Abstract

This research presents a methodological process for selecting the most appropriate construction technique for the reconstruction of housing after a seismic disaster in a rural and heritage context. This process, which is applicable to a large part of the Andean region, incorporates sustainability criteria to guarantee the economic, social and environmental balance of the intervention. The methodology was developed on a case study: the Colca Valley in Arequipa, Peru. In 2016 an earthquake affected this zone, where traditional unreinforced earthen buildings suffered serious damage. The objective of this research focuses on comparing six traditional building techniques strongly related to self-building: four techniques for adobe housing—reinforced with cane (CRA), wire mesh (WMRA), geogrid (GRA) and halyard ropes (HRRA)—and two techniques for masonry buildings— confined (CM) and reinforced (RM). For this purpose the authors used the Integrated Value Model for Sustainable Assessment (MIVES), a Multiple Criteria Decision Analysis (MCDA) model used to compare alternatives by assigning a “sustainability index” to each evaluated construction technique. This research study includes two types of variables: quantitative, such as economy ($/m2) and environmental impact (kgCO2/m2), among others, and qualitative, such as perception of safety, respect for the urban image and popular knowledge. The research results show that reinforced adobe techniques are a viable and competitive option, highlighting the cane reinforced adobe technique (CRA), with a value of 0.714 in relation to industrialized materials such as masonry. This technique has the same safety characteristics, but at almost half the price, with the additional advantage of using traditional materials and construction methods, having less environmental impact and showing better thermal performance in cold climates.

Highlights

  • From 1970 to 2020, earthquakes in developing countries caused 1,015,000 deaths, affected 178,000,000 inhabitants and produced damages of 226 billion dollars [1]

  • Since 2000, Multiple Criteria Decision Analysis (MCDA) methods have gained importance in comparative evaluations of the construction sector, where the nature of the variables is increasingly complex and requires more rigorous decision-making methods in addition to adequate weighting criteria. These type of holistic evaluations have been driven by the need to approach the building process with a more comprehensive method; most of them are based on a life cycle assessment (LCA) using tools such as Eco-Quantum (The Netherlands), ATHENA (Canada), EcoEffect

  • Reinforced adobe techniques have the struction costs is considerably lower than reinforced mamasonry (RM) and confined masonry (CM)

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Summary

Introduction

From 1970 to 2020, earthquakes in developing countries caused 1,015,000 deaths, affected 178,000,000 inhabitants and produced damages of 226 billion dollars [1]. In Peru there is an interesting scientific literature on earth building construction, mainly focused on the use and characterization of adobe, highly focused on two specific aspects: an architectural point of view, considering historical premises and/or urban determinants, and an engineering point of view, which very strictly addresses structural and/or construction issues This situation generates proposals with a reduced range of action that leave aside decisive variables in the reconstruction processes, such as the economy, community participation and access to materials, essential requirements for contexts of special heritage value such as the Colca Valley. Peru represent isolated cases [16], their implementation is necessary in the public housing programs, as stated by one of the objectives of the current national housing and urban planning policy in Peru [17] In this sense, this research project focuses on reconstruction scenarios in rural populated centers susceptible to being affected by seismic events.

Evaluation
Case Study
Boundary Conditions
Characterization
Economic Indicators—R1
Environmental Indicators—R2
Social Indicators—R3
Evaluation Model
10. Evaluation
Section 4.4.
Analysis of Results n
Analysis of Results
Rating indicators for obtaining
13. Results
Conclusions
Full Text
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