The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Susan E Hough - One of the best experts on this subject based on the ideXlab platform.
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Earthquake Intensity distributions a new view
Bulletin of Earthquake Engineering, 2014Co-Authors: Susan E HoughAbstract:Pioneering work by Nicolas Ambraseys and many collaborators demonstrates both the tremendous value of macroseismic data and the perils of its uncritical assessment. In numerous publications he shows that neglect of original sources and/or failure to appreciate the context of historical accounts, as well as use of unreliable indicators such as landsliding to determine intensities, commonly leads to inflated magnitude estimates for historical Earthquakes. The U.S. Geological Survey “Did You Feel It?” (DYFI) system, which now collects and systematically interprets thousands of first-hand reports from felt Earthquakes, provides the opportunity to explore further the biases associated with traditional Intensity distributions determined from written (media or archival) accounts. I briefly summarize and further develop the results of Hough (2013), who shows that traditional Intensity distributions imply more dramatic damage patterns than are documented by more spatially rich DYFI data, even when intensities are assigned according to the conservative practices established by Ambraseys’ work. I further consider the separate Intensity–attenuation relations that have been developed to characterize intensities for historical and modern Earthquakes in California, using traditionally assigned intensities and DYFI intensities, respectively. The results support the conclusion that traditionally assigned Intensity values tend to be inflated by a fundamental bias towards reporting of dramatic rather than representative effects. I introduce an empirical correction-factor approach to correct for these biases. This allows the growing wealth of well-calibrated DYFI data to be used as calibration events in the analysis of historical Earthquakes.
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spatial variability of did you feel it Intensity data insights into sampling biases in historical Earthquake Intensity distributions
Bulletin of the Seismological Society of America, 2013Co-Authors: Susan E HoughAbstract:Recent parallel development of improved quantitative methods to analyze Intensity distributions for historical Earthquakes and of web‐based systems for collecting Intensity data for modern Earthquakes provides an opportunity to reconsider not only important individual historical Earthquakes but also the overall characterization of Intensity distributions for historical events. The focus of this study is a comparison between Intensity distributions of historical Earthquakes with those from modern Earthquakes for which intensities have been determined by the U.S. Geological Survey “Did You Feel It?” (DYFI) website (see [Data and Resources][1]). As an example of a historical Earthquake, I focus initially on the 1843 Marked Tree, Arkansas, event. Its magnitude has been previously estimated as 6.0–6.2. I first reevaluate the macroseismic effects of this Earthquake, assigning intensities using a traditional approach, and estimate a preferred magnitude of 5.4. Modified Mercalli Intensity (MMI) values for the Marked Tree Earthquake are higher, on average, than those from the 2011 M w 5.8 Mineral, Virginia, Earthquake for distances ≤500 km but comparable or lower on average at larger distances, with a smaller overall felt extent. Intensity distributions for other moderate historical Earthquakes reveal similar discrepancies; the discrepancy is also even more pronounced using earlier published intensities for the 1843 Earthquake. I discuss several hypotheses to explain the discrepancies, including the possibility that Intensity values associated with historical Earthquakes are commonly inflated due to reporting/sampling biases. A detailed consideration of the DYFI Intensity distribution for the Mineral Earthquake illustrates how reporting and sampling biases can account for historical Earthquake Intensity biases as high as two Intensity units and for the qualitative difference in Intensity distance decays for modern versus historical events. Thus, Intensity maps for historical Earthquakes tend to imply more widespread damage patterns than are revealed by Intensity distributions of modern Earthquakes of comparable magnitude. However, Intensity accounts of historical Earthquakes often include fragmentary accounts suggesting long‐period shaking effects that will likely not be captured fully in historical Intensity distributions. Online Material: Archival accounts for the 4 January 1843 Marked Tree, Arkansas, and 8 October 1857 Southern Illinois Earthquakes. [1]: #sec-9
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Spatial Variability of “Did You Feel It?” Intensity Data: Insights into Sampling Biases in Historical Earthquake Intensity Distributions
Bulletin of the Seismological Society of America, 2013Co-Authors: Susan E HoughAbstract:Recent parallel development of improved quantitative methods to analyze Intensity distributions for historical Earthquakes and of web‐based systems for collecting Intensity data for modern Earthquakes provides an opportunity to reconsider not only important individual historical Earthquakes but also the overall characterization of Intensity distributions for historical events. The focus of this study is a comparison between Intensity distributions of historical Earthquakes with those from modern Earthquakes for which intensities have been determined by the U.S. Geological Survey “Did You Feel It?” (DYFI) website (see [Data and Resources][1]). As an example of a historical Earthquake, I focus initially on the 1843 Marked Tree, Arkansas, event. Its magnitude has been previously estimated as 6.0–6.2. I first reevaluate the macroseismic effects of this Earthquake, assigning intensities using a traditional approach, and estimate a preferred magnitude of 5.4. Modified Mercalli Intensity (MMI) values for the Marked Tree Earthquake are higher, on average, than those from the 2011 M w 5.8 Mineral, Virginia, Earthquake for distances ≤500 km but comparable or lower on average at larger distances, with a smaller overall felt extent. Intensity distributions for other moderate historical Earthquakes reveal similar discrepancies; the discrepancy is also even more pronounced using earlier published intensities for the 1843 Earthquake. I discuss several hypotheses to explain the discrepancies, including the possibility that Intensity values associated with historical Earthquakes are commonly inflated due to reporting/sampling biases. A detailed consideration of the DYFI Intensity distribution for the Mineral Earthquake illustrates how reporting and sampling biases can account for historical Earthquake Intensity biases as high as two Intensity units and for the qualitative difference in Intensity distance decays for modern versus historical events. Thus, Intensity maps for historical Earthquakes tend to imply more widespread damage patterns than are revealed by Intensity distributions of modern Earthquakes of comparable magnitude. However, Intensity accounts of historical Earthquakes often include fragmentary accounts suggesting long‐period shaking effects that will likely not be captured fully in historical Intensity distributions. Online Material: Archival accounts for the 4 January 1843 Marked Tree, Arkansas, and 8 October 1857 Southern Illinois Earthquakes. [1]: #sec-9
Michael Bauer - One of the best experts on this subject based on the ideXlab platform.
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real time Earthquake Intensity estimation using streaming data analysis of social and physical sensors
Pure and Applied Geophysics, 2017Co-Authors: Yelena Kropivnitskaya, K F Tiampo, Michael BauerAbstract:Earthquake Intensity is one of the key components of the decision-making process for disaster response and emergency services. Accurate and rapid Intensity calculations can help to reduce total loss and the number of casualties after an Earthquake. Modern Intensity assessment procedures handle a variety of information sources, which can be divided into two main categories. The first type of data is that derived from physical sensors, such as seismographs and accelerometers, while the second type consists of data obtained from social sensors, such as witness observations of the consequences of the Earthquake itself. Estimation approaches using additional data sources or that combine sources from both data types tend to increase Intensity uncertainty due to human factors and inadequate procedures for temporal and spatial estimation, resulting in precision errors in both time and space. Here we present a processing approach for the real-time analysis of streams of data from both source types. The physical sensor data is acquired from the U.S. Geological Survey (USGS) seismic network in California and the social sensor data is based on Twitter user observations. First, empirical relationships between tweet rate and observed Modified Mercalli Intensity (MMI) are developed using data from the M6.0 South Napa, CAF Earthquake that occurred on August 24, 2014. Second, the streams of both data types are analyzed together in simulated real-time to produce one Intensity map. The second implementation is based on IBM InfoSphere Streams, a cloud platform for real-time analytics of big data. To handle large processing workloads for data from various sources, it is deployed and run on a cloud-based cluster of virtual machines. We compare the quality and evolution of Intensity maps from different data sources over 10-min time intervals immediately following the Earthquake. Results from the joint analysis shows that it provides more complete coverage, with better accuracy and higher resolution over a larger area than either data source alone.
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the predictive relationship between Earthquake Intensity and tweets rate for real time ground motion estimation
Seismological Research Letters, 2017Co-Authors: Yelena Kropivnitskaya, K F Tiampo, Michael BauerAbstract:ABSTRACT The standard measure for evaluation of the immediate effects of an Earthquake on people and man‐made structures is Intensity. Intensity estimates are widely used for emergency response, loss estimation, and distribution of public information after Earthquake occurrence (Wood and Neumann, 1931; Brazee, 1976). Modern Intensity assessment procedures process a variety of information sources. Those sources are primarily from two main categories: physical sensors (seismographs and accelerometers) and social sensors (witness reports). Acquiring new data sources in the second category can help to speed up the existing procedures for Intensity calculations. One potentially important data source in this category is the widespread microblogging platform Twitter, ranked ninth worldwide as of January 2016 by number of active users, ∼320 million (Twitter, 2016). In our previous studies, empirical relationships between tweet rate and observed modified Mercalli Intensity (MMI) were developed using data from the M 6.0 South Napa, California, Earthquake (Napa Earthquake) that occurred on 24 August 2014 (Kropivnitskaya et al. , 2016). These relationships allow us to stream data from social sensors, supplementing data from other sensors to produce more accurate real‐time Intensity maps. In this study, we validate empirical relationships between tweet rate and observed MMI using new data sets from Earthquakes that occurred in California, Japan, and Chile during March–April 2014. The statistical complexity of the validation test and calibration process is complicated by the fact that the Twitter data stream is limited for open public access, reducing the number of available tweets. In addition, in this analysis only spatially limited positive tweets (marked as a tweet about the Earthquake) are incorporated into the analysis, further limiting the data set and restricting our study to a historical data set. In this work, the predictive relationship for California is recalibrated slightly, and a new set of relationships is estimated for Japan and Chile.
Zou Li - One of the best experts on this subject based on the ideXlab platform.
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Impact of Earthquake Intensity on flow deformation of the Upper San Fernando Dam
Journal of Hehai University, 2020Co-Authors: Zou LiAbstract:The antiseismic performance of an earth dam is determined not only by its geometry and composition, but also by the Intensity of an Earthquake to which the dam is subjected. A series of fully coupled finite element analyses of the response of the Upper San Fernando Dam to Earthquakes of different intensities are presented for the study of the impact of the Earthquake Intensity on flow deformation of the earth dam. A critical state sand model cooperating with the concept of statedependent dilatancy is employed to describe the soil behavior under all of the loading conditions. The analyses provide not only the global displacement and deformation of the dam, but also elemental soil responses at representative locations. The calculated deformation of the dam is in good agreement with the observed data.
T.y. Zheng - One of the best experts on this subject based on the ideXlab platform.
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Effects of soil density and Earthquake Intensity on flow deformation of the upper San Fernando dam
Geotechnique, 2011Co-Authors: H.y. Ming, Xiang Song Li, T.y. ZhengAbstract:The seismic performance of the upper San Fernando dam is systematically studied by using a fully coupled finite-element procedure in conjunction with a unified state-dependent dilatancy sand model. With detailed information produced by this procedure, the effects of soil density and Earthquake Intensity on flow deformation of the embankment are examined. This paper provides convincing numerical evidence to prove that even though stronger Earthquakes always produce larger deformation in the Upper San Fernando dam, an Earthquake serves mainly as a trigger to initiate flow liquefaction. Once flow liquefaction is triggered by a sufficiently strong Earthquake, the Earthquake-induced flow deformation is controlled dominantly by the difference between the shear stress required for equilibrium and the shear strength of the liquefied soil, which is determined by its density under undrained Earthquake loading conditions. The influence of the Intensity of the Earthquake itself on flow deformation of the embankment b...
Liang Qi - One of the best experts on this subject based on the ideXlab platform.
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Analysis of the Overall Stability of Tube in tube Structures Under Vertical Seismic Action
Journal of South China University of Technology, 2020Co-Authors: Liang QiAbstract:By the compatibility of deformation of the two tubes, the equation of the overall stability of a tube in tube structure is set up. This paper computes the p cr —the values of the critical load factor of the overall stability of the structure under vertical seismic action of mode Earthquake Intensity corresponding to 7, 8 and 9 degrees of Earthquake Intensity. The result indicates that the vertical seismic action greatly affects the overall stability of the structure by decreasing the value p cr . The value p cr decreases by 20.19% when the Earthquake Intensity is 9 degrees.
