Year: 2024
Type: article
Abstract: Although thermal waves are ubiquitous in nature and engineering, the development of diagnostic tools capable of elucidating the roles of reaction and transport remains an unmet need. This limits our comprehension of the physics and ability to predict wave dynamics. Here we demonstrate that thermal properties and chemical kinetics can be learned directly from observing thermal wave dynamics, using partial differential equation-constrained optimization. This enables the determination of unobserved reaction rates without the need for a comprehensive measurement of all state variables, given the model space constrained by governing equations. Examples include steady planar waves and unsteady pulsating waves of which dynamics are commonly observed in nature. We show successful learning of thermal properties and chemical kinetics and reconstruction of wave dynamics with the inferred properties, which enables the comprehension of the intricate reaction-transport coupling from thermal data. Thermal waves describe the propagation of heat in chemically reacting flows such as combustion processes. Here the authors establish a differential-equation based framework that reveals reaction and material properties directly from analyzing thermal waves.
Source: Nature Communications
Authors: Suyong Kim, Sili Deng
Institution: Massachusetts Institute of Technology
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,790
Funders: Volkswagen of America, MathWorks
OpenAlex ID: W4404400021