Sensitivity analysis of an equivalent source model for a military jet aircraft

2013 ◽  
Vol 134 (5) ◽  
pp. 4127-4127
Author(s):  
Tracianne B. Neilsen ◽  
Kent L. Gee ◽  
David M. Hart ◽  
Michael M. James
2014 ◽  
Author(s):  
Tracianne B. Neilsen ◽  
Kent L. Gee ◽  
David M. Hart ◽  
Michael M. James

2019 ◽  
Vol 109 (6) ◽  
pp. 2305-2324 ◽  
Author(s):  
Amin Esmaeilzadeh ◽  
Dariush Motazedian

Abstract We used a finite‐difference modeling method to investigate the sensitivity of the ground‐motion simulation results to the main input parameters, including the source model, regional path properties, and local site conditions. We used a spectral frequency range of 0.1–1 Hz for the Kinburn bedrock topographic basin, Ottawa, Canada, for the Ladysmith earthquake (Mw 4.7). Some findings are known facts; however, the unique geophysical conditions in the Ottawa area, such as the high contrast between the shear‐wave velocities of the bedrock and the shear‐wave velocity of the soil, were the reason for a comprehensive sensitivity analysis. Using a Gaussian source function with a short half‐duration increased the peak ground velocities (PGVs) and the amplitude of the velocity Fourier spectrum. Relaxation times and relaxation coefficients for the viscoelastic simulation significantly increased the amplitude of later arrivals at the soil site, which, consequently, led to an increase in PGV, the amplitude of the pseudospectral acceleration (PSA) ratio, and the velocity Fourier spectrum for a small earthquake. Employing a small soil Q model damped a significant amount of energy of the waves in the basin; thus, PGV, the PSA of soil to rock ratios, and the velocity Fourier spectrum were dependent on the soil Q model. Also, using a high‐velocity contrast between soil and rock increased PGVs and the amplitude of the PSA of the soil to rock ratios, whereas the frequency content of the waves shifted toward lower frequencies. Using a finite‐fault source model for a scenario large earthquake (Mw 7) significantly reduced the PGV values relative to a point‐source model. Using nonlinear‐viscoelastic simulation for a large earthquake (Mw 7) reduced the amplitude of the later arrivals and the amplitude of the PSA of the soil to rock ratios, and shifted the frequency content of waves toward lower frequency.


2009 ◽  
Vol 323 (3-5) ◽  
pp. 697-717 ◽  
Author(s):  
C. Polacsek ◽  
G. Desquesnes ◽  
G. Reboul

2021 ◽  
Author(s):  
Duan Li ◽  
Jinsong Du ◽  
Chao Chen ◽  
Qing Liang ◽  
Shida Sun

Abstract. Marine magnetic surveys over oceanic ridge regions are of great interest for investigations of structure and evolution of oceanic crust, and have played a key role in developing the theory of plate tectonics (Dyment, 1993; Maus et al, 2007; Vine and Matthews, 1963). In this study, we propose an interpolation approach based on the dual-layer equivalent source model for the generation of a magnetic anomaly map based on sparse survey line data over oceanic ridge areas. In this approach, information from an ocean crust age model is utilized as constraint for the inversion procedure. The constraints can affect the magnetization distribution of equivalent sources following crust age. The results of synthetic tests show that the obtained magnetic anomalies have higher accuracy than those obtained by other interpolation methods. Meanwhile, considering the unclear on the true magnetization directions of sources and the background field in the synthetic model, well interpolation result can still be obtained. We applied the approach to magnetic data obtained from five survey lines east of the Southeast Indian Ridge. This prediction result is useful to improve the lithospheric magnetic field models WDMAMv2 and EMAG2v3, in the terms of spatial resolution and the consistency with observed data.


2015 ◽  
Vol 137 (4) ◽  
pp. 2398-2398 ◽  
Author(s):  
Vera A. Khokhlova ◽  
Petr V. Yuldashev ◽  
Pavel B. Rosnitskiy ◽  
Wayne Kreider ◽  
Adam D. Maxwell ◽  
...  

2019 ◽  
Vol 6 (4) ◽  
pp. 7038-7047 ◽  
Author(s):  
Huapeng Zhao ◽  
Chaofeng Li ◽  
Zhizhang Chen ◽  
Jun Hu

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