Industrial Safety Technology

Profound structural realignment is unfolding across the global energy system, and China has integrated carbon peaking and carbon neutrality frameworks into governance practices at all administrative levels. For regional economies, advancing the new energy sector transcends purely environmental imperatives — it has evolved into a core engine underpinning sustained economic expansion and a vital pathway to strengthening domestic energy supply resilience[1]. Shantou stands out as the primary hub for the offshore wind power infrastructure in eastern Guangdong, boasting exceptional marine wind resources and benefiting from various supportive industrial policies. A new energy ecosystem centered around offshore wind power has been preliminarily established. Nevertheless, it encounters significant practical hurdles such as incomplete industrial chain extension, limited innovation capacity in key technologies, and constrained power consumption capabilities. This study delves into the foundational aspects of Shantou's new energy sector and systematically examines the factors impeding its high-quality advancement. It also puts forth development recommendations encompassing enhancements to the policy framework, facilitation of coordinated industrial chain growth, bolstering of technological innovation, augmentation of consumption capacity, assurance of essential resources, and promotion of holistic development. These efforts aim to assist Shantou in establishing a new energy industry cluster valued at 100 billion yuan and attaining regional "dual carbon" objectives.

With the rapid development of the semiconductor manufacturing industry, the large quantities of high-risk chemicals, specialty gases, and precision equipment involved in its production processes have brought severe industrial safety challenges. Traditional safety monitoring methods have limitations in sensitivity, response speed, and adaptability to complex environments. Based on InAs/GaSb type-II superlattice infrared detection technology, this paper discusses a smart safety monitoring system for semiconductor factories. The paper first analyzes the typical safety risks and detection requirements in semiconductor manufacturing scenarios; second, it explains the physical advantages of type-II superlattice materials in the field of infrared detection and their application principles in gas leak detection; on this basis, it designs a smart monitoring system architecture of "infrared detection + AI analysis"; finally, it looks ahead to the application prospects of this technology in the field of industrial safety. This study aims to transform cutting-edge semiconductor optoelectronic technology into industrial safety productivity and provide new ideas for the intrinsic safety of semiconductor factories.

Coal accounts for over 53% of China's primary energy consumption, making its production safety a critical pillar of national energy security. However, major coal mine accidents persist, largely attributable to inadequate emergency response capabilities. To address the challenges of information uncertainty and complex indicator interdependencies, this paper constructs a Bayesian Network (BN)-based evaluation model for coal mine emergency response capability. Following the Coal Mine Safety Regulations, an index system encompassing 4 dimensions—personnel, equipment, environment, and management—with 14 specific indicators was established. The BN structure, comprising 19 nodes and 21 directed edges, was built using GeNIe software, with Conditional Probability Tables parameterized via a logic-grading method based on expert-defined rules and indicator grading standards. A case study at a large Shandong mine demonstrates that the comprehensive capability is rated "Excellent" (probability 38%), with a cumulative probability of 70% for "Excellent" and "Good", consistent with the mine's actual safety status during its intelligent transformation. Sensitivity analysis identifies "safety violation inspections" as the most influential factor.

To investigate the impact of full-cycle floor drifts on the production and safety of mining faces, this study aims to clarify the overlapping range of fracture zones between coal roadways and floor gas drainage drifts during excavation, as well as the stability-maintaining parameters and functional mechanisms of full-cycle floor drifts during mining. The time-varying superimposed effects of fracture zones in full-cycle floor drifts and coal roadways were analyzed, leading to the determination of the optimal layout interval between full-cycle floor drifts  (with different service lives) and coal roadways. Additionally, the optimal goaf pressure reduction coefficient was identified using the comprehensive mean difference, and the depth and width of fracture development in the mining face floor were quantified. Based on these theoretical results, numerical simulations were performed using FLAC^3D software, field tests were conducted to verify the reliability of the theoretical deductions and numerical models. The verification results indicate that when the full-cycle floor drifts in the Xin'an Coalfield is arranged 17 m below the coal seam floor and 10 m inward offset from the coal roadway, it can fully satisfy to the technical requirements of face excavation and mining. Specifically, the height and width deformations of the full-cycle floor drifts are reduced from 800–950 mm and 510–520 mm to 450–550 mm and 250–350 mm, respectively, with deformation reduction rates of 42–43% (height) and 32–50% (width). Meanwhile, temporary boreholes in the full-cycle floor drifts can effectively extract gas from the coal seam (around the open-off cut of the mining face) and goaf, reducing the gas emission rate of the working face by 0.95 m³/min and ensuring that the gas concentration in the return airflow remains stable within 0.22% during mining in thick coal zones.

To reasonably determine the sensitive indicators for predicting coal and gas outburst hazards in mining faces, this study employs mathematical modeling to process measured drill cuttings gas desorption data through dimensionless and standardized treatment, calculating their sensitivity functions and identifying their sensitivity. The results indicate that among the three indicators used for outburst prediction, the drill cuttings gas desorption index K1 is more sensitive than the drill cuttings gas desorption index Δh2 and the drill cuttings volume S. Thus, K1 can serve as the sensitive indicator for predicting coal and gas outburst hazards in this mining face. When the K1 value exceeds the internal control threshold of 0.4 mL/(g·min^1/2), abnormal phenomena such as borehole spraying, bit jamming, abnormal gas emission from drill holes, or coal burst sounds may occur during drilling, and the more significant the K1 value, the more pronounced the dynamic effects. Comparative analysis of field test data shows that the mathematical model's analysis results are largely consistent with actual observations, ultimately confirming the drill cuttings gas desorption sensitive indicator for the test area. Through practical application of the sensitive indicator for coal and gas outburst hazard prediction in the 1306 mining face of a certain mine, favorable outcomes were achieved.

To improve the connection between fire-dynamics review and engineering-oriented numerical simulation, this paper reviews research progress in heat release rate characterization, fire plumes and ceiling jets, smoke-layer development, flame spread, and numerical modeling methods. A PyroSim/FDS model is then established for a semi-enclosed compartment to compare temperature fields, smoke-layer height, visibility, and ventilation effects under different fire sizes, opening conditions, and mechanical exhaust scenarios. The computational domain is 12.0 m x 6.0 m x 4.0 m, with a 2.0 m x 2.0 m doorway, a 1.5 m x 1.0 m side window, and a 1.0 m x 1.0 m fire source. Large eddy simulation is adopted to describe the smoke movement. The results show that, in the 2.0 MW baseline case, the smoke layer descends to 2.0 m at approximately 222 s, while the far-field visibility at a height of 1.5 m decreases to 15 m at approximately 216 s. Closing the side window significantly accelerates smoke accumulation, whereas mechanical exhaust keeps the smoke-layer height above 2.79 m and the visibility at approximately 29.2 m at 300 s. The proposed framework, which combines literature review, model-credibility control, and multi-index safety evaluation, provides a reference for fire-risk assessment and smoke-control optimization in semi-enclosed spaces.