Abstract: A simulation analysis system for dioxin concentration in furnace of municipal solid waste incineration process includes an area division module, the area division module is connected with a numerical simulation module, the numerical simulation module is connected with a single-factor analysis module, the single-factor analysis module includes an orthogonal test analysis module, and the orthogonal test analysis module is connected with a control module; the area division module is used for dividing areas in the incinerator, the numerical simulation module is used for conducting modeling simulation on the divided areas, the single-factor analysis module is used for conducting single-factor analysis according to the output of the numerical simulation module, and the orthogonal test analysis module is used for conducting orthogonal test analysis according to the output of the numerical simulation module.

Abstract: A method for separating oil-water two-phase NMR signals by using dynamic nuclear polarization comprising: using a combination of a non-selective free radical and a selective relaxation reagent to selectively enhance an NMR signal of an oil phase or a water phase, the relaxation reagent being capable of selectively suppressing dynamic polarization enhancement of the water phase or oil phase, thus achieving the polarization enhancement of a single fluid phase in the mixed fluid phases and realizing separation of the two-phase signals; or using a selective free radical to selectively enhance the NMR signal of the oil phase or the water phase, thus achieving the polarization enhancement of a single fluid phase in the mixed fluid phases and realizing separation of the oil-water two-phase NMR signals. The method is simple and easy to operate, has a short test time, and can efficiently separate NMR signals of oil and water phases.

Abstract: A method for measuring oil-water distribution using DNP-MRI, comprising adding a free radical for DNP enhanced NMR signal of a water phase or an oil phase in a sample containing oil and water; performing an MRI experiment on the sample, and collecting an MRI image of the sample without DNP enhancement; applying microwave excitation for DNP-MRI experiment under the same MRI experiment condition as step 2, and collecting an MRI image of the sample after DNP enhancement; and comparing the MRI image after DNP enhancement with the MRI image without DNP enhancement. In the MRI image with DNP enhancement, an area with enhanced MRI signal intensity is a selectively enhanced fluid phase distribution area, and an area without obviously changed MRI signal intensity is a non-selectively enhanced fluid phase distribution area. The method is simple, convenient to operate, short in measurement time, and high in measurement efficiency.

Abstract: An NMR relaxation time inversion method based on an unsupervised neural network includes simulating inversion kernel matrix, simulating continuous NMR relaxation time spectrum, simulating noise, calculating NMR relaxation signals as samples, various samples forming a sample set, constructing an unsupervised neural network model, and defining a loss function of the unsupervised neural network model; and taking the samples in the training sample set as an input of the unsupervised neural network model, to obtain an optimal mapping relationship between the NMR relaxation signals and the NMR relaxation time spectrum with a minimum loss function. The present invention provides the possibility of using experimental data as the sample for training since the trading sample does not need to be labeled, can automatically learn the optimal regularization parameters without depending on the initial value and manual experience, and predicts fast.

Abstract: An NMR relaxation time inversion method based on an unsupervised neural network includes simulating inversion kernel matrix, simulating continuous NMR relaxation time spectrum, simulating noise, calculating NMR relaxation signals as samples, various samples forming a sample set, constructing an unsupervised neural network model, and defining a loss function of the unsupervised neural network model; and taking the samples in the training sample set as an input of the unsupervised neural network model, to obtain an optimal mapping relationship between the NMR relaxation signals and the NMR relaxation time spectrum with a minimum loss function. The present invention provides the possibility of using experimental data as the sample for training since the trading sample does not need to be labeled, can automatically learn the optimal regularization parameters without depending on the initial value and manual experience, and predicts fast.

Abstract: A method for measuring oil-water distribution using DNP-MRI, comprising adding a free radical for DNP enhanced NMR signal of a water phase or an oil phase in a sample containing oil and water; performing an MRI experiment on the sample, and collecting an MRI image of the sample without DNP enhancement; applying microwave excitation for DNP-MRI experiment under the same MRI experiment condition as step 2, and collecting an MRI image of the sample after DNP enhancement; and comparing the MRI image after DNP enhancement with the MRI image without DNP enhancement. In the MRI image with DNP enhancement, an area with enhanced MRI signal intensity is a selectively enhanced fluid phase distribution area, and an area without obviously changed MRI signal intensity is a non-selectively enhanced fluid phase distribution area. The method is simple, convenient to operate, short in measurement time, and high in measurement efficiency.

Abstract: A method for separating oil-water two-phase NMR signals by using dynamic nuclear polarization comprising: using a combination of a non-selective free radical and a selective relaxation reagent to selectively enhance an NMR signal of an oil phase or a water phase, the relaxation reagent being capable of selectively suppressing dynamic polarization enhancement of the water phase or oil phase, thus achieving the polarization enhancement of a single fluid phase in the mixed fluid phases and realizing separation of the two-phase signals; or using a selective free radical to selectively enhance the NMR signal of the oil phase or the water phase, thus achieving the polarization enhancement of a single fluid phase in the mixed fluid phases and realizing separation of the oil-water two-phase NMR signals. The method is simple and easy to operate, has a short test time, and can efficiently separate NMR signals of oil and water phases.