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Semantic Data Model for Multibody System Modelling Dissertation VTT PUBLICATIONS 766 Juha Kortelainen Semantic Data Model for Multibody System Modelling VTT PUBLICATIONS 766 Semantic Data Model for Multibody System Modelling Juha Kortelainen Thesis for the degree of Doctor of Science (Technology) to be presented with due permission for public examination and criti- cism in the Auditorium 1383 at Lappeenranta University of Tech- nology, Lappeenranta, Finland on the 19th of August, 2011, at noon. ISBN 978-951-38-7742-2 (soft back ed.) ISSN 1235-0621 (soft back ed.) ISBN 978-951-38-7743-9 (URL: http://www.vtt.fi/publications/index.jsp) ISSN 1455-0849 (URL: http://www.vtt.fi/publications/index.jsp) Copyright c Juha Kortelainen 2011 JULKAISIJA { UTGIVARE { PUBLISHER VTT, Vuorimiehentie 5, PL 1000, 02044 VTT puh. vaihde 020 722 111, faksi 020 722 4374 VTT, Bergsmansv¨agen 5, PB 1000, 02044 VTT tel. v¨axel 020 722 111, fax 020 722 4374 VTT Technical Research Centre of Finland, Vuorimiehentie 5, P.O. Box 1000, FI-02044 VTT, Finland phone internat. +358 20 722 111, fax + 358 20 722 4374 Kopijyv¨a Oy, Kuopio 2011 Juha Kortelainen. Semantic Data Model for Multibody System Modelling [Semanttinen tietomalli monikappaledynamiikan mallitiedon hallinnassa]. Espoo 2011. VTT Publications 766. 119 p. + app. 34 p. Keywords multibody application, data management, semantic data model, reasoning Abstract Multibody system simulation, as one area of system simulation, represents a considerable improvement in predicting machine dynamic performance com- pared to previous methods that are often based on analytic equations or empir- ical testing. With multibody system simulation, it is fast and efficient to study the effects of design variables on the dynamic behaviour of the mechanism com- pared to the experimental approach. Accordingly, the use of multibody system simulation in the design process can decrease the need for physical prototypes, thus accelerating the overall design process and saving resources. In the product development sense, the interaction between computational tools can be cumbersome. For this reason, multibody system simulation is often omitted in terms of the main stream of product development. Due to the increase of computational resources, the trend is towards extensive usage of simulation, including multibody system simulation, in the product develop- ment. The research emphasis in the field of multibody system dynamics has been on the areas of improved multibody system formulations, such as recursive methods, representation of flexible structures, application of multibody sim- ulation in new areas such as biomechanics, and including multibody simula- tion into multitechnical and multiphysics simulation. The research on model- ling data management and integration approaches concerning tools applied in product design and development has not been in the main stream. The growth of the World Wide Web and the evolution of Web technologies have multiplied the amount of data and information available on the Internet. In this expansion of information, it has become cumbersome to find and distil the useful information from the data mass. In order to utilise the information available on the Internet and to sort meaningful information out of the data mass, the World Wide Web Consortium began a development project for the next generation Web, the Semantic Web. In this development effort, methods and technologies based on semantic data representation are developed and utilised. These methods and technologies are general enough to be applied to other application areas as well. This work concentrates on the modelling data management of multibody 3 Abstract system simulation within a simulation-based product process. The main ob- jectives of this work can be summarised as follows: introduce a procedure for managing multibody system modelling data using semantic data model and ontology-based modelling approach, demonstrate that the semantic data model allows application-based reasoning on the model data, and show that ontology- based modelling is able to capture domain knowledge by using semantic data and constraint- and rule-based reasoning. In this work, the semantic data representation approach is used for describ- ing modelling data of a multibody system. This is accomplished by developing a multibody system modelling ontology, i.e. a semantic data model for multi- body system model description, and then applying this ontology to model an example multibody system. 4 Juha Kortelainen. Semantic Data Model for Multibody System Modelling [Semanttinen tietomalli monikappaledynamiikan mallitiedon hallinnassa]. Espoo 2011. VTT Publications 766. 119 s. + liitt. 34 s. Avainsanat multibody application, data management, semantic data model, reasoning Tiivistelm¨a Monikappaledynamiikka, yhten¨a systeemisimuloinnin erikoisalueena, edustaa merkitt¨av¨a¨a parannusta koneiden ja mekaanisten j¨arjestelmien suorituskyvyn arvioinnissa verrattuna muihin menetelmiin, jotka usein perustuvat joko ana- lyyttisiin laskelmiin tai kokeellisiin menetelmiin. Verrattuna kokeellisiin me- netelmiin monikappaledynaamiikkaa soveltamalla on nopeaa ja tehokasta sel- vitt¨a¨a eri muuttujien vaikutus mekanismin dynaamisiin ominaisuuksiin. T¨aten monikappaledynamiikan soveltaminen suunnitteluprosessissa voi v¨ahent¨a¨a tar- vetta todellisten prototyyppien k¨ayt¨olle ja siten nopeuttaa suunnitteluprosessia kokonaisuutena sek¨a s¨a¨ast¨a¨a resursseja. Laskennallisten ohjelmistojen yhteisk¨aytt¨o voi olla hankalaa tuotekehityk- sen n¨ak¨okulmasta. T¨ast¨a syyst¨a tuotesuunnittelun valtavirrassa usein v¨alte- t¨a¨an monikappaledynamiikan k¨aytt¨o¨a. Laskennallisten resurssien kasvusta joh- tuen suuntaus on kuitenkin kohti enenev¨a¨a simuloinnin k¨aytt¨o¨a tuotekehityk- sess¨a, mukaan lukien monikappaledynamiikka. Monikappaledynamiikan tutkimus on painottunut monikappaledynamiikan formuloinnin, kuten esimerkiksi rekursiivisten menetelmien, kehitt¨amiseen, ra- kenteellisen joustavuuden huomioimiseen, monikappaledynamiikan soveltami- seen uusilla tutkimusalueilla, kuten biomekaniikassa, sek¨a monikappaledyna- miikan soveltamiseen moniteknisess¨a ja monifysikaalisessa simuloinnissa. Mo- nikappaledynamiikan tiedonhallinta sek¨a tuotekehitykseen k¨aytettyjen lasken- nallisten ohjelmistojen ja menetelmien integrointi eiv¨at ole kuuluneet keskeisiin tutkimusalueisiin monikappaledynamiikassa. Internetin kasvu sek¨a Web-teknologioiden kehitys ovat moninkertaistaneet Internetiss¨a tarjolla olevan tiedon m¨a¨ar¨an. T¨am¨an tiedon m¨a¨ar¨an kasvun my¨o- t¨a oikean tiedon l¨oyt¨amisest¨a Internetin tietomassasta on tullut hankalaa. In- ternetiss¨a tarjolla olevan tiedon paremman hy¨odynnett¨avyyden mahdollistami- seksi World Wide Web Consortium on k¨aynnist¨anyt kehityshankkeen nimelt¨a Semanttinen Web, jossa kehitet¨a¨an seuraavan sukupolven verkkoa. Kehitys- hankkeessa kehitet¨a¨an ja sovelletaan tiedon semanttiseen kuvaukseen perustu- via menetelmi¨a ja tekniikoita, jotka ovat riitt¨av¨an yleisi¨a sovellettaviksi my¨os muille alueille, kuten laskennallisen tiedon hallintaan. T¨ass¨a ty¨oss¨a keskityt¨a¨an tuotekehitykseen liittyv¨an monikappaledynamii- 5 Tiivistelm¨a kan mallitiedonhallintaan. Ty¨on tavoitteet voidaan tiivist¨a¨a seuraavalla taval- la: esitell¨a periaate monikappaledynamiikan mallitiedon hallintaan k¨aytt¨aen semanttista tietomallia sek¨a ontologiapohjaista mallinnusmenetelm¨a¨a; osoit- taa, ett¨a semanttisen tietomallin soveltaminen mahdollistaa sovelluspohjaisen p¨a¨attelyn monikappaledynamiikan mallitiedosta; sek¨a osoittaa, ett¨a ontologia- pohjainen mallintaminen mahdollistaa my¨os tiet¨amyksen tallentamisen yhdes- s¨a mallitiedon kanssa soveltaen semanttista tietomallia sek¨a rajoite- ja s¨a¨an- t¨opohjaista p¨a¨attely¨a. T¨am¨a osoitetaan kehitt¨am¨all¨a mallinnusontologia moni- kappaledynamiikan mallitiedon hallintaan ja soveltamalla t¨at¨a ontologiaa mo- nikappaledynaamisen esimerkkitapauksen mallin kuvaukseen. 6 Preface In a short period of technological evolution, the world has seen enormous changes. We are now heading into a new era of information and knowledge. Humankind is producing information at a continuously increasing speed { with the wealth of information available, the challenge now facing us is how to dis- til the desired information and knowledge out of the huge data masses. The development of computation, including progress in algorithms, computational methods, and computer hardware, has provided us with new tools to search and analyse the data masses. On the other hand, new methods and innova- tions in computational modelling and simulation have drastically increased the speed of producing new data, e.g. for product development. This doctoral thesis concentrates on combining new methods in knowledge management and system simulation. The former seeks to solve the challenges rising from the latter in order to ensure further improvements in the overall efficiency of applying computational methods for purposes such as product development. Acknowledgements I would like to thank several people for helping me with this work. First, I would like to thank Professor Aki Mikkola for providing me with a great envir- onment for my scientific work. In this tranquil but inspiring environment, in the company of the skilled and bright members of the research group, I could concentrate on the subject. I was very lucky to be a member of the research group while writing my thesis. The whole group gave me great support and the positive and excited atmosphere helped me in my work. I would especially like to thank doctoral student
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