Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

RISK ANALYSIS OF STEEL FRAME BUILDINGS DUE TO EARTHQUAKE MAINSHOCK-AFTERSHOCK SEQUENCES

Following a large earthquake, numerous aftershocks can be triggered due to the complex stress interaction between and within tectonic plates. The aftershocks have the potential to cause severe weakening of mainshock-damaged buildings, threaten life safety, hamper reoccupation and restoration of buildings, and increase financial loss. The probability of aftershocks has not been included in the description of seismic hazard in performance-based earthquake engineering. This study proposes methodologies and a framework to investigate the performance and risk assessment of steel frame buildings subjected to mainshock-aftershock sequences. The collapse probability of mainshock-damaged steel buildings in aftershocks is investigated based on a calibrated steel frame model which is able to capture the key structural properties of strength and stiffness degradation. A scaling method was proposed to combine the mainshock and the aftershock in incremental dynamic analysis. This research finds that the structural collapse capacity may be reduced significantly when the building is subjected to a high intensity mainshock and the structure is likely to collapse even if a small aftershock follows the mainshock. In an effort to examine the aftershock effect on seismic loss, a framework is developed to evaluate seismic loss of structures subjected to mainshock-aftershock sequences. The framework is applied to examine the effects of aftershocks on seismic loss considering two intensity levels of mainshocks: the Design Earthquake, and the Maximum Considered Earthquake. It is found that aftershocks may have a significant impact on the seismic loss due to the uncertainty of the damage state and cost estimation. Limited study has been performed to investigate the impact of ground motion characteristics on the collapse risk of buildings, especially for the post-mainshock buildings. This research investigates the impact of the mean period on structural collapse. This paper finds that structural collapse capacity decreases and the peak interstory drift as well as peak residual drift before collapse decreases when the mean period increases. The influence of duration and mean period of earthquakes on the collapse risk of postmainshock buildings were also examined accounting for four damage states. This research shows that both duration and mean period of aftershocks play a significant role in structural collapse capacity. The degree of influence of aftershock characteristics on post-mainshock building collapse capacities becomes more significant as the mainshockinduced damage level increases. Additionally, a vector measure of ground motion intensity consisting of the spectral acceleration at the first-mode period, epsilon (an indicator of spectral shape), and duration are employed to investigate collapse risk of mainshock-damaged buildings. The results indicate that a building may be more vulnerable when subjected to a ground motion with smaller epsilon and longer duration. The collapse risk of post-mainshock buildings may be remarkably overestimated when synthesizing the artificial aftershocks by scaling mainshock records, since aftershocks tend to have a larger epsilon and shorter duration than mainshocks

The 2020 global stock market crash: Endogenous or exogenous?

Starting on February 20, 2020, the global stock markets began to suffer the worst decline since the Great Recession in 2008, and the COVID-19 has been widely blamed on the stock market crashes. In this study, we applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major world stock market indexes from both developed and emergent stock markets, including the S&P 500, the DJIA, and the NASDAQ from the United State, the FTSE from the United Kingdom, the DAX from Germany, the NIKKEI from Japan, the CSI 300 from China, the HSI from Hong Kong, the BSESN from India, and the BOVESPA from Brazil. In order to effectively distinguish between endogenous crash and exogenous crash in stock market, we proposed using the LPPLS confidence indicator as a classification proxy. The results show that the apparent LPPLS bubble patterns of the super-exponential increase, corrected by the accelerating logarithm-periodic oscillations, have indeed presented in the price trajectories of the seven indexes: S&P 500, DJIA, NASDAQ, DAX, CSI 300, BSESN, and BOVESPA, indicating that the large positive bubbles have formed endogenously prior to the 2020 stock market crash, and the subsequent crashes for the seven indexes are endogenous, stemming from the increasingly systemic instability of the stock markets inherently, while the well-known external shocks, such as the COVID-19 pandemic, the corporate debt bubble, and the 2020 Russia–Saudi Arabia oil price war, only served as sparks during the 2020 global stock market crash. In contrast, the crashes in the three remaining indexes: FTSE, NIKKEI, and HSI, are exogenous and hence are perhaps the only crashes truly due to the COVID-19 pandemic. We also found that in terms of the regime changes of the stock markets, no obvious LPPLS negative bubble pattern has been observed in the price trajectories of the 10 stock market indexes, indicating that the regime changes from a bear market to a bull market in late March 2020 are exogenous, stemming from external factors. The unprecedented market and economy rescue efforts from federal reserves and central banks across the world in unison may have played a critical role in quelling the 2020 global stock market crash in the nick of time. This paper creates a paradigm for future studies in real-time crash detection and underlying mechanism dissection. It serves to warn us of the imminent risks in not only the stock market but also other financial markets and economic indexes

The ‘COVID’ crash of the 2020 U.S. Stock market

We employed the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors with different levels of total market capitalizations through four major U.S. stock market indexes, including the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index, representing the stocks overall, the large capitalization stocks, the middle capitalization stocks and the small capitalization stocks, respectively. During the 2020 U.S. stock market crash, all four indexes lost more than a third of their values within five weeks, while both the middle capitalization stocks and the small capitalization stocks have suffered much greater losses than the large capitalization stocks and stocks overall. Our results indicate that the price trajectories of these four stock market indexes prior to the 2020 stock market crash have clearly featured the obvious LPPLS bubble pattern and were indeed in a positive bubble regime. Contrary to the popular belief that the 2020 US stock market crash was mainly due to the COVID-19 pandemic, we have shown that COVID merely served as sparks and the 2020 U.S. stock market crash had stemmed from the increasingly systemic instability of the stock market itself. We also performed the complementary post-mortem analysis of the 2020 U.S. stock market crash. Our analyses indicate that the probability density distributions of the critical time for these four indexes are positively skewed; the 2020 U.S. stock market crash originated from a bubble that had begun to form as early as September 2018; and the bubble profiles for stocks with different levels of total market capitalizations have distinct temporal patterns. This study not only sheds new light on the makings of the 2020 U.S. stock market crash but also creates a novel pipeline for future real-time crash detection and mechanism dissection of any financial market and/or economic index

Loss estimation of a code-conforming steel building to mainshock-aftershock sequences

Recent earthquakes have reminded us that a building designed under modern building codes aimed for life safety are at risk of significant financial loss. Aftershocks triggered by the mainshock could contribute significantly to the overall seismic loss. This paper presents an approach for loss estimation of buildings subjected to mainshock-aftershock sequences. The approach is to evaluate the seismic loss of a code-conforming four-story steel building subjected to two intensity levels of mainshocks, including Design Earthquake and Maximum Considered Earthquake, and the following aftershocks. Uncertainty propagation of loss estimation is examined by Monte Carlo Simulation with the Latin Hypercube Sampling. It was found that aftershocks may have a significant effect on the seismic loss. The transition cost is the main contributor to the losses caused by mainshocks, while the downtime costs may become the main contributor to seismic loss caused by aftershocks when the seismic intensity level increases. The dispersion associated with the expected loss uncertainties decreases as the mainshock intensity increases. The research could contribute to improve seismic loss estimation of buildings and facilitate stakeholders to make risk-informed decisions

Consideration of mainshock-aftershock sequences into performance-based seismic engineering

This paper investigates collapse probability of steel buildings from mainshock-aftershock sequences, as part of the ongoing research to develop a framework to integrate aftershock hazard into Performance-Based Engineering (PBE). During earthquake events, aftershocks can be observed following the mainshock. Aftershocks have the potential to cause severe damage to buildings and threaten life safety, even only minor damage is present from a mainshock. To date, the description of seismic hazard in PBE has not included the probability of aftershocks. Three approaches to generate collapse fragility for steel buildings that sustain certain level of damage from a mainshock are used to investigate the effects of mainshock-aftershock sequences. It is found that structural collapse capacity may reduce significantly when the building is subjected to a high intensity mainshock. As a result, the structure is likely to collapse even if only a small aftershock follows the mainshock. © 2013 American Society of Civil Engineers