This thesis examines the thermal distribution and material behavior in in-space additive manufacturing (ISAM) using metal directed energy deposition (DED), addressing challenges of the orbital environment, including microgravity and vacuum. Experimental studies with a Scandium-modified Al-5183 alloy, conducted via Wire Are Additive Manufacturing, validated heat transfer coefficients and simulated ISAM thermal profiles. A finite element model, developed in Ansys Mechanical and calibrated with experimental data, accurately predicted overall thermal histories despite underestimating melt pool temperatures. Applied to orbital conditions, the model showed environmental healing effects were minimal for small components but significant for larger structures, supporting ISAM’s potential for space infrastructure. Material analysis revealed enhanced mechanical properties due to Scandium addition, with refined grains and Al3Sc precipitates. Integrating experiments, simulations, and characterization, this work advances ISAM thermal modeling, offering insights for future refinements in simulation accuracy and orbital testing.

Fused Deposition Modelling (FDM) is one of the most popular 3D printing technologies because of its affordability and accessibility. FDM, however, often suffers from printing errors that result in wasted time, materials and energy. To address these challenges, this thesis introduces a novel fault detection system for FDM printers. This system is designed to identify a broad range of errors without interrupting the printing process. To achieve a real-time detection system, an innovative multi-camera setup is designed, integrating two side cameras and one nozzle camera. Our hypothesis is that a system including three cameras can provide a more comprehensive view and can ensure more error types to be detected. Error detection is achieved using Convolutional Neural Networks (CNNs). This is a type of machine learning that excels at image recognition and pattern detection, making it well-suited for identifying printing errors in real-time models. Two CNN models are developed to classify images into common 3D printing errors: one model for the nozzle and another for the side cameras. The models were trained and validated on diverse datasets containing various shapes, infills, and augmented data. The nozzle camera model achieved a high validation accuracy of 97.68% with a low loss of 0.07464. The side camera model achieved comparable performance with a validation accuracy of 97.61% and validation loss of 0.1196. These two well performing models were for the first time ever integrated into a unified fault detection system based on a logic-driven priority framework. From this research, we learned that integrating multiple viewpoints into a logic-driven priority framework significantly improved the robustness of error classification, as many more error types could be detected in-situ and real-time. As a result, the integrated system successfully detected 12 common printing errors. In summary, this work shows the feasibility of developing a robust multi-input fault detection system to improve 3D printing. It paves the way for further research and implementation for complex integrated error detection and correction mechanisms.

Airbus Cabin Vision 2035 aims to transform the future experience of air travel with a focus on sustainability through its three pillars: Transparency, Decarbonization, and Circularity (Airbus, Airspace Cabin Vision 2035+). As part of this initiative, the current thesis explores the potential of bio-based materials to replace conventional fossil-based thermoplastics in aircraft seating trims. By investigating whether nature can provide lighter and more environmentally friendly alternatives, this study seeks to reduce the aviation industry's carbon footprint (during the usage phase of aircraft) while enhancing the circularity of the materials.

This research is structured in a three-phase iterative framework. The initial phase involves problem analysis and the development of design specifications. The next phase, material exploration, identifies a list of potential bio-based materials suitable for design exploration, followed by a literature review to understand their flammability and moisture resistance properties, which are critical for compliance with the rigorous standards of aircraft applications.

From the material exploration, a family of hardwood, natural fibers, and mycelium emerged as potential materials for further design exploration. Lightweighting method was employed to optimize their geometry and meet the required mechanical strength established in the design specifications (Load bearing strength up to 100kgs). This method led to the development of a more practical option: the Designing of Composites. Static load-bearing capacity calculations were conducted to assess the feasibility of the composite design with the variations in facesheet materials. The pretreated Baxis Sinica wood panel with a mycelium core emerged as a feasible solution, primarily due to its weight-to-strength ratio, ability to meet the functional requirements of aircraft, and its circularity.

In the pursuit of material optimization, studies were undertaken in exploring bio-based coatings, to enhance the flammability and moisture resistance properties ensuring its suitability for the stringent requirements of aircraft applications. With established research on enhancing the flammability and water resistance of wood-based composites, the focus was to improving the properties of mycelium. Initial post-treatment methods using inorganic flame retardants like sodium silicate effectively demonstrated flame-extinguishing properties; however, further research is required to further enhance the material's water resistance. Additionally, there is promising potential for utilizing bio-based coatings to simultaneously improve both the flame retardancy and moisture resistance of mycelium. As it is well-established that bio-derived materials can degrade over time, it is crucial to develop strategies and treatments to ensure this does not compromise the product's lifespan. Current efforts also focuses on understanding the long-term behavior of these materials and their coatings under extreme conditions. However, as these materials have not yet reached full maturity, further optimization and enhancement remain within the scope of future research.

Positioned within the framework of Circular R-strategies, this study proposes an ambitious design, utilizing a wood and mycelium to develop a composite, with textile serving as the adhesive layer. The proposed design not only eliminates the need for fossil-based materials but also reduces weight by up to 50% compared to conventional thermoplastics in seat trims. This weight reduction is significant, as even a single kilogram less can lead to a decrease of 5,000 to 15,000 kg CO2 emissions over the aircraft's lifetime.

This study explores the potential of biomimetic vibrissal sensors for tactile navigation in aerial robotics. Inspired by the sophisticated sensory system of rodents, we developed a non-intrusive, whisker-based tactile sensor system integrated into a drone platform. The system enables real-time detection and navigation through complex environments by emulating the tactile perception capabilities of natural whiskers. Our approach includes a novel platform design for easy sensor integration, a preprocessing solution to mitigate signal distortion as well as a simple static calibration set-up to estimate normal contact distances. The effectiveness of the system was validated through contour following tasks, where the whisker sensors provided feedback for precise navigation along surfaces with varying orientations. Results demonstrate that our system can estimate normal distances and wall orientations with sufficient accuracy, despite challenges such as lateral slip. This research highlights the potential of whisker-inspired sensors in enhancing the tactile sensing capabilities of aerial robots, offering significant advantages over traditional tactile sensors in terms of weight, power consumption, and operational flexibility in diverse environmental conditions.

Additive Manufacturing (AM) plays a crucial role in the revolution towards Industry 4.0, by enabling the direct translation of digital 3D models into physical objects while reducing process steps and minimizing human intervention. While conventional AM machines are generally limited to three-axis movement, multi-axis AM equipment extends the manufacturing flexibility by enabling the fabrication of freeform layers, thus creating new opportunities to improve part quality, though at the cost of increased complexity in process planning. Wire Arc Additive Manufacturing (WAAM) is a multi-axis technique for producing large metal components, with potential applications in maritime, aerospace and civil infrastructure. However, this potential is hindered by factors such as deformation during fabrication, which compromises part precision and can lead to process failure. Recently, a computational approach has been developed to reduce distortion by optimizing the fabrication sequence. While promising, the optimized sequence is characterized by large variations in layer thickness, rendering them non-manufacturable. This research proposes numerical methods to evaluate and restrict layer thickness in fabrication sequence optimization, ensuring uniform thickness within each layer and a consistent average thickness across the entire sequence. A 3D computational framework has been developed, integrating latest advancements in sequence optimization. To address the intensive computation in 3D, this framework features a parallel implementation using the PETSc library. This framework enables the numerical assessment of the method’s performance and provides a foundation for future experimental validation.

Incorporating living cells into a non-living matrix is one of the many possible steps that can be undertaken to stop climate change. Especially, photosynthetic organisms have a promising future in material design as they can capture atmospheric carbon dioxide and ’ breathe’ oxygen. This research dives into unravelling the properties of a hydrogel-based living material containing C. reinhardtii.
To facilitate a systematic exploration, this goal was divided into three smaller pieces. Firstly, the study delves into the mechanical characteristics, aiming to identify the most suitable bio-ink crosslink technique and composition. To validate the mechanical properties the living material was subjected to rheology and a bridging test. Concluded can be that crosslinking and algae growth improve the mechanical stability of the material, whereas, gelatin did not. The sagging behaviour of the material looked promising.
Secondly, the photosynthetic activity of this living material was researched. It was found that the rise of O2 levels can not be measured accurately, the non-living matrix can release a high amount of CO2 of over 20.000 ppm and airtightness poses a complex challenge in this field of research.
Lastly, the project incorporates attempts to find effective techniques for studying the livingness of this unique material. In this part of the research, inverted optical microscopy, 3D laser scanning microscopy and chlorophyll extraction were discarded as suitable methods to study the livingness of the algae material. It was proven that leveraging the autofluorescence of the algal chlorophyll confocal laser scanning microscopy gives high-resolution images and the livingness of this living material could be studied with this technique in the near future.
This research significantly contributes to our understanding of this hydrogel-based living material and its many challenging properties. It underscores the importance of innovative materials like these in addressing contemporary environmental challenges, particularly in carbon capture. Moreover, it highlights the complexity of characterizing such materials, paving the way for further exploration and development in this relatively new field.

Frontal polymerization (FP) has emerged as a promising alternative to traditional bulk curing methods in recent years for manufacturing high-performance fibre-reinforced polymer (FRP) composites. The energy utilized in this self-propagating curing strategy is solely derived from the exothermic enthalpy of polymerization, making it potentially more efficient than traditional curing methods, which are extremely energy-intensive and therefore unsustainable. Research in the field of FP has been primarily focused on studying the effectiveness of the FP formulations, particularly the relationship between the monomer types and initiator concentrations on front properties. However, the research on the use of FP for manufacturing FRPs has been limited to flat rectangular plates. Therefore, this research aims to investigate the behaviour of the propagating fronts in composites with varying fibre volume fractions (Vf) within the sample and varying geometries to assess the feasibility of using FP in structures that more closely resemble real-life applications. Several test setups were explored to determine the best method for maintaining the heat balance required to sustain a propagating front. Through these trials, a stainless steel-based closed mould test setup with Teflon sheets was conceptualized and manufactured, consistently allowing for the manufacturing of composite samples with a Vf below 36%. The influence of changing Vfs on the behaviour of the front was studied, and the results were quantified using temperature data captured via thermocouples placed at strategic locations. Through a series of experiments, a critical length was established that allowed the propagation of the front from the low Vf region to the high Vf region. When the length of the low Vf region with respect to the high Vf region was smaller than the critical length, the front was seen to quench at the interface. This phenomenon was attributed to the physical reduction in the volume of the resin, which implied a reduction in the generated heat through polymerization. This led to fronts with lower peak temperatures, which upon reaching the interface would quickly fall below the threshold temperature required to sustain the front due to the higher rate of heat loss resulting from the higher fibre content. This study was followed by the manufacturing of L-shaped composite samples with uniform Vf, which showed the propagation of the front in complex geometry. Finally, the Vf was varied within the L-shaped samples, and the behaviour of the front showed similarities to the rectangular samples with varied Vf, leading to the conclusion of the presence of a critical length irrespective of geometry. These findings effectively contribute to the knowledge base necessary for implementing FP as a curing strategy for FRPs. The results obtained from this study can inform the design of manufacturing processes and setups tailored for the use of FP, potentially leading to more efficient and sustainable manufacturing practices.

Piezoelectric materials have the ability to convert mechanical to electrical energy (direct effect) and vice versa. They are readily used in the aerospace, automobile, telecommunication industry etc. as both sensors and actuators. For this work the focus is on the sensor application, which utilizes the direct piezoelectric effect. With the rapidly growing technological demands, sensors should be flexible enough to adapt to different applications while also having adequate sensing capabilities. Currently, lead- and lead-based piezoelectrics are used in the industry due to their excellent piezoelectric properties. However, due to their toxic nature, research has been ongoing into more lead-free systems which are capable of replicating the performance of these lead-based systems. In this work, we aim to improve the sensing capabilities of lead-free piezoelectric composites. To further improve their performance, reducing the dielectric constant (ε) of the composite is the main strategy of this work. The reduction is achieved by fabricating a porous composite structure. The reduction in permittivity leads to an increase in the piezoelectric voltage constant (g), which defines the sensitivity of the piezoelectric composite.

The main focus of this work is to optimize a polymer and polymer foaming technique to obtain a high level of porosity, while also retaining adequate mechanical properties. The next step is to achieve a high poling efficiency for the composite in order to obtain good piezoelectric properties. For the polymer system, polyvinyl alcohol (PVA) is selected as the matrix due to its excellent film forming ability as well as its relatively high dielectric properties (compared to polymers). The direct foaming technique is used for this work, due to its simplicity and its reproducibility. For the lead-free ceramic system, Barium Titanate (BaTiO3) and Sodium Potassium Niobate doped with Lithium (KNLN3) is selected as they have good piezoelectric properties, and have been used in piezoelectric composites extensively. As a porous piezoelectric composite is used in this work, the contact poling is replaced by the corona poling method to prevent localized dielectric breakdowns and non-uniform poling.

With the direct foaming technique, foams with porosites in the range of 90-95 % are obtained, resulting in a drastic reduction in the permittivity of the composite. Such a high porosity level also results in a much softer composite. The optimization of the corona poling process is done by selecting the adequate poling temperature and the grid voltage, which is found to be 110 °C and 6 kV respectively. The effective piezoelectric charge coefficient is measured using Al plates as electrodes, to prevent the soft composites from compressing locally. The foam composites exhibit remarkably high g33 values exceeding the 1000 mV.m/N mark, almost double the best sensor used in the industry currently (PVDF). This is attributed to the high poling efficiency and the reduced dielectric permittivity of the composite. This opens up the vast number of possibilities for future systems based on porous structures to be used as sensors which can showcase good piezoelectric properties as well as being more flexible/conformable.

Mechanical air entrapment, void compression and void dissolution are the main mechanisms behind void formation in liquid composite molding. Mechanical air entrapment is induced by the highly non-uniform geometry at the meso- and micro-scale and the heterogeneous properties of the reinforcing material. This results in differences in the velocity profile through the porous- and free flow domains, which can lead to air being entrapped in slow-flowing domains, by resin flowing through the faster flowing domains. Depending on the competition between the viscous flow through the free flow domains and the capillary flow through the porous domains, voids occur either in the intra-bundle domain or in the inter-bundle domain, where the competition between the two flow types can be quantified by the capillary number. Once the voids are entrapped, they can change in size due to void compression and -dissolution, all which occur on considerably different timescales. An experimental set-up was developed which uses fast radiation curing to almost instantly cure the resin during injection and thus detach the different stages of void formation from each other. In this research the relationship between the mesoscale structure of a woven fabric and mesoscale void formation was investigated. The mesoscale structure is strongly related to void formation, as viscous flow is related to the inter-bundle domain size in the through-thickness direction of the preform and capillary flow is related to the mesoscale bundle porosity. As the bundle porosity is related to both the bundle permeability, and the capillary pressure, its influences on void formation were considered to be large, and thus bundle porosity became the main research topic. A 2D semi-analytical model based on mechanical air entrapment was constructed which was capable of determining the filling times of the intra- and inter-bundle domains on the mesoscale. A parameter called the competitive number was introduced which was related to these filling times. Once the competitive number was larger than 1, spherical inter-bundle voids should be formed, once it was equal to 1 no voids should be formed and once it was lower than 1 ellipsoidal intra-bundle voids should be formed. This model was validated experimentally. Flow behavior predicted by the model was compared to video footage of the flow front propagation at the surface of the preform at the macro- and mesoscale during multiple injections. Void volumes, types and locations obtained from the model were compared to voids observed in micro-CT scanned samples and were in agreement with each other. The validated model was eventually used to investigate the effects of bundle porosity on void formation. It was found that increased bundle porosity at a constant global preform porosity, leads to increased intra-bundle flow and decreased viscous flow, thus considerably influencing void formation by mechanical air entrapment. In short injection cycles with high macroscopic flow velocities, which can lead to intra-bundle voids, it could be beneficial to switch a fabric with a higher bundle porosity, as that would effectively reduce the intra-bundle void size. For injections with low macroscopic flow velocities, the opposite would apply, thus usage of fabrics with lower bundle porosities could help to reduce the inter-bundle void volumes.

Additive manufacturing of smart polymers is a rapidly growing field. Additive manufacturing presents a versatile, low-waste manufacturing method for functional materials. Self-healing polymers are a type of smart polymers that are able to mend damage, either by the incorporation of an encapsulated healing agent or by intrinsic polymer design. Beside this ability to repair damage, certain types of self-healing polymers have also shown to improve interlayer adhesion of 3D printed parts due to the formation of reversible cross-links. This thesis demonstrated the additive manufacturing of a self-healing polyurethane (CR1) by fused deposition modelling. A protocol was established in order to print with this self-healing polyurethane while minimising material loss. Measurable polymer properties that were relevant to fused deposition modelling were identified and measured in order to establish the processing window of the polymer. CR1 was synthesised, processed into a filament using a commercial filament maker and successfully printed using a modified commercial 3D printer. The elastomeric nature of the polymer combined with its high sensitivity to temperature, resulted in a narrow printing window. Beside the ability to 3D print the polymer into rectangular bars, the self-supportability of the 3D printed CR1 was demonstrated by the printing of a single-wall structure. Printing at 230 °C and 20 mm/s resulted in the most regular sample, with a very low void concentration in its cross-section. The mechanical response of 3D printed CR1 showed good resemblance to that of the bulk. Furthermore, the test showed that the polymer retained its self-healing ability after printing.