Determination of Friction Performance of High Friction Surface Treatment Based on Alternative Macrotexture Metric

Surface friction is currently the most common metric for evaluating the performance of high friction surface treatment (HFST). However, friction test methods such as the locked wheel skid tester (LWST) commonly provide a spot measurement. Large variations may arise in the LWST testing on curves. Based on 21 actual HFST projects, a study was performed to use a macrotexture metric, i.e., the mean profile depth (MPD) to evaluate HFST’s performance and improve its quality control (QC)/quality assurance (QA) procedures. The material properties were presented to understand the aspects of HFST. The method for calculating MPD was modified to account for the variations of macrotexture measurements. A vehicle-based test system was utilized to measure MPD periodically over an 18-month period since HFST installation. Statistical analysis was performed on the MPD measurements to identify the effects of influencing factors. Compared with the friction from LWST, MPD was equally effective in evaluating HFST performance. However, the use of MPD eliminated the errors as arisen in LWST testing and made it possible to detect surface distresses, including aggregate loss, delamination, and cracking. The expected overall MPD may be calculated by combining the MPD measurements made three months after installation at different HFST sites and used as a metric for evaluating HFST performance and QC/QA.

Why do clogged porous asphalt pavements give better traffic noise reduction than a dense-graded asphalt pavement?

In Europe, porous asphalt concrete pavements (PAC) are commonly used to reduce traffic noise. Especially the double-layer type (DPAC) provides substantial traffic noise reduction. Unfortunately, PAC pavements compared to dense asphalt pavements have reduced acoustic longevity; the main reason being clogging of the pores and voids, sometimes also more ravelling. The dense-graded pavements considered here are stone mastic asphalts (SMA, in the US known as stone matrix asphalt) which often have surface macrotexture of the same size as the PAC. The main difference is that the PAC has accessible pores/voids providing sound absorption, while the SMA has practically no porosity. One would expect that when the pores in the PAC have become clogged while ravelling is not yet substantial, that the noise property of the PAC would approach that of the SMA. But experimental studies suggest that even when PAC:s are effectively clogged, they retain a certain noise reduction compared to SMA:s. This paper examines this feature of clogged PAC versus SMA and reasons for this unexpected property, for a few Swedish DPAC pavements compared to SMA pavements, with due consideration of possible difference in maximum aggregate size and macrotexture as represented by mean profile depth (MPD) and grading curves.

Analysis of the Anti-Skid Properties of New Airfield Pavements in Aspect of Applicable Requirements

The assessment of the anti-skid properties of airfield pavements is one of the elements in the process of determining their current technical condition, which is important in terms of the safety of air operations. The condition of the pavement should be qualified on the basis of the specified and required values (criteria), in this case, the coefficient of friction and the depth of the texture. Unfortunately, in practice, the assessment of the texture of new airfield pavements raises some doubts with regard to the existing requirements. The work presents an analysis of the results of texture tests for new airfield pavements in relation to current requirements. In addition, the authors proposed a new criterion of average texture depth for new airfield pavements, based on actual field measurement results. Field studies used an innovative method of assessing anti-skid properties with a measuring system that allows simultaneous measurement of the coefficient of friction, μ, and the new continuous coefficient of average profile depth and texture CMPTD, from which MPD (Mean Profile Depth) and ETD (Estimated Texture Depth) can be determined. The results of the tests cast doubt on the possibility of obtaining the average texture depth (currently 1.00 mm) required for new airfield pavements.

Selected Aspects of Pavement Texture Influence on Tire Rolling Resistance

Tire rolling resistance has a significant influence on fuel consumption in cars and trucks and on CO2 emissions. Rolling resistance depends on the tire construction, pavement texture and stiffness, as well as environmental and traffic conditions. This article presents a pilot study on the impact of pavement texture on the rolling resistance of passenger car tires. Reasons why Mean Profile Depth is not a good descriptor of pavement characteristics from the point of view of rolling resistance are presented, and an experimental method which takes into account tire deformation on texture and partial enveloping is described. A method based on testing the volume and depth of tire tread deformation is also proposed.

Application of machine learning for acoustic emissions waveform to classify galling wear on sheet metal stamping tools

Galling wear in sheet metal stamping processes can degrade the product quality and adversely affect mass production. Studies have shown that acoustic emission sensors can be used to measure galling. In the literature, attempts have been made to correlate the acoustic emission features and galling wear in the sheet metal stamping process. However, there is very little attempt made to implement machine learning techniques to detect acoustic emission features that can classify non-galling and galling wear as well as provide additional wear-state information in the form of strong visualisations. In the first part of the paper time domain and frequency domain analysis are used to determine the acoustic emission features that can be used for unsupervised classification. Due to galling wear progression on the stamping tools, the behaviour of acoustic emission waveform changes from stationary to a non-stationary state. The initial change in acoustic emission waveform behaviour due to galling wear initiation is very difficult to observe due to the ratio of change against the large data size of the waveform. Therefore, a time-frequency technique “Hilbert Huang Transform” is applied to the acoustic emission waveform as that is sensitive to change of wear state, and is used for the classification of ‘non galling’ and the ‘transition of galling’. Also, the unsupervised learning algorithm fuzzy clustering is used as comparison against the supervised learning techniques. Despite not knowing a priori the wear state labels, fuzzy clustering is able to define three relatively accurate distinct classes: “unworn”, “transition to galling”, and “severe galling”. In the second part of the paper, the acoustic emission features are used as an input to the supervised machine learning algorithms to classify acoustic emission features related to non-galling and galling wear. An accuracy of 96% was observed for the prediction of non-galling and galling wear using Classification, Regression Tree (CART) and Neural Network techniques. In the last part, a reduced Short Time Fourier Transform of top 10 absolute maximum component acoustic emission feature sets that correlates to wear measurement data “profile depth” is used to train and test supervised Neural Network and CART algorithms. The algorithms predicted the profile depth of 530 unseen parts (530 unseen cases), which did not have any associated labelled depth data. This shows the power of using machine learning techniques that can use a small data training set to provide additional predicted wear-state on a much larger data set. Furthermore, the machine learning techniques presented in this paper can be used further to develop a real-time measurement system to detect the transition of galling wear from measured acoustic emission features.

Effect of ellipse motion paths with different aspect ratios on friction and wear of highly crosslinked polyethylene

Cobalt chromium molybdenum alloy and highly cross-linked polyethylene are selected as the counterpairs in this study to carry out friction and wear testing over different ellipse motion paths to explore the influence of ellipse motion path on friction and wear of prosthesis materials. Here, the analytical methods for the periodic friction coefficient and special point wear are proposed to investigate the relationship between motion paths and tribological properties. The damage mechanism model of high cross-linked polyethyleneunder ellipse motion paths was established, which revealed the connection among material composition, motion paths and friction and wear mechanism. The results show that the friction coefficient and wear morphology are directly affected by changes in motion paths. The friction coefficient decreases with increasing aspect ratios, and the wear profile depth increases with increasing aspect ratios. The spatially resolved friction coefficient curve distinctly exhibits periodic “W”-type variation in elliptical motion paths. The friction coefficient shows maximum values at the long-axis endpoints and minimum values at the short-axis endpoints. There are different wear morphologies in different characteristic areas over the elliptical wear paths. The wear profile depth and width at the long-axis endpoints are larger than those at the short-axis endpoints, and the wear morphology is also more serious.

Tire/Road Rolling Resistance Modeling: Discussing the Surface Macrotexture Effect

This paper deals with the modeling of rolling resistance and the analysis of the effect of pavement texture. The Rolling Resistance Model (RRM) is a simplification of the no-slip rate of the Dynamic Friction Model (DFM) based on modeling tire/road contact and is intended to predict the tire/pavement friction at all slip rates. The experimental validation of this approach was performed using a machine simulating tires rolling on road surfaces. The tested pavement surfaces have a wide range of textures from smooth to macro-micro-rough, thus covering all the surfaces likely to be encountered on the roads. A comparison between the experimental rolling resistances and those predicted by the model shows a good correlation, with an R2 exceeding 0.8. A good correlation between the MPD (mean profile depth) of the surfaces and the rolling resistance is also shown. It is also noticed that a random distribution and pointed shape of the summits may also be an inconvenience concerning rolling resistance, thus leading to the conclusion that beyond the macrotexture, the positivity of the texture should also be taken into account. A possible simplification of the model by neglecting the damping part in the constitutive model of the rubber is also noted.

Spatial Distribution Characteristic of Antimony in Typical Paddy Soil of Eastern Hunan Province, China

Considering the eastern part of Hunan Province as the research area, 34 sampling sites were set up, 198 samples were collected from representative paddy soil, the distribution characteristics of antimony (Sb) were studied. The results showed that: (1) The content of Sb on the surface of paddy soil ranging from 0.07 to 11.00 mg/kg and the geometric mean was 1.56 mg/kg. (2) The distribution of contents of Sb in paddy soil in different areas was shown as Yueyang > Changsha > Zhuzhou > Xiangtan. (3) Sb showed a strong migration in paddy soil in the research area and its content increased initially and then decreased or gradually decreased with the increase of profile depth. (4) The content of Sb in the substratum was significantly affected by parent materials.