Skew-normal log-volatility model of road surface profile. (1st September 2022)

• Record Type: Journal Article
• Authors: Mobasserfar, Yasin; Adibnazari, Saeed; Shariyat, Mohammad
• Is Part Of: Mechanical systems and signal processing. Volume 177(2022)
• Publication Date: 2022-09-01
• Subjects: Particle filter -- Road profile -- Skew-normal distribution -- Moving average model -- Stochastic volatility; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109236
• Languages: English
• ISSNs: 0888-3270

Abstract

Graphical abstract: Highlights: A new model of the road roughness is developed with skew-normal distribution for the logarithm of the road volatility. A general detailed modeling procedure of the road roughness profile is presented with general assumptions. Bayesian methods are used to estimate the road volatility while assessing the uncertainty associated with the estimation. Fatigue damage index (FDI) calculations based on the new road roughness model show enhanced fatigue damage prediction accuracy. Abstract: Road roughness-induced vibrations are the main source of fatigue damage accumulation in vehicles. Hence, road surface profile modeling and simulation are of high importance when it comes to vehicle fatigue damage assessment. This research focuses on uncovering the statistical distributions that describe the characteristics of road loads that affect fatigue damage accumulation. Particle filtering is deployed to estimate the log-volatility of the road surface profile by assuming a random walk behavior for the hidden log-volatility. The skew-normal distribution with three parameters is fitted to the estimated log-volatility. The inferred parameters are used for synthesizing artificial road profiles used in a vehicle simulation to calculate fatigue damage indices (FDI). The new road profile model outperforms all the previous models in predicting the real road FDI.