This paper presents a novel technique for the simulation of shock and vibrations related to road surface irregularities. The technique is based on a recently developed universal road profile classification scheme, which is one of the main outcomes of a project aimed at better understanding the statistical nature of road surfaces and their interactions with road vehicles. The method, which focuses on the nonstationary and non-Gaussian nature of road profiles, is described along with an analysis procedure developed and implemented to automatically detect and extract transient events from the road spatial acceleration data as well as identify stationary segments of similar roughness (RMS). The paper shows how the concept of treating road surface irregularities as two fundamental components, namely, steady-state road surface irregularities and transient events, can be employed for classification and simulation purposes. The simulation technique is based on a universal statistical model of road surface profiles that characterizes the power spectral density of the underlying irregularities, the probability distribution function of the RMS level using the offset Raleigh distribution function, and the transient density. The transient events are generated with random amplitudes according to the Gaussian distribution, the mean and standard deviation of which are functions of the underlying RMS level. This paper shows how these two components can be combined to numerically synthesize a process that faithfully represents the nonstationary, transient-laden nature of road surface profiles. The synthesized process can be physically realized on a vibration shaker to simulate road profiles.

A new method for the measurement of shock-absorbing characteristics of cushioning materials and determination of 'cushion curves' is discussed in this paper The method not only significantly reduces testing time but also improves the accuracy of the estimate of a cushion curve. Cushion curves are determined from the material's static compression characteristics and the impact data (static load/peak acceleration) obtained from a small number of impacts on a cushion tester. However, the method is capable of producing a cushion curve from the measurement of just a single impact. The process involves an iterative least mean squares (ILMS) minimisation of the discrepancy between peak acceleration values predicted from a theoretical model and measured in the impact tests. The algorithm of the ILMS method, examples demonstrating its application and the dynamic effect in impacts of various materials such as the EPU; the EPS and corrugated fibreboard are presented. Copyright (C) 2000 John Wiley & Sons, Ltd.

This paper introduces a universal classification methodology for discretely sampled sealed bituminous road profile data for the study of shock and vibrations related to the road transportation process. Data representative of a wide variety of Victorian (Australia) road profiles were used to develop a universal classification methodology with special attention to their non-Gaussian and nonstationary properties. This resulted in the design of computer software to automatically detect and extract transient events from the road spatial acceleration data as well as to identify segments of the constant RMS level enabling transients to be analyzed separately from the underlying road process. Nine universal classification parameters are introduced to describe road profile spatial acceleration based on the statistical characteristics of the transient amplitude and stationary RMS segments. Results from this study are aimed at the areas of road transport simulation as well as road surface characterization.

This paper introduces a universal methodology for the analysis of discretely sampled sealed bituminous road profile data. Several hundred kilometers of Victorian (Australia) road profile data are analyzed in both the frequency and the amplitude domains. Road profile spectral characteristics are shown to be independent of road roughness. However, statistical analysis of the road elevation data shows them to be highly nonstationary, non-Gaussian processes that contain transients. Transients are difficult to locate when the data are analyzed in the road profile elevation domain itself, as they often occur within the Gaussian distribution. The road profile spatial acceleration is adopted as the preferred analysis domain, as roughness variations and transient events are identified with greater reliability and accuracy. Analysis of the spatial acceleration data enables the identification of large amplitude, short duration events (transients) as they occur extremely outside the Gaussian distribution. Higher order statistics, such as skewness and kurtosis, as well as the crest factor, are also used to detect transients (see Appendix I). It is shown that the road surface elevation becomes a stationary mean process with a nonstationary root-mean square when analyzed in the spatial acceleration domain.

The laboratory evaluation of package performance is traditionally based on the reproduction of vehicle vertical acceleration from the Power Spectral Density (PSD) estimate. The vertical vehicle response acceleration is primarily a function of vehicle suspension and speed, but is ultimately caused by fluctuations in the road surface. This thesis introduces a universal analysis and classification methodology for discretely sampled road profile data. It originates from the premise that current laboratory simulation of the transport environment, which utilises vehicle tray acceleration, is inadequate for package optimisation through performance testing. Package evaluation procedures, which utilise the road surface roughness as the fundamental excitation variable, are shown to require an accurate road profile characterisation for successful implementation. In this study, several hundred kilometres of Victorian (Australia) road profile data are analysed with the focus on the characterisation of their non-Gaussian and non-stationary properties, for future use in the simulation of the road transportation process. Road profiles are found to be highly non-stationary, non-Gaussian, and contain transients. However, transients are difficult to locate when the data is analysed in the road profile elevation domain. The road profile spatial acceleration is adopted as the preferred analysis domain as roughness variations and transient events are identified with greater reliability and accuracy. Computer software is designed to automatically detect and extract transient events from the majority of road data, which contains short segments of constant RMS level. Transients are analysed separately from the constant RMS sections. Nine universal classification parameters are introduced to fully describe road profile spatial acceleration characteristics from the transient amplitude and stationary RMS distributions. Results from this study are applied to the areas of simulation of roads and classification of individual roads based solely on the nine classification parameters.