The objective of this study was to generate last-mile test protocols for e-commerce distribution routes, carried out in cities with optimal road conditions such as those found in main Spanish cities with a particular focus on shocks and vibrations. The study was conducted using delivery vans, with 8 to 103 and 1.5 tonnes capacity fitted with air suspension, operated by delivery companies. The data presented in this study, is aimed at reducing the ‘last mile’ distribution damage while avoiding overpackaging, by improving and optimising packaging design and test protocols. In this study, representative last-mile distribution routes in Spain were selected and the resulting shocks and vibrations were measured, analysed with the specific aim of developing laboratory simulation test protocols for the last-mile transport environment in Spain and similar distribution environments. In addition, a detailed study of the shocks encountered during last-mile delivery routes were made to evaluate the influence of fragility labels on the handling severity of packages. The method for calculating the Effective Drop Height (EDH) from shock acceleration measurements were validated by controlled laboratory experiments using a free-fall drop testing apparatus. Drop height estimated from shocks during last mile routes were compiled to produce a laboratory test protocol for drop tests. Vibration data were subjected to frequency analysis to obtain the Power Spectral Density (PSD) based on the upper one-sided normal tolerance limit (NTL) (30, 95,50) method, resulting in a test spectrum with a grms level of 0.11.

Detecting and characterising shocks is challenging because they do not occur in isolation but are instead superimposed onto underlying vehicle vibrations which themselves are a result of the interaction with uneven road surfaces. Consequently, shocks are buried within vehicle vibration response measurements (usually acceleration). This paper presents the development and validation of an automated algorithm to detect shocks from vertical acceleration signals measured from road vehicles. To avoid inherent difficulties with experimentation, this initial paper is confined to numerical simulation whereby the response of two typical quarter-car truck models (one with air ride and the other with steel suspension) when travelling on artificially-generated random road elevation profiles laced with Hanning-shaped surface aberrations of known amplitude, lengths and location along the elevation profile. The shock detection algorithm was developed as a dual mode classifier to accommodate the two natural frequencies of each 2DoF quarter car models. Detection was implemented by first passing the vibration response signal through a band-pass filter around the two resonant modes in turn then calculating the filtered signals’ instantaneous frequency (envelope) by means of the Hilbert transform. Shock detection was based on the local peak-to-mean ratio (LPTMR) of the instantaneous magnitude where ‘local’ was defined by the duration of the filtered signal's impulse response function. Sensitivity analysis and validation were undertaken on artificially-generated roads of varying roughness onto which aberrations of known shape were superimposed. The effectiveness and limitations (detection threshold) of the algorithm were evaluated by creating a range of aberrations with a broad range of lengths (effective frequencies) and diminishing amplitudes. Results show that shocks of ‘significant’ magnitudes are always detected with no detection of false positives. As the road roughness increases relative to the aberration amplitudes, the resulting shocks become increasingly drowned-out by the vibration response due to the underlying road roughness, especially for the quarter-car model with steel suspension. The main conclusion is that the signal analysis approach taken is ultimately effective and needs to be further validated using experimental response data.

This article addresses the essential task of understanding vibrations produced by vehicles to enhance the design of authentic laboratory tests. The article focuses on two primary sources of vibrations: those arising from vehicle-road surface interaction, which is largely random, and those emanating from the drivetrain, characterized as a summation of harmonics with a time-varying fundamental frequency. The method involves the application of the extended Kalman filter (EKF) paired with robust nonlinear least-squares (NLS) initialization to isolate the harmonic components effectively. Through a comprehensive analysis involving mean-square-error (MSE) evaluation via Monte Carlo simulation, considering additive white Gaussian noise (AWGN) and a two-degrees-of-freedom quarter-car model's simulation response to the road, the research demonstrates the EKF's proficiency. The results indicate the EKF's capability to accommodate AWGN with a signal-to-noise ratio (SNR) up to 0 dB and road-induced random background vibrations up to an SNR of -3 dB, maintaining an MSE order of approximately 10-3.

ABSTRACTFor decades, numerous attempts at re‐creating realistic (vertical) vibrations that purport to represent typical conditions during road transport have been proposed and published. This has and continues to result in a significant number of target power density spectra (PDS) for use in laboratory simulation of vibrations despite the fact that the underlying parameters that influence the vibrations (road surface unevenness and vehicle dynamics) remain largely unchanged. This paper seeks to address this situation by analysing published and measured PDS (129 in total) from a variety of vehicles and road types with the aim of establishing typical PDS. Through the analysis of the frequency of the first natural mode of these PDS, it was found that there exist five typical response PDS (three for steel leaf suspension and two for air ride suspension) that can be considered as representative vibration response PDS for road transport in general. These representative PDS were matched with a two degree‐of‐freedom quarter‐car model representing the heave response of the rigid body motion of the vehicles. The analysis suggests that the higher frequency content of the measured data is not related to rigid body motion but emanates from drivetrain and, in some cases, structural vibrations. These usually comprise numerous harmonics of fixed and varying frequencies as well as transients. As these vibrations are impossible to classify based on vehicle type, it is recommended that the five quarter‐car representative spectral models proposed in this paper—namely, for steel leaf spring suspended vehicles with heavy, moderate and light loads and air ride type vehicles with heavy and light loads—be used for laboratory simulation for the purpose of evaluating the vibration resistance of products and packaged systems. It is suggested that, for most packaged product, this is sufficient to test their ability to survive road transport vibrations. These will yield more realistic vibrations than those endorsed by standards organisations and should have a positive impact on the optimisation of packaging designs and a corresponding reduction in packaging waste. Finally, the need for further work aimed at developing methods to identify and extract fixed and varying discrete frequency vibration as well as transient vibrations was identified.

This paper studies the cushion performance of a range of sustainable cushion systems and applies two methods to estimate cushion curves from limited cushion test data. The methods employed were previously developed to allow for (1) the conversion of cushion curves representing a material's performance for a given drop height and sample thickness to alternative (non-measured) drop heights and sample thicknesses and (2) generating a complete cushion curve for a given thickness and drop height from a single acceleration (shock) measurement. The results include those generated for medium-density polyethylene (MDP) closed-cell foam for benchmarking of the materials and to aid in validating the approach. The results indicate that predicting cushion curves from single shock measurements is generally accurate for polymeric materials (MDP closed-sell foam and HDPE inflated bag) but much less so for organic materials (sugarcane bagasse and perforated cardboard). Finally, all alternative cushioning materials and systems evaluated are shown to only be effective for very low static stresses. This finding demonstrates that much higher volumes are required when using the alternative materials to achieve the same cushioning effectiveness as MPD foam. Comparison of cushion curves for all materials investigated clearly shows that the alternative (sustainable) materials are not capable of withstanding static stresses as large as those of MDP closed-cell foam. Any gain (environmental and economic) achieved by the use of sustainable, readily degradable material will be mitigated by increased volumetric as well as bulk consumption. This points to the need for further work towards the development of processes to enhance the shock absorbing capabilities of such environmentally friendly materials.image

The aim of this study was to measure the vibration levels in one of the types of truck most used in Spain for the shipment of packaged goods, formed by tractor unit and air-suspension semi-trailer with 26 tonnes (26 000 kg) payload capacity, considering the most representative routes of the main Spanish road network. The data presented in this study will enable the development of new specific vibration tests and will help product and package engineers to reduce damage in transit. In this study, 30 transport routes recording nearly 10 000 km of the Spanish main road network have been selected and analysed, and power spectral density (PSD) profiles are provided to simulate truck transport in Spain using random vibration test methods. The resulting PSD profiles were established by generating two g(rms) levels (0.21 and 0.15) obtaining the highest intensity from the calculation of the upper one-sided normal tolerance limit (NTL) (30,95,50) and an average intensity profile at -6 dB with respect to the calculated NTL curve, which represents 70% of the lowest g(rms) values of the study. This study uses NTL analysis to explore the vibration characteristics of a typical heavy goods transport vehicle type for various routes along main highways in Spain and propose new transport simulation test protocols dedicated to the Spanish main road distribution environment.

Mechanical damage in packaged fruits is known to be exacerbated by the intensity and exposure duration of vibration excitation during road transport. However, the current single degree of freedom (SDOF) vibration simulation test standards for road vehicle transport have limitations for simulating long distance road trips. The accelerated vibration simulation testing, based on the Basquin model of cyclic fatigue, has been used for reducing the simulation test time. However, the time-compression factor used in this model can result in significant errors in simulation outcome as the power constant is usually assumed (i.e. k = 2 or 5). This work aimed at developing an accelerated vibration simulation test for packaged bananas. For this, mechanical damage levels that occurred during the field transport of packaged bananas were compared with the damage levels resulted from laboratory-based vibration simulation. A SDOF averaged power-spectra derived from the measurement of vertical acceleration levels during the field transport, with a vibration intensity of 0.36 gRMS for a test duration of three hours, was found to be the most suitable test protocol that closely replicated the field damage levels during long distance transport of bananas. The power constant in the Basquin model was derived by comparing the simulation-induced mechanical damage levels, with those occurred during the field transport. This study therefore provides a practical time-compressed simulation test for packaged bananas and other similar products undergoing long distance transport. Improved package testing will contribute to developing more realistic solutions to minimize damage to delicate products in-transit.

The ability to synthesize dual, parallel track road elevation profiles is essential for studying the multi-axial motion of vehicles. It is important that the profiles retain the random and variable character of real roads. This research introduces a novel method for synthesizing dual-track longitudinal pavement elevation profiles. Using measured data from asphalted roads, probability density functions were produced to describe the variations in roughness and correlation between the tracks. The correlation between the tracks was analysed using the coherence function and roughness ratio between the measured kerb-side and driver-side tracks. The results showed that variations in the roughness of the tracks were well described by the Weibull probability distribution function defined by the shape, scale and location parameters. The location and shape parameters were shown to be independent to road roughness, leaving the scale parameter as the main index to define the roughness distribution. This finding led to the creation of a new roughness classification scheme for asphalt roads which was used to select appropriate roughness levels for simulation. Variations in the coherence functions and roughness ratios were found to be independent of road roughness and were also able to be described using the Weibull distribution. Using the results from a detailed statistical survey, a novel method was developed to enable the synthesis of parallel track elevation profiles that emulate real roads.

Purpose: Instrumentation systems are increasingly used in rowing to measure training intensity and performance but have not been validated for measures of power. In this study, the concurrent validity of Peach PowerLine (six units), Nielsen-Kellerman EmPower (five units), Weba OarPowerMeter (three units), Concept2 model D ergometer (one unit), and a custom-built reference instrumentation system (Reference System; one unit) were investigated.Methods: Eight female and seven male rowers [age, 21 +/- 2.5 years; rowing experience, 7.1 +/- 2.6 years, mean +/- standard deviation (SD)] performed a 30-s maximal test and a 7 x 4-min incremental test once per week for 5 weeks. Power per stroke was extracted concurrently from the Reference System (via chain force and velocity), the Concept2 itself, Weba (oar shaft-based), and either Peach or EmPower (oarlock-based). Differences from the Reference System in the mean (representing potential error) and the stroke-to-stroke variability (represented by its SD) of power per stroke for each stage and device, and between-unit differences, were estimated using general linear mixed modeling and interpreted using rejection of non-substantial and substantial hypotheses.Results: Potential error in mean power was decisively substantial for all devices (Concept2, -11 to -15%; Peach, -7.9 to -17%; EmPower, -32 to -48%; and Weba, -7.9 to -16%). Between-unit differences (as SD) in mean power lacked statistical precision but were substantial and consistent across stages (Peach, similar to 5%; EmPower, similar to 7%; and Weba, similar to 2%). Most differences from the Reference System in stroke-to-stroke variability of power were possibly or likely trivial or small for Peach (-3.0 to -16%), and likely or decisively substantial for EmPower (9.7-57%), and mostly decisively substantial for Weba (61-139%) and the Concept2 (-28 to 177%).Conclusion: Potential negative error in mean power was evident for all devices and units, particularly EmPower. Stroke-to-stroke variation in power showed a lack of measurement sensitivity (apparent smoothing) that was minor for Peach but larger for the Concept2, whereas EmPower and Weba added random error. Peach is therefore recommended for measurement of mean and stroke power.

Today, there exist a number of standards designed to assist packaging engineers with implementing suitable laboratory testing regimes for road transport. However, these standards generally focus on translational vibrations and do not include other motions that may affect survival rates during transport (e.g., pitch and roll). The standards also do not account for the significant variations in vibration (root mean square [rms]) levels that are clearly evident during transport. Further, the analysis and interpretation of vibration frequency spectra typically ignore the possible presence of harmonics or shocks. Most standards also advocate some form of time compression to reduce testing duration by artificially amplifying the simulated vibrations. Each of these individual approaches combines to render the simulated vibrations currently in use unrepresentative of what occurs during transport, thereby making it difficult to optimise packaging systems. This article focuses on road transport shocks and vibrations and highlights the shortcomings of proposing and making changes to test methods based on limited data obtained from specific transport scenarios. It argues that only once all the evidence, taking into account a broader set of scenarios from multiple studies, has been collected and the correct scientific analysis applied, should changes to test protocols be proposed and implemented. The paper includes specific recommendations for further evidence collection and analysis for each of the main issues associated with road transport vibrations, namely, spectral shape, rms levels and test duration, nonvibratory events such as shocks and multiaxis vibrations.

It has long been recognised that the level of road vehicle vibrations are mainly a function of vehicle characteristics, road roughness and vehicle speed. With the introduction of easy‐to‐use vibration data recorders, significant amounts of data have been recorded, and numerous studies on the rms levels of truck vibrations have been published. However, the results available to date are typically from specific scenarios and do not provide comprehensive comparisons with similar published work. In addition, most of the publications only report the mean rms level with no indication of how the rms varies throughout the journey nor statistical information on the likelihood of particular rms levels being exceeded. This paper brings together the available information on road transport vehicle vibration levels for analysis. It does so by first collating published mean vibration rms values for a broad range of scenarios and supplements them with additional mean rms values recorded by the authors. The collated results were analysed statistically to reveal the influence of important parameters, namely, suspension type, road type, payload and vehicle type. Results from the statistical analysis are used to quantify the influence of each parameter and to allow for the prediction of expected rms levels based on the transport scenario. This introduces a risk‐based approach to laboratory testing which allows the analyst to set the test rms levels based the road transport scenario and the accepted level of risk.

This paper reviews the various ways that have been proposed to characterise road transport vehicle vibrations and recommends a new approach to characterise the vibrations levels during a transport journey. Some 47 road vehicle vibration records, obtained from a broad range of conditions, were analysed, and results show that the root‐mean‐square (rms) distribution of the vibrations can be accurately modelled with a reduced version of the three‐parameter Weibull distribution (shape parameter set to 2). This statistical approach to characterising road vehicle vibrations takes into account the random fluctuations in rms levels that occur naturally during a road journey and can be used to classify the severity of RVV. This offers significant improvement on the simplistic mean rms value that has, so far, been the sole parameter to describe vibration levels during transport. The Weibull location parameter represents the low threshold of the rms level in the record (except when xo is less than zero, in which case the low rms threshold is zero), whereas the Weibull range parameter is proportional to the range of rms level. Results also reveal a strong relationship between the rms mean and the sum of the location and scale parameters. In addition, this enables generation of rms distributions from the mean power density spectrum (PDS) alone. The modified (fixed‐shape) Weibull distribution can be used to faithfully describe the entire statistical distribution of the rms level of a journey or transport mode with just two parameters. This new approach can be used in a practical way for quantifying and comparing transport vibration rms levels for design and testing purposes.

Until recently, laboratory testing of packaged systems has been undertaken by simulating vertical vibrations alone. However, with increasing demand for a reduction in packaging waste, the use lightweight systems, such as stretch film, is increasing. Such containment systems are susceptible to the lateral forces generated by the pitch and roll vibratory motion of vehicles due to road surface unevenness. If laboratory simulation is to be realistic, multi‐axial motion must be taken into account and an understanding of the relationships between the random heave, pitch, and roll vibrations is essential. This paper uses vibration data collected from a number of transport vehicles traveling along typical urban and suburban routes to establish the nature and level of the multi‐axial vibrations that exist. These are presented with average Power Density Spectra (PDS) as well as statistical distributions of the moving root‐mean‐square (rms). The paper analyses the data for correlation of the rms levels with respect to nonstationarity. This is important when simulating nonstationary (randomly fluctuating rms) vibrations for heave, pitch and roll. These statistical correlation functions are used to manage the relative rms levels of each of the three Degrees of Freedom (DoFs) when undertaking vibration simulations using multi‐axis vibration test systems. The results show that the relationships between the moving rms of heave, pitch and roll vibrations are not strongly correlated but can be characterized statistically as joint distributions to enable realistic simulation of multi‐axial random vibrations of road transport vehicles under controlled laboratory conditions.

Packaging is the primary protection of fresh produce against the environmental hazards such as vibration in the distribution process. This study evaluated the effectiveness of two types of corrugated paperboard packaging, reusable plastic creates (RPC) and vacuum tightening for their protective performance in reducing damage of bananas under simulated transport vibration. Both vibration transmissibility and the construction material of packaging influenced the mechanical damage levels in bananas with the RPCs showing the highest damage levels. The best protective performance for bananas was exhibited by one-piece corrugated paperboard cartons with additional benefits of reduced vibration transmissibility at the top-tiers. Vacuum tightening effectively reduced the vibration damage, especially in the most bottom and top tier packages, by over 70% and thus, can be considered for further reducing mechanical damage to bananas. One-piece cartons, with the possible addition of vacuum tightening or tensioned plastic wrapping, could therefore substitute the widely used two-piece carton in Australia in order to minimize mechanical damage to bananas in-transit.

The ability to accurately simulate the vibratory motion of transport vehicles is of great importance when designing vehicle components and product containment systems. Direct measurement and analysis of the vibrations is not always practical and laboratory testing using synthesized road elevation data is a common alternative, as is numerical simulation. However, no technique exists to generate realistic nonstationary dual track road elevation data. This research focuses on uncovering statistical distributions that describe the nonstationary relationships between the left and right wheel-paths. Analysis of the short-time (nonstationary) coherence functions and instantaneous International Roughness Index (IRI) of measured road profile data provided distributions which describe variations in left to right wheel-path correlation and roughness variations for both tracks. The resulting distributions can be described with a three-parameter Weibull distribution and can be adopted to generate nonstationary dual wheel-path profile data that can be used to excite numerical vehicle models and physical vehicles via multi-axis simulators. (C) 2020 Elsevier Ltd. All rights reserved.

During the distribution process, products are continuously exposed to dynamic forces resulting from vehicle vibrations as well as drops and shocks from various types of handling. In order to reduce the adverse effects of such loads, protective packaging or cushioning materials are used. Engineered packaging materials are generally petroleum based (plastics) and present significant environmental concerns after their disposal. The use of environmentally friendly, bio-compostable, alternatives is a logical development; however, if the salient protective characteristics of these materials are not well established, their use may lead to greater losses and a larger environmental impact through product loss. This paper introduces a comprehensive approach for the mechanical characterisation of alternative cushioning materials, which includes the effects of environmental conditions. The procedure is used to compare the performance of loose fill starch beads with a commonly used engineering cushioning material, namely medium density, closed cell polyethylene. The results show that the starch beads can offer a viable alternative to the engineered cushioning materials as they provide reasonable overall cushioning character, albeit over a narrower stress range when compared with the polyethylene cushions. The loose fill was also shown to perform in terms of vibration damping and resistance to sustained dynamic loads for low static stress levels.

Road surface imperfections and aberrations generate shocks causing vehicles to sustain structural fatigue and functional defects, driver and passenger discomfort, injuries, and damage to freight. The harmful effect of shocks can be mitigated at different levels, for example, by improving road surfaces, vehicle suspension and protective packaging of freight. The efficiency of these methods partly depends on the identification and characterisation of the shocks. An assessment of four machine learning algorithms (Classifiers) that can be used to identify shocks produced on different roads and test tracks is presented in this paper. The algorithms were trained using synthetic signals. These were created from a model made from acceleration measurements on a test vehicle. The trained Classifiers were assessed on different measurement signals made on the same vehicle. The results show that the Support Vector Machine detection algorithm used in conjunction with a Gaussian Kernel Transform can accurately detect shocks generated on the test track with an area under the curve (AUC) of 0.89 and a Pseudo Energy Ratio Fall-Out (PERFO) of 8%.

The ability to characterize shocks which occur during road transport is a vital prerequisite for the design of optimized protective packaging, which can assist in reducing cost and waste related to products and good transport. Many methods have been developed to detect shocks buried in road vehicle vibration signals, but none has yet considered the nonstationary nature of vehicle vibration and how, individually, they fail to accurately detect shocks. Using machine learning, several shock detection methods can be combined, and the reliability and accuracy of shock detection can also be improved. This paper presents how these methods can be integrated into four different machine learning algorithms (Decision Tree, k-Nearest Neighbors, Bagged Ensemble, and Support Vector Machine). The Pseudo-Energy Ratio/Fall-Out (PERFO) curve, a novel classification assessment tool, is also introduced to calibrate the algorithms and compare their detection performance. In the context of shock detection, the PERFO curve has an advantage over classical assessment tools, such as the Receiver Operating Characteristic (ROC) curve, as it gives more importance to high-amplitude shocks.

Until recently, a vehicle’s vertical vibrations were considered the main cause of damage during transport. Consequently, laboratory testing has been undertaken by simulating heave (vertical) vibrations alone. However, with increasing demand for a reduction in packaging waste, there is an impetus to use lightweight systems, such as stretch film, for containing unitized loads. Such containment systems are susceptible to the lateral forces generated by the vibratory motions that arise from the pitch and roll vibratory motion of vehicles due to road surface unevenness. If laboratory simulation is to be realistic, multi-axial motion must be taken into account and an understanding of the relationships between the random heave, pitch, and roll vibrations is essential. This paper uses vibration data collected from a number transport vehicles traveling along typical urban and suburban routes to establish the nature and level of the multi-axial vibrations that exist. These are presented with average Power Density Spectra (PDS) as well as time histories and statistical distributions of salient moving statistics such as the root-mean-square (rms). The paper analyses the data for correlation of the rms levels with respect to nonstationarity. This is important when simulating nonstationary (randomly fluctuating rms) vibrations across the three degrees of freedom (DoF) namely, heave, pitch and roll. These statistical correlation functions are used to manage the relative rms levels of each of the three DoFs when undertaking vibration simulations using multi-axis vibration test systems. The results show that the relationships between moving rms of heave, pitch and roll vibrations are not highly correlated but can be characterized statistically as joint distributions to enable realistic simulation of multi-axial random vibrations of road transport vehicles under controlled laboratory conditions.

The printing images on products and packaging play an important role in increasing the business value, adding artistic quality, and sending information. During transportation, scuffing of the printing images will emerge due to vibrations and impacts induced by rough roads and vehicles. This paper investigates experimentally the vibration scuffing through an ink transfer device. The scuffing value–time curves are obtained. Then the scuffing life curves G rms,e ‐N a,e based on excitation acceleration root‐mean‐square (RMS) and G rms,r ‐ N a,r based on relative acceleration RMS are developed. Both Basquin ‐type and exponential‐type curves may be applied to describe the scuffing life in this case. The excitation frequency width covering the resonance frequency has a significant effect on the scuffing life curve G rms,e ‐N a,e based on excitation acceleration RMS; however, it is not obvious on the scuffing life curve G rms,r ‐ N a,r based on relative acceleration RMS. The vibration system filters out the broadband excitation vibration frequencies away from the resonance zone and makes the relative acceleration signal a narrow one. The scuffing life curve in the resonance scuffing state is very different from that in the nonresonance scuffing state, and they should be distinguished in practical application. The scuffing life equations and curves obtained in this paper may provide a reference to the further research on packaging scuffing and its test evaluation and accelerated vibration test in laboratory.