Robust Flood Risk Analysis (FRA) is essential for effective flood risk management. The performance of any flood defence assets will heavily influence the estimate of an area's flood risk. It is therefore critical that the probability of a coastal flood defence asset incurring a structural failure when subjected to a particular loading i.e. its fragility is accurately quantified. The fragility representations of coastal defence assets presently adopted in UK National FRA (NaFRA) suffer three pertinent limitations. Firstly, assumptions relating to the modelling of the dependence structure of the variables that comprise the hydraulic load, including the water level, wave height and period, are restricted to a single loading variable. Consequently, due to the "system wide" nature of the analysis, a defence's conditional failure probability must also be expressed in terms of a single loading in the form of a fragility curve. For coastal defences the single loading is the overtopping discharge, an amalgamation of these basic loading variables. The prevalence of other failure initiation mechanisms may vary considerably for combinations of the basic loadings which give rise to equal overtopping discharges. Hence the univariate nature of the existing representations potentially restricts their ability to accurately assess an asset's structural vulnerability. Secondly, they only consider failure at least partially initiated through overtopping and thus neglect other pertinent initiation mechanisms acting in its absence. Thirdly, fragility representations have been derived for 61 generic assets (idealised forms of the defences found around the UK coast) each in five possible states of repair. The fragility representation associated with the generic asset and its state of repair deemed to most closely resemble a particular defence is adopted to describe its fragility. Any disparity in the parameters which influence the defence's structural vulnerability in the generic form of the asset and those observed in the field are also likely to further reduce the robustness of the existing fragility representations. In NaFRA coastal flood defence assets are broadly classified as vertical walls, beaches and embankments. The latter are typically found in sheltered locations where failure is water level driven and hence expressing failure probability conditionally on overtopping is admissible. Therefore new fragility representations for vertical wall and gravel beach assets which address the limitations of those presently adopted in NaFRA are derived. To achieve this aim it was necessary to propose new procedures for extracting information on the site and structural parameters characterising a defence's structural vulnerability from relevant resources (predominately beach profiles). In addition novel statistical approaches were put forward for capturing the uncertainties in the parameters on the basis of the site specific data obtained after implementation of the aforementioned procedures. A preliminary validation demonstrated the apparent reliability of these approaches. The pertinent initiation mechanisms behind the structural failure of each asset type were then identified before the state-of-the-art models for predicting the prevalence of these mechanisms during an event were evaluated. The Obhrai et al. (2008) re-formulation of the Bradbury (2000) barrier inertia model, which encapsulates all of the initiating mechanisms behind the structural failure of a beach, was reasoned as a more appropriate model for predicting the breach of a beach than that adopted in NaFRA. Failure initiated exclusively at the toe of a seawall was explicitly accounted for in the new formulations of the fragility representations using the predictors for sand and shingle beaches derived by Sutherland et al. (2007) and Powell & Lowe (1994). In order to assess whether the new formulations warrant a place in future FRAs they were derived for the relevant assets in Lyme Bay (UK). The inclusion of site specific information in the derivation of fragility representations resulted in a several orders of magnitude change in the Annual Failure Probabilities (AFPs) of the vertical wall assets. The assets deemed most vulnerable were amongst those assigned the lowest AFPs in the existing analysis. The site specific data indicated that the crest elevations assumed in NaFRA are reliable. Hence it appears the more accurate specification of asset geometry and in particular the inclusion of the beach elevation in the immediate vicinity of the structure in the overtopping calculation is responsible for the changes. The AFP was zero for many of the walls (≈ 77%) indicating other mechanism(s) occurring in the absence of any overtopping are likely to be responsible for failure. Toe scour was found to be the dominant failure mechanism at all of the assets at which it was considered a plausible cause of breach. Increases of at least an order of magnitude upon the AFP after the inclusion of site specific information in the fragility representations were observed at ≈ 86% of the walls. The AFPs assigned by the new site specific multivariate fragility representations to the beach assets were positively correlated with those prescribed by the existing representations. However, once the new representations were adopted there was substantially more variability in AFPs of the beach assets which had previously been deemed to be in identical states of repair. As part of the work, the new and existing fragility representations were validated at assets which had experienced failure or near-failure in the recent past, using the hydraulic loading conditions recorded during the event. No appraisal of the reliability of the new representations for beaches was possible due to an absence of any such events within Lyme Bay. Their AFPs suggest that armed with more information about an asset's geometry the new formulations are able to provide a more robust description of a beach's structural vulnerability. The results of the validation as well as the magnitude of the AFPs assigned by the new representations on the basis of field data suggest that the newly proposed representations provide the more realistic description of the structural vulnerability of seawalls. Any final conclusions regarding the robustness of the representations must be deferred until more failure data becomes available. The trade-off for the potentially more robust description of an asset's structural vulnerability was a substantial increase in the time required for the newly derived fragility representations to compute the failure probability associated with a hydraulic loading event. To combat this increase, (multivariate) generic versions of the new representations were derived using the structural specific data from the assets within Lyme Bay. Although there was generally good agreement in the failure probabilities assigned to the individual hydraulic loading events by the new generic representations there was evidence of systematic error. This error has the potential to bias flood risk estimates and thus requires investigation before the new generic representations are included in future FRAs. Given the disparity in the estimated structural vulnerability of the assets according to the existing fragility curves and the site-specific multivariate representations the new generic representations are likely to be more reliable than the existing fragility curves.

The American Society of Civil Engineers (ASCE) Standard 41-06 Supplement No.1 (2007) assists engineers in modeling and evaluating the non-linear behavior of structures till collapse. Different levels of conservatism were used throughout the standard to produce modeling parameters for different structural elements, which leads to inconsistencies at the system level. Task to update current ASCE 41-06 provisions pertaining to RC structures is now handled by ACI (American Concrete Institute) committee 369 entitled “Seismic Repair and Rehabilitation”. This study is a part of ACI 369 committee’s effort. Existing provisions for non-linear analysis are re-assessed in this study for both rectangular and circular reinforced concrete columns. A database of 490 column tests was compiled for this project. Median rather than conservative estimates of non-linear modeling parameters were produced to achieve “best” estimates of structural behavior. Proposed modeling parameters show improved fit with experimental data over existing parameters. Data necessary for selection of acceptance criteria are provided. / text

There are many calamitous events such as earthquakes, hurricanes, tsunamis etc. that occur suddenly and cause great loss of life, damage, or hardship. Hurricanes cause significant damage to power distribution systems, resulting in prolonged customer outages and excessive delays in the reconstruction efforts. Accordingly, predicting the effects of power outages on the performance of power distribution systems is of major importance to government agencies, utilities, and customers. Unfortunately, the current tools to predict the performance of power distribution systems during catastrophic events are limited in both the performance measures considered, as well as in their ability to model real systems. The main goal of this research is to develop a methodology for simulating hurricanes of different intensity on power distribution systems of small and medium size cities. Our study includes a detailed comparison between the engineering-based and connectivity-based models of power distribution systems, as well as the impact of power re-routing algorithms on the system reliability. Our approach is based on fragility curves that capture the ability of the system to withstand a range of wind speeds. In addition, we develop a multiscale approach that facilitates efficient computation of fragility curves for large cities. With this approach, hurricanes are simulated over small zones of a city and fragility curves are obtained. These are used to estimate the damage for identical zones throughout the city. To validate our techniques, two testbeds, Micropolis and Mesopolis, were used. Micropolis is synthetic model for a small city and Mesopolis for a big city. Obtained results have validated our approach and have shown that they can be used to effectively predict hurricane damage.

Damage observed after previous earthquakes indicates that a large number of existing buildings are vulnerable to seismic hazard. This research intends to assess seismic vulnerability of regular and irregular shear wall buildings in Canada, having different heights and different levels of seismic design and detailing. As seismic hazard is a probabilistic event, a probabilistic methodology has been adopted to assess the seismic vulnerability of the shear wall buildings. The proposed research encompasses a comprehensive fragility analysis for seismic vulnerability of shear wall buildings in Canada. The first phase of the investigation involves shear wall buildings with different heights (hence different structural periods), designed based on the 2010 National Building Code of Canada. The second phase involves shear wall buildings designed prior to 1975, representing pre-modern seismic code era. The third phase involves the evaluation of pre-1975 shear wall buildings with irregularities. 3-Dimensional simulations of the buildings were constructed by defining nonlinear modelling for shear wall and frame elements. These models were subjected to dynamic time history analyses conducted using Perform 3D software. Two sets of twenty earthquake records, compatible with western and eastern Canadian seismicity, were selected for this purpose. Spectral acceleration and peak ground acceleration were chosen as seismic intensity parameters and the first storey drift was selected as the engineering demand parameter which was further refined for irregular cases. The earthquake records were scaled to capture the structural behaviour under different levels of seismic excitations known as Incremental Dynamic Analysis. The resulting IDA curves were used as the input for seismic fragility analysis. Fragility curves were derived as probabilistic tools to assess seismic vulnerability of the buildings. These curves depict probability of exceeding immediate occupancy, life safety and collapse prevention limit states under different levels of seismic intensity.

La probabilité de défaillance d’une structure sous séisme est représentée à l’aide de « courbes de fragilité ». Pour les estimer, nous proposons d’enrichir une base de données pré-existante à l’aide du modèle de l’article de F. Poirion et I. Zentner, Stochastic model construction of natural hazards given experimental data, qui se fonde sur la représentation de Karhunen-Loève. Les signaux générés sont triés par classes d’indicateur de nocivité sismique à l’aide d’un algorithme de partitionnement de données. Malgré la ressemblance certaine que présentent plusieurs signaux simulés, et les conséquences que nous tirons de ce problème, ils sont soumis à la structure. Les signaux de réponses résultants sont eux aussi enrichis, en prenant en compte certaines incertitudes afin de construire un intervalle autour de la courbe. La méthode fonctionne pour tout indicateur de nocivité sismique, et permet de s’affranchir de plusieurs hypothèses simplificatrices courantes. Les caractéristiques du scénario sismique sont conservées lors de l’enrichissement, et le processus modélisant le mouvement du sol garde toute sa généralité. Notre démarche est validée d’abord sur un cas simple, puis sur un cas industriel. / The failure probability of a structure under earthquake is represented with « fragility curves ». To estimate them, we propose to enrich a pre-existing data basis using the model of the article Stochastic model construction of natural hazards given experimental data, written by F. Poirion et I. Zentner, which is based on the Karhunen-Loeve expansion. The generated signals are sorted by seismic indicator classes using a data partitioning algorithm. Despite the resemblance between some simulated signals, and the consequences we draw from this problem, the structure is submitted to them. The resulting response signals are also enriched, taking into account uncertainties to construct an interval around the curve. The method works for any seismic indicator, and overcomes several common simplifying assumptions. The characteristics of the seismic scenario are preserved during the enrichment, and the process modeling the ground motion retains its generality. Our approach is first validated on a simple case, then on an industrial case.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19340号 / 情博第592号 / 新制||情||103(附属図書館) / 32342 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 多々納 裕一, 教授 矢守 克也, 教授 守屋 和幸 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

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

With the increased push towards performance-based engineering (PBE) design, there is a need to understand and design more resilient building envelopes when subjected to natural hazards. Since architectural glass curtain walls (CW) have become a popular façade type, it is important to understand how these CW systems behave under extreme loading, including the relationship between damage states and loading conditions. This study subjects 3D computational models of glass CW systems to in- and out-of-plane loading simulations, which can represent the effects of earthquake or hurricane events. The analytical results obtained were used to support fragility curve development which could aid in multi-hazard PBE design of CWs. A 3D finite element (FE) model of a single panel CW unit was generated including explicit modeling of the CW components and component interactions such as aluminum-to-rubber constraints, rubber-to-glass and glass-to-frame contact interactions, and semi-rigid transom-mullion connections. In lieu of modeling the screws, an equivalent clamping load was applied with magnitude based on small-scale experimental test results corresponding to the required screw torque. This FE modeling approach was validated against both an in-plane racking displacement test and out-of-plane wind pressure test from the literature to show the model could capture in-plane and out-of-plane behavior effectively. Different configurations of a one story, multi-panel CW model were generated and subjected to in- and out-of-plane simulations to understand CW behavior at a scale that is hard to test experimentally. The structural damage states the FE model could analyze included: 1) initial glass-to-frame contact; 2) glass/frame breach; 3) initial glass cracking; 4) steel anchor yielding; and 5) aluminum mullion yielding. These were linked to other non-structural damage states related to the CW's moisture, air, and thermal performance. Analytical results were converted into demand parameters corresponding to damage states using an established derivation method within the FEMA P-58 seismic fragility guidelines. Fragility curves were then generated and compared to the single panel fragility curves derived experimentally within the FEMA P-58 study. The fragility curves within the seismic guidelines were determined to be more conservative since they are based on single panel CWs. These fragility curves do not consider: the effects of multiple glass panels with varying aspect ratios; the possible component interactions/responses that may affect the extent of damages; and the continuity of the CW framing members across multiple panels. Finally, a fragility dispersion study was completed to observe the effects of implementing the Derivation method or the Actual Demand Data method prescribed by FEMA P-58, which differ on how they account for different levels of uncertainty and dispersion in the fragility curves based on analytical results. It was concluded that an alternative fragility parameter derivation method should be implemented for fragility curves based on analytical models, since this may affect how conservative the analytically based fragility curves become at a certain probability of failure level. / Master of Science / Performance-based engineering (PBE) can allow engineers and building owners to design a building envelope for specific performance objectives and strength/serviceability levels, in addition to the minimum design loads expected. These envelope systems benefit from PBE as it improves their resiliency and performance during natural multi-hazard events (i.e. earthquakes and hurricanes). A useful PBE tool engineers may utilize to estimate the damages an envelope system may sustain during an event is the fragility curve. Fragility curves allow engineers to estimate the probability of reaching a damage state (i.e. glass cracking, or glass fallout) given a specified magnitude of an engineering demand parameter (i.e. an interstory drift ratio during an earthquake). These fragility curves are typically derived from the results of extensive experimental testing of the envelope system. However, computational simulations can also be utilized as they are a viable option in current fragility curve development frameworks. As it’s popularity amongst owners and architects was evident, the architectural glass curtain wall (CW) was the specific building envelope system studied herein. Glass CWs would benefit from implementing PBE as they are very susceptible to damages during earthquakes and hurricanes. Therefore, the goal of this computational research study was to develop fragility curves based on the analytical results obtained from the computational simulation of glass CW systems, which could aid in multi-hazard PBE design of CWs. As v opposed to utilizing limited, small experimental data sets, these simulations can help to improve the accuracy and decrease the uncertainties in the data required for fragility curve development. To complete the numerical simulations, 3D finite element (FE) models of a glass CW system were generated and validated against experimental tests. 11 multi-panel CW system configurations were then modeled to analyze their effect on the glass CW’s performance during in-plane and out-of-plane loading simulations. These parametric configurations included changes to the: equivalent clamping load, glass thickness, and glass-to-frame clearance. Fragility curves were then generated and compared to the single panel CW fragility curves derived experimentally within the FEMA P-58 Seismic Fragility Curve Development study. The fragility curves within FEMA P-58 were determined to be more conservative since they are based on single panel CWs. These fragility curves do not consider: the effects of multiple glass panels with varying aspect ratios; the possible component interactions/responses that may affect the extent of damages; and the continuity of the CW framing members across multiple panels. Finally, a fragility dispersion study was completed to observe the effects of implementing different levels of uncertainty and dispersion in the fragility curves based on analytical results.

<p>Developing countries typically suffer far greater than developed countries as a result of earthquakes. Poor socioeconomic conditions often lead to poorly constructed homes that are vulnerable to damage during earthquakes. Literature review in this study highlights the lack of existing fragility curves for buildings in developing countries. Furthermore, fragility curves derived using empirical data are almost nonexistent due to the scarcity of post-earthquake damage data and insufficient ground motion recordings in developing countries. Therefore, this research proposes a methodology for developing empirical fragility curves using ground motion data in the form of USGS ShakeMaps.</p> <p>The methodology has been applied to a case study consisting of damage data collected in Bantul Regency, Indonesia in the aftermath of the May 2006 Yogyakarta earthquake in Indonesia. Fragility curves for non-engineered single-storey unreinforced masonry (URM) homes have been derived using the damage dataset for three ground motion parameters; peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo-spectral acceleration (PSA). The fragility curves indicate the high seismic vulnerability of non-engineered URM homes in developing countries. There is a probability of 80% that a seismic event with a PGA of only 0.1g will induce significant cracking of the walls and reduction in the load carrying capacity of a URM home, resulting in moderate damage or collapse. Fragility curves as a function of PGA and PSA were found to reasonably represent the damage data; however, fits for several PGV fragility curves could not be obtained. The case study illustrated the extension of ShakeMaps to fragility curves, and the derived fragility curves supplement to the limited collection of empirical fragility curves for developing countries. Finally, a comparison with an existing fragility study highlights the significant influence of the derivation method used on the fragility curves. The diversity in construction techniques and material quality in developing countries, particularly for non-engineered cannot be sufficiently represented through simplified or idealized analytical models. Therefore, the empirical method is considered to be the most suitable method for deriving fragility curves for structures in developing countries.</p> / Master of Applied Science (MASc)

Buildings with torsional irregularity represent the main focus of many current investigations. However, despite this volume of research, there is no established framework that describes adequately the seismic vulnerability of reinforced concrete shear wall systems. In this study, the three-dimensional behavior of a particular shear-wall structure under earthquake effects was examined with regard to the nonlinear behavior of the reinforced concrete assembly and the parameters that characterize the structure exposed to seismic motion for damage assessment. A three story reinforced concrete shear-wall building was analyzed using the finite element method based ANSYS software. The scaled model building was subjected to shaking table tests at Saclay, France. The project was led by the Atomic Energy Agency (CEA Saclay, France) under the &ldquo / SMART 2008 Project.&rdquo / The investigation was conducted in two phases. In the first phase, the results of the finite element method and experiments were examined, and were reported in this study. For time history analysis, micro-modeling was preferred due to allowing inclusion the nonlinear effects of concrete and steel for analysis. The guiding parameters (acceleration, displacement, strain) of analytical results are compared with the corresponding values that were measured in the experiments to be able to quantify the validity of models and simulation. For the comparison of v the numerical model results with the experimental results FDE (Frequency Domain Error) method was used. After comparison of the numerical model results with the experimental results, the second phase of the SMART 2008 Project was undertaken. The second phase consisted of two parts summarized as &ldquo / Sensitivity Study&rdquo / and &ldquo / Vulnerability Analyses&rdquo / . However, in this report only the sensitivity study and fragility analyses will be reported. Sensitivity study was done to understand which parameters affect the response of the structure. Twelve parametric cases were investigated under two different ground motions. Different behavior parameters were investigated. The effective damping coefficient was found to affect the structural response at 0.2 g design level as well as at 0.6 g over-design level. At the design level, it was observed that elasticity modulus of concrete and additional masses on the specimen determined as effective on the calculated results. To derive the failure probabilities of this structure under various earthquake forces for the given limit states, fragility curves were obtained. Different seismic indicators such as PGA (Peak ground acceleration), PGV (Peak ground velocity), PGD (Peak ground displacement) and CAV (Cumulative absolute velocity) were used as seismic indicators and MISD (Maximum interstory drift) were used as damage indicator for fragility curves. In all 30 time history analyses were done. Regression analyses using least squares method were performed to determine the median capacity and its deviation. Correlation coefficients of the time history data versus fitted curves obtained from the regression analyses changes between 0.65 and 0.99. The lower cases were for PGD- MISD graphs. The scatter of the fragility curves calculated for each damage limit was slightly wider. HAZUS MH MR1 (2003) damage states were also used for the calculation of the fragility curves and compared with the SMART 2008 damage states.