Computer-Aided Design最新文献

The digitalization of manufacturing processes and recent trends, such as the Industrial Metaverse, are continuously increasing in adoption in various critical industries, resulting in a surging demand for 3D CAD models and their exchange. Following this, it becomes necessary to protect the intellectual property of content designers in increasingly decentralized production environments where 3D assets are repeatedly shared online within the ecosystem. CAD models can be protected by traditional security methods such as watermarking, which embeds additional information into the file. Nevertheless, malicious actors may find ways to remove the information from a file. To authenticate and protect 3D models without relying on additional information, we propose a robust 3D perceptual hash generated based on the prevalent geometric features. Furthermore, our geometry-based approach generates compact and tamper-resistant fingerprints for a 3D model by projecting multiple spherical sliced layers of intersection points into cluster distances. The resulting hash links the 3D model to an owner, supporting the detection of counterfeits. The approach was benchmarked for similarity search and evaluated against established state-of-the-art shape retrieval techniques. The results show promising resistance against arbitrary transformations and manipulations, with our approach detecting 25.6% more malicious tampering attacks than the baseline.

Least-squares progressive iterative approximation (LSPIA) is an effective tool for fitting data points with curves and surfaces in CAD/CAM, due to its intuitive geometric meaning and its suitability for handling mass data. However, the classic LSPIA method for blending curves and surfaces has a slow convergence rate and takes a long CPU execution time, since the spectral radius of its iteration matrix is near to 1. To achieve a reduction in CPU execution time, this paper presents a distributed least-squares progressive iterative approximation (DLSPIA) method by dividing the collocation matrix into some blocks, which are called processors. The proposed method distributes the computation of the control points progressively in a way that each processor is responsible for a block of the whole point set. Combining the information obtained from the previous processors with that of the current processor, the DLSPIA method can progressively and quickly approximate the least-squares fitting result of the original data set block by block via distributed computation. And the algorithm converges within a finite number of iterations. Furthermore, the iterative formulae for blending surface fitting are expressed in matrix form, which can avoid the computation of the matrix Kronecker product to reduce the CPU execution time. Several numerical examples are presented to demonstrate the superiority of the proposed method compared with the previous methods.

In this study, we present a novel method for modeling the canopy surface of an umbrella. Our approach involves representing the area between the ribs on the canopy as a trimmed bilinear patch. Furthermore, we conduct an in-depth exploration of various differential geometric properties of the umbrella surface. We introduce a method for unfolding the canopy surface onto a plane, which serves as a valuable technique for fabricating a cardboard template to accurately cut canopy fabrics. To validate the effectiveness of our geometric modeling method, we apply it to several umbrella models, showcasing its practical application and benefits.

Methods that use neural networks for synthesizing 3D shapes in the form of a part-based representation have been introduced over the last few years. These methods represent shapes as a graph or hierarchy of parts and enable a variety of applications such as shape sampling and reconstruction. However, current methods do not allow easily regenerating individual shape parts according to user preferences. In this paper, we investigate techniques that allow the user to generate multiple, diverse suggestions for individual parts. Specifically, we experiment with multimodal deep generative models that allow sampling diverse suggestions for shape parts and focus on models which have not been considered in previous work on shape synthesis. To provide a comparative study of these techniques, we introduce a method for synthesizing 3D shapes in a part-based representation and evaluate all the part suggestion techniques within this synthesis method. In our method, which is inspired by previous work, shapes are represented as a set of parts in the form of implicit functions which are then positioned in space to form the final shape. Synthesis in this representation is enabled by a neural network architecture based on an implicit decoder and a spatial transformer. We compare the various multimodal generative models by evaluating their performance in generating part suggestions. Our contribution is to show with qualitative and quantitative evaluations which of the new techniques for multimodal part generation perform the best and that a synthesis method based on the top-performing techniques allows the user to more finely control the parts that are generated in the 3D shapes while maintaining high shape fidelity when reconstructing shapes.

Cardiac simulators can assist in the diagnosis of heart disease and enhance human understanding of this leading cause of mortality. The coupling of multiphysics, such as electrophysiology and active–passive mechanics, in the simulation of the heart poses challenges in utilizing existing methodologies for real-time applications. The low efficiency of physically-based simulation is mostly caused by the need for electrical-stress conduction to use tiny time steps in order to prevent numerical instability. Additionally, the mechanical simulation experiences sluggish convergence when dealing with significant deformation and stiffness, and there are also concerns regarding volume inversion. We provide a coupling physics model that transforms the active–passive dynamics into multiphysics solving constraints, aiming at boosting the real-time efficiency of the cardiac electromechanical simulation. The multiphysics processes are initially divided into two levels: cell-level electrical stimulation and organ-level electrical-stress diffusion/conduction. This separation is achieved by employing operator splitting in combination with the quasi-steady-state method, which simplifies the system equations. Next, utilizing spatial discretization, we employ the matrix-free conjugate gradient approach to solve the electromechanical model, therefore improving the efficiency of the simulation. The experimental results illustrate that our simulation model is capable of replicating intricate cardiac physiological phenomena, including 3D spiral waves and rhythmic contractions. Moreover, our model achieves a significant advancement in real-time computation while maintaining a comparable level of accuracy to current methods. This improvement is advantageous for interactive medical applications.

We present a learning based framework for mesh quality improvement on unstructured triangular and quadrilateral meshes. Our model learns to improve mesh quality according to a prescribed objective function purely via self-play reinforcement learning with no prior heuristics. The actions performed on the mesh are standard local and global element operations. The goal is to minimize the deviation of the node degrees from their ideal values, which in the case of interior vertices leads to a minimization of irregular nodes.

Owing to the rapid development in additive manufacturing, the potential to fabricate intricate structures has become a reality, emphasizing the importance of designing structures conducive to additive manufacturing processes. A crucial consideration is the ability to design structures requiring no additional support during manufacturing. This paper employs implicit B-spline representations for self-supporting structure design by integrating a topology optimization model with self-supporting constraints derived analytically from the implicit representation. This analytical derivation for detecting overhang regions enables accurate and efficient calculation of constraints, outperforming other B-spline-based methods. Compared to the traditional voxel-based methods, the implicit B-spline representation significantly expedites the optimization process by reducing the number of design variables. Additionally, several acceleration techniques are implemented to enhance the efficiency of our method, allowing simulations of 3D models with millions of finite elements to be completed within one and half an hour, excelling other B-spline-based methods and voxel-based methods. Various numerical experiments validate its excellent performance, confirming the effectiveness and efficiency of the proposed algorithm.

Shell structures refer to structural elements that derive strength and load-bearing capacity from their thin and curved geometry. In practical applications, shell structures are commonly composed of multiple patches to represent intricate and diverse architectural configurations faithfully. Nevertheless, the design of multi-patch shell structures holds considerable promise. However, most of the previous work is devoted to the numerical analysis of multi-patch shell structures without further optimization design. The work proposes an inverse design framework, specifically focusing on multi-patch configurations based on Reissner–Mindlin theory. First, reparameterization and global refinement operations are employed on the provided multi-patch shell structures. Renumbering the indices of control points with shared degrees of freedom at the interface naturally ensures $C^0$-continuity between patches. Subsequently, this study investigates the amalgamation of Isogeometric Analysis (IGA) and the Solid Isotropic Material with Penalization (SIMP) method for topology optimization of shell structures. The proposed approach is validated through numerical examples, emphasizing its capacity to enhance multi-patch shell structure design, showcasing robustness and efficiency.

Designing the layout for complex electromechanical products involves the challenging task of automatically laying out cables. This challenge is particularly pronounced in the case of branch cables, which are more intricate due to their multiple connection terminals and branches. This paper presents a polynomial-time wiring algorithm based on dynamic programming to determine branching point locations in the layout design of cables, given the electrical definition of the wire harness. The method considers various engineering constraints, including obstacle avoidance, wall adherence, minimum bend radius, and gray areas. To validate our method, we implemented a branch cable auto-layout system through secondary development based on the UG platform. The experimental results indicate the effectiveness of our approach, demonstrating promising performance in terms of time and high-quality layouts. This showcases its potential for practical application in cable layout design for complex electromechanical systems.

The benefits of integrated design using the Model Based System Engineering (MBSE) approach in the design process of mechatronic systems have gradually become apparent. The automatic generation of simulation models and geometric models based on System Modeling Languages (SysML) models enables system engineers to swiftly analyze and simulate system performance, visually depict design outcomes, and expedite the product development process. Due to the current system modeling's lack of model integration and geometric design functions, this paper proposes an integrated design and simulation method for mechatronic systems that can carry out complete model synchronization and verification, rapid geometric solution generation, and visual representation. Furthermore, a corresponding model synchronization integration framework is established. This framework primarily encompasses system de-sign, system simulation, and geometric design, with its model integration method being model transformation and model synchronization. The paper concludes with an example of the design process of a quadruped robot to validate the framework and its supported methods, providing a reference for other system design and integration endeavors.