Aerospace propulsion

The research group activities embrace multiple aspects related to both aeronautical and space propulsion. The main research topics to which the group's skills are devoted are the aerodynamic design of turbomachinery components, the aerothermodynamics of aerospace propulsion, the numerical simulation of aeronautical engines and combustion, and the analysis of space trajectories.

dario.pastrone@polito.it

 

  • Aerospace propulsion systems: performance analysis, optimization and experimental test

 

  • Multidisciplinary design and optimization of jet engine systems and their components

The research activity is devoted to the development of multidisciplinary optimization techniques for the design of aerospace propulsion systems and their components. Several alternative approaches are investigated, from adjoint based methods to evolutionary algorithms, including inverse design techniques. Multifidelity strategies are considered in order to exploit data from different sources and new techniques for reduced order modeling are investigated.

 

  • Development of numerical methods for thermal and aero-elastic simulation of internal and external flows and their control, and for combustion / combustion instabilities

The research activity is focused on the development of numerical methods and simulation tools for the prediction of the flow field in aerospace propulsion systems. The goal is to improve the present modeling capability for turbulent, compressible and reacting flows. Several applications in both aviation and space are under investigation, with particular attention to flow control, combustion and combustion instabilities. The research effort is devoted to the improvement of different simulation strategies, from scale-resolving simulations like Large Eddy Simulations to classical Reynolds-averaged Navier Stokes (RANS) equations. Both body-fitted and immersed boundary techniques are investigated in order to improve the simulation capability in the presence of complex geometries or deforming bodies.

 

While the interest in scale-resolving simulations is constantly growing, classical approaches based on Reynolds-averaged Navier Stokes (RANS) equations will remain a fundamental tool in the design of aerospace propulsion systems for several decades. Closure models for RANS equations are usually based on analytical and empirical assumptions: data-driven methods allow to systematically exploit high-fidelity data from experiments or scale resolving simulations for improving existing RANS model. The research activity is focused on the application of machine learning techniques for improving turbulence and transition models in aerospace propulsion systems with particular attention to the imposition of physical constraints to the data-driven models.

 

  • Multidisciplinary optimization of rocket propulsion systems

The research activity is focused on the development of multidisciplinary optimization methodologies for the study of chemical rockets, delving into aspects related to ascent trajectory, propellant technology, and more generally, the various elements that constitute the propulsion system. In particular, the potential of direct, indirect, and evolutionary optimization methods is being investigated, whether used individually or synergistically. Additionally, machine learning techniques are integrated into the optimization process to study the combustion and the environmental impact of rocket-based launch systems.

 

  • Development, analysis and testing of innovative propellants

The research activity focuses on the development, analysis, and testing of innovative propellants for solid rocket motors, exploiting innovative production techniques, particularly UV-curing and 3D-printing. Specifically, the experimental work concerns the analysis and the characterization of non-reactive mixtures and the fine-tuning of the various elements of the production process.

 

  • Space trajectory optimization

The subject of the research line is the application of optimization methods to space trajectories. The specific purpose of the research is the improvement of optimization methods and the combined use of traditional (direct and indirect methods, evolutionary algorithms) and innovative techniques (artificial intelligence and machine learning) for the optimization of geocentric and interplanetary trajectories and rendezvous missions.

 

ERC sectors

 

  • PE8_1 Ingegneria aerospaziale

Keywords

  • Space trajectory optimization
  • Trajectory/propulsion system multidisciplinary optimization
  • CFD
  • Multidisciplinary optimization
  • Turbulence modeling
  • Data-driven methods
  • Rocket Propulsion