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The book provides information on the major EEW systems in operation and on the state-of-the-art of the different blocks forming an EW system: the rapid detection and estimation of the earthquake’s focal parameters, the signal transmission, the engineering interface and the information reliability/false alarm problem. It is the first time that so many aspects of EEW systems have been specifically focused upon within a single book.
Man’s intensifying use of the Earth’s habitat has led to an urgent need for scientifically advanced ‘geo-prediction systems’ that accurately locate subsurface resources and forecast the timing and magnitude of earthquakes, volcanic eruptions and land subsidence. As advances in the earth sciences lead to process-oriented ways of modeling the complex processes in the solid Earth, the papers in this volume provide a survey of some recent developments at the leading edge of this highly technical discipline. The chapters cover current research in predicting the future behavior of geologic systems as well as the mapping of geologic patterns that exist now in the subsurface as frozen evidence of the past. Both techniques are highly relevant to humanity’s need for resources such as water, and will also help us control environmental degradation. The book also discusses advances made in seismological methods to obtain information on the 3D structure of the mantle and the lithosphere, and in the quantitative understanding of lithospheric scale processes. It covers recent breakthroughs in 3D seismic imaging that have enhanced the spatial resolution of these structural processes, and the move towards 4D imaging that measures these processes over time. The new frontier in modern Earth sciences described in this book has major implications for oceanographic and atmospheric sciences and our understanding of climate variability. It brings readers right up to date with the research in this vital field.
Written for a broad audience this book offers a comprehensive account of early warning systems for hydro meteorological disasters such as floods and storms, and for geological disasters such as earthquakes. One major theme is the increasingly important role in early warning systems played by the rapidly evolving fields of space and information technology. The authors, all experts in their respective fields, offer a comprehensive and in-depth insight into the current and future perspectives for early warning systems. The text is aimed at decision-makers in the political arena, scientists, engineers and those responsible for public communication and dissemination of warnings.
Cover Image Credit: Zhaofei Liu and Ying Li From the Institute of Earthquake Forecasting, China
Part 1: Research in the last decade on Earthquake Early Warning Systems (EEWSs) has undergone rapid development in terms of theoretical and methodological advances in real time data analysis, improved telemetry, and computer technology and is becoming a useful tool for practical real time seismic hazard mitigation. The main focus of this study is to undertake a feasibility study of an EEWS for the New Madrid Seismic Zone (NMSZ) from the standpoint of source location. Magnitude determination is addressed in a separate paper. The NMSZ covers a wide area with several heavily populated cities, vital infrastructures, and facilities located within a radius of less than 70 km from the epicenters of the 1811-1812 earthquakes. One of the challenges associated with the NMSZ is that while low to moderate levels of seismic activity are common, larger earthquakes are rare (i.e. there are no instrumentally recorded data for earthquakes with magnitudes greater than M5.5 in the NMSZ). We also recognize that it may not be realistic to provide early warning for all possible sources as is done on the west coast U.S. and we therefore focus on a specific source zone. We examine the stations within the NMSZ in order to answer the question What changes should be applied to the NMSZ network to make it suitable for earthquake early warning (EEW). We also explore needed changes to the Advanced National Seismic System (ANSS) Earthquake Monitoring System Real Time (AQMS RT) data acquisition system to make it useful for EEW. Our results show that EEW is feasible, though several technical challenges remain in incorporating its use with the present network.Part 2: Increasing vulnerability of metropolitan areas within stable continental regions (SCR), such as Memphis, TN and St. Louis, MO near the New Madrid Seismic Zone (NMSZ), to earthquakes and the very low probability level at which short term earthquake forecasting is possible make an earthquake early warning system (EEWS) a viable alternative for effective real-time risk reduction in these cities. In this study, we explore practical approaches to earthquake early warning (EEWS), and test the adaptability and potential of the real-time monitoring system in the NMSZ. We determine empirical relations based on amplitude and frequency magnitude proxies from the initial four seconds of the P-waveform records available from the Cooperative New Madrid Seismic Network (CNMSN) database for magnitude ????>2.1. The amplitude-based proxies include low pass filtered peak displacement (Pd), peak velocity (Pv), and integral of the velocity squared (IV2), whereas the frequency-based proxies include predominant period (????????), characteristic period (????????), and log average period (????????????????). Very few studies have considered areas with lower magnitude events. With an active EEW system in the NMSZ, damage resulting from the catastrophic event, as witnessed in 1811-1812, may be mitigated in real-time.
The present topical volume presents a collection of contributions from a workshop that took place in Madrid in February 2014. Earthquake Early Warning System (EEWS) are a rather recent development in seismology that allows issue warnings to a site with a short lead-time about the impending arrival of the largest strong ground motion from an earthquake, after the first wave arrivals have been detected nearer to the source by adequate sensors. The Ibero-Mahgrebian region, containing Portugal, Spain, Morocco, Algeria and Tunisia, is subject to the occurrence of large earthquakes that may be followed by large tsunamis, as was the case of the Lisbon earthquake of 1755.
Original research on SHM sensors, quantification strategies, system integration and control for a wide range of engineered materials New applications in robotics, machinery, as well as military aircraft, railroads, highways, bridges, pipelines, stadiums, tunnels, space exploration and energy production Continuing a critical book series on structural health monitoring (SHM), this two-volume set (with full-text searchable CD-ROM) offers, as its subtitle implies, a guide to greater integration and control of SHM systems. Specifically, the volumes contain new research that will enable readers to more efficiently link sensor detection, diagnostics/quantification, overall system functionality, and automated, e.g., robotic, control, thus further closing the loop from inherent signal-based damage detection to responsive real-time maintenance and repair. SHM performance is demonstrated in monitoring the behavior of composites, metals, concrete, polymers and selected nanomaterials in a wide array of surroundings, including harsh environments, under extreme (e.g., seismic) loading and in space. New information on smart sensors and network optimization is enhanced by novel statistical and model-based methods for signal processing and data quantification. A special feature of the book is its explanation of emerging control technologies. Research in these volumes was initially presented in September 2013 at the 9th International Workshop on Structural Health Monitoring (IWSHM), held at Stanford University and sponsored by the Air Force Office of Scientific Research, the Army Research Laboratory, and the Office of Naval Research.
This book gathers selected high-impact articles from the 3rd International Conference on Data Science, Machine Learning & Applications 2021. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
After the great tsunami of 2004 and the earthquake in Sichuan, China, in 2008, two big thinkers knew they must try to prevent the damage inflicted by surprise earthquakes. George R. Daglish and Iurii P. Sizov teamed up to create an experimental seismic software system that contains application areas for inclusion in an earthquake early warning software structure. In this book, they highlight the work they’ve done thus far. The algorithms can be grouped into several main types: planar earth calculations to determine epicenters; calculations over a spherical earth model to determine epicenters; rapid tabular scans to determine epicenters and hypocenters concurrently, using either spherical or spheroidal earth geometry directly; and hypocenter scans using spheroidal earth geometry. The authors also describe the testing of all members of the grouping, using real earthquake data. They assess the timing and accuracy of each against received and current results taken from the Incorporated Research Institutions for Seismology archive. If the world doesn’t take concerted action to predict and track earthquakes, the consequences will be unthinkable, which is why we must work toward real-time earthquake tracking and localization.