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The purpose of this study is to investigate the thermoforming process of 3D-printed parts made from polylactic acid (PLA) and explore its application in producing wrist-hand orthoses. These orthoses were 3D printed flat, heated and molded to fit the patient’s hand. The advantages of such an approach include reduced production time and cost.

The study used both experimental and numerical methods to analyze the thermoforming process of PLA parts. Thermal and mechanical characteristics were determined at different temperatures and infill densities. An equivalent material model that considers infill within a print is proposed. Its practical use was proven using a coupled finite-element analysis model. The simulation strategy enabled a comparative analysis of the thermoforming behavior of orthoses with two designs by considering the combined impact of natural convection cooling and imposed structural loads.

The experimental results indicated that at 27°C and 35°C, the tensile specimens exhibited brittle failure irrespective of the infill density, whereas ductile behavior was observed at 45°C, 50°C and 55°C. The thermal conductivity of the material was found to be linearly related to the temperature of the specimen. Orthoses with circular open pockets required more time to complete the thermoforming process than those with hexagonal pockets. Hexagonal cutouts have a lower peak stress owing to the reduced reaction forces, resulting in a smoother thermoforming process.

This study contributes to the existing literature by specifically focusing on the thermoforming process of 3D-printed parts made from PLA. Experimental tests were conducted to gather thermal and mechanical data on specimens with two infill densities, and a finite-element model was developed to address the thermoforming process. These findings were applied to a comparative analysis of 3D-printed thermoformed wrist-hand orthoses that included open pockets with different designs, demonstrating the practical implications of this study’s outcomes.

This study aims to fabricate the acrylic-based polymeric composite coating with a hydrophobic surface associated with natural oil polyol (NOP) and polydimethylsiloxane with the incorporation of 3 Wt.% SiO₂ nanoparticle (SiO₂np) against the corrosive NaCl media.

The structural properties of the formulated polymeric composite coatings were investigated by using Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, water contact angle (WCA) and cross-hatch (X-Hatch) tests. The WCA measurement was used to study the surface wettability of the formulated polymeric composite coatings. The corrosion protection performance of the nanocomposite coated on the mild steel substrate was studied by immersing the samples in 3.5 Wt.% NaCl solution for 30 days using electrochemical impedance spectroscopy.

The enhanced polymeric composite coating system performed with an excellent increase in the WCA up to 111.1° which is good hydrophobic nature and very high coating resistance in the range of 10¹⁰ Ω attributed to the superiority of SiO₂np.

The incorporation of SiO₂np into the polymeric coating could enhance the surface roughness and hydrophobic properties that could increase corrosion protection. This approach is a novel attempt of using NOP along with the addition of SiO₂np.

This study establishes a method for predicting ground vibrations caused by railway tunnels in unsaturated soils with spatial variability.

First, an improved 2.5D finite-element-method-perfect-matching-layer (FEM-PML) model is proposed. The Galerkin method is used to derive the finite element expression in the ub-pl-pg format for unsaturated soil. Unlike the ub-v-w format, which has nine degrees of freedom per node, the ub-pl-pg format has only five degrees of freedom per node; this significantly enhances the calculation efficiency. The stretching function of the PML is adopted to handle the unlimited boundary domain. Additionally, the 2.5D FEM-PML model couples the tunnel, vehicle and track structures. Next, the spatial variability of the soil parameters is simulated by random fields using the Monte Carlo method. By incorporating random fields of soil parameters into the 2.5D FEM-PML model, the effect of soil spatial variability on ground vibrations is demonstrated using a case study.

The spatial variability of the soil parameters primarily affected the vibration acceleration amplitude but had a minor effect on its spatial distribution and attenuation over time. In addition, ground vibration acceleration was more affected by the spatial variability of the soil bulk modulus of compressibility than by that of saturation.

Using the 2.5D FEM-PML model in the ub-pl-pg format of unsaturated soil enhances the computational efficiency. On this basis, with the random fields established by Monte Carlo simulation, the model can calculate the reliability of soil dynamics, which was rarely considered by previous models.