The negative Poisson’s ratio(NPR)bolt is an innovative support element distinguished by its high strength,elongation,and a slightly negative Poisson’s ratio.Unlike conventional prestressed(PR)bolts with a positive P...The negative Poisson’s ratio(NPR)bolt is an innovative support element distinguished by its high strength,elongation,and a slightly negative Poisson’s ratio.Unlike conventional prestressed(PR)bolts with a positive Poisson’s ratio,the NPR bolt exhibits a quasi-ideal plastic response without a prominent yield platform,enabling it to sustain high prestress with a substantial safety margin,which is particularly advantageous for jointed rock masses.However,investigations into the shear resistance mechanisms of NPR bolts under varying prestress levels remain limited.This study conducted full-scale double shear tests to assess the shear strength,deformation behavior,energy absorption,and failure mechanisms of NPR bolts under different prestress conditions.To ensure a fair comparison with PR bolts,a prestress utilization coefficient(PUC)was introduced.The results reveal that at a PUC of 0.25,the NPR bolt achieved peak axial force,shear displacement,and peak shear force values that are 2.41,1.88,and 2.13 times greater than those of the PR bolt,respectively.Shear performance was optimized at a prestress level of 100 kN,with energy absorption reaching 47.1 kJ,which is 2.8 times that of the PR bolt.Furthermore,the necking ratio was significantly reduced,indicating more distributed plastic deformation and delayed failure.Field applications verified the superior performance,resulting in a 27.4%reduction in roof settlement and enhanced structural integrity.These findings confirm that NPR bolts possess excellent shear resistance,energy absorption,and deformation adaptability,and optimizing prestress significantly enhances their support performance,providing a strong basis for geotechnical engineering applications.展开更多
With technological advancements,virtual reality(VR),once limited to high-end professional applications,is rapidly expanding into entertainment and broader consumer domains.However,the inherent contradiction between mo...With technological advancements,virtual reality(VR),once limited to high-end professional applications,is rapidly expanding into entertainment and broader consumer domains.However,the inherent contradiction between mobile hardware computing power and the demand for high-resolution,high-refresh-rate rendering has intensified,leading to critical bottlenecks,including frame latency and power overload,which constrain large-scale applications of VR systems.This study systematically analyzes four key technologies for efficient VR rendering:(1)foveated rendering,which dynamically reduces rendering precision in peripheral regions based on the physiological characteristics of the human visual system(HVS),thereby significantly decreasing graphics computation load;(2)stereo rendering,optimized through consistent stereo rendering acceleration algorithms;(3)cloud rendering,utilizing object-based decomposition and illumination-based decomposition for distributed resource scheduling;and(4)low-power rendering,integrating parameter-optimized rendering,super-resolution technology,and frame-generation technology to enhance mobile energy efficiency.Through a systematic review of the core principles and optimization approaches of these technologies,this study establishes research benchmarks for developing efficient VR systems that achieve high fidelity and low latency while providing further theoretical support for the engineering implementation and industrial advancement of VR rendering technologies.展开更多
Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperature...Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperatures.The stress−strain curve,ultimate strength,yield strength,modulus of elasticity,elongation after fracture,and percentage reduction of area of NPR steel bars were measured at 9 different temperatures ranging from 20 to 800℃.The experimental results indicate that high-temperature environments significantly affect the mechanical properties of NPR steel.However,compared to other types of steel,NPR steel exhibits better resistance to deformation.When the test temperature is below 700℃,NPR steel exhibits a ductile fracture characteristic,while at 800℃,it exhibits a brittle fracture characteristic.Finally,based on the experimental findings,a constitutive model suitable for NPR steel at high temperatures is proposed.展开更多
Background Physics-based differentiable rendering(PBDR)aims to propagate gradients from scene parameters to image pixels or vice versa.The physically correct gradients obtained can be used in various applications,incl...Background Physics-based differentiable rendering(PBDR)aims to propagate gradients from scene parameters to image pixels or vice versa.The physically correct gradients obtained can be used in various applications,including inverse rendering and machine learning.Currently,two categories of methods are prevalent in the PBDR community:reparameterization and boundary sampling methods.The state-of-the-art boundary sampling methods rely on a guiding structure to calculate the gradients efficiently.They utilize the rays generated in traditional path-tracing methods and project them onto the object silhouette boundary to initialize the guiding structure.Methods In this study,we propose an augmentation of previous projective-sampling-based boundary-sampling methods in a bidirectional manner.Specifically,we utilize the rays spawned from the sensors and also employ the rays emitted by the emitters to initialize the guiding structure.Results To demonstrate the benefits of our technique,we perform a comparative analysis of differentiable rendering and inverse rendering performance.We utilize a range of synthetic scene examples and evaluate our method against state-of-the-art projective-sampling-based differentiable rendering methods.Conclusions The experiments show that our method achieves lower variance gradients in the forward differentiable rendering process and better geometry reconstruction quality in the inverse-rendering results.展开更多
Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores t...Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores the changes in pixel values during the previous rendering process,which may result in additional iterative operations.展开更多
In geotechnical engineering applications,including mining and tunnel construction,the stability of fractured rock masses is paramount to ensuring structural safety.The spatial distribution and temporal evolution of in...In geotechnical engineering applications,including mining and tunnel construction,the stability of fractured rock masses is paramount to ensuring structural safety.The spatial distribution and temporal evolution of internal fractures fundamentally govern the mechanical behavior and failure mechanisms of rock masses.Nevertheless,the inherent complexity and structural concealment of rock mass systems pose significant challenges for the direct measurement of critical internal mechanical parameters.This study explores the use of deep learning to invert mechanical responses of NPR(Negative Poisson's Ratio)anchored fractured rock masses.Discrete Element Method(DEM)simulations were conducted to generate datasets including stress-strain curves and crack numbers under various initial fracture distributions.Three models—GRU,CNN+GRU,and CNN+GRU+ATT—were developed to predict rock mechanical parameters from NPR cable force data.Results show that the CNN+GRU+ATT model achieves superior accuracy,with R^(2)>0.90 and RMSE<5 on stress prediction tasks.It also accurately estimates initial crack quantity(np),with mean prediction error under 10%for high-fracture scenarios.The proposed model effectively captures stress fluctuations,offering early-warning potential for failure.The approach demonstrates strong generalization and robustness across varying crack configurations,providing a feasible framework for real-time health monitoring and mechanical parameter estimation in fractured rock engineering.展开更多
Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and entertainment.However,achieving a balance b...Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and entertainment.However,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains challenging.Methods This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and VR.Therefore,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image graph.Using this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of views.The rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image graph.The detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in real-time.In addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light intensities.Results Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,respectively.While achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering approaches.Conclusions Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR environments.Nevertheless,the handling of morphing artifacts in the parallax image regions remains a topic for future research.展开更多
With the rapid development of deep resource extraction and underground space construction,the design of anchored support systems for jointed rock masses in complex stress environments faces significant challenges.This...With the rapid development of deep resource extraction and underground space construction,the design of anchored support systems for jointed rock masses in complex stress environments faces significant challenges.This study investigates the influence of prefabricated crack dip angles on the mechanical properties of anchored rock masses in deep soft rock roadways.By constructing similarity models of NPR(Negative Poisson’s Ratio)and PR(Positive Poisson’s Ratio)anchored solids,biaxial compression experiments under varying crack dip angles were conducted.Strain gauges,3D Digital Image Correlation(3D DIC),and acoustic emission monitoring were employed to systematically analyze the strength characteristics,deformation-damage evolution,and energy dissipation mechanisms of the two types of anchor systems.The results show that:(1)The stress-strain curves of anchored solids with prefabricated cracks exhibit a distinct bimodal characteristic.Compared to PR anchors,NPR anchors show 20%and 23%improvements in peak strength and elastic modulus,respectively,with residual strength enhanced by up to 34%.(2)Owing to high pre-tightening force and large deformation capacity,NPR anchors maintain superior integrity under increasing crack dip angles,demonstrating more uniform free-surface displacement and localized shear-tensile composite crack patterns.(3)Acoustic emission analysis reveals that NPR anchors exhibit higher cumulative energy absorption(300%improvement over PR anchors)and lack low-rate energy development phases,indicating enhanced ductility and impact resistance at high crack dip angles.(4)Crack dip angle critically governs failure mechanisms by modulating the connectivity between shear cracks and prefabricated fissures:bimodal effects dominate at low angles,while vertical tensile crack propagation replaces bimodal behavior at high angles.The study proposes prioritizing NPR anchor cables in deep engineering applications and optimizing support parameters based on crack dip angles to mitigate stress concentration and ensure the long-term stability of surrounding rock.展开更多
基金supported by the State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering(Grant No.SDGZ2505)the Postdoctoral Fellowship Program of the China Postdoctoral Science Foundation(Grant No.GZB20250742)the General Program of the China Postdoctoral Science Foundation(Grant No.2025M773213).
文摘The negative Poisson’s ratio(NPR)bolt is an innovative support element distinguished by its high strength,elongation,and a slightly negative Poisson’s ratio.Unlike conventional prestressed(PR)bolts with a positive Poisson’s ratio,the NPR bolt exhibits a quasi-ideal plastic response without a prominent yield platform,enabling it to sustain high prestress with a substantial safety margin,which is particularly advantageous for jointed rock masses.However,investigations into the shear resistance mechanisms of NPR bolts under varying prestress levels remain limited.This study conducted full-scale double shear tests to assess the shear strength,deformation behavior,energy absorption,and failure mechanisms of NPR bolts under different prestress conditions.To ensure a fair comparison with PR bolts,a prestress utilization coefficient(PUC)was introduced.The results reveal that at a PUC of 0.25,the NPR bolt achieved peak axial force,shear displacement,and peak shear force values that are 2.41,1.88,and 2.13 times greater than those of the PR bolt,respectively.Shear performance was optimized at a prestress level of 100 kN,with energy absorption reaching 47.1 kJ,which is 2.8 times that of the PR bolt.Furthermore,the necking ratio was significantly reduced,indicating more distributed plastic deformation and delayed failure.Field applications verified the superior performance,resulting in a 27.4%reduction in roof settlement and enhanced structural integrity.These findings confirm that NPR bolts possess excellent shear resistance,energy absorption,and deformation adaptability,and optimizing prestress significantly enhances their support performance,providing a strong basis for geotechnical engineering applications.
基金Supported by the National Key R&D Program of China under grant No.2022YFB3303203the National Natural Science Foundation of China under grant No.62272275.
文摘With technological advancements,virtual reality(VR),once limited to high-end professional applications,is rapidly expanding into entertainment and broader consumer domains.However,the inherent contradiction between mobile hardware computing power and the demand for high-resolution,high-refresh-rate rendering has intensified,leading to critical bottlenecks,including frame latency and power overload,which constrain large-scale applications of VR systems.This study systematically analyzes four key technologies for efficient VR rendering:(1)foveated rendering,which dynamically reduces rendering precision in peripheral regions based on the physiological characteristics of the human visual system(HVS),thereby significantly decreasing graphics computation load;(2)stereo rendering,optimized through consistent stereo rendering acceleration algorithms;(3)cloud rendering,utilizing object-based decomposition and illumination-based decomposition for distributed resource scheduling;and(4)low-power rendering,integrating parameter-optimized rendering,super-resolution technology,and frame-generation technology to enhance mobile energy efficiency.Through a systematic review of the core principles and optimization approaches of these technologies,this study establishes research benchmarks for developing efficient VR systems that achieve high fidelity and low latency while providing further theoretical support for the engineering implementation and industrial advancement of VR rendering technologies.
基金Projects(41702320,52104125)supported by the National Natural Science Foundation of ChinaProject(ZR2021MD005)+2 种基金supported by the Natural Science Foundation of Shandong Province,ChinaProject(TMduracon2022002)supported by the Engineering Research Center of Marine Environmental Concrete Technology,Ministry of Education,China。
文摘Negative Poisson ratio(NPR)steel is a new material with high strength and toughness.This study conducted tensile tests at elevated temperatures to investigate the mechanical properties of NPR steel at high temperatures.The stress−strain curve,ultimate strength,yield strength,modulus of elasticity,elongation after fracture,and percentage reduction of area of NPR steel bars were measured at 9 different temperatures ranging from 20 to 800℃.The experimental results indicate that high-temperature environments significantly affect the mechanical properties of NPR steel.However,compared to other types of steel,NPR steel exhibits better resistance to deformation.When the test temperature is below 700℃,NPR steel exhibits a ductile fracture characteristic,while at 800℃,it exhibits a brittle fracture characteristic.Finally,based on the experimental findings,a constitutive model suitable for NPR steel at high temperatures is proposed.
基金Supported by National Natural Science Foundation of China(No.62072020)the Leading Talents in Innovation and Entrepreneurship of Qingdao,China(19-3-2-21-zhc).
文摘Background Physics-based differentiable rendering(PBDR)aims to propagate gradients from scene parameters to image pixels or vice versa.The physically correct gradients obtained can be used in various applications,including inverse rendering and machine learning.Currently,two categories of methods are prevalent in the PBDR community:reparameterization and boundary sampling methods.The state-of-the-art boundary sampling methods rely on a guiding structure to calculate the gradients efficiently.They utilize the rays generated in traditional path-tracing methods and project them onto the object silhouette boundary to initialize the guiding structure.Methods In this study,we propose an augmentation of previous projective-sampling-based boundary-sampling methods in a bidirectional manner.Specifically,we utilize the rays spawned from the sensors and also employ the rays emitted by the emitters to initialize the guiding structure.Results To demonstrate the benefits of our technique,we perform a comparative analysis of differentiable rendering and inverse rendering performance.We utilize a range of synthetic scene examples and evaluate our method against state-of-the-art projective-sampling-based differentiable rendering methods.Conclusions The experiments show that our method achieves lower variance gradients in the forward differentiable rendering process and better geometry reconstruction quality in the inverse-rendering results.
基金supported partially by the National Natural Science Foundation of China(No.U19A2063)the Jilin Provincial Science&Technology Development Program of China(No.20230201080GX)。
文摘Currently,the main idea of iterative rendering methods is to allocate a fixed number of samples to pixels that have not been fully rendered by calculating the completion rate.It is obvious that this strategy ignores the changes in pixel values during the previous rendering process,which may result in additional iterative operations.
基金supported by State Key Laboratory for Tunnel Engineering(TESKL202425)the National Natural Science Foundation of China(Grant Nos.U24A2085,52174096,52304110)+1 种基金the Henan Province Key Research and Development Program(Grant Nos.241111322000)the Henan Provincial Science and Technology Research Project(Grant Nos.252102320020)。
文摘In geotechnical engineering applications,including mining and tunnel construction,the stability of fractured rock masses is paramount to ensuring structural safety.The spatial distribution and temporal evolution of internal fractures fundamentally govern the mechanical behavior and failure mechanisms of rock masses.Nevertheless,the inherent complexity and structural concealment of rock mass systems pose significant challenges for the direct measurement of critical internal mechanical parameters.This study explores the use of deep learning to invert mechanical responses of NPR(Negative Poisson's Ratio)anchored fractured rock masses.Discrete Element Method(DEM)simulations were conducted to generate datasets including stress-strain curves and crack numbers under various initial fracture distributions.Three models—GRU,CNN+GRU,and CNN+GRU+ATT—were developed to predict rock mechanical parameters from NPR cable force data.Results show that the CNN+GRU+ATT model achieves superior accuracy,with R^(2)>0.90 and RMSE<5 on stress prediction tasks.It also accurately estimates initial crack quantity(np),with mean prediction error under 10%for high-fracture scenarios.The proposed model effectively captures stress fluctuations,offering early-warning potential for failure.The approach demonstrates strong generalization and robustness across varying crack configurations,providing a feasible framework for real-time health monitoring and mechanical parameter estimation in fractured rock engineering.
基金Supported by the Bavarian Academic Forum(BayWISS),as a part of the joint academic partnership digitalization program.
文摘Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and entertainment.However,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains challenging.Methods This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and VR.Therefore,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image graph.Using this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of views.The rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image graph.The detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in real-time.In addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light intensities.Results Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,respectively.While achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering approaches.Conclusions Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR environments.Nevertheless,the handling of morphing artifacts in the parallax image regions remains a topic for future research.
基金supported by the National Natural Science Foundation of China(Grant Nos.52174096 and 52304110).
文摘With the rapid development of deep resource extraction and underground space construction,the design of anchored support systems for jointed rock masses in complex stress environments faces significant challenges.This study investigates the influence of prefabricated crack dip angles on the mechanical properties of anchored rock masses in deep soft rock roadways.By constructing similarity models of NPR(Negative Poisson’s Ratio)and PR(Positive Poisson’s Ratio)anchored solids,biaxial compression experiments under varying crack dip angles were conducted.Strain gauges,3D Digital Image Correlation(3D DIC),and acoustic emission monitoring were employed to systematically analyze the strength characteristics,deformation-damage evolution,and energy dissipation mechanisms of the two types of anchor systems.The results show that:(1)The stress-strain curves of anchored solids with prefabricated cracks exhibit a distinct bimodal characteristic.Compared to PR anchors,NPR anchors show 20%and 23%improvements in peak strength and elastic modulus,respectively,with residual strength enhanced by up to 34%.(2)Owing to high pre-tightening force and large deformation capacity,NPR anchors maintain superior integrity under increasing crack dip angles,demonstrating more uniform free-surface displacement and localized shear-tensile composite crack patterns.(3)Acoustic emission analysis reveals that NPR anchors exhibit higher cumulative energy absorption(300%improvement over PR anchors)and lack low-rate energy development phases,indicating enhanced ductility and impact resistance at high crack dip angles.(4)Crack dip angle critically governs failure mechanisms by modulating the connectivity between shear cracks and prefabricated fissures:bimodal effects dominate at low angles,while vertical tensile crack propagation replaces bimodal behavior at high angles.The study proposes prioritizing NPR anchor cables in deep engineering applications and optimizing support parameters based on crack dip angles to mitigate stress concentration and ensure the long-term stability of surrounding rock.
