Rapid source inversions of the 2023 SE Türkiye earthquakes with teleseismic and strong-motion data

We conducted rapid inversions of rupture process for the 2023 earthquake doublet occurred in SE Türkiye,the first with a magnitude of M_(W)7.8 and the second with a magnitude of M_(W)7.6,using teleseismic and strong-motion data.The teleseismic rupture models of the both events were obtained approximately 88 and 55 minutes after their occurrences,respectively.The rupture models indicated that the first event was an asymmetric bilateral event with ruptures mainly propagating to the northeast,while the second one was a unilateral event with ruptures propagating to the west.This information could be useful in locating the meizoseismal areas.Compared with teleseismic models,the strong-motion models showed relatively higher resolution.A noticeable difference was found for the M_(W)7.6 earthquake,for which the strong-motion models shows a bilateral event,rather than a unilateral event,but the dominant rupture direction is still westward.Nevertheless,all strong-motion models are consistent with the teleseismic models in terms of magnitudes,durations,and dominant rupture directions.This suggests that both teleseismic and strong-motion data can be used for fast determination of major source characteristics.In contrast,the strong-motion data would be preferable in future emergency responses since they are recorded earlier and have a better resolution ability on the source ruptures.

GBO algorithm for seismic source parameters inversion

The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault parameters inversion has nonlinear characteristics, and the gradient-based optimizer(GBO) has the characteristics of fast convergence speed and falling into local optimum hardly. This paper applies GBO algorithm to simulated earthquakes and real LuShan earthquakes in the nonlinear inversion of the Okada model to obtain the source parameters. The simulated earthquake experiment results show that the algorithm is stable, and the seismic source parameters obtained by GBO are slightly closer to the true value than the multi peak particle swarm optimization(MPSO). In the 2013 LuShan earthquake experiment, the root mean square error between the deformation after forwarding of fault parameters obtained by the introduced GBO algorithm and the surface observation deformation was 3.703 mm, slightly better than 3.708 mm calculated by the MPSO. Moreover, the inversion result of GBO algorithm is better than MPSO algorithm in stability. The above results show that the introduced GBO algorithm has a certain practical application value in seismic fault source parameters inversion.

Research on inversion method for complex source-term distributions based on deep neural networks

This study proposes a source distribution inversion convolutional neural network (SDICNN), which is deep neural network model for the inversion of complex source distributions, to solve inversion problems involving fixed-source distributions. A function is developed to obtain the distribution information of complex source terms from radiation parameters at individual sampling points in space. The SDICNN comprises two components:a fully connected network and a convolutional neural network. The fully connected network mainly extracts the parameter measurement information from the sampling points,whereas the convolutional neural network mainly completes the fine inversion of the source-term distribution. Finally, the SDICNN obtains a high-resolution source-term distribution image. In this study, the proposed source-term inversion method is evaluated based on typical geometric scenarios. The results show that, unlike the conventional fully connected neural network, the SDICNN model can extract the two-dimensional distribution features of the source terms, and its inversion results are better. In addition, the effects of the shielding mechanism and number of sampling points on the inversion process are examined. In summary, the result of this study can facilitate the accurate assessment of dose distributions in nuclear facilities.

An improved four-dimensional variation source term inversion model with observation error regularization

Aiming at the Four-Dimensional Variation source term inversion algorithm proposed earlier,the observation error regularization factor is introduced to improve the prediction accuracy of the diffusion model,and an improved Four-Dimensional Variation source term inversion algorithm with observation error regularization(OER-4DVAR STI model)is formed.Firstly,by constructing the inversion process and basic model of OER-4DVAR STI model,its basic principle and logical structure are studied.Secondly,the observation error regularization factor estimation method based on Bayesian optimization is proposed,and the error factor is separated and optimized by two parameters:error statistical time and deviation degree.Finally,the scientific,feasible and advanced nature of the OER-4DVAR STI model are verified by numerical simulation and tracer test data.The experimental results show that OER-4DVAR STI model can better reverse calculate the hazard source term information under the conditions of high atmospheric stability and flat underlying surface.Compared with the previous inversion algorithm,the source intensity estimation accuracy of OER-4DVAR STI model is improved by about 46.97%,and the source location estimation accuracy is improved by about 26.72%.

Multi-Frequency Contrast Source Inversion for Reflection Seismic Data

In the contrast source inversion(CSI)method,the contrast sources(equiva-lent scattering sources)and the contrast(parameter perturbation)are iteratively recon-structed by an alternating optimization scheme.Traditionally integral equation CSI method is formulated for transmission tomography using analytic Green’s function in homogeneous background.To extend the method to the case of reflection seismology,in this paper,we use WKBJ method to compute the Green’s function of depth dependent background media and the solving method of equations to initialize the contrast source of different frequencies,resulting in an efficient method to invert multi-frequency reflection seismic data–multi-frequency contrast source inversion method(MFCSI).Numerical results for the Marmousi model show that MFCSI method can obtain good results even when low frequency data are missing,in which case the conventional FWI fails.

Time-Dependent Tsunami Source Following the 2018 Anak Krakatau Volcano Eruption Inferred from Nearby Tsunami Recordings

The eruption of the Anak Krakatau volcano,Indonesia,on 22 December 2018 induced a destructive tsunami(the Sunda Strait tsunami),which was recorded by four nearby tidal gauges.In this study we invert the tsunami records and recover the tsunami generation process.Two tsunami sources are obtained,a static one of instant initial water elevation and a time-dependent one accounting for the continuous evolution of water height.The time-dependent results are found to reproduce the tsunami recordings more satisfactorily.The complete tsunami generation process lasts approximately 9 min and features a two-stage evolution with similar intensity.Each stage lasts about 3.5 min and elevates a water volume of about 0.13 km3.The time,duration and volume of the volcano eruption in general agree with seismic records and geomorphological interpretations.We also test different sizes of the potential source region,which lead to different maximum wave height in the source area,but all the results of time-dependent tsunami sources show the robust feature of two stages of wave generation.Our results imply a time-dependent and complex process of tsunami generation during the volcano eruption.

EXPONENTIAL TIKHONOV REGULARIZATION METHOD FOR SOLVING AN INVERSE SOURCE PROBLEM OF TIME FRACTIONAL DIFFUSION EQUATION

In this paper,we mainly study an inverse source problem of time fractional diffusion equation in a bounded domain with an over-specified terminal condition at a fixed time.A novel regularization method,which we call the exponential Tikhonov regularization method with a parameter γ,is proposed to solve the inverse source problem,and the corresponding convergence analysis is given under a-priori and a-posteriori regularization parameter choice rules.Whenγis less than or equal to zero,the optimal convergence rate can be achieved and it is independent of the value of γ.However,when γ is greater than zero,the optimal convergence rate depends on the value of γ which is related to the regularity of the unknown source.Finally,numerical experiments are conducted for showing the effectiveness of the proposed exponential regularization method.

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

Identifying and localizing of seismogenic electromagnetic anomalies from data observed by permanent MT stations

In this research, an arbitrarily oriented electric dipole at subsurface is used to simulate Seismogenic Electromagnetic(SEM) radiation emanating from a seismic zone during its gestation phase. Analytical synthesis of responses at the Lijiang magnetotelluric(MT) station has revealed that SEM radiation could induce identifiable anomalies in the electromagnetic(EM)spectrum, apparent resistivity and phase within specific frequency bands. Background variations were extracted from long-term observation data of Dali and Lijiang MT stations, enabling the identification of SEM anomalies related to the Yunlong and Yangbi earthquakes. Multiple parameters of dipole sources at subsurface were obtained by applying the Differential Ant Colony Optimization(DACO) algorithm to anomalous data of two stations with multi-frequencies and various response functions. The spatial distribution of these predicted dipoles is predominantly clustered in or around the seismogenic area, with their azimuthal orientation aligning towards the seismogenic fault in general. This study has demonstrated the potential of using subsurface electric dipole simulations for SEM radiation analysis, offering a feasible approach for the prediction and understanding of seismogenic zones.

SOURCE TERM IDENTIFICATION WITH DISCONTINUOUS DUAL RECIPROCITY A PPROXIM ATION AND QUASI-NEWTON METHOD FROM BOUNDARY OBSERVATIONS

This paper deals with discontinuous dual reciprocity boundary element method for solving an inverse source problem.The aim of this work is to determine the source term in elliptic equations for nonhomogenous anisotropic media,where some additional boundary measurements are required.An equivalent formulation to the primary inverse problem is established based on the minimization of a functional cost,where a regularization term is employed to eliminate the oscillations of the noisy data.Moreover,an efficient algorithm is presented and tested for some numerical examples.

An Inverse Source Problem with Sparsity Constraint for the Time-Fractional Diffusion Equation

In this paper,an inverse source problem for the time-fractional diffusion equation is investigated.The observational data is on the final time and the source term is assumed to be temporally independent and with a sparse structure.Here the sparsity is understood with respect to the pixel basis,i.e.,the source has a small support.By an elastic-net regularization method,this inverse source problem is formulated into an optimization problem and a semismooth Newton(SSN)algorithm is developed to solve it.A discretization strategy is applied in the numerical realization.Several one and two dimensional numerical examples illustrate the efficiency of the proposed method.

Radiogenic Source Identification for the Helium Production-Diffusion Equation

Knowledge of helium diffusion kinetics is critical for materials in which helium measurements are made,particulary for thermochronology.In most cases the helium ages were younger than expected,an observation attributes to diffusive loss of helium and the ejection of high energy alpha particles.Therefore it is important to accurately calculate the distribution of the source term within a sample.In this paper,the prediction of the helium concentrations as function of a spatially variable source term are considered.Both the forward and inverse solutions are presented.Under the assumption of radially symmetric geometry,an analytical solution is deduced based on the eigenfunction expansion.Two regularization methods,the Tikhonov regularization and the spectral cutoff regularization,are considered to obtain the regularized solution.Error estimates with optimal convergence order are shown between the exact solution and the regularized solution.Numerical examples are presented to illustrate the validity and effectiveness of the proposed methods.