基于散射光强度的碳黑团聚体分形结构和粒径分布同时反演

利用散射光信号实现碳黑团聚体分形结构和粒径分布参数的同时反演，在火焰辐射换热模拟和污染物测定方面有着重要应用价值。反演的正问题基于瑞利-德拜-甘斯多分散分形团聚体（RDG-PFA）散射理论，研究了2种信号方案，包括多角度散射及多角度散射-准直透射率。反演前，对比2种信号方案的残余适应度值分布发现，散射与透射信号同时使用有效减弱了反问题的病态性。反演过程基于协方差矩阵自适应的演化策略（CMA-ES）算法，该算法具有很强的局部搜索能力，为快速且稳定地反演各个目标参数提供了保障。反演结果表明了CMA-ES算法较大搜索空间内的可行性和普适性，同时也证明了采用多角度散射-准直透射率的组合信号有效提高了目标参数的反演精度。 

Simultaneous inversion of fractal morphology and particle size distribution of soot aggregate based on light scattering intensity

The use of light scattering signals to achieve the simultaneous inversion of the fractal morphology and particle size distribution parameters of soot aggregates have important application value in flame radiation heat transfer simulation and pollution control. The direct model of inversion is based on the Rayleigh-Debye-Gans Polydisperse Fractal Approximation (RDG-PFA) light scattering theory. Two signal schemes were investigated: multi-angle scattering, multi-angle scattering and collimated transmittance. Before the inversion, by comparing the residual fitness value distributions of the two signal schemes, it is found that the simultaneous use of scattering and transmission signals effectively reduces the ill-posedness of the inverse problem. The inversion process is based on the Covariance Matrix Adaptive Evolutionary Strategy (CMA-ES) algorithm, which has a strong local search capability and provides a guarantee for fast and stable inversion of each target parameter. The final inversion results demonstrate the feasibility and universality of the method in a large search space. And it is also proved that the combination of multi-angle scattering and collimated transmittance effectively improves the inversion accuracy of the target parameters.