Alcoholate (Dry) Corrosion: Critical damage mechanisms and their progression identified and described via experiment and modeling (AlcoMo)

醇盐（干）腐蚀：通过实验和建模识别和描述的关键损坏机制及其进展 (AlcoMo)

• 批准号: 408781233
• 负责人: Dr. Daniel Höche
• 金额: --
• 依托单位: Fachgebiet und Institut für Werkstoffkunde
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/408781233?language=en
• 关键词: Alcoholate; Dry; Corrosion; Critical; damage

Subject of this research proposal is to seek the opportunity to continue the (ongoing) project "AlkoMo", which is funded by the DFG, for another two years.The overall objective is the experimental and model-theoretical investigation of alcoholate (dry) corrosion on aluminium alloys in biogenic fuel blends in order to describe and predict the risk potential for corrosion and thus to enable valid statements to be made on the material compatibility of relevant material-fuel combinations. The physical and chemical fundamentals as well as the relevance of the topic have already been discussed in detail in the first application. During the first 20 months of the current project, a statistical method was developed to initiate the initiation phase of the initially local attack during alcoholate corrosion in anhydrous ethanol using the example of pure aluminium EN AW-1050A. Furthermore, the growth could be characterized by a Gumbel analysis of the pit size maxima, so that a prediction of the maximum lateral expansion of isolated and localized attack sites at a given medium temperature is possible. In principle, these methods can also be applied to alloyed material-fuel combinations and fuel blends close to the field. In addition to the development of a suitable evaluation methodology, the microreactor outlined in the initial application was designed, manufactured, commissioned and successfully validated. First promising experiments were carried out, which allow a considerably more sensitive application of the stress parameters as well as a more precise detection and generation of input data for further model development.To create a completely physically based and time-dependent finite element model the evaluation plan defined in the initial application was modified and an intermediate step based on data analysis and neural networks was introduced, which allows to extract differential equations and constants from data series. This innovative and promising method is now able to cope with the multitude of variable parameters and the resulting complexity of the system under investigation. It also allows to develop a model based on physical relationships for predicting the corrosion behavior of aluminum materials in biogenic fuels.The goals are directly based on the goals of AlkoMo, but have been adapted by the simulative, experimental and methodological knowledge gained during the project as well as the newly available innovative experimental equipment: 1. identification of corrosion initiation and characterization of corrosion progress.2. model adaptation and experimental validation3. development of a physicochemical description approach for corrosion initiation4. transfer of results and final evaluation

本研究提案的主题是寻求机会继续（正在进行的）项目“AlkoMo”，该项目由DFG资助，总的目标是醇盐（干）的实验和模型理论研究。生物燃料混合物中铝合金的腐蚀，以描述和预测腐蚀的潜在风险，从而能够对材料做出有效声明相关材料-燃料组合的兼容性。物理和化学的基本原理以及主题的相关性已经在第一个应用程序中详细讨论。在当前项目的前20个月期间，开发了一种统计方法，以使用纯铝EN AW-1050 A为例，在无水乙醇中的醇盐腐蚀期间启动初始局部侵蚀的初始阶段。此外，增长的特点可以通过一个Gumbel分析的坑大小的最大值，以便在一个给定的介质温度的最大横向膨胀的预测孤立和本地化的攻击网站是可能的。原则上，这些方法也可以应用于接近现场的合金材料-燃料组合和燃料混合物。除了开发合适的评估方法外，还设计、制造、调试并成功验证了初始应用中概述的微反应器。首先进行了有希望的实验，这使得应力参数的应用更加敏感，并且可以更精确地检测和生成输入数据，以用于进一步的模型开发。为了创建完全基于物理和时间依赖的有限元模型，修改了初始应用中定义的评估计划，并引入了基于数据分析和神经网络的中间步骤，其允许从数据序列中提取微分方程和常数。这种创新和有前途的方法现在能够科普众多的可变参数和所造成的复杂性的系统正在调查。它还允许开发一个基于物理关系的模型，用于预测生物燃料中铝材料的腐蚀行为。目标直接基于AlkoMo的目标，但已经通过项目期间获得的模拟，实验和方法学知识以及新可用的创新实验设备进行了调整：1.腐蚀起始的识别和腐蚀过程的表征.模型适应和实验验证3.发展腐蚀起始的物理化学描述方法4.成果移交和最终评价