TY - JOUR
T1 - The Dual Model under Pressure
T2 - How Robust Is Leak Detection under Uncertainties and Model Mismatches?
AU - Campbell, Enrique
AU - Abraham, Edo
AU - Koslowski, Johannes
AU - Piller, Olivier
AU - Steffelbauer, David B.
PY - 2024
Y1 - 2024
N2 - This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) the number of sensors, and (iv) network topology. Our investigation results indicate that the Dual Model is highly sensitive to discrepancies in the first three parameters. However, the impact can be mitigated through sensor-specific calibration, such as adjusting sensor elevations. Moreover, the Dual Model has demonstrated robustness to minor topology mismatches, like those introduced by closed valves.
AB - This paper investigates the robustness of one innovative model-based method for leak detection, namely the Dual Model. We evaluate the algorithm’s performance under various leakage scenarios in the L-Town network, despite uncertainties and model mismatches in (i) base demand, (ii) pipe roughness, (iii) the number of sensors, and (iv) network topology. Our investigation results indicate that the Dual Model is highly sensitive to discrepancies in the first three parameters. However, the impact can be mitigated through sensor-specific calibration, such as adjusting sensor elevations. Moreover, the Dual Model has demonstrated robustness to minor topology mismatches, like those introduced by closed valves.
KW - dual model
KW - leak detection
KW - robustness
KW - simulation model
UR - http://www.scopus.com/inward/record.url?scp=85218128999&partnerID=8YFLogxK
U2 - 10.3390/engproc2024069089
DO - 10.3390/engproc2024069089
M3 - Article
AN - SCOPUS:85218128999
SN - 2673-4591
VL - 69
JO - Engineering Proceedings
JF - Engineering Proceedings
IS - 1
M1 - 89
ER -