Natural disasters are increasing in frequency and intensity, causing escalating humanitarian crises and complex housing challenges globally. Traditional post-disaster housing solutions often fall short, being slow, costly, and ill-adapted to specific community needs. This study addresses these limitations by proposing an innovative, technology-driven model for post-disaster housing that integrates parametric design with 3D printing. The objective is to develop a flexible and adaptable system capable of providing both immediate temporary shelter and evolving permanent housing solutions. In this study, the methodology of the proposed model for post-disaster housing solutions is structured around three main phases: the development of the theoretical framework, the parametric design process, and the implementation phase. In the first phase, a comprehensive literature review and conceptual analyses were conducted to examine the concept of disaster, post-disaster housing approaches, and advanced technologies, thereby establishing the conceptual foundation of the model. In the second phase, parametric modeling was carried out for a modular system using algorithmic design tools such as Grasshopper; the model’s applicability across various scales and its flexibility were analyzed. In the final phase, material selection and digital prototyping of the gridal system were undertaken using 3D printing technology to evaluate the model’s feasibility for rapid on-site production, assembly, and disassembly. The model prioritizes user participation, modularity, and configurability to ensure rapid response and socio-cultural sensitivity. Findings indicate that this integrated approach offers substantial benefits, including accelerated construction, reduced labor and material waste, enhanced design flexibility, and the use of local, sustainable materials. This research highlights the transformative potential of advanced manufacturing in providing resilient, user-centered, and environmentally sustainable post-disaster housing, advocating for governmental financial support to overcome adoption barriers and foster broader implementation.
Mehdizade et al. (Sat,) studied this question.