Article
Engineering, Electrical & Electronic
Luo Fang, Qiang Liu, Ding Zhang
Summary: This paper proposes a lightweight approach for common CAD assembly models of Digital Twins, which simplifies CAD models by adding constraints of discrete folded corner plane characteristics and using penalty functions, as well as utilizing a segmentation algorithm to identify and remove interfaces. Experimental results show that the proposed method effectively reduces geometric errors, improves frame rates, and preserves the integrity of geometric features and triangular facets.
Article
Multidisciplinary Sciences
Mladen Buric, Tina Bosner, Stanko Skec
Summary: The most common way to retrieve symmetry information in 3D CAD models is through visual recognition by engineers. However, computer-aided symmetry detection is employed to overcome the limitations of human recognition. This research introduces a symmetry detection framework for 3D CAD models with boundary representation, addressing exact and partial axi- and reflectional symmetry.
Article
Computer Science, Software Engineering
Chiara Romanengo, Andrea Raffo, Silvia Biasotti, Bianca Falcidieno
Summary: The paper addresses the problem of recognizing simple and complex geometric primitives in point clouds obtained from scans of mechanical CAD objects. It proposes a robust solution based on the Hough transform that can handle noise, outliers, and missing parts. The method can also extract geometric descriptors and reduce oversegmentation. Experimental results demonstrate the method's robustness and competitiveness.
COMPUTER-AIDED DESIGN
(2023)
Article
Engineering, Mechanical
Bohan Wang, Bo Chen, Kaixin Yu, Lijun Xie, Jianjun Chen
Summary: This paper proposes an ultralight geometry processing library to ensure the refined surface in applications like parallel mesh refinement accurately respects the original CAD model. The library utilizes simplified surface boundary representation and radial edge structure to depict the geometry model and surface mesh, and records their connections. With these data structures and algorithms, precise matching between the geometry model and surface mesh can be achieved.
ADVANCES IN AERODYNAMICS
(2022)
Article
Engineering, Manufacturing
Dheeraj Peddireddy, Xingyu Fu, Anirudh Shankar, Haobo Wang, Byung Gun Joung, Vaneet Aggarwal, John W. Sutherland, Martin Byung-Guk Jun
Summary: The manufacturing industry still relies on human labor and knowledge for Machining Process Identification (MPI), crucial for sourcing qualified suppliers and achieving efficient automated industrial logistic systems. This paper presents a novel two-step MPI system based on 3D Convolutional Neural Networks and transfer learning, demonstrating high accuracy in identifying manufacturability and manufacturing processes.
JOURNAL OF MANUFACTURING PROCESSES
(2021)
Article
Engineering, Biomedical
Jiting Yang, Haiyan Li, Jun Wu, Liang Sun, Dan Xu, Yuanyuan Wang, Yufeng Zhang, Yue Chen, Lin Chen
Summary: The study found that ABUS had better imaging results for implanted LW meshes, and the contribution of pore texture features in the 3D coronal plane was more valuable.
BIOMEDICAL ENGINEERING ONLINE
(2021)
Article
Computer Science, Software Engineering
Donghun Ryou, Kim Youwang, Tae-Hyun Oh
Summary: We propose a rank statistic adaptive multi-stage pruning method for lightweight neural network discovery in 3D human mesh recovery. We observe prominent low-rank patterns in some feature maps regardless of input human images. Our method, rank statistic adaptive multi-stage pruning, can prune more filters while recovering mesh reconstruction accuracy. Compared to the competing L1 filter pruning method, our method achieves comparable accuracy with significant parameter and FLOPs savings.
Article
Engineering, Electrical & Electronic
Alberto Adrian Toledano-Garcia, Hugo Rene Perez-Cabrera, Danya Ortega-Cabrera, David Navarro-Duran, Erick Mauricio Perez-Hernandez
Summary: In Industry 4.0, robots play a crucial role, especially collaborative robots that work alongside humans. This paper focuses on the applications of welding and gluing in manufacturing processes. It highlights the need for specific speed, efficiency, and accuracy that robots can provide. However, programming the path for these tasks can be time-consuming. The paper proposes an open-source software solution to automatically generate trajectories for welding and gluing applications, providing a more affordable option compared to specialized software licenses.
Article
Chemistry, Multidisciplinary
Daria Vlah, Vanja Cok, Uros Urbas
Summary: The study aims to explore the usefulness of existing VR 3D modelling tools for mechanical engineering, finding that VR tools provide a fast way to create complex part geometries but also have certain drawbacks.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Software Engineering
Wanquan Feng, Juyong Zhang, Yuanfeng Zhou, Shiqing Xin
Summary: This article addresses the problem of mesh super-resolution and proposes a deep neural network called GDR-Net to solve it. Experimental results demonstrate that GDR-Net outperforms previous methods for recovering geometric details.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Environmental Sciences
Woonhyung Jung, Janghun Hyeon, Nakju Doh
Summary: This paper proposes a robust cuboid modeling method for point clouds under high noise and occlusion conditions. The method estimates the parameters of a cuboid using soft constraints, which avoids over-constraint. The experimental results demonstrate that the proposed method outperforms previous modeling methods in terms of robustness.
Article
Materials Science, Multidisciplinary
Guoqing Zhang, Rongrui Feng, Junxin Li, Yongsheng Zhou, Xiaoyu Zhou, Anmin Wang
Summary: Nowadays, the redesign of new shock-absorbing load-bearing parts has gained more attention due to energy pressure, environmental protection, and people's pursuit of high-performance travel tools. The development of 3D printing technology allows for the design of such high-performance parts. Through software analysis and optimization, followed by direct manufacturing using 3D printers, the lightweight design of the parts achieves reduced weight and improved shock absorption performance. The 3D printed parts have advantages such as a bright surface, low roughness, and good molding effect, laying a solid foundation for mass production of high-performance shock-absorbing load-bearing parts.
Article
Dentistry, Oral Surgery & Medicine
Hans-Joachim Nickenig, Maximilian Riekert, Matthias Zirk, Max-Philipp Lentzen, Joachim E. Zoller, Matthias Kreppel
Summary: This study presents an optimized method for using screw-retained restoration in situations with unfavorable buccal bone concavities. Customized bone regeneration with titanium meshes is shown to be reliable in terms of healing and extent of augmentation. However, further research is needed to evaluate the long-term effectiveness of the presented protocol.
CLINICAL ORAL INVESTIGATIONS
(2022)
Article
Computer Science, Information Systems
Lida Asgharian, Hossein Ebrahimnezhad
Summary: This paper proposes an efficient feature preserving method to simplify CAD models by extracting sharp edges and decomposing the original mesh model into low varying curvature sub-regions which are representable through their boundary curves. Experimental results demonstrate that the proposed method can efficiently simplify a CAD model with complex geometric features and complicated shapes.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
George Fahim, Khalid Amin, Sameh Zarif
Summary: The study proposes a mesh-based single-view object reconstruction model enhanced with additional implicit surface learning, leading to lower surface-to-surface error compared to using an explicit branch alone. The hybrid method outperforms state-of-the-art mesh reconstruction methods and compares favorably to prior work incorporating a hybrid approach. Despite being trained with synthetic images, it generalizes well to real-world images.
IMAGE AND VISION COMPUTING
(2022)
Article
Construction & Building Technology
Cong Hong Phong Nguyen, Young Choi
AUTOMATION IN CONSTRUCTION
(2018)
Article
Green & Sustainable Science & Technology
Cong Hong Phong Nguyen, Youngdoo Kim, Young Choi
Summary: Lattice structures are widely used for designing lightweight and multifunctional parts. With the advancement of additive manufacturing, the design of lattice structures has progressed, particularly for functionally graded lattice structures. This study introduces a novel method for designing additively manufactured functionally graded lattice structures considering anisotropic properties induced by AM processes. Validation using three-point bending-beam design problem proves the practicality and validity of the proposed method.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Cong Hong Phong Nguyen, Youngdoo Kim, Quang Thang Do, Young Choi
Summary: The study proposes an implicit-based computer-aided design framework tailored for additively manufactured functionally graded cellular structures (AM-FGCSs), effectively aiding in both single- and multiscale structural optimization. The implicit-based modeling provides a reliable geometric representation, efficiently assisting in computation tasks such as visualization, validation, and process planning for fabrication. Two case studies demonstrate the framework's effectiveness in structural design and process planning for fabrication and engineering analysis.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Cong Hong Phong Nguyen, Young Choi
Summary: The emergence of additive manufacturing has enabled the design of complex structures such as functionally graded cellular structures. Level-set-based methods have gained attention as an efficient design tool for structures fabricated with AM. A multiscale structural optimization method utilizing level-set descriptions is proposed to replace topology optimization for microscale structural optimization with reduced computation cost and comparable results.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Manufacturing
Quang Thang Do, Cong Hong Phong Nguyen, Young Choi
Summary: A method for cellular structure design based on homogenization and Voronoi tessellation is proposed, improving structural stability and robustness while reducing computation costs.
ADDITIVE MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Phong Cong Hong Nguyen, Youngdoo Kim, Young Choi
Summary: In this study, a stress-based structural optimization method is proposed for the design of lightweight components filled with functionally graded cellular structures fabricated by selective laser melting. The experimental results show that components filled with functionally graded cellular structures can withstand a higher load.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Youngdoo Kim, Phong C. H. Nguyen, Hoon Kim, Hae-Jin Choi, Young Choi
Summary: Multi-morphology cellular structures have gained attention due to their ability to adjust geometric and mechanical properties. This study characterizes the deformation of these structures and proposes a deformation prediction method. The effects of design variables and neighboring unit cells on deformation were measured, and a prediction model considering neighboring effects was developed. Numerical studies validated the method, showing good agreement between optimized cellular structures and desired deformation.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2023)
Review
Chemistry, Applied
Joseph B. Choi, Phong C. H. Nguyen, Oishik Sen, H. S. Udaykumar, Stephen Baek
Summary: Artificial intelligence is widely used in materials design to analyze trends and patterns, optimize material designs, and improve performance. This paper reviews AI-driven materials-by-design methods and suggests future research directions.
PROPELLANTS EXPLOSIVES PYROTECHNICS
(2023)
Article
Chemistry, Applied
Phong C. H. Nguyen, Yen-Thi Nguyen, Pradeep K. Seshadri, Joseph B. Choi, H. S. Udaykumar, Stephen Baek
Summary: This study proposes an efficient and accurate multiscale framework for predicting the shock-to-detonation transition (SDT) in heterogeneous energetic materials (EM). By using deep learning to model the mesoscale energy localization of shock-initiated EM microstructures, the complex thermo-mechanics of EM during SDT can be accurately captured. The proposed approach reduces computation cost and provides improved representations of the sub-grid physics.
PROPELLANTS EXPLOSIVES PYROTECHNICS
(2023)
Article
Multidisciplinary Sciences
Phong C. H. Nguyen, Yen-Thi Nguyen, Joseph B. Choi, Pradeep K. Seshadri, H. S. Udaykumar, Stephen S. Baek
Summary: The thermo-mechanical response of shock-initiated energetic materials can be engineered by manipulating their microstructures. However, current design practices are limited due to the need for a large number of simulations. This study introduces a physics-aware recurrent convolutional neural network that can accurately predict the thermo-mechanical response of shocked energetic materials with fewer computations.
