Design and Uniformity Analysis of Fully Premixed Natural Gas Burner Venturi Mixer

Zhenglu, Sun; Yongtang, Wang; Li, Hong; Dong, Aihua; Yunxin, Shi; Yu, Bin

doi:10.1088/1757-899x/721/1/012009

Cited by 4 publications

(5 citation statements)

References 1 publication

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“…The local resistance loss is mainly caused by collision and vortex. In the calculation process, the resistance in the expanding area of the inlet section, the resistance in the shrinking area of the outlet section and the resistance of the spiral blade are primarily considered [22]. The uniformity U of the gas-mixing device is calculated by the following formula:…”

Section: Digital Analog Modelmentioning

confidence: 99%

Numerical Simulation and Experimental Analysis of Dynamic Continuous Operation of Low-Concentration Coalbed-Methane-Mixing Device

2022

Processes

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The concentration of low-concentration coalbed methane extracted from underground coal mine fluctuates greatly, which does not meet the requirements of intake concentration of coalbed-methane utilization devices. Due to this fluctuation, the coalbed-methane-utilization device cannot maintain stable and safe operation. The gas-mixing device is mainly used in coalbed-methane-utilization systems, providing each with a stable feed gas source with qualified concentration. In order to solve the problems of unsatisfactory uniformity of gas mixing and the large resistance of the existing coalbed-methane-mixing device, the mathematical model of the internal flow of the gas-mixing device is established. The influence of the internal structure of the gas-mixing device on the change in the uniformity of gas mixing and resistance loss is studied by numerical simulation and experiment. When the flow is 7000 Nm3/h, 50,000 Nm3/h and 160,000 Nm3/h, respectively, the spiral structure combination of L-N-R, N-L-R and L-N-R is optimal (L, R, N indicate left rotation, right rotation and without setting screw, respectively). There are some defects in the processing technology of the experimental device, which make the simulation and experimental data different. The numerical simulation of the gas-mixing process inside the unit can provide technical means for reducing resistance and improving the uniformity of gas mixing, and provide a stable gas source and safety measures for the coalbed-methane-utilization unit.

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Section: Digital Analog Modelmentioning

confidence: 99%

Numerical Simulation and Experimental Analysis of Dynamic Continuous Operation of Low-Concentration Coalbed-Methane-Mixing Device

2022

Processes

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“…The experimental measured value is the pressure difference between the inlet and outlet sections of the gas mixing installation value, which is collected by the differential pressure transmitter. In the calculation, the resistance of the unit includes local resistance loss and resistance loss along the path, among which the local resistance loss is mainly caused by collision and vortex, and the resistance of the expanding area of the inlet section, the shrinking area of the outlet section, and the resistance of the spiral blade are mainly considered in the calculation process [28]. The resistance ΔP is calculated by the following formula:…”

Section: Mathematical Modelmentioning

confidence: 99%

Optimization Analysis of Pretreatment Device Structural Parameters for Low-Concentration CBM Utilization

2022

Geofluids

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The unstable concentration of the difficulty in utilizing low-concentration CBM causes a large amount of CBM to be discharged into the atmosphere. In order to ensure the safe and stable operation of the CBM utilization device, the gas mixing unit is used to stabilize the concentration of feed gas. Generally, the resistance of the gas mixing unit is not higher than 500 Pa and the uniformity of gas is not less than 90%. In order to solve the problems of heavy resistance and low uniformity of the existing CBM mixing unit, a three-dimensional calculation model is established, and the structural parameters such as the number of spiral blades, blade length, and pitch in the gas mixing unit are adjusted and verified by experiments to achieve optimal performance. The dimensionless mathematical correlation between the resistance loss and the uniformity of gas is refined, and the maximum error between the resistance loss and the simulation results is controlled within 10%; it provides a theoretical basis for the uniformity and low resistance mixing of different gases in the gas industry. When the flow is 7000 Nm3/h, 50000 Nm3/h, and 160000 Nm3/h, respectively, the optimal structural parameters of the mixing zone are as follows: the number of blades is 3, 3, and 2, respectively, the pitch is 1000 mm, 2000 mm, and 2636 mm, respectively, and the length of blades is 500 mm, 1600 mm, and 1845 mm, respectively. The optimal structural parameters of the small pipe area are as follows: the mixing device with a flow of 50000 Nm3/h is not equipped with blades, the number of blades of the other two devices is 4, the pitch is 1400 mm, and the length of blades is 700 mm.

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“…The architecture of the D 3 -CNN model is depicted in Table 2. Validation of the D 3 -CNN investigates the actual diffusion activity functions in the prediction of the D 3 -CNN model and the ADD that depicts a comparison of the actual diffusion activity functions for the testing samples with vacancies of sizes 0.42 to 0.81 as predicted by the model, the ADD, the experimental results in [22], and the model presented in [17]. The actual diffusion activity value of vacancy defect substances grows linearly with the increase in the number of defects.…”

Section: The Verification Of the D 3 -Cnn Modelmentioning

confidence: 99%

“…The published research on diffusion prediction of vacancy defect substances is mostly in two-dimensional structures. For instance, the authors in [22] predicted the operative heat conductivity of vacancy defect substances using geometrical 2D images employing intelligent learning models. They established models that can attain operative heat conductivity of vacancy defect substances.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Model for Prediction of Diffusion in Defect Substances

AlArfaj

Mahmoud

2022

Processes

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Actual diffusion activity function is an important metric utilized to describe the diffusion activities of a vacancy defect substance. In this paper, we propose a deep learning three-dimensional convolutional CNN model (D3-CNN). A 3D convolution has its kernel slides in three dimensions as opposed to two dimensions with 2D convolutions. 3D convolution is more suitable for three-dimensional data. We also propose an amplification learning technique to predict the actual diffusion activity of a vacancy defect substance, which is impacted by the geometrical parameters of the defect substance and the vacancy distribution function. In this model, the geometric parameters of a three-dimensional constructed vacancy defect substance are generated. The 3D dataset is obtained by the atoms diffusion defect (ADD) simulation model. The geometric parameters of the 3D vacancy defect substance are computed by the proposed amplification technique. The 3D geometric parameters and the diffusion activity values are applied to a deep learning model for training. The actual diffusion activity values of a substance with a vacancy size ranging from size 0.52 mm to 0.61 mm are used for training, and the actual diffusion activity values of substance vacancy of size between 0.41 and 1.01 are classified by the three-dimensional network. The model can realize high speed and accuracy for the actual diffusion activity value. The mean relative absolute errors between the D3-CNN and the ADD models are 0.028–7.85% with a vacancy size of 0.41 to 0.81. For a usual sample with a vacancy of size equal to 0.6, the CPU computation load required by our model is 14.2 × 10−2 h, while the time required is 15.16 h for the ADD model. These results indicate that our proposed deep learning model has a strong learning capability and can function as an influential model to classify the diffusion activity of compound vacancy defect substances.

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Design and Uniformity Analysis of Fully Premixed Natural Gas Burner Venturi Mixer

Cited by 4 publications

References 1 publication

Numerical Simulation and Experimental Analysis of Dynamic Continuous Operation of Low-Concentration Coalbed-Methane-Mixing Device

Numerical Simulation and Experimental Analysis of Dynamic Continuous Operation of Low-Concentration Coalbed-Methane-Mixing Device

Optimization Analysis of Pretreatment Device Structural Parameters for Low-Concentration CBM Utilization

Deep Learning Model for Prediction of Diffusion in Defect Substances

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