Abstract: A method for preparing a supercritical fluid by deep-sea pressure is provided and belongs to the technical field of supercritical fluid preparation. The method includes the following steps of: placing a low-pressure fluid in a closed flexible container, sending the closed flexible container down to a location of a sea at a depth where a seawater pressure meets a requirement by using a powered or unpowered traction device, leaving the flexible container standing still until a volume of the flexible container does not change, wrapping the closed flexible container with a rigid pressure-bearing container, transferring the closed flexible container to the sea surface by the powered or unpowered traction device, and taking out the fluid in the flexible container as supercritical fluid. Then the supercritical fluid is produced. Therefore, the process of preparing supercritical (high pressure) liquid in the deep-sea is safer and more stable than the preparation way on land.

Abstract: The present disclosure provides a treatment method for oily sludge and a method for soil remediation. The treatment method for oily sludge includes: mixing the oily sludge with target biochar uniformly according to a first preset mass ratio, and conducting catalytic pyrolysis at a first preset temperature to achieve efficient removal of petroleum hydrocarbons, to obtain a pyrolysis residue used for soil remediation. In the present disclosure, the method realizes resource utilization and harmless utilization of the pyrolysis residue.

Abstract: Disclosed is an optimizing method for multi-source municipal solid waste combinations based on machine learning, including obtaining relevant property data, classifying the feature variables and obtaining a raw materials pre-combination from the classified feature variables according to a classification ratio, followed by cooperative combustion treatment to obtain data after combustion, summarizing the obtained data into a database, constructing a matrix of raw material components, operating conditions and pollutant distribution according to the database, obtaining matrix data; performing principal component analysis on the matrix data, constructing an information processing model, obtaining a data set of samples; carrying out training according to the data set to construct a relational model, obtaining processed parameters; training the obtained processed parameters to construct a regression module, an optimal parameter, and performing regression calculation using the optimal parameter together with the matr