Classification and computation of extreme events in turbulent combustion

Hassanaly, Malik; Raman, Venkat

doi:10.1016/j.pecs.2021.100955

Title: Classification and computation of extreme events in turbulent combustion

Journal Article · 27 August 2021 · Progress in Energy and Combustion Science

DOI: https://doi.org/10.1016/j.pecs.2021.100955 · OSTI ID:1818885

^[1]; Raman, Venkat ^[2]

Univ. of Michigan, Ann Arbor, MI (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
Univ. of Michigan, Ann Arbor, MI (United States)

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: US Air Force Office of Scientific Research (AFOSR); USDOE

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1818885

Report Number(s):: NREL/JA--2C00-80843; MainId:78621; UUID:0468164f-1807-4bdc-8967-4cac7a7e7a8c; MainAdminID:61697

Journal Information:: Progress in Energy and Combustion Science, Journal Name: Progress in Energy and Combustion Science Vol. 87; ISSN 0360-1285

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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