Introduction HAMZA LATIF MEHR Mechanical Engineer Education: MS Mechanical Engineering Thesis ongoing Research Assistant at DPL

B.E Mechanical Engineering NUST 2 01 School and High School 03 Thesis: Optimization of HVAC unit through Better Air flow control mechanism 02 04 Past Industrial Experience 1. Textile and HVAC industries- Internships 2. Vehicle Design Engineer- Ahmed Medix 3. Project Management & Engineering- GSK Current Research Experience Industrial R&D Design, simulation, experimentation and condition monitoring 05 MS in Mechanical Engineering NUST Introduction Graduated with Distinction 4th Semester- Thesis Ongoing (3.88 CGPA) 06 Specialization

Thesis Optimization by Design by Morphing of Vertical Axis Wind Turbines with application of Bayesian Optimization Objectives: • Develop a non intuitive Design Approach • Use a morphing algorithm to dynamically generate blade shapes (An efficient Amalgam of Drag and Lift base turbine.) • Apply Bayesian Optimization to refine turbine design. • Enhance Aerodynamic Efficiency • Optimize blade shape, speed ratio, distance between blades and angle of attack. • Calculate turbine efficiency (Cp) through CFD (CFD will be validated first). • Implement a “Reinforced” Bayesian Optimization Process • Generate and evaluate turbine designs using Bayesian Optimization & CFD. • Continuously refine designs based on performance metrics (Coefficient of Power).

Optimization of HVAC Unit (Digital Twin) • 2D Simulation to find the optimum time after the desired area has been cooled • Time-dependent UDF to control the velocity of the HVAC blower • Data fed to Arduino controller to communicate with HVAC blower according to the hotspot region temperature • Energy consumption reduction Validation

Optimization of machine fault detection using a machine learning algorithm with Python • Multivariable dependence on machine fault • Random Forest Classifier used for tabular data • Data manipulation for features and target • Hyperparameter Optimization using Random Search CV • Exporting the model

•Higher efficiency wind turbine designs using CFD and optimization algorithms. •Smart energy systems integrating AI-based optimization for performance enhancement. •Decentralized renewable energy deployment, supporting the shift to a carbon-neutral society Research Interest and Future Goals ECS Major Challenge •MEMS in Finland •Multiphysics modelling, MEMS in Norway •Cyberphysical systems related to wind turbines SSI Interests Source: EpoSS