Faster inverse transient analysis with a head-based method of characteristics and a flexible computational grid for pipeline condition assessment

Targeted and proactive pipeline condition assessment is critical for cost-effective maintenance of aging water transmission and distribution systems. The current research proposes a fast inverse transient analysis (ITA) with a head-based method of characteristics (HBMOC) and a flexible computational grid for condition assessment of long pressurized pipelines. Compared with conventional ITA, the key innovations of the proposed method include (1) the development and use of an innovative forward-modeling scheme HBMOC to enhance computational efficiency; and (2) use of a flexible characteristics grid to avoid the need for interpolation and hence enhance the accuracy by satisfying the Courant condition in all iterations of forward modeling. To examine and verify the proposed method, numerical simulations are conducted in a pipeline with multiple sections of deterioration (simulated by changes in wavespeed). Both the conventional ITA and proposed ITA are applied to the numerical pipe model, and the wavespeeds estimated by different ITA approaches are compared. It is concluded that the proposed ITA is more accurate and four times more computationally efficient than the conventional ITA. The impact of neglecting friction in the proposed approach is shown to be insignificant given that the proposed ITA was aimed at condition assessment of transmission mains, and only transient pressures that cover the pipe section of interest are analyzed.