Emergency response teams, need various internal information about facilities such as building usage type, number of floors, occupancy information, building contents and vulnerable locations in facility during and immediately after multi hazard emergencies. Accessing such information accurately and timely is very important in order to speed up the guidance of occupants in a facility that is under the effect of multi-hazards to safe exits and speed up the decision process of emergency response teams to identify vulnerable locations (e.g. locations where secondary disasters can arise following an earthquake / fires, explosions). In the current practice, emergency response teams access such vital information to respond the emergency by visual investigating the environment and by asking the people in the neighborhood which causes gaining wrong and misleading information and results in loosing time and increasing the hazardous effect of emergency. Hence, there is a need for an approach to enable emergency response teams to access timely and accurate needed information items. To start the first step of this approach, the information items needed by emergency response teams to guide occupants the safe exits, to direct emergency response teams to vulnerable locations of the facility are identified and classified. Identified information items will be represented to emergency response teams by a model based system (BIM). The opportunities of model based system (BIM) will enable fast and safe evacuation of the facility, identification of vulnerable locations within the facility in a multi hazard emergency.

A probabilistic framework is developed to assess the structural reliability of offshore wind turbines. Probabilistic models are developed to predict the deformation, shear force and bending moment demands on the support structure of wind turbines. The proposed probabilistic models are developed starting from a commonly accepted deterministic model and by adding correction terms and model errors to capture respectively, the inherent bias and the uncertainty in developed models. A Bayesian approach is then used to assess the model parameters incorporating the information from virtual experiment data. The database of virtual experiments is generated using detailed three-dimensional finite element analyses of a suite of typical offshore wind turbines. The finite element analyses properly account for the nonlinear soil-structure interaction. Separate probabilistic demand models are developed for three operational/load conditions including: (1) operating under day-to-day wind and wave loading; (2) operating throughout earthquake in presence of day-to-day loads; and (3) parked under extreme wind speeds and earthquake ground motions. The proposed approach gives special attention to the treatment of both aleatory and epistemic uncertainties in predicting the demands on the support structure of wind turbines. The developed demand models are then used to assess the reliability of the support structure of wind turbines based on the proposed damage states for typical wind turbines and their corresponding performance levels. A multi-hazard fragility surface of a given wind turbine support structure as well as the seismic and wind hazards at a specific site location are incorporated into a probabilistic framework to estimate the annual probability of failure of the support structure. Finally, a framework is proposed to investigate the performance of offshore wind turbines operating under day-to-day loads based on their availability for power production. To this end, probabilistic models are proposed to predict the mean and standard deviation of drift response of the tower. The results are used in a random vibration based framework to assess the fragility as the probability of exceeding certain drift thresholds given specific levels of wind speed.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18563号 / 工博第3924号 / 新制||工||1603(附属図書館) / 31463 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 藤田 正治, 教授 中川 一, 准教授 竹林 洋史 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

There is a need to develop efficient multi-hazard performance based design (PBD) tools to analyze and optimize buildings at a preliminary stage of design. The first step was to develop a database and it is supported by five major contributions: 1) development of nomenclature of variables in PBD; 2) creation of mathematical model to fit data; 3) collection of data; 4) identification of gaps and methods for filling data in PBD; 5) screening of soil, foundation, structure, and envelope (SFSE) combinations.. A unified nomenclature was developed with the collaboration of a multi-disciplinary team to navigate through the PBD. A mathematical model for incremental dynamic analysis was developed to fit the existing data in the database in a manageable way. Three sets of data were collected to initialize the database: 1) responses of structures subjected to hazard; 2) fragility curves; 3) consequence functions. Fragility curves were critically analyzed to determine the source and the process of development of the curves, but structural analysis results and consequence functions were not critically analyzed due to lack of similarities between the data and background information respectively. Gaps in the data and the methods to fill them were identified to lay out the path for the completion of the database. A list of SFSE systems applicable to typical midrise office buildings was developed. Since the database did not have enough data to conduct PBD calculations, engineering judgement was used to screen SFSE combinations to identify the potential combinations for detailed analysis. Through these five contributions this thesis lays the foundation for the development of a database for multi- hazard PBD and identifies potential future work in this area. / Master of Science

Vulnerability to weather-related hazards is a considerable humanitarian, economic and environmental concern for cities, especially in developing countries. However, there is a limited understanding of urban vulnerability and its specific implications. This study assesses the spatio-temporal vulnerability caused by climatic and societal change in Chile’s key coastal urban areas. In this urban vulnerability assessment, both regional and local approaches were undertaken, the former to give a broad sense of the possible futures that these cities face and the latter to explore, using all available and reliable data, how climatic and societal change affected one of these metropolitan areas. For the time points 2025, 2055 and 2085, the regional assessment shows that vulnerability is likely to vary across different scenarios and time frames. A significant future increase in exposure to hazards is mainly moderated, to a greater or lesser extent, by an increase in the adaptive capacity of the cities in question. Cities in central and southern Chile are more vulnerable. The local assessment provides a detailed evaluation of recent past vulnerabilities in the Concepción Metropolitan Area (CMA). In the local assessment, an urban indicator framework was first designed and then employed to explore changes in exposure and sensitivity of areas within CMA and the general ability of the urban system to adapt to different hazards. Five weather-related hazards were explored: coastal flooding, fluvial flooding, water scarcity, heat stress and wildfire, using a flexible methodology based on spatial fuzzy modelling with geographic information systems. Hazard-specific vulnerability and overall vulnerability indices were created. The local assessment results indicate a high vulnerability in the CMA that decreased slightly between 1992 and 2002. The combined socio-economic factors of sensitivity and adaptive capacity influenced the index more than the biophysical factors of exposure. Changes in age structure and economic growth had a greater influence on vulnerability that other variables. Overall vulnerability varied across municipalities and hazards, with wildfires and water scarcity influencing overall vulnerability the most. Fuzzy modelling enabled realism and flexibility in the standardization and aggregation of indicators with different attributes. It permitted the exploration of the individual and aggregate influence of the indicators that comprise the indices. ArcGIS software favoured transparency and simplicity in the aggregation of multiple entry criteria, facilitating spatial representation through maps, which can help identify indicators, components and hazards or combinations thereof that influence municipal vulnerability. The results can be used to improve and promote dialogue among policy-makers and stakeholders regarding the prioritization of resources for urban development in ways that can reduce vulnerability to climate change.

The recent 2011 Tōhoku earthquake and tsunami served as a stark reminder of the destructive capabilities of such combined events. Civil Engineers are increasingly tasked with protecting coastal populations and infrastructure against more severe multi-hazard events. Whilst the protective measures must be robust, their deployment over long stretches of coastline necessitates an economical and environmentally friendly design. The dual row retaining wall concept, which features two parallel sheet pile walls with a sand infill between them and tie rods connecting the wall heads, is potentially an efficient and resilient system in the face of both earthquake and tsunami loading. Optimal use of the soil's strength and stiffness as part of the structural system is an elegant geotechnical solution which could also be applied to harbours or elevated roads. However, both the static equilibrium and dynamic response of these types of constructions are not well understood and raise many academic and practical challenges. A combination of centrifuge and numerical modelling was utilised to investigate the problem. Studying the mechanics of the walls in dry sand from the soil stresses to the system displacements revealed the complex nature of the soil structure interaction. Increased wall flexibility can allow more utilisation of the soil's plastic capacity without necessarily increasing the total displacements. Recognising the dynamically varying vertical effective stresses promotes a purer understanding of the earth pressures mobilised around the walls and may encourage a move away from historically used dynamic earth pressure coefficients. In a similar vein, the proposed modified Winkler method can form the basis of an efficient preliminary design tool for practice with a reduced disconnect between the wall movements and mobilised soil stresses. When founded in liquefiable soil and subjected to harmonic base motion, the dual row walls were resilient to catastrophic collapse and only accrued deformation in a ratcheting fashion. The experiments and numerical simulations highlighted the importance of relative suction between the walls, shear-induced dilation and regained strength outside the walls and partial drainage in the co-seismic period. The use of surrogate modelling to automatically optimise parameter selection for the advanced constitutive model was successfully explored. Ultimately, focussing on the mechanics of the dual row walls has helped further the academic and practical understanding of these complex but life-saving systems.

Critical Infrastructure Systems (CISs) are key for providing essential services and managing critical resources. The failure of one CIS can result in severe consequences on national security, health & safety, the environment, social well-being, and the economy. However, CISs are inherently complex, operating as systems-of-systems with dynamic, non-linear, and uncertain operation conditions, all geared towards fulfilling complex operational objectives. The complexity of both system architecture and operational objectives contributes to challenges in comprehending system-level behavior under normal and disruptive conditions. CISs are also highly exposed to multi-hazard environments characterized by probabilistic behaviors that can impact one or more system components—leading to diverse system failure modes. Understanding the dynamic interaction between hazards and the system response in such environments adds another layer of complexity to CISs safety. Addressing such complexity is crucial and it necessitates thorough investigations to ensure the continuous and reliable operation of CISs. Accordingly, the main objective of this thesis is to develop dynamic resilience quantification approaches for CISs in multi-hazard environments, considering the probabilistic behavior of both the hazard and the system. Given that dam infrastructure is one of the most significant CISs, this thesis employs an actual dam system as a demonstration application for the developed models. Nonetheless, it should be emphasized that the thesis focuses on the generalizability of the developed model to the CISs rather than the specificities related to dam systems, which are adopted herein merely to show the utility of the developed models to complex CISs. Specifically, this thesis first employs a meta-research approach (Chapter 2), using text analytics, to conduct a quantitative and qualitative review of extensive prior research focused on CISs operational safety, considering dam and reservoir systems as one of the key CISs. Such meta-research aims to unveil latent topics in the field and identify key opportunities for future research, particularly in addressing limitations associated with existing risk-based and resilience-based safety assessment approaches for CISs. To overcome such limitations, this thesis (Chapter 3) subsequently developed a coupled Continuous-Time Markov Chain and Bayesian network, facilitating the dynamic quantification of CISs failure risk (propagation of the system's probability of failure with time), considering the temporal variation of uncertainties in system components during operations. Starting from where the risk-based assessment ends (the immediate response of the system at the hazard realizations), resilience-based assessment focuses more on the dynamic system functionality gain/reduction and, subsequently, the system deterioration and recovery rates following hazard realizations. Accordingly, this thesis (Chapter 4) presents a resilience-centric System Dynamics simulation modeling approach capable of representing CISs components, estimating their dynamic system performance, and subsequent dynamic resilience (propagation of the system resilience with time). Such a modeling approach proposes a combinatorial procedure for generating multi-hazard scenarios, encompassing both natural and anthropogenic hazards, where one primary hazard can trigger one or more subsequent hazards. As a result, the developed models can investigate system operations under both single and multi-hazard environments. Furthermore, the coupling between System Dynamics and Monte Carlo simulations (Chapter 5) enables the model to seamlessly incorporate the probabilistic behaviors of both multi-hazard and system responses. The developed approaches can provide the decision-makers with a more detailed system representation that includes probabilistic dynamic system components with multi-operational objectives under probabilistic multi-hazard environments (Chapter 6). Moreover, the developed models can introduce more realistic evaluations for risk-adaptive and mitigation plans in real-time, contributing to more efficient safety assessment plans for the CISs. / Thesis / Doctor of Philosophy (PhD) / Critical infrastructure systems (CISs) play pivotal roles in delivering and supporting the essential needs of our daily lives. However, ensuring the safety of CISs poses layered challenges due to the complexity of their systems and operations, compounded by their susceptibility to multi-hazard environments, all with probabilistic behaviors. Recognizing the criticality and safety obstacles associated with CISs, this thesis introduces dynamics resilience quantification approaches for CISs safety based on a holistic system dynamics representation. The developed models are designed to enhance understanding of the system's performance under multi-hazard disruption conditions, considering the probabilistic behavior of both hazards and system response. Moreover, these models yield resilience-based metrics, allowing for the evaluation of the effectiveness of various risk mitigation plans, which would subsequently lead to more reliable safety assessment plans for CISs. Considering that dam infrastructure is a key CISs, this thesis focuses on the former as a demonstration application to show the developed models’ utility and their efficiency in devising resilience-guided assessment plans for CISs.

On-going population growth and urbanization increasingly force people to occupy environments where natural processes intensely affect the landscape, by way of potentially hazardous natural events. Tectonic plate boundaries, active volcanic regions and rapidly uplifting mountain ranges are prominent examples of geomorphically hazardous areas which today accommodate some of the world’s largest cities. These areas are often affected by more than one hazard such as volcanic eruptions, earthquakes, landslides, tsunamis, floods, storms and wildfires, which frequently interact with each other increasing the total impact on communities. Despite progress in natural hazards research over the last two decades, the increasing losses from natural disasters highlight the limitations of existing methodologies to effectively mitigate the adverse effects of natural hazards. A major limitation is the lack of effective hazard and risk assessments incorporating hazard interactions and cascade effects. Most commonly, the assessment of risks related to different hazards is carried out through independent analyses, adopting different procedures and time-space resolutions. Such approaches make the comparison of risks from different hazard sources extremely difficult, and the implicit assumption of independence of the risk sources leads to neglect of possible interactions among hazard processes. As a result the full hazard potential is likely to be underestimated and lead to inadequate mitigation measures or land-use planning. Therefore there is a pressing need to improve hazard and risk assessments and mitigation strategies especially in highly dynamic environments affected by multiple hazards. A prominent example of such an environment is the western Southern Alps of New Zealand. The region is located along an actively deforming plate boundary and is subject to high rates of uplift, erosion and orographically-enhanced precipitation that drive a range of interrelated geomorphic processes and consequent hazards. Furthermore, the region is an increasingly popular tourist destination with growing visitor numbers and the prospect for future development, significantly increasing societal vulnerability and the likelihood of serious impacts from potential hazards. Therefore the mountainous landscape of the western Southern Alps is an ideal area for studying the interaction between a range of interrelated geomorphic hazards and human activity. In an effort to address these issues this research has developed an approach for the analysis of geomorphic hazards in highly dynamic environments with particular focus on tectonically-active mountains using the western Southern Alps as a study area. The approach aims to provide a framework comprising the stages required to perform multi-hazard and risk analyses and inform land-use planning. This aim was approached through four main objectives integrating quantitative geomorphology, hazard assessments and GIS. The first objective was to identify the dominant geomorphic processes, their spatial distribution and interrelationships and explore their implications in hazard assessment and modelling. This was achieved through regional geomorphic analysis focusing on catchment morphometry and the structure of the drainage networks. This analysis revealed the strong influence and interactions between frequent landslides / debris-flows, glaciers, orographic precipitation and spatially-variable uplift rates on the landscape evolution of the western Southern Alps, which supports the need for hazard assessment approaches incorporating the interrelationships between different processes and accounting for potential event cascades. The second and third objectives were to assess the regional susceptibility to rainfall-generated shallow landslides and river floods respectively, as these phenomena are most often responsible for extensive damage to property and infrastructure, injury, and loss of lives in mountainous environments. To achieve these objectives a series of GIS-based models was developed, applied and evaluated in the western Southern Alps. Evaluation results based on historical records indicated that the susceptibility assessment of shallow landslides and river floods using the proposed GIS-based models is feasible. The output from the landslide model delineates the regional spatial variation of shallow landslide susceptibility and potential runout zones while the results from the flood modelling illustrate the hydrologic response of major ungauged catchments in the study area and identify flood-prone areas. Both outputs provide critical insights for land-use planning. Finally, a multi-hazard analysis approach was developed by combining the findings from the previous objectives based on the concepts of interaction and emergent properties (cascade effects) inherent in complex systems. The integrated analysis of shallow landslides, river floods and expected ground shaking from a M8 plate-boundary fault (Alpine fault) earthquake revealed the areas with the highest and lowest total susceptibilities. Areas characterized by the highest total susceptibility require to be prioritized in terms of hazard mitigation, and areas with very low total susceptibility may be suitable locations for future development. This doctoral research project contributes to the field of hazard research, and particularly to geomorphic hazard analyses in highly dynamic environments such as tectonically active mountains, aiming to inform land-use planning in the context of sustainable hazard mitigation.

Hydrogeological hazards are quite diffuse rainfall-induced phenomena that affect mountain regions and can severely impact these territories, producing damages and sometimes casualties. For this reason, hydrogeological risk reduction is crucial. Mitigation strategies aim to reduce hydrogeological risk to an acceptable level and can be classified into structural and non-structural measures. This work focuses on enhancing some non-structural risk mitigation measures for mountain areas: debris-flow rainfall thresholds, as a part of an Early Warning System (EWS), multivariate rainfall scenarios with multi-hazard mapping purpose and public awareness. Regarding debris-flow rainfall thresholds, an innovative calibration method, a suitable uncertainty analysis and a proper validation process are developed. The Backward Dynamical Approach (BDA), a physical-based calibration method, is introduced and a threshold is obtained for a study area. The BDA robustness is then tested by assessing the uncertainty in the threshold estimate. Finally, the calibrated threshold's reliability and its possible forecast use are assessed using a proper validation process. The findings set the stage for using the BDA approach to calibrate debris-flow rainfall thresholds usable in operational EWS. Regarding hazard mapping, a multivariate statistical model is developed to construct multivariate rainfall scenarios with a multi-hazards mapping purpose. A confluence between a debris-flow-prone creek and a flood-prone river is considered. The multivariate statistical model is built by combining the Simplified Metastatistical Extreme Value approach and a copula approach. The obtained rainfall scenarios are promising to be used to build multi-hazard maps. Finally, the public awareness within the LIFE FRANCA (Flood Risk ANticipation and Communication in the Alps) European project is briefly considered. The project action considered in this work focuses on training and communication activities aimed at providing a multidisciplinary view of hydrogeological risk through the holding of courses and seminars.

Fires following earthquake (FFE) have historically produced enormous post-earthquake damage and losses in terms of lives, buildings and economic costs, like the San Francisco earthquake (1906), the Kobe earthquake (1995), the Turkey earthquake (2011), the Tohoku earthquake (2011) and the Christchurch earthquakes (2011). The structural fire performance can worsen significantly because the fire acts on a structure damaged by the seismic event. On these premises, the purpose of this work is the investigation of the experimental and numerical response of structural and non-structural components of steel structures subjected to fire following earthquake (FFE) to increase the knowledge and provide a robust framework for hybrid fire testing and hybrid fire following earthquake testing. A partitioned algorithm to test a real case study with substructuring techniques was developed. The framework is developed in MATLAB and it is also based on the implementation of nonlinear finite elements to model the effects of earthquake forces and post-earthquake effects such as fire and thermal loads on structures. These elements should be able to capture geometrical and mechanical non-linearities to deal with large displacements. Two numerical validation procedures of the partitioned algorithm simulating two virtual hybrid fire testing and one virtual hybrid seismic testing were carried out. Two sets of experimental tests in two different laboratories were performed to provide valuable data for the calibration and comparison of numerical finite element case studies reproducing the conditions used in the tests. Another goal of this thesis is to develop a fire following earthquake numerical framework based on a modified version of the OpenSees software and several scripts developed in MATLAB to perform probabilistic analyses of structures subjected to FFE. A new material class, namely SteelFFEThermal, was implemented to simulate the steel behaviour subjected to FFE events.