基于Smart 3D的船体结构开孔参数化工具开发

为了解决船体结构开孔设计建模效率低下的问题,基于Smart 3D二次开发框架,通过研究参数化设计方法,建立一种基于Smart3D二次开发的结构开孔参数化设计方法。在Microsoft Visual Studio集成开发环境下,基于Net FrameWork框架,运用vb.net语言进行船体结构开孔参数化建模工具的二次开发。在此基础上,以某7000 TEU箱船Smart 3D模型为应用实例,借助开发的工具进行实例验证,验证表明,该工具可实现多船体肋位上结构开孔的批量建模功能,与传统开孔技术相比,可进一步提升开孔设计建模效率,增加建模的准确性和规范性。

Cellular interplay to 3D in vitro microphysiological disease model:cell patterning microbiota-gut-brain axis

The microbiota-gut-brain axis(MGBA)has emerged as a key prospect in the bidirectional communication between two major organ systems:the brain and the gut.Homeostasis between the two organ systems allows the body to function without disease,whereas dysbiosis has long-standing evidence of etiopathological conditions.The most common communication paths are the microbial release of metabolites,soluble neurotransmitters,and immune cells.However,each pathway is intertwined with a complex one.With the emergence of in vitro models and the popularity of three-dimensional(3D)cultures and Transwells,engineering has become easier for the scientific understanding of neurodegenerative diseases.This paper briefly retraces the possible communication pathways between the gut microbiome and the brain.It further elaborates on three major diseases:autism spectrum disorder,Parkinson’s disease,and Alzheimer’s disease,which are prevalent in children and the elderly.These diseases also decrease patients’quality of life.Hence,understanding them more deeply with respect to current advances in in vitro modeling is crucial for understanding the diseases.Remodeling of MGBA in the laboratory uses many molecular technologies and biomaterial advances.Spheroids and organoids provide a more realistic picture of the cell and tissue structure than monolayers.Combining them with the Transwell system offers the advantage of compartmentalizing the two systems(apical and basal)while allowing physical and chemical cues between them.Cutting-edge technologies,such as bioprinting and microfluidic chips,might be the future of in vitro modeling,as they provide dynamicity.

Geostatistical seismic inversion and 3D modelling of metric flow units,porosity and permeability in Brazilian presalt reservoir

Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.

A Web-Based Approach for the Efficient Management of Massive Multi-source 3D Models

Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.

3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Review of Artificial Intelligence for Oil and Gas Exploration: Convolutional Neural Network Approaches and the U-Net 3D Model

Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Our review traces the evolution of CNN, emphasizing the adaptation and capabilities of the U-Net 3D model in automating seismic fault delineation with unprecedented accuracy. We find: 1) The transition from basic neural networks to sophisticated CNN has enabled remarkable advancements in image recognition, which are directly applicable to analyzing seismic data. The U-Net 3D model, with its innovative architecture, exemplifies this progress by providing a method for detailed and accurate fault detection with reduced manual interpretation bias. 2) The U-Net 3D model has demonstrated its superiority over traditional fault identification methods in several key areas: it has enhanced interpretation accuracy, increased operational efficiency, and reduced the subjectivity of manual methods. 3) Despite these achievements, challenges such as the need for effective data preprocessing, acquisition of high-quality annotated datasets, and achieving model generalization across different geological conditions remain. Future research should therefore focus on developing more complex network architectures and innovative training strategies to refine fault identification performance further. Our findings confirm the transformative potential of deep learning, particularly CNN like the U-Net 3D model, in geosciences, advocating for its broader integration to revolutionize geological exploration and seismic analysis.

A review of road 3D modeling based on light detection and ranging point clouds

Increasing development of accurate and efficient road three-dimensional(3D)modeling presents great opportunities to improve the data exchange and integration of building information modeling(BIM)models.3D modeling of road scenes is crucial for reference in asset management,construction,and maintenance.Light detection and ranging(Li DAR)technology is increasingly employed to generate high-quality point clouds for road inventory.In this paper,we specifically investigate the use of Li DAR data for road 3D modeling.The purpose of this review is to provide references about the existing work on the road 3D modeling based on Li DAR point clouds,critically discuss them,and provide challenges for further study.Besides,we introduce modeling standards for roads and discuss the components,types,and distinctions of various Li DAR measurement systems.Then,we review state-of-the-art methods and provide a detailed examination of road segmentation and feature extraction.Furthermore,we systematically introduce point cloud-based 3D modeling methods,namely,parametric modeling and surface reconstruction.Parameters and rules are used to define model components based on geometric and non-geometric information,whereas surface modeling is conducted through individual faces within its geometry.Finally,we discuss and summarize future research directions in this field.This review can assist researchers in enhancing existing approaches and developing new techniques for road modeling based on Li DAR point clouds.

Mesh representation matters:investigating the influence of different mesh features on perceptual and spatial fidelity of deep 3D morphable models

Background Deep 3D morphable models(deep 3DMMs)play an essential role in computer vision.They are used in facial synthesis,compression,reconstruction and animation,avatar creation,virtual try-on,facial recognition systems and medical imaging.These applications require high spatial and perceptual quality of synthesised meshes.Despite their significance,these models have not been compared with different mesh representations and evaluated jointly with point-wise distance and perceptual metrics.Methods We compare the influence of different mesh representation features to various deep 3DMMs on spatial and perceptual fidelity of the reconstructed meshes.This paper proves the hypothesis that building deep 3DMMs from meshes represented with global representations leads to lower spatial reconstruction error measured with L_(1) and L_(2) norm metrics and underperforms on perceptual metrics.In contrast,using differential mesh representations which describe differential surface properties yields lower perceptual FMPD and DAME and higher spatial fidelity error.The influence of mesh feature normalisation and standardisation is also compared and analysed from perceptual and spatial fidelity perspectives.Results The results presented in this paper provide guidance in selecting mesh representations to build deep 3DMMs accordingly to spatial and perceptual quality objectives and propose combinations of mesh representations and deep 3DMMs which improve either perceptual or spatial fidelity of existing methods.

UAV-based transient electromagnetic 3D forward modeling and inversion and analysis of exploration capability

Unmanned aerial vehicle transient electromagnetic(UAV-TEM)is a novel airborne exploration method that offers advantages such as low cost,simple operation,high exploration efficiency and suitability for near-surface exploration in complex terrain areas.To improve the accuracy of data interpretation in this method,the authors conducted a systematic three-dimensional(3D)forward modeling and inversion of the UAV-TEM.This study utilized the finite element method based on unstructured tetrahedral elements and employed the second-order backward Euler method for time discretization.This allowed for accurate 3D modeling and accounted for the effects of complex terrain.Based on these,the influence characteristics of flight altitudes and the sizes,burial depths,and resistivities of anomalies are compared and analyzed to explore the UAV-TEM systems’exploration capability.Lastly,four typical geoelectrical models of landslides are designed,and the inversion method based on the Gauss-Newton optimization method is used to image the landslide models and analyze the imaging effect of the UAV-TEM method on landslide geohazards.Numerical results showed that UAV-TEM could have better exploration resolution and fine imaging of nearsurface structures,providing important technical support for monitoring,early warning,and preventing landslides and other geological hazards.

3D time-domain forward modeling of airborne transient electromagnetism considering superparamagnetic effect

The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field.This phenomenon manifests in transient electromagnetic data primarily as a deceleration in the attenuation rate of late-stage signals,a characteristic difficult to discern directly from airborne transient electromagnetic signals,consequently leading to significant misinterpretations of subterranean electrical structures.This study embarks on 3D forward modeling of airborne electromagnetic responses in the frequency domain,accounting for the superparamagnetic effect,utilizing an unstructured finite element method.Superparamagnetic responses in the time domain were obtained through frequency-time conversion.This investigation explores the influence of various parameters-such as magnetic susceptibility,time constants,and flight altitude-on the superparamagnetic effect by examining the response characteristics of typical targets.Findings indicate that in its late stages,the superparamagnetic effect can induce a relative anomaly of up to 300%.There is a positive correlation between magnetic susceptibility and the strength of the superparamagnetic effect.The influence of the time constant's upper and lower limits on the superparamagnetic effect is minimal;however,the range between these limits significantly affects the effect,showing a negative correlation with its intensity.Higher flight altitudes weaken the superparamagnetic signal.The impact is most pronounced when superparamagnetic minerals are shallowly buried,effectively shielding the underlying geology with the characteristics of a good conductivity anomaly,but this effect diminishes with greater depth.The insights from this study provide a theoretical framework for a deeper understanding of the superparamagnetic effect in transient electromagnetic signals and for more accurate interpretations of subterranean geological and electrical structures.

3D打印技术在创伤性骨折中的应用

背景:3D打印技术可根据患者实际病情和治疗需求设计构建模型、手术导板和个性化植入体或固定物,在创伤性骨折修复中展示了巨大的应用前景。目的:综述3D打印技术在创伤性骨折中的应用。方法:检索Web of science、PubMed和中国知网数据库2020-2024年发表的创伤骨科领域3D打印技术应用的相关文献,英文检索词为“traumatic fracture,3D printing technology,digital model,surgical guide”,中文检索词为“创伤性骨折,3D打印技术,数字模型,手术导板”,经筛选和分析,最终纳入60篇文献进行分析。结果与结论:①创伤性骨折是各种致伤因素导致的骨骼连续性中断和完整性破坏的骨折现象,以可靠方案提高复位愈合效果,已成为骨外科相关研究领域亟需解决的热点问题;②3D打印技术是以数字模型数据为基础的,运用粉末状金属或聚合物等可黏合成型材料以立体光刻、沉积建模和光聚合物喷射等形式制造满足需求三维实体的技术,在数字骨科生物医学领域应用广泛;③3D打印技术在疾病诊断、术前规划、重建骨折三维模型、定制骨科植入体、定制固定支具及假肢、手术导板制作和骨缺损修复等方面发挥了显著的优势,可根据患者实际病情和治疗需求设计构建模型、手术导板和个性化植入体或固定物,为创伤性骨折的治疗提供了新的思路。

Contribution to the Full 3D Finite Element Modelling of a Hybrid Stepping Motor with and without Current in the Coils

The paper presents our contribution to the full 3D finite element modelling of a hybrid stepping motor using COMSOL Multiphysics software. This type of four-phase motor has a permanent magnet interposed between the two identical and coaxial half stators. The calculation of the field with or without current in the windings (respectively with or without permanent magnet) is done using a mixed formulation with strong coupling. In addition, the local high saturation of the ferromagnetic material and the radial and axial components of the magnetic flux are taken into account. The results obtained make it possible to clearly observe, as a function of the intensity of the bus current or the remanent induction, the saturation zones, the lines, the orientations and the magnetic flux densities. 3D finite element modelling provide more accurate numerical data on the magnetic field through multiphysics analysis. This analysis considers the actual operating conditions and leads to the design of an optimized machine structure, with or without current in the windings and/or permanent magnet.

Mathematical Wave Functions and 3D Finite Element Modelling of the Electron and Positron

The wave/particle duality of particles in Physics is well known. Particles have properties that uniquely characterize them from one another, such as mass, charge and spin. Charged particles have associated Electric and Magnetic fields. Also, every moving particle has a De Broglie wavelength determined by its mass and velocity. This paper shows that all of these properties of a particle can be derived from a single wave function equation for that particle. Wave functions for the Electron and the Positron are presented and principles are provided that can be used to calculate the wave functions of all the fundamental particles in Physics. Fundamental particles such as electrons and positrons are considered to be point particles in the Standard Model of Physics and are not considered to have a structure. This paper demonstrates that they do indeed have structure and that this structure extends into the space around the particle’s center (in fact, they have infinite extent), but with rapidly diminishing energy density with the distance from that center. The particles are formed from Electromagnetic standing waves, which are stable solutions to the Schrödinger and Classical wave equations. This stable structure therefore accounts for both the wave and particle nature of these particles. In fact, all of their properties such as mass, spin and electric charge, can be accounted for from this structure. These particle properties appear to originate from a single point at the center of the wave function structure, in the same sort of way that the Shell theorem of gravity causes the gravity of a body to appear to all originate from a central point. This paper represents the first two fully characterized fundamental particles, with a complete description of their structure and properties, built up from the underlying Electromagnetic waves that comprise these and all fundamental particles.

3D打印模型特征细节自适应分层优化方法及试验研究

针对3D打印自适应分层技术无法较好地保留模型特征细节的问题,提出3D打印模型特征细节自适应分层优化方法(model details adaptive slice method, MDASM),该方法基于三角面片法向量的自适应分层方法(normal vector of triangular face adaptive slice method, NTASM)来确定不存在模型特征细节的分层厚度。首先,设定角度变化阈值与切平面相邻高度三角面片法向量的角度变化进行比较,识别是否存在垂直尖角特征,并确定垂直尖角特征分层厚度。其次,设定面积变化阈值与切平面封闭轮廓曲线面积进行比较,识别是否存在平行尖角特征,并确定平行尖角特征分层厚度。最后,取3种分层厚度的最小值作为分层厚度。Matlab仿真表明,相较于NTASM,MDASM模型成形精度提高了24.2%。熔融沉积成形(fused deposition modeling, FDM)结果表明,相较于NTASM,MDASM模型成形效率降低了21.8%,表面粗糙度减小了14.57%。仿真和FDM试验研究表明,MDASM在保证模型成形效率的前提下,能够更好地保留模型特征细节,具有更好的模型成形精度和实用性。

基于GIS与Scoops 3D的水动力型滑坡区域稳定性分析

库岸边坡在库水位变动、降雨等水动力因素的作用下易发生水动力型滑坡,进而威胁库区居民生命及财产安全。以某流域HD和DHQ库段为主要研究区段,在对已有滑坡点进行地质调查和遥感解译的基础上,将ArcGIS的空间分析与三维斜坡稳定性分析模型(Scoops 3D)相结合,对研究区段的潜在滑面进行系统的三维搜索及识别,并基于GIS数据与室内试验等确定计算参数,对天然和暴雨两种工况下的区域滑坡稳定性进行评价比较。结果表明:(1)研究区历史滑坡点分布与基础地质环境、岩土体强度指标参数有很强的相关性;(2)天然工况下,非稳定区主要分布在DHQ坝区、迤场、DH坝址、拉巴铁、宝塔河以及甸尾附近;(3)暴雨工况下,非稳定区面积较天然工况有显著的增大,DHQ坝址、营盘镇、甸尾、HD坝址附近有较为密集的分布;(4)暴雨工况下模型计算的非稳定区与历史滑坡点的分布特征基本一致。由此可见,三维斜坡稳定性分析模型可以较为准确模拟不同工况下滑坡稳定性,且易发程度区分明显,稳定性评价结果在一定程度上反映了研究区段的稳定性时空分布。

基于单片机开发板和3D打印的一种多参数呼吸训练装置的研究开发

目的通过野火骄阳32单片机开发板和3D建模及打印技术进行软硬件开发,实现一种多参数呼吸训练装置的专利样机转化。方法利用野火骄阳32单片机开发板开发应用程序,通过单片机开发板实现流量信号和压力信号的输入,舵机阀、涡轮风机、电磁阀的控制输出与上位机的数据通信等功能;样机非标零部件通过3D建模及打印技术完成制造,并将单片机开发板、标准零部件和非标零部件进行组合以完成样机开发。结果野火骄阳32单片机开发实现了传感器数据采集、运动部件的控制输出、上位机软件的数据上传和接收;3D建模及打印技术实现了非标零部件及机器外壳的制作,以低成本成功制作出样机;样机通过质控仪检测,流量值误差范围为±15%,气道压力值误差范围为±[2%FS(满量程)+4%×实际读数],样机参数精度满足JJF1234-2018《呼吸机校准规范》要求。结论野火骄阳32单片机开发板和3D建模及打印技术的应用,以低成本实现了样机制作,能够为专利的商业转化提供重要参考,为医工专利转化提供了一种新的思路。

自适应组合滤波算法在3D假肢模型中的应用

针对经典统计滤波算法无法自适应选取参数以及传统双边滤波算法难以兼顾保特征和光顺性的问题,提出一种自适应组合滤波算法。首先引入基于局部点云体积的自适应标准差倍数以灵活滤除假肢点云大尺度噪声;在滤除大尺度噪声的基础上,引入一种新的协方差矩阵加权方式,提高估计点云法向的准确性,并通过法向夹角变化程度的均值对特征权重因子进行改进,增强双边滤波因子的保特征性,旨在光顺三维假肢模型小尺度噪声。与单独使用统计滤波、双边滤波相比,所提算法在3个假肢模型的最大误差E_(max)至少降低了5%;平均误差E_(ave)至少降低了6.9%。仿真结果表明,该改进算法在有效剔除假肢模型大尺度噪声的同时又避免了过光顺和去噪不彻底,可以较好地保持模型中的几何特征。

3D打印模型结合翻转课堂在脊柱外科微创培训中的应用

目的探讨翻转课堂联合3D打印模型教学在脊柱外科微创培训中的应用效果。方法选择2020年5月—2022年5月在浙江大学医学院附属第二医院脊柱外科微创中心进修的42名学员为研究对象,随机分为研究组和对照组,研究组21名进修学员采用翻转课堂联合3D打印模型教学,对照组21名进修学员采用单纯翻转课堂方法进行授课讲解。2组学员分别进行了出科考试测验和满意度问卷调查。结果2组进修学员培训前检测成绩、微创理论知识成绩,差异无统计学意义(P>0.05)。研究组学员在培训结束后其出科脊柱微创临床知识成绩及微创基本技能操作、微创手术技巧提高和总体满意度均高于对照组,差异均有统计学意义(P<0.05)。结论应用3D打印模型教学结合翻转课堂可明显提高脊柱外科进修学员的学习质量和总体满意度,提升脊柱微创培训的效果。为脊柱外科微创培训的一种新型教学模式。

基于3D打印模型的案例教学方法在气管插管教学中的应用

目的探讨基于3D打印模型的案例教学方法(case-based learning,CBL)在气管插管教学中的应用效果。方法采用整群抽样方法,选取2019年1月—2022年1月在浙江省丽水市人民医院进行临床实习的温州医科大学2015级、2016级、2017级五年制临床医学专业80名学生为研究对象。采用随机数字表法,将80名学生分为试验组和对照组,每组40名学生。试验组学生采用基于3D打印模型的案例教学方法,对照组学生采用传统教学方法。教学结束后,通过理论知识、操作技能考核成绩和问卷调查结果,比较两组学生各自教学方法的实施效果。两组学生按照不同级次分批进行教学和考核。结果理论知识考核结果显示,试验组学生成绩[(45.23±2.66)分]优于对照组学生[(40.94±3.41)分],其差异具有统计学意义(P<0.05);操作技能考核结果显示,试验组学生成绩[(48.26±2.33)分]优于对照组学生[(42.89±3.25)分],其差异具有统计学意义(P<0.05)。问卷调查结果显示,在学习兴趣、学习效率、主动的互动、知识掌握程度、总体教学满意度5个方面,试验组学生的评分均高于对照组学生,其差异均具有统计学意义(均P<0.05)。结论基于3D打印模型的案例教学方法,与传统教学方法相比,可以为学生带来全新的立体视觉感受和模拟体验,有助于提高学生的学习兴趣和效率,有助于学生将理论知识和操作技能掌握得更加牢固,教学满意度更高,值得进一步深入研究与推广应用。

3D打印技术在舰船管系三维建模设计中的应用

为提升复杂结构舰船管系的设计灵活性,研究3D打印技术在舰船管系三维建模设计中的应用。利用CAD软件建立舰船管系的二维模型,依据舰船管系三角面片的交线段,确定舰船管系的点、线、面关系,将其转换为舰船管系三维模型。将舰船管系三维模型,导入切片软件中,利用切片引擎运行3D打印切片引擎增强处理算法,切片处理舰船管系三维模型,输出舰船管系三维模型的Gcode代码文件。将Gcode代码导入3D打印机,采用Z字填充法填充舰船管系3D打印材料,实现舰船管系模型的3D打印。实验结果表明,该方法可以精准打印舰船管系三维模型,打印结果的尺寸偏差小,提升了舰船管系设计的灵活性。