Statistical Approach to Deriving Characteristic Seismic Decay Time of Moonquake Mechanisms

STATISTICAL APPROACH TO DERIVING CHARACTERISTIC SEISMIC DECAY TIME OF MOONQUAKE MECHANISMS. P. M. Bremner1 and H. B. Woo1, 1NASA Marshall Space Flight Center, 320 Sparkman Dr NW, Huntsville, AL 35812 ([email protected], [email protected]). Introduction: The Apollo Passive Seismic Experiment (PSE) operated from 1969 to 1977 providing seismic data from 5 types of ballistic seismic wave sources: (1) Deep moonquakes, (2) Shallow moonquakes, (3) Natural impacts from meteorite strikes, (4) Artificial impacts, and (5) thermal moonquakes. Seismic hazard assessment can be described with peak ground accelerations and ground acceleration decay times. Work by [4] and others have modeled characteristics of peak ground acceleration for shallow moonquake reuters along lobate scarps. The work presented here uses a simplistic statistical approach to analyze the decay time and character of ground accelerations. Moreover, the results below have been incorporated into the NASA Design Specification for Natural Environments (DSNE) revision-J document to specify ground shaking conditions for engineering purposes. Methods: Seismograms of each event (2-hour slice) were downloaded from the data archive with a 0.5 hours time buffer before and after the time slice to reduce edge effects when applying pass-band filters and Fourier transform. The seismic instrument response was removed using a Python toolbox ObsPy with pre-defined frequency filters and flat-response transfer functions for mid-period vertical (MHZ) and horizontal (MH1 and MH2) components and short-period vertical (SHZ) component to acquire seismic acceleration data [1,3]. Linear interpolation was applied to account for missing data points and outliers in the 4th quartile (above 75%) were removed using the Interquartile Range (IQR) method. After pre-processing, the envelope of ground acceleration was extracted and separated into 1-minute time bins, where the average and maximum values were estimated in each bin. This process was repeated for all events, and bins that share the same time range within a single event category and sensor channel were grouped for statistical analysis to compute their RMS, standard deviation, and peak value to evaluate the event decay trend in time. To qualitatively identify decay trends of different event types and seismic components, a non-linear least square method was used to find best fitting exponential curves. Results and Discussion: It should be noted that the observed ground accelerations were not adjusted for distance to the seismometers, but instead processed as-recorded. Since the RMS averages include observed events from a variety of distances and directions from the seismometers, the statistical time series show characteristic decay times observed by the longand short-period Apollo seismometers. The following results are shown in Figure 1: For natural impacts, moderate short-period ground accelerations continue throughout the two-hour window, likely due to the high scattering/low attenuation properties of the lunar regolith. Long-period ground accelerations are characterized by a steep climb in amplitude reaching peak in ≤10 min, and then followed by a steady decline. At 60 minutes past the onset of shaking, the long-period time series shows amplitudes have reduced to near background levels of scattered seismic energy. Artificial impacts show similar characteristics to Natural impacts for short-period signals, but have a steeper increase in amplitude reaching the peak for long-period acceleration signals. However, longer time is required for the amplitude to reach the background noise level. For shallow moonquakes, both shortand long-period ground accelerations exhibit a steep climb in amplitudes, again, reaching peak in ≤10 min. A steady decline was observed in the long-period ground accelerations, similar to the long-period natural impacts. The short-period ground accelerations, however, decline near symmetric about the peak. At 40 minutes past the onset of shaking, the short-period time series shows amplitudes have reduced to near background level of scattered seismic energy. Deep moonquakes exhibit the lowest peak amplitudes among the different seismic wave sources posing minimal hazard. A strong and consistent background tremor is observed throughout the recording that almost masks the short-period signal. Moonquake signals are characterized by the signal peak arrival time (rise time), where longer rise time indicates increased scattering from waves propagating through a more heterogeneous or fractured medium followed by an even longer decay time [2]. The characteristics of signal decay also vary in frequency potentially related to the origin of the event source and source mechanism. Though this analysis was done for engineering purposes of hazard mitigation for lunar assets, the characteristic decay times can be further developed to illuminate source mechanics of different moonquake types. References: [1] Lognonné, P. et al. (2009). Journal of Geophysical Research: Planets, 114(E12). [2] Nunn, C. et al. (2020). Space Science Reviews, 216(5), 89. [3] Nunn, C. et al. (2022). The Planetary Science Journal, 3(9), 219. [4] Watters, T. R. et al. (2019). Nature Geoscience, 12(6), 411-417. Figure 1: Seismic acceleration decay times for the labeled lunar seismic event types from aggregated statistics of all moonquakes of that type recorded by the Apollo PSE. See text for description of processing method. RMS is the root mean square of peak accelerations aggregated from the processed events. STD is the RMS plus the first standard deviation, and 2 STD is the RMS plus two times the × standard deviation. Green plus signs denote the maximum observed acceleration out of the aggregate at the indicated times in the timeseries. The red curves are the best-fit functions of the max peaks and have the form . MHZ 𝐴(𝑡)=𝑎×𝑒−𝑏*𝑡+𝑐 indicates the vertical component of the mid-period sensor, and likewise MH1_2 for the combined horizontal components. SHZ indicates the vertical component of the short-period sensors.