Multi-material products are required in fused deposition modelling (FDM) to meet a desired specification such as a rigid structure with soft material for impact protection. This paper focuses on the thermoformability and shape recovery characteristics of three-dimensional (3D)-printed multi-material specimens under different thermoforming temperatures. The multi-material specimens consist of polylactic acid (PLA) and thermoplastic polyurethane (TPU). The PLA/TPU specimens were prepared by depositing the TPU component on top of the PLA component using a fused deposition modelling (FDM) machine. Simple thermoforming tests were proposed, where the specimens were bent under load and molded into a circular shape at different thermoforming temperatures. The bent specimens were then reheated at 60 °C to evaluate their shape memory ability. The test results were quantified into apparent bending modulus and shape recovery percentage. The PLA/TPU specimens showed a better apparent bending modulus of 143 MPa than a PLA specimen at a temperature between 60 °C to 90 °C. However, only the PLA/TPU specimens being thermoformed into a circular shape at 100 °C or greater showed good shape retention accuracy and interfacial surface bonding. The PLA/TPU specimens that were thermoformed at 60 °C to 90 °C showed reasonable shape memory of about 60% recovery when reheated. Finally, suitable thermoforming temperatures for thermoforming PLA/TPU specimens were suggested based on design needs.

Directed energy deposition (DED) provides a promising additive manufacturing method to fabricate and repair large metallic parts. However, it may suffer from excessive heat accumulation due to a high build rate, particularly during a wire feeding-type DED process. The implementation of interpass time in between two depositions of beads plays an important process role to passively control the interpass temperature. In this study, a method to estimate the proper interpass time using regression analysis from heat transfer finite element analysis is proposed for maintaining the interpass temperature during a wire feeding-type DED deposition of a planar layer. The overlapping beads of a planar layer are estimated using a polygonal-shaped bead profile in the finite element model. From the estimated proper interpass time, a selected proper interpass time scheme (PITS) is suggested for practical implementation. The selected PITS is applied in a thermo-mechanical finite element model to evaluate the temperature distribution and its effects on the depth of the melt pool, the depth of the heat-affected zone (HAZ), displacement, and residual stresses. By comparing the predicted results with those using a constant interpass time scheme (CITS), the selected PITS shows better control in reducing the depths of the melt pool and HAZ without severely inducing large displacement and residual stresses.

Solar photovoltaic (PV) array shows non-linear P-V characteristic when the array is illuminated under uniform solar irradiance. In this circumstance, the P-V characteristic consists only one maximum power point (MPP) along the functional operating voltage. However, the P-V characteristic has changed and become more complex with multiple MPP when the array is exposed under partially shaded conditions. This circumstance has caused maximum power point tracking (MPPT) algorithm faces difficulty to allocate the exact optimal operating voltage for PV array to generate maximum power. In this paper, initial voltage tracking function (IVTF) has been introduced to assign new initial voltage for tracking the absolute MPP when the PV array is at shaded conditions. Nevertheless, MPPT approach deals with the challenge of tracking the MPP in the faster mode while maintaining the power stability of the PV array toward the MPP. Therefore, fuzzy logic is embedded in the conventional MPPT to adapt the size of the perturbed voltage. The obtained results show that fuzzy logic based MPPT with IVTF is able to track the absolute MPP faster while minimizing power lost due to the power fluctuations.

This paper presents the fuzzy logic based maximum power point tracking for the optimization of the solar photovoltaic (PV) array under partially shaded conditions. The PV system is modelled in MATLAB/SIMULINK where the PV array is formed by five PV modules connected in series. The PV characteristic of PV module and PV array under uniform solar irradiance are nonlinear but there are one maximum power point (MPP) can be identified. Nevertheless, the PV characteristic becomes more complex with multiple MPP when the PV array under partially shaded conditions (PSC). In this paper, maximum power point tracking (MPPT) approach based on perturb and observe algorithm has been investigated. Fuzzy logic is adopted into the conventional MPPT to enhance the overall performance of the PV system. The performances of MPPT and FMPPT are investigated particularly on the transient response and the steady state response when the PV array is exposed under different partially shaded conditions. The simulation results show that FMPPT has better performance where it can facilitate the PV array to reach the MPP faster and provide more stable output power.

This paper presents the particle swarm optimization based maximum power point tracking (MPPT) approach for maximizing output power of photovoltaic (PV) array under partially shaded conditions (PSC). During PSC, the P-V characteristic becomes more complex with multiple maximum power points (MPP). Most of the conventional MPPT approaches will be trapped at the local MPP and hence limiting the maximum power generation. As such, the investigation on particle swarm optimization (PSO) based MPPT is carried out to maximize the PV generated power principally under PSC operation. The performances of conventional MPPT approach and the proposed PSO-MPPT are investigated particularly on the transient and steady state responses under various shaded conditions. The simulation results show that the PSO-MPPT is able to facilitate the PV array to reach the global MPP as well as to assist the PV array to produce more stable output power compared to the conventional perturb and observe (P&O) algorithm.