2 results about "Chemical risk" patented technology

This invention discloses a method for assessing the risk of heavy metal contamination in soil of newly constructed reservoir areas through multi-scenario coupling simulation. The method includes the following steps: selecting soil samples with the highest content of the target heavy metal in the reservoir area for Al content detection and heavy metal speciation analysis; collecting background control samples from areas far from the reservoir area for heavy metal and Al content detection and heavy metal speciation analysis; calculating enrichment factors and geoaccumulation indices to determine pollution sources at sampling points; preparing average and extreme samples; preparing simulated reservoir water; and conducting static leaching experiments, dynamic disturbance experiments, and vertical leaching experiments, covering chemical risks during quiescent periods, physical risks during disturbance periods, and long-term infiltration geological risks. This invention not only couples multiple scenarios and simulates the most unfavorable conditions to accurately identify the maximum instantaneous risk of heavy metal release, but also quantifies and determines pollution sources, possessing source tracing capabilities.

This invention provides a method, medium, and system for establishing a gridded hazardous chemicals knowledge base, belonging to the technical field of knowledge base establishment methods. First, data is collected and high-quality data is filtered through a recognition index. Then, an accuracy evaluation model is constructed to automatically label various types of knowledge and form a knowledge association matrix to quantify the association strength. Next, a gridded knowledge mapping structure is established, knowledge grid units are divided, and grid centrality is calculated to determine the weight of knowledge points. Subsequently, a minimum spanning tree is automatically constructed to handle knowledge conflicts, and a matrix completion algorithm is applied to handle defective knowledge. Then, a chemical risk association network is constructed, and a hazardous chemicals grid index is calculated to quantify the hazard level. Next, a knowledge reasoning mechanism is designed, and a grid knowledge compression function is used to handle excessively long knowledge. Finally, an adaptive optimization algorithm is implemented to dynamically adjust the grid structure, forming a gridded hazardous chemicals knowledge base that reduces manual dependence and enhances the expression of associations.