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Tang Y.,University of California at Los Angeles | Tang Y.,Air Worldwide Corporation | Zhang J.,University of California at Los Angeles
Engineering Structures | Year: 2011

Reinforced concrete shear walls are often used to resist the lateral loads imposed by earthquakes. Accurate evaluation of the seismic demands on shear walls requires adequate considerations of the nonlinear behavior of structural and foundation elements, the interaction between them, and the uncertainty and variability associated with earthquake ground motions. This paper presents a comprehensive probabilistic seismic demand analysis of a typical mid-rise slender shear wall in western US with a flexible foundation and evaluates the significance of soil-structure interaction (SSI) effects on their damage probability. Utilizing realistic numerical models for the shear wall and its foundation, the nonlinear time history analyses were conducted with a large number of recorded ground motions. Response quantities such as maximum inter-story drift ratio, base shear, foundation displacement and rotation are monitored and related to the intensity measure of ground motions (i.e. the inelastic spectral displacement Sdi) for the cases with and without considering the SSI effects. Subsequently, the fragility functions of the shear wall are derived and the impact of SSI effects is investigated. It is found that the SSI generally reduces the damage probability of the shear wall, especially when soil nonlinearity is taken into account. The sensitivity of various seismic demands to soil parameters is also discussed. Under strong ground shakings, SSI effects on the maximum inter-story drift are most sensitive to the friction angle of the soil. It is suggested that the damages in foundation and surrounding soil should also be considered in order to systematically evaluate the SSI effects on damage probability of shear wall buildings. © 2010 Elsevier Ltd.


Ghosh J.,Air Worldwide Corporation | Padgett J.E.,Rice University | Duenas-Osorio L.,Rice University
Probabilistic Engineering Mechanics | Year: 2013

Seismic response and vulnerability assessment of key infrastructure elements, such as highway bridges, often requires a large number of nonlinear dynamic analyses of complex finite element models to cover the predictor parameter space. The substantial computation time may be reduced by using statistical learning techniques to develop surrogate models, or metamodels, which efficiently approximate the complex and implicit relationship between predictor variables, such as bridge design and ground motion intensity parameters, and the predicted bridge component seismic responses (e.g., column and bearing deformations). Addressing the existing disadvantages of unidimensional metamodels and lack of systematic exploration of different metamodeling strategies to predict bridge responses, this study analyzes four different metamodels, namely, polynomial response surface models as a reference to classical surrogate models, along with emerging multivariate adaptive regression splines, radial basis function networks, and support vector machines. These metamodels are used to develop multi-dimensional seismic demand models for critical components of a multi-span simply supported concrete girder bridge class. The predictive capabilities of the metamodels are assessed by comparing cross-validated goodness-of-fit estimates, and benchmark Monte Carlo simulations. Failure surfaces of bridges under seismic loads are explored for the first time to reveal low curvature the multi-dimensional limit state function and confirm the applicability of metamodels. Lastly, logistic regression is employed to develop parameterized fragility models which offer several advantages over "classical" unidimensional fragility curves. The results and methodologies presented in this study can be applied to efficiently estimate bridge-specific failure probabilities during seismic events. © 2013 Elsevier Ltd.


Tolwinski-Ward S.E.,Air Worldwide Corporation | Tingley M.P.,Pennsylvania State University | Evans M.N.,University of Maryland University College | Hughes M.K.,University of Arizona | Nychka D.W.,U.S. National Center for Atmospheric Research
Climate Dynamics | Year: 2014

We explore a probabilistic, hierarchical Bayesian approach to the simultaneous reconstruction of local temperature and soil moisture from tree-ring width observations. The model explicitly allows for differing calibration and reconstruction interval responses of the ring-width series to climate due to slow changes in climatology coupled with the biological climate thresholds underlying tree-ring growth. A numerical experiment performed using synthetically generated data demonstrates that bimodality can occur in posterior estimates of past climate when the data do not contain enough information to determine whether temperature or moisture limitation controlled reconstruction-interval tree-ring variability. This manifestation of nonidentifiability is a result of the many-to-one mapping from bivariate climate to time series of tree-ring widths. The methodology is applied to reconstruct temperature and soil moisture conditions over the 1080–1129 C.E. interval at Methusalah Walk in the White Mountains of California, where co-located isotopic dendrochronologies suggest that observed moisture limitations on tree growth may have been alleviated. Our model allows for assimilation of both data sources, and computation of the probability of a change in the climatic controls on ring-width relative to those observed in the calibration period. While the probability of a change in control is sensitive to the choice of prior distribution, the inference that conditions were moist and cool at Methuselah Walk during the 1080–1129 C.E. interval is robust. Results also illustrate the power of combining multiple proxy data sets to reduce uncertainty in reconstructions of paleoclimate. © 2014, Springer-Verlag Berlin Heidelberg.


Sasanian S.,Air Worldwide Corporation | Newson T.A.,University of Western Ontario
Soils and Foundations | Year: 2014

Although extensive research has been conducted on the mechanical behaviour of Portland cement-treated soft clays, there has been less emphasis on the correlation of the observed behaviour with clay mineralogy. In this study, experimental results from the authors have been combined with the data found in the literature to investigate the effect of parameters such as curing time, cement content, moisture content, liquidity index, and mineralogy on the mechanical properties of cement-treated clays. The findings show that undrained shear strength and sensitivity of cemented clays still continue to increase after relatively long curing times; expressions are proposed to predict the strength and sensitivity with time. This parametric study also indicates the relative importance of the activity of the soil, as well as the water-cement ratio, to the mechanical properties of cementitious admixtures. Two new empirical parameters are introduced herein. Based on the results of unconfined compression, undrained triaxial, and oedometer tests on cement-enhanced clays, expressions that use these parameters to predict undrained shear strength, yield stress, and the slope of the compression line are proposed. The observed variations in the mechanical behaviour with respect to mineralogy and the important effect of curing time are explained in terms of the pozzolanic reactions. The possible limitations of applying Abrams' law to cement-admixed clays are also discussed. © 2014 The Japanese Geotechnical Society.


Mallard M.S.,North Carolina State University | Mallard M.S.,U.S. Environmental Protection Agency | Lackmann G.M.,North Carolina State University | Aiyyer A.,North Carolina State University | Hill K.,Air Worldwide Corporation
Journal of Climate | Year: 2013

The Weather Research and Forecasting (WRF) model is used in a downscaling experiment to simulate a portion of the Atlantic hurricane season both in present-day conditions and with modifications to include future thermodynamic changes. Temperature and moisture changes are derived from an ensemble of climate simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) A1B scenario and added to analyzed initial and lateral boundary conditions, leaving horizontal temperature gradients and vertical wind shear unaltered. This method of downscaling excludes future changes in shear and incipient disturbances, thereby isolating the thermodynamic component of climate change and its effect on tropical cyclone (TC) activity. The North Atlantic basin is simulated with 18-and 6-km grid spacing, and a four-member physics ensemble is composed by varying microphysical and boundary layer parameterization schemes. This ensemble is used in monthly simulations during an active (2005) and inactive (2009) season, and the simulations are able to capture the change in activity between the different years. TC frequency is better reproduced with use of 6-km grid spacing and explicitly simulated convection, relative to simulations with 18-km grid spacing. A detailed comparison of present-day and future ensemble results is provided in a companion study.©2013 American Meteorological Society.


Shu C.,Air Worldwide Corporation | Ouarda T.B.M.J.,Masdar Institute of Science and Technology
Water Resources Research | Year: 2012

In this paper, improved flow duration curve (FDC) and area ratio (AR) based methods are developed to obtain better daily streamflow estimation at ungauged sites. A regression based logarithmic interpolation method which makes no assumption on the distribution or shape of a FDC is introduced in this paper to estimate regional FDCs. The estimated FDC is combined with a spatial interpolation algorithm to obtain daily streamflow estimates. Multiple source sites based AR methods, especially the geographical distance weighted AR (GWAR) method, are introduced in an effort to maximize the use of regional information and improve the standard AR method (SAR). Performances of the proposed approaches are evaluated using a jackknife procedure. The application to 109 stations in the province of Quebec, Canada indicates that the FDC based methods outperform AR based methods in all the summary statistics including Nash, root mean squared error (RMSE), and Bias. The number of sites that show better performances using the FDC based approaches is also significantly larger than the number of sites showing better performances using AR based methods. Using geographical distance weighted multiple sources sites based approaches can improve the performance at the majority of the catchments comparing with using the single source site based approaches. Copyright 2012 by the American Geophysical Union.


Catastrophe bonds are used by the insurance and reinsurance industry and by national governments to cede catastrophic risks to the financial markets. Triggers whose outcomes depend only on the earthquake parameter data published by respected third parties can be implemented to determine without moral hazard whether the bond principal is paid for a certain event. Sensitivity analyses to different design assumptions show that these transactions are often affected by trigger error, unless a sufficiently dense geographic discretization is selected to define the trigger zones. A process of general application to any geography is developed to minimize the trigger error. The methodology is illustrated with the design of a hypothetical cat bond for Costa Rica. © 2010, Earthquake Engineering Research Institute.


Tolwinski-Ward S.E.,Air Worldwide Corporation
Journal of Advances in Modeling Earth Systems | Year: 2015

A spatially resolved climatology for the annual frequency of tropical cyclone (TC) landfalls along the Atlantic coast of North America is developed, and its uncertainty deriving from multiple sources is quantified. Historical landfall counts in piecewise-linear segments approximating the coastline are modeled using Poisson regression with spatial random effects. Predictors include index representations of the mean hurricane-season phases of the Southern Oscillation, the Atlantic Multidecadal Oscillation, and the North Atlantic Oscillation, with the effect of the latter also modeled spatially. This spatial generalized linear model for landfall frequency is used in conjunction with a data level accounting explicitly for the time-dependent uncertainty in the recorded landfall positions. The model performs skillfully in cross-validation exercises. The inferred effects of the climatic predictors are also consistent with current scientific understanding of the mechanisms through which related large-scale climatic variability affects the development and motion of Atlantic tropical cyclones. Sampling variability in the data over the short length of the observational record and observational error in the historical data are found to contribute substantially to the overall climatological uncertainty. The contribution from uncertainty in the underlying model parameters is negligible compared to these other sources. The model presented here could be used for applications in insurance and risk management, and adaptations could also be used to investigate changes in TC landfall climatology under an uncertain and changing climate. © 2015. The Authors.


Senarath S.U.S.,Air Worldwide Corporation
World Environmental and Water Resources Congress 2015: Floods, Droughts, and Ecosystems - Proceedings of the 2015 World Environmental and Water Resources Congress | Year: 2015

Flood frequency analysis plays an important role in the design of hydraulic structures and in the delineation of floodplains. There are several factors in the flood frequency analysis procedure that depend on the user's judgment or input. One such consideration, the detection and treatment of outliers, is investigated in this study. The Bulletin 17B (IACWD, 1982) defines outliers as data points that depart significantly from the trend of the remaining data. Hypothesis-testing-based approaches are widely used to detect outliers. These outliers, however, are not automatically eliminated from flow records. Verifiable ground-based information is needed for both the retention and elimination of outliers. In the absence of such information, they are subject to modification as a compromise solution. As the results of this study show, each of these choices (outlier retention, modification and elimination) has impacts on the ensuing flood frequency analysis. The study-results also show that statistical outliers are often present in flow records and that the number of outliers identified can vary depending on the test and significance level chosen for outlier detection. © 2015 ASCE.


Ramirez C.M.,Air Worldwide Corporation | Miranda E.,Stanford University
Earthquake Engineering and Structural Dynamics | Year: 2012

The influence of residual interstorey drifts on economic losses in building resulting from earthquakes is examined. Current building-specific loss estimation methodologies that estimate economic losses based on peak response quantities such as peak interstorey drift ratios or peak floor accelerations are extended to explicitly account for residual interstorey drifts. The new approach incorporates the influence of residual drifts by accounting for the possibility of having to demolish a building as a result of excessive residual interstorey drifts, where the probability of demolition is computed as a function of the maximum residual drift in the building. The proposed approach is illustrated by estimating direct economic seismic losses in four reinforced concrete moment-resisting frame buildings in Los Angeles, California. Two buildings have nonductile detailing representative of pre-1970s building codes, whereas the other two buildings have ductile requirements satisfying current seismic building codes in the U.S. Results indicate that economic losses at intermediate levels of ground motion intensity are often dominated by losses due to residual interstorey drifts. This is particularly true in the case of ductile buildings in which neglecting losses from residual drifts can lead to significant underestimations of economic losses. © 2012 John Wiley & Sons, Ltd.

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