Background Advancements in computer science and knowledge have made the incorporation of control theory,graphics processing,and mathematical models increasingly important for urban design planning.However,challenges r...Background Advancements in computer science and knowledge have made the incorporation of control theory,graphics processing,and mathematical models increasingly important for urban design planning.However,challenges remain in aligning virtual reality(VR)environments with real-world spatial and preparation requirements,particularly in indoor urban spaces.Methods This study investigates the application of VR technology to urban design,focusing on the growth and assessment of the redirection of the space-tree sorter algorithm(STSA).It outlines various assessment indicators,organization of the VR-based system architecture,and construction of 3D urban models and databases.This research also examined methods for the interactive adjustment of indoor space layout plans within a VR environment.Results This research study involved developing and demonstrating the creation and simulation of urban indoor spaces and cityscapes in VR and implementing an experimental setup to test layout modifications and system interactivity.The results indicated enhanced alignment between the virtual and physical spatial configurations.The analysis highlights the strengths and limitations of current VR systems for urban design and identifies key areas for optimization and refinement.Conclusion High congruence between virtual simulations and real-world urban spaces is necessary for effective VR-driven urban planning.This study contributes to a clearer understanding of how 3D modeling,interactive layout design,and reproduction technology can be efficiently employed to support urban increase initiatives.展开更多
This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D n...This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications.展开更多
This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injecti...This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injection-molded parts.At its core,the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles,leading to improvements in both mechanical strength and material efficiency.The design optimization is validated through a series of rigorous experimental tests,including three-point bending and torsion tests performed on key-socket frames,ensuring that the optimized designs meet practical performance requirements.A critical innovation of the framework is the development of the Adjacent Element Temperature-Driven Prestress Algorithm(AETDPA),which refines the prediction of mechanical failure and strength fitting.This algorithm has been shown to deliver mesh-independent accuracy,thereby enhancing the reliability of simulation results across various design iterations.The framework’s adaptability is further demonstrated by its ability to adjust optimization methods based on the unique geometry of each part,thus accelerating the overall design process while ensuring struc-tural integrity.In addition to its immediate applications in injection molding,the study explores the potential extension of this framework to metal additive manufacturing,opening new avenues for its use in advanced manufacturing technologies.Numerical simulations,including finite element analysis,support the experimental findings and confirm that the optimized designs provide a balanced combination of strength,durability,and efficiency.Furthermore,the integration challenges with existing injection molding practices are addressed,underscoring the framework’s scalability and industrial relevance.Overall,this hybrid topology optimization framework offers a computationally efficient and robust solution for advanced manufacturing applications,promising significant improvements in design efficiency,cost-effectiveness,and product performance.Future work will focus on further enhancing algorithm robustness and exploring additional applications across diverse manufacturing processes.展开更多
Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected ...Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.展开更多
The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater...The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.展开更多
This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discre...This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.展开更多
Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulner...Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.展开更多
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz...The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.展开更多
A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D po...A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.展开更多
Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sen...Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.展开更多
To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) po...To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.展开更多
The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the dat...The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.展开更多
The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN appli...The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN application is automatic creating data structure. Although a raster algorithm has been introduced by some authors, the problems in accuracy, memory requirement, speed and integrity are still existent. In this paper, the raster algorithm is completed and a vector algorithm is presented after a 3-D data model and structure of TEN have been introducted. Finally, experiment, conclusion and future work are discussed.展开更多
With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study...With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study mainly examines a method to deconvolve the LaBr_3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration.In the algorithm, the full width at half maximum(FWHM)of full energy peak was calculated by the cubic spline interpolation algorithm and calibrated by a square root of a quadratic function that changes with the energy. Additionally, the detector response matrix was constructed to deconvolve the gamma spectrum. Furthermore, an improved SNIP algorithm was proposed to eliminate the background. In the experiment, several independent peaks of ^(152)Eu,^(137)Cs, and ^(60)Co sources were detected by a LaBr_3:Ce scintillator that were selected to calibrate the energy resolution. The Boosted Gold algorithm was applied to deconvolve the gamma spectrum. The results showed that the peak position difference between the experiment and the deconvolution was within ± 2 channels and the relative error of peak area was approximately within 0.96–6.74%. Finally, a ^(133) Ba spectrum was deconvolved to verify the efficiency and accuracy of the algorithm in unfolding the overlapped peaks.展开更多
With the rapid increase in the number of three-dimensional （3D） models each year, to quickly and easily find the part desired has become a big challenge of enterprises. Meanwhile, many methods and algorithms have be...With the rapid increase in the number of three-dimensional （3D） models each year, to quickly and easily find the part desired has become a big challenge of enterprises. Meanwhile, many methods and algorithms have been proposed for part retrieval. However, most of the existing methods are designed lbr mechanical parts, and can not be well worked for sheet metal part re- trieval. An approach to feature-based retrieval of sheet metal parts is presented. Firstly, the features frequently used in sheet metal part design are chosen as the ＂＇key words＂ in retrieval. Based on those features, a relative position model is built to express the different relationships of the features in 3D space. Secondly, a description method of the model is studied. With the descrip- tion method the relative position of features in sheet metal parts can be expressed by four location description matrices. Thirdly, based on the relative position model and location description matrices, the equivalent definition of relationships of two feature groups is given which is the basis to calculate the similarity of two sheet metal parts. Next, the tbrmula of retrieval algorithm for sheet metal parts is given. Finally, a prototype system is developed to test and verify the effectiveness of the retrieval method suggested. Experiments verify that the new method is able to meet the requirements of searching sheet metal parts and possesses potentials in practical application.展开更多
The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration meth...The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration methods suffer from low convergence efficiency and poor adaptability for large-scale structures in engineering.In this paper,a novel 3D algorithm is established by complementing the three shear moduli of the constitutive equation in principal stress coordinates.In contrast to the existing 3D shear modulus constructed based on experience,in this paper the shear modulus is derived theoretically through a limit process.Then,a theoretically self-consistent complemented algorithm is established and implemented in ABAQUS via UMAT;its good stability and convergence efficiency are verified by using benchmark examples.Numerical analysis shows that the calculation error for bimodulus structures using the traditional linear elastic theory is large,which is not in line with reality.展开更多
A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise(DBSCAN)algorithm.To identify convective and stratiform clo...A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise(DBSCAN)algorithm.To identify convective and stratiform clouds in different developmental phases,two-dimensional(2D)and three-dimensional(3D)models are proposed by applying reflectivity factors at 0.5°and at 0.5°,1.5°,and 2.4°elevation angles,respectively.According to the thresholds of the algorithm,which include echo intensity,the echo top height of 35 dBZ(ET),density threshold,andεneighborhood,cloud clusters can be marked into four types:deep-convective cloud(DCC),shallow-convective cloud(SCC),hybrid convective-stratiform cloud(HCS),and stratiform cloud(SFC)types.Each cloud cluster type is further identified as a core area and boundary area,which can provide more abundant cloud structure information.The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing,Xuzhou,and Qingdao.The results show that cloud clusters can be intuitively identified as core and boundary points,which change in area continuously during the process of convective evolution,by the improved DBSCAN algorithm.Therefore,the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification.Because density thresholds are different and multiple elevations are utilized in the 3D model,the identified echo types and areas are dissimilar between the 2D and 3D models.The 3D model identifies larger convective and stratiform clouds than the 2D model.However,the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds.In addition,the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.展开更多
文摘Background Advancements in computer science and knowledge have made the incorporation of control theory,graphics processing,and mathematical models increasingly important for urban design planning.However,challenges remain in aligning virtual reality(VR)environments with real-world spatial and preparation requirements,particularly in indoor urban spaces.Methods This study investigates the application of VR technology to urban design,focusing on the growth and assessment of the redirection of the space-tree sorter algorithm(STSA).It outlines various assessment indicators,organization of the VR-based system architecture,and construction of 3D urban models and databases.This research also examined methods for the interactive adjustment of indoor space layout plans within a VR environment.Results This research study involved developing and demonstrating the creation and simulation of urban indoor spaces and cityscapes in VR and implementing an experimental setup to test layout modifications and system interactivity.The results indicated enhanced alignment between the virtual and physical spatial configurations.The analysis highlights the strengths and limitations of current VR systems for urban design and identifies key areas for optimization and refinement.Conclusion High congruence between virtual simulations and real-world urban spaces is necessary for effective VR-driven urban planning.This study contributes to a clearer understanding of how 3D modeling,interactive layout design,and reproduction technology can be efficiently employed to support urban increase initiatives.
文摘This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications.
文摘This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injection-molded parts.At its core,the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles,leading to improvements in both mechanical strength and material efficiency.The design optimization is validated through a series of rigorous experimental tests,including three-point bending and torsion tests performed on key-socket frames,ensuring that the optimized designs meet practical performance requirements.A critical innovation of the framework is the development of the Adjacent Element Temperature-Driven Prestress Algorithm(AETDPA),which refines the prediction of mechanical failure and strength fitting.This algorithm has been shown to deliver mesh-independent accuracy,thereby enhancing the reliability of simulation results across various design iterations.The framework’s adaptability is further demonstrated by its ability to adjust optimization methods based on the unique geometry of each part,thus accelerating the overall design process while ensuring struc-tural integrity.In addition to its immediate applications in injection molding,the study explores the potential extension of this framework to metal additive manufacturing,opening new avenues for its use in advanced manufacturing technologies.Numerical simulations,including finite element analysis,support the experimental findings and confirm that the optimized designs provide a balanced combination of strength,durability,and efficiency.Furthermore,the integration challenges with existing injection molding practices are addressed,underscoring the framework’s scalability and industrial relevance.Overall,this hybrid topology optimization framework offers a computationally efficient and robust solution for advanced manufacturing applications,promising significant improvements in design efficiency,cost-effectiveness,and product performance.Future work will focus on further enhancing algorithm robustness and exploring additional applications across diverse manufacturing processes.
基金supported by the National Natural Science Foundation of China(Grant No.42407232)the Sichuan Science and Technology Program(Grant No.2024NSFSC0826).
文摘Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.
基金supported by the National Natural Science Foundation of China(Grant Nos.42172312 and 52211540395)support from the Institut Universitaire de France(IUF).
文摘The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.
基金supported by the BK21 FOUR funded by the Ministry of Education of Korea and National Research Foundation of Korea,a Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure,and Transport(Grant 1615013176)IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)grant funded by the Korea government(Ministry of Science and ICT)(RS-2024-00438411).
文摘This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.
基金supported by the fundings from 2024 Young Talents Program for Science and Technology Thinking Tanks(No.XMSB20240711041)2024 Student Research Program on Dynamic Simulation and Force-on-Force Exercise of Nuclear Security in 3D Interactive Environment Using Reinforcement Learning,Natural Science Foundation of Top Talent of SZTU(No.GDRC202407)+2 种基金Shenzhen Science and Technology Program(No.KCXFZ20240903092603005)Shenzhen Science and Technology Program(No.JCYJ20241202124703004)Shenzhen Science and Technology Program(No.KJZD20230923114117032)。
文摘Vulnerability assessment is a systematic process to identify security gaps in the design and evaluation of physical protection systems.Adversarial path planning is a widely used method for identifying potential vulnerabilities and threats to the security and resilience of critical infrastructures.However,achieving efficient path optimization in complex large-scale three-dimensional(3D)scenes remains a significant challenge for vulnerability assessment.This paper introduces a novel A^(*)-algorithmic framework for 3D security modeling and vulnerability assessment.Within this framework,the 3D facility models were first developed in 3ds Max and then incorporated into Unity for A^(*)heuristic pathfinding.The A^(*)-heuristic pathfinding algorithm was implemented with a geometric probability model to refine the detection and distance fields and achieve a rational approximation of the cost to reach the goal.An admissible heuristic is ensured by incorporating the minimum probability of detection(P_(D)^(min))and diagonal distance to estimate the heuristic function.The 3D A^(*)heuristic search was demonstrated using a hypothetical laboratory facility,where a comparison was also carried out between the A^(*)and Dijkstra algorithms for optimal path identification.Comparative results indicate that the proposed A^(*)-heuristic algorithm effectively identifies the most vulnerable adversarial pathfinding with high efficiency.Finally,the paper discusses hidden phenomena and open issues in efficient 3D pathfinding for security applications.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP23K24899)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145).
文摘The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.
文摘A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.
基金supported by the National Natural Science Foundation of China(52272177,12204010)the Foundation for the Introduction of High-Level Talents of Anhui University(S020118002/097)+1 种基金the University Synergy Innovation Program of Anhui Province(GXXT-2023-066)the Scientific Research Project of Anhui Provincial Higher Education Institution(2023AH040008)。
文摘Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.
基金supported by the Key-Area Research and Development Program of Guangdong Province(No.2020B1111360003)the National Natural Science Foundation of China(Nos.42465008 and 42105164)+2 种基金Yunnan Science and Technology Department Project(No.202501AT070239)Yunnan Science and Technology Department Youth Project(No.202401AU070202)Xianyang Rapid Response Decision Support Project for Ozone(No.YZ2024-ZB019).
文摘To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.
基金This research is sponsored by the National Natural Science Foundation of China （No. 40374024）.
文摘The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.
基金Project supported by the National Natural Science Foundation of China (No.69833010)
文摘The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN application is automatic creating data structure. Although a raster algorithm has been introduced by some authors, the problems in accuracy, memory requirement, speed and integrity are still existent. In this paper, the raster algorithm is completed and a vector algorithm is presented after a 3-D data model and structure of TEN have been introducted. Finally, experiment, conclusion and future work are discussed.
基金supported by the National Natural Science Foundation of China(Nos.41374130 and 41604154)
文摘With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study mainly examines a method to deconvolve the LaBr_3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration.In the algorithm, the full width at half maximum(FWHM)of full energy peak was calculated by the cubic spline interpolation algorithm and calibrated by a square root of a quadratic function that changes with the energy. Additionally, the detector response matrix was constructed to deconvolve the gamma spectrum. Furthermore, an improved SNIP algorithm was proposed to eliminate the background. In the experiment, several independent peaks of ^(152)Eu,^(137)Cs, and ^(60)Co sources were detected by a LaBr_3:Ce scintillator that were selected to calibrate the energy resolution. The Boosted Gold algorithm was applied to deconvolve the gamma spectrum. The results showed that the peak position difference between the experiment and the deconvolution was within ± 2 channels and the relative error of peak area was approximately within 0.96–6.74%. Finally, a ^(133) Ba spectrum was deconvolved to verify the efficiency and accuracy of the algorithm in unfolding the overlapped peaks.
基金National High-tech Research and Development Program of China (2009AA043302)
文摘With the rapid increase in the number of three-dimensional （3D） models each year, to quickly and easily find the part desired has become a big challenge of enterprises. Meanwhile, many methods and algorithms have been proposed for part retrieval. However, most of the existing methods are designed lbr mechanical parts, and can not be well worked for sheet metal part re- trieval. An approach to feature-based retrieval of sheet metal parts is presented. Firstly, the features frequently used in sheet metal part design are chosen as the ＂＇key words＂ in retrieval. Based on those features, a relative position model is built to express the different relationships of the features in 3D space. Secondly, a description method of the model is studied. With the descrip- tion method the relative position of features in sheet metal parts can be expressed by four location description matrices. Thirdly, based on the relative position model and location description matrices, the equivalent definition of relationships of two feature groups is given which is the basis to calculate the similarity of two sheet metal parts. Next, the tbrmula of retrieval algorithm for sheet metal parts is given. Finally, a prototype system is developed to test and verify the effectiveness of the retrieval method suggested. Experiments verify that the new method is able to meet the requirements of searching sheet metal parts and possesses potentials in practical application.
基金the National Natural Science Foundation of China(Grant 51908071)Scientific Research Project of Education Department of Hunan Province(Grant 18C0194)Open Fund of Key Laboratory of Road Structure and Material of Ministry of Transport,Changsha University of Science&Technology(Grant kfi 170303).
文摘The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration methods suffer from low convergence efficiency and poor adaptability for large-scale structures in engineering.In this paper,a novel 3D algorithm is established by complementing the three shear moduli of the constitutive equation in principal stress coordinates.In contrast to the existing 3D shear modulus constructed based on experience,in this paper the shear modulus is derived theoretically through a limit process.Then,a theoretically self-consistent complemented algorithm is established and implemented in ABAQUS via UMAT;its good stability and convergence efficiency are verified by using benchmark examples.Numerical analysis shows that the calculation error for bimodulus structures using the traditional linear elastic theory is large,which is not in line with reality.
基金funded by the Key-Area Research and Development Program of Guangdong Province(Grant No.2020B1111200001)the Key project of monitoring,early warning and prevention of major natural disasters of China(Grant No.2019YFC1510304)+1 种基金the S&T Program of Hebei(Grant No.19275408D)the Scientific Research Projects of Weather Modification in Northwest China(Grant No.RYSY201905).
文摘A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise(DBSCAN)algorithm.To identify convective and stratiform clouds in different developmental phases,two-dimensional(2D)and three-dimensional(3D)models are proposed by applying reflectivity factors at 0.5°and at 0.5°,1.5°,and 2.4°elevation angles,respectively.According to the thresholds of the algorithm,which include echo intensity,the echo top height of 35 dBZ(ET),density threshold,andεneighborhood,cloud clusters can be marked into four types:deep-convective cloud(DCC),shallow-convective cloud(SCC),hybrid convective-stratiform cloud(HCS),and stratiform cloud(SFC)types.Each cloud cluster type is further identified as a core area and boundary area,which can provide more abundant cloud structure information.The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing,Xuzhou,and Qingdao.The results show that cloud clusters can be intuitively identified as core and boundary points,which change in area continuously during the process of convective evolution,by the improved DBSCAN algorithm.Therefore,the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification.Because density thresholds are different and multiple elevations are utilized in the 3D model,the identified echo types and areas are dissimilar between the 2D and 3D models.The 3D model identifies larger convective and stratiform clouds than the 2D model.However,the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds.In addition,the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.
