Pregled bibliografske jedinice broj: 1084218
EXCHAIN – Collaborative Platform and Database to share experimental data, results and acquired knowledge
EXCHAIN – Collaborative Platform and Database to share experimental data, results and acquired knowledge // Proceedings of the 17th World Conference on Earthquake Engineering, version 2020 / Meguro, Kimiro (ur.).
Sendai: Japan Association for Earthquake Engineering (JAEE), 2020. str. 1-12 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1084218 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
EXCHAIN – Collaborative Platform and Database
to share experimental data, results and
acquired knowledge
Autori
Schwarz, Jochen ; Kaufmann, Christian ; Ansari, Meisam ; Abrahamczyk, Lars ; Penava, Davorin ; Anić, Filip ; Isaković, Tatjana ; Anžlin, Andrej ; Kähler, Uwe ; Lopes, Nuno ; Kövesdi, Balázs ; Dunai, László
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 17th World Conference on Earthquake Engineering, version 2020
/ Meguro, Kimiro - Sendai : Japan Association for Earthquake Engineering (JAEE), 2020, 1-12
Skup
17th World Conference on Earthquake Engineering (17WCEE)
Mjesto i datum
Sendai, Japan, 27.09.2021. - 02.10.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
database ; experiments ; laboratory tests ; pushover analysis
Sažetak
The design of engineering structures like it is done today and in the past is based on static calculations. The consideration of uncertainties in the model quality becomes more and more important with the development of new construction methods and design requirements. In addition to the traditional forced-based approaches, experiences and observations about the deformation of components and the overall structure under different exposures, lead to novel detection and evaluation criteria. This continuous process can be observed and followed by code development, respectively. Accessible knowledge collected and provided on database will indeed play an essential role for future decisions. Additionally, the use of machine learning methods which require training data is becoming more and more common. Therefore, the establishment of a database, in which experimental results, information and acquired knowledge are collected and provided for future common activities in research and education, becomes more and more important. The network of the EU funded Erasmus+ strategic partnership between Universidade de Aveiro, Budapest University of Technology and Economics, University of Ljubljana, Josip Juraj Strossmayer University of Osijek, and BauhausUniversität Weimar created such a collaborative platform to share existing and future experimental data, results, and acquired knowledge with researchers all around the world. The different expertise, research work, and facilities from the partners are brought together for easier common use and application. Quite often data from experiments conducted in the past cannot be easily accessed for many reasons (e.g. compatibility, change of responsibilities, etc.). This paper addresses the database created in the project and the currently available datasets. At the same time, those interested are encouraged to use the database for their purpose and to provide additional data sets for wider use and usability for others. Based on the synopsis of the available data sets, information on the scope, completeness, and examined parameters is presented. In accordance with the objective of providing not only data but also information, results of analytical investigations are assigned to the experiments, too. The aim is to provide the users with access to the available results and models.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo, Temeljne tehničke znanosti
Napomena
The research presented in the manuscript is
carry out in part of the Erasmus+ Strategic
Partnership project “Forecast Engineering: From
Past Design to future
decisions”. The Erasmus+ SP project partners
are grateful for the sponsorship by the
European Union by the grant no. 2016-1-DE01-
KA203-002905.
POVEZANOST RADA
Ustanove:
Građevinski i arhitektonski fakultet Osijek