The cooling performance of halogenated alkane fire extinguishing agent and its quantitative prediction model

Author(s):  
Wei Ke ◽  
Kai Wang ◽  
Biao Zhou ◽  
Zhengyang Wang ◽  
Wei Wang ◽  
...  
Author(s):  
Osamu Suzuki ◽  
Atsuo Nishihara

A novel electronics cooling system that uses water heat pipes under an ambient temperature range from −30°C to 40°C has been developed. The system consists of several water heat pipes, air-cooled fins, and a metal block. The heat pipes are separated into two groups according to the thermal resistance of their fins. One set of heat pipes, which have fins with higher thermal resistance, operates under an ambient temperature range from −30°C to 40°C. The other set, which have lower resistance, operates from 0°C to 40°C. A prediction model based on the frozen-startup limitation of a single heat pipe was first devised and experimentally verified. Then, a prediction model for the whole-system was formulated according to the former model. The whole-system model was used to design a prototype cooling system, and it was confirmed that the prototype has a suitable cooling performance for an environmentally friendly electronics cooling system.


Author(s):  
Liming Dai ◽  
Huay Seen Lee

A Highway Prediction Model (HPM) using the ray acoustics modeling approach is developed in this research. The HPM model can be used to quantitatively predict the environmental noise levels on highways of different pavements. Comparison between the measured noise levels using the SPB method and predicted noise levels with the model developed shows that the prediction model established is reliable for estimating highway noise in Canada.


2012 ◽  
Vol 166-169 ◽  
pp. 2309-2314
Author(s):  
Wu Sheng Hu ◽  
Hao Wang ◽  
Hong Lin Nie

A method which gives the quantitative prediction for earthquake magnitude is proposed in this paper. By this method, after calculating the earthquake parameters and the astronomical time-varying parameters, an earthquake prediction model can be established to gives the quantitative prediction for earthquake magnitude in the future prediction period. In this research, the research object was the experimental areas, the prediction period was 6 months, and Linear Regression analysis and conventional BP (Back Propagation) Neural Network were used respectively in prediction. Through backtracking test, the RMSEs(root mean square error) of earthquake magnitude prediction are ±0.78 ML and ±0.61 ML. Then after summarizing the advantages and disadvantages of the two methods, an integrated model based on linear regression and neural network was proposed. Through backtracking test, the RMSE of earthquake magnitude prediction reaches ± 0.41 ML, results improving significantly.


Author(s):  
Youpeng Huangfu ◽  
Shuhong Wang ◽  
Shuli Yin

This paper presents a quantitative prediction model of conducted electromagnetic emissions (EME) for a variable frequency drive (VFD) motor system based on the macro-modeling approach. This model relies on the effective representations of the frequency dependent characteristics of the parasitic behaviors between converter arms and heatsink, of shielded power cable, and of motor windings. The frequency dependent performances between converter arms and heatsink, and of the motor windings are obtained by processing measurement data. Then the vector fitting method (VFM) with passivity enforcement and circuit synthesis method are adopted to obtain the corresponding equivalent circuits. The equivalent circuit implementation of shielded power cable is achieved by applying a node-to-node admittance functions (NAFs) model, which considers the propagation phenomenon and frequency dependent losses accurately. The conducted EME model is compatible with commonly used transient circuit solvers since it only includes constant circuit elements. The conducted emissions of the VFD system are then evaluated by analyzing the common mode (CM) and differential mode (DM) voltages and currents.


Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2509
Author(s):  
Nguyen Xuan Quy ◽  
Takumi Noguchi ◽  
Seunghyun Na ◽  
Jihoon Kim ◽  
Yukio Hama

This paper presents a prediction method and mathematical model based on experimental results for the change in pore structure of cement-based materials due to environmental conditions. It focuses on frost damage risk to cement-based materials such as mortar. Mortar specimens are prepared using water, ordinary Portland cement, and sand and the pore structure is evaluated using mercury intrusion porosimetry. New formulas are proposed to describe the relationship between the pore structure change and the modified maturity and to predict the durability factor. A quantitative prediction model is established from a modified maturity function considering the influences of environmental factors like temperature and relative humidity. With this model, the frost resistance of cement-based materials can be predicted based on weather data. Using the prediction model and climate data, a new distribution map of frost damage risk is created. It is found that summer weather significantly affects frost resistance, owing to the change in pore structure of cement-based mortar. The model provides a valuable tool for predicting frost damage risk based on weather data and is significant for further research.


2015 ◽  
Vol 1092-1093 ◽  
pp. 1440-1443
Author(s):  
Wei Huang ◽  
Xiao Li Zhang ◽  
Xi Zheng ◽  
Gao Run Zhong

Using the acoustictime logging data to establish reasonable and effective porosity parameter quantitative prediction model, can predict quality reservoir and favorable petroliferous province. Chang 6 formation in Hejiaji area is taken as an example to studing the reservoir physical properties and logging response characteristics, and the acoustictime logging and core analysis porosity are used to set up porosity logging interpretation model, then acculate porosity according to the model. The results show that after the core place treatment, the porosity quantitative prediction model established by acoustictime and layer point analysis porosity has high precision. To verify the porosity logging interpretation model of the calculated porosity and core analysis porosity, the application effect is good.


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