Defect and Diffusion Forum Vol. 451

Abstract: Carbon Fiber Reinforced Polymers (CFRPs) are essential to the aerospace industry, offering superior strength-to-weight ratios. Currently, the manufacturing of primary structures via standard autoclave curing is a robust, mastered process that successfully minimizes defects, keeping porosity levels below critical thresholds (typically < 1 %). Consequently, porosity is generally not considered as an issue in standard, optimized production lines.However, this stability may be affected by emerging industrial paradigms aimed at increasing production rates and reducing costs. The shift toward accelerated manufacturing – characterized by rapid heating rates, shortened cure cycles and by new manufacturing processes – and the introduction of complex material architectures risk re-introducing significant porosity. In parallel, there is currently no numerical model capable of accurately predicting porosity formation and evolution under these complex conditions. Existing simulation approaches are typically macroscopic and rely on homogenized porous media assumptions, failing to capture the essential micro-scale interactions between bubbles and fibres.To address this gap, this study presents an extended, custom multi-physics Computational Fluid Dynamics (CFD) solver built upon an existing OpenFOAM framework. The goal is to provide the first predictive tool for void evolution within realistic microstructures. The numerical framework couples a two-phase compressible flow model with the complete thermo-chemo-rheological physics of thermoset curing.The solver is applied to 2D Representative Volume Elements (RVEs) of a prepreg ply. Simulations of a standard autoclave cycle demonstrated the solver's ability to capture micro-scale dynamics, showing how voids are compressed and transported during the resin viscosity drop before being frozen at gelation. A parametric study comparing 3-bars and 7-bars pressures confirmed the model's physical ability in predicting void volume reduction.While currently focused on mechanical compression, the tool is designed to support the development of future manufacturing cycles. Future work will incorporate moisture diffusion physics and includes experimental validation via X-ray micro-tomography and in-situ synchrotron monitoring.

Abstract: Conventional hard-bait lure prototyping relies on manual shaping, full-body additive manufacturing or early-stage injection moulding, each associated with limitations in geometric repeatability, development time or tooling cost. This paper evaluates a hybrid approach combining thermoformed PETG outer shells with additively manufactured internal frames to produce batches of geometrically consistent lure bodies with tuneable internal mass layouts. Across several educational development projects, the process enabled fast replication of outer form, systematic variation of ballast and harness configuration, and prototype assembly suitable for qualitative hydrodynamic observation. Compared with full additive manufacturing or manual crafting, the method reduced fabrication effort for multi-variant batches and delivered mould-like surface quality. Joining reliability of shell halves emerged as the dominant limitation, with elastic polyurethane adhesives outperforming brittle cyanoacrylate and poorly controllable low-energy fusion. The results position thermoforming as a methodologically valuable prototyping tool where external geometry is stable but internal behaviour requires iterative adjustment. Future work should address seam design, cage-shell tolerances and sealing repeatability to support quantitative hydrodynamic testing and assess whether the process has potential beyond prototyping applications.

Abstract: The demand for lightweight, multifunctional, and durable hybrid structures is rapidly increasing in aerospace, biomedical, and advanced engineering sectors. Ultrasonic welding (USW) offers a promising route to assemble thermoplastic polymers with dissimilar materials such as stainless steel, aluminium, and ceramics, without adhesives or additional fasteners. This study investigates the ultrasonic joining of high-performance thermoplastics, including carbon fibre-reinforced polyetheretherketone (PEEK), and polyetherimide (PEI) as energy director (ED), with aluminium alloys. Improvement of manufacturing efficiency and weld attributes such as welded area, strength, and failure mechanisms are essential for industrial adoption. In this work, particular attention was given to the effect of metal surface preparation and ED film on weld quality. Weld attributes were analysed in terms of joint area continuity, interfacial morphology, tensile shear strength, and observed failure modes. Whereas not all parameter sets led to successful joining, the findings provide insight into the role of surface finish and ED in determining weldability. These results contribute to the ongoing development of reliable welding for hybrid joining between thermoplastics and metals, highlighting opportunities for thermal process innovation beyond conventional approaches.

Abstract: Thermoplastic composites offer new opportunities for multifunctional lightweight structures through their ability to be joined by fusion welding. However, the welding of dissimilar thermoplastic composites remains challenging due to asymmetric melting behavior and heterogeneous reinforcement architectures, all of which influence interfacial quality and mechanical performance. Within the CONNECT project, this study focuses on the adhesion development between a short carbon fiber reinforced PEEK and a continuous carbon fiber reinforced LM-PAEK laminate. Welding was performed using the TACOMA platform, which allows precisely controlled and asymmetric conductive heating cycles. The influence of welding temperature and contact time on interface formation was examined through Double Cantilever Beam (DCB) tests under Mode I loading, complemented by surface topography and scanning electron microscopy. Results show that welding at 350 °C significantly enhances interfacial fracture toughness compared to 345 °C, reflecting increased chain mobility of the PEEK matrix while the LM-PAEK phase is already molten. However, prolonged contact times lead to reorientation of short fibers parallel to the interface within the molten PEEK suppressing fiber bridging mechanisms at the interface and reducing the resistance to crack initiation, resulting in lower measured GIC values. These findings provide new mechanistic insight into the welding of dissimilar PAEK-based composites and identify a narrow processing window in which asymmetric melting and reinforcement morphology jointly govern interfacial performance. The interfacial fracture toughness was evaluated using a mode I initiation energy approach, selected due to unstable crack propagation in this bi-material configuration.

Abstract: Injection molding tools are characterized by high costs, due to the use of expensive materials such as aluminum or tool steel, and the lengthy production process involving machining. This greatly limits the economic viability of using metal molds for producing small series, and even more so for rapid prototyping. Additive manufacturing processes, such as masked stereolithography (mSLA), enable the production of molds from polymers providing short production time and good accuracy. However, injection molds manufactured using mSLA using conventional resins suffer from long cooling times and lower strength. This contribution presents a new approach that significantly overcomes these disadvantages by developing and characterizing a novel composite material. To this end, aluminum oxide ceramic particles will be incorporated into a photopolymer resin. Various additives will also be employed to optimize the processability and printability of the newly developed material. This should enhance the thermal and mechanical properties of additively manufactured molds. A series of simple test specimens were produced using mSLA. Sedimentation and printability were analyzed by varying the aluminum oxide mixing ratio. The effect of various additives was also investigated. The composite materials were tested for processability, heat flow and mechanical properties. Scanning electron microscopy (SEM) was used to evaluate the particle size, quantity, distribution and homogeneity of the composite material. To demonstrate the application of the new material in additive tooling, a typical set of tool inserts for injection molding was manufactured.

Abstract: Wood-filled PLA filaments enable 3D pyrography in material-extrusion (MEX) printing, in which tonal gradients and surface shading are generated in situ by controlling the thermal history during deposition, thereby avoiding post-processing or multi-material strategies. This enables the direct embedding of motifs and graded shading for customized product design, while also allowing appearance stabilization for repeatable manufacturing of wood-filled PLA parts. In this work, PLA/olive-wood (OW) composite filaments containing 0-20 wt.% OW (particle size < 180 µm) were manufactured and printed into 20 mm discs using MEX. The extrusion (nozzle) temperature was varied from 180 to 280 °C, and the printing speed was set to 20 and 200 mm/s to modulate thermal exposure. Surface color was quantified as L^*, a^*, b^* from visible absorbance measurements (400-700 nm) converted into CIELAB coordinates. Percentual differences were assessed using the CIEDE2000 metric ΔE₀₀. The results demonstrated that increasing nozzle temperature progressively reduced lightness L^*, and under severe conditions, a marked loss of chroma (a^* and b^*), particularly for higher OW contents. Low-speed printing (20 mm/s) amplified the pyrographic effect, reaching strong perceptual contrasts (maximum ΔE₀₀ ≈ 9 at 280 °C for 20 wt.% OW), whereas high-speed printing (200 mm/s) mitigated extreme darkening and maintained more moderate, controlled color differences (typically ΔE₀₀ < 3). Accordingly, ΔE00< 3 can be used as a practical “color-stable” target for uniform-looking parts, whereas ΔE00= 3-9 provides clearly distinguishable shades for pyrographic marking/shading. These findings defined practical process windows to either maximize tonal contrast for 3D pyrography or stabilize the appearance for consistent manufacturing of PLA/OW parts.

Abstract: Poly (ethylene 2,5-furandicarboxylate) (PEF) is a bio-based polyester that is the subject of growing interest as a potential alternative to Poly (ethylene terephthalate) (PET) for sustainable packaging. Its excellent gas-barrier properties and reduced carbon footprint make it a promising candidate, but its use at industrial scale requires a solid understanding of how temperature and thermal history affect its mechanical and viscoelastic behavior. In this study, Differential Scanning Calorimetry (DSC), Dynamic Mechanical Thermal Analysis (DMA), and optical microscopy were used to characterize the thermal transitions and crystallization behavior of PEF, compared with PET and recycled PET (rPET). DSC results show that thermal crystallization of PEF proceeds very slowly, a result confirmed by in-situ microscopy. DMA measurements provide complementary information on the evolution of both storage and loss moduli with temperature, highlighting its dependence on crystallinity and thermal history. Together, these thermal and mechanical analyses clarify how PEF’s crystallization behavior affects its thermo-mechanical response. From a processing perspective, the very slow thermal crystallization of PEF is advantageous for stretch blow molding (SBM) process of bottles, as the polymer remains essentially amorphous during heating and crystallizes predominantly under deformation during the fast forming stage.

Abstract: Epoxy-based composites used in the aerospace industry are highly sensitive to moisture absorption, which can lead to porosity formation during the curing process and compromise structural integrity. Therefore, accurate prediction of temperature fields, degree of cure, and moisture concentration is essential for process optimization and defect mitigation. However, classical numerical approaches for solving the coupled governing equations are computationally expensive, limiting their applicability in real-time analyses and optimization strategies. In this work, Physics-Informed Neural Networks (PINNs) are investigated for predicting the transient thermal behavior, cure kinetics, and moisture concentration in an epoxy composite laminate during autoclave curing. Two PINNs are developed: the first solves the coupled transient heat transfer and cure kinetics equations in a compositetooling system, while the second predicts the moisture concentration field in the laminate using the temperature information provided by the first network. Different network architectures are evaluated, and their performance is compared with numerical solutions obtained via the Finite Volume and Finite Element Methods. The results demonstrate that PINNs accurately reproduce temperature profiles, degree of cure, and moisture concentration, achieving high coefficients of determination, while also providing significant computational efficiency advantages during the prediction stage. These findings highlight the potential of PINNs as a robust and efficient tool for modeling complex coupled phenomena in composite manufacturing processes.

Abstract: This work presents a hybrid formulation combining the Method of Fundamental Solutions (MFS) and the Method of Particular Solutions (MPS) coupled with an implicit Finite Difference Method (FDM) to simulate the transient heat conduction in a two-layer domain composed of a steel tool and an epoxy resin. The proposed approach incorporates a non-homogeneous source term in the governing equation, allowing the analysis of the curing heat release within the resin layer while maintaining a meshless boundary-based structure. Sequential numerical tests were performed to empirically assess the influence of key hyper-parameters number and position of source points, distance parameters, and the Tikhonov regularization factor on the stability and accuracy of the method. The MFS-MPS/FDM model showed excellent agreement with the finite element results reported by Dei Sommi et al., achieving low RMSE and MAE values relative to the thermal scale of the process. These results confirm the robustness and predictive capability of the MFS in capturing transient thermal evolution even in the presence of a source term, although its performance remains sensitive to the proper calibration of numerical hyper-parameters.