Enabling cost effective mean of reducing pollutant emissions from gas turbines

碳氢燃料是发电的主要能源。 燃烧过程的污染物排放对环境和人类健康有影响。 为了限制这些影响而在世界范围内实施的严格立法对燃烧系统的设计提出了相互矛盾的要求。 该建议的目的是开发一种新的方法，用于预测工业燃气轮机在湍流燃烧环境中的排放。 * 燃烧过程的详细模拟仍然超出计算能力。 模型假设、其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燃气涡轮机燃烧系统开发的唯一选择。* 不确定性量化理论（UQ）在过去几十年中得到了激烈的发展，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建模分析的各个方面的改进。 这种范式的转变为系统地研究其他未确定的问题提供了一个新的框架。 这项发现补助金的目的是建立一个UQ框架，这将有助于解决当前排放预测方法的局限性。 我们的研究的长期目标是开发预测能力，具有较低的不确定性，为所有燃烧过程的重要性，燃气轮机。* 三个综合项目构成了该提案的核心;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，以及开发具有量化不确定性的排放预测一致的CRN方法。UQ是计算建模的一个步骤，它将科学调查、模型验证和工程设计整合到一个共同的框架中，从而实现更好的决策。受过这种技能培训的HQP将在工程和科学的所有分支的需求量很大。 这项研究计划将有利于目前在加拿大的燃气轮机制造商，因此对加拿大经济。

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.