Scientific Journal

Herald of Advanced Information Technology

DEVELOPMENT OF THE ONTOLOGY MODEL FOR THE TECHNICAL CONDITION OF HYDRAULIC STRUCTURES
Abstract:
Hydrotechnical constructures are complex structures that represent the interaction between soil-, water- and technological environment. For trouble-free and safe operation of hydrotechnical constructures, as well as maintaining them in operational mode, by the operating organization, as well as by organizations that conduct technical supervision, constant technical inspections are carried out to fix the damage (defects). This allows you to determine the actual technical condition of structures. Currently, building information modelling (BIM) methodology is most widely used for modelling structures. This methodology supports the seamless exchange of all information between relevant participants using digital technology. However, IFC files are mainly used to store data on structures. The evolution of this methodology provides for interoperability based on the network. The W3C LBD-CG community group presented an adapt extensible ontology called Building Topology Ontology (BOT), which provides a high-level description of the topology of structures, including the natures and types of hydrotechnical constructures depending on the purpose and operating conditions of structural elements of different levels. Authors have created an adapted ontology that does not have the same disadvantages as the IFC in terms of size and complexity. Reuse of existing ontologies has been an important priority, which allows the inclusion of ontologies for specialized areas. The issue of describing the technical condition of hydrotechnical constructures is considered. Basic terms and statements are introduced that extend the multi-sorted language of applied logic to describe the knowledge of this subject area. The ontology model provides terminology for defining damage associated with hydrotechnical constructures. The ontology model makes it possible to introduce into the developed ontologies the relationship of damages with structural elements and spatial zones of their location. The ontology can also be used to represent observations of the technical state of damage in a machine-interpreted format.
Authors:
Keywords
DOI
10.15276/aait.01.2021.2
References
  1. Sacks, R., Eastman, C., Lee, G. & Teicholz, P. “BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers”. Wiley & Sons. Hoboken. USA. 2018. DOI: 10.1002/9781119287568.
  2. Volk, R., Stengel, J. & Schultmann, F. “Building Information Modeling (BIM) for existing buildings: Literature review and future needs”. Automation in construction. 2014; 38: 109–127. DOI: 10.1016/j.autcon.2013.10.023.
  3. Burlutsky, S. G., Ezersky, V. V. & Khakhaev, I. A. “Elektronnyiy sertifikat kak osnova informatsionnogo obespecheniya avtomatizirovannyih sistem podderzhki prinyatiya resheniy” (“Electronic certificate as the basis for information support of automated decision support systems”). Information and control systems (in Russian). 2015; 1: 100–104. DOI: 10.15217 / issn1684-8853.2015.1.100.
  4. Bertelsen, S. “Construction as a complex system”.  Proceedings of the 11th Annual Conference of the5 International Group for Lean Construction. 2003. р.143–168.
  5. Schneider, G. F., Bougain, A., Noisten, P. S. & Mitterhofer, M. “Information Requirement Definition for BIM: A Life Cycle Perspective”. Proc. of ECPPM. Limas1483 sol. Cyprus. 2016. р. 225–234.
  6. “ISO 16739. Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries”. International Standardisation Organisation. Geneva: Switzerland. 2013.
  7. “ISO 19650. Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) – Information management is using building information modelling”. International Standardization Organization. Geneva: Switzerland. 2018.
  8. “UNI 11337-5. Building and civil engineering works Digital management of the informative processes”. Ente Nazionale Italiano di Unificazione. Italy. 2017.
  9. Rasmussen, M. H., Lefrançois, M., Bonduel, M., Hviid, C.A.  & Karlshøj. J. “OPM: An ontology for describing properties that evolve over time”. Proceedings of the 6th Linked Data in Architecture and Construction Workshop. CEUR Workshop Proceedings. London: UK. 2018; Vol. 2159: 24–33.https://hal.archives-ouvertes.fr/hal-01885248.
  10.  Rasmussen, M. H., Lefrançois, M., Schneider, G. F. & Pauwels, P. “BOT: the Building Topology Ontology of the W3C Linked Building Data Group”. Semantic Web. 2021; Vol.12, No.1: 143–161. DOI: 10.3233/SW-200385.
  11.  Pauwels, P., Zhang, S. & Lee, Y.-C. “Semantic web technologies in AEC industry: a literature review”. Automation in Construction. 2017; 73: 145–165. DOI: 10.1016/j.autcon.2016.10.003.
  12. “Instruction on engineering inspection and certification of port hydrotechnical constructures”. State Department of Maritime and River Transport of Ukraine (in Ukrainian). Odessa, Ukraine. 2001.
  13.  “Rules of technical supervision of hydrotechnical constructures in operation and measuring works”. Register of Shipping of Ukraine (in Ukrainian).  Kyiv: Ukraine. 2012.
  14.  Kleshchev, A. S. & Artemjeva I. L. “A mathematical apparatus for ontology simulation. Specialized extensions of the extendable language of applied logic”.  Inf. Theories and Appl.  2005; Vol.12 Issue 3: 265–271.
  15.  Pauwels, P. & Terkaj, W. “EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology”. Automation in Construction 63. 2016. р.100–133. DOI: 10.1016/j.autcon.2015.12.003.
  16.  Pauwels, P., Poveda-Villalón, M., Sicilia, Á. & Euzenat, J. “Semantic technologies and interoperability in the built environment”. Semantic Web 9(6).  2018: р.731–734. DOI: 10.3233/sw-180321.
  17.  Schneider, G. F., Rasmussen, M. H., Bonsma, P., Oraskari, J. & Pauwels, P. “Linked Building Data for Modular Building Information Modelling of a Smart Home”. In: eWork and eBusiness in Architecture, Engineering and Construction.CRC Press. Copenhagen: Denmark. 2018. р.407–414. DOI: 10.1201/9780429506215-51.
  18.  Lee, D. Y., Lin Chi, H., Wang, J., Wang, X. & Park, C. S. “A linked data system framework for sharing construction defect information using ontologies and BIM environments”. Automation in Construction 68. 2016. р.102–113. DOI: org/10.1016/j.autcon.2016.05.003.
  19.  Cacciotti, R., Blasko, M. & Valach, J. “A diagnostic ontological model for damages to historical constructions”. Journal of Cultural Heritage. 16. 2015. р.40–48. DOI: org/10.1016/j.culher.2014.02.002.
  20.  Rasmussen, M. H., Pauwels, P., Hviid, C. A. & Karlshoj J. “Proposing a Central AEC Ontology That Allows for Domain Specific Extensions”. In: Proceedings of the Joint Conference on Computing in Construction. Heriot-Watt University. Heraklion. Crete, Greece. 2017. Vol.1. DOI: 10.24928/jc3-2017/0153.
  21.  Rasmussen, M. H., Pauwels, P., Lefrançois, M., Schneider, G. F., Hviid, C. & Karlshoj, J. “Recent changes in the Building Topology Ontology”. In: 5th Linked Data in Architecture and Construction Workshop. Dijon: France. 2017. DOI: 10.13140/RG.2.2.32365.28647.
  22.  Hamdan, A., Bonduel, M. & Scherer, R J. “An ontological model for representation of damage to constructions”. In: Proceedings of the 7th Workshop on Linked Data in Architecture and Construction. Lisbon: Portugal. 2019.
  23.  Artemyeva, I. L. & Reshtanenko, N.V. “An intelligent system based on a multilevel ontology of chemistry” (in Russian). Software products and systems. 2008. 1. р.84–87. 
  24.  Artemyeva, I. L. “ Artificial Intelligence” (in Russian). (2006). 4. р. 85–94. 
  25.  Melnik, K. V. & Ershova, S. I. “Problems and main approaches to solving the problem of medical diagnostics”. Information processing systems (in Russian). 2011; Issue 2 (92): 244–248. 
  26.  Nesterenko, S. A., Tishin, P. M. & Makovetskiy, A. S.  “Development of an ontology model for diagnostics of service-oriented network structures based on a multi-sorted language of applied logic”.Electrical and computer systems. 2012; 07 (83): 102–108 (in Ukrainian).Access mode: http://nbuv.gov.ua/UJRN/etks_2012_7_20.
  27.  Tishin, P. M. & Makovetskiy, A. S. “Development of diagnostic ontology model of distributed information systems based on the many-sorted language of applied logic Information technology”. Industry control systems. 2015; Vol. 2 No. 2(74): 21–26.  DOI: org/10.15587/1729-4061.2015.40548.
  28.  Korotenko, G. M., Korotenko, L. M. & Khar, A.T. “Ontological classification of chemicals of technogenic origin in problems of social and hygienic monitoring”. Scientific notes of Tavriya National University named after VI Vernadsky. Series: Technical Sciences (in Russian). 2018; Vol. 29 (68) No. 3(1): 152–158. Access mode: http://nbuv.gov.ua/UJRN/sntuts_2018_29_3 (1) __29. 
  29.  Matheus, C., Baclawski, K. & Kokar, M. “BaseVISor: A Triples-Based Inference Engine Outfitted to Process RuleML and R-Entailment Rules”. Conference: Rules and Rule Markup Languages for the Semantic Web. 2006. р.67–74. DOI: 10.1109/RULEML.2006.6.
  30.  “Iso/np 21597: Information container for data drop (icdd)”. Standard, International Organization for Standardization.2017.
Published:
Last download:
20 Oct 2021

Contents


[ © KarelWintersky ] [ All articles ] [ All authors ]
[ © Odessa National Polytechnic University, 2018.]