Modern Transportation and Metallurgical Materials

Reflections and prospects on the intelligent development of the iron and steel industry

Artificial intelligence technology is comprehensively reshaping the steel industry. This paper adopts a research methodology that combines literature review， comparative analysis of domestic and international cases of steel intelligentization development， and industry practice induction. It reviews the global development trends of steel industry intelligentization and analyzes the technological pathways and implementation outcomes of steel industry intelligentization construction in countries such as the United States， Japan， Europe， South Korea， and India. With the goal of building a strong steel nation， this paper explores the establishment of an AI-driven on-demand design technology system for steel products in China， develops a new paradigm of fully autonomous production centered on the implementation and application of vertical large models integrating mechanism and data， and proposes an innovative model of exploring an AI-empowered steel platform economy consortium with comprehensive supdemand alignment to achieve intensive operation of advantageous production capacity，aiming to provide a reference for the intelligent transformation of the steel industry.

Special Topic Introduction

Special Topic Introduction

Normative mapping and scenario⁃specific mechanisms for trusted data spaces in Jiangsu’s transport sector

Transport data are multi-source， heterogeneous， real-time， generated by diverse participants， and highly sensitive. This study examines the trusted data space for Jiangsu’s transport sector and how general specifications can be translated into executable industry capabilities for marketoriented and regulatory scenarios. Using normative text analysis， scenario-mechanism analysis， and a case study， it maps identity， catalogue， connectors， digital contracts， usage control， and performance auditing into a framework of one data-resource system， three platforms， and N scenarios. It compares the two scenario types in terms of authorization basis， delivery， audit responsibility， and value rules.The Zhongtian Steel inland-waterway dispatch data service case shows that API-based data products can establish a compliant and controlled data-circulation channel between the Subei Navigation Administration and an enterprise， supporting real-time awareness of navigation conditions and dispatch adjustments. The findings provide a reference for building trusted data spaces in transport and other multiparty， sensitive sectors.

Large⁃scale 3D reconstruction algorithm for transportation infrastructure

Large-scale 3D reconstruction of transportation infrastructure faces multiple challenges， including wide scene coverage， uneven scene point density， limited GPU memory， and seam artifacts at block boundaries. This paper proposes a block-fusion method based on 3D Gaussian Splatting （3DGS）. The sparse point clouds are used for global coarse training to establish geometric priors for road alignments， bridge profiles， and surrounding scene features. The entire scene is adaptively partitioned based on Gaussian density and octree-based spatial relationships. Meanwhile， a view-block relevance filtering mechanism is introduced to eliminate redundant images and balance local computational loads. Geometric and color consistency constraints applied to overlapping regions enable seamless block fusion， and level-of-detail rendering improves the efficiency of interactive visualization. Experiments are conducted on 1892 UAV images capturing an approximately 3 km² transportation corridor， with roads and bridges as the primary reconstruction targets. Compared with the SfM-MVS base‑line method， the proposed method reduces total processing time from 267 min to 197 min， with a 26.2% reduction. Across six test categories， the average SSIM increases from 0.459 to 0.840， the average PSNR increases from 17.041 dB to 28.495 dB， and the average LPIPS decreases from 0.589 to 0.291. Experimental results verify that the proposed method improves reconstruction efficiency， structural continuity， and texture fidelity， and can support digital modeling and digital twin visualization of transportation infrastructure.

Research on the simulation and optimization for seaport anchorage area configuration with an anchorage position sharing mechanism

To promote the optimized integration of port resources, this study focuses on the configuration optimization of seaport anchorage areas. Considering the increasingly diversity of vessel types, an anchorage position sharing mechanism is introduced to more realistically characterize the complex interactions among stochastic vessel arrivals, tidal variations, extreme weather, and berth constraints. A multi-objective optimization model for anchorage position configuration is constructed based on the discrete-event system simulation, aiming to minimize both average vessel time in port and anchorage construction and operation costs. The Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ) is employed to solve the model. A case study of the Lvsi Operating Area within the Tongzhou Bay Port Area of Nantong Port is conducted to evaluate the applicability of the proposed model. The results indicate that, a structural mismatch exists between the current anchorage position configuration and actual vessel demand, characterized by a surplus of 50000 DWT anchorage positions and a deficiency of 100000 DWT anchorage positions; by reconfiguring the general and dangerous anchorages to four and three 100000 DWT anchorage positions respectively, the system incorporating the sharing mechanism can fully accommodate vessels waiting offshore, reducing the average turnaround time by approximately 3.71%; further optimization reveals that, compared to the exclusive anchorage position mechanism, the sharing mechanism effectively reduces vessel turnaround time by 1.2% to 7.5% under optimized configurations.

New energy vehicle industry: current development state and issues

The development of new energy vehicles has become a core strategy for the Chinese automotive industry to achieve a competitive advantage. This paper analyzes the current development status of new energy vehicles in both domestic and international market, as well as the penetration modes of different levels of new energy vehicles in China. The results show that new energy vehicles have entered a period of fast penetration, and the production and sales volume have increased exponentially. In 2022, China's new energy vehicles accounted for 59% of the global market share, and the proportion is continuing to rise. The development of China's new energy vehicle market is becoming more diversified, with a penetration rate of 100% for A00-class and gradually penetrating into higher-class vehicle sectors. Chinese automobile companies have emerged strongly in the field of new energy vehicle market, with each showcasing their unique strengths, and the competition among companies is becoming increasingly fierce. We look forward to creating a new pattern of coordinated development and win-win cooperation.

State-of-the-art and prospect of intelligent shipping

Shipping is a transportation mode with vessels as the carrier,ports as the nodes and oceans,rivers,lakes as the channels. Intelligent shipping includes five elements:intelligent port,intelligent vessel,intelligent waterway,intelligent supervision and intelligent service. This paper mainly studies the state-of-the-art of the key technologies and applied cases involved in the intelligent port and vessel,makes a prospect to the future new-generation shipping system.

New energy vehicle industry: current development state and issues

The development of new energy vehicles has become a core strategy for the Chinese automotive industry to achieve a competitive advantage. This paper analyzes the current development status of new energy vehicles in both domestic and international market, as well as the penetration modes of different levels of new energy vehicles in China. The results show that new energy vehicles have entered a period of fast penetration, and the production and sales volume have increased exponentially. In 2022, China's new energy vehicles accounted for 59% of the global market share, and the proportion is continuing to rise. The development of China's new energy vehicle market is becoming more diversified, with a penetration rate of 100% for A00-class and gradually penetrating into higher-class vehicle sectors. Chinese automobile companies have emerged strongly in the field of new energy vehicle market, with each showcasing their unique strengths, and the competition among companies is becoming increasingly fierce. We look forward to creating a new pattern of coordinated development and win-win cooperation.