715 research outputs found

    Mates2Motion: Learning How Mechanical CAD Assemblies Work

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    We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations. We train our model using a large dataset of real-world mechanical assemblies consisting of CAD parts and mates joining them together. We present methods for re-defining these mates to make them better reflect the motion of the assembly, as well as narrowing down the possible axes of motion. We also conduct a user study to create a motion-annotated test set with more reliable labels.Comment: Contains 5 pages, 2 figures. Presented at the ICML 2022 Workshop on Machine Learning in Computational Desig

    Information hiding through variance of the parametric orientation underlying a B-rep face

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    Watermarking technologies have been proposed for many different,types of digital media. However, to this date, no viable watermarking techniques have yet emerged for the high value B-rep (i.e. Boundary Representation) models used in 3D mechanical CAD systems. In this paper, the authors propose a new approach (PO-Watermarking) that subtly changes a model's geometric representation to incorporate a 'transparent' signature. This scheme enables software applications to create fragile, or robust watermarks without changing the size of the file, or shape of the CAD model. Also discussed is the amount of information the proposed method could transparently embed into a B-rep model. The results presented demonstrate the embedding and retrieval of text strings and investigate the robustness of the approach after a variety of transformation and modifications have been carried out on the data

    Geometric reasoning via internet crowdsourcing

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    The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach

    Validation of purdue engineering shape benchmark clusters by crowdsourcing

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    The effective organization of CAD data archives is central to PLM and consequently content based retrieval of 2D drawings and 3D models is often seen as a "holy grail" for the industry. Given this context, it is not surprising that the vision of a "Google for shape", which enables engineers to search databases of 3D models for components similar in shape to a query part, has motivated numerous researchers to investigate algorithms for computing geometric similarity. Measuring the effectiveness of the many approaches proposed has in turn lead to the creation of benchmark datasets against which researchers can compare the performance of their search engines. However to be useful the datasets used to measure the effectiveness of 3D retrieval algorithms must not only define a collection of models, but also provide a canonical specification of their relative similarity. Because the objective of shape retrieval algorithms is (typically) to retrieve groups of objects that humans perceive as "similar" these benchmark similarity relationships have (by definition) to be manually determined through inspection

    Revisiting the design intent concept in the context of mechanical CAD education

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    [EN] Design intent is generally understood simply as a CAD modelÂżs anticipated behavior when altered. However, this representation provides a simplified view of the modelÂżs construction and purpose, which may hinder its general understanding and future reusability. Our vision is that design intent communication may be improved by recognizing the multifaceted nature of design intent, and by instructing users to convey each facet of design intent through the better-fitted CAD resource. This paper reviews the current understanding of design intent and its relationship to design rationale and builds on the idea that communication of design intent conveyed via CAD models can be satisfied at three levels provided that specialized instruction is used to instruct users in selection of the most suitable level for each intent.Otey, J.; Company, P.; Contero, M.; Camba, J. (2018). Revisiting the design intent concept in the context of mechanical CAD education. Computer-Aided Design and Applications. 15(1):47-60. https://doi.org/10.1080/16864360.2017.1353733S476015

    Calibration and alignment of metrology system for the Nuclear Spectroscopic Telescope Array mission

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    A metrology system to measure the on-orbit movement of a ten meter mast has been built for the Nuclear Spectroscopic Telescope Array (NuSTAR) x-ray observatory. In this paper, the metrology system is described, and the performance is measured. The laser beam stability is discussed in detail. Pre-launch alignment and calibration are also described. The invisible infrared laser beams must be aligned to their corresponding detectors without deploying the telescope in Earth’s gravity. Finally, a possible method for in-flight calibration of the metrology system is described

    Extracting, managing, and exploiting the semantics of mechanical CAD models in assembly tasks

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    The manufacturing of mechanical products is increasingly assisted by technologies that exploit the CAD model of the final assembly to address complex tasks in an automated and simplified way, to reduce development time and costs. However, it is proven that industrial CAD models are heterogeneous objects, involving different design conventions, providing geometric data on parts but often lacking explicit semantic information on their functionalities. As a consequence, existing approaches are mainly mathematics-based or need expert intervention to interpret assembly components, and this is limiting. The work presented in the thesis is placed in this context and aims at automatically extracting and leveraging in industrial applications high-level semantic information from B-rep models of mechanical products in standard format (e.g. STEP). This makes possible the development of promising knowledge intensive processes that take into account the engineering meaning of the parts and their relationships. The guiding idea is to define a rule-based approach that matches the shape features, the dimensional relations, and the mounting schemes strictly governing real mechanical assemblies with the geometric and topological properties that can be retrieved in CAD models of assemblies. More in practice, a standalone system is implemented which carries out two distinct operations, namely the data extraction and the data exploitation. The first involves all the steps necessary to process and analyze the geometric objects representing the parts of the assembly to infer their engineering meaning. It returns an enriched product model representation based on a new data structure, denoted as liaison, containing all the extracted information. The new product model representation, then, stands at the basis of the data exploitation phase, where assembly tasks, such as subassembly identification, assembly planning, and design for assembly, are addressed in a more effective way

    CFD investigation of airflow on a model radio control race car

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    The modern day design of vehicles, especially in the racing industry involve a great deal of air flow study. This study shows that drag force adversely affects the forward motion of the car and that there is a difference in the pressure between the air flowing above and below the car. This produces forces along the vertical axis. Aerodynamic forces acting on a car greatly reduces its efficiency. If the car is redesigned to optimise these forces it could produce better results. This paper discusses various techniques that have been used to redesign and optimise the aerodynamics of a model radio control race car
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