Uncertainty Quantification; |

Metodologia per la valutazione del rischio sismico integrata coi processi di recupero delle strutture mediante stima delle incertezze

Wed, 14 Jan 2026 00:00:00 +0000

ingenio

Alla pagina e intervista su : novita’ dal convegno ANIDIS 2025.

Riferimenti

Click the Cite button above to copy .bib publication metadata into your notes.
or directly download here either the bibtex version: Download BibTeX or the plain text one: Download Plain.txt

Adaptive regional seismic risk assessment under uncertainty: a case study in the Alto Garda area

Sun, 14 Sep 2025 00:00:00 +0000

Abstract

A reliable national and regional risk assessment is essential for researchers, practitioners, and decision-makers. Seismic risk assessment is crucial for evaluating earthquake-induced damage to structures, infrastructure, and society. However, it cannot be effectively performed without properly managing uncertainty. In this context, hazard models and vulnerability analysis are the two critical pillars that contribute most to improving risk management, infrastructure planning, and disaster response. In this work, we present an adaptive risk assessment framework for the Alto Garda area, located in northern Italy. Leveraging newly available microzonation data and advanced hazard analysis within OpenQuake engine, the study achieves high spatial resolution at a local scale. Historical earthquake records, cadastral data, open-source maps, and satellite imagery are integrated to (i) compile a comprehensive building taxonomy and (ii) dynamically refine vulnerability models. Additionally, both aleatoric and epistemic uncertainties are carefully considered using a logic tree approach applied to both hazard and fragility analysis. Moreover, an adaptive approach is implemented, meaning that as new information becomes available, updates are seamlessly integrated to enhance accuracy and refine models. By combining hazard and vulnerability maps, the study delivers a first semiquantitative risk evaluation for the region. This approach highlights the potential of adaptive methodologies in improving seismic risk mitigation strategies and strengthening decision-making under uncertainty.

Tip

Click the Cite button above to copy .bib publication metadata into your notes.
or directly download here either the bibtex version: Download BibTeX or the plain text one: Download Plain.txt

UQ based state-dependent framework for recovery and seismic risk assessment

Sun, 14 Sep 2025 00:00:00 +0000

Abstract

Recovery processes and seismic risk assessment represent a critical and challenging frontier in engineering risk analysis under uncertainty. Despite growing attention, the problem remains inherently complex, shaped by nonlinear system behaviours and high-dimensional stochastic spaces. These difficulties are compounded by the limited availability and often confidential nature of recovery data, highlighting the urgent need for modelling approaches that are not only efficient, but also flexible enough to adapt to real-world constraints. In this work, we introduce a novel framework that explicitly integrates recovery into state-dependent seismic risk assessment. The approach combines fragility modelling, recovery processes, and hazard evaluation into a cohesive structure, enabling holistic and reliable risk analysis. Designed for flexibility, the framework draws from the state-of-the-art in different disciplines, such as structural engineering, recovery modelling and probabilistic seismic modelling, and focuses on balancing adaptability and computational efficiency. At the core of the methodology is a state-dependent seismic risk model that embeds recovery through a Continuous-Time Markov Chain (CTMC) framework. This enables the joint evaluation of damage progression and recovery over time. Spectral analysis of the reduced transition matrix allows for reliability-based metrics. The framework is applied to a full-scale industrial steel frame from the European SPIF project, tested under seismic loading at EUCENTRE, demonstrating its ability to capture resilience dynamics with computational efficiency.

Tip

Click the Cite button above to copy .bib publication metadata into your notes.
or directly download here either the bibtex version: Download BibTeX or the plain text one: Download Plain.txt