Optimization of CO Turndown for an Axially Staged Gas Turbine Combustor
Notice bibliographique
Résumé
Abstract This paper reports on an optimization study of the CO turndown behavior of an axially staged combustor, in the context of industrial gas turbines (GTs). The aim of this work is to assess the optimally achievable CO turndown behavior limit given system and operating characteristics, without considering flow-induced behaviors such as mixing quality and flame spatial characteristics. To that end, chemical reactor network (CRN) modeling is used to investigate the impact of various system and operating conditions on the exhaust CO emissions of each combustion stage, as well as at the combustor exit. Different combustor residence time combinations are explored to determine their contribution to the exhaust CO emissions. The two-stage combustor modeled in this study consists of a primary (Py) and a secondary (Sy) combustion stage, followed by a discharge nozzle (DN), which distributes the exhaust to the turbines. The Py is modeled using a freely propagating flame (FPF), with the exhaust gas extracted downstream of the flame front at a specific location corresponding to a specified residence time (tr). These exhaust gases are then mixed and combusted with fresh gases in the Sy, modeled by a perfectly stirred reactor (PSR) operating within a set tr. These combined gases then flow into the DN, which is modeled by a plug flow reactor (PFR) that cools the gas to varying combustor exit temperatures within a constrained tr. Together, these form a simplified CRN model of a two-stage, dry-low emissions (DLEs) combustion system. Using this CRN model, the impact of the tr distribution between the Py, Sy, and DN is explored. A parametric study is conducted to determine how inlet pressure (Pin), inlet temperature (Tin), equivalence ratio (ϕ), and Py–Sy fuel split (FS), individually impact indicative CO turndown behavior. Their coupling throughout engine load is then investigated using a model combustor, and its effect on CO turndown is explored. Thus, this aims to deduce the fundamental, chemically driven parameters considered to be most important for identifying the optimal CO turndown of GT combustors. In this work, a parametric study and a model combustor study are presented. The parametric study consists of changing a single parameter at a time, to observe the independent effect of this change and determine its contribution to CO turndown behavior. The model combustor study uses the same CRN, and varies the parameters simultaneously to mimic their change as an engine moves through its steady-state power curve. The latter study thus elucidates the difference in CO turndown behavior when all operating conditions are coupled, as they are in practical engines. The results of this study aim to demonstrate the parameters that are key for optimizing and improving CO turndown.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».