{"title":"Smooth connection of trimmed NURBS surfaces","authors":"Pifu Zhang, F. Cheng","doi":"10.1145/376957.377000","DOIUrl":"https://doi.org/10.1145/376957.377000","url":null,"abstract":"An automatic smooth surface connection method that has the capability of tension control is presented. Given two trimmed NURBS surfaces, the new method constructs a smooth connection surface to connect the trimming regions of the trimmed surfaces at the trimming curves. The connection satisfies the pseudo-G1 or pseudo-C1 smoothness requirement, a condition not as strong as G1 or C1, but smooth enough for most industrial applications. The construction process consists of four major steps: connection curves construction and alignment, initial blends construction, setting up continuity constraints, and internal and external boundary smoothing. The advantages of the new method include: (1) providing the users with more flexibility in adjusting the shape of the connection surface, (2) the representation of the connection surface is compatible with most of the current data-exchange standards, (3) including the classical blending as a special case but with more flexibility on the setting of the rail curves, and (4) smoother shape of the resulting connection surface through an energy optimization process. Test cases that cover important applications are included.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129371908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A solid modeling services architecture for KBE applications","authors":"Alan L. Clark","doi":"10.1145/376957.376999","DOIUrl":"https://doi.org/10.1145/376957.376999","url":null,"abstract":"","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic adjustment of invalid feature models","authors":"Alex Noort, W. Bronsvoort","doi":"10.1145/376957.376988","DOIUrl":"https://doi.org/10.1145/376957.376988","url":null,"abstract":"In current feature modeling systems, all dimensions in a model have to be fully specified by the user. It is desirable that systems become more flexible in this respect, i.e. that non-critical dimensions in a model can be declared as variant, and that the model can be automatically adjusted when this is appropriate. A method and an implementation to realize this will be described. The underlying feature model definition and validation approach will be introduced. Validation is done by a collection of constraint solvers. An overview of invalid situations in which automatic model adjustment can be applied will be given. The constrain solving scheme and, in particular, the automatic model adjustment strategies for different types of constraints will elaborated. Applications in the areas of design by features, creating a member from a family of products, and feature conversion will be given. These will illustrate that automatic feature model adjustment is a very useful concept.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115397529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Deformation multi-tool combining existing deformation tools","authors":"D. Bechmann, H. Peyré","doi":"10.1145/376957.376997","DOIUrl":"https://doi.org/10.1145/376957.376997","url":null,"abstract":"","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124298679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A graph-based framework for feature recognition","authors":"S. Venkataraman, M. Sohoni, V. Kulkarni","doi":"10.1145/376957.376980","DOIUrl":"https://doi.org/10.1145/376957.376980","url":null,"abstract":"This paper discusses a feature recognition system for recognizing User Defined Features (UDF). The feature recognizer uses a graph-based approach to represent and recognize features. An attributed face adjacency graph consisting of topological and geometric attributes is used to represent UDF's. The feature recognition step involves finding similar subgraphs in the part graph. The novelty of the framework lies in the usage of a rich set of attributes to recognize a wide range of features efficiently. A unique representation using graph grammars has also been developed to define family of features such as pockets with variable number of side faces. The feature recognizer also addresses many kinds of feature interactions by progressive suppression of the identified features. New techniques have been implemented for suppressing degenerate or virtual features. The feature recognizer also consists of a parameterization module to extract user-defined parameters from the recognized features.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123006655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Octree based assembly sequence generation","authors":"R. Sung, J. Corney, D. Clark","doi":"10.1145/376957.376972","DOIUrl":"https://doi.org/10.1145/376957.376972","url":null,"abstract":"This paper describes a system for the automatic recognition of assembly features and the generation of assembly/disassembly sequences. The paper starts by reviewing the nature and use of assembly features. One of the conclusions drawn from this survey is that the majority of assembly features involve sets of spatially adjacent faces. Two principle types of adjacency relationships are identified and an algorithm is presented for identifying assembly features which arise from “spatial” and “contact” face adjacency relationships (known as s-adjacency and c-adjacency respectively).\u0000The algorithm uses an octree representation of a B-rep model to support the geometric reasoning required to locate assembly features on disjoint bodies. A pointerless octree representation is generated by recursively sub-dividing the assembly model's bounding box into octants which are used to locate:Those portions of faces which are c-adjacent (i.e. they effectively touch within the tolerance of the octree).\u0000Those portions of faces which are s-adjacent to a nominated face.\u0000\u0000The resulting system can locate and partition spatially adjacent faces in a wide range of situations and a different resolutions. The assembly features located are recorded as attributes in the B-rep model and are then used to generate a disassembly sequence plan for the assembly. This sequence plan is represented by a transition state tree which incorporates knowledge of the availability of feasible gripping features.\u0000By way of illustration, the algorithm is applied to several trial components","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122832706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Web-based collaborative feature modeling","authors":"Rafael Bidarra, E. V. D. Berg, W. Bronsvoort","doi":"10.1145/376957.377002","DOIUrl":"https://doi.org/10.1145/376957.377002","url":null,"abstract":"","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133442171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An efficient data structure for random walk algorithms in faceted porous media","authors":"Jean-François Delesse, B. L. Saëc, G. Vignoles","doi":"10.1145/376957.376991","DOIUrl":"https://doi.org/10.1145/376957.376991","url":null,"abstract":"Modern X-ray Computerized Micro-Tomography (CMT) facilities allow researchers interested in composite materials and porous media to image their samples in 3D with micrometer resolution. The datasets obtained for representative samples are frequently very large (10243 voxels in gray-scale levels). Performing a tessellation on such datasets would produce hundreds millions facets, which would be impossible to handle in memory on rather powerful computers.\u0000Various numerical methods are classical for the prediction of some effective properties of porous and other composite media from the phase properties and the micro-structure (diffusivities, conductivities). The choice of a Monte-Carlo random walk scheme is justified by its minimal memory cost in addition to image storage. In order to employ it, one must be able to perform ray-tracing in large and precise 3D images. The new framework we present allows that feature by using a memory-sparing data structure dedicated to such algorithms.\u0000We only store in memory the vertices provided by the marching cube algorithm. So, since the facets are not stored, the needed memory size is divided by a factor of five, without any significant increasing of the computation time: the extraction of properties from very large micro-porous media samples is now possible.\u0000This study allows us to claim that a simulation making an intensive use of ray-tracing in tessellated media obtained with the marching-cube algorithm is not as expensive (in terms of memory and time cost) as it could seem. We show that the marching-cube algorithm, when it is used dynamically to connect vertices upon request, is still a very powerful mesh generator since it consumes then very few memory, and that it can be trivially implemented.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114198577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A laminae approach to constructing geometric feature volumes","authors":"T. Lim, J. Corney, D. Clark","doi":"10.1145/376957.376979","DOIUrl":"https://doi.org/10.1145/376957.376979","url":null,"abstract":"The limiting factor for the majority of reported feature recognition (AFR) algorithms lie in their inability to handle anything more complex than the restricted geometric domain of 2.5D machined components. This paper describes a novel approach to recognising shape features on models comprising both simple and complex ruled surfaces. Specifically, the paper describes how the concept of 3D-laminae enables feature volumes bounded by complex ruled surfaces to be constructed. This generic feature recognition algorithm requires no predefined feature libraries and advocates the notion of neutral features, which separates the generic features identified by the extraction algorithm from those (features) classified subsequently to suit a discrete domain. The work concentrates on identifying machinable volumes (for manufacture by CNC machines) and the classifications presented apply specifically to this context. However, because the algorithm is capable of handling complex ruled surfaces, it is envisaged that the proposed methodology will be applicable to industries involved with the manufacture of dies and moulds.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116173260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A constraint solving-based approach to analyze 2D geometric problems with interval parometers","authors":"R. Joan-Arinyo, N. Mata, Antoni Soto-Riera","doi":"10.1145/376957.376959","DOIUrl":"https://doi.org/10.1145/376957.376959","url":null,"abstract":"Many applications of geometric nature can be modeled by geometric problems defined by constraints in which the constraint parameters have interval uncertainty. In a previous work, we developed a method for solving geometric constraint problems where parameters are narrow intervals in the domain of the geometric problem. Based on this work, we present a new approach to solve more general problems with non-trivial-width interval parameters that may not necessarily be in the domain of the problem. We show how our approach is successfully applied to a number of problems like solving geometric problems with tolerances, checking constraint feasibility and analyzing link motion of planar mechanisms.","PeriodicalId":286112,"journal":{"name":"International Conference on Smart Media and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116418543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}