Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extens...Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.展开更多
A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element...A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element shape functions, which form a partition of unity, with the local subspaces defined on the corresponding shape functions, which include a priori knowledge about the wave motion equation in trial spaces and approximately reproduce the highly oscillatory properties within a single element. Numerical examples demonstrate the performance of the proposed partition of unity finite element in both computational accuracy and efficiency.展开更多
A revised displacement discontinuity method(DDM) program is developed for the simulation of rock joint propagation and dilatancy analysis. The non-linear joint model used in the program adopts Barton-Bandis normal def...A revised displacement discontinuity method(DDM) program is developed for the simulation of rock joint propagation and dilatancy analysis. The non-linear joint model used in the program adopts Barton-Bandis normal deformation model, Kulhaway shear deformation model and Mohr-Coulomb criterion. The joint propagation criterion is based on the equivalent stress intensity factor which can be obtained by regression analysis. The simulated rock joint propagation accords well with the existing knowledge. The closure and opening of joint is investigated by DDM, and it is shown that if the opening volume of propagated joint is larger than closure volume of the old joint, the joint dilatancy occurs. The dilatancy condition is mainly controlled by the normal stiffness of the rock joint. When the normal stiffness is larger than the critical value, joint dilatancy occurs. The critical normal stiffness of rock joint changes with the joint-load angle, and joint dilatancy is most possible to occur at 30°.展开更多
Partition of unity based numerical manifold method can solve continuous and discontinuous problems in a unified framework with a two-cover system,i.e.,the mathematical cover and physical cover.However,renewal of the t...Partition of unity based numerical manifold method can solve continuous and discontinuous problems in a unified framework with a two-cover system,i.e.,the mathematical cover and physical cover.However,renewal of the topology of the two-cover system poses a challenge for multiple crack propagation problems and there are few references.In this study,a robust and efficient strategy is proposed to update the cover system of the numerical manifold method in simulation of multiple crack propagation problems.The proposed algorithm updates the cover system with a bottom-up process:1)identification of fractured manifold elements according to the previous and latest crack tip position;and 2)local topological update of the manifold elements,physical patches,block boundary loops,and non-persistent joint loops according to the scenario classification of the propagating crack.The proposed crack tracking strategy and classification of the renewal cases promote a robust and efficient cover renewal algorithm for multiple crack propagation analysis.Three crack propagation examples show that the proposed algorithm performs well in updating the cover system.This cover renewal methodology can be extended for numerical manifold method with polygonal mathematical covers.展开更多
[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under c...[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions,such as strong light exposure and weed interference.The aims are to develop an effective crop line extraction method by combining YOLOv8-G,Affinity Propagation,and the Least Squares method to enhance detection accuracy and performance in complex field environments.[Methods]The proposed method employs machine vision techniques to address common field challenges.YOLOv8-G,an improved object detection algorithm that combines YOLOv8 and Ghost‐NetV2 for lightweight,high-speed performance,was used to detect the central points of crops.These points were then clustered using the Affinity Propagation algorithm,followed by the application of the Least Squares method to extract the crop lines.Comparative tests were conducted to evaluate multiple backbone networks within the YOLOv8 framework,and ablation studies were performed to validate the enhancements made in YOLOv8-G.[Results and Discussions]The performance of the proposed method was compared with classical object detection and clustering algorithms.The YOLOv8-G algorithm achieved average precision(AP)values of 98.22%,98.15%,and 97.32%for corn detection at 7,14,and 21 days after emergence,respectively.Additionally,the crop line extraction accuracy across all stages was 96.52%.These results demonstrate the model's ability to maintain high detection accuracy despite challenging conditions in the field.[Conclusions]The proposed crop line extraction method effectively addresses field challenges such as lighting and weed interference,enabling rapid and accurate crop identification.This approach supports the automatic navigation of agricultural machinery,offering significant improvements in the precision and efficiency of field operations.展开更多
针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为...针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。展开更多
基金Project(52175445)supported by the National Natural Science Foundation of ChinaProject(2022JJ30743)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(2023GK2024)supported by the Key Research and Development Program of Hunan Province,ChinaProject(2023ZZTS0391)supported by the Fundamental Research Funds for the Central Universities of China。
文摘Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.
基金Project supported by the National Basic Research Program of China (973Project) (No.2002CB412709) and the National Natural Science Foundation of China (Nos.50278012,10272027,19832010)
文摘A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element shape functions, which form a partition of unity, with the local subspaces defined on the corresponding shape functions, which include a priori knowledge about the wave motion equation in trial spaces and approximately reproduce the highly oscillatory properties within a single element. Numerical examples demonstrate the performance of the proposed partition of unity finite element in both computational accuracy and efficiency.
基金Project(2009318000046) supported by the Western Transport Technical Program of the Ministry of Transport,China
文摘A revised displacement discontinuity method(DDM) program is developed for the simulation of rock joint propagation and dilatancy analysis. The non-linear joint model used in the program adopts Barton-Bandis normal deformation model, Kulhaway shear deformation model and Mohr-Coulomb criterion. The joint propagation criterion is based on the equivalent stress intensity factor which can be obtained by regression analysis. The simulated rock joint propagation accords well with the existing knowledge. The closure and opening of joint is investigated by DDM, and it is shown that if the opening volume of propagated joint is larger than closure volume of the old joint, the joint dilatancy occurs. The dilatancy condition is mainly controlled by the normal stiffness of the rock joint. When the normal stiffness is larger than the critical value, joint dilatancy occurs. The critical normal stiffness of rock joint changes with the joint-load angle, and joint dilatancy is most possible to occur at 30°.
基金Project(51321065,51479191,11672360)supported by the National Natural Science Foundation of China。
文摘Partition of unity based numerical manifold method can solve continuous and discontinuous problems in a unified framework with a two-cover system,i.e.,the mathematical cover and physical cover.However,renewal of the topology of the two-cover system poses a challenge for multiple crack propagation problems and there are few references.In this study,a robust and efficient strategy is proposed to update the cover system of the numerical manifold method in simulation of multiple crack propagation problems.The proposed algorithm updates the cover system with a bottom-up process:1)identification of fractured manifold elements according to the previous and latest crack tip position;and 2)local topological update of the manifold elements,physical patches,block boundary loops,and non-persistent joint loops according to the scenario classification of the propagating crack.The proposed crack tracking strategy and classification of the renewal cases promote a robust and efficient cover renewal algorithm for multiple crack propagation analysis.Three crack propagation examples show that the proposed algorithm performs well in updating the cover system.This cover renewal methodology can be extended for numerical manifold method with polygonal mathematical covers.
文摘[Objective]Crop line extraction is critical for improving the efficiency of autonomous agricultural machines in the field.However,traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions,such as strong light exposure and weed interference.The aims are to develop an effective crop line extraction method by combining YOLOv8-G,Affinity Propagation,and the Least Squares method to enhance detection accuracy and performance in complex field environments.[Methods]The proposed method employs machine vision techniques to address common field challenges.YOLOv8-G,an improved object detection algorithm that combines YOLOv8 and Ghost‐NetV2 for lightweight,high-speed performance,was used to detect the central points of crops.These points were then clustered using the Affinity Propagation algorithm,followed by the application of the Least Squares method to extract the crop lines.Comparative tests were conducted to evaluate multiple backbone networks within the YOLOv8 framework,and ablation studies were performed to validate the enhancements made in YOLOv8-G.[Results and Discussions]The performance of the proposed method was compared with classical object detection and clustering algorithms.The YOLOv8-G algorithm achieved average precision(AP)values of 98.22%,98.15%,and 97.32%for corn detection at 7,14,and 21 days after emergence,respectively.Additionally,the crop line extraction accuracy across all stages was 96.52%.These results demonstrate the model's ability to maintain high detection accuracy despite challenging conditions in the field.[Conclusions]The proposed crop line extraction method effectively addresses field challenges such as lighting and weed interference,enabling rapid and accurate crop identification.This approach supports the automatic navigation of agricultural machinery,offering significant improvements in the precision and efficiency of field operations.
文摘针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。
