Army Research Laboratory System Engineering Approach to Advanced Concept Architecture Selection (SEA2CAS)

Objective: With the increasing role of Unmanned Aerial Systems (UAS) in the battlespace, the Army Research lab was interested in developing a tool to enable rapid exploration of the design space to produce mission-specific vehicles. This would allow operators in the field to quickly tailor an architecture to be additively manufactured and deployed – with the advantage of the vehicle being ideally configured for the mission – all within the space of 24 hours.

Contribution:

• Worked with the team to develop the required environment: System Engineering Approach to Advanced Concept Architecture Selection (SEA2CAS); an environment enabling exploration and quantification of capabilities of different small-sized UAS architectures across a broad set of mission parameters

• Implemented probabilistic analysis (Monte Carlo methods) to integrate future design forecasting into the existing environment

• Utilized probabilistic methods to investigate the impact of technology shift on vehicle performance by using web-based algorithms to continually update available component specifications

Skills: 

• Systems engineering for scalable design architectures

• Design space exploration and modeling

• Software development (Python)

• Probabilistic simulation & forecasting

• Developing web crawlers and data aggregators

Takeaways: This project – focused on the conceptual design phase – gave me a great appreciation of the importance of developing systems that can utilize and optimize early design flexibility, particularly with changing mission requirements. Working with the Army Research Lab was an opportunity that gave me experience with another kind of stakeholder, and insight into the interaction between academic research and the defense stakeholders.