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Selective inspection planning with ageing forecast for sewer types
1Technische Universität Dresden, Fakultät Bauingenieurwesen, Lehrstuhl Stadtbauwesen, Dresden, Germany.
Summary
Forecasting sewer conditions relies on empirically derived transition functions. This method predicts critical deterioration dates based on sewer characteristics, aiding proactive infrastructure management.
Area of Science:
- Civil Engineering
- Environmental Engineering
- Wastewater Management
Background:
- Effective sewer rehabilitation requires accurate condition assessment and risk evaluation.
- Forecasting future sewer conditions is crucial for proactive infrastructure management and investment planning.
Purpose of the Study:
- To develop a method for forecasting sewer network conditions using a limited inspection sample.
- To predict the most probable date for sewers entering critical condition classes based on their characteristics.
Main Methods:
- Empirically derived transition functions were used to model condition changes between classes.
- Transition functions were calibrated for different sewer types using sub-samples.
- Sewer characteristics (material, age, location, use, profile, diameter, gradient) were used for forecasting.
Main Results:
- The study successfully estimated the current condition of the Dresden sewer network.
- Deterioration trends were projected, highlighting the impact of inaction.
- The method provides probable dates for sewers reaching critical condition stages.
Conclusions:
- The developed forecasting method enables data-driven investment in sewer rehabilitation.
- The procedure aids in scheduling inspections for both uninspected and previously inspected sewers.
- Accurate condition forecasting supports optimized resource allocation for wastewater infrastructure maintenance.