The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform
Chengxian Du - One of the best experts on this subject based on the ideXlab platform.
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study on the critical velocity in a sloping tunnel fire under longitudinal ventilation
Applied Thermal Engineering, 2016Co-Authors: Miaocheng Weng, Xinling Lu, Chengxian DuAbstract:Abstract The critical velocity and the backlayering length of smoke in tunnel fires are the two most important parameters in longitudinal ventilation design. This paper deduced the dimensionless expression of backlayering length and critical velocity of smoke in tunnel fires using the dimensional analysis method. The sectional coefficient ζ (ζ = A/H2) was introduced to describe the Geometrical Characteristic of the tunnel section, and the Characteristic hydraulic diameter of the tunnel H ¯ replaced the tunnel height H. Then, CFD simulations were conducted in nine tunnels with different cross sectional shapes using the proprietary software Fire Dynamic Simulator (FDS), version 5.5. With the FDS simulations, prediction models for backlayering length and critical velocity modified by the sectional coefficient ζ and the tunnel slope were proposed. Meanwhile, complementary experiments were carried out in a 1/10 scale tunnel in order to provide a verification. The experimental results show a good agreement with the numerical simulations. Moreover, the prediction models for critical velocity on different slopes were compared with the prediction models proposed by others.
Miaocheng Weng - One of the best experts on this subject based on the ideXlab platform.
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study on the critical velocity in a sloping tunnel fire under longitudinal ventilation
Applied Thermal Engineering, 2016Co-Authors: Miaocheng Weng, Xinling Lu, Chengxian DuAbstract:Abstract The critical velocity and the backlayering length of smoke in tunnel fires are the two most important parameters in longitudinal ventilation design. This paper deduced the dimensionless expression of backlayering length and critical velocity of smoke in tunnel fires using the dimensional analysis method. The sectional coefficient ζ (ζ = A/H2) was introduced to describe the Geometrical Characteristic of the tunnel section, and the Characteristic hydraulic diameter of the tunnel H ¯ replaced the tunnel height H. Then, CFD simulations were conducted in nine tunnels with different cross sectional shapes using the proprietary software Fire Dynamic Simulator (FDS), version 5.5. With the FDS simulations, prediction models for backlayering length and critical velocity modified by the sectional coefficient ζ and the tunnel slope were proposed. Meanwhile, complementary experiments were carried out in a 1/10 scale tunnel in order to provide a verification. The experimental results show a good agreement with the numerical simulations. Moreover, the prediction models for critical velocity on different slopes were compared with the prediction models proposed by others.
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prediction of backlayering length and critical velocity in metro tunnel fires
Tunnelling and Underground Space Technology, 2015Co-Authors: Miaocheng Weng, Xinling Lu, Longxing YuAbstract:Abstract This paper proposes two prediction models for backlayering length and critical velocity in metro tunnel fires, in which the Characteristic hydraulic diameter of the tunnel H ¯ was introduced to describe Geometrical Characteristic of the tunnel section. The dimensional analysis method was adopted to deduce the dimensional expressions of backlayering length and critical velocity. In addition, CFD simulations were conducted in nine tunnels with different cross sectional shapes by code of FDS 5.5. Meanwhile, a 1/10 scale model tunnel was built to provide a verification by carrying out small scale experiments. The experiment result shows a good agreement to the predicted values from the CFD simulation results. Then two prediction models of backlayering length and critical velocity were obtained from the dimensional expressions and the CFD simulation results. Moreover, the comparison of the prediction for the backlayering length indicates that the prediction model by Li et al. is lower than the CFD prediction model. And the critical velocity of the Wu & Barkar model are also underestimated.
Junkui Mao - One of the best experts on this subject based on the ideXlab platform.
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a machine learning algorithm for retrieving the Geometrical Characteristic parameters of soot fractal aggregates from polarized light signal
Optik, 2021Co-Authors: Qixuan Zhao, Junkui MaoAbstract:Abstract Polarized light measurement technology is provided to study geometric Characteristics of soot fractal aggregates. The inverse problem is solved by two mature applications of machine learning, i.e. stacked ensemble model and deep network. A new Fractal Aggregates Generative Adversarial Network (FAGAN) is proposed to generate synthetic data to solve the class imbalance problem. The results show that compared with the stacked ensemble model which is sensitive to noise, the performance of the deep network is still satisfactory even under 10 % Gaussian noise, and the maximum mean absolute percentage error is not more than 3.87 %, which means that the synthetic data generated by FAGAN is very similar to the real data. As a whole, the combination of deep network and FAGAN has important guiding significance for complex and time-consuming experiments and engineering applications where noise is difficult to control or continuous and regular data cannot be obtained.
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application of the steady state and unsteady state lasers in reconstructing the Geometrical Characteristic parameters of soot fractal aggregates
Optik, 2020Co-Authors: Chuanhui Dong, Junkui MaoAbstract:Abstract The unsteady-state laser, i.e. time-domain (TD) and frequency-domain (FD) lasers, and the steady-state (SS) laser are employed as the measurement lasers to reconstruct the Geometrical Characteristic parameters of soot fractal aggregates, i.e. the root mean square radius Rg and fractal dimension Df. The direct problems are solved by the finite volume method and Rayleigh-Debye-Gans fractal aggregate method, while an improved artificial bee colony algorithm is used as the inverse problem algorithm. The sensitivity analysis is employed to study the effective sampling region of the TD and FD laser measurement signals, and the results show that the time-resolved signals selected within [L, 0.5L + ctp] for the TD laser and the dimensionless frequency selected within [0.5, 5] for the FD laser are conducive to improving the retrieval accuracy. Then, the Geometrical Characteristic parameters of soot fractal aggregates are retrieved by using different measurement lasers, and the results reveal that the retrieval accuracy can be ensured by using the TD laser measurement technique. Moreover, the retrieval accuracy and robustness of Rg are better than those of Df. All the studies in the present manuscript supply an application plat of the laser measurement techniques in reconstructing the Geometrical Characteristic parameters of soot fractal aggregates.
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determining of Geometrical Characteristic parameters of particle fractal aggregates from light scattering measurement signals
Thermal Science, 2020Co-Authors: Junkui Mao, Xingsi HanAbstract:Two kind of light scattering measurement methods, i.e. the forward light scattering measurement (FLSM) method and the angular light scattering measurement (ALSM) method, are applied to reconstruct the Geometrical morphology of particle fractal aggregates. An improved Attractive and Repulsive Particle Swarm Optimization (IARPSO) algorithm is applied to reconstruct the Geometrical structure of fractal aggregates. It has been confirmed to show better convergence properties than the original Particle Swarm Optimization (PSO) algorithm and the Attractive and Repulsive Particle Swarm Optimization (ARPSO) algorithm. Compared with the FLSM method, the ASLM method can obtain more accurate and robust results as the distribution of the fitness function value obtained by the ALSM method is more satisfactory. Meanwhile, the retrieval accuracy can be improved by increasing the number of measurement angles or the interval between adjacent measurement angles even when the random noises are added. All the conclusions have important guiding significance for the further study of the geometry reconstruction experiment of fractal aggregates.
Xinling Lu - One of the best experts on this subject based on the ideXlab platform.
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study on the critical velocity in a sloping tunnel fire under longitudinal ventilation
Applied Thermal Engineering, 2016Co-Authors: Miaocheng Weng, Xinling Lu, Chengxian DuAbstract:Abstract The critical velocity and the backlayering length of smoke in tunnel fires are the two most important parameters in longitudinal ventilation design. This paper deduced the dimensionless expression of backlayering length and critical velocity of smoke in tunnel fires using the dimensional analysis method. The sectional coefficient ζ (ζ = A/H2) was introduced to describe the Geometrical Characteristic of the tunnel section, and the Characteristic hydraulic diameter of the tunnel H ¯ replaced the tunnel height H. Then, CFD simulations were conducted in nine tunnels with different cross sectional shapes using the proprietary software Fire Dynamic Simulator (FDS), version 5.5. With the FDS simulations, prediction models for backlayering length and critical velocity modified by the sectional coefficient ζ and the tunnel slope were proposed. Meanwhile, complementary experiments were carried out in a 1/10 scale tunnel in order to provide a verification. The experimental results show a good agreement with the numerical simulations. Moreover, the prediction models for critical velocity on different slopes were compared with the prediction models proposed by others.
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prediction of backlayering length and critical velocity in metro tunnel fires
Tunnelling and Underground Space Technology, 2015Co-Authors: Miaocheng Weng, Xinling Lu, Longxing YuAbstract:Abstract This paper proposes two prediction models for backlayering length and critical velocity in metro tunnel fires, in which the Characteristic hydraulic diameter of the tunnel H ¯ was introduced to describe Geometrical Characteristic of the tunnel section. The dimensional analysis method was adopted to deduce the dimensional expressions of backlayering length and critical velocity. In addition, CFD simulations were conducted in nine tunnels with different cross sectional shapes by code of FDS 5.5. Meanwhile, a 1/10 scale model tunnel was built to provide a verification by carrying out small scale experiments. The experiment result shows a good agreement to the predicted values from the CFD simulation results. Then two prediction models of backlayering length and critical velocity were obtained from the dimensional expressions and the CFD simulation results. Moreover, the comparison of the prediction for the backlayering length indicates that the prediction model by Li et al. is lower than the CFD prediction model. And the critical velocity of the Wu & Barkar model are also underestimated.
Lin Zhang - One of the best experts on this subject based on the ideXlab platform.
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Erratum: "Simulation on the aggregation process of spherical particle confined in a spherical shell"
International Journal of Modern Physics B, 2016Co-Authors: J. Wang, J. J. Xu, Lin ZhangAbstract:The aggregation process of spherical particles confined in a spherical shell was studied by using a diffusion-limited cluster–cluster aggregation (DLCA) model. The influence of Geometrical confinement and wetting-like properties of the spherical shell walls on the particle concentration profile, aggregate structure and aggregation kinetics had been explored. The results show that there will be either depletion or absorption particles near the shell walls depending on the wall properties. It is observed that there are four different types of density distribution which can be realized by modifying the property of the inner or outer spherical shell wall. In addition, the aggregate structure will become more compact in the confined spherical shell comparing to bulk system with the same particle volume fraction. The analysis on the aggregation kinetics indicates that Geometrical confinement will promote the aggregation process by reducing the invalid movement of the small aggregates and by constraining the movement of those large aggregates. Due to the concave Geometrical Characteristic of the outer wall of the spherical shell, its effects on the aggregating kinetics and the structure of the formed aggregates are more evident than those of the inner wall. This study will provide some instructive information of controlling the density distribution of low-density porous polymer hollow spherical shells and helps to predict gel structures developed in confined geometries.
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Simulation on the aggregation process of spherical particle confined in a spherical shell
International Journal of Modern Physics B, 2016Co-Authors: J. Wang, J. J. Xu, Lin ZhangAbstract:The aggregation process of spherical particles confined in a spherical shell was studied by using a diffusion-limited cluster–cluster aggregation (DLCA) model. The influence of Geometrical confinement and wetting-like properties of the spherical shell walls on the particle concentration profile, aggregate structure and aggregation kinetics had been explored. The results show that there will be either depletion or absorption particles near the shell walls depending on the wall properties. It is observed that there are four different types of density distribution which can be realized by modifying the property of the inner or outer spherical shell wall. In addition, the aggregate structure will become more compact in the confined spherical shell comparing to bulk system with the same particle volume fraction. The analysis on the aggregation kinetics indicates that Geometrical confinement will promote the aggregation process by reducing the invalid movement of the small aggregates and by constraining the movement of those large aggregates. Due to the concave Geometrical Characteristic of the outer wall of the spherical shell, its effects on the aggregating kinetics and the structure of the formed aggregates are more evident than those of the inner wall. This study will provide some instructive information of controlling the density distribution of low-density porous polymer hollow spherical shells and helps to predict gel structures developed in confined geometries.