Research areas

A brief overview of several research topics is provided here. Click on the navigation tabs directly below this text to see more detailed information on selected topics.

 
    Research Topics: General | Epsilon | Pulse Classification | Attenuation scripts |

Earthquake ground motion characterization


Project sponsors: U.S. Geological Survey and the Pacific Earthquake Engineering Research Center

Collaborators: Nico Luco, U.S. Geological Survey, Steve Harmsen, U.S. Geological Survey, and Allin Cornell, Stanford University

As nonlinear dynamic analysis becomes a more frequently used procedure for evaluating the demand on a structure due to earthquakes, it is increasingly important to understand which properties of ground motions are most strongly related to the response caused in the structure. A value that quantifies the effect of a record on a structure is often called an Intensity Measure (IM). Spectral acceleration at the first-mode period of vibration, Sa(T1), has frequently been used as an IM for predicting response of structures. But among records with the same value of Sa(T1), there is still significant variability in response of a multi-degree-of-freedom, nonlinear structural model. Here we consider a two-parameter (i.e., vector-valued) intensity measures which have greater potential to account for this variability in response.

A reference page for the ground motion parameter 'epsilon' is available here. It may be helpful to researchers investigating the effect of epsilon on their structures.

Quantitative classification of near-fault ground motions


Project sponsor: National Science Foundation

Ground motions with velocity pulses caused by near-fault directivity have received a great deal of attention from engineers and seismologists because of their potential to cause severe damage to structures. Many studies have investigated the dynamic response of structures to these "pulse-like" ground motions, but the ground motions are typically identified using judgment rather than some classification procedure. The lack of a systematic, quantitative classification scheme has hindered progress in answering even seemingly simple questions such as the probability that a ground motion with a given magnitude, distance and source-site geometry will have a velocity pulse. In this project, a quantitative scheme for detecting pulses is being developed. The procedure uses a wavelet-based signal decomposition to identify and extract the largest velocity pulse from a ground motion, and if the extracted signal is large relative to the remaining signal, the ground motion is classified as a pulse-like motion. The identified pulse-like ground motions are then being used in dynamic nonlinear structural analyses to identify relationships between near-fault directivity effects and structural response.

Additional details regarding this project are provided here.

Characterization of random fields and their impact on the mechanics of geosystems at multiple scales


Project sponsor: National Science Foundation

Collaborator: Jose Andrade, Northwestern University

The multi-scale nature of soil behavior is explicitly accounted for by obtaining the mechanical response of geosystems using an accurate multi-scale hierarchical computational framework. It is well known that the behavior of particulate media, such as sands, is encoded at the granular-scale and hence methods for up-scaling such behavior across relevant scales of interest-from granular-scale (~1mm) to field-scale (>1m)-are needed to attain a more accurate prediction of soil behavior. Multi-scale analysis is especially important under extreme conditions such as strain localization, penetration or liquefaction, where the classical constitutive description may no longer apply. Several unanswered questions illustrate the importance of studying such phenomena: What material parameterizations are most appropriate at various scales? What are the relevant scales needed for an accurate material description? What are the impacts of uncertainties and inhomogeneities on field-scale behavior? A probabilistic framework across multiple scales is needed to answer these questions and to consistently compute the behavior of the material across scales.

Probabilistic models for soil porosity are developed at multiple scales, using experimental results from X-Ray computed tomography to study spatial correlation down to the millimeter scale. From a computational standpoint, the multi-scale framework is demonstrated using well-established models for sands. In this hierarchical approach, a more accurate material description-at finer scales-is pursued only in the presence of strong inhomogeneities, either material or imposed (e.g. by deformations). The hierarchical approach is based on passing the macroscopic deformation down to the finer scale(s) and then returning more accurate, averaged stresses. Monte Carlo simulation is used to generate material properties in a hierarchical manner, so that fine scale material data can be obtained whenever necessary, conditional upon previously simulated coarse scale data. These modeling approaches will be developed and then used in several parametric and validation studies to bring insight to practical problems where multi-scale effects are important. Multi-scale modeling opens the door to develop design-specific engineering systems with desirable qualities or properties, and will allow scientists and engineers to better understand the role of finer scales on the behavior of geotechnical systems.

Spatial correlation of earthquake ground motion intensity


Project sponsor: U.S. Geological Survey

Collaborators: Paolo Bazzurro and Jaesung Park, AIR Worldwide

Many seismic loss problems (such as damage of distributed infrastructure and losses to portfolios of structures) are dependent upon the regional distribution of ground motion intensity, rather than intensity at only a single site. This work extends traditional probabilistic seismic hazard analysis (which considers distributions of future event magnitudes, distances, attenuation variability, etc.), to consider spatial distribution of intensity. Spatial correlations of this intensity have been developed empirically based on data from well-recorded past earthquakes. This can then be used in forward simulations of ground motion intensity in future earthquakes. When implemented in a Monte Carlo simulation, one may obtain millions of simulations of intensity from future events, so methods have been developed to select a greatly reduced number of representative events from a large number of simulations. This will facilitate computationally-intensive risk analyses of systems such as transportation networks.

Propagation of uncertainty for seismic loss estimation


Project sponsor: Pacific Earthquake Engineering Research Center

Collaborator: Allin Cornell, Stanford University

Probabilistic estimation of losses in a building due to earthquake damage is a topic of interest to decision makers and an area of active research. One promising approach to the problem, proposed by the Pacific Earthquake Engineering Research (PEER) Center, involves breaking the analysis into separate components associated with ground motion hazard, structural response, damage to components and repair costs. Each stage of this method has both inherent (aleatory) randomness and (epistemic) model uncertainty, and these two sources of uncertainty must be propagated through the analysis in order to determine the total uncertainty in the resulting loss estimates. In this work, the PEER framework for seismic loss estimation is reviewed and options for both characterizing and propagating the various sources of uncertainty are proposed.