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Stefania Gemma

Researcher, Università La Sapienza

Stefania Gemma graduated with honors in Aeronautical Engineering in 2011 at University of Rome “La Sapienza” (Italy).  On April 2015, she awarded her PhD in Aeronautical and Space Technologies at the department of Mechanical and Aerospace Engineering at University of Rome “La Sapienza”. Her research activity focuses on Multidisciplinary and Multi-Objective Optimization for aerospace applications. In 2014 she spent a research period at NASA Langley Research Center. In this framework, she contributed to the verification of a unconventional aircraft concept (the Over-the-Wing-Nacelle), by carrying out advanced integrated analyses comprised of high-fidelity simulations and developing innovative optimization strategies (MDO-MOO). 
Since January 2012 she has been working as Stress and Design Engineer at Airworks Engineering (an aerospace consulting company), collaborating with multinational companies in the aerospace industry. In 2013 she also worked as consultant for A350 door analysis at Airbus Helicopters in Munich.

Speeches

Multi-Disciplinary and Multi-Objective Optimization for the design of a Over-the-Wing-Nacelle aircraft and a High-Altitude Long-Endurance unmanned vehicle
Academy
Sala Terra, Tue, 17/05/2016 - 14:50 - 15:10

The aerospace engineering typically deals with multidisciplinary complex systems, and narrow margins of the design parameters make necessary the introduction of optimization approaches in order to pick the best designs.

In this work, two integrated computational environments have been implemented using modeFRONTIER for the Multidisciplinary Design Optimization (MDO) of unconventional concepts, a Over-the-Wing-Nacelle (OWN) aicraft proposed by NASA LaRC and a High-Altitude Long-Endurance (HALE) unmanned vehicle. The problems have been solved through an explicit Multi-Objective Optimization (MOO) by applying the Multi Objective Genetic Algorithm (MOGA II) for evaluating the Pareto frontier.

In the first work, a OWN concept has been investigated and the optimization criteria include minimum Empty Weight and minimum Fuel Weight, taking into account of structural, aeroelastic and mission constraints according to Airworthiness Standards. The level of fidelity for the involved disciplines is a relevant issue when iterative analyses are addressed and a compromise between high-fidelity and computational burden should be found. In this work, high-fidelity analyses for the structural and aeroelastic assessment, together with middle-fidelity analyses for the aerodynamic, mission and performance analyses are performed through specific codes (i.e., MSC.Nastran, FLOPS, FEMWING). A complex MultiDisciplinary Analysis (MDA) framework is implemented. Specifically, a Multidisciplinary Feasible architecture (MDF) for the MDA is developed, in order to simulate the interdisciplinary interaction and to provide a self-consistent analysis.

The aim of the second work is to optimize a HALE vehicle powered by solar cells. Three objectives have been optimized, namely, the aerodynamic lift to drag ratio, the structural weight and the solar flux. The computational environment includes, besides MSC.Nastran and FEMWING, SunWing, which is a sun energy flow estimator developed within this activity.

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