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Numerous high-thrust and low-thrust space propulsion technologies have been developed in the recent years with the goal of expanding space exploration capabilities; however, designing and optimizing a multi-mission campaign with both high-thrust and low-thrust propulsion options are challenging due to the coupling between logistics mission design and trajectory evaluation. Specifically, this computational burden arises because the deliverable mass fraction (i.e., final-to-initial mass ratio) and time of flight for low-thrust trajectories can can vary with the payload mass; thus, these trajectory metrics cannot be evaluated separately from the campaignlevel mission design. To tackle this challenge, this paper develops a novel event-driven space logistics network optimization approach using mixed-integer linear programming for space campaign design. An example case of optimally designing a cislunar propellant supply chain to support multiple lunar surface access missions is used to demonstrate this new space logistics framework. The results are compared with an existing stochastic combinatorial formulation developed for incorporating low-thrust propulsion into space logistics design; our new approach provides superior results in terms of cost as well as utilization of the vehicle fleet. The eventdriven space logistics network optimization method developed in this paper can trade off cost, time, and technology in an automated manner to optimally design space mission campaigns.(GMCNF) model [5,6]. These space logistics methods have been extended to campaign-level mission design framework using a time-expanded network by Ho et al [7,8]. These frameworks approach the problem of campaign design through a logistics-driven perspective. Other works such as the EXAMINE framework [9] and the graph-theory-based space system architectures model developed by Arney et al. [10] can compare and/or optimize user-input system architecture scenarios.A critical limitation of the conventional space logistics design methods referenced above is that they are unable to account for the use of low-thrust vehicles for transportation. More specifically, the conventional methods assumed a decoupling between logistics mission design and trajectory evaluation, where the mission design model takes pre-computed trajectory metrics such as the final-to-initial mass ratio (or ∆v) and time of flight for each arc as inputs and then optimize the mission architecture including the logistics flows of propellant, payload, and other commodities. This approach is effective for a campaign with a fleet of high-thrust spacecraft, and responded well to the background that many past space exploration campaigns considered only high-thrust spacecraft options (e.g., chemical propulsion). However, given the significant advancements made in low-thrust propulsion technology (e.g., SEP) in recent years, there is a growing interest in the question of how low-thrust spacecraft can be optimally integrated into a space exploration campaign. Thus, we need a mathematical fram...

The Lower Atmosphere/Ionosphere Coupling Experiment (LAICE) CubeSat mission will focus on understanding the interaction of atmospheric gravity waves generated by weather systems in the lower atmosphere with the mesosphere, lower thermosphere, and ionosphere (MLTI). Specifically, LAICE will focus on the energy and momentum delivered by these waves and attempt to connect the wave sources and the wave effects in three widely different altitude ranges, substantially adding to our knowledge of critical coupling processes between disparate atmospheric regions. The LAICE mission consists of a 6U CubeSat with a four-instrument payload. The retarding potential analyzer (RPA) will provide in-situ ion density and temperature measurements. A four-channel photometer will measure density and temperature variations in the mesosphere through observations of O 2 (0,0) Atmospheric band and O 2 Herzberg I band airglows. There are two pressure sensors that comprise the Space Pressure Suite (SPS): the Space Neutral Pressure Instrument (SNeuPI) and the LAICE Ionization gauge Neutral Atmosphere Sensor (LINAS). Both will provide neutral density measurements, but SNeuPI is a prototype sensor that will be validated by LINAS. This CubeSat mission, scheduled for launch in early 2016 from the International Space Station, provides a cost-effective approach to measuring low altitude in-situ parameters along with simultaneous imaging that is capable of addressing the fundamental questions of atmospheric gravity wave coupling in the MLTI region.

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