Abstract
Groundborne vibration from construction works can cause significant impacts on the environment, through damage to structures or disturbance of the occupants of buildings. Reliable prediction of the extent of such impacts can be a benefit to the cost and public tolerance of the works and to the effects on the wider environment. This thesis addresses the prediction of vibration caused by four mechanised civil engineering activities: percussive and vibratory piling, and dynamic and vibratory compaction. New field data are presented and analysed. These data have been compared with predictors in the literature for vibration from piling and dynamic compaction. The dearth of information in the literature relating to groundborne vibration from vibratory compaction stimulated a particular emphasis on the study of vibrating rollers. For dynamic compaction, it was found that the existing empirical predictive equation provided a reliable estimate of groundborne vibration, provided that its use was restricted to within the ranges of the parameters from which it was determined. For vibration caused by percussive piling, a number of limitations were identified in the existing prediction formulae. A modified empirical predictor is proposed based on a combination of the literature and the new data. For vibratory piling, it is demonstrated that the magnitude of vibration is not related to the nominal energy per cycle of the vibrodriver, although this is the basis of the predictors in the literature. A new empirical prediction equation for groundborne vibration from vibratory piling is proposed. The vibration arising from vibrating rollers is shown to be dependent upon those factors reported in the literature to determine the efficiency of a vibrating roller to achieve compaction. A new prediction equation is proposed which relates the groundborne vibration to the nominal amplitude of the vibrating drum. For ease of application, all the predictors proposed are based on parameters which are provided by plant manufacturers in their data sheets and the distance from the source. The ranges for each parameter from which the predictors were developed is specified: it is recommended that the predictors are not used outside these ranges.