NIOM Analysis of Earthquake Observation Records in a Rockfill Dam

ABSTRACT We applied the normalized input–output minimization method (a method developed for the analysis of propagation times in vertical array records) to long-term earthquake observation records from Aratozawa Dam (in Kurihara, Miyagi prefecture, Japan), spanning the period from July 1992 to December 2019 to determine the propagation velocity of seismic waves in the embankment, and investigated changes in soil properties. As a result, we showed that (1) the velocities of S and P waves in the upper section were 449 and 993 m/s, respectively, prior to the strong earthquake motions derived from earthquake records from January 1997 through October 2001, whereas 608 and 1538, respectively, in the lower section, (2) in the Iwate–Miyagi Nairiku earthquake, the S-wave velocity in the upper section decreased to 158 m/s in the principal shock, and (3) in subsequent minor earthquakes the propagation velocity increased more or less in proportion with the logarithm of the number of elapsed days, requiring three years or longer to return to the initial value, (4) although similar changes were observed in the Great East Japan earthquake of 2011, the reduction in propagation velocity that remained after the principal shock was smaller than in the case of the Iwate–Miyagi Nairiku earthquake, and it was judged that there were no large effects on the dam body such as those that occurred in the Iwate–Miyagi Nairiku earthquake, and furthermore (5) in the principal shock of the Iwate–Miyagi Nairiku earthquake, the shear modulus in the upper part of the dam body decreased from 400 to 50 MPa (with a maximum shear strain of 10−3), resulting in more pronounced changes than in the lower section, whereas the damping ratio increased by at least 10% in the lower section during the principal shock of the Iwate–Miyagi Nairiku earthquake, resulting in much greater changes than in the upper section.

A machine learning damage prediction model for the 2017 Puebla-Morelos, Mexico, earthquake

The 2017 Puebla, Mexico, earthquake event led to significant damage in many buildings in Mexico City. In the months following the earthquake, civil engineering students conducted detailed building assessments throughout the city. They collected building damage information and structural characteristics for 340 buildings in the Mexico City urban area, with an emphasis on the Roma and Condesa neighborhoods where they assessed 237 buildings. These neighborhoods are of particular interest due to the availability of seismic records captured by nearby recording stations, and preexisting information from when the neighborhoods were affected by the 1985 Michoacán earthquake. This article presents a case study on developing a damage prediction model using machine learning. It details a framework suitable for working with future post-earthquake observation data. Four algorithms able to perform classification tasks were trialed. Random forest, the best performing algorithm, achieves more than 65% prediction accuracy. The study of the feature importance for the random forest shows that the building location, seismic demand, and building height are the parameters that influence the model output the most.

A Review of the Capacitive MEMS for Seismology

MEMS (Micro Electro-Mechanical Systems) sensors enable a vast range of applications: among others, the use of MEMS accelerometers for seismology related applications has been emerging considerably in the last decade. In this paper, we provide a comprehensive review of the capacitive MEMS accelerometers: from the physical functioning principles, to the details of the technical precautions, and to the manufacturing procedures. We introduce the applications within seismology and earth sciences related disciplines, namely: earthquake observation and seismological studies, seismic surveying and imaging, structural health monitoring of buildings. Moreover, we describe how the use of the miniaturized technologies is revolutionizing these fields and we present some cutting edge applications that, in the very last years, are taking advantage from the use of MEMS sensors, such as rotational seismology and gravity measurements. In a ten-year outlook, the capability of MEMS sensors will certainly improve through the optimization of existing technologies, the development of new materials, and the implementation of innovative production processes. In particular, the next generation of MEMS seismometers could be capable of reaching a noise floor under the lower seismic noise (few tenths of ng/ H z ) and expanding the bandwidth towards lower frequencies (∼0.01 Hz).