Computer-aided Chemical Kinetic Modeling in Near Space
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摘要:
围绕临近空间大气化学过程数值模拟计算问题，以平流层大气4个典型光化学系统为例，运用化学动理学预处理（KPP）工具，对不同复杂度的光化学反应质量平衡方程体系进行预处理，快速建立各系统化学动理学方程组的代数表示；针对模型中的大刚性ODE方程组，选取6种不同的数值计算方案（rodas，ros3，ros4，rosenbrock，sdirk，seulex） ， 实现ODE方程组的离散表示，并自动生成所需计算代码。在此基础上，开展平流层光化学过程数值模拟试验，重点考察了：各数值计算方案的计算效率和计算稳定性；各系统主要化学成分随着时间的演化规律；光化学系统复杂度对各模型主要成分变化的影响。模拟结果显示：KPP工具能有效应对临近空间大气化学反应系统复杂度的增长，缩短大气化学模型建模与检验周期，为临近空间大气化学过程研究提供有效技术支撑。
Abstract:As the typical processes in stratospheric photochemical reactions, four systems with different complicities in mass balance equations are selected as the bench mark cases, to show the efficiency and convenience for application of the Chemical Kinetics Preprocess (KPP) tool in Near Space chemical modelings. Focusing on the large rigid ODE equations in the model, six different numerical calculation schemes are selected (rodas, ros3, ros4, rosenbrock, sdirk, seulex), to realize the discrete representation of ODE equations, and automatically generate the required calculation code. On this basis, the numerical simulation experiments of stratospheric photochemical processes are carried out, focusing on: (i) the computational efficiency and stability of the numerical calculation schemes; (ii) the evolution of main chemical components of each system with time; (iii) the influence of the complexity of the photochemical system on the changes of the main components of each model. Simulation results show that the KPP tool can effectively cope with the increase of the complexity of atmospheric chemical reaction system in adjacent space, shorten the modeling and testing period of atmospheric chemical model, and provide effective technical support for the research of the atmospheric chemical process in adjacent space.
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Key words:
- Near space /
- Atmospheric chemistry /
- KPP /
- Numerical Simulation
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图 2 Chapman Ⅰ模型对比结果（rosenbrock求解器）
Figure 2. Comparison of Chapman Ⅰ model (rosenbrock)
图 3 Straro Ⅰ模型各成分体积分数变化曲线（rosenbrock求解器）
Figure 3. Volume fraction variation curve of each component in Straro Ⅰ model
图 5 模型主要成分数密度与上海站实测浓度值对比（rosenbrock求解器）
Figure 5. Comparison between the number density of major component in model and the measured concentration values in Shanghai station
表 1 平流层中的单分子、双分子和三分子光化学反应
Table 1. Single, bimolecular and trimolecular chemical reactions in the stratosphere
反应方程式 反应速率 1 O3+hv = O+O2 6.120×10–4 J 2 O3+O = 2O2 8.0×10–12 e(–2060/T) 3 H + OH +N2 = H2O + N2 1.38×10–24×(1/T)2.6 
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表 2 Chapman Ⅰ模型的化学反应方程式
Table 2. Chemical reaction equation of Chapman Ⅰ model
反应方程式 反应速率 O2+hv = 2O 2.643×10–10 J 3 O2+O = O3 8.018×10–17 O3+hv = O+O2 6.120×10–4 J O3+O = 2O2 1.576×10–15 NO+O3 = NO2+O2 6.062×10–15 NO2+O = NO+O2 1.069×10–11
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表 3 Chapman Ⅰ模型中各成分初始体积分数
Table 3. Initial volume fraction of each component in Chapman Ⅰ model
O O2 O3 NO NO2 8.159×10–9 0.209 6.560×10–6 1.075×10–8 2.759×10–9
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表 4 Chapman Ⅱ模型的化学反应方程式
Table 4. Chemical reaction equation of Chapman Ⅱ model
反应方程式 反应速率 1 O2+hv=2O 2.643×10–10 J 3 2 O2+O=O3 8.018×10–17 3 O3+hv=O+O2 6.120×10–4 J 4 O3+O=2O2 1.576×10–15 5 NO+O3=NO2+O2 6.062×10–15 6 NO2+O=NO+O2 1.069×10–11 7 O3+hv=O(1D)+O2 1.070×10–3 J 2 8 O(1D)+M=O+M 7.110×10–11 9 O(1D)+O3=2O2 1.200×10–10 10 NO2+hv=NO+O 1.289×10–2 J
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表 5 各求解器计算Chapman模型效率（单位 s）
Table 5. Each solver calculates the efficiency of the Chapman model (Unit s)
ros3 rosenbrock ros4 sdirk seulex rodas ChapmanⅠ模型 0.029 0.027 0.037 0.03 0.025 0.025 ChapmanⅡ模型 0.03 0.032 0.029 0.03 0.027 0.023
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表 6 各求解器计算Chapman模型误差值
Table 6. Each solver calculates the error value of the Chapman model
ros3 rosenbrock ros4 sdirk seulex rodas ChapmanⅠ模型（×10–13） 6.195 3.481 3.846 3.075 14.178 2.996 ChapmanⅡ模型（×10–13） 4.712 2.918 3.559 2.680 11.994 2.586
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表 7 各求解器计算Strato模型效率（单位 s）
Table 7. Each solver calculates the efficiency of the Strato model (Unit s)
ros3 rosenbrock ros4 sdirk seulex rodas StratoⅠ模型 0.088 0.081 0.086 0.085 0.085 0.091 StratoⅡ模型 0.100 0.105 0.099 0.094 0.105 0.108
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表 8 各求解器计算Strato模型误差值
Table 8. Each solver calculates the error value of the Strato model
ros3 rosenbrock ros4 sdirk seulex rodas StratoⅠ模型（×10–11） 8.9809 8.9985 8.9806 8.9803 8.9994 8.9797 StratoⅡ模型（×10–13) 1.6525 3.4438 1.6432 1.6033 3.5338 1.5614
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