Abstract
Bridge scour is a major cause of bridge failures and has emerged as a significant concern for bridge engineers. Most previous studies focus on investigating causes of the scour but not on its consequences, in other words, very few studies have been carried out on the response and feature changes of structures due to scour. Therefore, the present paper mainly studied the scour effect on a single pile or pier. A theoretical solution was derived first to obtain the relationship between the scour depth and the pile response, including static and dynamic responses. Since the expression of the solution is tedious and not easy to understand, two examples were used for the demonstration and parametric study. Based on the numerical observation, the present study proposed three possible methods for detecting and monitoring the bridge scour. Finally, a monitoring system using fiber optic sensors was designed and tested in the laboratory to verify the theoretical and numerical results and the monitoring mechanisms.
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Changes were made to this article on 10 April 2013. The acknowledgments section was corrected.
1. Introduction
Bridge scour is a significant issue in the United States. In the past 30 years, more than 1000 bridges have collapsed and approximately 60% of their failures are related to foundation scour (Shirhole and Holt 1991, Lagasse and Richardson 2001). On-going screening and evaluation of the vulnerability of the nation's highway bridges to scour by different state departments of transportation have identified more than 18 000 bridges that are considered as scour-critical and in need of repair or replacement. Furthermore, more than 100 000 bridges over water in the United States have 'unknown foundations' (Lagasse et al 1995), which means that their vulnerability to scour cannot be calculated by normal hydraulic and geotechnical analysis procedures. Therefore, there is an urgent need for innovative, effective, and economical techniques to detect and monitor foundation scour.
Bridge scour is a very complicated process that involves the interaction between the flow, the erodible riverbed, and the bridge pier or abutment. Deng and Cai (2010) presented a comprehensive review on approaches for modeling and predicting bridge scour. In the past few decades, the previous research mainly focused on studying the scour mechanism by developing numerical models (Melville and Raudkivi 1977, Young et al 1998, Kassem et al 2003) as well as laboratory models (Umbrell et al 1998, Sheppard and William 2006). Based on these studies, different methods to predict bridge scour using the available information prior to or during flood events have been proposed, including empirical equations (Laursen and Toch 1956, Breusers et al 1977, Melville and Sutherland 1988, Lim 1997, Heza et al 2007), and neural network methods (Lee et al 2007, Mohammad et al 2009) to establish a relationship between the scour depth and various factors.
A more direct approach is to investigate the consequences of scour, i.e., the structural response and feature changes of the bridge due to scour. However, until now only a few studies have been carried out on this topic. Han et al (2010) studied the influence of scour on the seismic performance of foundations through several elasto-plastic static pushover analyses. Lin et al (2010) studied scour effects on the response of laterally loaded piles, considering the stress history of the remaining sand. Foti and Sabia (2011) performed numerical simulations to assess the sensitivity of the overall dynamic response of the system to foundation scour.
The present study mainly focuses on the scour effect on a single pile or pier, from which scour monitoring strategies can be developed. By considering the scour depth as a variable, piecewise differential equations were derived first to establish the relationship between the scour depth and the pile response under static loading and free vibration. A program in MATLAB was developed to obtain the solution. As the solution is tedious, two examples were then used to demonstrate and parametrically study the structural response due to changes of different factors. Based on observations of these analyses, the present study proposed three possible methods for detecting and monitoring bridge scour. Finally, a monitoring system using fiber optic sensors has been designed and tested in the laboratory.
2. Analytical study
2.1. Static solution
Beams and columns supported along their length are very common structure configurations, and the most routine method to treat the elastic foundation is the Winkler model (Ding 1993 and Coskun 2003). A pile embedded in soil is similar to a beam resting on a Winkler elastic foundation. Herein, assume the pile is fully buried in soil at the beginning. After the soil is eroded, the top part of the pile is exposed to the water flow, as shown in figure 1. The pile length is L with the origin at the top of the pile, and the unsupported depth is l, which is also the loading length with a distributed load q(x). The unsupported length l, due to initial scour and/or initial construction, is generically called the initial scour depth hereafter. The rest of the pile is embedded in the soil with an elastic spring coefficient k(x). The governing equation of the pile with a uniform cross-section and flexural rigidity and partially embedded in soil as shown in figure 1 can be expressed as
where w(x) is the lateral displacement of the pile. Herein, k(x) is considered as a constant. The general solution of equation (1) consists of two parts, namely, the deflection of the pile is divided piecewise as
where β = (k/4EI)1/4, and Ci and Ai (i = 1–4) are unknown constants. The boundary condition at x = l requires the geometric continuity of displacement and slope, and the continuity of bending moment and shear force, which are expressed as
Four additional conditions can be derived from boundaries at x = 0 and x = L. For a free-fixed pile, we have:
From and , we have C1 = C2 = 0. This leads to six condition equations to solve six constants, C3,C4 and Ai (i = 1–4). The six equations can be rewritten in the matrix form as
where
This equation can be solved very conveniently by mathematical tools, such as Mathcad or MATLAB. The six constants, expressed as a function of the scour depth and other variables, are not presented here because they are very tedious. For a pinned–pinned pile, the boundary conditions are expressed as
and equations and solutions can be similarly obtained.
2.2. Dynamic solution
As for the dynamic free vibration, the equation of motion of the same system is derived as
where w(x,t) is the time-dependent displacement of the pile, ρ is the mass density, and A is the cross-section area. The coefficient k(x) is also considered as a constant, K. A general solution can be obtained easily by separating the variables into time and space domains using
The solution of the governing equation thus reduces to that of
in which . The characteristic roots of equation (6b) are derived as
Depending on the relationship between λ4 and K/EI, different solutions can be obtained next.
If λ4 > K/EI, the general solution is
where .
If λ4 < K/EI,
where .
If λ4 = K/EI, namely, ω2 = K/ρA,
Similar to the static solution, the boundary condition at x = l requires the geometric continuity of displacement and slope, and the continuity of bending moment and shear force. They are expressed as:
Four additional conditions from the boundaries at x = 0 and x = L depend on the particular geometry under consideration. For a free-fixed pile, we have:
From and , we have C1 = C3 and C2 = C4. The remaining six equations can be rewritten in the matrix form as:
The frequency equation is given by setting the determinant of the coefficient matrix M to be zero, i.e., |M| = 0. Different coefficient matrices can be derived for the three cases discussed above. Therefore, the natural frequency in different ranges should be solved by different frequency equations derived from the corresponding coefficient matrix, as described below.
If , i.e. λ4 > K/EI, the coefficient matrix is derived from equation (7) and denoted as M1. The natural frequencies are obtained by solving |M1| = 0.
If , i.e. λ4 < K/EI, the coefficient matrix is derived from equation (8) and denoted as M2. The natural frequencies are obtained by solving |M2| = 0.
If , the natural frequencies are automatically obtained.
2.3. Numerical examples and parametric analyses
Example 1 On the basis of the above analytical solution, an example was used for a demonstration. A square concrete pile with properties: L = 24.38 m (40 ft), A = 0.37 m2 (24 × 24 in2),EI = 2.48 × 108 N m−2 (599 424 kips ft2), and q = 146 kN m−1 (10 kips ft−1). The elastic coefficient of soil per unit is k = 2.76 × 105 kN m−2 (5760 kips ft−2). The pile head is free and the pile bottom is assumed to be fixed. A program was developed in MATLAB to solve the analytical equations. In the case of l = L, the pile without soil supporting is identical to a cantilever beam with a distributed loading, which is a special case and can be used for validation. Figure 2 shows that the pile deflections of both cases (cantilever beam and l/L = 1) are exactly the same as they are supposed to be, which validates the numerical solution procedure of the present study.
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Standard imageThe scour ratio is defined as the ratio between the length without soil supporting and the pile length, l/L, and ranges from 0 to 1. The pile deflection and moment at various scour ratios are shown in figures 2 and 3. It can be easily seen that the pile displacement, moment and the location of the maximum moment increase with the increase of the scour ratio. There exists a turning point in the moment curve at a location close to the interface between the water and soil. More details will be described in the next section.
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Standard imageFigure 4 shows the pile displacement at different positions versus the scour ratio and all the curves have the same trend. Figure 5 shows the pile moment (curvature) at different positions versus the scour ratio. It is found that for any position of the pile, if it is buried deeply in the soil, its moment is not significant. Only if the scour depth approaches that position does the moment become significant. Take the x = 0.8L section as an example. As the scour ratio increases from 0 to about 0.6, the moment of this section is small and hardly changes because the section is buried in the soil. However, when the scour ratio is larger than 0.6, the moment increases quickly from a small negative value to a positive value. It reaches a maximum at a scour ratio of 0.8 and remains constant since the section is totally exposed to the water at and after this scour ratio. Figures 6 and 7 demonstrate the influence of pile stiffness, represented by beta = EI/k, and soil stiffness, represented by k.
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Standard imageExample 2 A pile similar to example 1 was adopted for a demonstration of the dynamic solution: L = 24.38 m (40 ft), A = 0.37 m2 (24 × 24 in2), E = 2.15 × 1010 Pa (3122 ksi), I = 0.0115 m4 (1.333 ft4), and density = 2403 kg m−3 (150 pcf). In order to validate the relationship between ρA and K for different cases, the coefficient of soil here is 2760 kN m−2 (57.6 kips ft−2). The pile head is free and the pile bottom is assumed to be fixed. A program was developed in MATLAB to obtain the frequency equation from the determinant and then to solve the equations. Again, the special case of l = L was used for verification. The first four natural frequencies from the present study are 0.4957 Hz, 3.1059 Hz, 8.6986 Hz and 17.038 Hz, respectively, while from the reference (Clough and Penzien 2003) they are 0.4957, 3.1065, 8.6992 and 17.0459 Hz, which are very close to each other.
Figures 8 and 9 show the first and fourth natural frequencies of the pile versus the scour ratio. The natural frequency decreases as the scour ratio increases, with the frequency of the first mode dropping much faster than that of the fourth mode. It means that the scour effect on the lower mode is more significant than on the higher mode, which will benefit the scour monitoring discussed later. Figure 10 shows the effect of the soil stiffness on the first natural frequency, mainly affecting the natural frequency when the scour ratio is small.
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Standard image3. Proposed methods for scour detection and monitoring
Many methods have been developed for short-term detection and long-term monitoring of bridge scour. In the early days, methods based on geophysical techniques, such as radar and sonar, were employed to identify the scour depth. However, most of them have found very limited applications due to difficulties such as interpretation of results, high noise sensitivity, and different issues during flood events (Deng and Cai 2010). In recent years, techniques using time-domain reflectometry (TDR) and fiber Bragg grating (FBG) sensors have been under development and used for real-time field monitoring. Due to their advantages over traditional sensors, such as their long-term stability and reliability, good resistance to environmental corrosion, and multiplexing along one single fiber (Deng and Cai 2007), fiber optic sensors have become popular in structural performance monitoring. The challenge of FBG applications in bridge scour is how to design the instruments and mount the sensors to obtain useful data. Lin et al (2005) developed two types of local scour monitoring systems, using a cantilever beam or plate that is fixed to the pier. Lu et al (2008) used a sliding magnetic collar (SMC) and a steel rod to monitor bridge scour.
In the present study, methods based on a single pile were proposed. Instead of attaching an instrument to the bridge pier/pile, a separate pile or similar structure installed with FBG sensors was adopted, to be driven beside the monitored pile group. Anti-collision piers can be used for this purpose. Based on the analytical and numerical analyses of scour effects on the pile response discussed earlier, three possible methods to detect and monitor the foundation scour were proposed and are discussed below. They are methods based on (a) the pile's natural frequency change, (b) bending moment profile, and (c) modal strain profile.
3.1. Scour monitoring based on frequency change
The first step of damage detection is to determine the occurrence of damage (Rytter 1993). From the results of example 2 shown in figures 8–10, it is found that the reduction of soil around the pile will reduce the pile's natural frequency, especially the low-order frequencies. Since the low-order frequencies are easy to measure, the change of frequency is an alternative feature for detecting the occurrence of scour damage. Figure 11 presents the change ratio of the first natural frequency versus the initial scour depths (the initial position of the interface between soil and water) for three different additional scour ratios, namely 5% (scour depth = 4 ft), 10% (8 ft) and 15% (12 ft). It can been seen that for this 34.38 m (80 ft) pile, when the initial soil position is above the 15.24 m (50 ft) line (measured from the pile top), an additional scour ratio of 5% (4 ft) can result in more than 10% change in the first natural frequency. It implies that if an additional scour with a ratio of more than 5% occurs on a pile with an unsupported length of less than 62.5% (50/80 = 0.625), it can be detected through the change of the fundamental frequency. Figure 12 displays the same observation on the piles supported with soil of different stiffness.
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Standard image3.2. Scour monitoring based on bending moment profile
Figures 3 and 5 have shown that the maximum moment of the pile changes with the scour ratio and its location is slightly below but close to the scour depth. Therefore, a method based on the bending moment profile was proposed here for scour monitoring. As shown in figure 13, the turning points of the three curves are 2.68 m (8.8 ft), 5.12 m (16.8 ft) and 7.56 m (24.8 ft), compared to the total unsupported length (scour depth) of 2.44 m (8 ft), 4.88 m (16 ft), and 7.32 m (24 ft), respectively. As expected, the detected turning point of moments is typically lower than the true soil (scour) line because the soil provides an elastic (not rigid) support to the pile. The turning point of the pile moment profile can still be considered as the detected scour depth since it is very close to the true scour depth. From an engineering practice point of view, the top soil is typically weak after being disturbed and it does not provide much support to the pile. Therefore, the fact that the detected scour depth is slightly lower than the true soil position has a practical significance. For a single pile, it is easy to obtain the moment profile through strain sensors attached along the pile under applied testing loads or hydraulic loads.
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Standard image3.3. Scour monitoring based on modal strain profile
Modal information such as natural frequency and mode shape is easy to obtain from the time-history data recorded from dynamic tests, which makes it attractive for damage and scour detection. Similar to the moment profile method, a strategy based on the modal strain (curvature) profile was also proposed in the present study. As shown in figure 14, the modal strain extracted from the first modal shape is similar to the bending moment profile. The detected scour based on this strategy would be 8.78 m (28.8 ft), 15.36 m (50.4 ft) and 20.24 m (66.4 ft), compared to the true scour depth 7.32 m (24 ft), 14.63 m (48 ft), and 19.51 m (64 ft), respectively. The same as the bending moment case, the detected turning point of strains is typically lower than the true soil (scour) line because the soil provides an elastic (not rigid) support to the pile. Since the modal information is related to the physical property of the structure, it should be more applicable and practical than the bending moment from static loading.
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Standard image4. Laboratory test
The present study developed a scour monitoring system using fiber optic sensors (FOSs) that have wide applications in long-term monitoring of structures, especially in harsh environments. The major benefits of choosing FOSs for scour applications are: good corrosion resistance and long-term stability, making it possible to be embedded in soil and submerged in water; distributed sensing and multiplexing capabilities, making it possible to install a series of sensors along a single cable to collection information along the depth of the foundation; small size and light weight with little disturbance to the structure and soil; immunity to electromagnetic/radio frequency interference, etc
Laboratory tests were conducted to verify the structural behavior under static and dynamic loadings and the feasibility of the proposed motoring methods. A pipe made of glass fiber-reinforced polymer (GFRP) buried in sand was used to simulate the pile structure in soil, which is schematically depicted in figure 15. A fiber-reinforced polymer (FRP) bar attached with FBG sensors was mounted on the GFRP pipe at three positions, 0.0, 0.4 and 0.8 m, to measure the response of water impact. Both the pipe and the bar are fixed on a steel plate at the bottom. To simulate the water flow action, a shaking table was used to exert the stroke to the water tank sitting on the table. The water in the real river is in one direction, but it moves back and forth in the tank. In order to reduce the drag force of water, the specimen was put close to one side of the tank. Five sensors were deployed both on the GFRP pipe and the FRP bar at intervals of 0.2 m, namely, at the positions 0.0, 0.2, 0.4, 0.6, and 0.8 m. For tests in water, the specimen was partially buried in a sand container and then submerged in the water tank. The heights of water and sand are adjustable as needed. Figure 15 shows an example where the bottom 0.4 m is in the sand and the top 0.4 m is in the water. A velocimeter was also used to measure the water velocity. Figure 16 shows the test specimen and layout. The property of the GFRP pipe is: outer diameter = 11.4 cm (4.5 in), inner diameter = 10.2 cm (4 in) and the axial Young's modulus obtained through the material test is 5.4 GPa. The frequency filter is 250 Hz.
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Standard imageThree monitoring mechanisms were tested. The first one is to detect the scour occurrence through the frequency change by clicking the GFRP pipe. The second one is the bending moment mechanism due to the static loading or the water flow, as shown in figure 17(a). Herein a force was applied on the top of the pipe to produce the bending moment. The third one is the high-frequency response of the FBG sensors to water flow or debris impact, as shown in figure 17(b). A hanging weight was used to simulate the debris in river water, and the sensors on the FRP bar were specially designed for this mechanism.
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Standard image4.1. Detection of frequency change
The GFRP pipe was first put on the ground without sand and clicked on the top, and was then buried in the sand with different heights, 0.2, 0.4 and 0.6 m. The time histories of strain response are transferred into the frequency domain using the fast Fourier transform (FFT), as shown in figure 18. The first frequencies of the four cases are 34.85 Hz, 35.25 Hz, 38.30 Hz and 42.00 Hz, respectively. Therefore, it confirms that the fundamental frequency of the structure decreases with the reduction of sand height, which indicates a scour activity.
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Standard image4.2. Detection of moment/strain profile change
As observed earlier in the numerical simulation, the location of the maximum moment in the pile changes with the scour depth. In this section, tests of the GFRP pipe under different supporting conditions were conducted: without sand and with different heights of sand. A lateral force was applied intermittently on the top of the GFRP pipe to generate the bending moment in the pipe, and the time history of the strain response at different locations was recorded by the five sensors.
Without sand: The GFRP pipe was on the ground without any sand around and six runs were conducted. The strain responses of the five sensors of the first run are shown in figure 19. For each run, the strain value of the five sensors at a specific time was extracted to demonstrate the strain distribution along the pipe length. Figure 20 is the strain value along the pile length at the five peak times shown in figure 19. Those values are then normalized based on the ratio to the strain of the bottom sensor, namely, the strain value of the sensor at the position of 0.0 m is set to be 1, as shown in figure 21. The average of the normalized strain value at each run is then summarized in figure 22. It can be found that the stain distribution is nearly linear.
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Standard imageWith sand 0.2 m high and 0.4 m high: The GFRP pipe was buried in the sand with a height of 0.2 m and 0.4 m, respectively. With the same procedure, the normalized strain distributions of all the three runs are summarized in figures 23 and 24. The maximum strain in figure 23 is at the position of 0.2 m and that in figure 24 is at the position of 0.4 m, which is equal to the sand height of each case and indicates the scour depth.
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Standard image4.3. Water current test on the shaking table
In this test, the specimen was put into the water tank on the shaking table to simulate the water flow action and hanging weights were used to simulate debris in the river water. The GFRP pipe with the FRP bar was buried in different heights of sand. In the first case, the sand height was 0.4 m and one hanging weight was at the position 0.6 m. In the second case, the sand height was 0.2 m and two hanging weights were arranged at the positions 0.2 m and 0.6 m, respectively. The water height was 0.8 m and the speed of the shaking table was set to be 0.1, 0.25 and 0.5 m s−1.
The time histories of strains at a speed of 0.5 m s−1 are shown in figures 25 and 26. Figure 25 is the strain response from sensors on the FRP bar and figure 26 is that from sensors attached on the GFRP pipe. It is observed that the response of the FRP bar is much stronger than that of the GFRP pipe, especially at the 0.6 m position where the hanging weight is located. Also, the curves of both cases look totally different. The one in figure 25 for height 0.6 m looks like an impulse signal and is very obviously distinguished from the others, due to the discontinuous impact of the hanging weight.
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Standard imageThe same observation can be seen from the results of the second case with 0.2 m sand, as shown in figures 27 and 28. Besides the 0.6 m position, figure 27 reveals an impulse-like signal appears at the position of 0.2 m as well. From case 1 to case 2, the sand height reduces from 0.4 to 0.2 m, which exposes the sensor and the hanging weight at the 0.2 m position. It indicates that as the soil is scoured, the sensor originally buried in the soil is exposed to the water and begins to respond recognizably differently due to the water current and debris impact. It is a good sign for scour detection.
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Standard imageWith the same procedure as described above, the strain distribution of the pipe at a given time was obtained by extracting from the time-history results of the five sensors, as shown in figure 29, with a sand height of 0.4 m and water speed of 0.25 m s−1. The maximum strain is at the 0.2 m position, which is lower than the sand height. A possible reason could be that the elastic coefficient of sand is not constant, but rather is linearly distributed along the depth, which means that the stiffness of the top sand is very small. Moreover, the sand saturated in water weakens its supporting ability and the water flow drags the top sand and makes it loose. Therefore, the identified scour depth is not exactly the same as the actual scour depth.
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Standard image5. Conclusions
The present study mainly focused on the static and dynamic response of a single pile to scour effects. Based on observations from the theoretical and parametric analyses, the present study proposed three possible methods for detecting and monitoring bridge scour and developed a monitoring system using fiber optic sensors that had been verified in the laboratory. The following conclusions can be drawn:
- (1)For any position of the pile, if it is buried deeply in soil, its bending moment is not significant. Only if the scour depth approaches that position does the moment become significant and increase quickly to its maximum. Furthermore, the location of the maximum moment in the pile is close to the interface between water and soil, and can be used to detect the scour depth.
- (2)The pile's natural frequency decreases as the scour ratio increases, especially for the fundamental frequency of the pile, which is beneficial for scour monitoring.
- (3)The bending test of the GFRP pipe buried in sand with different heights verifies the numerical observations, namely, the position of the maximum moment in the pile is close to the interface of sand and water. It also confirms the feasibility of the scour monitoring method based on the bending moment profile.
- (4)The water flow test on the shaking table verifies the scour monitoring method based on the high-frequency signal from the debris in the river water. As the sand level is reduced, the sensor originally buried in the soil is exposed to the water, and it begins to respond recognizably differently due to the water flow and debris impact. It is a good sign for scour detection.
- (5)The scour monitoring method based on the moment profile caused by the water flow impact is not as accurately verified. A possible reason is that the elastic coefficient of sand is not constant, but rather is linearly distributed along the depth, which means the stiffness of the top sand is very small. Moreover, the sand saturated in water weakens its supporting ability and the water flow drags the top sand and makes it loose. Therefore, the identified scour depth is not exactly the same as the actual scour depth.
Acknowledgments
The investigators are thankful to the Innovative Bridge Research and Deployment (IBRD) program, Federal Highway Administration and Louisiana Transportation Research Center (LTRC) for funding this project. The contents presented reflect only the views of the writers who are responsible for the facts and the accuracy of the data presented herein. We would like to also express thankfulness to those who provided help during the development of these initial tasks of this research program. Special thanks go to the project manager Dr Walid Alaywan, Louisiana Department of Transportation and Development (LADOTD).