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Additive manufacturing is a fabrication technology with flexibility and economy. 18Ni300 is one of maraging steels with ultra-high strength, superior toughness, so it is an excellent candidate of structural material. This paper aims to explore the feasibility of using direct laser metal deposition method to fabricate18Ni300, and the evolution of its microstructure and defects is studied.

The experiments were conceived from single-trace-single-layer (STSL) test to multi-trace-multi-layers (MTML) test via single-trace-multi-layers (STML) test. The microstructure, defects and mechanical properties were analyzed.

The STML results showed that the columnar/equiaxed transformation occurred at the top part and the grain size increased with the layer number increasing, and it was explained by an innovative attempt combining columnar/equiaxed transformation model and the change of grain size. The MTML test with the interlayer orthogonal parallel reciprocating scanning pattern resulted in the grain growing along orthogonal directions; with the increase of overlap rate, the length and the area of the columnar grain decreased. What is more, the later deposition layer had lower micro-hardness value because of heat history.

Direct laser metal deposition method was a novel additive manufacturing method to manufacture 18Ni300 components, as 18Ni300 maraging steel was mainly manufactured by selective laser melting (SLM) method nowadays. It was useful to manufacture maraging steel parts using direct laser deposition method because it could manufacture larger parts than SLM method. Influence of processing parameters on forming quality and microstructure evolution was studied. The findings will be helpful to understand the forming mechanism of laser additive manufacturing of 18Ni300 components.

This paper aims to explore the influences of different process parameters, including laser power, scanning speed, defocusing distance and scanning mode, on the shape features of molten pool and, based on the obtained relationship, realize the diagnosis of forming defects during the process.

Molten pool was captured on-line based on a coaxial CCD camera mounted on the welding head, then image processing algorithms were developed to obtain melt pool features that could reflect the forming status, and it suggested that the molten pool area was the most sensitive characteristic. The influence of the processing parameters such as laser power, traverse speed, powder feed rate, defocusing distance and the melt pool area was studied, and then the melt pool area was used as the characteristic to detect the forming defects during the cladding and additive manufacturing process.

The influences of different process parameters on molten pool area were explored. Based on the relationship, different types of defects were accurately detected through analyzing the relationship between the molten pool area and time.

The findings would be helpful for the quality control of laser additive manufacturing.

The purpose of this paper was to use visual and arc sensors to simultaneously obtain the underwater wet welding information, and a weld seam-forming model was made to predict the weld seam's geometric parameters. It is difficult to obtain a fine welding quality in underwater welding because of the intense disturbances of the water environment. To automatically control the welding quality, the weld seam-forming model should first be established. Thus, the foundation was laid for automatically controlling the underwater welding seam-forming quality.

Visual and arc sensors were used simultaneously to obtain the weld seam image, current and voltage information; then signal algorithms were used to process the information, and the back propagation (BP) neural network was used to model the process.

Experiment results showed that the BP neural network model could precisely predict the weld seam-forming parameters of underwater wet welding.

A weld seam-forming model of underwater wet welding process was made; this laid the foundation for establishing a controller for controlling the underwater wet welding process automatically.

This study aims to explore the influence of information presentation conditions on the flow experience of digital reading for high school students.

Firstly, a survey determines the preferred reading medium and the types of texts that high school students frequently read. Secondly, Experiment 1 focuses on the effects of the text type and reading medium on flow experience and reading comprehension. Finally, Experiment 2 addresses a narrative text presented on a smartphone, and discusses the influence of advance organizer, presentation format and page layout on flow experience and reading comprehension.

In digital reading, the narrative text has a stronger flow experience than explanatory text; the flow experience of reading narration on smartphones is more evident than on computers. The advance organizer and text combined with pictures are more conducive to a flow experience when a smartphone is used as a reading medium. From the perspective of reading comprehension, scrolling is more suitable for reading text combined with pictures and paging best suits pure text.

Through experimental methods, this study reveals the influence of information presentation conditions on the digital reading flow experience, which is a meaningful and innovative topic. The findings can provide more enlightenment and reference for the design and promotion of digital resources and digital reading by teenagers.