Purpose This study aims to introduce and validate a robust experimental methodology for the tensile testing of compliant filaments such as thermoplastic polyurethane (TPU) to generate reliable material data for numerical modeling. Accurate strain measurement was a primary focus, particularly in the low-strain elastic regime (≤ 10%), where minimal elongation requires sensitive measurement techniques. Design/methodology/approach A custom desktop tensile testing setup with high-precision loading was developed to address the challenges of testing highly elastic filaments. Various clamping configurations and strain measurement methods were evaluated to minimize experimental errors. A modified printing strategy was introduced to solidify specimens before contacting the print bed, preserving their circular geometry and enabling easier removal. Tensile tests were conducted on both raw and printed TPU filaments to investigate the influence of the printing process on mechanical behavior. Two different filament diameters were also tested to evaluate potential nozzle diameter effects. Strain measurements obtained from clamp displacement tracking, an extensometer and optical strain measurement (OSM) were systematically compared. The resulting stress–strain data were used to calibrate an Ogden hyper-elastic model with isotropic, volume-preserving and rate-dependent parameters, while the Prony series was incorporated to capture rate effects. Findings Clamp displacement tracking overestimated strain due to slippage effects, while extensometer measurements presented alignment challenges for highly elastic TPU specimens. OSM provided more reliable strain data. The mechanical properties of printed filaments were found to be independent of filament diameter, whereas raw and printed filaments exhibited different tensile behaviors. The calibrated Ogden model accurately represented TPU behavior within the low-strain regime relevant to many engineering applications. Originality/value This study addresses the lack of reliable filament-level mechanical data for highly elastic materials such as TPU, which is essential for numerical modeling and constitutive material calibration. To the best of the authors’ knowledge, no prior study has systematically characterized raw and printed TPU filaments at this level for use in finite element modeling. The proposed experimental framework provides reliable material data for low-strain applications involving controlled elastic deformation, while more complex constitutive models for large deformations are left for future work.
Purpose This study aims to investigate the densification behavior and defect evolution of CuCrZr alloy fabricated by laser powder bed fusion (LPBF), with emphasis on the effects of laser power (LP), scanning speed (SS), hatch distance (HD) and powder bed layer thickness (PBLT) on density, microstructure, defects and mechanical performance. The suitability of volumetric energy density (VED) for predicting densification and defect formation is also evaluated. Design/methodology/approach A statistically validated experimental framework based on a modified Taguchi method was used to optimize the LPBF process parameters. Eighty-one CuCrZr specimens were fabricated under different processing conditions. Density measurements, optical and scanning electron microscopy, defect characterization and mechanical testing were performed to establish process-structure-property relationships and evaluate the effects of post-heat treatment. Findings The optimized parameters of LP = 370 W, SS = 610 mm/s, HD = 0.10 mm and PBLT = 30 µm produced relative density above 99.6% with minimal defects. Lack-of-fusion defects, gas porosity and interlayer cracking were strongly influenced by melting pool behavior and process parameter interactions. Microstructural analysis revealed a transition from fine equiaxed grains to elongated columnar grains along the build direction. Direct aging produced the highest strength, with a yield strength of 435 MPa and ultimate tensile strength of 437 MPa, while solution treatment followed by aging increased elongation up to 13%. Originality/value The results demonstrate that VED alone is insufficient for predicting densification because different parameter combinations with similar VED values produced distinct density levels and defect morphologies. The modified Taguchi framework provides a systematic approach for optimizing LPBF parameters and establishing relationships between processing conditions, defects, microstructure and mechanical performance of CuCrZr alloy.
Purpose This study aims to propose a physics-informed framework to describe densification behavior in Laser Powder Bed Fusion (LPBF). Design/methodology/approach A new dimensionless number, Π, combines absorbed laser energy, track and layer overlap and heat-transfer effects. The framework is evaluated using experimental data from several alloys. Findings The relative-density data follow a common relative density (RD)–Π trend and reveal clear densification regions, including lack of fusion, rapid densification, near-full density and excessive energy input. Machine learning results confirm that Π alone captures the dominant mechanisms governing densification. Originality/value The proposed framework provides a simple, physically meaningful and transferable tool for LPBF process design. It offers an alternative to conventional energy-density measures and purely data-driven models.
Purpose This study aims to establish a systematic isothermal annealing post-treatment to mitigate residual stress and poor interlayer adhesion inherent in fused filament fabrication (FFF) of polyetherketoneketone (PEKK), thereby enhancing the mechanical performance of printed components. The optimized protocol is further extended to gyroid triply periodic minimal surface (TPMS) structures to evaluate its broader applicability. Design/methodology/approach Thermal transitions and stability were characterized via differential scanning calorimetry and thermogravimetric analysis, revealing a glass transition temperature of ∼218 °C and stability up to 542 °C. X-ray diffraction and molecular dynamics simulations confirmed predominantly amorphous behavior. Annealing was conducted at 180, 200, 220, 240 and 260 °C for 6 h under constrained conditions followed by furnace cooling, with flexural testing used for the optimization. Failure mechanisms were examined via digital microscopy and scanning electron microscopy. The optimized protocol was validated on cylindrical gyroid structures under compression. Findings Annealing at 240°C increased flexural modulus and strength by 58.7 % and 72.7 %, respectively, shifting failure from delamination to bulk fracture. For gyroid structures, compressive modulus and yield strength improved by 16.7% and 23.2%. Enhancements stemmed from stress relaxation and improved interlayer bonding rather than crystallinity changes. Originality/value This work combines thermal analysis, molecular simulation and failure characterization to explain why annealing improves the performance of amorphous FFF-printed PEKK and provides a practical route for post-processing optimization of complex PEKK structures.
Purpose - Microfluidic device design remains time-intensive and heavily reliant on computer-aided design (CAD) expertise, which limits scalability in rapid prototyping, high-throughput experimentation and standardized design workflows. While large language models (LLMs) offer a route toward automated CAD, existing script-based CAD tools, e.g. CADQuery, are prompt-sensitive and prone to geometric inconsistencies. This study aims to enable reliable rapid prototyping by accelerating the design-to-fabrication cycle through an LLM-assisted, Python-mediated framework for microfluidics and performing physical fabrication and dimensional validation to confirm whether designs meet manufacturing tolerances and functional requirements. Design/methodology/approach - ChatGPT is used to generate a closed-loop Python script, executed through a Python script that generates scalable vector graphics (SVG), drawing exchange format (DXF) and standard tessellation language (STL) outputs of microfluidic geometries, including Spiral Mixers, T-Junctions and Y-Junctions along with script execution time. Each design run is logged with a cryptographic hash to ensure traceability and confirm reproducibility. Physical fabrication using fused deposition modelling and dimensional validation using optical metrology on a digital microscope were essential to confirm whether designs meet manufacturing tolerances and functional requirements. Device functionality was assessed through pressure resistance evaluation, with indicative pressure-drop estimates calculated at leakage onset using the Hagen-Poiseuille approximation. Findings - ChatGPT/Python workflow substantially reduces iteration time compared with the manual CAD workflow. Post-fabrication measurements showed dimensional deviations up to 12.6% across all geometries while iterative compensation further reduced dimensional deviations. Pressure resistance testing confirmed indicative functional device integrity within low-to-moderate flow regimes, with leakage onset observed at flow rates consistent with fused deposition modelling-related sealing limitations, with no evidence of gross geometric errors in the generated CAD files. Originality/value - This workflow separates probabilistic LLM interaction from deterministic geometry execution. It provides a traceable route from design generation to exploratory fabrication, supported by cryptographic logging, dimensional validation and iterative compensation.
