In the steelmaking industry,enhancing production cost-effectiveness and operational efficiency requires the integration of intelligent systems to support production activities.Thus,effectively integrating various prod...In the steelmaking industry,enhancing production cost-effectiveness and operational efficiency requires the integration of intelligent systems to support production activities.Thus,effectively integrating various production modules is crucial to enable collaborative operations throughout the entire production chain,reducing management costs and complexities.This paper proposes,for the first time,the integration of Vision-Language Model(VLM)and Large Language Model(LLM)technologies in the steel manufacturing domain,creating a novel steelmaking process management system.The system facilitates data collection,analysis,visualization,and intelligent dialogue for the steelmaking process.The VLM module provides textual descriptions for slab defect detection,while LLM technology supports the analysis of production data and intelligent question-answering.The feasibility,superiority,and effectiveness of the system are demonstrated through production data and comparative experiments.The system has significantly lowered costs and enhanced operational understanding,marking a critical step toward intelligent and cost-effective management in the steelmaking domain.展开更多
Washing is a promising method for separating contaminants bound to the particles of soil ex-situ by chemical mobilization. Laboratory batch washing experi- ments were conducted using deionized water and varying concen...Washing is a promising method for separating contaminants bound to the particles of soil ex-situ by chemical mobilization. Laboratory batch washing experi- ments were conducted using deionized water and varying concentrations of oxalic acid, citric acid, tartaric acid, acetic acid, hydrochloric acid and ethylenediaminetetra acetic acid （EDTA） to assess the efficiency of using these chemicals as washing agents and to clean up heavy metals from two heavily polluted soils from an iron and streel smelting site. The toxicity reduction index and remediation costs were analyzed, and the results showed that the soils were polluted with Cd, Pb and Zn. Hydrochloric acid and EDTA were more efficient than the other washing agents in the remediation of the test soils. The maximum total toxicity reduction index showed that 0.5 mol·L^-1 hydro- chloric acid could achieve the remediation with the lowest costs.展开更多
文摘In the steelmaking industry,enhancing production cost-effectiveness and operational efficiency requires the integration of intelligent systems to support production activities.Thus,effectively integrating various production modules is crucial to enable collaborative operations throughout the entire production chain,reducing management costs and complexities.This paper proposes,for the first time,the integration of Vision-Language Model(VLM)and Large Language Model(LLM)technologies in the steel manufacturing domain,creating a novel steelmaking process management system.The system facilitates data collection,analysis,visualization,and intelligent dialogue for the steelmaking process.The VLM module provides textual descriptions for slab defect detection,while LLM technology supports the analysis of production data and intelligent question-answering.The feasibility,superiority,and effectiveness of the system are demonstrated through production data and comparative experiments.The system has significantly lowered costs and enhanced operational understanding,marking a critical step toward intelligent and cost-effective management in the steelmaking domain.
文摘Washing is a promising method for separating contaminants bound to the particles of soil ex-situ by chemical mobilization. Laboratory batch washing experi- ments were conducted using deionized water and varying concentrations of oxalic acid, citric acid, tartaric acid, acetic acid, hydrochloric acid and ethylenediaminetetra acetic acid （EDTA） to assess the efficiency of using these chemicals as washing agents and to clean up heavy metals from two heavily polluted soils from an iron and streel smelting site. The toxicity reduction index and remediation costs were analyzed, and the results showed that the soils were polluted with Cd, Pb and Zn. Hydrochloric acid and EDTA were more efficient than the other washing agents in the remediation of the test soils. The maximum total toxicity reduction index showed that 0.5 mol·L^-1 hydro- chloric acid could achieve the remediation with the lowest costs.
