Modeling Multidimensional and Multi-scale Seismic Site Response Using a Data-driven 3D Vs Model

Modeling Multidimensional and Multi-scale Seismic Site Response Using a Data-driven 3D Vs Model PDF Author: Mohamad Mahdi Hallal
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
Subsurface spatial variability is known to significantly influence the frequency content and amplitude of seismic ground shaking. A significant amount of seismic site response research over the past decade has focused on our abilities to replicate recorded ground motions at borehole array sites, where both the input (rock) and output (surface) ground motions are known. When viewed in aggregate, these studies have found that approximately 50% of borehole array sites are poorly modeled using one-dimensional (1D) ground response analyses (GRAs) based on a single shear wave velocity (Vs) profile, with individual studies reporting values between approximately 30-80%. When 1D GRAs fail to accurately predict recorded site response, the site is often considered too complex to be effectively modeled as 1D. While three-dimensional (3D) numerical GRAs are possible and believed to be more accurate, there is rarely a 3D subsurface model available for these analyses. The lack of affordable and reliable site characterization methods to quantify spatial variability in subsurface conditions, particularly regarding Vs measurements needed for GRAs, has pushed researchers to adopt stochastic approaches, such as Vs randomization and spatially correlated random fields. However, these stochastically generated models require the assumption of generic, or guessed, input parameters, introducing significant uncertainties into the site response predictions. This research describes a new geostatistical approach that can be used for building pseudo-3D Vs models as a means to rationally account for spatial variability in GRAs, increase model accuracy, and reduce uncertainty. The proposed approach distinguishes itself from previous studies in three key ways: (1) it requires only a single, accurately measured Vs profile down to engineering bedrock, (2) it relies majorly on estimates of fundamental site frequency (f0; a key parameter governing site effects) obtained from simple horizontal-to-vertical spectral ratio (H/V) noise measurements (f0,[subscript H/V]), and (3) it creates models that can be used to ensure proper incorporation of site-specific spatial variability in 1D, 2D, and 3D GRAs. At the two sites investigated in this research, the H/V geostatistical approach is capable of generating pseudo-3D Vs models that reliably capture important subsurface features present in geologic cross-sections. Furthermore, the 1D GRA predictions associated with the H/V geostatistical approach were more accurate than those associated with common and recently proposed strategies of accounting for Vs variability. One of the most significant contributions of this research is providing insights on the lateral area influencing seismic site response. The H/V geostatistical approach enables predicting site response as a function of the spatial variability across different footprints. The results show that 1D GRAs are significantly improved when an area of at least 400 m x 400 m (i.e., 0.16 km2) is incorporated, and even larger incorporated areas could produce better results. Thus, this size of an area might be considered as a minimum over which to account for spatial variability in GRAs. These results are supported by two-dimensional (2D) GRAs, which show that incorporating variability along at least 600 m was needed to appropriately model decreased amplification at the fundamental mode caused by wave scattering, while a lateral extent of 1700 m was needed to more accurately model other observed complex phenomena. These results and insights work toward achieving more accurate and reliable seismic hazard assessment and risk mitigation

Modeling Multidimensional and Multi-scale Seismic Site Response Using a Data-driven 3D Vs Model

Modeling Multidimensional and Multi-scale Seismic Site Response Using a Data-driven 3D Vs Model PDF Author: Mohamad Mahdi Hallal
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
Subsurface spatial variability is known to significantly influence the frequency content and amplitude of seismic ground shaking. A significant amount of seismic site response research over the past decade has focused on our abilities to replicate recorded ground motions at borehole array sites, where both the input (rock) and output (surface) ground motions are known. When viewed in aggregate, these studies have found that approximately 50% of borehole array sites are poorly modeled using one-dimensional (1D) ground response analyses (GRAs) based on a single shear wave velocity (Vs) profile, with individual studies reporting values between approximately 30-80%. When 1D GRAs fail to accurately predict recorded site response, the site is often considered too complex to be effectively modeled as 1D. While three-dimensional (3D) numerical GRAs are possible and believed to be more accurate, there is rarely a 3D subsurface model available for these analyses. The lack of affordable and reliable site characterization methods to quantify spatial variability in subsurface conditions, particularly regarding Vs measurements needed for GRAs, has pushed researchers to adopt stochastic approaches, such as Vs randomization and spatially correlated random fields. However, these stochastically generated models require the assumption of generic, or guessed, input parameters, introducing significant uncertainties into the site response predictions. This research describes a new geostatistical approach that can be used for building pseudo-3D Vs models as a means to rationally account for spatial variability in GRAs, increase model accuracy, and reduce uncertainty. The proposed approach distinguishes itself from previous studies in three key ways: (1) it requires only a single, accurately measured Vs profile down to engineering bedrock, (2) it relies majorly on estimates of fundamental site frequency (f0; a key parameter governing site effects) obtained from simple horizontal-to-vertical spectral ratio (H/V) noise measurements (f0,[subscript H/V]), and (3) it creates models that can be used to ensure proper incorporation of site-specific spatial variability in 1D, 2D, and 3D GRAs. At the two sites investigated in this research, the H/V geostatistical approach is capable of generating pseudo-3D Vs models that reliably capture important subsurface features present in geologic cross-sections. Furthermore, the 1D GRA predictions associated with the H/V geostatistical approach were more accurate than those associated with common and recently proposed strategies of accounting for Vs variability. One of the most significant contributions of this research is providing insights on the lateral area influencing seismic site response. The H/V geostatistical approach enables predicting site response as a function of the spatial variability across different footprints. The results show that 1D GRAs are significantly improved when an area of at least 400 m x 400 m (i.e., 0.16 km2) is incorporated, and even larger incorporated areas could produce better results. Thus, this size of an area might be considered as a minimum over which to account for spatial variability in GRAs. These results are supported by two-dimensional (2D) GRAs, which show that incorporating variability along at least 600 m was needed to appropriately model decreased amplification at the fundamental mode caused by wave scattering, while a lateral extent of 1700 m was needed to more accurately model other observed complex phenomena. These results and insights work toward achieving more accurate and reliable seismic hazard assessment and risk mitigation

Measuring, Modeling and Predicting the Seismic Site Effect

Measuring, Modeling and Predicting the Seismic Site Effect PDF Author: Yefei Ren
Publisher: Frontiers Media SA
ISBN: 2832540090
Category : Science
Languages : en
Pages : 297

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Book Description
As recognized universally by both seismology and earthquake engineering communities, the amplitude and frequency content of ground motions are influenced by local site effects, including the effects of near-surface geologic materials, surface topographic and basin effects, and so on. Strong linkage between seismic site effect and earthquake damage has been commonly demonstrated from many past earthquakes. Therefore, quantitative and reliable evaluation of the seismic site effect is one of the crucial aspects in seismic hazard assessment and risk mitigation. With the significant advancement of modern seismic monitoring networks and arrays, huge amounts of high-quality seismic records are now being accumulated. This encourages us to measure the site responses and its associated uncertainty for selected seismic stations by some record-dependent approaches, such as horizontal-to-vertical spectral ratio (HVSR) measurements, generalized spectral inversion (GIT) methods, etc. Machine learning techniques also show significant promise in characterization of the near-surface geologic properties and prediction of site response. These data-driven approaches help us to better understand the physics of spatial and temporal variabilities of ground motions. Due to more and more site-specific data being captured, invoking non-ergodic assumptions in seismic response analysis has recently been a topic of great interest in the community. For specific site response analysis, numerical simulations are carried out to model the dynamic process of seismic waves propagating and scattering in the subsurface strata. With development of modeling capacity, great efforts have been taken to evaluate quantitatively the complex 2D and 3D effects on seismic site response.

Data-driven Frameworks for Hybrid Analysis of Structures Under Seismic Loading

Data-driven Frameworks for Hybrid Analysis of Structures Under Seismic Loading PDF Author: Fardad Mokhtari Dizaji
Publisher:
ISBN:
Category : Earthquake engineering
Languages : en
Pages : 0

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Book Description
Numerical simulation and hybrid simulation are extensively used in earthquake engineering to evaluate the seismic response of structures under seismic loading. Despite the advances in computing power and the development of efficient integration algorithms in the past, numerical simulation techniques suffer from a high computational cost and the uncertainty associated with the definition of constitutive material models, boundary conditions, and mesh density, in particular in highly nonlinear, large or complex structures. On the other hand, the results of hybrid simulation can become biased when only one or limited number of potential critical components, seismic fuses, are physically tested due to laboratory or cost constraints. The recent progress in machine learning algorithms and applications in engineering has motivated novel and innovative simulation techniques achieved by leveraging data in various fields of engineering including seismic engineering where complexities arising from the stochastic nature of the phenomenon can be tackled by making use of available experimental and numerical data towards the development of more reliable simulation models and dynamic analysis frameworks. Furthermore, to better exploit the potential of data-driven models, such models can efficiently be incorporated into the physics-based and experimental techniques, leading to improved seismic response assessment methods. This M.Sc. thesis proposes two new hybrid analysis frameworks by integrating emerging data-driven techniques into the conventional structural response assessment techniques, namely numerical simulation and hybrid testing, to perform the nonlinear structural analysis under seismic loading. The first framework, referred to as the hybrid data-driven and physics-based simulation (HyDPS) technique, combines the well-understood components of the structure modeled numerically with the critical components of the structure, e.g., seismic fuses, simulated using the proposed data-driven PI-SINDy model. The data-driven model is developed for steel buckling-restrained braces based on experimental data to mathematically estimate the underlying relationship between displacement history and restoring force. The second framework incorporates the data-driven model into the conventional seismic hybrid simulation framework where the experimental test data of one of the critical components (physical twin), e.g., steel buckling-restrained brace, produced during hybrid simulation can be used in real-time to predict the nonlinear cyclic response of the other critical components of the system (digital twins) that are not physically tested. This framework features a novel multi-element seismic hybrid simulation technique achieved by recursively updating the force-deformation response of the digital twin. The performance of the proposed data-driven hybrid analysis frameworks is verified using past experimental test data and nonlinear response history analyses performed under representative earthquake ground motion accelerations. The results reveal that integrating data-driven techniques into conventional seismic analysis methods, namely numerical simulation and hybrid simulation, yields a more efficient seismic simulation tool that can be used to examine the seismic response of structural systems.

A Data-driven Building Seismic Response Prediction Framework: from Simulation and Recordings to Statistical Learning

A Data-driven Building Seismic Response Prediction Framework: from Simulation and Recordings to Statistical Learning PDF Author: HAN SUN
Publisher:
ISBN:
Category :
Languages : en
Pages : 211

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Book Description
Structural seismic resilience society has been grown rapidly in the past three decades. Extensive probabilistic techniques have been developed to address uncertainties from ground motions and building systems to reduce structural damage, economic loss and social impact of buildings subjected to seismic hazards where seismic structural responses are essential and often are retrieved through Nonlinear Response History Analysis. This process is largely limited by accuracy of model and computational effort. An alternative data-driven framework is proposed to reconstruct structure responses through machine learning techniques from limited available sources which may potentially benefit for "real-time" interpolating monitoring data to enable rapid damage assessment and reducing computational effort for regional seismic hazard assessment. It also provides statistical insight to understand uncertainties of seismic building responses from both structural and earthquake engineering perspective.

Recent Advances and Applications of Hybrid Simulation

Recent Advances and Applications of Hybrid Simulation PDF Author: Wei Song
Publisher: Frontiers Media SA
ISBN: 2889663809
Category : Technology & Engineering
Languages : en
Pages : 213

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Book Description


Nonequilibrium Statistical Mechanics

Nonequilibrium Statistical Mechanics PDF Author: Robert Zwanzig
Publisher: Oxford University Press, USA
ISBN: 0195140184
Category : Science
Languages : en
Pages : 233

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Book Description
This is a presentation of the main ideas and methods of modern nonequilibrium statistical mechanics. It is the perfect introduction for anyone in chemistry or physics who needs an update or background in this time-dependent field. Topics covered include fluctuation-dissipation theorem; linear response theory; time correlation functions, and projection operators. Theoretical models are illustrated by real-world examples and numerous applications such as chemical reaction rates and spectral line shapes are covered. The mathematical treatments are detailed and easily understandable and the appendices include useful mathematical methods like the Laplace transforms, Gaussian random variables and phenomenological transport equations.

Earthquake Geotechnical Engineering for Protection and Development of Environment and Constructions

Earthquake Geotechnical Engineering for Protection and Development of Environment and Constructions PDF Author: Francesco Silvestri
Publisher: CRC Press
ISBN: 0429633505
Category : Technology & Engineering
Languages : en
Pages : 5946

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Book Description
Earthquake Geotechnical Engineering for Protection and Development of Environment and Constructions contains invited, keynote and theme lectures and regular papers presented at the 7th International Conference on Earthquake Geotechnical Engineering (Rome, Italy, 17-20 June 2019. The contributions deal with recent developments and advancements as well as case histories, field monitoring, experimental characterization, physical and analytical modelling, and applications related to the variety of environmental phenomena induced by earthquakes in soils and their effects on engineered systems interacting with them. The book is divided in the sections below: Invited papers Keynote papers Theme lectures Special Session on Large Scale Testing Special Session on Liquefact Projects Special Session on Lessons learned from recent earthquakes Special Session on the Central Italy earthquake Regular papers Earthquake Geotechnical Engineering for Protection and Development of Environment and Constructions provides a significant up-to-date collection of recent experiences and developments, and aims at engineers, geologists and seismologists, consultants, public and private contractors, local national and international authorities, and to all those involved in research and practice related to Earthquake Geotechnical Engineering.

Applied Mechanics Reviews

Applied Mechanics Reviews PDF Author:
Publisher:
ISBN:
Category : Mechanics, Applied
Languages : en
Pages : 348

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Book Description


Hart's E&P.

Hart's E&P. PDF Author:
Publisher:
ISBN:
Category : Gas industry
Languages : en
Pages : 712

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Book Description


Introduction to Computational Earthquake Engineering

Introduction to Computational Earthquake Engineering PDF Author: Muneo Hori
Publisher: World Scientific
ISBN: 1848163991
Category : Computers
Languages : en
Pages : 438

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Book Description
Introduction to Computational Earthquake Engineering covers solid continuum mechanics, finite element method and stochastic modeling comprehensively, with the second and third chapters explaining the numerical simulation of strong ground motion and faulting, respectively. Stochastic modeling is used for uncertain underground structures, and advanced analytical methods for linear and non-linear stochastic models are presented. The verification of these methods by comparing the simulation results with observed data is then presented, and examples of numerical simulations which apply these methods to practical problems are generously provided. Furthermore three advanced topics of computational earthquake engineering are covered, detailing examples of applying computational science technology to earthquake engineering problems.