This report presents a comprehensive analysis of repurposing recycled wind turbine blades into functional structures, specifically focusing on the creation of a Strandbeest-inspired kinetic structure. Conducted by Group 17 of Delft University of Technology for the Design Synthesis Exercise, the project addresses the growing challenge of wind turbine blade waste, projected to reach 570 million tonnes by 2030. The report identifies the limitations of current recycling methods and explores the potential of repurposing as a sustainable alternative.

The market analysis highlights the intersection of sustainability, functional beach structures, and wind turbine blade recycling, proposing tangible projects like Theo Jansen’s Strandbeest to raise public awareness. Through a detailed trade-off analysis, the team evaluated multiple design concepts, ultimately selecting a hybrid design combining the Strandbeest and Windcar for its superior performance in harsh conditions and material utilization.

Material analysis focused on selecting sustainable alternatives for wind turbine blades, identifying flax-reinforced thermoplastics as a preferable choice due to their recyclability and mechanical properties. Among several natural fibre options, flax was chosen for its consistent mechanical properties, making it the preferred choice for the composite. The chosen composite material balances fibre and thermoplastic matrix influences, enhancing end-of-life performance. Manufacturing techniques and material recovery processes are outlined, emphasizing the potential for producing beams, flat panels, and aerofoil from recycled parts.

The wind turbine design prioritizes vertical axis wind turbines for their sustainability benefits and compatibility with the structure's needs. The design process considered rotor configurations, aerofoil selection, and aspect ratio optimization, ensuring reliable performance under varied wind conditions. The H-rotor configuration was chosen for its manufacturability and space efficiency, and the aerofoil pitch was optimized to account for wind shear effects, ensuring consistent performance.

Kinematic analyses addressed the movement of the structure, incorporating modified Jansen linkages and differential steering for improved navigation. The linkage was designed to improve stability and step height, with the crankshaft and fixed points optimized for a walking robot. Autonomous navigation and obstacle detection systems were integrated using LiDAR sensors and GPS, ensuring the structure can navigate the Dutch coast independently.

Structural analysis was a critical component of the project, divided into body analysis, leg analysis, and evaluation of failure modes. The body analysis involved stability assessments and stress evaluations to determine the optimal width and configuration to prevent tipping and withstand wind turbine forces. The design included springs to dampen vibrations and reduce bending stresses, ensuring the structure's integrity. Leg analysis focused on selecting cross-sections that could handle the stresses without exceeding material limits. This involved a detailed stress analysis and selection of joints to ensure durability.

Power management strategies combined wind turbine and solar panel outputs to meet the system's energy requirements. The final power budget ensured sufficient energy for motion, control, navigation, weather data collection, and other subsystems, balancing the contributions from wind and solar sources.

In conclusion, this report demonstrates a viable method for repurposing wind turbine blades into functional, sustainable structures. By leveraging innovative design, material science, and comprehensive structural analysis, the project addresses significant environmental challenges and showcases the potential for creative reuse of composite materials.

Airspeed information plays a crucial role in the takeoff, flight, and landing processes in animal flyers and aerial vehicles. Among the aerial vehicles, Flapping Wing Micro Air Vehicles (FWMAVs) represent the novel engineering approach of learning and mimicking animal flyers in the past two decades. A few prototypes of various sizes and functionalities of FWMAVs have been developed by MAVLab in the TU Delft Aerospace department since 2005. For these small and lightweight platforms, stable control under disturbances remains a challenge, and could further benefit from integrating effective airflow sensing into control system design.

Current commercial products are either not suitable due to size, weight, and power (SWaP) restrictions of the drone platform, or have very limited low-speed sensitivity. Therefore, to facilitate this, this thesis aims to develop a MEMS-based capacitive airflow sensor for a miniaturized and low-power implementation. Inspired by the filiform hair structure of arthropods, the sensor design comprises two key parts: the hair structure, whose displacement is governed by the drag force induced by the incident airflow, and the sensing base, located at the hair structure's base, which translates the structural displacement into a change in capacitance. The sensor exhibits the capability to sense airflow in one dimension and can be further adapted for omnidirectional sensing.

This thesis predominately focuses on the design and reliable fabrication of the sensing base. It is comprised of a suspended membrane supported by corner beams, supplemented by a pivoting dimple and anti-stitching dimples to facilitate robust hair movement and ensure optimal sensor functionality. The sensing base is fabricated at the TU Delft EKL cleanroom facility, equipped with sophisticated machinery that enables fabrication at micro and nano scales. Furthermore, the membrane suspension is achieved through the implementation of Vapor HF etching of a sacrificial layer beneath the membrane.

In conclusion, the devised sensors aspire to optimize flight control for FWMAVs within the constraints of SWaP, by drawing profound inspiration from the intricate workings of nature.

Flapping wing micro aerial vehicles (FWMAVs) are known for their flight agility and maneuverability. However, their in-gust flight performance and stability is still inferior to their biological counterparts. To this end, a simplified in-gust dynamic model, which could capture the main gust effects on FWMAVs, has been identified with real in-gust flights' data of a FWMAV, the Flapper Drone. Based on this model, an adaptive position and velocity controller was proposed with gain scheduling and implemented for in-gust flights under gust speeds up to 2.4 m/s. With this airflow-sensing based adaptive controller, the in-gust hovering stability of the Flapper Drone has been improved when the gust's intensity and frequency changes, comparing with the original fixed-gain cascaded PID controller case.