In-house techniques and expertise
The group is a pioneer in DSO, utilizing the OPTIONS and OPTIMAT software suites. Originally developed by Professor Andy Keane, these tools allow for the rapid comparison of evolutionary and classical search methods. Professor David Toal extends this expertise through multi-fidelity Kriging and machine learning techniques (such as AeroINR and SDF-GAN) to accelerate the design of aerodynamic geometries and engine components.
For aircraft conceptual design, the group utilizes ADRpy (Aircraft Design Recipes in Python), an open-source library developed by Professor András Sóbester. This tool facilitates rapid sizing and performance analysis, enabling geometry-centric optimization and the digitalization of complex aerospace design processes.
Professor Ali Elham focuses on next-generation sustainable aircraft through advanced multidisciplinary design optimization (MDO). His research utilizes unique in-house codes to bridge the gap between aerodynamics and structural performance. FEMWET, a coupled-adjoint nonlinear aero-structural optimization code for high-fidelity wing design. AeroTop, a specialized topology optimization code for internal and external (thermo)fluid problems, including cold plate management for electric vehicles. TopSteer, an adjoint optimisation code for tow-steered composite structures, developed in collaboration with the University of South Carolina.
Dr. Sergio Araujo-Estrada leads research into the dynamics and control of autonomous vehicles, particularly VTOL and rotorcraft platforms. He utilizes custom flight dynamics simulation frameworks integrated with adaptive machine learning controllers to improve robustness against environmental disturbances. His experimental specialization includes multi-DOF free-motion testing platforms with distributed sensing for high-fidelity aerodynamic state estimation, developed in partnership with Luffy AI.
Dr Haris Moazam Sheikh specializes in data-efficient optimization for high-cost engineering challenges. He leads the development of Design-by-Morphing, a data-driven technique that enables precise local and global shape control using minimal design variables. He also pioneered MixMOBO, a Bayesian optimization framework designed for complex, mixed-variable, multi-objective black-box problems. His work delivers significant performance gains in metamaterials and fluid mechanics while drastically reducing the need for costly data evaluations.
Led by Professor James Scanlan and Dr Bob Entwistle, the group employs the DECODE (Decision Environment for Complex Designs) environment. This platform streamlines the design and manufacture of low-cost civilian UAVs. Specialized in-house capabilities also include UAV Ground Risk planning and health monitoring systems to ensure the safety and reliability of autonomous flight operations.
Dr Kamal Djidjeli leads research into Meshless/Particle (MPS) Method codes. These techniques are particularly effective for modeling Fluid–Structure Interaction (FSI) and bioinspired designs, such as reverse spoilers and flapping foils, which are critical for both aerospace efficiency and renewable energy harvesting.
Dr Jie Yuan manages a suite of cutting-edge simulation tools focused on stochastic and nonlinear dynamic analysis. These techniques are applied to large-scale engineering systems to quantify uncertainty and ensure robust structural mechanics under complex loading conditions.
Professor Gennaro Scarselli specializes in Finite Element Method (FEM) and experimental mechanics for lightweight aerospace structures. The group’s in-house expertise includes novel approaches to Structural Health Monitoring (SHM) and fracture mechanics, ensuring the integrity of advanced composite materials.