A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.T...A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.The proposed method enables high-fidelity parameterized deformation for both flat and curved perforated surfaces while maintaining mesh quality with minimal geometric distortion.To evaluate its effectiveness,comparative studies between HFFD and conventional FFD methods are conducted,demonstrating superior performance in mesh quality and geometric fidelity.The HFFD-based framework is further applied to the Multidisciplinary Design Optimization(MDO)of a double-wall turbine blade leading edge.Results indicate an 11.6%increase in cooling efficiency and a 16.21%reduction in maximum stress.Additionally,compared to traditional geometry-based parameterization in MDO,the HFFD approach improves model processing efficiency by 84.15%and overall optimization efficiency by20.05%.These findings demonstrate HFFD's potential to significantly improve complex engineering design optimization by achieving precise shape preservation and improving computational efficiency.展开更多
This paper studies high order compact finite volume methods on non-uniform meshes for one-dimensional elliptic and parabolic differential equations with the Robin boundary conditions.An explicit scheme and an implicit...This paper studies high order compact finite volume methods on non-uniform meshes for one-dimensional elliptic and parabolic differential equations with the Robin boundary conditions.An explicit scheme and an implicit scheme are obtained by discretizing the equivalent integral form of the equation.For the explicit scheme with nodal values,the algebraic system can be solved by the Thomas method.For the implicit scheme with both nodal values and their derivatives,the system can be implemented by a prediction-correction procedure,where in the correction stage,an implicit formula for recovering the nodal derivatives is introduced.Taking two point boundary value problem as an example,we prove that both the explicit and implicit schemes are convergent with fourth order accuracy with respect to some standard discrete norms using the energy method.Two numerical examples demonstrate the correctness and effectiveness of the schemes,as well as the indispensability of using non-uniform meshes.展开更多
Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,...Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,frequency-domain methods rely on complex parameterization and spectral decomposition,which are sensitive to mesh topology and resolution and often introduce perceptible artifacts.Spatial-domain techniques,on the other hand,typically embed watermarks in global or randomly selected regions,leading to visible distortions and reduced robustness.To address the above limitations and protect model copyright without compromising the original aesthetic quality,we propose a deterministice PCA-synchronized 3Dmeshwatermarkingmethodwith fullerene-guided carrier selection.First,a deterministic principal component analysis(PCA)-based mesh synchronization algorithm is employed to align the models to a canonical pose.Next,a fullerene-inspired carrier selection strategy is employed to determine the watermark carriers,leveraging the structural characteristics of fullerene molecules to achieve a more rational and effective carrier selection.Finally,to balance the embedding strength and enhance visual quality,the watermark information is embedded using an APQIM(Adaptive Parity-Check Quantization Index Modulation)scheme.The experimental results show that our method can achieve high visual quality with scalable capacity and strong robustness compared with existing methods.The watermarking scheme can resist various attacks,including simplification,smoothing,Gaussian noise,translation,and rotation.展开更多
Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstru...Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstructed from point clouds,they are usually too dense,leading to high computational costs.This paper presents an optimization method for converting dense meshes into optimal meshes,enabling fast and accurate computation of the electrostatic interaction by point clouds.First,the dense mesh reconstructed from point clouds is simplified into a coarse mesh using local operators.Second,the simplified mesh is refined by an iterative strategy that integrates a lightweight method of moments and an impedance matrix inheritance technique,ultimately yielding an optimal mesh for computing the electrostatic interaction.Simulation results show that our method effectively optimizes dense meshes,making electrostatic interaction computations using point clouds approximately 63.4 times more efficient than the previous method.展开更多
This work elaborates an innovative mesh denoising approach that combines feature recovery and denoising in an alternating manner.It proposes a feature-driven variational model and introduces an iterative scheme that a...This work elaborates an innovative mesh denoising approach that combines feature recovery and denoising in an alternating manner.It proposes a feature-driven variational model and introduces an iterative scheme that alternates between feature recovery and the denoising process.The main idea is to estimate feature candidates,filter noisy face normals in the smooth(non-feature)domain,and utilize erosion and dilation operators on the feature candidates.By imposing connectivity constraints on normal vectors with large amplitude variations,the proposed scheme effectively removes noise and progressively recovers both sharp and small-scale features during the iterative process.To validate its effectiveness,this work conducts extensive numerical experiments on both simulated and real-scanned data.The results demonstrate significant improvements in noise reduction and feature preservation compared to existing methods.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
Objective:To explore and analyze the clinical efficacy of flat mesh tension-free hernioplasty in the treatment of patients with inguinal hernia.Methods:A total of 60 patients with inguinal hernia were included and equ...Objective:To explore and analyze the clinical efficacy of flat mesh tension-free hernioplasty in the treatment of patients with inguinal hernia.Methods:A total of 60 patients with inguinal hernia were included and equally divided into an observation group(30 cases,flat mesh tension-free hernioplasty)and a control group(30 cases,mesh plug tension-free hernioplasty)based on differences in surgical plans.The visual analog scale(VAS)for postoperative pain,inflammatory markers(C-reactive protein,white blood cell count),and complication rates were compared between the two groups.Results:At 24 and 48 hours postoperatively,the VAS scores in the observation group were significantly lower than those in the control group(P<0.05).At 24 hours postoperatively,the levels of CRP and WBC were also lower in the observation group(P<0.05).The complication rate was slightly lower in the observation group(P>0.05).Conclusion:Flat mesh tension-free hernioplasty for inguinal hernia can alleviate postoperative pain and suppress inflammatory responses,with fewer complications,making it suitable for promotion at primary healthcare facilities.展开更多
基金supported by the National Science and Technology Major Project,China(No.2017-II-0006-0019)the National Natural Science Foundation of China(No.52375266)the Shaanxi Science Foundation for Distinguished Young Scholars,China(No.2022JC-36)。
文摘A Hybrid Free-Form Deformation(HFFD)method is developed to improve shape preservation in mesh deformation for perforated surfaces,which traditional Free-Form Deformation(FFD)techniques struggle to handle effectively.The proposed method enables high-fidelity parameterized deformation for both flat and curved perforated surfaces while maintaining mesh quality with minimal geometric distortion.To evaluate its effectiveness,comparative studies between HFFD and conventional FFD methods are conducted,demonstrating superior performance in mesh quality and geometric fidelity.The HFFD-based framework is further applied to the Multidisciplinary Design Optimization(MDO)of a double-wall turbine blade leading edge.Results indicate an 11.6%increase in cooling efficiency and a 16.21%reduction in maximum stress.Additionally,compared to traditional geometry-based parameterization in MDO,the HFFD approach improves model processing efficiency by 84.15%and overall optimization efficiency by20.05%.These findings demonstrate HFFD's potential to significantly improve complex engineering design optimization by achieving precise shape preservation and improving computational efficiency.
文摘This paper studies high order compact finite volume methods on non-uniform meshes for one-dimensional elliptic and parabolic differential equations with the Robin boundary conditions.An explicit scheme and an implicit scheme are obtained by discretizing the equivalent integral form of the equation.For the explicit scheme with nodal values,the algebraic system can be solved by the Thomas method.For the implicit scheme with both nodal values and their derivatives,the system can be implemented by a prediction-correction procedure,where in the correction stage,an implicit formula for recovering the nodal derivatives is introduced.Taking two point boundary value problem as an example,we prove that both the explicit and implicit schemes are convergent with fourth order accuracy with respect to some standard discrete norms using the energy method.Two numerical examples demonstrate the correctness and effectiveness of the schemes,as well as the indispensability of using non-uniform meshes.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 62272331the Key Laboratory of Data Protection and Intelligent Management,Ministry of Education,Sichuan University and the Fundamental Research Funds for the Central Universities under Grant SCU2023D008.
文摘Mesh models are among the primary representations for storing 3-D objects,encapsulating detailed geometric information.3-D mesh watermarking,in particular,plays a central role in the protection of 3-D content.However,frequency-domain methods rely on complex parameterization and spectral decomposition,which are sensitive to mesh topology and resolution and often introduce perceptible artifacts.Spatial-domain techniques,on the other hand,typically embed watermarks in global or randomly selected regions,leading to visible distortions and reduced robustness.To address the above limitations and protect model copyright without compromising the original aesthetic quality,we propose a deterministice PCA-synchronized 3Dmeshwatermarkingmethodwith fullerene-guided carrier selection.First,a deterministic principal component analysis(PCA)-based mesh synchronization algorithm is employed to align the models to a canonical pose.Next,a fullerene-inspired carrier selection strategy is employed to determine the watermark carriers,leveraging the structural characteristics of fullerene molecules to achieve a more rational and effective carrier selection.Finally,to balance the embedding strength and enhance visual quality,the watermark information is embedded using an APQIM(Adaptive Parity-Check Quantization Index Modulation)scheme.The experimental results show that our method can achieve high visual quality with scalable capacity and strong robustness compared with existing methods.The watermarking scheme can resist various attacks,including simplification,smoothing,Gaussian noise,translation,and rotation.
基金supported by the National Natural Science Foundation of China(No.62003269).
文摘Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstructed from point clouds,they are usually too dense,leading to high computational costs.This paper presents an optimization method for converting dense meshes into optimal meshes,enabling fast and accurate computation of the electrostatic interaction by point clouds.First,the dense mesh reconstructed from point clouds is simplified into a coarse mesh using local operators.Second,the simplified mesh is refined by an iterative strategy that integrates a lightweight method of moments and an impedance matrix inheritance technique,ultimately yielding an optimal mesh for computing the electrostatic interaction.Simulation results show that our method effectively optimizes dense meshes,making electrostatic interaction computations using point clouds approximately 63.4 times more efficient than the previous method.
基金supported in part by the National Natural Science Foundation of China(62476219,62206220,12271140,12326609)the Young Talent Fund of Association for Science and Technology in Shaanxi,China(20230140)+1 种基金the Chunhui Program of Ministry of Education of China(HZKY20220537)the Fundamental Funds for the Central Universities(G2023KY0601).
文摘This work elaborates an innovative mesh denoising approach that combines feature recovery and denoising in an alternating manner.It proposes a feature-driven variational model and introduces an iterative scheme that alternates between feature recovery and the denoising process.The main idea is to estimate feature candidates,filter noisy face normals in the smooth(non-feature)domain,and utilize erosion and dilation operators on the feature candidates.By imposing connectivity constraints on normal vectors with large amplitude variations,the proposed scheme effectively removes noise and progressively recovers both sharp and small-scale features during the iterative process.To validate its effectiveness,this work conducts extensive numerical experiments on both simulated and real-scanned data.The results demonstrate significant improvements in noise reduction and feature preservation compared to existing methods.
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Objective:To explore and analyze the clinical efficacy of flat mesh tension-free hernioplasty in the treatment of patients with inguinal hernia.Methods:A total of 60 patients with inguinal hernia were included and equally divided into an observation group(30 cases,flat mesh tension-free hernioplasty)and a control group(30 cases,mesh plug tension-free hernioplasty)based on differences in surgical plans.The visual analog scale(VAS)for postoperative pain,inflammatory markers(C-reactive protein,white blood cell count),and complication rates were compared between the two groups.Results:At 24 and 48 hours postoperatively,the VAS scores in the observation group were significantly lower than those in the control group(P<0.05).At 24 hours postoperatively,the levels of CRP and WBC were also lower in the observation group(P<0.05).The complication rate was slightly lower in the observation group(P>0.05).Conclusion:Flat mesh tension-free hernioplasty for inguinal hernia can alleviate postoperative pain and suppress inflammatory responses,with fewer complications,making it suitable for promotion at primary healthcare facilities.
