CubeSats can encounter a myriad of difficulties in space like cosmic rays, temperature<br/>issues, and loss of control. By creating better, more reliable software, these problems can be<br/>mitigated and increase the chance of success for the mission. This research sets out to answer the<br/>question: how do we create reliable flight software for CubeSats? by providing a concentrated<br/>list of the best flight software development practices. The CubeSat used in this research is the<br/>Deployable Optical Receiver Aperture (DORA) CubeSat, which is a 3U CubeSat that seeks to<br/>demonstrate optical communication data rates of 1 Gbps over long distances. We present an<br/>analysis over many of the flight software development practices currently in use in the industry,<br/>from industry leads NASA, and identify three key flight software development areas of focus:<br/>memory, concurrency, and error handling. Within each of these areas, the best practices were<br/>defined for how to approach the area. These practices were also developed using experience<br/>from the creation of flight software for the DORA CubeSat in order to drive the design and<br/>testing of the system. We analyze DORA’s effectiveness in the three areas of focus, as well as<br/>discuss how following the best practices identified helped to create a more reliable flight<br/>software system for the DORA CubeSat.
star formation (Dahlem et al. 2006) by comparing maps of 120-240 MHz synchrotron emission and hydrogen alpha (Hα) emission of the tidally-interacting, edge-on, barred spiral galaxy UGC 9665. Synchrotron emission traces magnetic field strength to a rough first order, while Hα emission traces recent massive star formation. UGC 9665 was selected because it was included in the LOw Frequency ARray (LOFAR) TwoMetre Sky Survey (LoTSS; Shimwell et al. (2017)) as well as the Calar Alto Legacy Integral Field Area Survey (CALIFA; Sanchez et al. (2012)). I generated vertical intensity profiles at several distances along the disk from the galactic center for synchrotron emission and Hα in order to measure how the intensity of each falls off with distance from the midplane. In addition to correlating the vertical profiles to see if there is a relationship between star formation and magnetic field strength, I fit the LOFAR vertical profiles to characteristic Gaussian and exponential functions given by Dumke et al. (1995). Fitting these equations have been shown to be good indicators of the main mode of cosmic ray transport, whether it is advection (exponential fit) or diffusion (Gaussian fit) (Heesen et al. 2016). Cosmic rays originate from supernova,
and core collapse supernovae occur in star forming regions, which also produce
advective winds, so I test the correlation between star-forming regions and advective regions as predicted by the Heesen et al. (2016) method. Similar studies should be conducted on different galaxies in the future in order to further test these hypotheses and how well LOFAR and CALIFA complement each other, which will be made possible by the full release of the LOFAR Two-Metre Sky Survey (LoTSS) (Shimwell et al. 2017).