Effect of ultrasonic intensity on microstructure and mechanical properties of steel alloy in direct energy deposition-Arc.

To study the effect of ultrasonic intensity on the microstructure and mechanical properties during the direct energy deposition-Arc (DED-Arc) of ER70S-6 steel alloy, an ultrasound assisted DED-Arc system was developed by coupling ultrasonic energy with the electric arc deposition process. The propagation and vibration distribution of ultrasound in the substrate were analyzed by numerical simulation method. Deposition layers were fabricated using different ultrasonic amplitudes, and the microstructure, microhardness and tensile properties of the fabricated parts were systematically investigated. The results show that as the ultrasonic intensity increased, the grain refinement area expanded from the center of the molten pool to the surrounding area, and the grain morphology transforms from coarse columnar grains to fine equiaxed grains. When the ultrasonic amplitude was 15 µm, the grain refinement area of the cross-section was 94.6%, the average grain size was significantly increased to about grade 6. The microhardness increased by 10.6%. Thousands of ultrasonic cavitation events not only enhance the supercooling and wettability of the melt pool to promote nucleation, but also break the columnar grains into small grains by intense shock waves, which significantly improve the microstructure homogeneity and mechanical properties. The research provides an alternative approach to overcoming the long-standing problem of coarse columnar grains in the field of DED-Arc.

Microstructure and Mechanical Properties of Gradient Interfaces in Wire Arc Additive Remanufacturing of Hot Forging Die Steel.

Hot forging dies are subjected to periodic thermal stress and often fail in the forms of thermal fatigue, wear, plastic deformation, and fracture. A gradient multi-material wire arc additive remanufacturing method for hot forging dies was proposed to extend the service life of hot forging dies and reduce total production costs. The properties of multi-material gradient interfaces play a critical role in determining the overall performance of the final products. In this study, the remanufacturing zone of a hot forging die was divided into three deposition layers: the transition layer, the intermediate layer, and the strengthening layer. Experiments of wire arc additive manufacturing with gradient material were conducted on a 5CrNiMo hot forging die steel. The microstructure, microhardness, bonding strength, and impact property of gradient interfaces were characterized and analyzed. The results revealed that the gradient additive layers and their interfaces were defect-free and that the gradient interfaces had obtained a high-strength metallurgical bonding. The microstructure of the gradient additive layers presented a gradient transformation process of bainite-to-martensite from the bottom to the top layer. The microhardness gradually increased from the substrate layer to the surface-strengthening layer, forming a three-level gradient in the range of 100 HV. The impact toughness values of the three interfaces were 46.15 J/cm2, 54.96 J/cm2, and 22.53 J/cm2, and the impact fracture morphology ranged from ductile fracture to quasi-cleavage fracture. The mechanical properties of the gradient interfaces showed a gradient increase in hardness and strength, and a gradient decrease in toughness. The practical application of hot forging die remanufactured by the proposed method had an increase of 37.5% in average lifespan, which provided scientific support for the engineering application of the gradient multi-material wire arc additive remanufacturing of hot forging dies.

Laser radius measurement method based on the amplitude jump of a thermal wave.

The laser radius should be calculated with high precision when analyzing the characteristics of a Lamb wave excited by a laser in a thin plate. However, traditional methods for measuring the radius of a laser beam are complex. The paper aims to propose a novel convenient method, to the best of our knowledge, for measuring the radius of a laser ultrasonic beam. A laser interferometer (receiving laser) is used to receive ultrasonic signals excited by the laser to be measured (exciting laser) on the surface of a test block. Considering the characteristics represented by the thermal wave, positions where the receiving beam contacts and separates from the exciting beam are determined, and the spot of the radius is calculated by corresponding geometric relations. Experiments show that the accuracy of the proposed method is in the order of magnitude of 0.01 mm, and the relative errors of experimental data are within 2%. This paper provides an alternative method for the measurement of the laser beam radius and has great significance for the application of laser ultrasonic detection in the thin plate and the calculation and analysis of the dispersion curve.

Solid waste shape description and generation based on spherical harmonics and probability density function.

Transport and separation processes of solid waste can only be modelled successfully with discrete element methods in case the shape of the particles can be described accurately. The existing techniques for morphological data acquisition, such as computed tomography, laser scanning technique, optical interferometer, stereo photography and structured light technique, are laborious and require a large amount of realistic solid waste samples. Therefore, there is a pressing need for an alternative method to describe the shape of solid waste particles and to generate multiple variations of particles with almost similar shapes. In this paper, a new method to describe solid waste particles is proposed that is frequency-based and uses spherical harmonics (SHs). Additionally, a new shape generation method is introduced that uses the shape description of a single particle to generate an array of related shapes based on a probability density function with a dimensionless control factor η. The newly proposed methods were successfully applied to describe the complex shapes of pieces of metal and plastic scrap. The shapes of these pieces of scrap can be described adequately with 15° of SH expansion and the overall divergence is within 0.1 mm. Five different values for η were tested, which generated shapes with the same distribution as the original particle. Rising levels of η cause the morphological variation of the generated particles to increase. These new methods improve the modelling of transportation and separation processes.

A robust identification method for nonferrous metal scraps based on deep learning and superpixel optimization.

End-of-life vehicles (ELVs) provide a particularly potent source of supply for metals. Hence, the recycling and sorting techniques for ferrous and nonferrous metal scraps from ELVs significantly increase metal resource utilization. However, different kinds of nonferrous metal scraps, such as aluminium (Al) and copper (Cu), are not further automatically classified due to the lack of proper techniques. The purpose of this study is to propose an identification method for different nonferrous metal scraps, facilitate the further separation of nonferrous metal scraps, achieve better management of recycled metal resources and increase sustainability. A convolutional neural network (CNN) and SEEDS (superpixels extracted via energy-driven sampling) were adopted in this study. To build the classifier, 80 training images of randomly chosen Al and Cu scraps were taken, and some practical methods were proposed, including training patch generation with SEEDS, image data augmentation and automatic labelling methods for enormous training data. To obtain more accurate results, SEEDS was also used to optimize the coarse results obtained from the pretrained CNN model. Five indicators were adopted to evaluate the final identification results. Furthermore, 15 test samples concerning different classification environments were tested through the proposed model, and it performed well under all of the employed evaluation indexes, with an average precision of 0.98. The results demonstrate that the proposed model is robust for metal scrap identification, which can be expanded to a complex industrial environment, and it presents new possibilities for highly accurate automatic nonferrous metal scrap classification.

Laser Ultrasonic inspection of a Wire + Arc Additive Manufactured (WAAM) sample with artificial defects.

Certain defects like pores, incomplete fusion and micro cracks are sometimes inevitable in Wire + Arc Additive Manufactured (WAAM) components. However, these defects cannot be detected easily by conventional ultrasonic testing due to the rough surface and high temperature of WAAM components. In this paper, a Laser Ultrasonic (LU) system, consist of a pulsed laser and a laser interferometer, is employed to achieve non-contact inspection of artificial defects (crack, flat bottom hole and through hole) in a WAAM sample without surface machining. First, several WAAM samples with different welding parameters are manufactured by a robotic Gas Metal Arc Manufacture (GMAW) system. The 2D profiles of these samples are measured and reconstructed by a geometric optical measuring instrument for Finite Element (FE) analysis. Then, the multi-physics (Heat Transfer, Solid Mechanics, Pressure Acoustics) coupled FE model is established to simulate LU inspection of defects in the WAAM sample. The propagation of laser ultrasonic waves in the WAAM sample, as well as the mechanism of interaction between ultrasonic waves and defects is investigated numerically. In addition, LU inspection experiments are designed and conducted to obtain the A- and B-scan plots of different defects in the WAAM sample. Finally, quantitative inspection of the artificial defects is realized by analyzing the A- and B-scan plots. This paper verifies the feasibility of LU inspection of WAAM components without surface machining.

Operation parameters optimization of a separating system for non-ferrous metal scraps from end-of-life vehicles based on coupled simulation.

End-of-life vehicles (ELVs) provide a particularly potent source of non-ferrous metal scraps. At presents, conveyor belt and air-jet nozzle are widely used in the existing separation system for non-ferrous metal scraps. Parameters such as shape of the scraps, conveyor belt speed (v), nozzle air pressure (P) and nozzle angle (α) have a significant influences on the separating accuracy and efficiency. To investigate the interaction between these parameters and their influences on the separation distance, a coupled simulation model of (Discrete Element Method) DEM and (Finite Element Method) FEM was employed to simulate the motion of the scraps and the separation process, the trajectory of the scraps under different circumstances was recorded and analyzed, the simulation model was verified using a separation platform. The results indicated that block shaped scraps have the largest separation distance followed by rod and slice shaped scraps. The separation distance of rod and slice shaped scraps increases when each of the three parameters increases, and the speed of conveyor belt (v) plays a dominant role. For blocks shaped scraps, when nozzle pressure is high, the separation distance increase with the increase of conveyor belt speed, when nozzle pressure is low, the separation distance decrease with the increase of conveyor belt speed. The nozzle pressure (P) was found to have the most noticeable impact on separation distance for block shaped scraps. For the platform in this study, the optimal operation parameters obtained were v = 1.9 m/s, P = 0.53 MPa, and α = 42°.