6 resultados para Rework

em Cambridge University Engineering Department Publications Database


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Cambridge Flow Solutions Ltd, Compass House, Vision Park, Cambridge, CB4 9AD, UK Real-world simulation challenges are getting bigger: virtual aero-engines with multistage blade rows coupled with their secondary air systems & with fully featured geometry; environmental flows at meta-scales over resolved cities; synthetic battlefields. It is clear that the future of simulation is scalable, end-to-end parallelism. To address these challenges we have reported in a sequence of papers a series of inherently parallel building blocks based on the integration of a Level Set based geometry kernel with an octree-based cut-Cartesian mesh generator, RANS flow solver, post-processing and geometry management & editing. The cut-cells which characterize the approach are eliminated by exporting a body-conformal mesh driven by the underpinning Level Set and managed by mesh quality optimization algorithms; this permits third party flow solvers to be deployed. This paper continues this sequence by reporting & demonstrating two main novelties: variable depth volume mesh refinement enabling variable surface mesh refinement and a radical rework of the mesh generation into a bottom-up system based on Space Filling Curves. Also reported are the associated extensions to body-conformal mesh export. Everything is implemented in a scalable, parallel manner. As a practical demonstration, meshes of guaranteed quality are generated for a fully resolved, generic aircraft carrier geometry, a cooled disc brake assembly and a B747 in landing configuration. Copyright © 2009 by W.N.Dawes.

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Engineering change is a significant part of any product development programme. Changes can arise at many points throughout the product life-cycle, resulting in rework which can ripple through different stages of the design process. Managing change processes is thus a critical aspect of any design project, especially in complex design. Through a literature review, this paper shows the diversity of information models used by different change management methods proposed in the literature. A classification framework for organising these change management approaches is presented. The review shows an increase in the number of cross-domain models proposed to help manage changes.

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The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

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Change propagates, potentially affecting many aspects of a design and requiring much rework to implement. This article introduces a cross-domain approach to decompose a design and identify possible change propagation linkages, complemented by an interactive tool that generates dynamic checklists to assess change impact. The approach considers the information domains of requirements, functions, components, and the detail design process. Laboratory experiments using a vacuum cleaner suggest that cross-domain modelling helps analyse a design to create and capture the information required for change prediction. Further experiments using an electronic product show that this information, coupled with the interactive tool, helps to quickly and consistently assess the impact of a proposed change. © 2012 Springer-Verlag London Limited.