Processes

The flow and solidification inside the mould are crucial to the quality of the casting billet during continuous casting. In this work, a three-dimensional coupled model of flow and solidification was established, and the flow field and temperature distribution characteristics of molten steel were deeply explored. The results indicated that the molten steel streams out of the SEN at a defined degree and enters the mould in the form of an impact stream, and then impacts the narrow surface. The eddy core position in the upper recirculation region of the flow field is (0.565 m, −0.179 m), and eddy core position in the lower recirculation region is (0.524 m, −0.455 m). Within the range of 100–400 mm from the liquid surface, the main stream and upper ring flow of molten steel have a significant impact on the solidification of the casting billet, and the distribution and longitudinal variation in the liquid phase ratio at different height sections are very obvious. At the exit of the mould, the average thickness of the inner arc and outer arc shells is 15.2 mm and 14.5 mm, respectively. The model can provide guidance for enhancing and optimizing the quality of continuous casting billets.

This study addresses the challenge of low working gas ratios in China’s underground gas storage (UGS) facilities by optimizing geomechanical evaluations to enable safe pressure increases and capacity expansion. Through mini-fracturing tests conducted at the Liaohe Gas Storage Group, a cross-validated analytical framework was established, integrating the square-root-of-time, Geomechanical (G) function, and flow-back pressure–volume methods. This framework enables precise determination of the dynamic maximum safe pressure, effectively balancing storage efficiency against the risks of fracture and fault activation. The results indicate that the minimum horizontal stress is 37% higher in the caprock than in the reservoir, confirming the integrity of the natural stress barrier. A mere 0.39% discrepancy in interpretation results validates the consistency of the methodology. The derived three-dimensional (D) in situ stress model reveals that the upper sandstone section exhibits 15–20% higher horizontal stress than deeper intervals, acting as a secondary barrier against fracture propagation. Theoretically, we propose a ‘stress differential gradient sealing’ mechanism to explain the buffering effects observed in the sandstone–mudstone transition zone. Practically, we developed a standardized testing protocol for complex geological conditions, which achieved a 15% increase in the maximum safe operating pressure at the Liaohe facility. This study provides critical insights for optimizing gas storage operations.

Ensuring consistent quality and safety in agri-food processing is a strategic priority for firms seeking compliance with international standards such as ISO 9001 and ISO 22000. Traditional inspection practices in Ecuador’s food industry remain largely destructive, labor-intensive, and subjective, limiting real-time decision-making. This study developed a non-destructive, ISO-aligned framework for process-level quality control by integrating digital (RGB) imaging for surface-level inspection, hyperspectral imaging (HSI) for internal-quality prediction (e.g., moisture, firmness, and freshness), near-infrared spectroscopy (NIRS) for compositional and authenticity analysis, and deep learning (DL) models for automated classification of ripeness, maturity, and defects. Experimental results across four flagship commodities—bananas, cacao, coffee, and shrimp—achieved classification accuracies above 88% and ROC AUC values exceeding 0.90, confirming the robustness of AI-driven, multimodal (RGB–HSI–NIRS) inspection under semi-industrial conveyor conditions. Beyond technological performance, the findings demonstrate that digital inspection reinforces ISO principles of evidence-based decision-making, conformity verification, and traceability, thereby operationalizing the Plan–Do–Check–Act (PDCA) cycle at digital speed. The study contributes theoretically by advancing the conceptualization of Quality 4.0 as a socio-technical transformation that embeds AI-driven sensing and analytics within management standards, and practically by providing a roadmap for Ecuadorian SMEs to strengthen export competitiveness through automated, real-time, and auditable quality assurance.