This research report addresses the current uncertainties regarding the technical service life and aging behavior of the most common sewer rehabilitation method, Cured-in-Place Pipe (CIPP) lining. The goal of this study is to develop a robust data foundation for a CIPP liner survival curve for use in aging models. The methodological approach includes (i) a literature review, (ii) interviews with sewer rehabilitation experts, and (iii) an analysis of data from Berliner Wasserbetriebe to create an updated and suitable data basis for the calibration of survival curves. The literature review and expert interviews predominantly estimate the service life of CIPP liners to exceed 50 years. However, the study also reveals that this lifespan is influenced by numerous factors and that there is a lack of reliable data. Further investigations of long-used CIPP liners are therefore essential. The installation process, particularly the curing phase, has been identified as the primary factor contributing to defects and deficiencies in CIPP liners. Standardizing damage assessment and condition evaluation for liner-specific defects, as well as establishing non-destructive inspection methods, is necessary to improve the understanding of aging behavior in the future. Recommendations include improving data collection during the operation, installation, and removal of CIPP liners, enhancing quality assurance during installation, investigating the impact of damage on service life, and promoting knowledge exchange among operators.

Addressing Europe's current challenges of aging sewer networks, the presented research focuses on the uncertainties in service life and aging behavior of the most used renovation technique, Cured in Place Pipe (CIPP) lining. Examining its aging behavior, common defects and deficiencies were analyzed through literature review and expert interviews. The findings influenced the proposition of a calibration setting for a deterioration model using survival curves. Identified defects stress the need for precise installation and curing processes. The study recommends a thorough review of the initially specified 50-year service life, acknowledging uncertainties during the installation process.

German: In den vergangenen Jahren hat sich die Datenlage zum Zustand der Abwasserkanalisation und zur Wirkung unterschiedlicher Sanierungsverfahren stetig verbessert. Basierend auf diesen Erkenntnissen wurden durch das Kompetenzzentrum Wasser Berlin und die Berliner Wasserbetriebe Prognosemodelle zur Bewertung unterschiedlicher Sanierungsszenarien sowie zur Lokalisierung schadhafter Kanäle entwickelt. Die vorliegende Studie zeigt den Weg von Bestands- und Zustandsdaten des Kanalnetzes zu einem an die lokalen Randbedingungen angepassten Simulationswerkzeug für die strategische Kanalsanierungsplanung. Dabei werden Methoden zur modellgestützten Ergänzung von Datenlücken sowie die entwickelten Modellkomponenten für Kanalalterung und -sanierung vorgestellt. Darüber hinaus werden Ergebnisse ausgewählter Sanierungsszenarien und die wichtigsten Prognoseunsicherheiten diskutiert. Der entwickelte Ansatz unterstützt die Kanalsanierungs- und Investitionsplanung von Kommunen und hilft, den Zustand der Abwasserinfrastruktur langfristig zu erhalten oder zu verbessern.

Deterioration modelling has been developed in the last decades to support operators and municipalities in defining mid-long term asset management strategies with limited availability of sewer condition data (CCTV). Modelling can help validating and showing the viability of current strategies or provide information to justify the relevance of additional investments and expenditures. Several modelling approaches are now available but not commonly used by sewer operators and municipalities to support strategies mainly because of the lack of real scale demonstration of the tangible benefits provided. Indeed, most of these models fail to show that they can adequately forecast future conditions (Ana and Bauwens, 2010; Scheidegger et al., 2011; WERF, 2012).

Deterioration modelling can be a powerful tool to support utilities in planning efficient sewer rehabilitation strategies. However, the benefits of using deterioration models are still to be demonstrated to increase the confidence of utilities toward simulation results. This study aims at assessing the performance of a statistical deterioration model to estimate the current condition and predict the future deterioration of the network. The quality of prediction of the deterioration model GompitZ has been assessed using the extensive dataset of 35,826 inspections of the city of Braunschweig in Germany. The performance of the statistical model has been compared with the performance of a simple model based only on the condition of observed sewers. Results show that the statistical model performs much better than the simple model for simulating the deterioration of the network. The findings highlight the relevance of using modelling tools to simulate sewer deterioration and support strategic asset management.

Im Rahmen des Forschungsprojekts SEMA ist die Prognosequalität eines Alterungsmodells anhand der TV-Inspektionsdaten der Stadt Braunschweig geprüft worden. Die Qualität der Prognose wurde auf der Grundlage einer Probe von 35.826 Inspektionen bewertet. Die Inspektionen wurden mittels eines substanzbasierten Modells klassifiziert. In einem zweiten Schritt wurde das statistische Modell KANEW-Z angewandt, um die Kanalalterung zu simulieren. Der Vergleich der Inspektions- mit den Simulationsergebnissen zeigt, dass das Modell in der Lage ist, die Zustandsverteilung des Systems ziemlich genau wiederzugeben. Die Ergebnisse sind auch ermutigend auf individueller Haltungsebene. Im Allgemeinen zeigt das Alterungsmodell viel bessere Ergebnisse als ein einfaches lineares Alterungsmodell. Schlussfolgernd unterstreichen die Ergebnisse das Interesse und den potentiellen Nutzen der Anwendung von Alterungsmodellen zur Unterstützung von Asset-Management-Strategien.

Several infrastructure studies highlight the ongoing deterioration of critical assets in water and wastewater systems (WERF, 2007). A recent survey among 397 water and wastewater industry participants in the U.S.A. and Canada highlights that aging infrastructure and the management of capital and operational costs are the two main industry issues (Black and Veatch, 2013). From the participants, more than 70% of municipalities and utilities have already implemented condition assessment and inspection programs to assess the condition state of their systems. However, less than 10% are currently using simulation tools to support their asset management strategies. These results underline the strong opportunity for municipalities and utilities to increase the efficiency of their asset management programs by extracting the value of their (already) available data. Several modeling approaches are now available but not commonly used by sewer operators to support strategies (Caradot et al., 2013). Indeed, most of these models still fail to show that they can adequately forecast future conditions (Ana and Bauwens, 2010; Scheidegger et al., 2011). This article presents an assessment of the ability of sewer deterioration models to simulate the condition distribution of sewer networks. The analysis has been done using the extensive CCTV dataset of a German city, Braunschweig.