Restoration effect prediction modeling method of organic polluted underground water in-situ chemical oxidation process

Abstract

The invention relates to a restoration effect prediction modeling method of an organic polluted underground water in-situ chemical oxidation process. The method specifically comprises the following steps: step 1, performing detailed investigation on the basis of a polluted site; 2, determining an in-situ chemical oxidation process of the polluted site, and determining a related parameter range; 3, using a Plackett-Burman test for determining main influence factors of the effect of the repairing technology; 4, analyzing the response of different independent parameters by using Design Expert software to obtain test combinations under different test conditions; and 5, carrying out a laboratory small-scale test based on the simulated sample, and the like. The method is simpler and more convenient, the requirement for mathematical knowledge of operators is low, data is used as a support, the statistics principle is used as a support, and the problems of model uncertainty and mathematical calculation difficulty caused by the underground complex environment are emphatically solved.

Description

technical field [0001] The invention belongs to the technical field of pollution control, and in particular relates to a repair effect prediction modeling method of an in-situ chemical oxidation process for organically polluted groundwater. Background technique [0002] Response surface analysis method, that is, Response Surface Methodology (RSM), is to use a reasonable experimental design method and obtain certain data through experiments, and use multiple quadratic regression equations to fit the functional relationship between factors and response values , through the analysis of the regression equation to seek the optimal process parameters, a statistical method to solve multivariate problems. [0003] Artificial Neural Network (ANN) is a research hotspot emerging in the field of artificial intelligence. It abstracts the human brain neuron network from the perspective of information processing, establishes a simple model, and forms different networks according to differ...

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Problems solved by technology

[0004] In the current chemical oxidation remediation project of groundwater in organically polluted sites, there are problems such as large differences in site conditions, huge differences in the diffusion of chemicals depending on the soil properties of the site, and extensive drug administration methods resulting in drug residues. There is an urgent need for the establishment of models, but most of the current numerical model establishment methods are mechanism models for the reaction process between agents and pollutants, which have practical problems such as insufficient sensitivity to specific sites, poor adaptability, and difficult practical operations. Therefore, , a method for predicting the remediation effect of in-situ chemical oxidation process for organically polluted groundwater. In the first stage, it can use response surface method and The combination of artificial neural networks achieves the purpose of quickly and accurately predicting the prospects of chemical restoration sites

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