Embedding techniques for assessing debris-induced scour within practice

This is the final version.INTRODUCTION Background In the last decades, scientists, engineers and practitioners have become increasingly aware of the risks from debris blockage at bridge piers. Large wood is transported in rivers especially during flood events, in which debris could be entrapped by structures such as bridge piers, and may initiate an accumulation. The localised acceleration of the flow can substantially exacerbate the scour at the base of the pier that would normally occur with the pier alone, and consequently the risk of structural damage or collapse of the structure. Piers that have spread foundations, as most of the UK masonry bridge stock, are more prone to this problem. It was estimated that in the last century approximately more than a third of the bridge failures in the UK caused by scour involved the accumulation of woody debris (Benn, 2013). Similar figures were also observed in the US (Diehl, 1997). In 2015 the University of Exeter was awarded an EPSRC grant for the project Risk Assessment of Masonry Bridges Under Flood Conditions: Hydrodynamic Effects of Debris Blockage and Scour, the primary aim of which was the development of a robust method for estimating the scour depth at a bridge pier with debris accumulations. This research involved a comprehensive experimental investigation at the University of Exeter using a large flume. A total of 46 experiments was carried out. The results from these experiments along with those from others in literature were used to develop a functional relationship for predicting the maximum scour hole depth at a bridge pier. To implement the results from the research within the practice of non-academic partners, the University of Exeter in partnership with Devon County Council (DCC) started a project funded under an EPSRC Impact Accelerator Account (IAA) award. The IAA award focused specifically on trialling the methodology on DCC’s assets and using the knowledge to propose amendments to the current scour assessment practice, as recommended by the Highways England (HE) guidance document BD 97/12. BD 97/12, in its current form, acknowledges the importance of debris accumulations, but does not provide a systematic methodology to assess the effects of debris on scour. This report summarises the findings from the work undertaken as part of the IAA award. In particular, it summarises the proposed amendments to BD 97/12 and illustrates the impact of these changes on scour assessment practice via a number of full-scale case studies. [...]Engineering and Physical Sciences Research Council (EPSRC)Devon County Counci

Trapping large wood debris in rivers: experimental study on a novel debris retention system (article)

This is the author accepted manuscript. The final version is available from the American Society of Civil Engineers via the DOI in this record.The dataset associated with this article is available in ORE at: https://doi.org/10.24378/exe.2703Large wood debris can cause critical damage to bridges and other riverine structures, and increase flood risk. Although their effects on hydrodynamic actions and flood levels have been investigated in recent research, little effort has been devoted to reducing the amount of debris that can accumulate at structures. This paper proposes and experimentally tests a new type of large wood debris retention system in which a series of alternating porous and rack-type modules, is placed in-line with the current. Laboratory tests illustrate that the proposed retention system can offer high levels of efficiency in trapping large wood in rivers. The geometrical features of the structure are observed to play a major role and can be carefully chosen to optimise trapping efficiency. Results also show that large wood debris trapped by these structures have limited effects on the increase of the upstream water levels. Further development of the solution proposed in this work can pave the way for use of low-cost, highly-effective debris retention systems for effective river management and large wood debris removal in practice.Engineering and Physical Sciences Research Council (EPSRC)Devon County Counci

Data-driven approaches for measurement interpretation: analysing integrated thermal and vehicular response in bridge structural health monitoring

A comprehensive evaluation of a structure's performance based on quasi-static measurements requires consideration of the response due to all applied loads. For the majority of short- and medium-span bridges, temperature and vehicular loads are the main drivers of structural deformations. This paper therefore evaluates the following two hypotheses: (i) knowledge of loads and their positions, and temperature distributions can be used to accurately predict structural response, and (ii) the difference between predicted and measured response at various sensor locations can form the basis of anomaly detection techniques. It introduces a measurement interpretation approach that merges the regression-based thermal response prediction methodology that was proposed previously by the authors with a novel methodology for predicting traffic-induced response. The approach first removes both environmentally (temperature) and operationally (traffic) induced trends from measurement time series of structural response. The resulting time series is then analysed using anomaly detection techniques. Experimental data collected from a laboratory truss is used for the evaluation of this approach. Results show that (i) traffic-induced response is recognized once thermal effects are removed, and (ii) information of the location and weight of a vehicle can be used to generate regression models that predict traffic-induced response. As a whole, the approach is shown to be capable of detecting damage by analysing measurements that include both vehicular and thermal response

A Method for Evaluating Local Scour Depth at Bridge Piers due to Debris Accumulation

This is the author accepted manuscript. The final version is available from Thomas Telford via the DOI in this record This paper introduces a novel method for evaluating the effect of debris accumulation on local scour depth at bridge piers. The concept of a debris factor is proposed to replace the current effective and equivalent pier width approaches that have been shown to overestimate debris-induced scour in many instances. The concept enables a simpler, more direct and realistic estimation of the change in local scour depth due to debris since it accounts for (i) debris length (streamwise), width (spanwise) and thickness (depth wise), and (ii) the influence of debris elevation in flow, i.e. is applicable for free-surface debris, submerged debris, or debris resting on the stream bed. The concept works with all existing local scour equations alongside other factors that influence scour depth such as flow angle of attack and pier shape. The mathematical model that underpins the proposed concept is derived through multiple linear regression on experimental data obtained at Exeter and elsewhere. The proposed method is shown to improve accuracy by at least 24% and 5% in comparison to the effective and equivalent pier width approaches, respectively. More importantly, the method is shown to be robust, providing highly consistent results with significantly less uncertainty.Engineering and Physical Sciences Research Council (EPSRC

Hybrid approach combining modelling and measurement for fatigue damage estimation of welded connections in bridges

This is the author accepted manuscript. The final version is available from Taylor & Francis (Routledge) via the DOI in this record.The fatigue life of structural steel bridges is governed by the time history of in-situ stresses at its fatigue-critical structural details under service conditions. However, these stresses are often not directly and accurately measurable due to the complex geometry of the detail or due to access restrictions. This paper proposes a novel methodology to address this challenge. The methodology infers stresses at fatigue8 critical locations by combining in-situ strain measurements taken further away from a critical location in a full-scale bridge. Strains measured at various points around the physical welded connection are used to compute the forces and moments applied at the connection. These forces are then applied to a finite element model of the connection to predict the stresses that are required to evaluate the hot spot stresses. The developed methodology is illustrated for a welded connection in a full-scale bridge. Results show that the predicted time history of hot spot stress is accurate and much more realistic than those obtained from numerical simulations. Also, the study demonstrates that the proposed methodology is applicable for interpreting measurements from full-scale bridges and can be integrated within a measurement interpretation platform for continuous bridge monitoringThe Higher Committee for Education Development in Iraq (HCED IRAQ

Characterising the importance of porosity of large woody debris accumulations at single bridge piers on localised scour (article)

This is the author accepted manuscript.Data availability: The data used for supporting the results presented in this paper are openly available in ORE at: https://doi.org/10.24378/exe.4744The accumulation of large woody debris (LWD) at bridge piers is a serious hazard to the structural integrity of bridges across watercourses worldwide. The exacerbated scour that can directly result from LWD accumulations can lead to major structural damage or even catastrophic collapse. Recent research has led to empirical equations to estimate the scour depth for given LWD accumulation size; however these are mostly based on experimental tests with prismatic and impervious solid LWD accumulations, ignoring field observations that have shown that accumulations are neither impervious nor prismatic but are porous with inverted conical shapes. In this study, we therefore investigate the effects of porous LWD accumulations having shapes commonly observed in the field on scour holes. Results reveal that LWD size and shape, and flow characteristics are the primary factors influencing the erosion of sediments at the base of bridge piers. However, the porosity of accumulations is also observed to have a considerable effect on the size and maximum depth of scour holes. In particular, porous LWD reduce the maximum scour depth by up to 50% (and on average in the range of 5-25%) relative to the respective solid impervious accumulation. The results shown in this study also provide a practical tool for arriving at more realistic and less conservative estimates of scour depths at bridge piers when affected by LWD accumulations.Engineering and Physical Sciences Research Council (EPSRC)Devon County Counci

Configuring and enhancing measurement systems for damage identification

Engineers often decide to measure structures upon signs of damage to determine its extent and its location. Measurement locations, sensor types and numbers of sensors are selected based on judgment and experience. Rational and systematic methods for evaluating structural performance can help make better decisions. This paper proposes strategies for supporting two measurement tasks related to structural health monitoring – (1) installing an initial measurement system and (2) enhancing measurement systems for subsequent measurements once data interpretation has occurred. The strategies are based on previous research into system identification using multiple models. A global optimization approach is used to design the initial measurement system. Then a greedy strategy is used to select measurement locations with maximum entropy among candidate model predictions. Two bridges are used to illustrate the proposed methodology. First, a railway truss bridge in Zangenberg, Germany is examined. For illustration purposes, the model space is reduced by assuming only a few types of possible damage in the truss bridge. The approach is then applied to the Schwandbach bridge in Switzerland, where a broad set of damage scenarios is evaluated. For the truss bridge, the approach correctly identifies the damage that represents the behaviour of the structure. For the Schwandbach bridge, the approach is able to significantly reduce the number of candidate models. Values of candidate model parameters are also useful for planning inspection and eventual repair

Physics-informed neural networks for structural health monitoring: a case study for Kirchhoff–Love plates

This is the final version. Available on open access from Cambridge University Press via the DOI in this recordData Availability Statement. A demonstrative code that implements the proposed method is openly available at github (https://github.com/AnmarAl-Adly/PINNs_FOR_SHM.git). The data used throughout this paper were synthetically generated. The authors have ensured to provide sufficient information to replicate the analytical and numerical models used to generate the synthetic data.Physics-informed neural networks (PINNs), which are a recent development and incorporate physics-based knowledge into neural networks (NNs) in the form of constraints (e.g., displacement and force boundary conditions, governing equations) or loss function, offer promise for generating digital twins of physical systems and processes. Although recent advances in PINNs have begun to address the challenges of structural health monitoring (SHM), significant issues remain unresolved, particularly in modelling the governing physics through partial differential equations (PDEs) under temporally variable loading. This paper investigates potential solutions to these challenges. Specifically, the paper will examine the performance of PINNs that enforce a structure’s boundary conditions and utilises sensor data from a limited number of locations within it. Satisfaction of these boundary conditions, which can be expressed as derivatives of deflections and computed through automatic differentiation, is achieved through an additional term in the loss function. We also examine a PINN’s ability to predict deflections and internal forces for loads that have not been included in the training data sets. Three case studies are utilised to demonstrate and evaluate the proposed ideas. Case Study (1) assumes a constant uniformly distributed load (UDL) and analyses several setups of PINNs for four distinct simulated measurement cases obtained from a finite element model. In Case Study (2), the UDL is included as an input variable for the NNs. Results from these two case studies show that the modelling of the structure’s boundary conditions enables the PINNs to approximate the behaviour of the structure without requiring satisfaction of the governing PDEs across the whole domain of the plate. In Case Study (3), we explore the efficacy of PINNs in a setting resembling real-world conditions, wherein the simulated measurement data incorporates deviations from idealised boundary conditions and contains measurement noise. Results illustrate that PINNs can effectivelyHigher Committee for Education Development in Iraq (HCED

Performance of signal processing techniques for anomaly detection using a temperature-based measurement interpretation approach

This is the final version. Available on open access from Springer via the DOI in this record.This study investigates the effectiveness of four signal processing techniques in supporting a data-driven strategy for anomaly detection that relies on correlations between measurements of bridge response and temperature distributions. The strategy builds upon the regression-based thermal response prediction methodology which was developed by the authors to accurately predict thermal response from distributed temperature measurements. The four techniques that are investigated as part of the strategy are moving fast Fourier transform, moving principal component analysis, signal subtraction method and cointegration method. The techniques are compared on measurement time-histories from a laboratory structure and a footbridge at the National Physical Laboratory. Results demonstrate that anomaly events can be detected successfully depending on the magnitude and duration of the event and the choice of an appropriate anomaly detection technique