How well can we predict earthquake site response so far? Site-specific approaches

Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a “good match” in spectral shape at ∼80%–90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.

Color sensor application in high-temperature spectral ratio pyrometer

Contactless thermal control tools play an important role in solving the high-temperature technological processes improving energy efficiency problems. In order to create such controls, the authors analyzed the developing possibility of spectral ratio high-temperature pyrometer using a multispectral radiation receiver (color sensor) TCS34725. In the paper this receiver application coefficients are determined, signals ratio graphs in different spectral intervals on temperature are given for two applications: without additional filtration of the control object radiation infrared component and using an opaque in the infrared spectrum part external filter.

A Novel Method for Predicting Local Site Amplification Factors Using 1-D Convolutional Neural Networks

The analysis of site seismic amplification characteristics is one of the important tasks of seismic safety evaluation. Owing to the high computational cost and complex implementation of numerical simulations, significant differences exist in the prediction of seismic ground motion amplification in engineering problems. In this paper, a novel prediction method for the amplification characteristics of local sites was proposed, using a state-of-the-art convolutional neural network (CNN) combined with real-time seismic signals. The amplification factors were computed by the standard spectral ratio method according to the observed records of seven stations in the Lower Hutt Valley, New Zealand. Based on the geological exploration data from the seven stations and the geological hazard information of the Lower Hutt Valley, eight parameters related to the seismic information were presumed to influence the amplification characteristics of the local site. The CNN method was used to establish the relationship between the amplification factors of local sites and the eight parameters, and the training samples and testing samples were generated through the observed and geological data other than the estimated values. To analyze the CNN prediction ability for amplification factors on unrecorded domains, two CNN models were established for comparison. One CNN model used about 80% of the data from 44 seismic events of the seven stations for training and the remaining data for testing. The other CNN model used the data of six stations to train and the remaining station’s data to test the CNN. The results showed that the CNN method based on the observation data can provide a powerful tool for predicting the amplification factors of local sites both for recorded positions and for unrecorded positions, while the traditional standard spectral ratio method only predicts the amplification factors for recorded positions. The comparison of the two CNN models showed that both can effectively predict the amplification factors of local ground motion without records, and the accuracy and stability of predictions can meet the requirements. With increasing seismic records, the CNN method becomes practical and effective for prediction purposes in earthquake engineering.

Analysis of Site Amplification and Nonlinear Response Based on Ground Motion Records at MYGH10 Station in Japan

Strong horizontal ground motions with the peak ground acceleration (PGA) larger than 1400 gal were observed at Yamamoto (MYGH10) station during the February 2021 Mj 7.3 off the east coast of Honshu, Japan, Fukushima earthquake. Firstly, in this paper, we discussed and verified the theoretical assumptions of the “Nakamura” method under weak and strong ground motions. The site amplification factor of the MYGH10 station was estimated using the surface horizontal-vertical spectral ratio (HVSR) and the surface-to-borehole spectral ratio (SBSR), and the corrected HVSRC, respectively. Meanwhile, the reasons for underestimating the site amplification factor when using HVSR were explained. The vertical amplification phenomenon of seismic P-wave in the high-frequency band was analysed under weak and strong ground motions. Secondly, we utilized HVSR, SBSR, and theoretical transfer function (TTF) based on the 1D wave propagation theory to study the nonlinear site response of MYGH10 station under the mainshock of the Fukushima earthquake and the historically weak and strong ground motions, respectively. The changes in frequencies and amplitudes of the spectral ratio curves when nonlinearities were occurring at the site were analysed and compared using the spectra ratio curves of weak ground motion records and TTF as references. Finally, the recovery of the site after strong nonlinearity was also evaluated by comparing the spectral ratio curves of aftershocks records. We found that the most significant amplification factor of the site increased from 7 to more than 10, and the predominant frequency decreased from 10 Hz to 3.8 Hz under the mainshock of the Fukushima earthquake. The predominant frequency returned to the previous value within three days after the mainshock, but the amplification factor did not.

Cucumber Powdery Mildew Detection Using Hyperspectral Data

This study aimed to understand the spectral changes induced by Podosphaera xanthii, the causal agent of powdery mildew, in cucumber leaves from the moment of inoculation until visible symptoms are apparent. A Principal Component Analysis (PCA) was applied to the spectra to assess the spectral separability between healthy and infected leaves. A spectral ratio between infected and healthy leaf spectra was used to determine the best wavelengths for detecting the disease. Additionally, the spectra were used to compute two spectral variables, i.e., the Red-Well Point (RWP) and the Red-Edge Inflexion Point (REP). A linear Support Vector Machine (SVM) classifier was applied to certain spectral features to assess how well these features can separate the infected leaves from the healthy ones. The PCA showed that a good separability could be achieved from 4 DPI. The best model to fit the RWP and REP wavelengths corresponded to a linear model. The linear model had a higher adjusted R2 for the infected leaves than for the healthy leaves. The SVM trained with five first principal components scores achieved an overall accuracy of 95% at 4 DPI, i.e., two days before the visible symptoms. With the RWP and REP parameters, the SVM accuracy increased as a function of the day of inoculation, reaching 89% and 86%, respectively, when symptoms were visible at 6 DPI. Further research must consider a higher number of samples and more temporal repetitions of the experiment.

Analytical 1D transfer functions for layered soils

Transfer functions are constantly used in both Seismology and Geotechnical Earthquake Engineering to relate seismic displacement at different depths within strata. In the context of Diffusive Theory, they also appear in the expression of the imaginary part of 1D Green's functions. In spite of its remarkable importance, their mathematical structure is not fully understood yet, except in the simplest cases of two or three layers at most. This incomplete understanding, in particular as to the effect of increasing number of layers, hinders progress in some areas, as researchers have to resort to expensive and less conclusive numerical parametric studies. This text presents the general form of transfer functions for any number of layers, overcoming the above issues. Owing to the formal connection between seismic wave propagation and other phenomena that, in essence, represent different instances of wave propagation in a linear-elastic medium, one can extend the results derived elsewhere [Garcia-Suarez, Joaquin. 2021. “Trace Spectrum of 1D Transfer Matrices for Wave Propagation in Layered Media.” engrXiv. June 24. doi:10.31224/osf.io/ygt8z] in the context of longitudinal wave propagation in modular rods to seismic response of stratified sites. The knowledge of the general closed-form expression of the transfer functions allows to analytically characterize the long-wavelength asymptotics of the horizontal-to-vertical spectral ratio for any number of layers.