Research on the Process, Energy Consumption and Carbon Emissions of Different Magnesium Refining Processes.

Under the policy of low carbon energy saving, higher requirements are put forward for magnesium smelting. As the mainstream magnesium smelting process, the Pidgeon process has the disadvantages of a long production cycle, high energy consumption and high carbon emission, which makes it difficult to meet the requirements of green environmental protection. This paper reviews the research progress on different magnesium smelting processes and further analyzes their energy consumption and carbon emissions. It is concluded that the standard coal required for the production of tons of magnesium using the relative vacuum continuous magnesium refining process is reduced by more than 1.5 t, the carbon emission is reduced by more than 10 t and the reduction cycle is shortened by more than 9.5 h. The process has the advantages of being clean, efficient and low-carbon, which provides a new way for the development of the magnesium industry.

Automatic Extraction of Structural and Non-Structural Road Edges from Mobile Laser Scanning Data.

Accurate road information is important for applications involving road maintenance, intelligent transportation, and road network updates. Mobile laser scanning (MLS) can effectively extract road information. However, accurately extracting road edges based on large-scale data for complex road conditions, including both structural and non-structural road types, remains difficult. In this study, a robust method to automatically extract structural and non-structural road edges based on a topological network of laser points between adjacent scan lines and auxiliary surfaces is proposed. The extraction of road and curb points was achieved mainly from the roughness of the extracted surface, without considering traditional thresholds (e.g., height jump, slope, and density). Five large-scale road datasets, containing different types of road curbs and complex road scenes, were used to evaluate the practicality, stability, and validity of the proposed method via qualitative and quantitative analyses. Measured values of the correctness, completeness, and quality of extracted road edges were over 95.5%, 91.7%, and 90.9%, respectively. These results confirm that the proposed method can extract road edges from large-scale MLS datasets without the need for auxiliary information on intensity, image, or geographic data. The proposed method is effective regardless of whether the road width is fixed, the road is regular, and the existence of pedestrians and vehicles. Most importantly, the proposed method provides a valuable solution for road edge extraction that is useful for road authorities when developing intelligent transportation systems, such as those required by self-driving vehicles.

High-power air-cooled SiC-clad Nd:YVO4 slab lasers.

We demonstrate a diode-pumped, air-cooled, 100 W class SiC-clad Nd:YVO(4) active slab laser based on diffusion bonding of two SiC plates to a thin Nd:YVO(4) slab. We obtained 83 W of cw output power with a slope efficiency of 27% without water cooling. This demonstration initiates a novel (to the best of our knowledge) cooling design for efficient removal of waste heat generated from the diode edge-pumped high-power slab laser at room temperature.