For those interested in getting a better handle on the vehicle thermodynamics, see[1].
Feel free to play around with the open-source python model here[2]
Following Jean Luc Doumont's simple advice on creating powerpoints has dramatically helped me create more effective presentations that hold people's attention. I highly recommend his book [1] and presentations [2] on reducing noise in slides to maximize the effectiveness of key-takeaways.
I work for a large aerospace company. How can we adopt lean startup ideas for hardware projects where the design iterations are much more expensive and lead times more severe?
1 MILLION people aren't enough to see network effects??
Is 3M [1] closer to the magic number? I moved from Boston(4M) to Cleveland(1.7M) and although the lifestyle is different, there is still way more opportunities, culture, entertainment, etc..., than anyone could absorb in a single lifetime in either place.
I visit my friends in SF every year and although they make more than double my salary, they can't even come close to matching my apartment situation. There is an infinite number of things to do in any city, and I can already afford things (like a house, or an acre of land even!) that aren't even fathomable to them. I won't stay in Cleveland forever, simply because I'd like to experience other cities, but I can't say SF is even in my top three. SF is a great place, but I'd like to find one of the still relatively "undiscovered" great places that isn't completely saturated.
Warning: A common pitfall of "flashy" presentations is that even if you can avoid making it look gimmicky, the audience is too busy watching the effects and not listening to you. Is your intention to dazzle people, or optimize the amount of information your audience absorbs?
https://www.youtube.com/watch?v=meBXuTIPJQk
Hybrid Airships might not fair well on the particular log/log plot shown, but there are other figures of merit to be considered: Emissions, noise, necessary landing infrastructure, flight-time, fuel consumption vs. aircraft productivity (payload x distance / hr)
Many projects at NASA are just starting to ramp up open-source efforts, and it can be very challenging to publicly release aerospace toolsets. Give it some time to build up momentum.
NASA engineers have also released an optimization framework for the Hyperloop concept as well. It's completely open-source and written in Python.
Docs here:
http://openmdao-plugins.github.io/Hyperloop/
Their baseline optimization focuses on 5 subsystems: Compressor Cycle Analysis, Pod Geometry, Tube Flow Limitations, Tube Wall Temperature, and Mission Analysis
Initial results indicate that the concept is still very viable. However, due to very tight coupling between the tube and vehicle size, the tube size will need to be around twice as large as originally proposed by the Tesla/SpaceX team to reach the proposed speeds.
Feel free to download the entire analysis and play with it yourself, without purchasing several expensive toolboxes from MATLAB!