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 signi®cantly 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 ®breboard are presented.

Inefficient packaging constitutes a global problem that costs hundreds of billions of dollars, not to mention the additional environmental impacts. An insufficient level of packaging increases the occurrence of product damage, while an excessive level increases the packages' weight and volume, thereby increasing distribution cost. This problem is well known, and for many years, engineers have tried to optimize packaging to protect products from transport hazards for minimum cost. Road vehicle shocks and vibrations, which is one of the primary causes of damage, need to be accurately simulated to achieve optimized product protection.Over the past 50 years, road vehicle vibration physical simulation has progressed significantly from simple mechanical machines to sophisticated computer-driven shaking tables. There now exists a broad variety of different methods used for transport simulation. Each of them addresses different particularities of the road vehicle vibration. Because of the nature of the road and vehicles, different sources and processes are present in the vibration affecting freight. Those processes can be simplified as the vibration generated by the general road surface unevenness, road surface aberrations (cracks, bumps, potholes, etc.) and the vehicle drivetrain system (wheels, drivetrain, engine, etc.).A review of the transport vibration simulation methods is required to identify and critically evaluate the recent developments. This review begins with an overview of the standardized methods followed by the more advanced developments that focus on the different random processes of vehicle vibration by simulating non-Gaussian, non-stationary, transient and harmonic signals. As no ideal method exists yet, the review presented in this paper is a guide for further research and development on the topic.

It is today generally accepted that to carry-out realistic transport simulation trials, field data must be acquired from vehicles travelling on the actual route(s) to be used for a particular distribution environment. This approach requires time, effort, access to data recording equipment as well as the necessary expertise to analyse the collected data. Often, this is out of reach of smaller operators who want a reasonable approximation without the time and expense. Currently, the only available option is the adoption of generic test spectra and levels that have been shown to be approximate representations of distribution environments. This paper discusses an alternative and practical method that uses some knowledge of the dynamic characteristics of various vehicle types along with an assessment of the types of roads (road roughness) to be encountered along a particular route. The method exploits the fact that the spectral characteristics (power spectral density) of road profiles are well known. The paper shows how this road surface elevation spectral function is combined with a numerical model of a particular vehicle type and speed to produce a target vibration power spectral density suitable for vibration test systems. One added benefit is that the method is capable of calculating the variations in root mean square levels of the response vibrations. This is presented as the root mean square distribution which, when coupled with the target power spectral density, can be used to synthesize realistic random vibrations that bear statistical similitude with real, field vibrations.

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This paper presents a novel technique by which non-Gaussian vibrations are synthesized by generating a sequence of random Gaussian processes of varying root mean square (rms) levels and durations. The technique makes use of previous research by the authors which shows that non-Gaussian vibrations can be decomposed into a sequence of Gaussian processes. Synthesis is achieved by fi rst computing a modulation function which is produced from the rms and the segment length distribution functions, both of which were developed in previous research. This is achieved by fi rst generating a sequence of uniformly distributed random numbers scaled to the range of segment length, which itself is a function of the desired total duration of the synthesized process. In order to transform a uniformly distributed random variable into any arbitrary non-uniform distribution, the cumulative distribution function is established and used as a transfer function applied to the uniformly distributed random variable. This modulation function is applied to a Gaussian random signal itself generated by a standard laboratory random vibration controller (RVC) by means of a purposed-designed variable gain amplifi er system. In order to counteract the feedback function of the RVC, a second variable gain amplifi er is introduced into the system in order to attenuate the feedback signal in inverse proportion to the gain applied to the command signal. This result is a nonstationary, non-Gaussian random signal that statistically conforms to the desired PSD as well as the RMS distribution function.