Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as...Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as well as cumbersome and cluttered annotations on drawings, which interfere with the vector extraction heavily. In this article, the transmission tower containing the most complex structure is taken as the research object, and a semantic segmentation network is constructed to first segment the shape masks from the pixel-level drawings. Preprocessing and postprocessing are also proposed to ensure the stability and accuracy of the shape mask segmentation. Then, based on the obtained shape masks, a vector extraction network guided by heatmaps is designed to extract structural vectors by fusing the features from node heatmap and skeleton heatmap, respectively. Compared with the state-of-the-art methods, experiment results illustrate that the proposed semantic segmentation method can effectively eliminate the interference of many elements on drawings to segment the shape masks effectively, meanwhile, the model trained by the proposed vector extraction network can accurately extract the vectors such as nodes and line connections, avoiding redundant vector detection. The proposed method lays a solid foundation for automatic 3D model reconstruction and contributes to technological advancements in relevant fields.展开更多
This research establishes a methodological framework for generating geometrically accurate 3D representations of human crystalline lenses through scanning technologies and digital reconstruction. Multiple scanning sys...This research establishes a methodological framework for generating geometrically accurate 3D representations of human crystalline lenses through scanning technologies and digital reconstruction. Multiple scanning systems were evaluated to identify optimal approaches for point cloud processing and subsequent development of parameterized solid models, facilitating comprehensive morpho-geometric characterization. Experimental work was performed at the 3D Scanning Laboratory of SEDIC (Industrial Design and Scientific Calculation Service) at the Technical University of Cartagena, employing five distinct scanner types based on structured light, laser, and infrared technologies. Test specimens—including preliminary calibration using a lentil and biological analysis of a human crystalline lens—were digitized under rigorously controlled environmental conditions. Acquired point clouds underwent processing in Rhinoceros software to produce digital surface meshes, which were subsequently converted into solid CAD models via SolidWorks. Model fidelity and biomedical relevance were assessed through quantification of geometric and physical properties. Scanner performance varied significantly in reconstruction precision and resolution, with structured blue light systems (e.g., Artec SPIDER) exhibiting superior capability for capturing lens surface topography compared to infrared or white light alternatives. Resultant models enabled accurate dimensional analysis of clinically relevant parameters including volumetric and surface area measurements. Technology-specific advantages and constraints were rigorously cataloged relative to sample attributes. Findings indicate that structured blue light scanning provides the most effective foundation for crystalline lens digitization and modeling. The presented methodological approach not only ensures high-fidelity solid model generation but also demonstrates translational potential in medical domains, from custom intraocular lens design to refinement of ophthalmic therapeutic interventions.展开更多
This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are ob...This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.展开更多
With the widespread application of 3D visualization in digital exhibition halls and virtual reality,achieving efficient rendering and high-fidelity presentation has become a key challenge.This study proposes a hybrid ...With the widespread application of 3D visualization in digital exhibition halls and virtual reality,achieving efficient rendering and high-fidelity presentation has become a key challenge.This study proposes a hybrid point cloud generation method that combines traditional sampling with 3D Gaussian splatting,aiming to address the issues of rendering delay and missing details in existing 3D displays.By improving the OBJ model parsing process and incorporating an adaptive area-weighted sampling algorithm,we achieve adaptive point cloud generation based on triangle density.Innovatively,we advance the ellipsoidal parameter estimation process of 3D Gaussian splatting to the point cloud generation stage.By establishing a mathematical relationship between the covariance matrix and local curvature,the generated point cloud naturally exhibits Gaussian distribution characteristics.Experimental results show that,compared to traditional methods,our approach reduces point cloud data by 38% while maintaining equivalent visual quality at a 4096×4096 texture resolution.By introducing mipmap texture optimization strategies and a GPU-accelerated rasterization pipeline,stable rendering at 60 frames per second is achieved in a WebGL environment.Additionally,we quantize and compress the spherical harmonic function parameters specific to 3D Gaussian splatting,reducing network transmission bandwidth to 52% of the original data.This study provides a new technical pathway for fields requiring high-precision display,such as the digitization of cultural heritage.展开更多
Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of wat...Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.展开更多
Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust d...Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust dietary exposure levels of risk factors;however,traditional planar Transwell models have limitations,such as cell dedifferentiation and lack of key intestinal components,necessitating a more physiologically relevant in vitro platform.This study introduces an innovative three-dimensional(3D)intestinal organoid model using a microfluidic chip to evaluate Cd bioavailability in food.Caco-2 cells were cultured on the chip to mimic small intestinal villi's 3D structure,mucus production,and absorption functions.The model's physiological relevance was thoroughly characterized,demonstrating the formation of a confluent epithelial monolayer with well-developed tight junctions(ZO-1),high microvilli density(F-actin),and significant mucus secretion(Alcian blue staining),closely resembling the physiological intestinal epithelium.Fluorescent particle tracking confirmed its ability to simulate intestinal transport and diffusion.The Cd bioavailability in rice measured by the 3D intestinal organoid model((9.07±0.21)%)was comparable to the mouse model((12.82±3.42)%)but significantly lower than the Caco-2 monolayer model((26.97±1.11)%).This 3D intestinal organoid model provides a novel and reliable strategy for in vitro assessment of heavy metal bioavailability in food,with important implications for food safety and risk assessment.展开更多
To improve the reusability of three-dimensional （3D） models and simplify the complexity of natural scene reconstruction, this paper presents a 3D model database for universal 3D GIS. After the introduction of its ex...To improve the reusability of three-dimensional （3D） models and simplify the complexity of natural scene reconstruction, this paper presents a 3D model database for universal 3D GIS. After the introduction of its extensible function architecture, accompanied by the conclusion of implicit spatial-temporal hierarchy of models in any reconstructed scene of 3D GIS for general purpose, several key issues are discussed in detail, such as the storage and management of 3D models and related retrieval and load method, as well as the interfaces for further on-demand development. Finally, the validity and feasibility of this model database are proved through its application in the development of 3D visualization system of railway operation.展开更多
To speed up three-dimensional （3D） DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method （AGMG）. We first discretize the differential equation of the secondar...To speed up three-dimensional （3D） DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method （AGMG）. We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner （AGMG-CG） to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling （3DDCXH）. In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.展开更多
Design of internal combustion engine (ICE) components is one of the earliest and also the most active areas in which computer aided modeling techniques are applied. Computer aided modeling techniques could provide req...Design of internal combustion engine (ICE) components is one of the earliest and also the most active areas in which computer aided modeling techniques are applied. Computer aided modeling techniques could provide requisite information for follow up designing segments such as structural analysis, design of technological process and manufacturing etc, and thereby lead to the reduction of product design period and the quality and reliability improvement of ICE components. So the developing situations of ICE components' 2 D drafting, 3 D modeling of ICE, overall CAD of ICE as well as component design expert system etc. are surveyed, which are the typical applications of computer aided modeling techniques in ICE component design process, and some existent problems and tasks are pointed out so as to make some references for the further research work.展开更多
Anticancer drug resistance remains a major challenge in cancer treatment hindering the efficacy of chemotherapy and targeted therapies.Conventional two-dimensional(2D)cell cultures cannot replicate the complexity of t...Anticancer drug resistance remains a major challenge in cancer treatment hindering the efficacy of chemotherapy and targeted therapies.Conventional two-dimensional(2D)cell cultures cannot replicate the complexity of the in vivo tumor microenvironment(TME),limiting their utility for drug resistance research.Therefore,three-dimensional(3D)tumor models have proven to be a promising alternative for investigating chemoresistance mechanisms.In this review,various cancer 3D models,including spheroids,organoids,scaffold-based models,and bioprinted models,are comprehensively evaluated with a focus on their application in drug resistance studies.We discuss the materials,properties,and advantages of each model,highlighting their ability to better mimic the TME and represent complex mechanisms of drug resistance such as epithelial-mesenchymal transition(EMT),drug efflux,and tumor-stroma interactions.Furthermore,we investigate the limitations of these models,including scalability,reproducibility and technical challenges,as well as their potential therapeutic impact on personalized medicine.Through a thorough comparison of model performance,we provide insights into the strengths and weaknesses of each approach and offer guidance for model selection based on specific research needs.展开更多
This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)syste...This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.展开更多
According to the mining method for Dongguashan Copper Mine and Tongkeng Mine in China, and with the help of the cavity monitoring system（CMS） and mining software Surpac, the 3D cavity models were established exactly...According to the mining method for Dongguashan Copper Mine and Tongkeng Mine in China, and with the help of the cavity monitoring system（CMS） and mining software Surpac, the 3D cavity models were established exactly. A series of correlative techniques for calculating stope over-excavation and under-excavation, stope dilution and ore loss rates, and the blasting design of the pillar with complicated irregular boundaries were developed. These techniques were applied in Dongguashan Copper Mine and Tongkeng Mine successfully. Using these techniques, the dilution rates of stopes 52-2^#, 52-6^#, 52-8^#and 52-10^# of Dongguashan Copper Mine are calculated to be 2.12%, 8.46%, 12-67% and 10.68%, respectively, and the ore loss rates of stopes 52-6^# and 5-8^# are 4.41% and 3.70%, severally. Furthermore, according to the design accomplished by the technique for a pillar of Tongkeng Mine with irregular boundary, the volume, total length of boreholes and the dynamite quantity of the pillar are computed to be 1.2 ×10^4 m^3, 2.98 km and 10.97 t, correspondingly.展开更多
Soil-rock mixture （SRM） is a unique type of geomaterial characterized by a heterogeneous composition and a complicated structure. It is intractable for the continuum-based soil and rock mechanics theories to accurat...Soil-rock mixture （SRM） is a unique type of geomaterial characterized by a heterogeneous composition and a complicated structure. It is intractable for the continuum-based soil and rock mechanics theories to accurately characterize and predict the SRM＇s mechanical properties. This study reports a novel numerical method incorporating microfocus computed tomography and PFC3D codes to probe the deformation and failure processes of SRM. The three-dimensional （3D） PFC models that represent the SRM＇s complex structures were built. By simulating the entire failure process in PFC3D, the SRM＇s strength, elastic modulus and crack growth were obtained. The influence of rock ratios on the SRM＇s strength, deformation and failure processes, as well as its internal mesoscale mechanism, were analyzed. By comparing simulation results with experimental data, it was verified that the 3D PFC models were in good agreement with SRM＇s real structure and the SRM＇s compression process, deformation and failure patterns; its intrinsic mesomechanism can be effectively analyzed based on such 3D PFC models.展开更多
The full-length sequence of the odorant binding protein 5 gene,HarmOBP5,was obtained from an antennae cDNA library of cotton bollworm,Helicoverpa armigera （Hübner）.The cDNA contains a 444 bp open reading frame,...The full-length sequence of the odorant binding protein 5 gene,HarmOBP5,was obtained from an antennae cDNA library of cotton bollworm,Helicoverpa armigera （Hübner）.The cDNA contains a 444 bp open reading frame,encoding a protein with 147 amino acids,namely HarmOBP5.HarmOBP5 was expressed in Escherichia coli and the recombinant protein was purified by affinity chromatography.SDS-PAGE and Western blot analysis demonstrated that the purified protein can be used for further investigation of its binding characteristics.Competitive binding assays with 113 odorant chemicals indicated that HarmOBP5 has strong affinity to some special plant volatiles,including （E）-β-farnesene,ethyl butyrate,ethyl heptanoate,and acetic acid 2-methylbutyl ester.Based on three-dimensional （3D） model of AaegOBP1 from Aedes aegypti,a 3D model of HarmOBP5 was predicted.The model revealed that some key binding residues in HarmOBP5 may play important roles in odorant perception of H.armigera.This study provides clues for better understanding physiological functions of OBPs in H.armigera and other insects.展开更多
In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects...In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.展开更多
Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to effici...Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.展开更多
Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low tim...Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the ＂Shape Distribution （D2）＂ algorithm, and a new algorithm named ＂Quick D2＂ is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, ＂3D Searcher＂, a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.展开更多
The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the dat...The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.展开更多
The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience ...The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience of geologists.This approach has strong subjectivity,low efficiency,and high uncertainty.This uncertainty may be one of the key factors affecting the results of 3 D modeling of tight sandstone reservoirs.In recent years,deep learning,which is a cutting-edge artificial intelligence technology,has attracted attention from various fields.However,the study of deep-learning techniques in the field of lithofacies classification has not been sufficient.Therefore,this paper proposes a novel hybrid deep-learning model based on the efficient data feature-extraction ability of convolutional neural networks(CNN)and the excellent ability to describe time-dependent features of long short-term memory networks(LSTM)to conduct lithological facies-classification experiments.The results of a series of experiments show that the hybrid CNN-LSTM model had an average accuracy of 87.3%and the best classification effect compared to the CNN,LSTM or the three commonly used machine learning models(Support vector machine,random forest,and gradient boosting decision tree).In addition,the borderline synthetic minority oversampling technique(BSMOTE)is introduced to address the class-imbalance issue of raw data.The results show that processed data balance can significantly improve the accuracy of lithofacies classification.Beside that,based on the fine lithofacies constraints,the sequential indicator simulation method is used to establish a three-dimensional lithofacies model,which completes the fine description of the spatial distribution of tight sandstone reservoirs in the study area.According to this comprehensive analysis,the proposed CNN-LSTM model,which eliminates class imbalance,can be effectively applied to lithofacies classification,and is expected to improve the reality of the geological model for the tight sandstone reservoirs.展开更多
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
基金funded by the Chinese State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project Funding,Grant Number J2023031.
文摘Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as well as cumbersome and cluttered annotations on drawings, which interfere with the vector extraction heavily. In this article, the transmission tower containing the most complex structure is taken as the research object, and a semantic segmentation network is constructed to first segment the shape masks from the pixel-level drawings. Preprocessing and postprocessing are also proposed to ensure the stability and accuracy of the shape mask segmentation. Then, based on the obtained shape masks, a vector extraction network guided by heatmaps is designed to extract structural vectors by fusing the features from node heatmap and skeleton heatmap, respectively. Compared with the state-of-the-art methods, experiment results illustrate that the proposed semantic segmentation method can effectively eliminate the interference of many elements on drawings to segment the shape masks effectively, meanwhile, the model trained by the proposed vector extraction network can accurately extract the vectors such as nodes and line connections, avoiding redundant vector detection. The proposed method lays a solid foundation for automatic 3D model reconstruction and contributes to technological advancements in relevant fields.
基金funded by“Programa de Ayuda para la Puesta en Marcha o Mantenimiento de Líneas de Investigación Competitivas(LANZADERA)2025”of the Technical University of Cartagena.This study was also carried out in collaboration with the Association for the Integration of the Disabled in the Comarca del Mar Menor(AIDEMAR,collaboration protocol UPCT-AIDEMAR)Ophthalmology team at the“Hospital General Universitario Santa Lucia”in Cartagena for their support during this research.
文摘This research establishes a methodological framework for generating geometrically accurate 3D representations of human crystalline lenses through scanning technologies and digital reconstruction. Multiple scanning systems were evaluated to identify optimal approaches for point cloud processing and subsequent development of parameterized solid models, facilitating comprehensive morpho-geometric characterization. Experimental work was performed at the 3D Scanning Laboratory of SEDIC (Industrial Design and Scientific Calculation Service) at the Technical University of Cartagena, employing five distinct scanner types based on structured light, laser, and infrared technologies. Test specimens—including preliminary calibration using a lentil and biological analysis of a human crystalline lens—were digitized under rigorously controlled environmental conditions. Acquired point clouds underwent processing in Rhinoceros software to produce digital surface meshes, which were subsequently converted into solid CAD models via SolidWorks. Model fidelity and biomedical relevance were assessed through quantification of geometric and physical properties. Scanner performance varied significantly in reconstruction precision and resolution, with structured blue light systems (e.g., Artec SPIDER) exhibiting superior capability for capturing lens surface topography compared to infrared or white light alternatives. Resultant models enabled accurate dimensional analysis of clinically relevant parameters including volumetric and surface area measurements. Technology-specific advantages and constraints were rigorously cataloged relative to sample attributes. Findings indicate that structured blue light scanning provides the most effective foundation for crystalline lens digitization and modeling. The presented methodological approach not only ensures high-fidelity solid model generation but also demonstrates translational potential in medical domains, from custom intraocular lens design to refinement of ophthalmic therapeutic interventions.
基金supported by the Key Research and DevelopmentPlan in Shanxi Province of China(No.201803D421045)the Natural Science Foundation of Shanxi Province(No.2021-0302-123104)。
文摘This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.
文摘With the widespread application of 3D visualization in digital exhibition halls and virtual reality,achieving efficient rendering and high-fidelity presentation has become a key challenge.This study proposes a hybrid point cloud generation method that combines traditional sampling with 3D Gaussian splatting,aiming to address the issues of rendering delay and missing details in existing 3D displays.By improving the OBJ model parsing process and incorporating an adaptive area-weighted sampling algorithm,we achieve adaptive point cloud generation based on triangle density.Innovatively,we advance the ellipsoidal parameter estimation process of 3D Gaussian splatting to the point cloud generation stage.By establishing a mathematical relationship between the covariance matrix and local curvature,the generated point cloud naturally exhibits Gaussian distribution characteristics.Experimental results show that,compared to traditional methods,our approach reduces point cloud data by 38% while maintaining equivalent visual quality at a 4096×4096 texture resolution.By introducing mipmap texture optimization strategies and a GPU-accelerated rasterization pipeline,stable rendering at 60 frames per second is achieved in a WebGL environment.Additionally,we quantize and compress the spherical harmonic function parameters specific to 3D Gaussian splatting,reducing network transmission bandwidth to 52% of the original data.This study provides a new technical pathway for fields requiring high-precision display,such as the digitization of cultural heritage.
基金supported by the National Key R&D Program of China(No.2023YFC3006702)the Natural Science Foundation of Beijing Municipality(IS23117).
文摘Characterized by special morphologic,geographic,hydrologic,and societal behaviors,the water resources management of the Mediterranean catchment often shows a higher level of complexity including security issues of water supply,inundation risks,and environment management under the perspective of climate change.To have a comprehensive understanding of the Mediterranean water-cycle system,a deterministic distributed hydrologic modeling approach has been developed and presented in this study based on an application in the Var catchment(2800 km^(2))located at the French Mediterranean region.A 1D and 2D coupled model of MIKE SHE and MIKE 11 has been set up under a series of hypotheses to represent the whole hydrologic and hydrodynamic processes including rainfall-runoff,snow-melting,channel flow,overland flow,and the water exchange between land surface and unsaturated/saturated zones.The developed model was first calibrated with 4 years daily records from 2008 to 2011,then to be validated and further run within hourly time interval to produce detailed representation of the catchment water-cycle from 2012 to 2014.The deterministic distributed modeling approach presented in this study is able to represent its complicated water-cycle and used for supporting the decision‐making process of the water resources management of the catchment.
基金supported by National key research and development program of China(2022YFF1102500)。
文摘Given the severe toxicity and widespread presence of cadmium(Cd)in staple foods such as rice,accurate dietary exposure assessments are imperative for public health.In vitro bioavailability is commonly used to adjust dietary exposure levels of risk factors;however,traditional planar Transwell models have limitations,such as cell dedifferentiation and lack of key intestinal components,necessitating a more physiologically relevant in vitro platform.This study introduces an innovative three-dimensional(3D)intestinal organoid model using a microfluidic chip to evaluate Cd bioavailability in food.Caco-2 cells were cultured on the chip to mimic small intestinal villi's 3D structure,mucus production,and absorption functions.The model's physiological relevance was thoroughly characterized,demonstrating the formation of a confluent epithelial monolayer with well-developed tight junctions(ZO-1),high microvilli density(F-actin),and significant mucus secretion(Alcian blue staining),closely resembling the physiological intestinal epithelium.Fluorescent particle tracking confirmed its ability to simulate intestinal transport and diffusion.The Cd bioavailability in rice measured by the 3D intestinal organoid model((9.07±0.21)%)was comparable to the mouse model((12.82±3.42)%)but significantly lower than the Caco-2 monolayer model((26.97±1.11)%).This 3D intestinal organoid model provides a novel and reliable strategy for in vitro assessment of heavy metal bioavailability in food,with important implications for food safety and risk assessment.
基金Supported by the National Natural Science Foundation of China (No.40871212, No.40671158)the National High Technology Research and Development Program of China (No.2008AA121600)
文摘To improve the reusability of three-dimensional （3D） models and simplify the complexity of natural scene reconstruction, this paper presents a 3D model database for universal 3D GIS. After the introduction of its extensible function architecture, accompanied by the conclusion of implicit spatial-temporal hierarchy of models in any reconstructed scene of 3D GIS for general purpose, several key issues are discussed in detail, such as the storage and management of 3D models and related retrieval and load method, as well as the interfaces for further on-demand development. Finally, the validity and feasibility of this model database are proved through its application in the development of 3D visualization system of railway operation.
基金supported by the Natural Science Foundation of China(Nos.41404057,41674077 and 411640034)the Nuclear Energy Development Project of China,and the‘555’Project of Gan Po Excellent People
文摘To speed up three-dimensional （3D） DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method （AGMG）. We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner （AGMG-CG） to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling （3DDCXH）. In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.
文摘Design of internal combustion engine (ICE) components is one of the earliest and also the most active areas in which computer aided modeling techniques are applied. Computer aided modeling techniques could provide requisite information for follow up designing segments such as structural analysis, design of technological process and manufacturing etc, and thereby lead to the reduction of product design period and the quality and reliability improvement of ICE components. So the developing situations of ICE components' 2 D drafting, 3 D modeling of ICE, overall CAD of ICE as well as component design expert system etc. are surveyed, which are the typical applications of computer aided modeling techniques in ICE component design process, and some existent problems and tasks are pointed out so as to make some references for the further research work.
基金funded by the Ministry of Science,Technological Development and Innovation of the Republic of Serbia(grant numbers 451-03-136/2025-03/200007 and 451-03-136/2025-03/200042).
文摘Anticancer drug resistance remains a major challenge in cancer treatment hindering the efficacy of chemotherapy and targeted therapies.Conventional two-dimensional(2D)cell cultures cannot replicate the complexity of the in vivo tumor microenvironment(TME),limiting their utility for drug resistance research.Therefore,three-dimensional(3D)tumor models have proven to be a promising alternative for investigating chemoresistance mechanisms.In this review,various cancer 3D models,including spheroids,organoids,scaffold-based models,and bioprinted models,are comprehensively evaluated with a focus on their application in drug resistance studies.We discuss the materials,properties,and advantages of each model,highlighting their ability to better mimic the TME and represent complex mechanisms of drug resistance such as epithelial-mesenchymal transition(EMT),drug efflux,and tumor-stroma interactions.Furthermore,we investigate the limitations of these models,including scalability,reproducibility and technical challenges,as well as their potential therapeutic impact on personalized medicine.Through a thorough comparison of model performance,we provide insights into the strengths and weaknesses of each approach and offer guidance for model selection based on specific research needs.
文摘This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.
基金Projects(2007BAK22B04, 2006BAB02B05) supported by the National 11th Five-Year Science and Technology Supporting Plan of ChinaProject(50490274) supported by the National Natural Science Foundation of China
文摘According to the mining method for Dongguashan Copper Mine and Tongkeng Mine in China, and with the help of the cavity monitoring system（CMS） and mining software Surpac, the 3D cavity models were established exactly. A series of correlative techniques for calculating stope over-excavation and under-excavation, stope dilution and ore loss rates, and the blasting design of the pillar with complicated irregular boundaries were developed. These techniques were applied in Dongguashan Copper Mine and Tongkeng Mine successfully. Using these techniques, the dilution rates of stopes 52-2^#, 52-6^#, 52-8^#and 52-10^# of Dongguashan Copper Mine are calculated to be 2.12%, 8.46%, 12-67% and 10.68%, respectively, and the ore loss rates of stopes 52-6^# and 5-8^# are 4.41% and 3.70%, severally. Furthermore, according to the design accomplished by the technique for a pillar of Tongkeng Mine with irregular boundary, the volume, total length of boreholes and the dynamite quantity of the pillar are computed to be 1.2 ×10^4 m^3, 2.98 km and 10.97 t, correspondingly.
基金Acknowledgements The authors gratefully acknowledge the financial support from the State Key Research Development Program of China （Grant No. 2016YFC0600705）, the National Natural Science Foundation of China （Grant Nos. 51674251, 51727807, 51374213）, the National Natural Science Foundation for Distinguished Young Scholars of China （Grant No. 51125017）, the Fund for Creative Research and Development Group Program of Jiangsu Province （Grant No. 2014-27）, and the Priority Academic Program Development of Jiangsu Higher Education Institutions （Grant No. PAPD2014）, and an open project sponsored by the State Key Labo- ratory for Geomechanics and Deep Underground Engineering （Grant SKLGDUE K1318） for their financial support.
文摘Soil-rock mixture （SRM） is a unique type of geomaterial characterized by a heterogeneous composition and a complicated structure. It is intractable for the continuum-based soil and rock mechanics theories to accurately characterize and predict the SRM＇s mechanical properties. This study reports a novel numerical method incorporating microfocus computed tomography and PFC3D codes to probe the deformation and failure processes of SRM. The three-dimensional （3D） PFC models that represent the SRM＇s complex structures were built. By simulating the entire failure process in PFC3D, the SRM＇s strength, elastic modulus and crack growth were obtained. The influence of rock ratios on the SRM＇s strength, deformation and failure processes, as well as its internal mesoscale mechanism, were analyzed. By comparing simulation results with experimental data, it was verified that the 3D PFC models were in good agreement with SRM＇s real structure and the SRM＇s compression process, deformation and failure patterns; its intrinsic mesomechanism can be effectively analyzed based on such 3D PFC models.
基金supported by the National Basic Research Program of China(2012CB114104)the National Natural Science Foundation of China(30871640,31071694)+1 种基金the National High-Tech R&D Program of China(2008AA02Z307)the International Cooperation and Exchange Foundation of NSFC-RS of China(31111130203).
文摘The full-length sequence of the odorant binding protein 5 gene,HarmOBP5,was obtained from an antennae cDNA library of cotton bollworm,Helicoverpa armigera （Hübner）.The cDNA contains a 444 bp open reading frame,encoding a protein with 147 amino acids,namely HarmOBP5.HarmOBP5 was expressed in Escherichia coli and the recombinant protein was purified by affinity chromatography.SDS-PAGE and Western blot analysis demonstrated that the purified protein can be used for further investigation of its binding characteristics.Competitive binding assays with 113 odorant chemicals indicated that HarmOBP5 has strong affinity to some special plant volatiles,including （E）-β-farnesene,ethyl butyrate,ethyl heptanoate,and acetic acid 2-methylbutyl ester.Based on three-dimensional （3D） model of AaegOBP1 from Aedes aegypti,a 3D model of HarmOBP5 was predicted.The model revealed that some key binding residues in HarmOBP5 may play important roles in odorant perception of H.armigera.This study provides clues for better understanding physiological functions of OBPs in H.armigera and other insects.
基金the National Basic Research Program (973) of China (No. 2004CB719401)the National Research Foundation for the Doctoral Program of Higher Education of China (No.20060003060)
文摘In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.
基金supported by a grant(No.14DZ2292800,http://www.greengeo.net/)from“Technology Service Platform of Civil Engineering”of Science and Technology Commission of Shanghai Municipality.
文摘Underground pipeline networks constitute a major component of urban infrastructure,and thus,it is imperative to have an efficient mechanism to manage them.This study introduces a secondary development system to efficiently model underground pipeline networks,using the building information modeling(BIM)-based software Revit.The system comprises separate pipe point and tubulation models.Using a Revit application programming interface(API),the spatial position and attribute data of the pipe points are extracted from a pipeline database,and the corresponding tubulation data are extracted from a tubulation database.Using the Family class in Revit API,the cluster in the self-built library of pipe point is inserted into the spatial location and the attribute data is added;in the same way,all pipeline instances in the pipeline system are created.The extension and localization of the model accelerated the modeling speed.The system was then used in a real construction project.The expansion of the model database and rapid modeling made the application of BIM technology in three-dimensional visualization of underground pipeline networks more convenient.Furthermore,it has applications in pipeline engineering construction and management.
基金supported by National Natural Science Foundation of China(Grant No. 51175287)National Science and Technology Major Project(Grant No. 2011ZX02403)
文摘Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the ＂Shape Distribution （D2）＂ algorithm, and a new algorithm named ＂Quick D2＂ is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, ＂3D Searcher＂, a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.
基金This research is sponsored by the National Natural Science Foundation of China （No. 40374024）.
文摘The workload of the 3D magnetotelluric forward modeling algorithm is so large that the traditional serial algorithm costs an extremely large compute time. However, the 3D forward modeling algorithm can process the data in the frequency domain, which is very suitable for parallel computation. With the advantage of MPI and based on an analysis of the flow of the 3D magnetotelluric serial forward algorithm, we suggest the idea of parallel computation and apply it. Three theoretical models are tested and the execution efficiency is compared in different situations. The results indicate that the parallel 3D forward modeling computation is correct and the efficiency is greatly improved. This method is suitable for large size geophysical computations.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.300102278402)。
文摘The lithofacies classification is essential for oil and gas reservoir exploration and development.The traditional method of lithofacies classification is based on"core calibration logging"and the experience of geologists.This approach has strong subjectivity,low efficiency,and high uncertainty.This uncertainty may be one of the key factors affecting the results of 3 D modeling of tight sandstone reservoirs.In recent years,deep learning,which is a cutting-edge artificial intelligence technology,has attracted attention from various fields.However,the study of deep-learning techniques in the field of lithofacies classification has not been sufficient.Therefore,this paper proposes a novel hybrid deep-learning model based on the efficient data feature-extraction ability of convolutional neural networks(CNN)and the excellent ability to describe time-dependent features of long short-term memory networks(LSTM)to conduct lithological facies-classification experiments.The results of a series of experiments show that the hybrid CNN-LSTM model had an average accuracy of 87.3%and the best classification effect compared to the CNN,LSTM or the three commonly used machine learning models(Support vector machine,random forest,and gradient boosting decision tree).In addition,the borderline synthetic minority oversampling technique(BSMOTE)is introduced to address the class-imbalance issue of raw data.The results show that processed data balance can significantly improve the accuracy of lithofacies classification.Beside that,based on the fine lithofacies constraints,the sequential indicator simulation method is used to establish a three-dimensional lithofacies model,which completes the fine description of the spatial distribution of tight sandstone reservoirs in the study area.According to this comprehensive analysis,the proposed CNN-LSTM model,which eliminates class imbalance,can be effectively applied to lithofacies classification,and is expected to improve the reality of the geological model for the tight sandstone reservoirs.
