An official website of the United States government
Geometry projection-based topology optimization has attracted a great deal of attention because it enables the design of structures consisting of a combination of geometric primitives and simplifies the integration with computer-aided design (CAD) systems. While the approach has undergone substantial development under the assumption of linear theory, it remains to be developed for non-linear hyperelastic problems. In this study, a geometrically non-linear explicit topology optimization approach is proposed in the framework of the geometry projection method. The energy transition strategy is adopted to mitigate excessive distortion in low-stiffness regions that might cause the equilibrium iterations to diverge. A neo-Hookean hyperelastic strain energy potential is used to model the material behavior. Design sensitivities of the functions passed to the gradient-based optimizer are detailed and verified. The proposed method is used to solve benchmark problems for which the output displacement in a compliant mechanism is maximized and the structural compliance is minimized.
more »
« less
Computer-Aided Design-Based Topology Optimization System With Dynamic Feature Shape and Modeling History Evolution
Abstract Conventional topology optimization presentations generally highlight the numerical and optimization details established on the specially customized discrete geometric modeling system, which is incompatible with the existing computer-aided design (CAD)/computer-aided engineering (CAE) systems. Therefore, tedious preprocessing and postprocessing are required to improve the editability and manufacturability, which are both time consuming and labor intensive. Hence, to address this challenging issue, a novel CAD-based topology optimization system is developed in this work. The following points are highlighted: (i) interoperability issue between CAD and topology optimization was addressed by using macro files to communicate the feature and modeling history information; then, (ii) structural shape and topology optimization is performed based on a B-spline-based approach, which inherits the original spline information from the upstream CAD model and of course, can return spline-based geometric information for optimized CAD model generation, and the last but the most important point to mention is that, (iii) modeling history was incorporated into the optimization process and dynamic modeling history change is enabled based on the optimality criteria. This final point is significant because history-based CAD modeling is still a main-stream approach, especially given the excellent postmodeling editability and design intent capture.
more »
« less
- Award ID(s):
- 1634261
- PAR ID:
- 10208239
- Date Published:
- Journal Name:
- Journal of Mechanical Design
- Volume:
- 142
- Issue:
- 7
- ISSN:
- 1050-0472
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
3D Computer-Aided Design (CAD) modeling is ubiquitous in mechanical engineering and design. Modern CAD models are programs that produce geometry and can be used to implement high-level geometric changes by modifying input parameters. While there has been a surge of recent interest in program-based tooling for the CAD domain, one fundamental problem remains unsolved. CAD programs pass geometric arguments to operations using references, which are queries that select elements from the constructed geometry according to programmer intent. The challenge is designing reference semantics that can express programmer intent across all geometric topologies achievable with model parameters, including topologies where the desired elements are not present. In current systems, both users and automated tools may create invalid models when parameters are changed, as references to geometric elements are lost or silently and arbitrarily switched. While existing CAD systems use heuristics to attempt to infer user intent in cases of this undefined behavior, this best-effort solution is not suitable for constructing automated tools to edit and optimize CAD programs. We analyze the failure modes of existing referencing schemes and formalize a set of criteria on which to evaluate solutions to the CAD referencing problem. In turn, we propose a domain-specific language that exposes references as a first-class language construct, using user-authored queries to introspect element history and define references safely over all paths. We give a semantics for fine-grained element lineage that can subsequently be queried; and show that our language meets the desired properties. Finally, we provide an implementation of a lineage-based referencing system in a 2.5D CAD kernel, demonstrating realistic referencing scenarios and illustrating how our system safely represents models that cause reference breakage in existing CAD systems.more » « less
-
Computational modeling and simulation of real-world problems, e.g., various applications in the automotive, aerospace, and biomedical industries, often involve geometric objects which are bounded by curved surfaces. The geometric modeling of such objects can be performed via high-order meshes. Such a mesh, when paired with a high-order partial differential equation (PDE) solver, can realize more accurate solution results with a decreased number of mesh elements (in comparison to a low-order mesh). There are several types of high-order mesh generation approaches, such as direct methods, a posteriori methods, and isogeometric analysis (IGA)-based spline modeling approaches. In this paper, we propose a direct, high-order, curvilinear tetrahedral mesh generation method using an advancing front technique. After generating the mesh, we apply mesh optimization to improve the quality and to take advantage of the degrees of freedom available in the initially straight-sided quadratic elements. Our method aims to generate high-quality tetrahedral mesh elements from various types of boundary representations including the cases where no computer-aided design files are available. Such a method is essential, for example, for generating meshes for various biomedical models where the boundary representation is obtained from medical images instead of CAD files. We present several numerical examples of second-order tetrahedral meshes generated using our method based on input triangular surface meshes.more » « less
-
Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key characteristic of parametric CAD is that design intent is encoded not only via geometric primitives, but also by parameterized constraints between the elements. This relational specification can be viewed as the construction of a constraint program, allowing edits to coherently propagate to other parts of the design. Machine learning offers the intriguing possibility of accelerating the de- sign process via generative modeling of these structures, enabling new tools such as autocompletion, constraint inference, and conditional synthesis. In this work, we present such an approach to generative modeling of parametric CAD sketches, which constitute the basic computational building blocks of modern mechanical design. Our model, trained on real-world designs from the SketchGraphs dataset, autoregressively synthesizes sketches as sequences of primitives, with initial coordinates, and constraints that reference back to the sampled primitives. As samples from the model match the constraint graph representation used in standard CAD software, they may be directly imported, solved, and edited according to down- stream design tasks. In addition, we condition the model on various contexts, including partial sketches (primers) and images of hand-drawn sketches. Evaluation of the proposed approach demonstrates its ability to synthesize realistic CAD sketches and its potential to aid the mechanical design workflow.more » « less
-
Physics-based simulations are essential for designing autonomous construction equipment, but preparing models is time-consuming, requiring the integration of mechanical and geometric data. Current automatic modeling methods for modular robots are inadequate for construction equipment. This paper explores automating the modeling process by integrating mechanical data into 3D computer-aided design (CAD) models. A template library is developed with hierarchy and joint templates specific for equipment. During model generation, appropriate templates are selected based on the equipment type. Unspecified joint template data is extracted from technical specifications using a large language model (LLM). The 3D CAD model is then converted into a Universal Scene Description (USD) model. Users can adjust the part names and hierarchy within the USD model to align with the hierarchy template, and joint data is automatically integrated, resulting in a simulation-ready model. This method reduces modeling time by over 87 % compared to manual methods, while maintaining accuracy.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1115/1.4045301
