This article refers to the “Mathematics of Harmony” by Alexey Stakhov in 2009, a new interdisciplinary direction of modern science. The main goal of the article is to describe two modern scientific discoveries–New ...This article refers to the “Mathematics of Harmony” by Alexey Stakhov in 2009, a new interdisciplinary direction of modern science. The main goal of the article is to describe two modern scientific discoveries–New Geometric Theory of Phyllotaxis (Bodnar’s Geometry) and Hilbert’s Fourth Problem based on the Hyperbolic Fibonacci and Lucas Functions and “Golden” Fibonacci λ-Goniometry (λ > 0 is a given positive real number). Although these discoveries refer to different areas of science (mathematics and theoretical botany), however they are based on one and the same scientific ideas-the “golden mean,” which had been introduced by Euclid in his Elements, and its generalization—the “metallic means,” which have been studied recently by Argentinian mathematician Vera Spinadel. The article is a confirmation of interdisciplinary character of the “Mathematics of Harmony”, which originates from Euclid’s Elements.展开更多
Physics success is largely determined by using mathematics.Physics often themselves create the necessary mathematical apparatus.This article shows how you can construct a fractal calculus-mathematics of fractal geomet...Physics success is largely determined by using mathematics.Physics often themselves create the necessary mathematical apparatus.This article shows how you can construct a fractal calculus-mathematics of fractal geometry.In modem scientific literature often write from a firm that"there is no strict definition of fractals",to the more moderate that"objects in a certain sense,fractal and similar."We show that fractal geometry is a strict mathematical theory,defined by their axioms.This methodology allows the geometry of axiomatised naturally define fractal integrals and differentials.Consistent application on your input below the axiom gives the opportunity to develop effective methods of measurement of fractal dimension,geometri-cal interpretation of fractal derivative gain and open dual symmetry.展开更多
The space of internal geometry of a model of a real crystal is supposed to be finite, closed, and with a constant Gaussian curvature equal to unity, permitting the realization of lattice systems in accordance with Fed...The space of internal geometry of a model of a real crystal is supposed to be finite, closed, and with a constant Gaussian curvature equal to unity, permitting the realization of lattice systems in accordance with Fedorov groups of transformations. For visualizing computations, the interpretation of geometrical objects on a Clifford surface (SK) in Riemannian geometry with the help of a 2D torus in a Euclidean space is used. The F-algorithm ensures a computation of 2D sections of models of point systems arranged perpendicularly to the symmetry axes l3, l4, and l6. The results of modeling can be used for calculations of geometrical sizes of crystal structures, nanostructures, parameters of the cluster organization of oxides, as well as for the development of practical applications connected with improving the structural characteristics of crystalline materials.展开更多
Point-based rendering is a common method widely used in point cloud rendering.It realizes rendering by turning the points into the base geometry.The critical step in point-based rendering is to set an appropriate rend...Point-based rendering is a common method widely used in point cloud rendering.It realizes rendering by turning the points into the base geometry.The critical step in point-based rendering is to set an appropriate rendering radius for the base geometry,usually calculated using the average Euclidean distance of the N nearest neighboring points to the rendered point.This method effectively reduces the appearance of empty spaces between points in rendering.However,it also causes the problem that the rendering radius of outlier points far away from the central region of the point cloud sequence could be large,which impacts the perceptual quality.To solve the above problem,we propose an algorithm for point-based point cloud rendering through outlier detection to optimize the perceptual quality of rendering.The algorithm determines whether the detected points are outliers using a combination of local and global geometric features.For the detected outliers,the minimum radius is used for rendering.We examine the performance of the proposed method in terms of both objective quality and perceptual quality.The experimental results show that the peak signal-to-noise ratio(PSNR)of the point cloud sequences is improved under all geometric quantization,and the PSNR improvement ratio is more evident in dense point clouds.Specifically,the PSNR of the point cloud sequences is improved by 3.6%on average compared with the original algorithm.The proposed method significantly improves the perceptual quality of the rendered point clouds and the results of ablation studies prove the feasibility and effectiveness of the proposed method.展开更多
Haptic rendering is referred to as an approach for complementing graphical model of the virtual object with mechanics- based properties. As a result, when the user interacts with the virtual object through a haptic de...Haptic rendering is referred to as an approach for complementing graphical model of the virtual object with mechanics- based properties. As a result, when the user interacts with the virtual object through a haptic device, the object can graphically deflect or deform following laws of mechanics. In addition, the user is able to feel the resulting interaction force when interacting with the virtual object. This paper presents a study of defining the levels-of-detail (LOD) in point-based computational mechanics for haptic rendering of objects. The approach uses the description of object as a set of sampled points. In comparison with the finite element method (FEM), point-based approach does not rely on any predefined mesh representation and depends on the point representation of the volume of the object. Different from solving the governing equations of motion representing the entire object based on pre-defined mesh representation which is used in FEM, in point-based modeling approach, the number of points involved in the computation of displacement/deformation can be adaptively defined during the solution cycle. This frame work can offer the implementation of the notion for levels-of-detail techniques for which can be used to tune the haptic rendering environment for in- creased realism and computational efficiency. This paper presents some initial experimental studies in implementing LOD in such environment.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reac...The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.展开更多
The fracture surfaces of coal-rock masses formed under mining-induced stress generally exhibit complex geometries, and the fracture geometry is one of the primary factors affecting the seepage characteristics of coal-...The fracture surfaces of coal-rock masses formed under mining-induced stress generally exhibit complex geometries, and the fracture geometry is one of the primary factors affecting the seepage characteristics of coal-rock penetrating fracture. This paper investigates the seepage characteristics of 5 groups of coal penetrating fracture(CPF) with different joint roughness coefficients(JRCs). Based on 3D morphology scanner tests and hydraulic coupling tests, a characterization method of effective geometric parameters in fracture surfaces under various confining pressures was improved, and a relationship between effective geometric parameters and the confining pressure is established. The results indicate that the nonlinear flow behavior in a CPF primarily includes three types: non-Newtonian fluid seepage under high confining pressure and low JRC, non-Darcy seepage under low confining pressure and high JRC, and the whole process of seepage characteristics between these two conditions. Among them, nonNewtonian fluid seepage is caused by significant fracture expansion, while non-Darcy seepage can be attributed to turbulence effects. During the seepage process, the geometric parameters with different JRC fracture samples all exhibit exponential changes with the increase of confining pressure. In addition,under high confining pressure, the effective contact ratio, effective fracture aperture, and void deviation ratio with high JRC fracture samples under high confining pressure increase by 93.5%, 67.4%, and 24.9%,respectively, compared with those of low JRC fracture samples. According to the variation of geometric parameters in a CPF with external stress, a seepage model considering geometric parameters in a CPF is proposed. By introducing the root mean square error(RMSE) and coefficient of determination(R2) to evaluate the error and goodness of fit between model curves and experimental data, it is found that the theoretical curves of model in this paper have the best matching with the experimental data. The average values of RMSE and R2for model in this paper are 0.002 and 0.70, respectively, which are better than models in the existing literature.展开更多
Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine in...Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine interfaces.Crystalline silicon is one of the most mature and reliable materials for high-performance electronics;however,its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics.Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials,such as transforming them into thin nanomembranes or nanowires.This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics,from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates,and ultimately to shaping silicon nanowires using vapor-liquid-solid or in-plane solid-liquid-solid techniques.We explore the latest developments in Si-based soft electronic devices,with applications in sensors,nanoprobes,robotics,and brain-machine interfaces.Finally,the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.展开更多
This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of G...This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of GeoGebra software,it expounds upon the imperative and feasibility of its application within the realm of analytic geometry teaching.Furthermore,it presents a detailed account of the teaching practice process grounded in this software,encompassing teaching design and the demonstration of teaching cases,and conducts an in-depth investigation and analysis of the teaching outcomes.The research findings indicate that the GeoGebra software can effectively elevate the level of visualization in analytic geometry teaching,thereby augmenting students’learning enthusiasm and comprehension capabilities.It thus offers novel perspectives and methodologies for the pedagogical reform of analytic geometry.展开更多
Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how str...Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how stress affects lifespan,this review offers the first comprehensive,multiscale comparison of strategies that optimize geometry to improve fatigue performance.This includes everything from microscopic features like the shape of graphite nodules to large-scale design elements such as fillets,notches,and overall structural layouts.We analyze and combine various methods,including topology and shape optimization,the ability of additive manufacturing to finetune internal geometries,and reliability-based design approaches.A key new contribution is our proposal of a standard way to evaluate geometry-focused fatigue design,allowing for consistent comparison and encouraging validation across different fields.Furthermore,we highlight important areas for future research,such as incorporating manufacturing flaws,using multiscale models,and integrating machine learning techniques.This work is the first to provide a broad geometric viewpoint in fatigue engineering,laying the groundwork for future design methods that are driven by data and centered on reliability.展开更多
We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling consta...We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling constant.The model was constructed using the Karmarkar condition to obtain the radial metric component,while the time metric component followed the approach proposed by Adler.We assumed a specific charge distribution inside the star to build the model.To ensure a smooth spacetime transition,we established boundary conditions,considering Bardeen?s solution for the exterior spacetime.Additionally,we examined various physical aspects,such as energy density,pressure components,pressure anisotropy,energy conditions,the equation of state,surface redshift,compactness factor,adiabatic index,sound speed,and the Tolman-Oppenheimer-Volkoff equilibrium condition.All these conditions were met,demonstrating that the solutions we obtained are physically viable.展开更多
In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional tran...In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional transverse integrated equations using the transverse integration procedure over 3D hexagonal geometry and denoted the solutions as a nodal Green's functions under the Neumann boundary condition.By applying a quadratic polynomial expansion of the transverse-averaged quantities,we derived the net neutron current coupling equation,equation for the expansion coefficients of the transverse-averaged neutron flux,and formulas for the coefficient matrix of these equations.We formulated the closed system of equations in correspondence with the boundary conditions.The proposed model was tested by comparing it with the benchmark for the VVER-440 reactor,and the numerical results were in good agreement with the reference solutions.展开更多
The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a ...The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.展开更多
Fluid imbibition from hydraulic fractures into shale formations is mainly affected by a combination of capillary forces and viscous resistance,both of which are closely related to the pore geometry.This study establis...Fluid imbibition from hydraulic fractures into shale formations is mainly affected by a combination of capillary forces and viscous resistance,both of which are closely related to the pore geometry.This study established five self-imbibition models with idealized pore structures and conducted a comparative analysis of these models.These models include circular,square,and equilateral triangular capillaries;a triangular star-shaped cross-section formed by three tangent spherical particles;and a traditional porous medium representation method.All these models are derived based on Newton’s second law,where capillary pressure is described by the Young-Laplace equation and viscous resistance is characterized by the Hagen-Poiret equation and Darcy’s law.All derived models predict that the fluid imbibition distance is proportional to the square root of time,in accordance with the classical Lucas-Washburn law.However,different pore structures exhibit significantly different characteristic imbibition rates.Compared to the single pore model,the conventional Darcy’s law-based model for porous media predicts significantly lower imbibition rates,which is consistent with the relatively slower uptake rates in actual shale nanoscale pore networks.These findings emphasize the important role played by pore geometry in fluid imbibition dynamics and further point to the need for optimizing pore structure to extend fluid imbibition duration in shale reservoirs in practical operations.展开更多
Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on convent...Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on conventional ray-based geometry design methods,we incorporate imaging results as a constraint to optimize the geometry design and evaluate its effectiveness.Firstly,the geological model of the target layer is established based on the geological data of the study area and surface seismic data combined with exploration tasks.Then,the ray-tracing method is employed to simulate and assess the proposed geometry design,verifying whether its parameters meet the exploration requirements.Finally,the imaging effect of the designed geometry on the target layer is tested by the cross-well seismic reverse time migration method.This methodology was applied to design the cross-well seismic acquisition geometry for offshore deviated wells in the X Oilfield.The simulation results demonstrate that the imaging-driven geometry design approach effectively guides field operations,enhances the imaging quality of the target layer,and reduces acquisition costs.展开更多
The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive inte...The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.展开更多
Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular ...Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular cross-sections,often overlooking the impact of pore geometry on fluid flow behavior within reservoirs.In this work,the intermingled fractal theory of porous media is introduced to characterize the intricate local features within the internal space of tight rocks.Initially,iterative rules for diverse fractal units are skillfully designed to capture the actual characteristics of pore cross-sectional shapes.Subsequently,analytical relationships are derived between the iterative parameters and the area,wetted perimeter,and hydraulic diameter of pores generated by these units,followed by the establishment of a relative permeability model that considers pore geometry.The model's validity is confirmed through comparisons with experimental data and published relative permeability models,with correlation coefficients exceeding 0.996.Finally,various factors affecting two-phase flow characteristics are analyzed.The results reveal that pore geometry has a significant impact on flow behavior in porous media.Assuming that the flow channels are cylindrical typically leads to an overestimation of permeability,with the maximum relative error reaching 46.91%.Additionally,the tortuosity fractal dimension is a determinant factor influencing the relative permeability of both wetting and nonwetting fluids,and the phase permeability is sensitive to variations in solid particle size and porosity.The proposed intermingled fractal model enhances the accuracy of evaluating fluid flow characteristics in microscale pore channels and offers a novel framework for simulating porous media with complex geometries.展开更多
The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is l...The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.展开更多
Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the pro...Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the production of thoracic implants with complex geometries,offering more versatile performance.In this study,we investigated a design based on a spring-like geometry manufactured by laser powder bed fusion(LPBF),as proposed in earlier research.The biomechanical behavior of this design was analyzed using various isolated semi-ring-rib models at different levels of the rib cage.This approach enabled a comprehensive examination,leading to the proposal of several implant configurations that were incorporated into a 3D rib cage model with chest wall defects,to simulate different chest wall reconstruction scenarios.The results revealed that the implant design was too rigid for the second rib level,which therefore was excluded from the proposed implant configurations.In chest wall reconstruction simulations,the maximum stresses observed in all prostheses did not exceed 38%of the implant material's yield stress in the most unfavorable case.Additionally,all the implants showed flexibility compatible with the physiological movements of the human thorax.展开更多
文摘This article refers to the “Mathematics of Harmony” by Alexey Stakhov in 2009, a new interdisciplinary direction of modern science. The main goal of the article is to describe two modern scientific discoveries–New Geometric Theory of Phyllotaxis (Bodnar’s Geometry) and Hilbert’s Fourth Problem based on the Hyperbolic Fibonacci and Lucas Functions and “Golden” Fibonacci λ-Goniometry (λ > 0 is a given positive real number). Although these discoveries refer to different areas of science (mathematics and theoretical botany), however they are based on one and the same scientific ideas-the “golden mean,” which had been introduced by Euclid in his Elements, and its generalization—the “metallic means,” which have been studied recently by Argentinian mathematician Vera Spinadel. The article is a confirmation of interdisciplinary character of the “Mathematics of Harmony”, which originates from Euclid’s Elements.
文摘Physics success is largely determined by using mathematics.Physics often themselves create the necessary mathematical apparatus.This article shows how you can construct a fractal calculus-mathematics of fractal geometry.In modem scientific literature often write from a firm that"there is no strict definition of fractals",to the more moderate that"objects in a certain sense,fractal and similar."We show that fractal geometry is a strict mathematical theory,defined by their axioms.This methodology allows the geometry of axiomatised naturally define fractal integrals and differentials.Consistent application on your input below the axiom gives the opportunity to develop effective methods of measurement of fractal dimension,geometri-cal interpretation of fractal derivative gain and open dual symmetry.
文摘The space of internal geometry of a model of a real crystal is supposed to be finite, closed, and with a constant Gaussian curvature equal to unity, permitting the realization of lattice systems in accordance with Fedorov groups of transformations. For visualizing computations, the interpretation of geometrical objects on a Clifford surface (SK) in Riemannian geometry with the help of a 2D torus in a Euclidean space is used. The F-algorithm ensures a computation of 2D sections of models of point systems arranged perpendicularly to the symmetry axes l3, l4, and l6. The results of modeling can be used for calculations of geometrical sizes of crystal structures, nanostructures, parameters of the cluster organization of oxides, as well as for the development of practical applications connected with improving the structural characteristics of crystalline materials.
文摘Point-based rendering is a common method widely used in point cloud rendering.It realizes rendering by turning the points into the base geometry.The critical step in point-based rendering is to set an appropriate rendering radius for the base geometry,usually calculated using the average Euclidean distance of the N nearest neighboring points to the rendered point.This method effectively reduces the appearance of empty spaces between points in rendering.However,it also causes the problem that the rendering radius of outlier points far away from the central region of the point cloud sequence could be large,which impacts the perceptual quality.To solve the above problem,we propose an algorithm for point-based point cloud rendering through outlier detection to optimize the perceptual quality of rendering.The algorithm determines whether the detected points are outliers using a combination of local and global geometric features.For the detected outliers,the minimum radius is used for rendering.We examine the performance of the proposed method in terms of both objective quality and perceptual quality.The experimental results show that the peak signal-to-noise ratio(PSNR)of the point cloud sequences is improved under all geometric quantization,and the PSNR improvement ratio is more evident in dense point clouds.Specifically,the PSNR of the point cloud sequences is improved by 3.6%on average compared with the original algorithm.The proposed method significantly improves the perceptual quality of the rendered point clouds and the results of ablation studies prove the feasibility and effectiveness of the proposed method.
文摘Haptic rendering is referred to as an approach for complementing graphical model of the virtual object with mechanics- based properties. As a result, when the user interacts with the virtual object through a haptic device, the object can graphically deflect or deform following laws of mechanics. In addition, the user is able to feel the resulting interaction force when interacting with the virtual object. This paper presents a study of defining the levels-of-detail (LOD) in point-based computational mechanics for haptic rendering of objects. The approach uses the description of object as a set of sampled points. In comparison with the finite element method (FEM), point-based approach does not rely on any predefined mesh representation and depends on the point representation of the volume of the object. Different from solving the governing equations of motion representing the entire object based on pre-defined mesh representation which is used in FEM, in point-based modeling approach, the number of points involved in the computation of displacement/deformation can be adaptively defined during the solution cycle. This frame work can offer the implementation of the notion for levels-of-detail techniques for which can be used to tune the haptic rendering environment for in- creased realism and computational efficiency. This paper presents some initial experimental studies in implementing LOD in such environment.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
基金supported by the National Natural Science Foundation of China(Nos.12175321,11975021,and 11675275)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)。
文摘The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.
基金supported by the National Natural Science Foundation of China (Nos. 52474161, and 52404093)Fundamental Research Program of Shanxi Province (Nos. 202303021222168 and 202203021221143)+1 种基金Taiyuan University of Science and Technology Scientific Research Initial Funding (No. 20242103)the Postdoctoral Research Foundation of China(No. 2023M733778)。
文摘The fracture surfaces of coal-rock masses formed under mining-induced stress generally exhibit complex geometries, and the fracture geometry is one of the primary factors affecting the seepage characteristics of coal-rock penetrating fracture. This paper investigates the seepage characteristics of 5 groups of coal penetrating fracture(CPF) with different joint roughness coefficients(JRCs). Based on 3D morphology scanner tests and hydraulic coupling tests, a characterization method of effective geometric parameters in fracture surfaces under various confining pressures was improved, and a relationship between effective geometric parameters and the confining pressure is established. The results indicate that the nonlinear flow behavior in a CPF primarily includes three types: non-Newtonian fluid seepage under high confining pressure and low JRC, non-Darcy seepage under low confining pressure and high JRC, and the whole process of seepage characteristics between these two conditions. Among them, nonNewtonian fluid seepage is caused by significant fracture expansion, while non-Darcy seepage can be attributed to turbulence effects. During the seepage process, the geometric parameters with different JRC fracture samples all exhibit exponential changes with the increase of confining pressure. In addition,under high confining pressure, the effective contact ratio, effective fracture aperture, and void deviation ratio with high JRC fracture samples under high confining pressure increase by 93.5%, 67.4%, and 24.9%,respectively, compared with those of low JRC fracture samples. According to the variation of geometric parameters in a CPF with external stress, a seepage model considering geometric parameters in a CPF is proposed. By introducing the root mean square error(RMSE) and coefficient of determination(R2) to evaluate the error and goodness of fit between model curves and experimental data, it is found that the theoretical curves of model in this paper have the best matching with the experimental data. The average values of RMSE and R2for model in this paper are 0.002 and 0.70, respectively, which are better than models in the existing literature.
基金the National Natural Science Foundation of China under granted No.62104100National Key Research Program of China under No.92164201+1 种基金National Natural Science Foundation of China for Distinguished Young Scholars under No.62325403National Natural Science Foundation of China under No.61934004.
文摘Soft electronics,which are designed to function under mechanical deformation(such as bending,stretching,and folding),have become essential in applications like wearable electronics,artificial skin,and brain-machine interfaces.Crystalline silicon is one of the most mature and reliable materials for high-performance electronics;however,its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics.Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials,such as transforming them into thin nanomembranes or nanowires.This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics,from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates,and ultimately to shaping silicon nanowires using vapor-liquid-solid or in-plane solid-liquid-solid techniques.We explore the latest developments in Si-based soft electronic devices,with applications in sensors,nanoprobes,robotics,and brain-machine interfaces.Finally,the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.
基金The 2024 Undergraduate Education Teaching Research and Reform Project of Colleges and Universities in the Autonomous Region“Construction of School-based Digital Resources for Ideological and Political Education in the Course of Analytic Geometry”(XJGXJGPTB-2024104)。
文摘This paper delves into the visual teaching of analytic geometry facilitated by GeoGebra software.Through a meticulous analysis of the current landscape of analytic geometry instruction and the distinct advantages of GeoGebra software,it expounds upon the imperative and feasibility of its application within the realm of analytic geometry teaching.Furthermore,it presents a detailed account of the teaching practice process grounded in this software,encompassing teaching design and the demonstration of teaching cases,and conducts an in-depth investigation and analysis of the teaching outcomes.The research findings indicate that the GeoGebra software can effectively elevate the level of visualization in analytic geometry teaching,thereby augmenting students’learning enthusiasm and comprehension capabilities.It thus offers novel perspectives and methodologies for the pedagogical reform of analytic geometry.
文摘Fatigue failure continues to be a significant challenge in designing structural and mechanical components subjected to repeated and complex loading.While earlier studies mainly examined material properties and how stress affects lifespan,this review offers the first comprehensive,multiscale comparison of strategies that optimize geometry to improve fatigue performance.This includes everything from microscopic features like the shape of graphite nodules to large-scale design elements such as fillets,notches,and overall structural layouts.We analyze and combine various methods,including topology and shape optimization,the ability of additive manufacturing to finetune internal geometries,and reliability-based design approaches.A key new contribution is our proposal of a standard way to evaluate geometry-focused fatigue design,allowing for consistent comparison and encouraging validation across different fields.Furthermore,we highlight important areas for future research,such as incorporating manufacturing flaws,using multiscale models,and integrating machine learning techniques.This work is the first to provide a broad geometric viewpoint in fatigue engineering,laying the groundwork for future design methods that are driven by data and centered on reliability.
基金Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under Grant No.RGP2/30/45。
文摘We have developed a class of charged,anisotropic,and spherically symmetric solutions,described by the function f(R,A)=R+a A,where R represents the Ricci scalar,A is the anticurvature scalar,andαis the coupling constant.The model was constructed using the Karmarkar condition to obtain the radial metric component,while the time metric component followed the approach proposed by Adler.We assumed a specific charge distribution inside the star to build the model.To ensure a smooth spacetime transition,we established boundary conditions,considering Bardeen?s solution for the exterior spacetime.Additionally,we examined various physical aspects,such as energy density,pressure components,pressure anisotropy,energy conditions,the equation of state,surface redshift,compactness factor,adiabatic index,sound speed,and the Tolman-Oppenheimer-Volkoff equilibrium condition.All these conditions were met,demonstrating that the solutions we obtained are physically viable.
文摘In this paper,we propose a numerical calculation model of the multigroup neutron diffusion equation in 3D hexagonal geometry using the nodal Green's function method and verified it.We obtained one-dimensional transverse integrated equations using the transverse integration procedure over 3D hexagonal geometry and denoted the solutions as a nodal Green's functions under the Neumann boundary condition.By applying a quadratic polynomial expansion of the transverse-averaged quantities,we derived the net neutron current coupling equation,equation for the expansion coefficients of the transverse-averaged neutron flux,and formulas for the coefficient matrix of these equations.We formulated the closed system of equations in correspondence with the boundary conditions.The proposed model was tested by comparing it with the benchmark for the VVER-440 reactor,and the numerical results were in good agreement with the reference solutions.
基金supported in part by the National Natural Science Foundation of China(Nos.61873196,62373030,61772187)the Innovation Program for Quantum Science and Technology(No.2021ZD0303400)。
文摘The traditional orbit determination method based on pulsar profile distortion can determine the six elements of the orbit.However,the estimation accuracies of these methods are limited and the computational load of a six-dimensional search is huge.To solve this problem,the differential-geometry-based Multi-dimensional Joint Position-Velocity Estimation(MJPVE)using Crab pulsar profile distortion is proposed in this paper.Firstly,through theoretical analysis,it is found that the pulsar profile distortion caused by the initial state error in some joint positionvelocity directions is very small.In other words,the accuracies of estimation in these directions are very low.Namely,the search dimension can be reduced,which in turn greatly reduces the computational load.Then,we construct the chi-squared function of the pulsar profile with respect to the estimation error in joint position-velocity direction and use differential geometry to find the joint position-velocity directions corresponding to different degrees of distortion.Finally,we utilize the grid search based on directory folding in these joint position-velocity directions corresponding to large degrees of distortion to obtain the joint position-velocity estimation.The experimental results show that compared with the grouping bi-chi-squared inversion method,MJPVE has high precision and extensive navigation information.
文摘Fluid imbibition from hydraulic fractures into shale formations is mainly affected by a combination of capillary forces and viscous resistance,both of which are closely related to the pore geometry.This study established five self-imbibition models with idealized pore structures and conducted a comparative analysis of these models.These models include circular,square,and equilateral triangular capillaries;a triangular star-shaped cross-section formed by three tangent spherical particles;and a traditional porous medium representation method.All these models are derived based on Newton’s second law,where capillary pressure is described by the Young-Laplace equation and viscous resistance is characterized by the Hagen-Poiret equation and Darcy’s law.All derived models predict that the fluid imbibition distance is proportional to the square root of time,in accordance with the classical Lucas-Washburn law.However,different pore structures exhibit significantly different characteristic imbibition rates.Compared to the single pore model,the conventional Darcy’s law-based model for porous media predicts significantly lower imbibition rates,which is consistent with the relatively slower uptake rates in actual shale nanoscale pore networks.These findings emphasize the important role played by pore geometry in fluid imbibition dynamics and further point to the need for optimizing pore structure to extend fluid imbibition duration in shale reservoirs in practical operations.
基金funded by the Young Scientists Fund of the National Natural Science Foundation of China(42304135)the scientific research project of Gansu Coal Geology Bureau(2023-07).
文摘Reasonable field acquisition geometry can not only guide seismic exploration to obtain sufficient geological information of target body,but also reduce acquisition cost to the maximum.In this study,building on conventional ray-based geometry design methods,we incorporate imaging results as a constraint to optimize the geometry design and evaluate its effectiveness.Firstly,the geological model of the target layer is established based on the geological data of the study area and surface seismic data combined with exploration tasks.Then,the ray-tracing method is employed to simulate and assess the proposed geometry design,verifying whether its parameters meet the exploration requirements.Finally,the imaging effect of the designed geometry on the target layer is tested by the cross-well seismic reverse time migration method.This methodology was applied to design the cross-well seismic acquisition geometry for offshore deviated wells in the X Oilfield.The simulation results demonstrate that the imaging-driven geometry design approach effectively guides field operations,enhances the imaging quality of the target layer,and reduces acquisition costs.
基金funded by the National Key R&D Program of China(2022YFF0800601)National Natural Science Foundation of China(42174069,U1939204).
文摘The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.
基金financially supported by the Hebei Provincial Natural Science Foundation of China(No.D2023402012)the Major Science and Technology Project of China National Petroleum Corporation(No.2024DJ87)。
文摘Accurately predicting relative permeability is an important issue in the research of multiphase flow in tight reservoirs.Existing predictive models typically rely on the capillary tube bundle model featuring circular cross-sections,often overlooking the impact of pore geometry on fluid flow behavior within reservoirs.In this work,the intermingled fractal theory of porous media is introduced to characterize the intricate local features within the internal space of tight rocks.Initially,iterative rules for diverse fractal units are skillfully designed to capture the actual characteristics of pore cross-sectional shapes.Subsequently,analytical relationships are derived between the iterative parameters and the area,wetted perimeter,and hydraulic diameter of pores generated by these units,followed by the establishment of a relative permeability model that considers pore geometry.The model's validity is confirmed through comparisons with experimental data and published relative permeability models,with correlation coefficients exceeding 0.996.Finally,various factors affecting two-phase flow characteristics are analyzed.The results reveal that pore geometry has a significant impact on flow behavior in porous media.Assuming that the flow channels are cylindrical typically leads to an overestimation of permeability,with the maximum relative error reaching 46.91%.Additionally,the tortuosity fractal dimension is a determinant factor influencing the relative permeability of both wetting and nonwetting fluids,and the phase permeability is sensitive to variations in solid particle size and porosity.The proposed intermingled fractal model enhances the accuracy of evaluating fluid flow characteristics in microscale pore channels and offers a novel framework for simulating porous media with complex geometries.
基金co-supported by the Aeronautical Science Foundation of China(Nos.2018ZA52002 and 2019ZA052011)。
文摘The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.
文摘Thoracic reconstructions are essential surgical techniques used to replace severely damaged tissues and restore protection to internal organs.In recent years,advancements in additive manufacturing have enabled the production of thoracic implants with complex geometries,offering more versatile performance.In this study,we investigated a design based on a spring-like geometry manufactured by laser powder bed fusion(LPBF),as proposed in earlier research.The biomechanical behavior of this design was analyzed using various isolated semi-ring-rib models at different levels of the rib cage.This approach enabled a comprehensive examination,leading to the proposal of several implant configurations that were incorporated into a 3D rib cage model with chest wall defects,to simulate different chest wall reconstruction scenarios.The results revealed that the implant design was too rigid for the second rib level,which therefore was excluded from the proposed implant configurations.In chest wall reconstruction simulations,the maximum stresses observed in all prostheses did not exceed 38%of the implant material's yield stress in the most unfavorable case.Additionally,all the implants showed flexibility compatible with the physiological movements of the human thorax.
