Innovative Aerospace Engineers Need A Speech Recognition Based CADCAM Design Software System

About 4-years ago, I talked with an aerospace designer of high-tech stealthy aircraft, very much a Team USA type of person at the top of the food chain with one of the major top three defense aerospace companies, working on black projects. This individual and I discussed some of the challenges encountered with design, testing, rapid prototyping, risk management and making it all work. Okay so, I have some new ideas and concepts I’d like to suggest to the industry call it Sixth Generation Aerospace Design if you will – let’s talk.

Not long ago, I was reading an interesting research paper titled; “Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications,” by Stephen A. Jacklin, Johann M. Schumann, and Pramod P. Gupta of NASA Ames Research Center, and Michael Richard, Kurt Guenther, and Fola Soares of NASA Dryden Flight Research Center, which stated;

“Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur.”

Now then, I’d like to take this concept and system and couple it with AI software being used in manned and unmanned systems which soon will all be updated in real time, and have all of that downloaded into design software for the designing of future aerospace systems, modifying the fluid dynamic models and designs of the aircraft, performance envelope and even help suggest the materials needed for various components and the density, size, and weight of those components. Why not? Eventually such data could even be used on a robotic assembly line as prototypes or the first 200 of anything built encounter real world problems.

Indeed as an aerospace designer, I want this system to offer suggestions along the way and stored as I design. If I want to bypass suggestions for a moment, pause, or allowed to play if I choose to accept the advice in real time as offered.

I want this system to give detailed explanations for its advice – for instance it might tell me that my wing design will have stability problems and wing flutter passing through a given airspeed with a given pressure along with examples of altitudes where this might occur or in certain conditions – or – if such design changes alter the center of gravity or payload safety factors – things of this nature. Please consider this and think on it.

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