This study develops a comprehensive workflow for the analytical seismic vulnerability and structural performance assessment of a special-importance steel building located in a region of elevated seismic hazard in southern Spain. The work addresses the need for reliable analytical methodologies for facilities that must remain operational during earthquakes. The proposed framework integrates a probabilistic seismic hazard assessment, including uniform hazard spectra and hazard disaggregation to identify control earthquakes. Additionally, an analytical vulnerability assessment under the Spanish seismic design code, NCSE-02, is performed. Operational modal analysis and nonlinear analysis are combined to retrofit the numerical model of the building and capture the building’s realistic seismic response. The resulting demand spectra are derived from site-specific ground-motion scenarios for Los Barrios (Cádiz, Spain). Retrofitting strategies are designed and assessed to ensure compliance with the code-defined performance requirements. Results indicate that the retrofitted model reproduces the building’s dynamic behaviour with improved reliability, and that the strengthening interventions enhance seismic performance while still allowing moderate damage in specific components. These findings highlight the importance of analytical vulnerability approaches and code-oriented retrofitting when evaluating the seismic performance and vulnerability of essential facilities. The study demonstrates that rigorous analytical methods provide a robust basis for defining seismic vulnerability in special-importance buildings and support improved decision-making for structural safety and resilience.

Identification and classification of the different structures and infrastructures that make up a city (conventional buildings, power stations, nuclear power stations, routes of communication, etc.) are of great importance at the time of characterize their vulnerability and carry out estimates of seismic risk. Different types have different physical damage to some seismic movement, hence the importance of correctly assign a class of vulnerability. For this reason, it is necessary to know, updated form, the distribution and composition of structures and infrastructure of a city. Behaviour that presented these elements to a seismic phenomenon is linked, among others, building material and its geometric shape. Today, cadastral information updated about the infrastructure of a city does not have the data necessary and useful to carry out a calculation of seismic risk. For decades, the way of being able to have such information, has been through the development of campaigns of field for the elaboration of databases. This practice entails long time of work and the need for qualified personnel for the identification of the constructive typologies of the different structures. Nowadays, there are different geospatial techniques that allow data acquisition on a massive scale in a short time. In particular, by means of laser measurements, it is possible to have clouds of millions of points with geometric and radiometric information in a matter of seconds. This article presents a line of research whose main objective is to innovate in the vulnerability mapping and seismic risk estimation methods using geospatial techniques: static and dynamic laser. The end is contributing to knowledge and more accurate risk results, on which will be supported after the emergency plans that facilitate post event actions.

The current doctoral thesis focuses on innovating seismic risk assessments methods in buildings of special importance through the use of geospatial techniques. The main objective is to generate damage scenarios at a local scale for a building of special importance, ultimately aiming to enhance the definition of the vulnerability of these buildings by applying automation in the phase of geometric modelling from point clouds. The manuscript is divided into three main blocks. The first details the introduction to the research topic and an exhaustive analysis of the state of the art. The second block includes the methodology, research development, and results obtained. This block constitutes the most extensive and substantial part of the research. It is divided into four chapters. The first chapter, Chapter 3 of the thesis, on one hand, presents the developed algorithm, ABM-indoor, as a tool for automating the modelling of buildings from point clouds. On the other hand, includes the methodology to be followed for seismic risk assessments in buildings of special importance based on the calibration of the building model. The following three chapters constitute the application of all the concepts presented in Chapter 3. Chapter 4 presents the application of ABM-indoor to two different indoor scenarios: a parking lot and an office. Chapter 5 includes the application for seismic risk assessment in a manually modelled building of special importance. Finally, Chapter 6 presents the combination of the two previous applications: the use of ABM-indoor for defining the geometric model of a building of special importance (the same building used in Chapter 4) and seismic risk estimation for that building based on the calibrated model. Lastly, the third block of the thesis contains the general conclusions of the study and future lines of research. The application of the proposed methodology in this doctoral thesis has provided very positive results that validate the research. On one hand, ABM-indoor is an algorithm capable of automatically segmenting and modelling organized and unorganized point clouds from the interior and exterior of buildings. This algorithm has proven to be efficient and accurate in modelling buildings, providing detailed 3D models that are essential for conducting seismic risk assessments. On the other hand, the proposed methodology for seismic risk estimation based on the calibrated building model suggests that this approach could be extrapolated to larger-scale studies, encompassing a greater number of buildings, such as an entire city. RESUMEN La presente tesis doctoral se centra en innovar en los métodos de estimación del riesgo sísmico en edificaciones de importancia especial mediante el uso de técnicas geoespaciales. El objetivo principal es generar escenarios de daño a escala local, para un edificio de importancia especial, con el fin último de mejorar la definición de la vulnerabilidad de estos edificios mediante la aplicación de automatismos en la fase de modelización geométrica a partir de nubes de puntos. La estructura de la tesis se divide en tres bloques principales. El primero abarca una introducción detallada al tema de investigación y un análisis exhaustivo del estado del arte. El segundo bloque incluye la metodología, desarrollo de la investigación y resultados obtenidos. Este bloque constituye la parte más extensa y sustancial de la tesis doctoral. Está dividido en cuatro capítulos. El primer capítulo, Capítulo 3 de la memoria, por un lado, presenta el algoritmo desarrollado, ABM-indoor, como herramienta para la automatización de la modelización de edificios a partir de nubes de puntos. Por otro lado, define la metodología a seguir para la estimación del riesgo sísmico en edificios de importancia especial a partir de la calibración del modelo del edificio. Los tres capítulos siguientes constituyen la aplicación de todo lo expuesto en el Capítulo 3. El Capítulo 4 presenta la aplicación de ABM-indoor a dos escenarios interiores distintos: un aparcamiento y una oficina. El Capítulo 5 incluye la aplicación para la estimación de riesgo sísmico en un edificio de importancia especial modelado de forma manual. Por último, el Capítulo 6 presenta la combinación de las dos aplicaciones anteriores: uso de ABM-indoor para la definición del modelo geométrico de un edificio de importancia especial (mismo edificio que se ha usado en el Capítulo 4) y estimación del riesgo sísmico para ese edificio a partir del modelo calibrado. Por último, el tercer bloque de la memoria contiene las conclusiones generales del estudio y las futuras líneas de investigación. La aplicación de la metodología propuesta en la presente tesis doctoral ha proporcionado resultados muy positivos que validan la investigación. Por un lado, ABM-indoor es un algoritmo capaz de segmentar y modelar automáticamente nubes de puntos organizadas y no organizadas del interior y exterior de edificios. Este algoritmo ha demostrado ser eficiente y preciso en la modelización de edificaciones, proporcionando modelos 3D detallados que son fundamentales para realizar análisis de riesgo sísmico. Por otro lado, la metodología propuesta para la estimación del riesgo sísmico a partir del modelo calibrado del edificio sugiere que este enfoque podría extrapolarse a estudios a mayor escala, abarcando un mayor número de edificios, como una ciudad entera.