Several modeling methods are examined.
For planning of Mars surface missions, to be operated on a sol-by-sol basis by a team on Earth (where a “sol” is a Martian day), activities are described in terms of “sol types” that are strung together to build a surface mission scenario. Some sol types require ground decisions based on a previous sol’s results to feed into the activity planning (“ground in the loop”), while others do not. Due to the differences in duration between Earth days and Mars sols, for a given Mars local solar time, the corresponding Earth time “walks” relative to the corresponding times on the prior sol/day. In particular, even if a communication window has a fixed Mars local solar time, the Earth time for that window will be approximately 40 minutes later each succeeding day. Further complexity is added for non-Mars synchronous communication relay assets, and when there are multiple control centers in different Earth time zones.
The solution is the development of “ops efficiency factors” that reflect the efficiency of a given operations configuration (how many and location of control centers, types of communication windows, synchronous or non-synchronous nature of relay assets, sol types, more-or-less sustainable operations schedule choices) against a theoretical “optimal” operations configuration for the mission being studied. These factors are then incorporated into scenario models in order to determine the surface duration (and therefore minimum spacecraft surface lifetime) required to fulfill scenario objectives. The resulting model is used to perform “what-if” analyses for variations in scenario objectives. The ops efficiency factor is the ratio of the figure of merit for a given operations factor to the figure of merit for the theoretical optimal configuration.
The current implementation is a pair of models in Excel. The first represents a ground operations schedule for 500 sols in each operations configuration for the mission being studied (500 sols was chosen as being a long enough time to capture variations in relay asset interactions, Earth/Mars time phasing, and seasonal variations in holidays). This model is used to estimate the ops efficiency factor for each operations configuration.
The second model in a separate Excel spreadsheet is a scenario model, which uses the sol types to rack up the total number of “scenario sols” for that scenario (in other words, the ideal number of sols it would take to perform the scenario objectives). Then, the number of sols requiring ground in the loop is calculated based on the soil types contained in the given scenario. Next, the scenario contains a description of what sequence of operations configurations is used, for how many days each, and this is used with the corresponding ops efficiency factors for each configuration to calculate the “ops duration” corresponding to that scenario. Finally, a margin is applied to determine the minimum surface lifetime required for that scenario.
Typically, this level of analysis has not been performed until much later in the mission, and has not been able to influence mission design. Further, the notion of moving to sustainable operations during Prime Mission — and the effect that that move would have on surface mission productivity and mission objective choices — has not been encountered until the most recent rover missions (MSL and Mars 2018).
This work was done by Sharon L. Laubach of Caltech for NASA’s Jet Propulsion Laboratory. NPO-48262
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