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6An extensive information and data search was conducted at the onset of the project. The search included (1) questionnaires to state DOT engineers, consulting engineers, FHWA and U.S. Geological Survey (USGS) engineers, and university researchers; (2) electronic literature searches; and (3) emails and telephone calls to personal contacts working in this field in Japan, Portugal, India, Malaysia, Singapore, United Kingdom, Canada, New Zealand, Australia, and the United States. The questionnaire and some of the response statistics are presented in Appendix A (available on the NCHRP Report 682 summary web page: www.trb.org/Main/Blurbs/164161.aspx). The search resulted in the acquisition of 569 laboratory equilibrium scour data points, 943 field data points, and 142 laboratory scour evolution data sets. The important vari- ables were grouped in dimensionless groups that represent ratios of the pertinent physical phenomena. For example, the Froude number, , which is the ratio of flow velocity to the propagation speed of a shallow water surface wave, is important in open channel flow. For sediment transport and local sediment scour, the ratio of flow velocity to the velocity required to initiate sediment movement on a flat stream bed, V1/Vc, is important, etc. The range of the dimensionless groups more commonly used to characterize local scour covered by the compiled data sets is given in Table 1. The search also produced 23 equilibrium local scour and 10 scour evolution predictive equations/methods. Analysis of the search results showed that there is only limited information on local (equilibrium and evolution) scour depths for wide or long skewed piers. Most of the scour prediction equations do, however, state or imply that they are applicable for these conditions. For this reason, all equilibrium and evolution scour equations/methods that were obtained in the search were analyzed in this study. The next step was to perform a preliminary screening of the predictive equations to exclude those equations/methods that yielded predictions significantly different from those for the remaining equations. This screening reduced the V y g1 1 number of equilibrium and scour evolution equations from 23 and 10 to 17 and 6, respectively. A method for assessing the quality of the measured data was developed. The measurement of local scour depths and the sediment and flow parameters on which these depths depend is not straightforward. For example, the bed shear stress, which is one of the important parameters, is usually estimated (or inferred) from the depth-averaged approach velocity. It is assumed that the flow is fully developed and that the depth- averaged velocity can be obtained from a point measurement or that the sectional averaged velocity can be obtained from the volumetric discharge rate in the flume. If the distance from the flume entrance to the test section is too short, the flow will not be fully developed and the bed shear stress will most likely be larger than computed for a fully developed flow. Even small errors in discharge or velocity measurement in the clear-water scour regime can have major effects on equilibrium scour depths and scour depth predictions. These examples illustrate potential problems associated with making accurate local scour measurements in the laboratory. Accurate scour measurements at prototype structures in the field are even more difficult to make. In addition to the measurement problems resulting from the temporal and spatial variations in flow velocities, the soil properties can vary spatially in all directions as well. Perhaps the greatest problem with most field data is the lack of information regarding the level of maturity of the scour hole at the time of measurement, i.e., how near the measured scour depth is to its equilibrium value for the flow, sediment, and structure conditions at the time of measurement. Publications in professional journals often present insuffi- cient detail regarding measurement techniques, instrumenta- tion, etc., which makes assessing the quality of the reported data more difficult. It was necessary to develop a data evaluation scheme based on deviations from mean values computed using all the data. This procedure worked well for the equilibrium scour data. Refined laboratory and field data sets were created for use in evaluating the predictive equations. C H A P T E R 2 Research Approach
Evaluation of the equilibrium scour equations was a two-step process. The first step involved using all of the equations to evaluate the scour for a range of hypothetical (but practical) structure, sediment, and flow conditions and comparing their results. Equations that produced results that significantly deviated from the mean values were elim- inated from further consideration. The refined laboratory and field data sets were then used to evaluate the remaining equations. An initial screening procedure similar to that used for the equilibrium scour data was used for the scour evolution data. An initial screening of the scour evolution equations was per- formed by simply evaluating and plotting the predictions for a range of input conditions and omitting the equations produc- ing drastically different results from the mean produced by all of the equations. The remaining equations were then evaluated using the scour evolution laboratory data and errors were computed and presented in graphs. Based on the performance of the equations in these tests, the best-performing equations/methods were identified and recommended for predicting equilibrium scour depth and scour evolution rates at wide piers and long skewed piers. 7 Table 1. Range of values of the dimensionless groups covered by the compiled data sets. Data Type y1/a a/D50 V1/Vc 1 1V / y g Equilibrium Laboratory 0.05 to 21.05 3.65 to 4159 0.40 to 5.99 0.07 to 1.50 Equilibrium Field 0.18 to 9.67 8.33 to 65047 0.13 to 7.58 0.03 to 1.95 Laboratory Scour Evolution 0.09 to 11.11 6.72 to 4159 0.46 to 5.99 0.07 to 1.76 y1 = the approach water depth V1 = the depth-averaged velocity a = the structure width Vc = the sediment critical depth-averaged velocity D50 = the median sediment grain diameter g = the acceleration of gravity.