TY - GEN
T1 - Domain Knowledge Assisted Gas Tomography
AU - Wiedemann, Thomas
AU - Hinsen, Patrick
AU - Ruiz, Victor Prieto
AU - Shutin, Dmitriy
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
©2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The presented work addresses the challenging problem of Gas Tomography (GT) – a reconstruction technique for a spatial gas distribution based on measurements with an open-path sensor. Given that such a sensor only captures an integrated gas concentration along a laser trajectory, the reconstruction problem is inherently ill-posed. The method proposed in this work assists GT reconstruction using domain knowledge in the form of a gas dispersion model, formally described by the advection-diffusion Partial Differential Equation (PDE). Specifically, the model facilitates a physics-informed interpolation in regions not covered by measurements. As a result, the proposed numerical approach demonstrates a considerably improved performance in simulation studies, as compared to state-of-the-art GT algorithms.
AB - The presented work addresses the challenging problem of Gas Tomography (GT) – a reconstruction technique for a spatial gas distribution based on measurements with an open-path sensor. Given that such a sensor only captures an integrated gas concentration along a laser trajectory, the reconstruction problem is inherently ill-posed. The method proposed in this work assists GT reconstruction using domain knowledge in the form of a gas dispersion model, formally described by the advection-diffusion Partial Differential Equation (PDE). Specifically, the model facilitates a physics-informed interpolation in regions not covered by measurements. As a result, the proposed numerical approach demonstrates a considerably improved performance in simulation studies, as compared to state-of-the-art GT algorithms.
KW - gas dispersion model
KW - gas distribution mapping
KW - gas tomography
KW - open-path sensor
KW - tunable diode laser absorption spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85197376865&partnerID=8YFLogxK
U2 - 10.1109/ISOEN61239.2024.10556226
DO - 10.1109/ISOEN61239.2024.10556226
M3 - Conference contribution
AN - SCOPUS:85197376865
T3 - ISOEN 2024 - International Symposium on Olfaction and Electronic Nose, Proceedings
BT - ISOEN 2024 - International Symposium on Olfaction and Electronic Nose, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Symposium on Olfaction and Electronic Nose, ISOEN 2024
Y2 - 12 May 2024 through 15 May 2024
ER -