Dr Wrik Mallik
- Lecturer in Aerospace Engineering (Autonomous Systems & Connectivity)
email:
Wrik.Mallik@glasgow.ac.uk
pronouns:
He/him/his
Room 406, James Watt North Building, School of Engineering, Glasgow, G12 8LU
Biography
I received my BTech in Civil Engineering from Jadavpur University, India, and my PhD in Aerospace Engineering from Virginia Tech, USA. I was appointed as a postdoctoral research fellow at The University of British Columbia, Vancouver, before joining the University of Glasgow in September 2022.
Research interests
My research involves computational modelling of fluid dynamics, fluid-structure interaction and acoustics, with a vision to develop sustainable concepts for the aeronautics, wind engineering and marine sectors. My research is focused on the following broad areas:
- Fluid-structure interaction/aeroelasticity
- Data-driven modelling and scientific machine learning for physical systems:
- Fluid-structure interaction: development of low-order models of fluid-structure systems showing complex physical phenomena
- Wave propagation and acoustics: development of low-order models for learning the dynamics of acoustic propagation and wave scattering
- Engineering optimisation: shape optimisation, multidisciplinary design and optimisation of complex aerospace systems
- Computational aero-acoustic and underwater acoustics modelling
I have an active research collaboration with the Marine Science Research Group at the University of Glasgow. I also have ongoing research collaborations with the University of Strathclyde and Birmingham in the UK and with the University of British Columbia, Vancouver and the Indian Institute of Technology.
Grants
Active:
-
Data-driven manufacturing of energy-efficient porous-coated wind turbine blades, EPSRC, RIR36E231130-2, £45746.29, July 2024-
Completed:
- Underwater acoustic testing, College of Science & Engineering, ECDP Rewards for Excellence Award 2023-24, £10,000, March 2024-July 2024
- Collaborative international research activity on wind engineering between University of Glasgow and Indian Institute of Technology Delhi, University of Glasgow, International Partnership Development Funding Award 2023-24, £2,000, April 2024-July 2024
Supervision
Information for Prospective PhD applicants
I am looking for enthusiastic PhD students for the following research projects:
-
Aeroelasticity and shape optimisation of flexible next-generation aircraft configurations
Future innovative configurations for commercial aviation and urban air mobility would likely be developed with flexible aircraft configurations like the Truss-braced Wing (TBW) or NASA Helios for maintenance and manoeuvrability. Such configurations will be highly flexible leading to complex fluid-structure interaction. The goal of this research project is to investigate how such flexible structures deform under various flying conditions and if we can control the deformed shape of such structures by adaptive morphing. The project can be separated into two major PhD sub-projects:
- Computational modelling for exploring aeroelastic instability of flexible non-planar wings
- Development of novel shape optimisation and morphing methodology for flexible aircraft structures
Prerequisites: good background in fluid mechanics and structural mechanics is required. Interest or experience in computational fluid dynamics and engineering optimisation are a plus but not essential.
The project title is indicative of the research activities. Please contact me directly to discuss available topics in the area.
- Coupled aerodynamic-aeroacoustics analysis for silent design and operation of urban aerial vehicles
Noise will be a significant factor in the design and operation of urban aerial vehicles. We need accurate far-field acoustic signatures of such aerial vehicles to develop low-noise designs or to devise silent operation strategies for urban aerial vehicles. Thus, we require a coupled aerodynamic-aeroacoustics analysis of aerial vehicles in urban settings, which can analyse the noise propagation and noise backscattering from urban structures for various flying conditions. This project will involve the development and application of a coupled computational fluid dynamics (CFD)-computational aeroacoustics (CAA) analysis tool for performing far-field aeroacoustics analysis due to noise generated from various urban VTOL/drone takeoff and flight conditions.
Prerequisites: A good undergraduate background in computational fluid dynamics is required. Interest or experience in computational fluid dynamics is a plus but not essential.
The project title is indicative of the research activities. Please contact me directly to discuss available topics in the area.
- Data-driven surface porous-coating optimisation for energy-efficient and low-noise wind turbine blades
Wind turbines are one of the most significant contributors to the UK’s zero-carbon energy accounting for up to 19.8% of total energy generation in 2019 and up to 26.8% in 2022. At present construction of onshore windfarms is regulated by noise levels due to wind turbine operation at 350 meters from the wind turbine site, which limits the location of wind turbine sites and hours of the day when wind turbines can be operated. This motivates the development of innovative strategies for wind turbine noise reduction, which would enable significantly greater flexibility on onshore wind turbine usage and possible site locations near residential areas. This project would involve the development of radical wind turbine blade manufacturing concepts with the help of high-fidelity computational modelling, AI/ML-based surrogate models and novel concepts for wind turbine shape and topology optimisation.
Prerequisites: A good undergraduate background in computational fluid dynamics is required. Interest or experience in machine learning and engineering optimisation is a plus but not essential.
The project title is indicative of the research activities. Please contact me directly to discuss available topics in the area.
- Cavanagh, Alexander
Study of Vortex Stability in Swept Wing Configurations - Hernandez Gelado, Pedro
Low-order modelling of unsteady, nonlinear fluid dynamics using “Scientifically-Based” machine learning
Professional activities & recognition
Professional & learned societies
- Senior Member, American Institute of Aeronautics and Astronautics (AIAA)
Additional information
Conference Organisation and Chairs
- The IACM Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology Conference, 2021
- The 22nd IACM Computational Fluids Conference, 2023
- The UK Fluids Conference 2023.