Insight is the first planetary mission since the apollo mission dedicated to acquiring GEO- physical data from surface-installed instruments, including a short-period and a broad-band seismometer,…

This federal contract award is for a research grant to the Trustees of the Colorado School of Mines (doing business as Colorado School of Mines) to support the INSIGHT mission, the first planetary mission since the Apollo mission dedicated to acquiring geophysical data from surface-installed instruments on Mars. The $353,078.00 grant will fund the development of 3D spectral-element wave simulations to characterize seismic signals received from a broadband seismometer on the INSIGHT mission. The research aims to investigate the effect of Martian topography, crustal structure, and interior dynamics on seismic waveforms at regional and global scales. This grant is part of the INSIGHT mission, which is led by the National Aeronautics and Space Administration (NASA). The Colorado School of Mines frequently supports federal agencies through research contracts and grants, leveraging its expertise in areas like materials science, geosciences, and engineering.

Insight is the first planetary mission since the apollo mission dedicated to acquiring GEO- physical data from surface-installed instruments, including a short-period and a broad-band seismometer, to explore the internal structure and dynamics of a solar system object other than the earth and the moon. Our goal is to characterize seismic signals which we expect to receive from a single broadband instrument onboard insight by numerical simulations of seismic wave propagation in conjunction with 3D (an)elastic models. Such 3D wave simulations will play a crucial role for interpreting the real martian data, specifically the complex waveforms that cannot be explained by approximations to the wave equation. We will investigate the effect of topography and distinct crustal dichotomy, size of the core as well as the 3D variations in crust and mantle on seismic waveforms at regional and global scales. The spectral-element method is particularly well-suited for simulations of wave propagation in terms of its accuracy and flexibility to capture complex structures (e.g., komatitsch and tromp, 2002; chaljub ET AL., 2003; capdeville ET AL., 2003; chaljub and valette, 2004; peter ET AL., 2011). As part of insight, we have started examining the effect of 3D martian crust on waveforms performing 3D spectral-element simulations (bozdag ET AL. 2017) for initially selected reference mars models. We now propose a thorough investigation of mars internal structure, specifically the crust, using the global and regional versions of the spectral-element wave simulation package SPECFEM3D (komatitsch and tromp, 2002). Attenuation, ellipticity, rotation and gravity (cowling approximation) can all be incorporated in simulations. We will address the following questions: 1- global simulations: we will implement a set of 1D/3D mars models and optimise the 3D numerical solver. The 3D mantle structure derived from the current thermochemical and min- eralogical models will also be used in simulations to better assess 3D crustal effects on body and surface waves. In addition the deep interior will be studied by analysing mantle and core phases. 2- regional simulations: higher-resolution simulations will be performed using the CUR- rent high-resolution topography, regolith thickness models, etc. To investigate, for instance, the effect of the ejecta and the shape of craters on body and surface waveforms. 3- blind tests: using the global version of SPECFEM3D, synthetics will be generated for a chosen 3D crust and mantle model using various seismic sources (marsquakes, meteorite impacts) and DIS- seminated for blind tests to the other insight researchers to validate how far the source and structure can be inferred with data from a single seismometer. Bozdag ET AL. (2017) demonstrated global simulations down to 9 s. We aim to take IT further to ultimately go down to 1 s. 4- we will also use 3D simulations to define the source of complex waveforms to be observed in real martian data which may not be explained by 1D simulations and simplified inversions. We will ultimately employ machine-learning algorithms to detect and discriminate phases in COM- parison with the observed data from mars based on our experience and tools being developed for earth's imaging problems. The research will be carried out in close collaboration with the insight team.