A critical issue in design and operation of combustors in gas turbine engines is mitigation of thermoacoustic instabilities, because such instabilities may cause severe damage to the mechanical structure of the combustor. Hence, it is important to quantitatively assimilate the knowledge of the system conditions that would potentially lead to these instabilities. This technical brief proposes a dynamic data-driven technique for design of combustion systems by taking stability of pressure oscillations into consideration. Given appropriate experimental data at selected operating conditions, the proposed design methodology determines a mapping from a set of operating conditions to a set of quantified stability conditions for pressure oscillations. This mapping is then used as an extrapolation tool for predicting the system stability for other conditions for which experiments have not been conducted. Salient properties of the proposed design methodology are: (1) It is dynamic in the sense that no fixed model structure needs to be assumed, and a suboptimal model (under specified user-selected constraints) is identified for each operating condition. An information-theoretic measure is then used for performance comparison among different models of varying structures and/or parameters and (2) It quantifies a (statistical) confidence level in the estimate of system stability for an unobserved operating condition by using a Bayesian nonparametric technique. The proposed design methodology has been validated with experimental data of pressure time-series, acquired from a laboratory-scale lean-premixed swirl-stabilized combustor.
Skip Nav Destination
Article navigation
January 2019
Technical Briefs
Dynamic Data-Driven Combustor Design for Mitigation of Thermoacoustic Instabilities
Pritthi Chattopadhyay,
Pritthi Chattopadhyay
Mechanical Engineering Department,
Pennsylvania State University,
University Park, PA 16802
Pennsylvania State University,
University Park, PA 16802
Search for other works by this author on:
Sudeepta Mondal,
Sudeepta Mondal
Mechanical Engineering Department,
Pennsylvania State University,
Pennsylvania State University,
University Park
, PA 16802
Search for other works by this author on:
Asok Ray,
Asok Ray
Fellow ASME
Mechanical Engineering Department,
Pennsylvania State University,
e-mail: axr2@psu.edu
Mechanical Engineering Department,
Pennsylvania State University,
University Park
, PA 16802e-mail: axr2@psu.edu
Search for other works by this author on:
Achintya Mukhopadhyay
Achintya Mukhopadhyay
Mechanical Engineering Department,
Jadavpur University,
Kolkata 700 032, India
Jadavpur University,
Kolkata 700 032, India
Search for other works by this author on:
Pritthi Chattopadhyay
Mechanical Engineering Department,
Pennsylvania State University,
University Park, PA 16802
Pennsylvania State University,
University Park, PA 16802
Sudeepta Mondal
Mechanical Engineering Department,
Pennsylvania State University,
Pennsylvania State University,
University Park
, PA 16802
Asok Ray
Fellow ASME
Mechanical Engineering Department,
Pennsylvania State University,
e-mail: axr2@psu.edu
Mechanical Engineering Department,
Pennsylvania State University,
University Park
, PA 16802e-mail: axr2@psu.edu
Achintya Mukhopadhyay
Mechanical Engineering Department,
Jadavpur University,
Kolkata 700 032, India
Jadavpur University,
Kolkata 700 032, India
1Corresponding author.
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received February 8, 2018; final manuscript received April 23, 2018; published online September 7, 2018. Assoc. Editor: Jongeun Choi.
J. Dyn. Sys., Meas., Control. Jan 2019, 141(1): 014501 (7 pages)
Published Online: September 7, 2018
Article history
Received:
February 8, 2018
Revised:
April 23, 2018
Citation
Chattopadhyay, P., Mondal, S., Ray, A., and Mukhopadhyay, A. (September 7, 2018). "Dynamic Data-Driven Combustor Design for Mitigation of Thermoacoustic Instabilities." ASME. J. Dyn. Sys., Meas., Control. January 2019; 141(1): 014501. https://doi.org/10.1115/1.4040210
Download citation file:
Get Email Alerts
Cited By
Control of a Directional Downhole Drilling System Using a State Barrier Avoidance Based Method
J. Dyn. Sys., Meas., Control (May 2025)
Dynamic control of cardboard-blank picking by using reinforcement learning
J. Dyn. Sys., Meas., Control
Offline and online exergy-based strategies for hybrid electric vehicles
J. Dyn. Sys., Meas., Control
In-Situ Calibration of Six-Axis Force/Torque Transducers on a Six-Legged Robot
J. Dyn. Sys., Meas., Control (May 2025)
Related Articles
Transfer Learning for Detection of Combustion Instability Via Symbolic Time-Series Analysis
J. Dyn. Sys., Meas., Control (October,2021)
Dynamic Data-Driven Design of Lean Premixed Combustors for Thermoacoustically Stable Operations
J. Mech. Des (November,2017)
Pair Selection Analysis in Differential RSSI Based Localization
J. Dyn. Sys., Meas., Control (November,2015)
Experimental Study on the Role of Entropy Waves in Low-Frequency Oscillations in a RQL Combustor
J. Eng. Gas Turbines Power (April,2006)
Related Proceedings Papers
Related Chapters
Outlook
Closed-Cycle Gas Turbines: Operating Experience and Future Potential
Challenges in biomacromolecular delivery
Biocompatible Nanomaterials for Targeted and Controlled Delivery of Biomacromolecules
Research and Implementation on Test and Diagnose Program by ATML
International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)