Establishment of relationships for predicting the lateral drift demands of near-fault ground motions is one of the major challenges in earthquake engineering. Excessive lateral drifts caused by earthquake ground motions are the major causes of structural damage observed in structures. In this study, some of the fundamental characteristics of near-fault ground motions are examined. Response characteristics of elastic frame structures to near-fault ground motions are investigated. An approximate method for estimating the elastic ground story and interstory drifts for regular frame type structures is presented. Inelastic displacement demands imposed on elasto-plastic single degree of freedom (SDOF) systems subjected to near-fault ground are examined. Three equations for estimating the maximum lateral inelastic displacement demand from the maximum elastic displacement demand are established. Two of these equations relate the inelastic and elastic displacement demands through natural period and strength reduction factor. The third equation relates the inelastic and elastic displacement demands through the ratio of natural period to pulse period and the strength reduction factor. Efficiency of the natural period to pulse period ratio for estimating the inelastic displacement ratio is shown. Error statistics of the proposed equations are presented and compared with similar studies in the literature. According to the results, these equations can be used for quick and rough estimates of displacement demands imposed on regular elastic moment resisting frames and elasto-plastic single degree of systems.

The functionality of the transportation network following an earthquake event is critical for post-earthquake response and long-term recovery. The likely performance of a transportation network can be evaluated through a detailed seismic risk assessment. This paper presents an assessment of the seismic risk to the transportation network in the City of Charleston and the surrounding counties to support emergency response and the development of mitigation strategies and emergency planning efforts (such as lifeline selections). This study includes an inventory analysis of the 375 bridges in the Charleston area, and convolution of the seismic hazard with fragility curves analytically derived for classes of bridges common to this part of the country, damage-functionality relationships, and replacement cost estimates using relevant region-specific data. Using state-of-the-art tools, the distribution of potential bridge damage and functionality is evaluated for several scenario events, in order to aid in the identification of emergency routes and assess areas for investment in retrofit. Additionally, a sensitivity study is conducted to determine the criticality of a few of the different input models. Initial estimates of economic losses are assessed and preliminary recommendations for prioritizing retrofit are presented.

Cette thèse est consacrée à une analyse approfondie de la capacité des "réseaux de neurones artificiels" (RNA) à la prédiction des mouvements sismiques. Un premier volet important concerne la dérivation par RNA de "GMPE" (équations de prédiction du mouvement du sol) et la comparaison des performances ainsi obtenues avec celles des GMPE "classiques" obtenues sur la base de régressions empiriques avec une forme fonctionnelle préétablie (plus ou moins complexe). Pour effectuer l’étude comparative et obtenir les deux composnates inter-événement « betweeen-event » et intra-événement « within-event » de la variabilité aléatoire, nous intégrons l’algorithme du « modèle à effets aléatoires » à l’approche neuronale. Cette approche est testée sur différents jeux de données réelles et synthétiques : la base de données compilée à partir d'événements européens, méditerranéens et du Moyen-Orient (RESORCE : Reference database for Seismic grOund-motion pRediction in Europe), la base de données NGA-West 2 (Next Generation Attenuation West 2 développée aux USA), la base de données japonaise dérivée du réseau accélérométrique KiK-net. En outre, un set de données synthétiques provenant d'une approche par simulation stochastique est utilisé. Les paramètres du mouvement du sol les plus utilisés en génie parasismique (PGA, PGV, spectres de réponse et également, dans certains cas, les fonctions d'amplification locales) sont considérés. Les modèles neuronaux ainsi obtenus, complètement dirigés par les données « data-driven », nous renseignent sur les influences respectives et éventuellement couplées de l’atténuation avec la distance, de l'effet d’échelle lié à la magnitude, des conditions de site et notamment la présence éventuelle de non-linéarités. Un autre volet important est consacré à l'utilisation des RNA pour tester la pertinence de différents proxies de site, au travers de leur capacité à réduire la variabilité aléatoire des prédictions de mouvement du sol. Utilisés individuellement ou en couple, ces proxies de site décrivent de manière plus ou moins détaillée l'influence des conditions de site locales sur le mouvement sismique. Dans ce même volet, nous amorçons également une étude des liens entre les aspects non-linéaire de la réponse de site, et les différents proxies de site. Le troisième volet se concentre sur certain effets liés à la source : analyse de l’influence du style de la faille sismique sur le mouvement du sol, ainsi qu'une approche indirecte de la dépendance entre la magnitude et la chute de contrainte sismique. / This thesis is devoted to an in-depth analysis of the ability of "Artificial Neural Networks" (ANN) to achieve reliable ground motion predictions. A first important aspect concerns the derivation of "GMPE" (Ground Motion Prediction Equations) with an ANN approach, and the comparison of their performance with those of "classical" GMGEs derived on the basis of empirical regressions with pre-established, more or less complex, functional forms. To perform such a comparison involving the two "betweeen-event" and "within-event" components of the random variability, we adapt the algorithm of the "random effects model" to the neural approach. This approach is tested on various, real and synthetic, datasets: the database compiled from European, Mediterranean and Middle Eastern events (RESORCE: Reference database for Seismic grOund-motion pRediction in Europe), the database NGA West 2 (Next Generation Attenuation West 2 developed in the USA), and the Japanese database derived from the KiK-net accelerometer network. In addition, a comprehensive set of synthetic data is also derived with a stochastic simulation approach. The considered ground motion parameters are those which are most used in earthquake engineering (PGA, PGV, response spectra and also, in some cases, local amplification functions). Such completely "data-driven" neural models, inform us about the respective, and possibly coupled, influences of the amplitude decay with distance, the magnitude scaling effects, and the site conditions, with a particular focus on the detection of non-linearities in site response. Another important aspect is the use of ANNs to test the relevance of different site proxies, through their ability to reduce the random variability of ground motion predictions. The ANN approach allows to use such site proxies either individually or combined, and to investigate their respective impact on the various characteristics of ground motion. The same section also includes an investigation on the links between the non-linear aspects of the site response and the different site proxies. Finally, the third section focuses on a few source-related effects: analysis of the influence of the "style of faulting" on ground motion, and, indirectly, the dependence between magnitude and seismic stress drop.

Coastal cliff erosion is a widespread problem that threatens property and infrastructure along many of the world’s coastlines. The management of this risk calls for robust quantification of cliff erosion rates, which are often difficult to obtain along rocky coasts. Quantification of sea-cliff rates of retreat on annual to decadal time scales has typically been limited to rapidly eroding soft rock coastlines. Rates of erosion used for shoreline management in the UK are generally based on analysis of historic maps and aerial photographs which, in rocky coast environments, does not wholly capture the detail and timing at which the processes operate and the failures occur across the cliff face. The first stage of this study uses airborne LiDAR (Light Detection and Ranging) data at nine sites around a rocky coastline (Cornwall, UK) to gain a quantitative understanding of cliff erosion where average recession rates are relatively low (c. 0.1 m yr-1). It was found that three-dimensional volumetric changes on the cliff face and linear rates of retreat can be reliably calculated from consecutive digital elevation models (DEMs) several years apart. Rates of erosion ranged between 0.03–0.3 m yr-1. The spatial variability in recession rates was considered in terms of the relationship with the varying boundary conditions (rock mass characteristics, cliff geometries, beach morphology) and forcing parameters (wave climate and wave exposure). Recession rates were statistically correlated with significant wave height (Hs), rock mass characteristics (GSI) and the ratio between the two (GSI/Hs). Although the rates derived using airborne LiDAR are comparable to the longer term rates of retreat, the detail of erosion to the cliff-face provides additional insight into the processes occurring in slowly eroding environments, which are vital for understanding the failure of harder rock coastlines. In addition to this, the importance of the wave climate and rainfall needs further attention on a more localised scale. Monthly cliff face volume changes, at two particularly vulnerable sites (Porthleven and Godrevy, Cornwall, UK), were detected using a Terrestrial Laser Scanner (TLS). Using these volumes alongside information on beach profile, beach- cliff junction elevation changes and nearshore hydrodynamics have allowed an insight into how the cliffs respond to seasonal fluctuations in wave climate and beach morphology. Monthly variability in beach morphology between the two sites over a one-year survey period i  indicated the influence that beach slope and the elevation of the beach-cliff junction have on the frequency of inundation and the power of wave-cliff impacts. Failure mechanisms between the two sites ranged from rotational sliding of superficial material to quarrying and block removal over the entire cliff elevation, according to the extent of wave-cliff interaction. This particular survey period highlighted the sensitivity of cliff erosion to the variability in wave climate and beach morphology at two different locations in the south-west of the UK, where the vast majority (over 85% of the annual value) of cliff face erosion occurs during the winter when extreme storm waves prevail. Coastal cliff erosion from storm waves is observed worldwide but the processes are notoriously difficult to measure during extreme storm wave conditions when most erosion normally occurs, limiting our understanding of cliff processes. Over January-March 2014, during the largest Atlantic storms in at least 60 years with deep water significant wave heights of 6 – 8 m, cliff-top ground motions of a rocky cliff in the south-west of the UK (Porthleven, Cornwall) showed vertical ground displacements in excess of 50–100 μm; an order of magnitude larger than observations made previously. Repeat terrestrial laser scanner surveys, over a 2-week period encompassing the extreme storms, gave a cliff face volume loss 2 orders of magnitude larger than the long-term erosion rate. Cliff-top ground motions and erosion volumes were compared at two different locations, one a reflective beach with steeply shelving bathymetry (Porthleven, Cornwall) and the other an intermediate, low tide bar-rip beach with a wide coastal slope (Godrevy, Cornwall). Under similar wave conditions (6–8 m Hs and 15–20 s. Tp) the vertical ground motions were an order of magnitude greater at the cliffs fronted by steeply shelving bathymetry, where the breaking waves plunge right at the shoreline, with little prior dissipation, leading to large energetic runup impacting the cliff. These storm results imply that erosion of coastal cliffs exposed to extreme storm waves is highly episodic and that long-term rates of cliff erosion will depend on the frequency and severity of extreme storm wave impacts as well as the wave dissipation that occurs as a function of the nearshore bathymetry. Having recorded microseismic cliff-top motion on this scale for the first time and determined an effective method of monitoring the energetic wave impacts, this study emphasises how investigations of cliff behaviour during storms is not only obtainable, but paramount to understanding coastal evolution under extreme conditions.

A fragility function quantifies the probability that a structural system reaches an undesirable limit state, conditioned on the occurrence of a hazard of prescribed intensity level. Multiple sources of uncertainty are present when estimating fragility functions, e.g., record-to-record variation, uncertain material and geometric properties, model assumptions, adopted methodologies, and scarce data to characterize the hazard. Advances in the last decades have provided considerable research about parameter selection, hazard characteristics and multiple methodology for the computation of these functions. However, there is no clear path on the type of methodologies and data to ensure that accurate fragility functions can be computed in an efficient manner. Fragility functions are influenced by the selection of a methodology and the data to be analyzed. Each selection may lead to different levels of accuracy, due to either increased potential for bias or the rate of convergence of the fragility functions as more data is used. To overcome this difficulty, it is necessary to evaluate the level of agreement between different statistical models and the available data as well as to exploit the information provided by each piece of available data. By doing this, it is possible to accomplish more accurate fragility functions with less uncertainty while enabling faster and widespread analysis. In this dissertation, two methodologies are developed to address the aforementioned challenges. The first methodology provides a way to quantify uncertainty and perform statistical model selection to compute seismic fragility functions. This outcome is achieved by implementing a hierarchical Bayesian inference framework in conjunction with a sequential Monte Carlo technique. Using a finite amount of simulations, the stochastic map between the hazard level and the structural response is constructed using Bayesian inference. The Bayesian approach allows for the quantification of the epistemic uncertainty induced by the limited number of simulations. The most probable model is then selected using Bayesian model selection and validated through multiple metrics such as the Kolmogorov-Smirnov test. The subsequent methodology proposes a sequential selection strategy to choose the earthquake with characteristics that yield the largest reduction in uncertainty. Sequentially, the quantification of uncertainty is exploited to consecutively select the ground motion simulations that expedite learning and provides unbiased fragility functions with fewer simulations. Lastly, some examples of practices during the computation of fragility functions that results i n undesirable bias in the results are discussed. The methodologies are implemented on a widely studied twenty-story steel nonlinear benchmark building model and employ a set of realistic synthetic ground motions obtained from earthquake scenarios in California. Further analysis of this case study demonstrates the superior performance when using a lognormal probability distribution compared to other models considered. It is concluded by demonstrating that the methodologies developed in this dissertation can yield lower levels of uncertainty than traditional sampling techniques using the same number of simulations. The methodologies developed in this dissertation enable reliable and efficient structural assessment, by means of fragility functions, for civil infrastructure, especially for time-critical applications such as post-disaster evaluation. Additionally, this research empowers implementation by being transferable, facilitating such analysis at community level and for other critical infrastructure systems (e.g., transportation, communication, energy, water, security) and their interdependencies.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22259号 / 理博第4573号 / 新制||理||1657(附属図書館) / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 James Mori, 教授 久家 慶子, 教授 岩田 知孝 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24603号 / 工博第5109号 / 新制||工||1977(附属図書館) / 京都大学大学院工学研究科建築学専攻 / (主査)教授 松島 信一, 教授 竹脇 出, 教授 池田 芳樹 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

A new methodology is proposed to perform nonlinear time domain analysis on three-dimensional reinforced concrete bridge structures subjected to spatially varying seismic ground motions. A stochastic algorithm is implemented to generate unique and correlated time history records under each bridge support to model the spatial variability effects of seismic wave components traveling in the longitudinal and transverse direction of the bridge. Three-dimensional finite element models of highway bridges with variable geometry are considered where the nonlinear response is concentrated at bidirectional plastic hinges located at the pier end zones. The ductility demand at each pier is determined from the bidirectional rotations occurring at the plastic hinges during the seismic response evaluation of the bridge models. Variability of the soil characteristics along the length of the bridge is addressed by enforcing soil response spectrum compatibility of the generated time history records and of the dynamic stiffness properties of the spring sets modeling soil rigidity at the soil-foundation interface at each support location. The results on pier ductility demand values show that their magnitude depends on the type of soil under the pier supports, the pier location and the overall length and geometry of the bridge structure. Maximum ductility demand values were found to occur in piers supported on soft soils and located around the mid span of long multi-span bridges. The results also show that pier ductility demand values in the transverse direction of the bridge can be significantly different than the values in the longitudinal direction and in some instances, the maximum value occurs in the transverse direction. Moreover, results also show that ignoring the effects of spatial variability of the seismic excitation, the pier ductility demand can be severely underestimated. Finally, results show that increasing the vertical acceleration component in the seismic wave will generate an increase in the pier axial loads, which will reduce the ductility range of the pier plastic zones. As result, even though the increase in pier ductility demand associated with the increase in the vertical acceleration component was found to be relatively small, the number piers exhibiting significant structural damage increased.

Les couches de sol présentent fréquemment des hétérogénéités spatiales qui proviennent des processus d’érosion, de sédimentation et de l’effet de l’activité humaine. A ces hétérogénéités géologiques de premier ordre viennent s’ajouter des hétérogénéités de petite échelle au sein d’une même couche géologique. Sous sollicitation sismique faible ou forte, ces hétérogénéités spatiales des propriétés du sous-sol sont susceptibles de conduire à une variabilité spatiale importante des propriétés du mouvement sismique en surface (amplitude, durée, contenu fréquentiel, …). Dans cette thèse, une analyse probabiliste est réalisée pour évaluer l’effet de la variabilité spatiale de la vitesse des ondes de cisaillement (V_s) sur la variabilité du mouvement sismique en surface. Pour simplifier, une simple structure de sol 2D (une couche sédimentaire sur un demi-espace) est considérée. La structure 2D de V_s est modélisé comme un champ aléatoire en utilisant la méthode EOLE (Expansion Optimal Linear Estimation) et 9 modèles probabilistes sont considérés en faisant varier les trois paramètres de fluctuation du sol: le coefficient de variation (COV) sur V_s, les distances d'autocorrélation horizontale (θ_x) et verticale (θ_z). Les mouvements sismiques du sol en surface sont simulés à l’aide du logiciel de différences finies FLAC2D pour une excitation d'onde plane avec une polarisation SV.Une première partie porte sur l’étude de la variabilité en surface de différents indicateurs du mouvement sismique (fréquence de résonance, amplification, Intensité d’Arias, durée, corrélation spatiale). Nos simulations purement linéaires soulignent l’importance des ondes de surface diffractées localement au niveau des hétérogénéités du sol sur ces différents indicateurs et le contrôle de COV sur leur variabilité. Elles mettent également en évidence que, bien que les approches probabilistes 1D reproduisent correctement en moyenne les fréquences de résonance fondamentales et les amplifications associées, elles sous-estiment l’amplification à haute fréquence, l’Intensité d’Arias et la durée du mouvement sismique ainsi que leur variabilité. La deuxième partie porte sur la cohérence spatiale, calculée sur la phase forte et sur la coda des vitesses simulées en surface. Les résultats montrent que la perte de cohérence avec la fréquence ou la distance est principalement contrôlée par COV. A cette perte de cohérence globale s’ajoute la présence de fortes cohérences dans certaines bandes de fréquences étroites causées par les caractéristiques de propagation d’ondes de volume et de surface (résonance des ondes SV, phases d’Airy des ondes de Rayleigh). Ces observations sont cohérentes avec les observations sur les données réelles du site d’Argostoli en Grèce. La troisième partie s’intéresse à la prise en compte du comportement non-linéaire des sols. Le comportement non-linéaire du sol est basé sur des tests triaxiaux effectués sur la plaine alluviale de Nahr Beyrouth. L’effet du comportement non-linéaire et de sa variabilité est étudié pour les différents indicateurs du mouvement sismique (Intensité d’Arias, durée, corrélation spatiale, cohérence décalée). / Soil layers frequently exhibit spatial heterogeneities that arise from the erosion, sedimentation processes and from the effects of human activity. To these first order geological heterogeneities are added small-scale heterogeneities within the same geological layer. Under weak or strong seismic loading, these spatial heterogeneities of the subsurface properties are likely to lead to a significant variability in the ground motion properties within short distance on surface (amplitude, duration, frequency content, ...). In this thesis, a probabilistic analysis is carried out to evaluate the effect of the spatial variability of shear wave velocity (V_s) on the variability of surface seismic response. For sake of simplicity, a simple 2D soil structure (a sedimentary layer over a half-space) is considered. The 2D structure of V_s is modeled as a random field using the EOLE (Expansion Optimal Linear Estimation) method and nine probabilistic models are considered by varying the three soil fluctuation parameters: the coefficient of variation (COV) on V_s, the horizontal and vertical autocorrelation distances (θ_x and θ_z, respectively). The surface ground seismic motion is simulated using the FLAC2D finite difference code using a SV plane-wave plane excitation.The first part deals with the study of the surface variability of different ground motion indicators (resonance frequency, amplification, Arias intensity, duration, spatial correlation). Our purely linear simulations emphasize the importance of the locally diffracted surface waves due to soil heterogeneities on these different indicators and the control of COV on their variability. They also show that, although 1D probabilistic approaches correctly estimate the average of the fundamental resonant frequencies and the associated amplifications, they underestimate the high frequency amplification, the Arias intensity and the duration of the ground motion on surface, as well as their variability. The second part deals with another estimator the ground motion spatial variability: the coherency and it is calculated on the strong phase and on the coda of simulated seismograms on surface. The results show that the variation of the coherency as a function of frequency or distance is mainly controlled by COV. To this overall behavior of the average coherency on surface is superimposed the presence of strong loss or increase of coherency in certain narrow frequency bands caused by the propagation characteristics of body and surface waves (resonance of SV waves, Airy phases of Rayleigh waves). These observations are consistent with the observations on real data from the Argostoli site in Greece. The third part focuses on taking into account the non-linear behavior of soils. The definition of non-linear properties of the soil is based on triaxial tests carried out on the alluvial plain of Nahr Beirut. The effect of non-linear behavior and its variability is studied for the different ground motion indicators, mainly in the time domain (Arias intensity, duration, spatial correlation, Lagged coherency).

L’ambition de ce travail est la prédiction du champ d’onde incident réalistique, induit par des mouvement forts de sol, aux sites d’importance stratégique, comme des centrales nucléaires. À cette fin, un plateforme multi-outil est développé et exploité pour simuler les aspects différents d’un phénomène complexe et multi-échelle comme un tremblement de terre. Ce cadre computationnel fait face à la nature diversifiée d’un tremblement de terre par approche holistique local-régionale.Un cas d’étude complexe est choisie: le tremblement de terre MW6.6 Niigata-Ken Ch¯uetsu-Oki, qui a endommagé la centrale nucléaire de Kashiwazaki-Kariwa. Les effets de site non-linéaires observés sont à premier examinés et caractérisés. Dans la suite, le modèle 3D «de la faille au site» est construit et employé pour prédire le mouvement sismique dans une bande de fréquence de 0-7 Hz. L’effet de la structure géologique pliée au-dessous du site est quantifié en simulant deux chocs d’intensité modérée et en évaluant la variabilité spatiale des spectres de réponse aux différents endroits dans le site nucléaire. Le résultat numérique souligne le besoin d’une description plus détaillée du champ d’onde incident utilisé comme paramètre d’entrée dans la conception structurel antisismique de réacteurs nucléaires et des installations. Finalement, la bande de fréquences des signaux synthétiques obtenues comme résultat des simulations numériques est agrandie en exploitant la prédiction stochastique des ordonnées spectrales à courte période fournies par des Réseaux Artificiels de Neurones. / The ambition of this work is the prediction of a synthetic yet realistic broad-band incident wave-field, induced by strong ground motion earthquakes at sites of strategic importance, such as nuclear power plants. To this end, an multi-tool platform is developed and exploited to simulate the different aspects of the complex and multi-scale phenomenon an earthquake embodies. This multi-scale computational framework copes with the manifold nature of an earthquake by a holistic local-to-regional approach. A complex case study is chosen to this end: is the MW6.6 Niigata-Ken Ch¯uetsu-Oki earthquake, which damaged the Kashiwazaki-Kariwa nuclear power plant. The observed non-linear site-effects are at first investigated and characterized. In the following, the 3D source-to-site model is constructed and employed to provide reliable input ground motion, for a frequency band of 0-7 Hz. The effect of the folded geological structure underneath the site is quantified by simulating two aftershocks of moderate intensity and by estimating the spatial variability of the response spectra at different locations within the nuclear site. The numerical outcome stresses the need for a more detailed description of the incident wave-field used as input parameter in the antiseismic structural design of nuclear reactors and facilities. Finally, the frequency band of the time-histories obtained as outcome of the numerical simulations is enlarged by exploiting the stochastic prediction of short-period response ordinates provided by Artificial Neural Networks.