UTTiscaliWork Packages

work packages

The faculties execute work as specified in four packages:

WP1. Detecting and evaluating potential “problem” locations in a fast manner by thermal infrared (TIR) remote sensing,

WP2. Ground Penetrating Radar and TIR for site specific subsurface characterization for qualitative sewer condition assessment,

WP3. Locally quantifying the sewer condition by means of an in-pipe robotic inspection,

WP4. Building a subsurface information system, or toolkit, that supports objective sewer condition assessment.

The PhD project of Jonathan Franko Hempenius covers WP 1 and 2. The project of Hengameh Noshahri covers WP 3 and 4.


When using TIR techniques for subsurface assessments, use is made of differences in thermal inertia. Leakages and voids, generally show rather different thermal characteristics as compared to the bedding material.

WP 1

Task 1.1. Determination of favorable sensing conditions for the TIR-based sewer condition assessment in terms of leakage and poor backfill (or erosion voids). We will build upon the work of Romano (2012) and Alkhaier et al. (2012) who reported on factors influencing the determination of sub-surface conditions based on TIR observations. In addition use will be made of the WRS Urban Observation site.

Task 1.2. Development of a TIR-based methodology, or scheme, to “extract” the aforementioned problem areas where use will be made of the results and observations from Task 1.1.

Task 1.3. Validation and “calibration” of the developed scheme at the UT campus and Safety Campus field lab sites. Sewer conditions in terms of leakage and backfill will be simulated to assess the scheme’s performance. Testing of the methodology in “real life” situations will take place upon completion of WP 2 and WP 3, in close co-operation with RIONED.

Task 1.4. Integration with the GPR-based methodology resulting in a spatially distributed mapping of the remotely sensed sewer condition.

WP 2

Ad WP 2. GPR works by sending a tiny pulse of energy into a medium and recording the strength and the time required for the return of any reflected signal. The strength, or amplitude, of the reflection is determined by the contrast in the dielectric constants and conductivities inside the medium.

Task 2.1. Subsurface condition characterization and sewer pipe location determination. Methods are needed to not only locate buried sewer pipe, but to also determine if the pipes are functioning properly with respect to sewage transport. The primary focus of this task is to locate buried sewer pipe, and then determine if GPR provides insight into water conveyance functionality, where we will build on the work of Allred and Redman (2010), carried out for agricultural drainage pipes.

Task 2.2 Volumetric water content estimation One of the prime indicators of a damaged sewer is excess water in the surrounding of the damaged location, leading to locally increased water content. This can be identified using GPR through so-called normal‐moveout velocity analysis (Greaves et al, 1996; Rehman et al, 2016) combined with signal-loss analysis due to excessive water presence. By applying multiple velocity analyses on the stacked radar image we can determine subsurface water content and interval velocities. With results from Task 2.1, the velocity is converted to volumetric water content, which will be compared to the TIR measurements.

Task 2.3 Amplitude and attenuation analysis. A final task is to derive information on actual sewer pipe integrity. Based on the reflections from the sewer pipe and spatial variations in amplitude of the sewer pipe reflections an assessment can be made on sewer pipe materials and condition. Combined with information on the subsurface conditions, like volumetric water content, and spatial variations therein we can assess the sewer pipe conditions.

Task 2.4. Integration with the TIR-based methodology; same as Task 1.4.


Ad WP 3. Goal is to take steps toward autonomous inspection and feature detection by augmenting current (visual) inspection methodology with more layers of sensor information, providing the necessary quantitative assessment. In this first step automatic warnings based on thresholds in the acquired measurement data will alert the human observer to points of interest of points with increased risks. Data will be integrated in the assessment system as proposed in WP4.

Task 3.1. Identifying suitable sensing methodologies for detection of the key failure mechanisms listed in Task 4.1. One of the primary concerns is detection of influx or leakage of water. For integrity measurement a possible existing candidate is a laser profiling system integrated with a camera system. For sensing moisture and leakage additional sensing principles (acoustic, conductive, capacitive) will be investigated.

Task 3.2. Prototypes of the chosen sensing equipment will be developed for in-situ testing. Based on an existing robot platform (provided by ID-tec) interfacing hardware (both in mechanical and electronic domain) and interfacing software for data exchange will be developed. Besides the to be developed sensor and the profiling sensor a localisation sensing system and orientation sensor (IMU) will be added. A rapid prototyping methodology in an iterative cycle will be used to ensure practical applicability.

Task 3.3 In situ testing and acquisition of measurement data. Goal is to acquire data alongside the ‘normal’ (panoramic) video capture and provide an operator with extra ‘layers’ of information. Based on thresholds (performance indicators) set by the operator, the system will give warnings on encountering anomalies in the dataset, thus initially focussing the operator's effort and attention to relevant sections.

Task 3.4 Integration of the acquired sensing data with the smart subsurface system as described in WP 4.


Ad WP 4. Build a “smart” subsurface info system, supporting objective sewer condition assessment.

Task 4.1. Identifying the key failure mechanisms for sewage systems (internally, externally, on network level and component level). Existing practice documentation will be used to identify the most important factors that cause failures in sewage systems. This task identifies these factors and selects/categorizes the factors that are quantifiable and measurable via TIR, GPR and in-situ measurements.

Task 4.2. Developing an information scheme for sewer condition assessment that standardizes storage and exchange of sensor readings from WP 1-3. This task aims at developing a knowledge base for such an information system which complies to existing languages and structures such as RioNED’s GWSW. The knowledge base should contain the most important information that needs to be stored in the information system (e.g. object descriptions, object attributes, relations etc.).

Task 4.3. Identifying performance indicators and threshold values to meaningfully assess conditions based on sensor readings. To do so, this task aims at identifying the critical values of sewage conditions. In other words, the task identifies the minimal values of performance factors for a sewage system (e.g. temperature differences between pipe and bedding, cover-layer thickness as well as structural properties)

Task 4.4. Developing an information system that processes sensor readings and supports three stages. This task integrates Tasks 4.1-4.3. For all-level measurements, the programme; (1) interprets sensor data, (2) stores it using the information scheme standard, and (3) compares the stored values with threshold performance values to support condition assessment. The system will be delivered as open-source piece of software that integrates with existing formats for data sharing and integration.