AEroelastic Design and structural dynamics Lab
The aeroelastic Design and Structural Dynamics Lab (ADSL) was established in 2025 to research multidisciplinary fields regarding aircraft, rotorcraft, wind turbines, and space structures. Our group has 4 significant research topics: (1) Aeroelasticity, (2) Load and Control, (3) System design optimisation, and (4) System safety in cold climates.
(1) Aeroelasticity
Aeroelasticity is the interaction between the inertial, elastic, and aerodynamic forces when an elastic body is exposed to a fluid flow. We are mainly focusing on wind turbine and rotorcraft aeroelasticity.
(1-1) Aeroelastic analysis numerical tool development
We are developing an aeroelastic analysis tool. For the structural model, we use a modal approach and a co-rotational beam model. For the aerodynamic model, unsteady Blade Element Momentum (BEM) is applied. It is under development.
(1-2) Wind turbine dynamic and load investigation
We are investigating various wind turbine dynamic problems, such as blade edgewise vibrations, two-bladed wind turbine dynamics, floating wind turbine dynamics, structural coupling effects, etc. We are also developing innovative rotor concepts to mitigate the loads and LCoE.
(1-3) Fixed wing and rotorcraft dynamic and load investigation
We are investigating various dynamic problems for fixed-wing aircraft and rotorcraft, such as flutter, limited cycle oscillation, whirl flutter, etc. We are also developing innovative wing and rotor concepts to enhance aircraft performance.
(1-4) Stochastic aeroelasticity
In general, uncertainty is always present in aeroelastic systems in the form of aleatory uncertainty (inherent uncertainty) and epistemic uncertainty (which comes from a lack of knowledge and data). We are developing methods and tools to consider various uncertainties to simulate dynamics and design wind turbine and rotorcraft systems.
(2) Load control
All mechanical systems are exposed to various external loads, resulting in structural failures. We are developing various active and passive control methods to reduce the loads.
(2-1) Active control
It requires sensors and servos to control the system to enhance the system's responses, resulting in load reduction and/or performance improvement. Examples could be a trailing edge flap.
(2-2) Passive control
Passive control doesn't require sensors and servos to control the system. It works based on its own mechanical and/or material design. Examples are a passive pitch control system, swept blades, and composite material couplings.
(2-3) AI-based load control
Controller inputs are the main key parameters based on the sensors' measured inputs to control the systems. For example, the controller gains for the classical PID controller should be tuned depending on the considered system. In order to tune the controller gains, a linear model is required. However, we can use AI methods to compute the gains automatically. Moreover, we are working on developing more advanced controllers driven by AI techniques.
(3) System design optimisation
Rotating machinery design, such as rotorcrafts and wind turbines, requires multidisciplinary objectives such as aerodynamics, structure, materials, control, loads, hydrodynamics, etc. Therefore, system design optimization is required to design/modify rotating machinery components. In this research topic, we are focusing on developing a multidisciplinary design optimization framework.
(3-1) Multidisciplinary Design Analysis and Optimisation (MDAO)
We are currently developing a multidisciplinary design optimisation framework based on the OpenMDAO platform developed by NASA (https://software.nasa.gov/software/LEW-18550-1).
(3-2) Innovative wind turbine blade design
We are developing various innovative blade concepts to reduce fatigue and ultimate loads, such as structurally coupled blades, partial pitch segmented blades, and a passive pitch system.
(4) System safety in cold climates
(4-1) Ice shape and performance evaluation simulation for rotating wind turbines
We are developing the state-of-the-art numerical simulation tool WISE (Wind turbine Icing Simulation code with performance Evaluation). OpenFOAM is the main platform of WISE. In the main platform, the aerodynamic module, droplet field module, thermodynamic module, and ice surface growth module are implemented. The aerodynamic and droplet field modules predict both air and droplet fields in one-way coupling. WISE predicts various ice shapes and performances under cold environmental conditions. Currently, WISE is coupling with a structural module for the Fluid-Structure Interaction (FSI) analysis.
(4-2) Icing detection system
Various ice detection methods are being developed, and an AI-based monitoring system is being applied to detect the ice shape, amount, and position. Moreover, an innovative temperature sensor for ice detection has been developed. We are developing a general system safety monitoring system including sensors, detection methods, uncertainties.