Oil Fire Radiation Calculation Based on a Statistical Narrow-Band Model
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摘要: 近年来油料火灾污染事故频发危害性极大，通过分析光谱特性来提取火灾信息已成为研究油料火灾事故的重要途径。目前国内外学者已建立了多种气体辐射和炭黑辐射的模型对燃料燃烧进行研究，但少有对火焰光谱进行建模深入分析燃烧污染产物光谱特征信息。本文搭建了油料火焰光谱测试平台，测量了单一尺度下酒精、92号汽油、95号汽油和0号柴油的火焰光谱，以及多尺度下0号柴油的火焰光谱。实验结果表明3种油料的火焰光谱相似，随着尺度的增大辐射亮度呈非线性增大。基于统计窄谱带法（statistical narrow band，SNB）构建了油料火焰光谱辐射模型，通过实验数据验证曲线拟合度达0.895。利用该光谱辐射模型计算出油料火焰大尺度下的平均辐射亮度与平均透过率、不同烟气浓度下的平均透过率，能为遥感探测火灾污染及反演污染物浓度提供帮助。Abstract: In recent years, oil fire pollution accidents have occurred frequently and caused significant harm. It has become important to study oil fire accidents by extracting fire information through the analysis of spectral characteristics. Many domestic and foreign scholars have established a variety of gas radiation and carbon black radiation models to study fuel combustion; however, few scholars have directly modeled flame spectra to analyze and extract spectral characteristic information on combustion pollution products. In this study, a test platform for the flame spectra of oil was constructed, and the flame spectra of alcohol, 92 gasoline, 95 gasoline, and 0 diesel were measured at a single scale, as was the flame spectra of 0 diesel at multiple scales. The experimental results demonstrate that the flame spectra of the three oils are similar and the radiance increases nonlinearly with an increase in scale. Based on the statistical narrow-band method, a spectral radiation model for the oil flame was established, and a curve fitting degree of 0.895 was obtained based on experimental data. The spectral radiation model can be used to calculate the average radiance and transmittance of oil flames on a large scale, as well as the average transmittance at different flue gas concentrations, which can be helpful for remote fire pollution detection and pollutant concentration inversion.
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Key words:
- infrared radiation spectrum /
- oil flame /
- narrow band /
- soot radiation /
- numerical simulation
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图 3 6 cm尺度下柴油、92号汽油、95号汽油火焰光谱对比
Figure 3. Flame spectral comparison of diesel oil, No. 92 gasoline and No. 95 gasoline at the scale of 6cm
图 4 6 cm、14 cm、18 cm和22 cm四种尺度下柴油火焰光谱对比
Figure 4. Spectral comparison of diesel flame at 6 cm, 14 cm, 18 cm and 22 cm scales
图 5 柴油火焰光谱实测值与SNB模拟值对比
Figure 5. Comparison of measured values of diesel flame spectrum with simulated values of SNB
图 6 实验数据、逐线法模拟值、SNB模拟值对比
Figure 6. Comparison of experimental data, line by line simulation value and SNB simulation value
图 7 SNB模拟不同燃烧尺度、不同烟气浓度下火焰平均透过率
Figure 7. SNB simulates average flame transmittance at different combustion scales and flue gas concentrations
图 8 SNB模拟不同尺度下火焰光谱辐射亮度
Figure 8. SNB simulates flame spectral luminance at different scales
表 1 92号汽油，95号汽油，0号柴油，酒精燃烧60 s时的组分体积分数与温度
Table 1. Volume fraction and temperature of gasoline 92, gasoline 95, diesel 0, alcohol in 60 s combustion
Type 92#gasoline 95#gasoline 0#diesel Alcohol CO 0.0067% 0.0066% 0.0074% 0.0047% CO2 0.0821% 0.0892% 0.0854% 0.0823% T/K 1155 1165 1202 977 
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表 2 LBL, SNB和实验数据在2.5 μm, 2.7 μm, 4.3 μm, 5.5 μm，6.3 μm特征峰处辐射亮度比较
Table 2. LBL, SNB and experimental data were compared at characteristic peaks of 2.5, 2.7, 4.3, 5.5, 6.3 μm
Spectral radiance/(W·cm－2·μm－1·sr－1) 2.5 μm 2.7 μm 4.3 μm 5.5 μm 6.3 μm LBL 0.1236 0.2358 0.2936 0.0261 0.0142 SNB 0.1194 0.2245 0.2956 0.0381 0.0206 Experiment 0.1466 0.1976 0.3001 0.0299 0.0178
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表 3 SNB, LBL拟合评价指标分析
Table 3. Analysis of SNB and LBL fitting evaluation indexes
Evaluation RMSE MAE R2 LBL-experiment 0.0113 0.00769 0.9486 SNB-experiment 0.0162 0.0109 0.8950 SNB-LBL 0.0215 0.0129 0.7760
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