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Structure and Infrastructure Engineering
Maintenance, Management, Life-Cycle Design and Performance
Volume 19, 2023 - Issue 8
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Articles

On the influence of input data uncertainty on sewer deterioration models – a case study in Norway

, ORCID Icon & ORCID Icon
Pages 1064-1075 | Received 06 Apr 2021, Accepted 12 Sep 2021, Published online: 03 Nov 2021

Figures & data

Figure 1. Schematic illustration of the applied method.

Figure 1. Schematic illustration of the applied method.

Figure 2. Bar chart showing the deviation between this project's and professional pipe inspector’s condition classification of the same CCTV video and the derived uncertainty matrix showing the probability of a pipe to be really in condition y when inspected in condition x.

Figure 2. Bar chart showing the deviation between this project's and professional pipe inspector’s condition classification of the same CCTV video and the derived uncertainty matrix showing the probability of a pipe to be really in condition y when inspected in condition x.

Table 1. Uncertainty matrices for scenario 3 and 4.

Table 2. Uncertainty matrix for scenario 1 and 2.

Table 3. Distribution (%) of installation periods and observed CC for concrete pipes.

Figure 3. Condition probabilities of the calibrated GompitZ model with IFF and the corresponding uncertainty bands for the four defined scenarios.

Figure 3. Condition probabilities of the calibrated GompitZ model with IFF and the corresponding uncertainty bands for the four defined scenarios.

Figure 4. Condition probabilities of the calibrated marginal GompitZ model and the corresponding uncertainty bands for the four defined scenarios.

Figure 4. Condition probabilities of the calibrated marginal GompitZ model and the corresponding uncertainty bands for the four defined scenarios.