This study characterized the sooting tendencies of a set of gasolines and their surrogates using both experimental and computational methods. Sooting tendency was defined in terms of the soot yield when 1000 ppm of the test fuel is doped into the fuel of a methane/air flame, and it provides a measure of the intrinsic chemical tendency of the fuels to form soot in a generic combustion environment. The test fuels were real gasolines containing enhanced concentrations of alkanes, aromatics, cycloalkanes, olefins, and ethanol. These compositional differences caused the experimentally measured sooting tendencies of the fuels to vary by 240%. The surrogates were 3 mixtures defined by Szybist et al. (2017) and 3 alternative formulations modified for greater experimental convenience. The sooting tendencies measured for the surrogate mixtures agreed with the real fuels to within 15%, and varied with composition in the same order. The sooting tendencies of the surrogates could be predicted to within experimental error with an empirical quantitative structure-property relationship and a linear mixing model. The experimental flames were computationally simulated with a 743-species mechanism, and sooting tendencies derived from the results agreed with the measured values to within 11%. Overall, these results show that the sooting behavior of gasoline can vary considerably within the range of acceptable compositions, and that these variations can be accurately predicted with empirical models and computational simulations.

这项研究使用实验和计算方法对一组汽油及其替代物的烟so趋势进行了表征。当将1000 ppm的测试燃料掺入甲烷/空气火焰的燃料中时，烟灰趋势是根据烟灰产率来定义的，它提供了在一般燃烧环境中燃料形成烟灰的内在化学趋势的量度。 。测试燃料是包含浓度更高的烷烃，芳烃，环烷烃，烯烃和乙醇的真实汽油。这些组成差异导致实验测量的燃料烟so趋势发生了240％的变化。替代物是Szybist等人定义的3种混合物。（2017）和3种替代配方进行了修改，以提供更大的实验便利性。对替代混合物测得的烟灰趋势与真实燃料一致，在15％以内，并且随组成以相同顺序变化。可以通过经验的定量结构-性质关系和线性混合模型来预测替代物的烟ot趋势。用743种机理对实验火焰进行了计算模拟，从结果得出的烟灰趋势与测量值相符，在11％以内。总体而言，这些结果表明，汽油的烟behavior行为可以在可接受的成分范围内发生很大变化，并且可以通过经验模型和计算模拟来准确预测这些变化。可以通过经验的定量结构-性质关系和线性混合模型来预测替代物的烟ot趋势。用743种机理对实验火焰进行了计算模拟，从结果得出的烟灰趋势与测量值相符，在11％以内。总体而言，这些结果表明，汽油的烟behavior行为可以在可接受的成分范围内发生很大变化，并且可以通过经验模型和计算模拟来准确预测这些变化。可以通过经验的定量结构-性质关系和线性混合模型来预测替代物的烟ot趋势。用743种机理对实验火焰进行了计算模拟，从结果得出的烟灰趋势与测量值相符，在11％以内。总体而言，这些结果表明，汽油的烟behavior行为可以在可接受的成分范围内发生很大变化，并且可以通过经验模型和计算模拟来准确预测这些变化。结果得出的烟so趋势与测量值相符，在11％以内。总体而言，这些结果表明，汽油的烟behavior行为可以在可接受的成分范围内发生很大变化，并且可以通过经验模型和计算模拟来准确预测这些变化。结果得出的烟so趋势与测量值相符，在11％以内。总体而言，这些结果表明，汽油的烟behavior行为可以在可接受的成分范围内发生很大变化，并且可以通过经验模型和计算模拟来准确预测这些变化。