Digital Optimization of Public Assets for Enhanced Resilience to Socioeconomic and Environmental Disruptions

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Abstract

The escalating impacts of anthropogenic activities and natural disasters, aggravated by economic crises, have amplified the vulnerability of environmental and territorial systems, leading to significant urban planning and social implications. Consequently, numerous public and private buildings have been abandoned, necessitating crucial reorganizations or repurposing to prevent degradation and obsolescence due to disuse. The imperative goal is to foster resilience within territories, primarily by enhancing the adaptability of urban assets to altered conditions induced by both natural and anthropogenic disturbances, thereby increasing their inherent flexibility to offer functional responses to disruptions. This approach aims to mitigate adverse effects, expedite restoration of the status quo or augment the adaptability of structures, particularly public and strategic ones, during extraordinary phases. The proposed methodology for fortifying solidity and fostering resistance to change in the built environment involves digital cataloguing of heritage through the creation of three-dimensional models of structures. This process, known as Building Information Modelling (BIM), is predicated on a preliminary analysis of structural, architectural, and plant engineering data, which is beneficial for both ordinary and atypical management. The result is an efficient system that offers facility management opportunities for structures throughout their lifecycle and facilitates optimization of resource use. It aids in evaluating the extraordinary use of assets, examining various performance hypotheses for each scenario, understanding the time required for system setup, and determining relative economic indicators until the restoration of the preceding state.

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APA

Rainaldi, M. (2023). Digital Optimization of Public Assets for Enhanced Resilience to Socioeconomic and Environmental Disruptions. International Journal of Environmental Impacts, 6(3), 129–134. https://doi.org/10.18280/ijei.060305

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