Enabling cost effective mean of reducing pollutant emissions from gas turbines

碳氢燃料是发电的主要能源。燃烧过程中的污染物排放对环境和人类健康都有影响。世界各地为限制这些影响而执行的严格立法对燃烧系统的设计提出了相互矛盾的要求。该方案的目的是开发一种新的方法来预测湍流燃烧环境中的排放，并将其应用于工业燃气轮机。 对燃烧过程的详细模拟仍然超出了计算能力。模型假设、参数和边界条件定义中的不确定性的影响使问题进一步复杂化。因此，依赖昂贵的实验测试是开发燃气轮机燃烧系统的唯一选择。 不确定度量化理论在过去的几十年里得到了迅猛的发展，并在许多科学和工程学科中得到了应用。UQ提供了一种严格的方法来推动数值模拟分析的所有方面的改进。这一范式转变提供了一个新的框架，用于系统研究其他方面尚未确定的问题。这一发现基金的目标是建立一个UQ框架，帮助解决当前排放预测方法的局限性。我们研究的长期目标是开发对燃气轮机重要的所有燃烧过程的预测能力，而不确定程度较低。 该提案的核心是三个综合项目：减少天然气化学动力学机制的不确定性，包括NOx化学；开发用于化学反应器网络(CRN)模拟的新型湍流化学相互作用模型；以及为具有量化不确定性的排放预测开发一致的CRN方法。 UQ是计算建模的一步变化，它将科学调查、模型验证和工程设计结合到一个公共框架中，从而实现更好的决策。用这种技能训练的HQP在工程和科学的所有分支中都会有很高的需求。这项研究计划将使加拿大现有的燃气轮机制造商受益，从而使加拿大经济受益。

Hydrocarbon fuels are the main energy source for power generation. Pollutant emissions from combustion processes have environmental and human health impacts. Stringent legislation enforced worldwide to limit these impacts imposes conflicting requirements on the design of combustion system. The aim of this proposal is to develop a novel methodology for emissions predictions in turbulent combustion environment with application to industrial gas turbines. Detailed simulation of the combustion process still exceeds computational capabilities. The influence of the uncertainties in the model assumptions, in their parameters, and in the definitions of the boundary conditions further complicates the problem. As a consequence, reliance on costly experimental testing is the only alternative for the development of gas turbine combustion systems. The theory of uncertainty quantification (UQ) has been in intense development in the last few decades and has found applications in many scientific and engineering disciplines. UQ provides a rigorous methodology to drive improvements in all aspect of numerical modeling analysis. This paradigm shift provides a new framework to systematically study otherwise undetermined problems. The objective of this Discovery Grant is to build an UQ framework that will help to address the limitations of current emissions prediction methods. The long term goal of our research is to develop predictive capability, with low level of uncertainty, for the all combustion processes of importance for gas turbines. Three integrated projects form the core of the proposal; reduction uncertainty of natural gas chemical kinetics mechanism including NOx chemistry, development of novel turbulence chemistry interaction model for use in chemical reactor networks (CRN) simulations, and development of a consistent CRN methodology for emissions predictions with quantified uncertainty. UQ is a step change in computational modeling that brings together scientific investigation, model validation, and engineering design into a common framework that will enable better decision making. HQP trained with this skill will be in high demand in all branches of engineering and science. This research program will benefit gas turbines manufacturer present in Canada and therefore to the Canadian economy.