{"title":"基于知识的工程关联数据库系统","authors":"M.A. Moss , K. Jambunathan , E. Lai","doi":"10.1016/S0954-1810(99)00015-1","DOIUrl":null,"url":null,"abstract":"<div><p>Engineering design frequently relies on empirical data expressed in the form of non-dimensional correlations. These are almost always governed by applicability limits and the engineer is faced with the problem of choosing the right correlation that would provide design data with acceptable accuracy from a large number which are available. A knowledge based database system (KBDS) has been constructed which assists in the simple formulation of a jet impingement application based on which it retrieves and evaluates the relevant correlation from a database. Where the information in the database does not satisfy this specification the system uses knowledge of the application domain to either select suitable correlations for extrapolation or to modify the database query to select alternative information. The constraints which enable new correlations to be added or the knowledge in the network to be extended to include new geometries and flow conditions whilst maintaining the integrity are described. The operation of the KBDS has been demonstrated with a comprehensive database of correlations for the heat transfer due to the impingement of single and multiple air jets. This application provides typical engineering correlations and hence the techniques described are expected to be widely applicable.</p></div>","PeriodicalId":100123,"journal":{"name":"Artificial Intelligence in Engineering","volume":"13 3","pages":"Pages 201-210"},"PeriodicalIF":0.0000,"publicationDate":"1999-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0954-1810(99)00015-1","citationCount":"4","resultStr":"{\"title\":\"A knowledge based database system for engineering correlations\",\"authors\":\"M.A. Moss , K. Jambunathan , E. Lai\",\"doi\":\"10.1016/S0954-1810(99)00015-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Engineering design frequently relies on empirical data expressed in the form of non-dimensional correlations. These are almost always governed by applicability limits and the engineer is faced with the problem of choosing the right correlation that would provide design data with acceptable accuracy from a large number which are available. A knowledge based database system (KBDS) has been constructed which assists in the simple formulation of a jet impingement application based on which it retrieves and evaluates the relevant correlation from a database. Where the information in the database does not satisfy this specification the system uses knowledge of the application domain to either select suitable correlations for extrapolation or to modify the database query to select alternative information. The constraints which enable new correlations to be added or the knowledge in the network to be extended to include new geometries and flow conditions whilst maintaining the integrity are described. The operation of the KBDS has been demonstrated with a comprehensive database of correlations for the heat transfer due to the impingement of single and multiple air jets. This application provides typical engineering correlations and hence the techniques described are expected to be widely applicable.</p></div>\",\"PeriodicalId\":100123,\"journal\":{\"name\":\"Artificial Intelligence in Engineering\",\"volume\":\"13 3\",\"pages\":\"Pages 201-210\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0954-1810(99)00015-1\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence in Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0954181099000151\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0954181099000151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A knowledge based database system for engineering correlations
Engineering design frequently relies on empirical data expressed in the form of non-dimensional correlations. These are almost always governed by applicability limits and the engineer is faced with the problem of choosing the right correlation that would provide design data with acceptable accuracy from a large number which are available. A knowledge based database system (KBDS) has been constructed which assists in the simple formulation of a jet impingement application based on which it retrieves and evaluates the relevant correlation from a database. Where the information in the database does not satisfy this specification the system uses knowledge of the application domain to either select suitable correlations for extrapolation or to modify the database query to select alternative information. The constraints which enable new correlations to be added or the knowledge in the network to be extended to include new geometries and flow conditions whilst maintaining the integrity are described. The operation of the KBDS has been demonstrated with a comprehensive database of correlations for the heat transfer due to the impingement of single and multiple air jets. This application provides typical engineering correlations and hence the techniques described are expected to be widely applicable.