Monitoring of Dynamic Bridge Behaviour Using Digital Image Correlation

Bridges are a critical part of North America’s transportation network that need to be assessed frequently to inform bridge management decision making. Visual inspections are usually implemented for this purpose, during which inspectors must observe and report any excess displacements or vibrations. Unfortunately, these visual inspections are subjective and often highly variable and so a monitoring technology that can provide quantitative measurements to supplement inspections is needed. Digital Image Correlation (DIC) is a novel monitoring technology that uses digital images to measure displacement fields without any contact with the bridge. In this research, DIC and accelerometers were used to investigate the dynamic response of a railway bridge reported to experience large lateral displacements. Displacements were estimated using accelerometer measurements and were compared to DIC measurements. It was shown that accelerometers can provide reasonable estimates of displacement for zero-mean lateral displacements. By comparing measurements in the girder and in the piers, it was shown that for the bridge monitored, the large lateral displacements originated in the steel casting bearings positioned above the piers, and not in the piers themselves. The use of DIC for evaluating the effectiveness of rehabilitation of the LaSalle Causeway lift bridge in Kingston, Ontario was also investigated. Vertical displacements were measured at midspan and at the lifting end of the bridge during a static test and under dynamic live loading. The bridge displacements were well within the operating limits, however a gap at the lifting end of the bridge was identified. Rehabilitation of the bridge was conducted and by comparing measurements before and after rehabilitation, it was shown that the gap was successfully closed. Finally, DIC was used to monitor the midspan vertical and lateral displacements in a monitoring campaign of five steel rail bridges. DIC was also used to evaluate the effectiveness of structural rehabilitation of the lateral bracing of a bridge. Simple finite element models are developed using DIC measurements of displacement. Several lessons learned throughout this monitoring campaign are discussed in the hope of aiding future researchers.

Adding Run-Time Monitoring to UML-RT by Modifying the Papyrus-RT Code Generator

In Model-Driven Engineering (MDE), the developer creates a model using a language such as Unified Modeling Language (UML) or UML for Real-Time (UML-RT) and uses tools such as Papyrus or Papyrus-RT that generate code for them based on the model they create. Tracing allows developers to get insights such as which events occur and timing information into their own application as it runs. We try to add monitoring capabilities using Linux Trace Toolkit: next generation (LTTng) to models created in UML-RT using Papyrus-RT. The implementation requires changing the code generator to add tracing statements for the events that the user wants to monitor to the generated code. We also change the makefile to automate the build process and we create an Extensible Markup Language (XML) file that allows developers to view their traces visually using Trace Compass, an Eclipse-based trace viewing tool. Finally, we validate our results using three models we create and trace.

On the feasibility of time-lapse superconducting gravimetry for reservoir monitoring

The feasibility of monitoring fluid flow subsurface processes that result in density changes, using the iGrav superconducting gravimeter, is investigated. Practical targets include steam-assisted gravity drainage (SAGD) bitumen depletion and water pumping from aquifers, for which there is currently a void in low-impact, inexpensive monitoring techniques. This study demonstrates that the iGrav has the potential to be applied to multi-scale and diverse reservoirs. Gravity and gravity gradient signals are forward modeled for a real SAGD reservoir at two time steps, and for surface-fed and groundwater-fed aquifer pumping models, to estimate signal strength and directional dependency of water flow. Time-lapse gravimetry on small-scale reservoirs exhibits two obstacles, namely, a µgal sensitivity requirement and high noise levels in the vicinity of the reservoir. In this study, both limitations are overcome by proposing (i) a portable superconducting gravimeter, and (ii) a pair of instruments under various baseline geometries. This results in improved spatial resolution for locating depletion zones, as well as the cancellation of noise common in both instruments. Results indicate that a pair of iGrav superconducting gravimeters meet the sensitivity requirements and the spatial focusing desired to monitor SAGD bitumen migration at the reservoir scales. For SAGD reservoirs, the well pair separation, reservoir depth, and survey sampling determine the resolvability of individual well pair depletion patterns during the steam chamber rising phase, and general reservoir depletion patterns during the steam chamber spreading phase. Results show that monitoring water table elevation changes due to pumping and tracking whether groundwater or surface water is being extracted are feasible.

Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.

Supporting Run-time Monitoring of UML-RT through Customizable Monitoring Configurations in PapyrusRT

Model Driven Engineering uses the principle that code can automatically be generated from software models which would potentially save time and cost of development. By this methodology, a systems structure and behaviour can be expressed in more abstract, high level terms without some of the accidental complexity that the use of a general purpose language can bring. Models are the actual implementation of the system unlike in traditional software development where models are often used for documentation purposes only. However once the code is generated from the model, testing and debugging activities tend to happen on the code level and the model is not updated. We believe that monitoring on the model level could potentially facilitate quality assurance activities as the errors are detected in the early phase of development. In this thesis, we create a Monitoring Configuration for an open source model driven engineering tool called PapyrusRT in Eclipse. We support the run-time monitoring of UML-RT elements with a tracing tool called LTTng. We annotate the model with monitoring information to be used by the code generator for adding tracepoint statements for the corresponding elements. We provide the option of a timing specification to discover latency errors on the model. We validate the results by creating and tracing real time models in PapyrusRT.

Supporting the Model-Driven Development of Real-time Embedded Systems with Run-Time Monitoring and Animation via Highly Customizable Code Generation

This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.