Generating fit-for-purpose CAE models from complex CAD assemblies is time consuming and error-prone. Tedious tasks include identifying and isolating the components of interest, removing duplicate components, and correcting inconsistent component interfaces. In this paper a new approach to help engineers identify similar features and analyse the consistency of CAD assembly models is proposed. The method utilises a tensor factorisation technique developed for relational machine learning and applies it to B-Rep topological and geometrical relations. The model considers globally all the input relations to identify which entities in the assembly are similar (within a user-defined threshold) to a selected input entity. It is shown that a hierarchical clustering method can group entities, based on the similarities of their attributes and relationships with adjacent components. It is shown how some unsuspected CAD modelling errors show up as features which should be similar, but which are not. It is demonstrated how the technique can be used to support the, currently highly manual, task of decomposing a volume representing an internal fluid network into sub-volumes and features of significance.

Generating structured meshes is often an expensive process, limiting the use of high-fidelity numerical simulation methods for design, especially when the design is not yet fixed and design updates are likely. For hexahedral meshes generated by decomposing a B-Rep model into regions for which simple meshing strategies are known, robustly propagating design modifications to the decomposed representation and subsequent mesh is very challenging. In this paper, an approach is presented to propagate parametric update and feature changes to structured meshes. Geometric and topological modifications on the design model are identified first, enabling the equivalent modifications to be identified on the decomposition of the design model. Virtual topology operations used to generate the initial decomposition are combined with the meshing constraints of individual sub-regions to update the decomposition and associated mesh locally. The approach is demonstrated for a number of design updates.

Defining Simulation Intent involves capturing high level modelling and idealisation decisions in order to create an efficient and fit-for-purpose analysis. These decisions are recorded as attributes of the decomposed design space. An approach to defining Simulation Intent is described utilising three known technologies: Cellular Modelling, the subdivision of space into volumes of simulation significance (structures, gas paths, internal and external airflows, etc.); Equivalencing, maintaining functional links between different analysis representations of the same region of design space across multiple analysis models; and Virtual Topology, which offers tools for partitioning and de-partitioning the model without disturbing the manufacturing oriented design geometry. The end result is a convenient framework to which high-level analysis attributes can be applied, and from which detailed analysis models can be generated with a high degree of controllability, repeatability and automation. There are multiple novel aspects to the approach, including its reusability, robustness to changes in model topology and the inherent links created between analysis models at different levels of fidelity and physics. By utilising Simulation Intent, CAD modelling for simulation can be fully exploited and simulation work-flows can be more readily automated, reducing many repetitive manual tasks (e.g. the definition of appropriate coupling between elements of different types and the application of boundary conditions). The approach has been implemented and tested with practical examples, and significant benefits are demonstrated.

The finite element method plays an extremely important role in forging process design as it provides a valid means to quantify forging errors and thereby govern die shape modification to improve the dimensional accuracy of the component. However, this dependency on process simulation could raise significant problems and present a major drawback if the finite element simulation results were inaccurate. This paper presents a novel approach to assess the dimensional accuracy and shape quality of aeroengine blades formed from finite element hot-forging simulation. The proposed virtual inspection system uses conventional algorithms adopted by modern coordinate measurement processes as well as the latest free-form surface evaluation techniques to provide a robust framework for virtual forging error assessment. Established techniques for the physical registration of real components have been adapted to localise virtual models in relation to a nominal design model. Blades are then automatically analysed using a series of intelligent routines to generate measurement data and compute dimensional errors. The results of a comparison study indicate that the virtual inspection results and actual coordinate measurement data are highly comparable and the procedures for registration and virtual inspection are computationally efficient, validating the approach as an effective and accurate means to quantify forging error in a virtual environment. Consequently, this provides adequate justification for the implementation of the virtual inspection system in the virtual process design, modelling and validation of forged aeroengine blades in industry.

Thin-walled aerospace structures can be idealised as dimensionally reduced shell models. These models can be analysed in a fraction of the time required for a full 3D model yet still provide remarkably accurate results. The disadvantages of this approach are the time taken to derive the idealised model, though this is offset by the ease and rapidity of design optimisation with respect to parameters such as shell thickness, and the fact that the stresses in the local 3D details can not be resolved.A process for automatically creating a mixed dimensional idealisation of a component from its CAD model is outlined in this paper. It utilises information contained in the CAD feature tree to locate the sketches associated with suitable features in the model. Suitable features are those created by carrying out dimensional addition operations on 2D sketches, in particular sweeping the sketch along a line to create an extruded solid, or revolving the sketch around an axis to create an axisymetric solid. Geometric proximity information provided by the 2D Medial Axis Transform is used to determine slender regions in the sketch suitable for dimensional reduction. The slender regions in the sketch are used to create sheet bodies representing the thin regions of the component, into which local 3D solid models of complex details are embedded. Analyses of the resulting models provide accurate results in a fraction of the run time required for the 3D model analysis.Also discussed is a web service implementation of the process which automatically dimensionally reduces 2D planar sketches in the STEP format.

CAD technology plays an ever more central role in today's multidisciplinary simulation environments. While this has enabled highly complex and detailed models to be used earlier in the design process it has brought with it difficulties for simulation specialists. Most notably CAD models now contain many details which are irrelevant to simulation disciplines. CAD systems have feature trees which record feature creation but unfortunately this does not capture which features are relevant to which analysis discipline. Many features of little significance to an analysis only emerge during the construction of the model. The ability to selectively suppress and reinstate features while maintaining an audit trail of changes is required to facilitate the control of the idealisation process. Features suppressed for one analysis can be retrieved for use in another. This work uses combinatorial topology concepts to outline the necessary conditions so that CAD model simplification operations can be designed as continuous transformations. Irrelevant features can then be suppressed and subsequently reinstated, within defined limitations, independently from the order in which they were suppressed. The implementation of these concepts provides analysts with a mechanism for generating analysis models with different levels of detail, without having to repeat the simplification process from the original CAD geometry. Most importantly, the information recorded during the suppress operations forms an essential audit trail of the idealisation process and can be presented in a feature-tree like structure allowing analysts to review their modelling decisions retrospectively. The approach also facilitates the generation of local, detailed models encapsulating a feature of interest. The proposed system follows a Find and Fix paradigm, where different algorithms for feature finding and fixing can be utilised in a common cellular modelling framework.

Processing geometric models for finite element analysis is a major factor in the time required to develop and optimise a design. Efficient analysis may require simplification of the geometric model by dimensional reduction (replacing thin sheets or slender bars of material with equivalent line or surface elements) or detail suppression (the removal of small features below the scale of interest in the analysis). There are many situations where detailed local models of full dimension could be combined with global models containing reduced dimensional elements, or in which the abstract models used in preliminary design could be used to generate an initial version of the 3D solid model. Furthermore, the most appropriate representation of an object is dependent on the analysis type. These requirements provide significant challenges for future generations of CAE software in feature recognition and the modelling and representation of geometric objects.

The medial surface is a skeletal abstraction of a solid that provides useful shape information, which compliments existing model representation schemes. The medial surface and its associated topological entities are defined, and an algorithm for computing the medial surface of a large class of B-rep solids is then presented. The algorithm is based on the domain Delaunay triangulation of a relatively sparse distribution of points, which are generated on the boundary of the object. This strategy is adaptive in that the boundary point set is refined to guarantee a correct topological representation of the medial surface.