coverage, and draw conclusions that RPO mode can basically cover the flight operations of the dual-pilot, improve the accuracy of pilot operations and greatly reduce response time by 48% in pre-flight inspection. The above research would be the foundation for the RPO development of commercial aircraft in China.
2020, 37(2):288-299.
DOI: 10.16356/j.1005-1120.2020.02.010
Abstract:
As the rapid development of aviation industry and newly emerging crowd-sourcing projects such as Flightradar24 and FlightAware, large amount of air traffic data, particularly four-dimension (4D) trajectory data, have become available for the public. In order to guarantee the accuracy and reliability of results, data cleansing is the first step in analyzing 4D trajectory data, including error identification and mitigation. Data cleansing techniques for the 4D trajectory data are investigated. Back propagation (BP) neural network algorithm is applied to repair errors. Newton interpolation method is used to obtain even-spaced trajectory samples over a uniform distribution of each flight’s 4D trajectory data. Furthermore, a new method is proposed to compress data while maintaining the intrinsic characteristics of the trajectories. Density-based spatial clustering of applications with noise (DBSCAN) is applied to identify remaining outliers of sample points. Experiments are performed on a data set of one-day 4D trajectory data over Europe. The results show that the proposed method can achieve more efficient and effective results than the existing approaches. The work contributes to the first step of data preprocessing and lays foundation for further downstream 4D trajectory analysis.
As the rapid development of aviation industry and newly emerging crowd-sourcing projects such as Flightradar24 and FlightAware, large amount of air traffic data, particularly four-dimension (4D) trajectory data, have become available for the public. In order to guarantee the accuracy and reliability of results, data cleansing is the first step in analyzing 4D trajectory data, including error identification and mitigation. Data cleansing techniques for the 4D trajectory data are investigated. Back propagation (BP) neural network algorithm is applied to repair errors. Newton interpolation method is used to obtain even-spaced trajectory samples over a uniform distribution of each flight’s 4D trajectory data. Furthermore, a new method is proposed to compress data while maintaining the intrinsic characteristics of the trajectories. Density-based spatial clustering of applications with noise (DBSCAN) is applied to identify remaining outliers of sample points. Experiments are performed on a data set of one-day 4D trajectory data over Europe. The results show that the proposed method can achieve more efficient and effective results than the existing approaches. The work contributes to the first step of data preprocessing and lays foundation for further downstream 4D trajectory analysis.
2020, 37(2):300-310.
DOI: 10.16356/j.1005-1120.2020.02.011
Abstract:
European air transport network (EATN) and Chinese air transport network (CATN), as two important air transport systems in the world, are facing increasingly spatial hazards, such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way, a new spatial vulnerability model (SVM) is proposed in this paper, which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM, two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then, the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it, a comparative case study on EATN and CATN under two representative spatial hazard scenarios, one with an even spatial distribution, named as spatially uniform hazard, and the other with an uneven spatial distribution that takes rainstorm hazard as an example, is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard, but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors, including airspace openness and flight safety importance in Europe and China, EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future, EATN needs to pay more attention to the impact of rainstorm hazard.
European air transport network (EATN) and Chinese air transport network (CATN), as two important air transport systems in the world, are facing increasingly spatial hazards, such as extreme weathers and natural disasters. In order to reflect and compare impact of spatial hazards on the two networks in a practical way, a new spatial vulnerability model (SVM) is proposed in this paper, which analyzes vulnerability of a network system under spatial hazards from the perspectives of network topology and characteristics of hazards. Before introduction of the SVM, two abstract networks for EATN and CATN are established with a simple topological analysis by traditional vulnerability method. Then, the process to study vulnerability of an air transport network under spatial hazards by SVM is presented. Based on it, a comparative case study on EATN and CATN under two representative spatial hazard scenarios, one with an even spatial distribution, named as spatially uniform hazard, and the other with an uneven spatial distribution that takes rainstorm hazard as an example, is conducted. The simulation results show that both of EATN and CATN are robust to spatially uniform hazard, but vulnerable to rainstorm hazard. In the comparison of the results of the two networks that only stands from the points of network topology and characteristics of hazard without considering certain unequal factors, including airspace openness and flight safety importance in Europe and China, EATN is more vulnerable than CATN under rainstorm hazard. This suggests that when the two networks grow to a similar developed level in future, EATN needs to pay more attention to the impact of rainstorm hazard.
2020, 37(2):311-321.
DOI: 10.16356/j.1005-1120.2020.02.012
Abstract:
To collect and share information of projects or products and make it consistent and correct so that the quality and costs of projects can be effectively controlled, an integrative project architecture integrating different types of breakdown structures is necessary. In this paper, the international research status on work breakdown structure (WBS) was analyzed, and an integrative project architecture for commercial aero-engines was designed, where product breakdown structure (PBS), WBS, organization breakdown structure (OBS) and cost breakdown structure (CBS) were integrated and built. And the architecture was applied in information systems. A transfer from technological views of complex products through their lifecycles to management views has been realized with this standardized architecture, thus development tasks and costs can be controlled.
To collect and share information of projects or products and make it consistent and correct so that the quality and costs of projects can be effectively controlled, an integrative project architecture integrating different types of breakdown structures is necessary. In this paper, the international research status on work breakdown structure (WBS) was analyzed, and an integrative project architecture for commercial aero-engines was designed, where product breakdown structure (PBS), WBS, organization breakdown structure (OBS) and cost breakdown structure (CBS) were integrated and built. And the architecture was applied in information systems. A transfer from technological views of complex products through their lifecycles to management views has been realized with this standardized architecture, thus development tasks and costs can be controlled.
2020, 37(2):322-331.
DOI: 10.16356/j.1005-1120.2020.02.013
Abstract:
To deal with the high nonlinearities and strong couplings in the transition stage of tail-sitter aircraft, an adaptive gain-scheduling controller is proposed by combining the guardian maps theory and H∞ control theory. This method is applied to track the flight-path angle of the transition stage of tail-sitter aircraft, and compared with the linear quadratic regulator(LQR) method based on traditional gain scheduling. Simulation results show that the controller based on the guardian maps theory can autonomously schedule the appropriate control parameters and accomplish the stable transition. Besides, the proposed method shows better tracking performance than the LQR method based on traditional gain scheduling.
To deal with the high nonlinearities and strong couplings in the transition stage of tail-sitter aircraft, an adaptive gain-scheduling controller is proposed by combining the guardian maps theory and H∞ control theory. This method is applied to track the flight-path angle of the transition stage of tail-sitter aircraft, and compared with the linear quadratic regulator(LQR) method based on traditional gain scheduling. Simulation results show that the controller based on the guardian maps theory can autonomously schedule the appropriate control parameters and accomplish the stable transition. Besides, the proposed method shows better tracking performance than the LQR method based on traditional gain scheduling.
2020, 37(2):332-342.
DOI: 10.16356/j.1005-1120.2020.02.014
Abstract:
In the design of the motor used for electric vehicles(EVS), vibration and noise problems are often ignored, which reduce the reliability and service life of the motor. In this paper, an interior permanent magnet synchronous motor (IPMSM) with high power density is taken as an example, and its electromagnetic vibration and noise problem is investigated and optimized. Firstly, the factors that generate the electromagnetic force harmonic of IPMSM are analyzed by theoretical derivation. Furthermore, the mode and electromagnetic harmonic distribution of the motor are calculated and analyzed by establishing the electromagnetic-structure-sound coupling simulation model. Then, by combining finite element method(FEM) with modern optimization algorithm, an electromagnetic vibration and noise performance optimization method is proposed in the electromagnetic design stage of the motor. Finally, an IPMSM is optimized by this method for electromagnetic vibration and noise performance. The results of comparison between before and after optimization prove the feasibility of the method.
In the design of the motor used for electric vehicles(EVS), vibration and noise problems are often ignored, which reduce the reliability and service life of the motor. In this paper, an interior permanent magnet synchronous motor (IPMSM) with high power density is taken as an example, and its electromagnetic vibration and noise problem is investigated and optimized. Firstly, the factors that generate the electromagnetic force harmonic of IPMSM are analyzed by theoretical derivation. Furthermore, the mode and electromagnetic harmonic distribution of the motor are calculated and analyzed by establishing the electromagnetic-structure-sound coupling simulation model. Then, by combining finite element method(FEM) with modern optimization algorithm, an electromagnetic vibration and noise performance optimization method is proposed in the electromagnetic design stage of the motor. Finally, an IPMSM is optimized by this method for electromagnetic vibration and noise performance. The results of comparison between before and after optimization prove the feasibility of the method.
2020, 37(2):343-352.
DOI: 10.16356/j.1005-1120.2020.02.015
Abstract:
The modern transportation system is increasingly developed during recent years. It is an effective solution to set the noise barriers to reduce the traffic noise pollution caused by different kinds of transportation systems. Many deficiencies on concrete noise barriers and metal noise barriers with rivet structure can be eliminated by a new kind of noise barrier with no-riveted structure. The mechanical performance examination and acoustic performance test are conducted on the new-designed noise barrier with no-riveted structure. The results indicate that the maximum stress is 1.74 MPa and the maximum deformation is 1.04 mm with load acting on the unit plate. The noise reduction coefficient of this kind of no-riveted noise barrier unit plate is 0.75 and its noise insulation is 40 dB, which were conform to or superior to the standard requirements. Therefore, this new designed noise barrier meets the field application requirements of mechanical and acoustic performance, which demonstrates the noise barriers can be widely promoted.
The modern transportation system is increasingly developed during recent years. It is an effective solution to set the noise barriers to reduce the traffic noise pollution caused by different kinds of transportation systems. Many deficiencies on concrete noise barriers and metal noise barriers with rivet structure can be eliminated by a new kind of noise barrier with no-riveted structure. The mechanical performance examination and acoustic performance test are conducted on the new-designed noise barrier with no-riveted structure. The results indicate that the maximum stress is 1.74 MPa and the maximum deformation is 1.04 mm with load acting on the unit plate. The noise reduction coefficient of this kind of no-riveted noise barrier unit plate is 0.75 and its noise insulation is 40 dB, which were conform to or superior to the standard requirements. Therefore, this new designed noise barrier meets the field application requirements of mechanical and acoustic performance, which demonstrates the noise barriers can be widely promoted.
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