Algorithms for detecting dependencies and rigid subsystems for CAD

Geometric constraint systems underly popular Computer Aided Design soft- ware. Automated approaches for detecting dependencies in a design are critical for developing robust solvers and providing informative user feedback, and we provide algorithms for two types of dependencies. First, we give a pebble game algorithm for detecting generic dependencies. Then, we focus on identifying the "special positions" of a design in which generically independent constraints become dependent. We present combinatorial algorithms for identifying subgraphs associated to factors of a particular polynomial, whose vanishing indicates a special position and resulting dependency. Further factoring in the Grassmann- Cayley algebra may allow a geometric interpretation giving conditions (e.g., "these two lines being parallel cause a dependency") determining the special position.Comment: 37 pages, 14 figures (v2 is an expanded version of an AGD'14 abstract based on v1

Geometric Over-Constraints Detection: A Survey

Currently, geometric over-constraints detection is of major interest in several diferent felds. In terms of product development process (PDP), many approaches exist to compare and detect geometric over-constraints, to decompose geometric systems, to solve geometric constraints systems. However, most approaches do not take into account the key characteristics of a geometric system, such as types of geometries, diferent levels at which a system can be decomposed e.g numerical or structural. For these reasons, geometric over-constraints detection still faces challenges to fully satisfy real needs of engineers. The aim of this paper is to review the state-of-the-art of works involving with geometric over-constraints detection and to identify pos sible research directions. Firstly, the paper highlights the user requirements for over-constraints detection when modeling geometric constraints systems in PDP and proposes a set of criteria to analyze the available methods classifed into four categories: level of detecting over-constraints, system decomposition, system modeling and results generation. Secondly, it introduces and analyzes the available methods by grouping them based on the introduced criteria. Finally, it discusses pos sible directions and future challenges

Over-constraints detection and resolution in geometric equation systems

This paper proposes an original decision-support approach to address over-constrained geometric configurations in Computer-Aided Design. It focuses particularly on the detection and resolution of redundant and conflicting constraints when deforming free-form surfaces made of NURBS patches. Based on a series of structural decompositions coupled with numerical analyses, the proposed approach handles both linear and non-linear constraints. The structural decompositions are particularly efficient because of the local support property of NURBS. Since the result of this detection process is not unique, several criteria are introduced to drive the designer in identifying which constraints should be removed to minimize the impact on his/her original design intent. Thus, even if the kernel of the algorithm works on equations and variables, the decision is taken by considering the user-specified geometric constraints. The method is illustrated on academic and industrial examples realized with our prototype software

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Squeak and Rattle Prediction for Robust Product Development in the automotive industry

Squeak and rattle are nonstationary, irregular, and impulsive sounds that are audible inside the car cabin. For decades, customer complaints about squeak and rattle have been, and still are, among the top quality issues in the automotive industry. These annoying sounds are perceived as quality defect indications and burden warranty costs to the car manufacturers. Today, the quality improvements regarding the persistent type of sounds in the car, as well as the increasing popularity of electric engines, as green and quiet propulsion solutions, stress the necessity for attenuating annoying sounds like squeak and rattle more than in the past. The economical and robust solutions to this problem are to be sought in the pre-design-freeze phases of the product development and by employing design-concept-related practices. To achieve this goal, prediction and evaluation tools and methods are required to deal with the squeak and rattle quality issues upfront in the product development process. The available tools and methods for the prediction of squeak and rattle sounds in the pre-design-freeze phases of a car development process are not yet sufficiently mature. The complexity of the squeak and rattle events, the existing knowledge gap about the mechanisms behind the squeak and rattle sounds, the lack of accurate simulation and post-processing methods, as well as the computational cost of complex simulations are some of the significant hurdles in this immaturity. This research addresses this problem by identifying a framework for the prediction of squeak and rattle sounds based on a cause-and-effect diagram. The main domains and the elements and the sub-contributors to the problem in each domain within this framework are determined through literature studies, field explorations and descriptive studies conducted on the subject. Further, improvement suggestions for the squeak and rattle evaluation and prediction methods are proposed through prescriptive studies. The applications of some of the proposed methods in the automotive industry are demonstrated and examined in industrial problems.The outcome of this study enhances the understanding of some of the parameters engaged in the squeak and rattle generation. Simulation methods are proposed to actively involve the contributing factors studied in this work for squeak and rattle risk evaluation. To enhance the efficiency and accuracy of the risk evaluation process, methods were investigated and proposed for the system excitation efficiency, modelling accuracy and efficiency and quantification of the response in the time and frequency domains. The demonstrated simulation methods besides the improved understanding of the mechanisms behind the phenomenon can facilitate a more accurate and robust prediction of squeak and rattle risk during the pre-design-freeze stages of the car development

Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 20. bis 22.7. 2015, Bauhaus-Universität Weimar

The 20th International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering will be held at the Bauhaus University Weimar from 20th till 22nd July 2015. Architects, computer scientists, mathematicians, and engineers from all over the world will meet in Weimar for an interdisciplinary exchange of experiences, to report on their results in research, development and practice and to discuss. The conference covers a broad range of research areas: numerical analysis, function theoretic methods, partial differential equations, continuum mechanics, engineering applications, coupled problems, computer sciences, and related topics. Several plenary lectures in aforementioned areas will take place during the conference. We invite architects, engineers, designers, computer scientists, mathematicians, planners, project managers, and software developers from business, science and research to participate in the conference

Satellite Servicing's Autonomous Rendezvous and Docking Testbed on the International Space Station

The Space Servicing Capabilities Project (SSCP) at NASA's Goddard Space Flight Center (GSFC) has been tasked with developing systems for servicing space assets. Starting in 2009, the SSCP completed a study documenting potential customers and the business case for servicing, as well as defining several notional missions and required technologies. In 2010, SSCP moved to the implementation stage by completing several ground demonstrations and commencing development of two International Space Station (ISS) payloads-the Robotic Refueling Mission (RRM) and the Dextre Pointing Package (DPP)--to mitigate new technology risks for a robotic mission to service existing assets in geosynchronous orbit. This paper introduces the DPP, scheduled to fly in July of 2012 on the third operational SpaceX Dragon mission, and its Autonomous Rendezvous and Docking (AR&D) instruments. The combination of sensors and advanced avionics provide valuable on-orbit demonstrations of essential technologies for servicing existing vehicles, both cooperative and non-cooperative

Integrated modeling and analysis methodologies for architecture-level vehicle design.

In order to satisfy customer expectations, a ground vehicle must be designed to meet a broad range of performance requirements. A satisfactory vehicle design process implements a set of requirements reflecting necessary, but perhaps not sufficient conditions for assuring success in a highly competitive market. An optimal architecture-level vehicle design configuration is one of the most important of these requirements. A basic layout that is efficient and flexible permits significant reductions in the time needed to complete the product development cycle, with commensurate reductions in cost. Unfortunately, architecture-level design is the most abstract phase of the design process. The high-level concepts that characterize these designs do not lend themselves to traditional analyses normally used to characterize, assess, and optimize designs later in the development cycle. This research addresses the need for architecture-level design abstractions that can be used to support ground vehicle development. The work begins with a rigorous description of hierarchical function-based abstractions representing not the physical configuration of the elements of a vehicle, but their function within the design space. The hierarchical nature of the abstractions lends itself to object orientation - convenient for software implementation purposes - as well as description of components, assemblies, feature groupings based on non-structural interactions, and eventually, full vehicles. Unlike the traditional early-design abstractions, the completeness of our function-based hierarchical abstractions, including their interactions, allows their use as a starting point for the derivation of analysis models. The scope of the research in this dissertation includes development of meshing algorithms for abstract structural models, a rigid-body analysis engine, and a fatigue analysis module. It is expected that the results obtained in this study will move systematic design and analysis to the earliest phases of the vehicle development process, leading to more highly optimized architectures, and eventually, better ground vehicles. This work shows that architecture level abstractions in many cases are better suited for life cycle support than geometric CAD models. Finally, substituting modeling, simulation, and optimization for intuition and guesswork will do much to mitigate the risk inherent in large projects by minimizing the possibility of incorporating irrevocably compromised architecture elements into a vehicle design that no amount of detail-level reengineering can undo