Bridge Structrural Health Monitoring Using a Cyber-Physical System Framework

Highway bridges are critical infrastructure elements supporting commercial and personal traffic. However, bridge deterioration coupled with insufficient funding for bridge maintenance remain a chronic problem faced by the United States. With the emergence of wireless sensor networks (WSN), structural health monitoring (SHM) has gained increasing attention over the last decade as a viable means of assessing bridge structural conditions. While intensive research has been conducted on bridge SHM, few studies have clearly demonstrated the value of SHM to bridge owners, especially using real-world implementation in operational bridges. This thesis first aims to enhance existing bridge SHM implementations by developing a cyber-physical system (CPS) framework that integrates multiple SHM systems with traffic cameras and weigh-in-motion (WIM) stations located along the same corridor. To demonstrate the efficacy of the proposed CPS, a 20-mile segment of the northbound I-275 highway in Michigan is instrumented with four traffic cameras, two bridge SHM systems and a WIM station. Real-time truck detection algorithms are deployed to intelligently trigger the SHM systems for data collection during large truck events. Such a triggering approach can improve data acquisition efficiency by up to 70% (as compared to schedule-based data collection). Leveraging computer vision-based truck re-identification techniques applied to videos from the traffic cameras along the corridor, a two-stage pipeline is proposed to fuse bridge input data (i.e. truck loads as measured by the WIM station) and output data (i.e. bridge responses to a given truck load). From August 2017 to April 2019, over 20,000 truck events have been captured by the CPS. To the author’s best knowledge, the CPS implementation is the first of its kind in the nation and offers large volume of heterogeneous input-output data thereby opening new opportunities for novel data-driven bridge condition assessment methods. Built upon the developed CPS framework, the second half of the thesis focuses on use of the data in real-world bridge asset management applications. Long-term bridge strain response data is used to investigate and model composite action behavior exhibited in slab-on-girder highway bridges. Partial composite action is observed and quantified over negative bending regions of the bridge through the monitoring of slip strain at the girder-deck interface. It is revealed that undesired composite action over negative bending regions might be a cause of deck deterioration. The analysis performed on modeling composite action is a first in studying composite behavior in operational bridges with in-situ SHM measurements. Second, a data-driven analytical method is proposed to derive site-specific parameters such as dynamic load allowance and unit influence lines for bridge load rating using the input-output data. The resulting rating factors more rationally account for the bridge's systematic behavior leading to more accurate rating of a bridge's load-carrying capacity. Third, the proposed CPS framework is shown capable of measuring highway traffic loads. The paired WIM and bridge response data is used for training a learning-based bridge WIM system where truck weight characteristics such as axle weights are derived directly using corresponding bridge response measurements. Such an approach is successfully utilized to extend the functionality of an existing bridge SHM system for truck weighing purposes achieving precision requirements of a Type-II WIM station (e.g. vehicle gross weight error of less than 15%).PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163210/1/rayhou_1.pd

North Lake Ave Bridge Design

North Lake Ave is a road located in Worcester, MA that has been suffering from erosion for many years. Conceptual plans have been made to create a linear park and convert this road into a one-way. Options have been considered to address the erosion and collapse of the road. The design for a retaining wall and bridge will be compared based on safety, economic, constructability, environmental, societal and sustainability criteria. The design for the bridge includes the superstructure, substructure, and foundation, in compliance with AASHTO LRFD Bridge Design Specifications

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Wireless Monitoring Systems for Long-Term Reliability Assessment of Bridge Structures based on Compressed Sensing and Data-Driven Interrogation Methods.

The state of the nation’s highway bridges has garnered significant public attention due to large inventories of aging assets and insufficient funds for repair. Current management methods are based on visual inspections that have many known limitations including reliance on surface evidence of deterioration and subjectivity introduced by trained inspectors. To address the limitations of current inspection practice, structural health monitoring (SHM) systems can be used to provide quantitative measures of structural behavior and an objective basis for condition assessment. SHM systems are intended to be a cost effective monitoring technology that also automates the processing of data to characterize damage and provide decision information to asset managers. Unfortunately, this realization of SHM systems does not currently exist. In order for SHM to be realized as a decision support tool for bridge owners engaged in performance- and risk-based asset management, technological hurdles must still be overcome. This thesis focuses on advancing wireless SHM systems. An innovative wireless monitoring system was designed for permanent deployment on bridges in cold northern climates which pose an added challenge as the potential for solar harvesting is reduced and battery charging is slowed. First, efforts advancing energy efficient usage strategies for WSNs were made. With WSN energy consumption proportional to the amount of data transmitted, data reduction strategies are prioritized. A novel data compression paradigm termed compressed sensing is advanced for embedment in a wireless sensor microcontroller. In addition, fatigue monitoring algorithms are embedded for local data processing leading to dramatic data reductions. In the second part of the thesis, a radical top-down design strategy (in contrast to global vibration strategies) for a monitoring system is explored to target specific damage concerns of bridge owners. Data-driven algorithmic approaches are created for statistical performance characterization of long-term bridge response. Statistical process control and reliability index monitoring are advanced as a scalable and autonomous means of transforming data into information relevant to bridge risk management. Validation of the wireless monitoring system architecture is made using the Telegraph Road Bridge (Monroe, Michigan), a multi-girder short-span highway bridge that represents a major fraction of the U.S. national inventory.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116749/1/ocosean_1.pd

Extending Cyber-Physical Systems to Support Stakeholder Decisions Under Resource and User Constraints: Applications to Intelligent Infrastructure and Social Urban Systems

In recent years, rapid urbanization has imposed greater load demands on physical infrastructure while placing stressors (e.g., pollution, congestion, social inequity) on social systems. Despite these challenges, opportunities are emerging from the unprecedented proliferation of information technologies enabling ubiquitous sensing, cloud computing, and full-scale automation. Together, these advancements enable “intelligent” systems that promise to enhance the operation of the built environment. Even with these advancements, the ability of professionals to “sense for decisions” —data-driven decision processes based on sensed data that have quantifiable returns on investment—remains unrealized for an entire class of problems. In response, this dissertation builds a rigorous foundation enabling stakeholders to use sensor data to inform decisions in two applications: infrastructure asset management and community-engaged decision making. This dissertation aligns sensing strategies with decisions governing infrastructure management by extending the role of reliability methods to quantify system performance. First, the reliability index is used as a scalar measure of the safety (i.e., failure probability) that is extracted from monitoring data to assess structural condition relative to a failure limit state. As an example, long-term data collected from a wireless sensing network (WSN) installed on the Harahan Bridge (Memphis, TN) is used in a reliability framework to track the fatigue life of critical eyebar assemblies. The proposed reliability-based SHM framework is then generalized to formally and more broadly link SHM data with condition ratings (CRs) because inspector-assigned CRs remain the primary starting point for asset management decisions made in practice today. While reliability methods historically quantify safety with respect to a single failure limit state, this work demonstrates that there exist measurable reliability index values associated with “lower” limit states below failure that more richly characterize structural performance and rationally map to CR scales. Consequently, monitoring data can be used to assign CRs based on quantitative information encompassing the measurable damage domain, as opposed to relying on visual inspection. This work reflects the first-ever SHM framework to explicitly map monitoring data to actionable decisions and is validated using a WSN on the Telegraph Road Bridge (TRB) (Monroe, MI). A primary challenge faced by solar-powered WSNs is their stringent energy constraints. For decision-making processes relying on statistical estimation of performance, the utility of data should be considered to optimize the data collection process given these constraints. This dissertation proposes a novel stochastic data collection and transmission policy for WSNs that minimizes the variance of a measured process’ estimated parameters subject to constraints imposed by energy and data buffer sizes, stochastic models of energy and event arrivals, the value of measured data, and temporal death. Numerical results based on one-year of data collected from the TRB illustrate the gains achieved by implementing the optimal policy to obtain response data used to estimate the reliability index. Finally, this dissertation extends the work performed in WSN and sense-for-decision frameworks by exploring their role in community-based decision making. This work poses societal engagement as a necessary entry point to urban sensing efforts because members of under-resourced communities are vulnerable to lack of access to data and information. A novel, low-power WSN architecture is presented that functions as a user-friendly sensing solution that communities can rapidly deploy. Applying this platform, transformative work to “democratize” data is proposed in which members of vulnerable communities collect data and generate insights that inform their decision-making strategies.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162898/1/kaflanig_1.pd

Development of a decision support system for assessment of mobile bridges

The development of a prototype Decision Support System (DSS) for the condition assessment of the Armored Vehicle Launched Bridge (AVLB) has been demonstrated in the current work. AVLB is a mobile bridge that has been used by the US Army for tank and assault vehicle crossing. It is employed for spanning short gaps of 50 feet or less in the terrain. The condition assessment of such bridges, to ensure safety of personnel and tank, is of strategic importance. The methodology of the prototype DSS is based on a refined visual inspection procedure and a previously established vibration measurement technique.;Conforming to the design requirements, the DSS has been developed as an Internet based, interactive application, and is integrated with an automated vibration measurement system. The web-based DSS, which incorporates an expert system and a database system, can be run from a web-browser. The development of the system, as described in this thesis, involved: identification of important visual and vibration inspection parameters; development of an expert system for bridge condition assessment, based on these parameters; and design of a database for storing important inspection data and other vital bridge records. The prototype system has been validated through limited test runs. Discussion on further verification and validation issues has also been put forth in this work.;The unique feature of this DSS is its accessibility through the Internet, which is practical considering that the AVLB is deployed worldwide. With a central database, this system provides a useful research tool for further study of the AVLB behavior and damage mechanisms, and can be used to establish failure prediction model and remaining life assessment

D5.2: Digital-Twin Enabled multi-physics simulation and model matching

This deliverable presents a report on the developed actions and results concerning Digital-Twin-enabled multi-physics simulations and model matching. Enabling meaningful simulations within new human-infrastructure interfaces such as Digital twins is paramount. Accessing the power of simulation opens manifold new ways for observation, understanding, analysis and prediction of numerous scenarios to which the asset may be faced. As a result, managers can access countless ways of acquiring synthetic data for eventually taking better, more informed decisions. The tool MatchFEM is conceived as a fundamental part of this endeavour. From a broad perspective, the tool is aimed at contextualizing information between multi-physics simulations and vaster information constructs such as digital twins. 3D geometries, measurements, simulations, and asset management coexist in such information constructs. This report provides guidance for the generation of comprehensive adequate initial conditions of the assets to be used during their life span using a DT basis. From a more specific focus, this deliverable presents a set of exemplary recommendations for the development of DT-enabled load tests of assets in the form of a white paper. The deliverable also belongs to a vaster suit of documents encountered in WP5 of the Ashvin project in which measurements, models and assessments are described thoroughly.Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPreprin