Methods of correction to extrinsic parameters in a stereoscopic vision with the assistance of two known-distance points.

Stereoscopic vision plays a significant role in a three-dimensional measurement. With the calibrated intrinsic and extrinsic parameters, stereoscopic vision can complete an accurate measurement. However, the extrinsic parameters are inevitably disturbed by variations in the environment, such as vibration and assembly stress, resulting in a huge measurement error. To overcome the problem, with the assistance of two known-distance points, this Letter proposes correction methods based on triangulation and differential geometry, respectively. The methods formulate the distance and solve the corrected extrinsic parameters. Simulated and actual experiments are carried out, and the results show high accuracy and stability of the proposed methods.

Modeling and self-supporting printing simulation of fuse filament fabrication.

This study presented a comprehensive computational fluid dynamics-based model for fused filament fabrication (FFF) three-dimensional (3D) printing multiphase and multiphysics coupling. A model based on the framework of computational fluid dynamics was built, utilizing the front-tracking method for high precision of multiphase material interfaces, a fully resolved simulation at the mesoscale explores the underlying physical mechanism of the self-supported horizontal printing. The study investigated the influence of printing temperature and velocity on the FFF process, exhibiting a certain self-supporting forming ability over a specific range. The results indicated that during the printing of large-span horizontal extension structures, the bridge deck material transitions from initial straight extension to sagging deformation, ultimately adopting a curved shape. The straight extension distance is inversely proportional to the depth of the sagging deformation. Additionally, the study revealed that printing temperature primarily affected the curing time of the molten material, while printing velocity fundamentally affected the relaxation time of both thermal and dynamic characteristics of the material.

A Best-Fitting B-Spline Neural Network Approach to the Prediction of Advection-Diffusion Physical Fields with Absorption and Source Terms.

This paper proposed a two-dimensional steady-state field prediction approach that combines B-spline functions and a fully connected neural network. In this approach, field data, which are determined by corresponding control vectors, are fitted by a selected B-spline function set, yielding the corresponding best-fitting weight vectors, and then a fully connected neural network is trained using those weight vectors and control vectors. The trained neural network first predicts a weight vector using a given control vector, and then the corresponding field can be restored via the selected B-spline set. This method was applied to learn and predict two-dimensional steady advection-diffusion physical fields with absorption and source terms, and its accuracy and performance were tested and verified by a series of numerical experiments with different B-spline sets, boundary conditions, field gradients, and field states. The proposed method was finally compared with a generative adversarial network (GAN) and a physics-informed neural network (PINN). The results indicated that the B-spline neural network could predict the tested physical fields well; the overall error can be reduced by expanding the selected B-spline set. Compared with GAN and PINN, the proposed method also presented the advantages of a high prediction accuracy, less demand for training data, and high training efficiency.

Surface Treatments for Enhancing the Bonding Strength of Aluminum Alloy Joints.

Aluminum alloy adhesive bonding joint widely appears in many industrial products. Improving the mechanical performances of aluminum alloy bonding joints has been attracting much effort. To acquire more excellent bonding strength, this paper focused on the effects of different surface treatments, including laser ablation and milling superposed by phosphoric acid anodizing (PAA). The treated surfaces were characterized by roughness and contact angle, and the effects of the geometric parameters of microstructures on wettability, failure mode, and shear strength were examined. The results indicate that those surfaces where the spacing is smaller than the diameter present a hydrophilic property and the corresponding specimens are mainly subject to cohesive failure, and vice versa. Additionally, laser ablation with a properly designed dimple pattern can greatly improve the bonding strength, and the maximum average shear strength of specimens with a thickness of 50 µm reaches 32.82 MPa, which is an increase of 28.15% compared with the original milling specimen. Moreover, fabricating groove or grid patterns on the surfaces and applying PAA treatment can also significantly enhance the bonding strength, reaching up to 36.28 MPa.

Evaluation of the Equivalent Mechanical Properties of Lattice Structures Based on the Finite Element Method.

Lattice structures have excellent mechanical properties and can be designed by changing the cellular structure. However, the computing scale is extremely large to directly analyze a large-size structure containing a huge number of lattice cells. Evaluating the equivalent mechanical properties instead of the complex geometry of such lattice cells is a feasible way to deal with this problem. This paper aims to propose a series of formulas, including critical structural and material parameters, to fast evaluate the equivalent mechanical properties of lattice structures. A reduced-order model based on the finite element method and beam theory was developed and verified by comparing it with the corresponding full model. This model was then applied to evaluate the equivalent mechanical properties of 25 types of lattice cells. The effects of the material Young's modulus and Poisson's ratio, strut diameter, cell size, and cell number on those equivalent mechanical properties were investigated and discussed, and the linear relationship with the material parameters and the non-linear relationship with the structural parameters were found. Finally, a series of analytical-fitting formulas involving the structural and material parameters were obtained, which allows us to fast predict the equivalent mechanical properties of the lattice cells.

A Numerical Study on the Mesoscopic Characteristics of Ti-6Al-4V by Selective Laser Melting.

Selective laser melting is a typical powder-bed additive manufacturing technology, for which it is difficult and expensive to observe and measure the molten pool due to its short lifetime and tiny size. This paper introduced a two-stage mesoscopic layer-by-layer simulation framework for the numerical study of the SLM process, where the powder laying and laser scanning are included and conducted alternatively. For the simulation of powder laying, the dynamic behaviors of the particles as well as the particle-particle and particle-scraper interactions are included. For the simulation of laser scanning, a coupled multi-phase and multi-physics system was considered, where the effects of surface tension, Marangoni effect, and vapor recoil are considered, and the behaviors of heat transfer, fluid flow, and melting/solidification are simulated. This simulation framework was then used to simulate the Ti-6Al-4V SLM process. The evolutions of the molten pool and track were presented, and the characteristics of the molten pool, keyhole, and track were analyzed and discussed, specifically, the effects of the laser power and scanning speed on the three-dimensional morphology and size of the molten pool were numerically studied, and their dependencies were discussed and found.