Root-Mean-Square Vertical Acceleration as a Summary Roughness Statistic

Hudson, W R; Halbach, D S; Zaniewski, JP; Moser, Louise E.

doi:10.1520/stp34592s

Cited by 13 publications

(4 citation statements)

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“…The above results are not surprising as it has been widely known among pavement researchers that each of the above roughness indices was calculated with either a specific mathematical equation or model and is thus sensitive to roughness features of a particular frequency range (1,9). That this is so can be demonstrated by examining the coefficients of correlation between each of these roughness indices and the various wavelet subband energy terms.…”

Section: Analysis For Flexible Pavementmentioning

confidence: 65%

Characterizing Road Roughness by Wavelet Transform

Liu

Fwa

2004

Transportation Research Record: Journal of the Transportation R

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Summary roughness statistics are commonly used by highway agencies to characterize road roughness profiles to provide convenient numerical indices for pavement performance monitoring and management planning. Many different roughness indices have been used by different highway agencies worldwide. Unfortunately, since different indices are computed with different considerations and mathematical procedures, they often do not correlate with one another well. This presents a practical problem for exchange of information and experience among practitioners or highway agencies. A proposal is presented for the use of wavelet transform to overcome this problem. Wavelet transform can represent detailed pavement roughness features of different wavelengths quantitatively in terms of wavelet energy. The usefulness of wavelet transform representation of pavement roughness profiles was studied by analyzing the roughness data of 200 flexible pavement and 200 rigid pavement sections. Comparisons were made with four common roughness indices, namely, the international roughness index (IRI), rootmean-square vertical acceleration (RMSVA), mean absolute vertical acceleration (MAVA), and slope variance (SV). It was found that IRI, RMSVA, MAVA, and SV had pairwise coefficients of multiple determination ( R2) ranging from 0.18 to 0.75. But wavelet energy statistics had an R2 of at least 0.857 with each of the roughness indices. Therefore, wavelet energy statistics can be a useful common basis to relate different forms of pavement roughness measures.

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Section: Analysis For Flexible Pavementmentioning

confidence: 65%

Characterizing Road Roughness by Wavelet Transform

Liu

Fwa

2004

Transportation Research Record: Journal of the Transportation R

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“…On the other hand, a report by the environmental agency, UK [35] described that the rigid concrete structures such as sea defences, retaining walls and sea walls may cost as high as 750 US$/m 2 to 7500 US$/m 2 (543 to 5467 £/m 2 ). The flexible erosion control systems do not exhibit strength characteristics, but it is the most used product due to their low cost, as mentioned in Table 2.…”

Section: Cost and Construction-efficiencymentioning

confidence: 99%

Biopolymer-biocement composite treatment for stabilisation of soil against both current and wave erosion

2022

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Increased frequency of extreme weather events has made the conservation of riverbanks and coastlines a global concern. Soil stabilisation via microbially induced calcite precipitation (MICP) is one of the most eco-suitable candidates for improving resilience against erosion. In this study, the erosion characteristics of soil treated with various levels of biocementation are investigated. The samples were subjected to hydraulic flow in both tangential and perpendicular directions in a flume to simulate riverbank and coastal situations. Soil mass loss, eroded volume, and cumulative erosion rates of the treated soil against the applied hydraulic energy density have been reported. Post erosion exposure, the residual soil has been assessed for its properties using needle penetration resistance, precipitated calcium carbonate content and microstructure. It was observed that soil erosion declined exponentially with the increase in calcium carbonate content against the perpendicular waves. However, biocementation leads to brittle fracture beyond a threshold, limiting its efficacy, especially against the tangential waves. Additional composite treatment with a biopolymer was found to improve the resilience of the soil specimens against erosion. The composite treatment required half of the quantity of the biocementing reagents in comparison to the equally erosion-resistant plain biocemented sample. Therefore, stoichiometrically the composite treatment is likely to yield 50% lesser ammonia than plain biocement treatment. This investigation unravels a promising soil conservation technique via the composite effect of biocement and biopolymer.

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“…Researchers have long conducted studies to determine correlations between perceptions of roughness and the objective measures of roughness from various devices. For example, researchers found that the rootmean-square vertical acceleration (RMSVA) obtained from a Mays Ride Meter, which is the difference between adjacent slope measurements, was useful in equipment calibration, but unreliable as a predictor of panel ratings (Hudson, et al 1983). Generally, the lack of agreement between various roughness measuring devices circumvented the definition of a uniformly accepted single-index characterization of roughness until the World Bank defined the IRI in 1982 as a standard, objective measure of roughness (Gillespie, Sayers and Queiroz 1986).…”

Section: Perceptions Of Roughnessmentioning

confidence: 99%

Characterization of Transit Ride Quality

Cutr¹

2016

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Strategies often proposed to combat the growing traffic congestion problems of urban environments target enhancements to increase the use of bus transit. Therefore, service providers are keen to identify and understand factors that could attract more transit riders. Other than affordability, most researchers explored convenience and stress factors such as schedule uncertainty, waiting time, travel time, crowding, noises, and smells. However, few studies evaluated the significance of ride quality. The high cost to collect and analyze roughness data likely deters such studies. This work developed a low-cost smartphone based method and associated data transforms to characterize ride quality for non-uniform speed profiles. The method distinguished between vibrations induced from road unevenness and operator behavior. The authors validated the accuracy of the method by conducting surveys to characterize the perceived roughness intensities from buses traveling routes of distinctly different roughness levels. The surveys found that smooth rides mattered to most passengers, and that rough rides could even lead to some loss of ridership. Additionally, the authors proposed a theory of roughness acclimation and provided some evidence that unlike objective measurements, subjective assessments of ride quality could lead to significant biases and inconsistencies.

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Root-Mean-Square Vertical Acceleration as a Summary Roughness Statistic

Cited by 13 publications

References 0 publications

Characterizing Road Roughness by Wavelet Transform

Characterizing Road Roughness by Wavelet Transform

Biopolymer-biocement composite treatment for stabilisation of soil against both current and wave erosion

Characterization of Transit Ride Quality

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