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Guang Zhang
School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, China

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Article
Published: 07 July 2021 in Fire Technology
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Water mist is considered as a potential alternative to halon in fire extinguishing applications. However, penetration is remarkably reduced due to the rapid decay of momentum in the process of water mist movement, which makes it difficult for water mist to reach the flame zone to extinguish the fire. To effectively improve the momentum of the water mist, a novel water mist system namely co-flow jet water mist system was proposed. A configuration in which a co-flow jet was induced to control the motion of water mist. A three-dimensional simulation was performed on the gas–liquid flow in this system. The Realizable k-ε model coupled with the discrete phase model (DPM) was employed for high-speed co-flow jet and laden droplets respectively. Simulations were focused on the interaction of the gas–liquid phase. It was found that the potential core length of the co-flow jet was increased owing to the injection of droplets, but the turbulence intensity and the attenuation of the axial velocity of the co-flow jet were reduced by the broken droplets. In addition, the droplets produced by the atomizer were broken into uniform small ones under the action of co-flow jet, and the spatial distribution of droplets was also changed, more importantly, the momentum of droplets was increased effectively. The droplet size as well as spatial distribution and momentum was related to the gas–liquid mass ratio (GLR). The GLR should be increased as much as possible to enhance the performance of the co-flow jet once the required concentration to extinguish a fire is achieved. This technique is helpful to the popularization and application of a water mist system.

ACS Style

Mingli He; Guang Zhang; Shaohua Hu; Cheng Wang. Assessment of a Method to Enhance the Momentum of Water Mist: Co-Flow Jet Water Mist System. Fire Technology 2021, 1 -21.

AMA Style

Mingli He, Guang Zhang, Shaohua Hu, Cheng Wang. Assessment of a Method to Enhance the Momentum of Water Mist: Co-Flow Jet Water Mist System. Fire Technology. 2021; ():1-21.

Chicago/Turabian Style

Mingli He; Guang Zhang; Shaohua Hu; Cheng Wang. 2021. "Assessment of a Method to Enhance the Momentum of Water Mist: Co-Flow Jet Water Mist System." Fire Technology , no. : 1-21.

Journal article
Published: 07 January 2019 in Energies
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Due to high water pressure in the concrete reinforced hydraulic tunnels, surrounding rocks are confronted with nonlinear seepage problem in the pumped storage power station. In this study, to conduct nonlinear seepage numerical simulation, a nonlinear seepage numerical model combining the Forchheimer nonlinear flow theory, the discrete variational inequality formulation of Signorini’s type and an adaptive penalized Heaviside function is established. This numerical seepage model is employed to the seepage analysis of the hydraulic tunnel surrounding rocks in the Yangjiang pumped-storage power station, which is the highest water pressure tunnel under construction in China. Moreover, the permeability of the surrounding rocks under high water pressure is determined by high pressure packer test and its approximate analytical model. It is shown that the flow in the surrounding rocks is particularly prone to become nonlinear as a result of the high flow velocities and hydraulic gradients in the nearby of the seepage-control measures and the high permeability fault. The nonlinear flow theory generates smaller flow rate than the Darcy flow theory. With the increase of nonlinear flow, this observation would become more remarkable.

ACS Style

Shaohua Hu; Xinlong Zhou; Yi Luo; Guang Zhang. Numerical Simulation Three-Dimensional Nonlinear Seepage in a Pumped-Storage Power Station: Case Study. Energies 2019, 12, 180 .

AMA Style

Shaohua Hu, Xinlong Zhou, Yi Luo, Guang Zhang. Numerical Simulation Three-Dimensional Nonlinear Seepage in a Pumped-Storage Power Station: Case Study. Energies. 2019; 12 (1):180.

Chicago/Turabian Style

Shaohua Hu; Xinlong Zhou; Yi Luo; Guang Zhang. 2019. "Numerical Simulation Three-Dimensional Nonlinear Seepage in a Pumped-Storage Power Station: Case Study." Energies 12, no. 1: 180.

Journal article
Published: 05 September 2017 in RSC Advances
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Rockburst proneness was greater when the change of correlation dimensions exceeded 40%. In order to strengthen the forecasting of rockburst in underground engineering, the fractal characteristics of the rockburst proneness of rock were studied in this paper. The fractal characteristics of rock surface and acoustic emission were analyzed based on four types of rocks by uniaxial compression testing. The changes in fractal characteristics among the different types of rock were compared by calculating the geometric dimension and acoustic emission dimension. Results showed that the rock with stronger rockburst proneness had more intensive failure in the loading process.

ACS Style

Li Mo-Xiao; Song Ying-Hua; Zhang Guang. Study on the fractal characteristics of rock in the prediction of rockburst. RSC Advances 2017, 7, 43073 -43082.

AMA Style

Li Mo-Xiao, Song Ying-Hua, Zhang Guang. Study on the fractal characteristics of rock in the prediction of rockburst. RSC Advances. 2017; 7 (68):43073-43082.

Chicago/Turabian Style

Li Mo-Xiao; Song Ying-Hua; Zhang Guang. 2017. "Study on the fractal characteristics of rock in the prediction of rockburst." RSC Advances 7, no. 68: 43073-43082.

Journal article
Published: 05 April 2016 in Journal of the Indian Society of Remote Sensing
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Extraction of the magnitude and direction of deformation is an important issue. Deformation is typically extracted by comparing data related to a finite number of control point. However, such a method can only extract the magnitude of deformation, but not the direction of deformation. In this paper, the improved ICP model is exploited for extracting the deformation. The main idea of this method is the construction of improved ICP and the determination of the relationship between extraction of six deformation parameters and local matching. This proposed deformation extraction method is particularly suited for scenarios where the deformation area is 3D rigid-body. The performance of the proposed method is extensively evaluated numerically and experimentally according to the 3D rigid-body board deformation. It is important to note that the conclusions were achieved under non-ideal conditions, e.g. using non-calibrated TLS point cloud and non-special targets. Besides the simulation experiment, the validation results achieved on bridge test site are briefly discussed.

ACS Style

Xijiang Chen; Guang Zhang; Xianghong Hua; Hao Wu; Wei Xuan. Extracting of six Deformation Parameters Using Improved ICP Matching Based on Terrestrial Laser Scanning Data. Journal of the Indian Society of Remote Sensing 2016, 45, 123 -130.

AMA Style

Xijiang Chen, Guang Zhang, Xianghong Hua, Hao Wu, Wei Xuan. Extracting of six Deformation Parameters Using Improved ICP Matching Based on Terrestrial Laser Scanning Data. Journal of the Indian Society of Remote Sensing. 2016; 45 (1):123-130.

Chicago/Turabian Style

Xijiang Chen; Guang Zhang; Xianghong Hua; Hao Wu; Wei Xuan. 2016. "Extracting of six Deformation Parameters Using Improved ICP Matching Based on Terrestrial Laser Scanning Data." Journal of the Indian Society of Remote Sensing 45, no. 1: 123-130.

Journal article
Published: 04 January 2015 in Rare Metals
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In order to predict the wearing of stellite alloys, the related methods of rare metals data processing were discussed. The method of opposite degree (OD) algorithm was put forward to predict the wearing of stellite alloys. OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation (BP) and radial basis function (RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.

ACS Style

Xiao-Guang Yue; Guang Zhang; Qu Wu; Fei Li; Xian-Feng Chen; Gao-Feng Ren; Mei Li. Wearing prediction of stellite alloys based on opposite degree algorithm. Rare Metals 2015, 34, 125 -132.

AMA Style

Xiao-Guang Yue, Guang Zhang, Qu Wu, Fei Li, Xian-Feng Chen, Gao-Feng Ren, Mei Li. Wearing prediction of stellite alloys based on opposite degree algorithm. Rare Metals. 2015; 34 (2):125-132.

Chicago/Turabian Style

Xiao-Guang Yue; Guang Zhang; Qu Wu; Fei Li; Xian-Feng Chen; Gao-Feng Ren; Mei Li. 2015. "Wearing prediction of stellite alloys based on opposite degree algorithm." Rare Metals 34, no. 2: 125-132.