CFD Modelling and Optimization Procedure of an Adhesive System for a Modular Climbing Robot

Area of Science:

• Robotics
• Fluid Dynamics
• Mechanical Engineering

Background:

• Adhesion systems are critical for robots performing infrastructure inspection, particularly on vertical surfaces.
• Optimizing the vacuum-to-power consumption ratio is essential for battery-powered robots.

Purpose of the Study:

• To model and optimize a robot adhesion system for enhanced vacuum generation and reduced power consumption.
• To identify the optimal configuration balancing vacuum performance and energy efficiency.

Main Methods:

• Developed analytical and numerical models for predicting system behavior.
• Validated models using test rig measurements and calibrated inlet height for leakage flow simulation.
• Employed computational fluid dynamics (CFD) for optimization and variation of geometric parameters.

Main Results:

• The developed model accurately predicted system behavior with a 15% error for vacuum and 25% for motor power.
• Identified optimal geometric configurations and impeller blade numbers for improved vacuum/power ratio.
• Successfully optimized parameters for the ROMERIN climbing robot's adhesion system.

Conclusions:

• CFD modeling provides a reliable method for predicting and optimizing robot adhesion system performance.
• The optimized system design significantly improves the vacuum-to-power consumption ratio.
• This research contributes to the development of efficient climbing robots for infrastructure inspection.