Browsing by Author "Prieto Ibáñez, Andrés José"

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    An Approach Concerning Climate Change and Timber Building Resilience: Araucanía Region, South Chile
    (MDPI, 2021) Prieto Ibáñez, Andrés José; Verichev, Konstantin; Ferreira, Ana da Silva
    This study analysed climate change effects concerning the resilience of timber buildings located in southern Chile, specifically in two cities: Collipulli and Temuco (Araucanía Region). A digital fuzzy logic method was used in a set of timber buildings declared as heritage conservation buildings by Chilean Government standards. The outcomes revealed that climate change impacts did not substantially alter the functional performance of the set of heritage timber buildings examined. This study’s results can assist in developing upcoming strategies or recommendations that can support adaptation policies for administering architectural heritage regarding climate change forecasts. These data will invaluably help stakeholders who support the conservation of timber structures located in the southern environment of Chile and under the changing climatic hazard
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    BIM and procurement data integration in industrialized construction using artificial intelligence
    (2024) Pino Álvarez, Thomas Enrique; Barkokebas, Beda; Prieto Ibáñez, Andrés José; Costa, Dayana Bastos
    Industrialized construction (IC) has experienced significant achievements in the development of innovative construction methods in response to the demands of the construction industry. In this context, building information modeling (BIM) integrates and manages data throughout prefabrication phases (design, bid, and procurement) within an IC project. However, manual tasks such as data transfer between BIM models and enterprise resource planning (ERP) systems result in delays and errors due to the constant change of versions and large data flow between the involved parties. This research proposes the implementation of a novel method based on artificial intelligence (AI) to integrate the required information contained in elements in the BIM model with construction materials databases normally managed by ERP systems to procure and purchase materials in IC enterprises. Using a case study approach, this research presents a workflow with the proposed method whereas the results show that 81.57% of the elements were successfully identified, leading to a 63.47% reduction in the time compared to the manual assignment approach. Despite classifying a considerable percentage of the elements, it was identified that the implemented workflow depends on manual-dependent tasks during the design phase, such as modeling methodologies. This research contributes by providing new methods to improve IC projects and is expected to contribute to future research related to AI-based.
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    Heritage, resilience and climate change : A fuzzy logic application in timber-framed masonry buildings in Valparaiso, Chile
    (2020) Prieto Ibáñez, Andrés José; Verichev, K.; Carpio Martínez, Manuel