Characterization by laser diagnostics of the sooting propensity of biomass-derived fuels intended to be used as environmentally-friendly substitutes to fossil fuels

通过激光诊断表征旨在用作化石燃料的环保替代品的生物质衍生燃料的烟灰倾向

• 批准号: RGPIN-2017-05191
• 负责人: Lemaire, Romain
• 金额: $ 1.6万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754469
• 关键词: Characterization; laser; diagnostics; sooting; propensity

This program aims at improving the understanding of the sooting behavior of different biomass-derived fuels to support the development of cleaner energy carriers. Actually, soot is one of the major pollutants generated in combustion processes and one of the main contributors to anthropogenic aerosols. To limit its production with the view to meet actual and future regulations, source reduction remains a key option particularly considered by engine manufacturers. A thorough understanding of the physicochemical mechanisms involved in the formation of polycyclic aromatic hydrocarbons (PAHs) and soot is still required however (especially in the case of biofuels) to improve the predictive character of the computational codes used to design combustion devices. The purpose of the present program is therefore to provide insightful findings regarding the ability of different molecules to act as soot suppressors with the view to identify the must-have fuel properties necessary for the mid- to long-term commercialization of environmentally-friendly substitutes to petroleum-derived fuels. To do so, the present proposal which associates laboratory scale experiments and engine tests is composed of 3 main objectives summarized as follows:1) Developing predictive sooting propensity indicators incorporating all the fuel molecular structural effects known to influence soot production. To do so, the Fuel Equivalent Sooting Index (FESI) of various biofuels (including furan isomers and some components of bio-oils derived from wood pyrolysis) will be measured. Obtained results will then be processed by means of a structural group additivity approach to propose an original set of predictive sooting propensity group contribution factors.2) Developing Particulate Matter (PM) indexes suitable to predict engine particulate emissions. Based on measurements performed at the exhaust of direct injection Diesel and spark ignition engines, PM index formulations will be proposed integrating FESI values to represent the fuel molecular structure and fuel properties (including volatility factors) playing a role in the fuel/oxidizer mixture formation.3) Developing adapted metrological tools necessary to achieve the above-mentioned objectives. Such a transverse task includes 1/ the development of a time resolved laser-induced incandescence/fluorescence (LII/LIF) technique for the simultaneous detection of soot and PAHs and 2/ contributions in the modeling of LII signals to infer information on soot physical properties through the implementation of advanced optimization algorithms.At the end of this program, innovative measurement and modeling tools will be proposed to explore some of the major issues needing to be addressed in order to develop cleaner fuels and combustion technologies that will benefit the Canadian energy production, aerospace and automotive industries among others.

该计划旨在提高对不同生物质衍生燃料的烟雾行为的理解，以支持清洁能源载体的开发。实际上，烟灰是在燃烧过程中产生的主要污染物之一，也是人为气溶胶的主要贡献者之一。为了限制其生产以满足实际和将来的法规，源头减少仍然是发动机制造商特别考虑的关键选择。然而，仍然需要彻底了解与多环芳烃（PAHS）和烟灰形成有关的物理化学机制（尤其是在生物燃料的情况下），以改善用于设计燃烧设备的计算代码的预测性。因此，本计划的目的是提供有关不同分子充当烟灰抑制器能力的有见地的发现，以确定环境友好型替代品长期商业化所必需的必备燃料特性石油来源的燃料。为此，将实验室规模实验和发动机测试关联的本提案由3个主要目标组成，总结如下：1）开发预测性的烟灰倾向指标，其中包含所有燃料分子结构效应已知影响烟灰的生产。为此，将测量各种生物燃料的燃料当量烟雾指数（FESI）（包括呋喃异构体和一些来自木质燃料的生物油的成分）。然后，将通过结构组加成性方法来处理获得的结果，以提出一组原始的预测性烟雾倾向组贡献因素。2）开发适合预测发动机颗粒物排放的颗粒物（PM）索引。根据直接注入柴油和火花点火发动机进行的测量结果，将提出PM索引配方，以整合FESI值，以表示燃料分子结构和燃料性能（包括波动性因子）在燃料/氧化剂混合物形成中发挥作用。 3）开发实现上述目标所需的适​​应性计量工具。这样的横向任务包括1/开发时间解决激光诱导的白炽灯/荧光（LII/ LIF）技术，用于同时检测烟灰和PAHS，以及在LII信号建模中的2/贡献，以推断有关烟灰物理性能的信息通过实施高级优化算法。在该计划的结尾，将提出创新的测量和建模工具，以探索一些需要解决的主要问题，以开发有益于加拿大能源生产的清洁燃料和燃烧技术，航空航天和汽车行业等。