Jinghua Xu

This article proposes a toward zero-support design method for irregular manifold manufacturing of composite materials based on layered adhesion equalization (LAE). Especially, external support in holes of irregular 3D manifold manufacturing by additive manufacturing (AM) is difficult to remove, which means toward zero-support design is indispensable to some complex curved surface components. AM largely depends on three main constraints, such as external support, layer thickness, and build time, which are mainly affected by building orientation and infill trajectory. Moreover, considering problems that variable layer thickness will bring material imbalance and residual stress heterogeneity, the layered orthogonal projection areas of the virtual printing prototype on the orthogonal planes, such as the positive plane and side plane in the 3D printing coordinate system, are introduced as LAE constraints to realize equilibrium reinforcement design (ERD) for both LAE and external support. Subsequently, using transient thermal structure coupling via finite element analysis, the transient thermal structure coupling analysis of fiber composite under multiple working conditions is further obtained. In particular, the influence mechanism of continuous fiber forming on the mechanical behavior of the topological configuration is revealed. Taking the irregular three-way manifold by concept design as an example, a specimen was fabricated using polylactic acid (PLA) with carbon fiber on the strength of fused deposition modeling. The infrared thermographs using thermal field measurement were carried out to obtain the temperature distribution during manufacture. The innovatively proposed LAE method is propitious to improve the additive manufacturability and adaptability of lightweight thin-wall structures, especially for fiber-reinforced composites. This is advantageous for utilisation in the domain of aerospace components.

High-fidelity morphology modelling of complex surfaces is the basis for accurate characterization of surface quality and quasi-realistic performance analysis in areas such as digital process design and digital twin. High-fidelity morphology modelling is usually based on high-resolution data, which is inefficient to acquire and reconstruct, while conventional methods using sparse point cloud have poor modelling accuracy. To address this problem, a high-fidelity morphology modelling method with sparse point cloud of complex surface based on variational mode decomposition (VMD) feature extraction and predictive reconstruction is proposed. The algorithm is based on VMD for mode decomposition of surface morphology feature data of surface parts, firstly, a feedback mode separation method is used to determine the number of decomposed modes; secondly, a morphology feature extraction based on high-resolution point cloud is proposed, uses morphology feature functions to fit and extract surface features, and finally, a high-fidelity morphology model reconstruction with measured sparse point cloud is used, and an innovative high-fidelity prediction with shape and morphology feature reconstruction method is proposed to reconstruct the surface morphology of sparsely sampled surface parts into high-resolution surface morphology of parts. The experimental results of the turbine blade indicate that the sampled data volume of the sparse point cloud is only 6.25% of the high-resolution point cloud, and the average morphology error of the reconstruction algorithm is about 2 μm, with the average error rate and the standard deviation error rate of 0.08% and 0.21%, respectively. The proposed morphology modelling method has high accuracy and low complexity, which can achieve efficient and high-fidelity reconstruction with sparse point cloud of complex surfaces.