As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’trav...As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel efficiency.However,in the IoV system,there are always malicious vehicle nodes publishing false information.Therefore,it is essential to ensure the legitimacy of the source.In addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance bottlenecks.Most existing authentication schemes have the problem of low authentication efficiency in the scenario.To address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour Traffic.Here,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message authentication.In addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network attacks.In the simulation experiment,we compare our scheme with other existing works.Our scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.展开更多
Vision-based vehicle detection in adverse weather conditions such as fog,haze,and mist is a challenging research area in the fields of autonomous vehicles,collision avoidance,and Internet of Things(IoT)-enabled edge/f...Vision-based vehicle detection in adverse weather conditions such as fog,haze,and mist is a challenging research area in the fields of autonomous vehicles,collision avoidance,and Internet of Things(IoT)-enabled edge/fog computing traffic surveillance and monitoring systems.Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time.To evaluate vision-based vehicle detection performance in foggy weather conditions,state-of-the-art Vehicle Detection in Adverse Weather Nature(DAWN)and Foggy Driving(FD)datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle detection classes:cars,buses,motorcycles,and trucks.The state-of-the-art single-stage deep learning algorithms YOLO-V5,and YOLO-V8 are considered for the task of vehicle detection.Furthermore,YOLO-V5s is enhanced by introducing attention modules Convolutional Block Attention Module(CBAM),Normalized-based Attention Module(NAM),and Simple Attention Module(SimAM)after the SPPF module as well as YOLO-V5l with BiFPN.Their vehicle detection accuracy parameters and running speed is validated on cloud(Google Colab)and edge(local)systems.The mAP50 score of YOLO-V5n is 72.60%,YOLOV5s is 75.20%,YOLO-V5m is 73.40%,and YOLO-V5l is 77.30%;and YOLO-V8n is 60.20%,YOLO-V8s is 73.50%,YOLO-V8m is 73.80%,and YOLO-V8l is 72.60%on DAWN dataset.The mAP50 score of YOLO-V5n is 43.90%,YOLO-V5s is 40.10%,YOLO-V5m is 49.70%,and YOLO-V5l is 57.30%;and YOLO-V8n is 41.60%,YOLO-V8s is 46.90%,YOLO-V8m is 42.90%,and YOLO-V8l is 44.80%on FD dataset.The vehicle detection speed of YOLOV5n is 59 Frame Per Seconds(FPS),YOLO-V5s is 47 FPS,YOLO-V5m is 38 FPS,and YOLO-V5l is 30 FPS;and YOLO-V8n is 185 FPS,YOLO-V8s is 109 FPS,YOLO-V8m is 72 FPS,and YOLO-V8l is 63 FPS on DAWN dataset.The vehicle detection speed of YOLO-V5n is 26 FPS,YOLO-V5s is 24 FPS,YOLO-V5m is 22 FPS,and YOLO-V5l is 17 FPS;and YOLO-V8n is 313 FPS,YOLO-V8s is 182 FPS,YOLO-V8m is 99 FPS,and YOLO-V8l is 60 FPS on FD dataset.YOLO-V5s,YOLO-V5s variants and YOLO-V5l_BiFPN,and YOLO-V8 algorithms are efficient and cost-effective solution for real-time vision-based vehicle detection in foggy weather.展开更多
A mathematic model is established using infinitesimal geometry for the cutting edge design of special milling cutters which use equal lead helix as cutting edges; equations are given for front-end and proclitic surfac...A mathematic model is established using infinitesimal geometry for the cutting edge design of special milling cutters which use equal lead helix as cutting edges; equations are given for front-end and proclitic surface of revolution of ball pillar milling cutters, ball taper milling cutters and angularly conical milling cutters; and corresponding models are established for the continuity cutting edge curves of milling cutters. Typical examples are given to illustrate the applications of mathematic models, which prove the correctness and applicability of these geometric models.展开更多
With the high-speed development of digital image processing technology, machine vision technology has been widely used in automatic detection of industrial products. A large amount of products can be treated by comput...With the high-speed development of digital image processing technology, machine vision technology has been widely used in automatic detection of industrial products. A large amount of products can be treated by computer instead of human in a shorter time. In the process of automatic detection, edge detection is one of the most commonly used methods. But with the increasing demand for detection precision,traditional pixel-level methods are difficult to meet the requirement, and more subpixel level methods are in the use. This paper presents a new method to detect curved edge with high precision. First, the target area ratio of pixels near the edge is computed by using one-dimensional edge detection method. Second, parabola is used to approximately represent the curved edge. And we select appropriate parameters to obtain accurate results. This method is able to detect curved edges in subpixel level, and shows its practical effectiveness in automatic measure of products with arc shape in large industrial scene.展开更多
L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assig...L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assignment of integers to the vertices of G such that adjacent vertices receive integers which differ by at least s, and vertices that are at distance of two receive integers which differ by at least t. Given an L（s, t） -labeling f of a graph G, the L（s, t） edge span of f, βst （ G, f） = max { ｜f（u） -f（v）｜： （ u, v） ∈ E（G） } is defined. The L（ s, t） edge span of G, βst（G）, is minβst（G,f）, where the minimum runs over all L（s, t）-labelings f of G. Let T be any tree with a maximum degree of △≥2. It is proved that if 2s≥t≥0, then βst（T） =（ [△/2 ] - 1）t ＋s; if 0≤2s 〈 t and △ is even, then βst（T） = [ （△ - 1） t/2 ] ; and if 0 ≤2s 〈 t and △ is odd, then βst（T） = （△ - 1） t/2 ＋ s. Thus, the L（s, t） edge spans of the Cartesian product of two paths and of the square lattice are completely determined.展开更多
AIM：To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS：Fifteen subjects were recruited. The corneal images from optic...AIM：To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS：Fifteen subjects were recruited. The corneal images from optical coherence tomography（OCT）were imported into Matlab software. Five edge detection methods（Canny,Log,Prewitt,Roberts,Sobel）were used to identify the corneal surface. Then two manual identifying methods（ginput and getpts）were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve（y=Ax2＋Bx＋C）,Polynomial curve [p（x）=p1xn＋p2x（n-1）＋....＋pnx＋pn＋1] and Conic section（Ax2＋Bxy＋Cy2＋Dx＋Ey＋F=0）were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally,the eccentricity（e）obtained by corneal topography and conic section were compared with paired t-test. RESULTS：Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis,eccentricity,circle center,etc. There were no significant differences between ＇e＇ values by corneal topography and conic section（t=0.9143,P=0.3760 〉0.05）.CONCLUSION：It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.展开更多
The qualitative solutions of dynamical system expressed with nonlinear differential equation can be divided into two categories. One is that the motion of phase point may approach infinite or stable equilibrium point ...The qualitative solutions of dynamical system expressed with nonlinear differential equation can be divided into two categories. One is that the motion of phase point may approach infinite or stable equilibrium point eventually. Neither periodic excited source nor self-excited oscillation exists in such nonlinear dynamic circuits, so its solution cannot be treated as the synthesis of multiharmonic. And the other is that the endless vibration of phase point is limited within certain range, moreover possesses character of sustained oscillation, namely the bounded nonlinear oscillation. It can persistently and repeatedly vibration after dynamic variable entering into steady state;moreover the motion of phase point will not approach infinite at last;system has not stable equilibrium point. The motional trajectory can be described by a bounded space curve. So far, the curve cannot be represented by concretely explicit parametric form in math. It cannot be expressed analytically by human. The chaos is a most universally common form of bounded nonlinear oscillation. A number of chaotic systems, such as Lorenz equation, Chua’s circuit and lossless system in modern times are some examples among thousands of chaotic equations. In this work, basic properties related to the bounded space curve will be comprehensively summarized by analyzing these examples.展开更多
The algorithms for feedrate profile generation,such as linear and S-curve profiles,have been widely used in machinery controllers,and these algorithms can greatly improve the smoothness of motion.However,most of the a...The algorithms for feedrate profile generation,such as linear and S-curve profiles,have been widely used in machinery controllers,and these algorithms can greatly improve the smoothness of motion.However,most of the algorithms lead to the discontinuous acceleration/deceleration and jerk,or high jerk levels,which is very harmful to machine tool or robot in most occasions. This paper presents a smooth S-curve feedrate profiling generation algorithm that produces continuous feedrate,acceleration,and jerk profiles.Smooth jerk is obtained by imposing limits on the first and second time derivatives of acceleration,resulting in trapezoidal jerk profiles along the tool path.The discretization of smooth S-curve feedrate is realized with a novel approach that improves the efficiency without calculating the deceleration point in each sampled time.To ensure that the interpolation time is a multiple of the value of sampled time,the feedrate,acceleration,jerk,and jerk derivative are recalculated.Meantime,to improve the efficiency,the interpolation steps of all regions are computed before interpolation.According to the distance of trajectory,the smooth S-curve acceleration and decelerations are divided into three blocks：normal block,short block type-Ⅰ,and short block type-Ⅱ.Finally feedrate discretization of short block type-Ⅰand type-Ⅱis obtained with considering the efficiency.The proposed generation algorithm is tested in machining a part on a five axis milling machine,which is controlled with the CNC system for newly developed high-speed machine tools.The test result shows that the smooth S-curve approach has the smoother feedrate,acceleration,deceleration,and jerk profiles than S-curve.The proposed algorithm ensures the automated machinery motion smoothness,and improves the quality and efficiency of the automated machinery motion planning.展开更多
A novel type curve is presented for oil recovery factor prediction suitable for gas flooding by innovatively introducing the equivalent water-gas cut to replace the water cut,comprehensively considering the impact of ...A novel type curve is presented for oil recovery factor prediction suitable for gas flooding by innovatively introducing the equivalent water-gas cut to replace the water cut,comprehensively considering the impact of three-phase flow(oil,gas,water),and deriving the theoretical equations of gas flooding type curve based on Tong’s type curve.The equivalent water-gas cut is the ratio of the cumulative underground volume of gas and water production to the total underground volume of produced fluids.Field production data and the numerical simulation results are used to demonstrate the feasibility of the new type curve and verify the accuracy of the prediction results with field cases.The new type curve is suitable for oil recovery factor prediction of both water flooding and gas flooding.When a reservoir has no gas injected or produced,the gas phase can be ignored and only the oil and water phases need to be considered,in this case,this gas flooding type curve returns to the Tong’s type curve,which can evaluate the oil recovery factor of water flooding.For reservoirs with equivalent water-gas cuts of 60%-80%,the regression method of the new type curve works well in predicting the oil recovery factor.For reservoirs with equivalent water-gas cuts higher than 80%,both the regression and assignment methods of the new type curve can accurately predict the oil recovery factor of gas flooding.展开更多
The alternating method based on the fundamental solutions of the infinite domain containing a crack,namely Muskhelishvili’s solutions,divides the complex structure with a crack into a simple model without crack which...The alternating method based on the fundamental solutions of the infinite domain containing a crack,namely Muskhelishvili’s solutions,divides the complex structure with a crack into a simple model without crack which can be solved by traditional numerical methods and an infinite domain with a crack which can be solved by Muskhelishvili’s solutions.However,this alternating method cannot be directly applied to the edge crack problems since partial crack surface of Muskhelishvili’s solutions is located outside the computational domain.In this paper,an improved alternating method,the spline fictitious boundary element alternating method(SFBEAM),based on infinite domain with the combination of spline fictitious boundary element method(SFBEM)and Muskhelishvili’s solutions is proposed to solve the edge crack problems.Since the SFBEM and Muskhelishvili’s solutions are obtained in the framework of infinite domain,no special treatment is needed for solving the problem of edge cracks.Different mixed boundary conditions edge crack problems with varies of computational parameters are given to certify the high precision,efficiency and applicability of the proposed method compared with other alternating methods and extend finite element method.展开更多
基金funded by Guangxi Natural Science Foundation General Project—Research on Visual Positioning and Navigation Robot Based on Deep Learning,Project Number:2023GXNSFAA026025.
文摘As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel efficiency.However,in the IoV system,there are always malicious vehicle nodes publishing false information.Therefore,it is essential to ensure the legitimacy of the source.In addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance bottlenecks.Most existing authentication schemes have the problem of low authentication efficiency in the scenario.To address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour Traffic.Here,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message authentication.In addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network attacks.In the simulation experiment,we compare our scheme with other existing works.Our scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-RG23129).
文摘Vision-based vehicle detection in adverse weather conditions such as fog,haze,and mist is a challenging research area in the fields of autonomous vehicles,collision avoidance,and Internet of Things(IoT)-enabled edge/fog computing traffic surveillance and monitoring systems.Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time.To evaluate vision-based vehicle detection performance in foggy weather conditions,state-of-the-art Vehicle Detection in Adverse Weather Nature(DAWN)and Foggy Driving(FD)datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle detection classes:cars,buses,motorcycles,and trucks.The state-of-the-art single-stage deep learning algorithms YOLO-V5,and YOLO-V8 are considered for the task of vehicle detection.Furthermore,YOLO-V5s is enhanced by introducing attention modules Convolutional Block Attention Module(CBAM),Normalized-based Attention Module(NAM),and Simple Attention Module(SimAM)after the SPPF module as well as YOLO-V5l with BiFPN.Their vehicle detection accuracy parameters and running speed is validated on cloud(Google Colab)and edge(local)systems.The mAP50 score of YOLO-V5n is 72.60%,YOLOV5s is 75.20%,YOLO-V5m is 73.40%,and YOLO-V5l is 77.30%;and YOLO-V8n is 60.20%,YOLO-V8s is 73.50%,YOLO-V8m is 73.80%,and YOLO-V8l is 72.60%on DAWN dataset.The mAP50 score of YOLO-V5n is 43.90%,YOLO-V5s is 40.10%,YOLO-V5m is 49.70%,and YOLO-V5l is 57.30%;and YOLO-V8n is 41.60%,YOLO-V8s is 46.90%,YOLO-V8m is 42.90%,and YOLO-V8l is 44.80%on FD dataset.The vehicle detection speed of YOLOV5n is 59 Frame Per Seconds(FPS),YOLO-V5s is 47 FPS,YOLO-V5m is 38 FPS,and YOLO-V5l is 30 FPS;and YOLO-V8n is 185 FPS,YOLO-V8s is 109 FPS,YOLO-V8m is 72 FPS,and YOLO-V8l is 63 FPS on DAWN dataset.The vehicle detection speed of YOLO-V5n is 26 FPS,YOLO-V5s is 24 FPS,YOLO-V5m is 22 FPS,and YOLO-V5l is 17 FPS;and YOLO-V8n is 313 FPS,YOLO-V8s is 182 FPS,YOLO-V8m is 99 FPS,and YOLO-V8l is 60 FPS on FD dataset.YOLO-V5s,YOLO-V5s variants and YOLO-V5l_BiFPN,and YOLO-V8 algorithms are efficient and cost-effective solution for real-time vision-based vehicle detection in foggy weather.
文摘A mathematic model is established using infinitesimal geometry for the cutting edge design of special milling cutters which use equal lead helix as cutting edges; equations are given for front-end and proclitic surface of revolution of ball pillar milling cutters, ball taper milling cutters and angularly conical milling cutters; and corresponding models are established for the continuity cutting edge curves of milling cutters. Typical examples are given to illustrate the applications of mathematic models, which prove the correctness and applicability of these geometric models.
基金This work was supported in part by the National Natural Science Foundation of China (No. 61170094), Shanghai Committee of Science and Technology (14JC1402202 and 14441904403), and 863 Program 2014AA015101.
文摘With the high-speed development of digital image processing technology, machine vision technology has been widely used in automatic detection of industrial products. A large amount of products can be treated by computer instead of human in a shorter time. In the process of automatic detection, edge detection is one of the most commonly used methods. But with the increasing demand for detection precision,traditional pixel-level methods are difficult to meet the requirement, and more subpixel level methods are in the use. This paper presents a new method to detect curved edge with high precision. First, the target area ratio of pixels near the edge is computed by using one-dimensional edge detection method. Second, parabola is used to approximately represent the curved edge. And we select appropriate parameters to obtain accurate results. This method is able to detect curved edges in subpixel level, and shows its practical effectiveness in automatic measure of products with arc shape in large industrial scene.
基金The National Natural Science Foundation of China(No10671033)Southeast University Science Foundation ( NoXJ0607230)
文摘L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assignment of integers to the vertices of G such that adjacent vertices receive integers which differ by at least s, and vertices that are at distance of two receive integers which differ by at least t. Given an L（s, t） -labeling f of a graph G, the L（s, t） edge span of f, βst （ G, f） = max { ｜f（u） -f（v）｜： （ u, v） ∈ E（G） } is defined. The L（ s, t） edge span of G, βst（G）, is minβst（G,f）, where the minimum runs over all L（s, t）-labelings f of G. Let T be any tree with a maximum degree of △≥2. It is proved that if 2s≥t≥0, then βst（T） =（ [△/2 ] - 1）t ＋s; if 0≤2s 〈 t and △ is even, then βst（T） = [ （△ - 1） t/2 ] ; and if 0 ≤2s 〈 t and △ is odd, then βst（T） = （△ - 1） t/2 ＋ s. Thus, the L（s, t） edge spans of the Cartesian product of two paths and of the square lattice are completely determined.
基金Supported by the National Natural Science Foundation of China(No.81400428)Science and Technology Commission of Shanghai Municipality(No.134119b1600)
文摘AIM：To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS：Fifteen subjects were recruited. The corneal images from optical coherence tomography（OCT）were imported into Matlab software. Five edge detection methods（Canny,Log,Prewitt,Roberts,Sobel）were used to identify the corneal surface. Then two manual identifying methods（ginput and getpts）were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve（y=Ax2＋Bx＋C）,Polynomial curve [p（x）=p1xn＋p2x（n-1）＋....＋pnx＋pn＋1] and Conic section（Ax2＋Bxy＋Cy2＋Dx＋Ey＋F=0）were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally,the eccentricity（e）obtained by corneal topography and conic section were compared with paired t-test. RESULTS：Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis,eccentricity,circle center,etc. There were no significant differences between ＇e＇ values by corneal topography and conic section（t=0.9143,P=0.3760 〉0.05）.CONCLUSION：It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.
文摘The qualitative solutions of dynamical system expressed with nonlinear differential equation can be divided into two categories. One is that the motion of phase point may approach infinite or stable equilibrium point eventually. Neither periodic excited source nor self-excited oscillation exists in such nonlinear dynamic circuits, so its solution cannot be treated as the synthesis of multiharmonic. And the other is that the endless vibration of phase point is limited within certain range, moreover possesses character of sustained oscillation, namely the bounded nonlinear oscillation. It can persistently and repeatedly vibration after dynamic variable entering into steady state;moreover the motion of phase point will not approach infinite at last;system has not stable equilibrium point. The motional trajectory can be described by a bounded space curve. So far, the curve cannot be represented by concretely explicit parametric form in math. It cannot be expressed analytically by human. The chaos is a most universally common form of bounded nonlinear oscillation. A number of chaotic systems, such as Lorenz equation, Chua’s circuit and lossless system in modern times are some examples among thousands of chaotic equations. In this work, basic properties related to the bounded space curve will be comprehensively summarized by analyzing these examples.
基金supported by Major National S&T Program of China (Grant No.2009ZX04009-014-02)National Hi-tech Research and Development Program of China(863 Program,Grant No. 2009AA043901)
文摘The algorithms for feedrate profile generation,such as linear and S-curve profiles,have been widely used in machinery controllers,and these algorithms can greatly improve the smoothness of motion.However,most of the algorithms lead to the discontinuous acceleration/deceleration and jerk,or high jerk levels,which is very harmful to machine tool or robot in most occasions. This paper presents a smooth S-curve feedrate profiling generation algorithm that produces continuous feedrate,acceleration,and jerk profiles.Smooth jerk is obtained by imposing limits on the first and second time derivatives of acceleration,resulting in trapezoidal jerk profiles along the tool path.The discretization of smooth S-curve feedrate is realized with a novel approach that improves the efficiency without calculating the deceleration point in each sampled time.To ensure that the interpolation time is a multiple of the value of sampled time,the feedrate,acceleration,jerk,and jerk derivative are recalculated.Meantime,to improve the efficiency,the interpolation steps of all regions are computed before interpolation.According to the distance of trajectory,the smooth S-curve acceleration and decelerations are divided into three blocks：normal block,short block type-Ⅰ,and short block type-Ⅱ.Finally feedrate discretization of short block type-Ⅰand type-Ⅱis obtained with considering the efficiency.The proposed generation algorithm is tested in machining a part on a five axis milling machine,which is controlled with the CNC system for newly developed high-speed machine tools.The test result shows that the smooth S-curve approach has the smoother feedrate,acceleration,deceleration,and jerk profiles than S-curve.The proposed algorithm ensures the automated machinery motion smoothness,and improves the quality and efficiency of the automated machinery motion planning.
基金Supported by the National Natural Science Foundation of China(51974268)the Sichuan Province Science and Technology Program(2019YJ0423)。
文摘A novel type curve is presented for oil recovery factor prediction suitable for gas flooding by innovatively introducing the equivalent water-gas cut to replace the water cut,comprehensively considering the impact of three-phase flow(oil,gas,water),and deriving the theoretical equations of gas flooding type curve based on Tong’s type curve.The equivalent water-gas cut is the ratio of the cumulative underground volume of gas and water production to the total underground volume of produced fluids.Field production data and the numerical simulation results are used to demonstrate the feasibility of the new type curve and verify the accuracy of the prediction results with field cases.The new type curve is suitable for oil recovery factor prediction of both water flooding and gas flooding.When a reservoir has no gas injected or produced,the gas phase can be ignored and only the oil and water phases need to be considered,in this case,this gas flooding type curve returns to the Tong’s type curve,which can evaluate the oil recovery factor of water flooding.For reservoirs with equivalent water-gas cuts of 60%-80%,the regression method of the new type curve works well in predicting the oil recovery factor.For reservoirs with equivalent water-gas cuts higher than 80%,both the regression and assignment methods of the new type curve can accurately predict the oil recovery factor of gas flooding.
基金supported by the National Natural Science Foundation of China(51078150)the National Natural Science Foundation of China(11602087)+1 种基金the State Key Laboratory of Subtropical Building Science,South China University of Technology(2017ZB32)National Undergraduate Innovative and Entrepreneurial Training Program(201810561180).
文摘The alternating method based on the fundamental solutions of the infinite domain containing a crack,namely Muskhelishvili’s solutions,divides the complex structure with a crack into a simple model without crack which can be solved by traditional numerical methods and an infinite domain with a crack which can be solved by Muskhelishvili’s solutions.However,this alternating method cannot be directly applied to the edge crack problems since partial crack surface of Muskhelishvili’s solutions is located outside the computational domain.In this paper,an improved alternating method,the spline fictitious boundary element alternating method(SFBEAM),based on infinite domain with the combination of spline fictitious boundary element method(SFBEM)and Muskhelishvili’s solutions is proposed to solve the edge crack problems.Since the SFBEM and Muskhelishvili’s solutions are obtained in the framework of infinite domain,no special treatment is needed for solving the problem of edge cracks.Different mixed boundary conditions edge crack problems with varies of computational parameters are given to certify the high precision,efficiency and applicability of the proposed method compared with other alternating methods and extend finite element method.
