Orbox

https://bit.ly/3D7hmSz

https://bit.ly/3D7hmSz

Two parts:

First, a 'now' / 'near term' 'Story Telling' scheme to build a public mental model of the causes, progression, and impact of the Kessler situation, and 'Computational' to provide a technical architecture for state of the art AR and GPU visualizations.

The first part, is Building Analogy and Metaphors to build a mental model for the public - the scenario we selected was the 'Freeway'. Basically, we selected two technical graphics with salient technical aspects of the debris problem, then extracted those and assigned them to the everyday life actors and objects on a rather messy freeway. The freeway lanes were the various orbital altitudes, the debris and payload objects were assigned to various vehicles, and the total lifetime mission trajectory phase were mapped to driving maneuvers, possible adverse events, For instance, a truck losing a tarp covering it's load would be similar to a payload fairing shedding.

This gives us a selection of modular story telling contrivances useful in all sort of media - 'scripts' that can be expanded and repurposed to all forms of media story telling - podcasts, animations, videos, movie scenes, and other narratives. Hollywood spins stories from plays, comic books into a wide variety of end products - films, TV series, etc.

The second part, is to address new and next generation computational capabilities to support technologies like augmented reality. The Hollywood studios have pooled resources into Open Source projects like the voxel volumetric calculation framework OpenVDB ( https://www.openvdb.org/ ):

• OpenVDB is an Academy Award-winning open-source C++ library comprising a novel hierarchical data structure and a suite of tools for the efficient storage and manipulation of sparse volumetric data discretized on three-dimensional grids. It was developed by DreamWorks Animation for use in volumetric applications typically encountered in feature film production and is now maintained by the Academy Software Foundation (ASWF).

Voxels are 3-D ‘pixels’ that describe volumes - this has many benefits - it enables Hollywood quality Special effects for Visualiation and AR ( Augmented Reality ) of Orbital Dynamics - like particle clouds, it can be extended to any number of ’N’ dimensions beyond 3-D, for example, as Space / Time / Volume ‘SToxels’ , and allows for very rapid parallel computation through graphic processing unit pipelines. Also they allow for very fast calculation of Volume Intersections, Generation of ‘Level Sets’, Fast Mods to Existing Volumes, and rapid access via Indexes and compression using Octrees.

This is a very mature technology, currently used in Autonomous Vehicle Guidance, Medical Imaging, Finite Element Analysis, Computational Fluid Dynamics, Weather Modeling, and Game Engines, and as mentioed for Hollywood Special Effects with OpenVDB. It is also ported by being 'baked into' current generation GPU hardware: "Nvidia Jetson AGX Xavier delivers up to 32 TeraOPS (TOPS) of compute performance from a 512-core integrated Volta Tensor Core GPU, and dual Deep Learning Accelerator (DLA) engines." - so tracking and visualizing every one of millions of orbital objects and their relationships is now achievable.

We used mostly technical literature from the NASA NTRS Technical Report Server, NASA and ESA web content, and Open Source project documentation like OpenVDB - https://www.esa.int/Enabling_Support/Space_Transportation/Types_of_orbits#orbit , https://directory.eoportal.org/web/eoportal/satellite-missions/content/-/article/orbital-debris , and https://directory.eoportal.org/web/eoportal/satellite-missions/o/orbital-debris#environment and some conent from https://earthobservatory.nasa.gov/features/OrbitsCatalog for the 'Lanes' and of course the NASA https://orbitaldebris.jsc.nasa.gov/

From our team members:

How would you describe your Space Apps experience? It was another experience to work with NASA, I recently did the Deep Food Space challenge. Both provided unique experiences.

What did you learn? So far, every NASA hackathon has provided insights on what NASA cares about and how they are tackling the issues of space.

What inspired your team to choose this challenge? We chose this challenge because we all agree it would be a fun experience for everyone

What was your approach to developing this project? Our approach was a systems engineering path to give a modular solution to virtualize how space debris can be simulated

How did your team resolve setbacks and challenges? One challenges was awareness of the time zone differences in the hackathon

Is there anyone you'd like to thank and why? I would like to thank my team, fellow Space entrepreneurs and community at large., and of course NASA. I hope to work with them soon.

And a HUGE thanks to Joseph Gruber, our mentor., especially the encouragement and technical feedback

Our approach was constrained because we had no experienced coders, and a very wide range of experience and technical knowledge. We over came this by the two part approach, the non-technical people worked on the mind mapping, and the more technical people addressed the computational framework.

From Elaine: "This was my second SpaceApps Hackathon with the same team. NASA might recognize me from some poetic Tweets. I won't say I'm familiar with any software anymore. I used to do some database management in a purchasing department; and helped to coordinate typing, printing, and distribution of planning documents. I have done an assortment of other jobs. Senior citizens don't have one sentence experience unless you are permanently retired."

It worked well.

We used Slack, Discord , and Google Docs for collaboration, Onshape for model generation, Blender for the voxel mockups and animations. Inkscape and GIMP for some of the illustrations.

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