Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.71
M. Qin, Xiuli Liu
We used the DEA cross-efficiency method to explore the health effects of provincial differences in dietary patterns in China. The result showed that for the group aged 0-14, Inner Mongolia and Guizhou provinces rank the top, and children in Zhejiang province should add more dairy products and eggs in the diet; For the group aged 15-64, there are fewer differences between provinces, but it generally shows high calorie and high protein intake among them; For the group aged over 64, Shanghai and Tianjin provinces are low-ranking, and old people in Shanghai province should reduce the egg intake while those in Tianjin province should have more vegetable and meat intake.
{"title":"Analysis of the Influence of Dietary Pattern on the Health Level of Residents in China","authors":"M. Qin, Xiuli Liu","doi":"10.2991/MASTA-19.2019.71","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.71","url":null,"abstract":"We used the DEA cross-efficiency method to explore the health effects of provincial differences in dietary patterns in China. The result showed that for the group aged 0-14, Inner Mongolia and Guizhou provinces rank the top, and children in Zhejiang province should add more dairy products and eggs in the diet; For the group aged 15-64, there are fewer differences between provinces, but it generally shows high calorie and high protein intake among them; For the group aged over 64, Shanghai and Tianjin provinces are low-ranking, and old people in Shanghai province should reduce the egg intake while those in Tianjin province should have more vegetable and meat intake.","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130698120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.64
Jia-juan Chen, Zheng-rong Chen, Huaiyuan Liu, Chuan-tao Wang
During the execution of flight schedule, the capacity of airport and airspace is often reduced by external dynamic factors such as weather conditions and flow control, which makes it impossible to meet the flow demand of airport and airspace, resulting in flight delay. In order to better implement tactical management of air traffic flow and reduce flight delay time and delay cost, this paper considers the impact of weather conditions, and combines ground and air waiting strategies to construct a multi-objective short-term flight time optimization model based on weather conditions, and uses NSGA-II algorithm to solve it. Finally, the Yangtze River Delta Airport Group is taken as an example to verify. Introduction The planning and layout of regional airports has always been the core bottleneck of restricting the rapid development of regional air transport. With the single airport system becoming more and more difficult to meet the growing demand for air transport, multi-airport system (i.e. Airport group) with clear positioning and win-win cooperation in the region will inevitably become the future development trend. Because of the obvious air traffic interaction, limited airspace resources, strong demand for flight time and other reasons, airport groups are vulnerable to weather conditions, flow control and other external dynamic factors, resulting in lower than expected flight normal rate, largescale flight delay, which seriously affects the sustainable and healthy development of airport groups. Therefore, the implementation of scientific and reasonable optimization of short-term flight time is particularly important. At present, many researchers from all over the world have conducted research on airport group and flight time optimization issues. Rubin David (1976) began to study the airport group problem and first proposed the concept of an airport group, which briefly defined the airport group as "Multi Airport Region" [1]. Peter B (1994) analyzed the ground-holding policy of multiple airports in air traffic flow management and established a VBO model based on ground-holding policy [2]. Avijit Mukherjee (2007) established a dynamic random integer programming model based on weather forecast and ground-holding policy, and verified by example that the model can allocate flight time in different decision stages [3]. Husni Idris (2003) used the queuing model to analyze the collaborative operation of the New York airport group, focusing on the interaction of air traffic flows at airports within the airport group and the correlation of flight times at airports [4]. Alexandre Jacquillat (2013) used the delay value model and the Monte Carlo simulation model to approximate the dynamic characteristics of the airport queuing system, and analyzed the airport delay levels under different conditions, and optimized the flight time. [5,6]. Nikolas Pyrgiotis (2016) established a flight time optimization model considering the existing flight schedule and airline
{"title":"Study on Short-time Flight Timing Optimization of Airport Group Based on Weather Conditions","authors":"Jia-juan Chen, Zheng-rong Chen, Huaiyuan Liu, Chuan-tao Wang","doi":"10.2991/MASTA-19.2019.64","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.64","url":null,"abstract":"During the execution of flight schedule, the capacity of airport and airspace is often reduced by external dynamic factors such as weather conditions and flow control, which makes it impossible to meet the flow demand of airport and airspace, resulting in flight delay. In order to better implement tactical management of air traffic flow and reduce flight delay time and delay cost, this paper considers the impact of weather conditions, and combines ground and air waiting strategies to construct a multi-objective short-term flight time optimization model based on weather conditions, and uses NSGA-II algorithm to solve it. Finally, the Yangtze River Delta Airport Group is taken as an example to verify. Introduction The planning and layout of regional airports has always been the core bottleneck of restricting the rapid development of regional air transport. With the single airport system becoming more and more difficult to meet the growing demand for air transport, multi-airport system (i.e. Airport group) with clear positioning and win-win cooperation in the region will inevitably become the future development trend. Because of the obvious air traffic interaction, limited airspace resources, strong demand for flight time and other reasons, airport groups are vulnerable to weather conditions, flow control and other external dynamic factors, resulting in lower than expected flight normal rate, largescale flight delay, which seriously affects the sustainable and healthy development of airport groups. Therefore, the implementation of scientific and reasonable optimization of short-term flight time is particularly important. At present, many researchers from all over the world have conducted research on airport group and flight time optimization issues. Rubin David (1976) began to study the airport group problem and first proposed the concept of an airport group, which briefly defined the airport group as \"Multi Airport Region\" [1]. Peter B (1994) analyzed the ground-holding policy of multiple airports in air traffic flow management and established a VBO model based on ground-holding policy [2]. Avijit Mukherjee (2007) established a dynamic random integer programming model based on weather forecast and ground-holding policy, and verified by example that the model can allocate flight time in different decision stages [3]. Husni Idris (2003) used the queuing model to analyze the collaborative operation of the New York airport group, focusing on the interaction of air traffic flows at airports within the airport group and the correlation of flight times at airports [4]. Alexandre Jacquillat (2013) used the delay value model and the Monte Carlo simulation model to approximate the dynamic characteristics of the airport queuing system, and analyzed the airport delay levels under different conditions, and optimized the flight time. [5,6]. Nikolas Pyrgiotis (2016) established a flight time optimization model considering the existing flight schedule and airline ","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126359046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, first, based on the principle of sensitivity analysis, the key combustion control parameters that influence the combustion characteristics index indicated mean effective pressure (IMEP)and crank angle of 50% heat release (CA50) of diesel low temperature combustion(LTC)are determined by experimental study, which lays a foundation for simplifying the combustion control of diesel LTC. Then, the regulation law of the key combustion control parameters and the influence of that on the combustion characteristics IMEP and CA50 are further analyzed by using the experimental data. Finally, based on the above analysis, the physically-based control-oriented IMEP and CA50 model are developed. The model is validated by using the transient diesel experimental data and the validation result shows that the model can predict not only the dynamic characteristics but also the IMEP and CA50 of diesel engine under LTC conditions, accurately.
{"title":"Sensitivity Analysis and Modeling Research on Combustion Characteristic Parameters of Diesel LTC","authors":"Jiawei Li, T. Cui, Fujun Zhang, Hongli Gao, Sufei Wang, Hao Wu","doi":"10.2991/MASTA-19.2019.1","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.1","url":null,"abstract":"In this paper, first, based on the principle of sensitivity analysis, the key combustion control parameters that influence the combustion characteristics index indicated mean effective pressure (IMEP)and crank angle of 50% heat release (CA50) of diesel low temperature combustion(LTC)are determined by experimental study, which lays a foundation for simplifying the combustion control of diesel LTC. Then, the regulation law of the key combustion control parameters and the influence of that on the combustion characteristics IMEP and CA50 are further analyzed by using the experimental data. Finally, based on the above analysis, the physically-based control-oriented IMEP and CA50 model are developed. The model is validated by using the transient diesel experimental data and the validation result shows that the model can predict not only the dynamic characteristics but also the IMEP and CA50 of diesel engine under LTC conditions, accurately.","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131756934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.15
Chao Sun, Wei Liu, Heng Zheng, Hao Ma, Jian-meng Sun
Stimulated Reservoir Volume (SRV) is one of new emerging hydraulic fracturing techniques to develop shale gas, tight sandstone and other unconventional reservoirs. The favorable geological conditions and reasonable fracturing design are critical factors to form complex fracture network that is different from conventional bi-wing fracture. In the reservoir, conductivity and drainage space can be enhanced by the fracture network. At present, numerical simulation of complex fractures is still based on the pseudo-3D model and depend on huge amount of calculation to obtain the fracture network. Therefore, this method has distinct differences in actual propagation and need to be computed intensively. Applying the theory of mechanics of materials and fracture mechanics, the equations of expansion and propagation for natural fracture are derived and the equation of stress shadow is adopted to consider the additional normal stress induced by adjacent fractures. Based on the propagation pressure, the length of branching fracture can be obtained by establishing a novel fracture network model. The model can be solved explicitly through the net pressure. This method can reduce the iterations effectively when many natural fracture must be accounted for the realization of numerical calculation. In order to verify the accuracy of the results, the parameters applied in the treatment are adopted as input for simulation, and the data of microseismic mapping are also used for matching the fracture network. Introduction Hydraulic fracturing has become one of the most important technologies in the development tight oil resources. During the process of reservoir stimulation, how to create more fractures in tight sandstone reservoir becomes the key issue. However, some naturally fractured sand formations have geomechanical properties that allow hydraulically induced discrete fractures to initiate, propagate and lead to a complex fracture network. Many researchers have conducted a series of experiments and numerical simulations to investigate the mechanism of fracture propagation. Also, some key factors which affect the complex fracture network such as natural fracture, horizontal in situ stress difference, fracturing fluid viscosity, and injection rate [1,2,3,4] of fracturing fluid have been investigated. Blanton [5,6]discussed the relationship between induced fracture and natural fracture which displayed that hydraulic fractures cross the pre-existing fractures only under high differential stress conditions and high approach angle. In addition, the stress ratio of [7, 8]maximum principal horizontal stress to minimum principal horizontal stress below 1.5 demonstrated proportionally increasing branching and fracture multiplicity with proportionally decreasing stress orientation. In other words, the hydraulic fractures are more easily to extend along the natural fracture under the low horizontal stress difference [9, 10]. Chen mian and Zhou jian [11,12] used true triaxial
{"title":"Simulation Research and Application of Complex Fracture Network for SRV","authors":"Chao Sun, Wei Liu, Heng Zheng, Hao Ma, Jian-meng Sun","doi":"10.2991/MASTA-19.2019.15","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.15","url":null,"abstract":"Stimulated Reservoir Volume (SRV) is one of new emerging hydraulic fracturing techniques to develop shale gas, tight sandstone and other unconventional reservoirs. The favorable geological conditions and reasonable fracturing design are critical factors to form complex fracture network that is different from conventional bi-wing fracture. In the reservoir, conductivity and drainage space can be enhanced by the fracture network. At present, numerical simulation of complex fractures is still based on the pseudo-3D model and depend on huge amount of calculation to obtain the fracture network. Therefore, this method has distinct differences in actual propagation and need to be computed intensively. Applying the theory of mechanics of materials and fracture mechanics, the equations of expansion and propagation for natural fracture are derived and the equation of stress shadow is adopted to consider the additional normal stress induced by adjacent fractures. Based on the propagation pressure, the length of branching fracture can be obtained by establishing a novel fracture network model. The model can be solved explicitly through the net pressure. This method can reduce the iterations effectively when many natural fracture must be accounted for the realization of numerical calculation. In order to verify the accuracy of the results, the parameters applied in the treatment are adopted as input for simulation, and the data of microseismic mapping are also used for matching the fracture network. Introduction Hydraulic fracturing has become one of the most important technologies in the development tight oil resources. During the process of reservoir stimulation, how to create more fractures in tight sandstone reservoir becomes the key issue. However, some naturally fractured sand formations have geomechanical properties that allow hydraulically induced discrete fractures to initiate, propagate and lead to a complex fracture network. Many researchers have conducted a series of experiments and numerical simulations to investigate the mechanism of fracture propagation. Also, some key factors which affect the complex fracture network such as natural fracture, horizontal in situ stress difference, fracturing fluid viscosity, and injection rate [1,2,3,4] of fracturing fluid have been investigated. Blanton [5,6]discussed the relationship between induced fracture and natural fracture which displayed that hydraulic fractures cross the pre-existing fractures only under high differential stress conditions and high approach angle. In addition, the stress ratio of [7, 8]maximum principal horizontal stress to minimum principal horizontal stress below 1.5 demonstrated proportionally increasing branching and fracture multiplicity with proportionally decreasing stress orientation. In other words, the hydraulic fractures are more easily to extend along the natural fracture under the low horizontal stress difference [9, 10]. Chen mian and Zhou jian [11,12] used true triaxial","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114990815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.37
Yun-hai Wang, Xianming Zhang, Bin Ji
The classical two-dimensional airfoil flutter equations can be established by many ways. For the simplicity of solving it, a sinusoidal structure motion hypothesis and some kind of aerodynamic theory must be proposed in advance. However, when a wing flutter occurs, its structural movement is likely to be more complex. Furthermore, the well-known harmonic balance method may not sufficiently accurate due to those higher order terms are ignored, which might lead to larger errors. In this paper, we propose a parametric method such that the original equations are parameterized, namely Chebyshev expansion method. A simple example is used to illustrate our strategy. Introduction As is known to all, it’s easy to induce the continuous or divergent vibration form when the elastic structure of the aircraft in uniform flow is impacted coupling by the air force, elastic force and inertial force. This phenomenon is called “flutter”, and it is one of the most important questions in the pneumatic elastic mechanics [1]. In recent years, with the development of computer hardware and software technologies, the coupled flutter computation of the research based on the Computational Fluid Dynamic (CFD) and the Computational Structure Dynamics (CSD) began to prevail. The flutter calculation and research based on the two-dimensional airfoil can be divided into categories, the qualitative and the quantitative, which is similar to the three-dimensional airfoil flutter problem on the mechanism [2]. The former makes research on the stability of the system, and the latter focuses on the flutter amplitude, frequency, phase and so on. For a 2D wing prediction of flutter, the structural motion was scribed in a sine function in the pass, and the aerodynamics model established by the aid of Theodorsen unsteady aerodynamic force theory. Calculation results can be used in the primitive engineering practice [3]. Based on the sine motion hypothesis and the common harmonic balance method, the accuracy of quantitative calculation may not be very high [4], namely large errors may occur [5] because of the standard harmonic balance method ignoring the higher frequencies. Other works of modeling an aeroelasticity system or calculating air forces can be found in references [6,7] behind. This paper proposes a parametric approach to transform the original flutter equations: using Chebyshev expansion method. The method doesn’t only limit the form of structure movement, but also it can be applied to those nonlinear aeroelastic problems. Finally, one can obtain sufficiently precise result when solving the new equations expressed by Chebyshev series. Properties of the First Chebyshev Polynomial Since Chebyshev polynomial is put forward, it is widely used in academic fields such as in system analysis, parameter identification, optimal control, model reduction and so on[8]. In the field of aeronautics and astronautics, for example, the model identification problem, we can effectively improve the ac
{"title":"A 2D Flutter Equation Transformation Using Chebyshev Expansion Method","authors":"Yun-hai Wang, Xianming Zhang, Bin Ji","doi":"10.2991/MASTA-19.2019.37","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.37","url":null,"abstract":"The classical two-dimensional airfoil flutter equations can be established by many ways. For the simplicity of solving it, a sinusoidal structure motion hypothesis and some kind of aerodynamic theory must be proposed in advance. However, when a wing flutter occurs, its structural movement is likely to be more complex. Furthermore, the well-known harmonic balance method may not sufficiently accurate due to those higher order terms are ignored, which might lead to larger errors. In this paper, we propose a parametric method such that the original equations are parameterized, namely Chebyshev expansion method. A simple example is used to illustrate our strategy. Introduction As is known to all, it’s easy to induce the continuous or divergent vibration form when the elastic structure of the aircraft in uniform flow is impacted coupling by the air force, elastic force and inertial force. This phenomenon is called “flutter”, and it is one of the most important questions in the pneumatic elastic mechanics [1]. In recent years, with the development of computer hardware and software technologies, the coupled flutter computation of the research based on the Computational Fluid Dynamic (CFD) and the Computational Structure Dynamics (CSD) began to prevail. The flutter calculation and research based on the two-dimensional airfoil can be divided into categories, the qualitative and the quantitative, which is similar to the three-dimensional airfoil flutter problem on the mechanism [2]. The former makes research on the stability of the system, and the latter focuses on the flutter amplitude, frequency, phase and so on. For a 2D wing prediction of flutter, the structural motion was scribed in a sine function in the pass, and the aerodynamics model established by the aid of Theodorsen unsteady aerodynamic force theory. Calculation results can be used in the primitive engineering practice [3]. Based on the sine motion hypothesis and the common harmonic balance method, the accuracy of quantitative calculation may not be very high [4], namely large errors may occur [5] because of the standard harmonic balance method ignoring the higher frequencies. Other works of modeling an aeroelasticity system or calculating air forces can be found in references [6,7] behind. This paper proposes a parametric approach to transform the original flutter equations: using Chebyshev expansion method. The method doesn’t only limit the form of structure movement, but also it can be applied to those nonlinear aeroelastic problems. Finally, one can obtain sufficiently precise result when solving the new equations expressed by Chebyshev series. Properties of the First Chebyshev Polynomial Since Chebyshev polynomial is put forward, it is widely used in academic fields such as in system analysis, parameter identification, optimal control, model reduction and so on[8]. In the field of aeronautics and astronautics, for example, the model identification problem, we can effectively improve the ac","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123420322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Freak wave is a kind of instantaneous disastrous wave with large wave height, which has great destructive effect on the navigation of ships at sea. Based on the Boussinesq equation, a phase-focusing model for focusing simulation of freak wave is established, and the numerical generation of freak wave is realized. Through the calculation results, the evolution process and the non-linear characteristic parameters of freak wave are analyzed and discussed. The following conclusions are drawn: phase-focusing model based on Boussinesq equation can generate freak wave when the phase angle distribution is smaller than 6 . 1 . The change of phase angle distribution has less influence on skewness and more influence on kurtosis. Introduction As a special kind of disastrous wave, freak wave, because of its sudden occurrence and harmfulness to the safety of naval vessel activities, urgently needs us to improve our understanding of this threatening wave in order to protect the environment for human survival, predict the occurrence of such natural disasters and reduce the losses caused by it. Therefore, freak wave has become a hot topic in wave theory and application. At present, the research on the mechanism of freak wave formation is mostly carried out through the angle of energy focus. Kharif and Pelinovsky[1] summarized the generating mechanism of freak waves, believing that the generation of freak waves may be caused by one or more of the following factors: wave superposition, wave-current interaction, topographic change, wind action, Benjamin-Feir instability and so on. In order to studying the mechanism and influencing factors of freak wave, it is an effective way to reproduce the freak wave events in the laboratory. It is the most effective way to study freak wave in laboratory by focusing wave energy. Among them, the most commonly used method is the phase velocity method. According to the linear wave theory, the waves of different periods and amplitudes are combined in the form of linear superposition, and the initial phase of each component wave is artificially modulated to reach the maximum peak at the given position and time, so that the linear superposition of each component wave can produce large waves. In order to overcome the disadvantage that the wavefront in the focusing position is still before and after the wave is focused, and the probability of extreme wave is very low, Kriebel[2] and others divide the energy spectrum into two parts: background spectrum and singular spectrum. The background spectrum is used to generate random wave field, simulate the real sea surface, and use singular spectrum. The results show that only 15% or 20% of the total energy can be used to generate the extreme wave, that is, only a small part of the wave component can generate the extreme wave. Huang[3] used a model to obtain the time series of wave surface containing abnormal waves by manual intervention of the random initial phase of the composed waves, but t
{"title":"Phase-Focusing Model of Freak Wave Based on Boussinesq Equation","authors":"Xiang-jun Yu, Qing-hong Li, Hua Wang","doi":"10.2991/MASTA-19.2019.4","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.4","url":null,"abstract":"Freak wave is a kind of instantaneous disastrous wave with large wave height, which has great destructive effect on the navigation of ships at sea. Based on the Boussinesq equation, a phase-focusing model for focusing simulation of freak wave is established, and the numerical generation of freak wave is realized. Through the calculation results, the evolution process and the non-linear characteristic parameters of freak wave are analyzed and discussed. The following conclusions are drawn: phase-focusing model based on Boussinesq equation can generate freak wave when the phase angle distribution is smaller than 6 . 1 . The change of phase angle distribution has less influence on skewness and more influence on kurtosis. Introduction As a special kind of disastrous wave, freak wave, because of its sudden occurrence and harmfulness to the safety of naval vessel activities, urgently needs us to improve our understanding of this threatening wave in order to protect the environment for human survival, predict the occurrence of such natural disasters and reduce the losses caused by it. Therefore, freak wave has become a hot topic in wave theory and application. At present, the research on the mechanism of freak wave formation is mostly carried out through the angle of energy focus. Kharif and Pelinovsky[1] summarized the generating mechanism of freak waves, believing that the generation of freak waves may be caused by one or more of the following factors: wave superposition, wave-current interaction, topographic change, wind action, Benjamin-Feir instability and so on. In order to studying the mechanism and influencing factors of freak wave, it is an effective way to reproduce the freak wave events in the laboratory. It is the most effective way to study freak wave in laboratory by focusing wave energy. Among them, the most commonly used method is the phase velocity method. According to the linear wave theory, the waves of different periods and amplitudes are combined in the form of linear superposition, and the initial phase of each component wave is artificially modulated to reach the maximum peak at the given position and time, so that the linear superposition of each component wave can produce large waves. In order to overcome the disadvantage that the wavefront in the focusing position is still before and after the wave is focused, and the probability of extreme wave is very low, Kriebel[2] and others divide the energy spectrum into two parts: background spectrum and singular spectrum. The background spectrum is used to generate random wave field, simulate the real sea surface, and use singular spectrum. The results show that only 15% or 20% of the total energy can be used to generate the extreme wave, that is, only a small part of the wave component can generate the extreme wave. Huang[3] used a model to obtain the time series of wave surface containing abnormal waves by manual intervention of the random initial phase of the composed waves, but t","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125640669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surface defects of cathode filaments of microwave magnetron would cause magnetron failure and scrapped microwave systems. Therefore, surface defects on cathode filaments must be carefully inspected. Conventionally, filaments are manually and visually inspected using their amplified images under an optical microscope. This is because automatic defect detection of cathode filaments is a challenging problem. The difficulty comings from its complex surface shape with multiple turns of high curvature spiral circles, which occlude each other. Such complex shape prevents capturing of sharp focusing images, which are essential for a computerized automatic detection algorithm. Further, the variable nature of production defects complicated the process of automatic defect detection task. To solve these problems, this paper proposes an automatic defect detection method to deal with issues related to complex shapes containing occlusions as well as high curvatures, particularly for the quality inspection of spiral shaped cathode filaments. The method includes a novel digital scanner, which sequentially brings all sections of the filament sides into sharp focusing of the optical imaging system. The method also employs multiple optical systems to imaging multi-sides of the spiral filament. The computational algorithm primarily uses line-detectors. In an evaluation experiment, the proposed method was used to automatically inspect over 14 million cathode filaments. Experimental results indicate that its false negative rate was 0.0065%, and its false positive rate was 6.83%. This indicates that the proposed method could successfully detect all kinds of surface defects at over 99.99% accuracy. It reduces the workload for manual inspection from 100% down to 93.17%, over an order of magnitude reduction. Further, the efficiency of the proposed method is 70 spiral filaments per minute, satisfying the requirements of online quality detection of existing manufacturing lines of filament cathodes. Introduction Cathode magnetron are widely used in both military applications1,2 as well as household microwaves3,4. The core of a cathode magnetron is the cathode filament, which is typically made of thorium tungsten or barium-tungsten alloy. When excited at a high voltage, the cathode filament of a magnetron cathode within a microwave oven would generate Tera Hertz frequency microwaves causing water molecules to move, vibrate, and bump into other food molecules at high frequencies. In this way, the filament inside a cathode converts electromagnetic energy into heat, which is quickly absorbed by the food. Therefore, the filament within a cathode magnetron is the core component of a microwave oven. Though the chemical composition of the cathode filament determines the escape power, emission stability, and lifespan of a microwave oven. However, when the chemical composition is optimized and fixed, the manufacturing quality of the cathode filament determines the International Confere
{"title":"Defect Detection and Full Surface Characterization of High Curvature Cathode Filaments","authors":"Dingrong Yi, Cai-hong Huang, Jing-fang Xie, Yuhan Cai, Yong Qian, Ling-hua Kong","doi":"10.2991/MASTA-19.2019.48","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.48","url":null,"abstract":"Surface defects of cathode filaments of microwave magnetron would cause magnetron failure and scrapped microwave systems. Therefore, surface defects on cathode filaments must be carefully inspected. Conventionally, filaments are manually and visually inspected using their amplified images under an optical microscope. This is because automatic defect detection of cathode filaments is a challenging problem. The difficulty comings from its complex surface shape with multiple turns of high curvature spiral circles, which occlude each other. Such complex shape prevents capturing of sharp focusing images, which are essential for a computerized automatic detection algorithm. Further, the variable nature of production defects complicated the process of automatic defect detection task. To solve these problems, this paper proposes an automatic defect detection method to deal with issues related to complex shapes containing occlusions as well as high curvatures, particularly for the quality inspection of spiral shaped cathode filaments. The method includes a novel digital scanner, which sequentially brings all sections of the filament sides into sharp focusing of the optical imaging system. The method also employs multiple optical systems to imaging multi-sides of the spiral filament. The computational algorithm primarily uses line-detectors. In an evaluation experiment, the proposed method was used to automatically inspect over 14 million cathode filaments. Experimental results indicate that its false negative rate was 0.0065%, and its false positive rate was 6.83%. This indicates that the proposed method could successfully detect all kinds of surface defects at over 99.99% accuracy. It reduces the workload for manual inspection from 100% down to 93.17%, over an order of magnitude reduction. Further, the efficiency of the proposed method is 70 spiral filaments per minute, satisfying the requirements of online quality detection of existing manufacturing lines of filament cathodes. Introduction Cathode magnetron are widely used in both military applications1,2 as well as household microwaves3,4. The core of a cathode magnetron is the cathode filament, which is typically made of thorium tungsten or barium-tungsten alloy. When excited at a high voltage, the cathode filament of a magnetron cathode within a microwave oven would generate Tera Hertz frequency microwaves causing water molecules to move, vibrate, and bump into other food molecules at high frequencies. In this way, the filament inside a cathode converts electromagnetic energy into heat, which is quickly absorbed by the food. Therefore, the filament within a cathode magnetron is the core component of a microwave oven. Though the chemical composition of the cathode filament determines the escape power, emission stability, and lifespan of a microwave oven. However, when the chemical composition is optimized and fixed, the manufacturing quality of the cathode filament determines the International Confere","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123785805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.56
Tingke Wu, Haitao Luo, Hong Guo, Jia Fu, Guangming Liu
In order to study the temperature field (TF) distribution and material flow (MF) in the friction stir welding process, the finite element model of friction stir welding (FSW) was established to simulate the welding process. The temperature field results showed that the temperature on the advancing side (AS) was higher than the retreating side (RS). The temperature field has an important influence on the material flow, so the material flow in the plunging stage and welding stage is simulated numerically to study the material flow trajectory in different stages. The results show that the material distribution is more uniform due to the long time in the plunging stage, and the amount of material flow in the plunging stage is larger than that in the welding stage. In the welding stage, it is found that the shoulder can promote the material flow. After analyzing the displacement of tracking particles in the welding stage, it is found that the displacement of particles on the AS is significantly higher than that on the axis and the RS. Introduction Friction stir welding (FSW) is a solid phase joining technology. Because of its good weld performance and green pollution, it is widely used in the welding of light alloys in the aerospace and other industries [1-3]. However, if the welding parameters are not controlled properly in the welding process, abnormal material flow (MF) will lead to the formation of weld defects [4,5]. FSW process is a complex process of thermal-mechanical coupling, and the temperature field (TF) as the heat source input in the welding process is very important for the realization of FSW process. Some scholars have conducted some research on this process [6-9], but the simulation of temperature difference between the AS and the RS is relatively rare. The MF field has an important influence on the quality of weld forming, so it is necessary to study the MF, which is helpful to understand the process of FSW and explore the rule of weld forming [10]. In this paper, the finite element model of FSW is established to simulate the welding process, and the temperature field of the FSW process is studied. The temperature field of the welding zone has an important influence on the MF. Therefore, the numerical simulation of the MF in the plunging stage and the welding stage is carried out to study the influence of the tool on the MF trajectory. Finite Element Model The FSW process is a dynamic nonlinear process. The welding process is numerically simulated based on the Lagrange method. The tool material is W6, and the workpiece size is 150mm×100mm×6mm for the 2A14-T6 aluminum alloy. The tool shoulder diameter is 16.3mm, the tool cone angle is 15°, and the tool pin length is 5.7mm. In order to improve the accuracy of simulation solution, the workpiece and the tool are refined by adding meshwindow. the refined result is shown in Figure 1. The absolute mesh size is used to control the solution accuracy, but this method will increase the solution
{"title":"Numerical Simulation of Temperature Field and Material Flow in Friction Stir Welding","authors":"Tingke Wu, Haitao Luo, Hong Guo, Jia Fu, Guangming Liu","doi":"10.2991/MASTA-19.2019.56","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.56","url":null,"abstract":"In order to study the temperature field (TF) distribution and material flow (MF) in the friction stir welding process, the finite element model of friction stir welding (FSW) was established to simulate the welding process. The temperature field results showed that the temperature on the advancing side (AS) was higher than the retreating side (RS). The temperature field has an important influence on the material flow, so the material flow in the plunging stage and welding stage is simulated numerically to study the material flow trajectory in different stages. The results show that the material distribution is more uniform due to the long time in the plunging stage, and the amount of material flow in the plunging stage is larger than that in the welding stage. In the welding stage, it is found that the shoulder can promote the material flow. After analyzing the displacement of tracking particles in the welding stage, it is found that the displacement of particles on the AS is significantly higher than that on the axis and the RS. Introduction Friction stir welding (FSW) is a solid phase joining technology. Because of its good weld performance and green pollution, it is widely used in the welding of light alloys in the aerospace and other industries [1-3]. However, if the welding parameters are not controlled properly in the welding process, abnormal material flow (MF) will lead to the formation of weld defects [4,5]. FSW process is a complex process of thermal-mechanical coupling, and the temperature field (TF) as the heat source input in the welding process is very important for the realization of FSW process. Some scholars have conducted some research on this process [6-9], but the simulation of temperature difference between the AS and the RS is relatively rare. The MF field has an important influence on the quality of weld forming, so it is necessary to study the MF, which is helpful to understand the process of FSW and explore the rule of weld forming [10]. In this paper, the finite element model of FSW is established to simulate the welding process, and the temperature field of the FSW process is studied. The temperature field of the welding zone has an important influence on the MF. Therefore, the numerical simulation of the MF in the plunging stage and the welding stage is carried out to study the influence of the tool on the MF trajectory. Finite Element Model The FSW process is a dynamic nonlinear process. The welding process is numerically simulated based on the Lagrange method. The tool material is W6, and the workpiece size is 150mm×100mm×6mm for the 2A14-T6 aluminum alloy. The tool shoulder diameter is 16.3mm, the tool cone angle is 15°, and the tool pin length is 5.7mm. In order to improve the accuracy of simulation solution, the workpiece and the tool are refined by adding meshwindow. the refined result is shown in Figure 1. The absolute mesh size is used to control the solution accuracy, but this method will increase the solution","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125415517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.36
Zhengliang Zhou, Yue Qiang, H. Ran, Jin-yu Zhang
According to the status quo of a reservoir dam, relevant hydraulic calculations and structural calculations are carried out on the dam body and its ancillary buildings, which reveal that the dam body was not up to standard for flood control, the left abutment of the dam body was leaking, sliding resistance of downstream slope of dam body was insufficient, the height of the spillway side wall was insufficient, and length of the stilling pool was insufficient and so on. In response to these problems, the corresponding engineering and technical renovation measures were proposed for the main buildings of the dam. The results of finite element analysis and the implementation of renovation measures show that the renovation plan is economically reasonable and technically feasible, the reservoir diseases problems can be eliminated, the reservoir functions can be restored, and the renovation effect is obvious. Earth rock dams occupy a considerable proportion in the early construction of small reservoir dams in our country. Problems have appeared in some of them, such as dam body leakage, dam slope instability, failure of drainage measures, failure of flood control standards and so on after operating for many years, under the combined action of one or more factors such as unreasonable original design, low-level construction quality, unfulfillment of later operation management, untimely maintenance, earthquake disasters, termite disasters and so on [1]. The diseased reservoirs, which are out of repair for a long time, not only have low economic benefits, but also have great potential safety hazards, which seriously restrict the development of the comprehensive benefits of the reservoirs[2]. Therefore, it is imperative to improve and renovate the diseased reservoirs and restore the comprehensive performance of the old reservoirs. Taking a homogeneous earth reservoir dam as a typical case, this paper reveals many kinds of diseases existing in the homogeneous earth dam by calculation and analysis, and puts forward corresponding renovation measures, which can provide ideas and technical references for the renovation scheme of similar reservoir dams[3]. General Situation of Engineering A reservoir is located in a ditch in the upper reaches of Xian River, a tributary of Long River. The dam site is located in Changsha Bayi Village, Dining County, 8 km away from the county. There is no flood control and rescue road directly to the dam top, and traffic here is inconvenient. The total reservoir capacity is 129,000 m3, the dead reservoir capacity is 96,000 m3, the designed irrigation area is 312 mu, and the actual irrigation area is 100 mu. It is a small (2) type water conservancy project that is mainly based on irrigation and has comprehensive utilization of flood control. The reservoir dam is a homogeneous earth dam. It is with a maximum height of 11.21m, a bottom elevation of 463.06m, a top elevation of 474.27m, a top width of 2.7m, a top length of 89.60m and a bot
{"title":"Study on Safety Assessment and Renovation Measures of a Reservoir Dam","authors":"Zhengliang Zhou, Yue Qiang, H. Ran, Jin-yu Zhang","doi":"10.2991/MASTA-19.2019.36","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.36","url":null,"abstract":"According to the status quo of a reservoir dam, relevant hydraulic calculations and structural calculations are carried out on the dam body and its ancillary buildings, which reveal that the dam body was not up to standard for flood control, the left abutment of the dam body was leaking, sliding resistance of downstream slope of dam body was insufficient, the height of the spillway side wall was insufficient, and length of the stilling pool was insufficient and so on. In response to these problems, the corresponding engineering and technical renovation measures were proposed for the main buildings of the dam. The results of finite element analysis and the implementation of renovation measures show that the renovation plan is economically reasonable and technically feasible, the reservoir diseases problems can be eliminated, the reservoir functions can be restored, and the renovation effect is obvious. Earth rock dams occupy a considerable proportion in the early construction of small reservoir dams in our country. Problems have appeared in some of them, such as dam body leakage, dam slope instability, failure of drainage measures, failure of flood control standards and so on after operating for many years, under the combined action of one or more factors such as unreasonable original design, low-level construction quality, unfulfillment of later operation management, untimely maintenance, earthquake disasters, termite disasters and so on [1]. The diseased reservoirs, which are out of repair for a long time, not only have low economic benefits, but also have great potential safety hazards, which seriously restrict the development of the comprehensive benefits of the reservoirs[2]. Therefore, it is imperative to improve and renovate the diseased reservoirs and restore the comprehensive performance of the old reservoirs. Taking a homogeneous earth reservoir dam as a typical case, this paper reveals many kinds of diseases existing in the homogeneous earth dam by calculation and analysis, and puts forward corresponding renovation measures, which can provide ideas and technical references for the renovation scheme of similar reservoir dams[3]. General Situation of Engineering A reservoir is located in a ditch in the upper reaches of Xian River, a tributary of Long River. The dam site is located in Changsha Bayi Village, Dining County, 8 km away from the county. There is no flood control and rescue road directly to the dam top, and traffic here is inconvenient. The total reservoir capacity is 129,000 m3, the dead reservoir capacity is 96,000 m3, the designed irrigation area is 312 mu, and the actual irrigation area is 100 mu. It is a small (2) type water conservancy project that is mainly based on irrigation and has comprehensive utilization of flood control. The reservoir dam is a homogeneous earth dam. It is with a maximum height of 11.21m, a bottom elevation of 463.06m, a top elevation of 474.27m, a top width of 2.7m, a top length of 89.60m and a bot","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128062061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.2991/MASTA-19.2019.20
Ziji’an Wang, Chao Chen, Xiao-le Li, Jing Li
This paper proposed a method to forecast the short-term passenger flow, which is a vital component of urban rail transit system. We used a hybrid EMD-LSTM prediction model which combines empirical mode decomposition (EMD) and long short-term memory (LSTM) to forecast the short-term passenger flow in urban rail transit system. EMD can extract the variation trend of passenger flow, then LSTM can make the prediction to prove the accuracy. The experimental results indicate that the EMD-LSTM model used in this paper has better prediction accuracy than the LSTM model alone. Besides, the amount of data used in this experiment is small, and there is no need to consider additional features except temporal factor. According to what we have learned, this is the first time to combine EMD and LSTM to make short-term prediction in the urban rail transit system. Introduction Short-term passenger flow forecasting is a vital component of urban rail transit system. The forecasting results is an important basis for urban rail transit feasibility study and design, and also the main basis of project construction. In the recent studies, linear forecasting method and non-linear forecasting method are used. Grey System Theory and ARIMA are the represent of linear forecasting methods. LSTM [1], deep learning [2] and spatio-temporal deep learning [3] are the represent of nonlinear forecasting methods. Urban rail transit passenger flow has the characteristics of non-linear, periodicity and random, and it is inapplicability for short-term passenger flow forecasting. Moreover, some factors, like emergency, which affect passenger flow, are hard to acquire or forecast. So as to solve this problem, hybrid EMD-LSTM prediction model is used. Firstly, the passenger flow data of Beijing subway Line 10 is used, considering only the time characteristics of the data, then the hybrid EMD-LSTM prediction model is used. The EMD is used to decompose the original passenger flow data, and statistical method is used to select each component, then LSTM is used to predict each component separately. Finally, the prediction results of each component are added to the final result. Methodology Empirical Mode Decomposition Empirical mode decomposition (EMD) [4] is a signal decomposition algorithm, which is suitable for non-liner and non-stationary signal. The original time series signal can be decomposed into a small number of oscillatory modes which can be expressed as some intrinsic modals functions (IMF) and a residue. The residue retains a non-periodic trend of the original signal, and any periodic fluctuation in original signal will be decomposed into IMFs. IMFs must satisfy the following two conditions [4]: 1. In the whole data set, the number of extrema and the number of zero crossings must either equal or differ at most by one. 2. At any point, the mean value of the envelope defined by the local maxima and the envelope defined by the local minima is zero. International Conference on Modelin
{"title":"Short-term Urban Rail Transit Passenger Flow Forecasting Based on Empirical Mode Decomposition and LSTM","authors":"Ziji’an Wang, Chao Chen, Xiao-le Li, Jing Li","doi":"10.2991/MASTA-19.2019.20","DOIUrl":"https://doi.org/10.2991/MASTA-19.2019.20","url":null,"abstract":"This paper proposed a method to forecast the short-term passenger flow, which is a vital component of urban rail transit system. We used a hybrid EMD-LSTM prediction model which combines empirical mode decomposition (EMD) and long short-term memory (LSTM) to forecast the short-term passenger flow in urban rail transit system. EMD can extract the variation trend of passenger flow, then LSTM can make the prediction to prove the accuracy. The experimental results indicate that the EMD-LSTM model used in this paper has better prediction accuracy than the LSTM model alone. Besides, the amount of data used in this experiment is small, and there is no need to consider additional features except temporal factor. According to what we have learned, this is the first time to combine EMD and LSTM to make short-term prediction in the urban rail transit system. Introduction Short-term passenger flow forecasting is a vital component of urban rail transit system. The forecasting results is an important basis for urban rail transit feasibility study and design, and also the main basis of project construction. In the recent studies, linear forecasting method and non-linear forecasting method are used. Grey System Theory and ARIMA are the represent of linear forecasting methods. LSTM [1], deep learning [2] and spatio-temporal deep learning [3] are the represent of nonlinear forecasting methods. Urban rail transit passenger flow has the characteristics of non-linear, periodicity and random, and it is inapplicability for short-term passenger flow forecasting. Moreover, some factors, like emergency, which affect passenger flow, are hard to acquire or forecast. So as to solve this problem, hybrid EMD-LSTM prediction model is used. Firstly, the passenger flow data of Beijing subway Line 10 is used, considering only the time characteristics of the data, then the hybrid EMD-LSTM prediction model is used. The EMD is used to decompose the original passenger flow data, and statistical method is used to select each component, then LSTM is used to predict each component separately. Finally, the prediction results of each component are added to the final result. Methodology Empirical Mode Decomposition Empirical mode decomposition (EMD) [4] is a signal decomposition algorithm, which is suitable for non-liner and non-stationary signal. The original time series signal can be decomposed into a small number of oscillatory modes which can be expressed as some intrinsic modals functions (IMF) and a residue. The residue retains a non-periodic trend of the original signal, and any periodic fluctuation in original signal will be decomposed into IMFs. IMFs must satisfy the following two conditions [4]: 1. In the whole data set, the number of extrema and the number of zero crossings must either equal or differ at most by one. 2. At any point, the mean value of the envelope defined by the local maxima and the envelope defined by the local minima is zero. International Conference on Modelin","PeriodicalId":103896,"journal":{"name":"Proceedings of the 2019 International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128140402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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