Evaluation of retrofitting techniques for historical adobe constructions using a multi-criteria decision analysis: The case study of Chile

• Autor(a) principal: Juliá, P. B.
• Data de Publicação: 2023
• Outros Autores: Stellacci, S., Poletti, E.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/29764
• topic: Historical adobe buildings; Multi-criteria decision analysis; Participatory analysis; Performance-based assessment; Retrofitting; Chile

The evaluation of retrofitting techniques against multiple (often conflicting) criteria requires an expert-driven approach with in-depth context-based knowledge. This research evaluates the expected performance of retrofitting techniques for historical adobe constructions by integrating literature-data and expert assessment. Consideration is given to performance-based criteria (structural behaviour, material compatibility), values around cultural built heritage (degree of intrusion, retreatability), and local constraints (cost-effectiveness). A multi-criteria decision analysis using MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation TecHnique) is undertaken in this study in order to facilitate the selection process for retrofitting techniques within distinct damage scenarios. The MACBETH model is applied to three historical adobe buildings in Chile using a weighted criteria matrix, while a sensitivity analysis is conducted to determine the stability of interventions. The best-scoring options for each damage pattern are then compared with national guidelines and the current practice. Among the best-ranking solutions obtained from MACBETH models, the use of wooden corner keys makes it possible to effectively counteract flexural cracks or mid-height cracks, damage at intersections of perpendicular walls, corner-damage vertical cracks, and in-plane damage. Wooden tie beams are effective solutions for corner-damage vertical cracks. Geo-mesh also obtains a high score yet is limited by its cost and low reversibility.