{"title":"跨域特征模型之间的关联性","authors":"S. Subramani, B. Gurumoorthy","doi":"10.1145/781606.781658","DOIUrl":null,"url":null,"abstract":"Associativity between feature models implies the automatic updating of different feature models of a part after changes are made in one of its feature models. This is an important requirement in a distributed and concurrent design environment, where integrity of part geometry has to be maintained through changes made in different task domains.The proposed algorithm takes multiple feature models of a part as input and modifies other feature models to reflect the changes made to a feature in a feature model. The proposed algorithm updates feature volumes in a model that has not been edited and then classifies the updated volumes to obtain the updated feature model. The spatial arrangement of feature faces and adjacency relationship between features are used to isolate features in a view that are affected by the modification. Feature volumes are updated based on the classification of the feature volume of the modified feature with respect to feature volumes of the model being updated. The algorithm is capable of handling all types of feature modifications namely, feature deletion, feature creation, and changes to feature location and parameters. In contrast to current art in automatic updating of feature models, the proposed algorithm does not use an intermediate representation, does not re-interpret the feature model from a low level representation and handles interacting features. Results of implementation on typical cases are presented.","PeriodicalId":405863,"journal":{"name":"ACM Symposium on Solid Modeling and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Associativity between feature models across domains\",\"authors\":\"S. Subramani, B. Gurumoorthy\",\"doi\":\"10.1145/781606.781658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Associativity between feature models implies the automatic updating of different feature models of a part after changes are made in one of its feature models. This is an important requirement in a distributed and concurrent design environment, where integrity of part geometry has to be maintained through changes made in different task domains.The proposed algorithm takes multiple feature models of a part as input and modifies other feature models to reflect the changes made to a feature in a feature model. The proposed algorithm updates feature volumes in a model that has not been edited and then classifies the updated volumes to obtain the updated feature model. The spatial arrangement of feature faces and adjacency relationship between features are used to isolate features in a view that are affected by the modification. Feature volumes are updated based on the classification of the feature volume of the modified feature with respect to feature volumes of the model being updated. The algorithm is capable of handling all types of feature modifications namely, feature deletion, feature creation, and changes to feature location and parameters. In contrast to current art in automatic updating of feature models, the proposed algorithm does not use an intermediate representation, does not re-interpret the feature model from a low level representation and handles interacting features. Results of implementation on typical cases are presented.\",\"PeriodicalId\":405863,\"journal\":{\"name\":\"ACM Symposium on Solid Modeling and Applications\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Symposium on Solid Modeling and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/781606.781658\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Symposium on Solid Modeling and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/781606.781658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Associativity between feature models across domains
Associativity between feature models implies the automatic updating of different feature models of a part after changes are made in one of its feature models. This is an important requirement in a distributed and concurrent design environment, where integrity of part geometry has to be maintained through changes made in different task domains.The proposed algorithm takes multiple feature models of a part as input and modifies other feature models to reflect the changes made to a feature in a feature model. The proposed algorithm updates feature volumes in a model that has not been edited and then classifies the updated volumes to obtain the updated feature model. The spatial arrangement of feature faces and adjacency relationship between features are used to isolate features in a view that are affected by the modification. Feature volumes are updated based on the classification of the feature volume of the modified feature with respect to feature volumes of the model being updated. The algorithm is capable of handling all types of feature modifications namely, feature deletion, feature creation, and changes to feature location and parameters. In contrast to current art in automatic updating of feature models, the proposed algorithm does not use an intermediate representation, does not re-interpret the feature model from a low level representation and handles interacting features. Results of implementation on typical cases are presented.