Raffaele Gradini
Advisor: Prof. Mavris

will defend a doctoral thesis entitled,

Ship And Naval Technology Trades-offs for Science and Technology Investment Purposes

On

Monday, December 13 at 8 a.m.
https://bluejeans.com/874936340/5458

Abstract
Long-term naval planning has always been a challenge, but in recent years the difficulty has increased. The degradation of the security environment is leading toward a more volatile, uncertain, complex, and ambiguous world, heavily affecting the quality of predictions needed in long-term defense technology investments. This work tackles the problem from the perspective of the maritime domain, with a new approach stemming from the state-of-the-art in the defense investment field. Moving away from classic methodologies that rely on well-defined assumptions, it is possible to find investment processes that are broad enough, yet concrete, to support decision making in naval technology trades for science and technology purposes. In fulfilling this objective, this work is divided in two main areas: identifying technological gaps in the security scenario and providing robust technology investment strategies to cover those gaps. The core of the first part is the capability of decomposing maritime assets using modern taxonomies, to map the impact of different technologies on the ship. Once technologies are mapped, they can be traded inside assets, and assets inside fleets to quantitatively evaluate the overall fleet robustness. The first deliverable achieved through this process is called Vulnerable Scenarios, a list of possible conflict scenarios in which a tested fleet would consistently fail. The second deliverable is called Robust Strategies and is composed of different technological investments to allow the studied fleet in succeeding the discovered Vulnerable Scenario. The methodology uses the Patient Rule Induction Method and an adaptive response system to provide an innovative way of enhancing screening of non-relevant maritime scenarios reducing the leading time for investment decisions on naval technologies. The study was tested on a NATO fleet assigned to a mission in which several tasks had to be accomplished. The mission was designed to represent a challenge requiring new technology investment to be fulfilled. The primary results of this work show that once Vulnerable Scenarios are discovered, it is possible to employ an iterative algorithm that recursively infuse new technologies into the fleet until Robust Technology Strategies that can support the fleet are selected. 

Committee

• Prof. Dimitri Mavris – School of Aerospace Engineering (advisor)
• Prof. Gen. Philip Breedlove – School of International Affairs
• Prof. Daniel Schrage – School of Aerospace Engineering
• Prof. Mariel Borowitz – School of International Affairs
• Dr. Michael Steffens – School of Aerospace Engineering