Estimation of Pavement Layer Thickness Variability for Reliability-Based Design

2003 ◽  
Vol 1849 (1) ◽  
pp. 156-165 ◽  
Author(s):  
Y. “Jane” Jiang ◽  
Olga Selezneva ◽  
Goran Mladenovic ◽  
Susanne Aref ◽  
Michael Darter
Keyword(s):  
Layer Thickness ◽  
Core Layer ◽  
Pavement Design ◽  
Pavement Performance ◽  
Reliability Based Design ◽  
Thickness Variability ◽  
Design Values ◽  
The Mean ◽  
Thickness Variations ◽  
Distribution Type

Estimating the variability of key pavement design inputs is essential to reliability-based pavement design. The thickness of most pavement layers has a great impact on the outcome of practically all analyses of pavement performance. The within-section layer thickness variability is investigated here, as is the extent of the mean layer thickness deviation from its design thickness. Pavement layer thickness data (elevation and core measurements) from a large number of newly constructed flexible and rigid pavement sections in the Long-Term Pavement Performance (LTPP) program were examined. To determine the distribution type of the thickness data, a combined statistical test for skewness and kurtosis showed that ( a) thickness variations within a layer indicate a normal distribution for 86% of 1,034 layers and ( b) the mean thickness deviations from the design values may be assumed to be normally distributed for a layer having a given type and design thickness. The estimated thickness-within-layer variability values and the estimated typical thickness deviations derived from LTPP data may serve as benchmarks for use in pavement design reliability, construction quality assurance specifications, and other research studies. In addition, statistical comparisons of layer thickness variability indicators were made between the elevation and core layer thickness data to determine whether there are systematic differences between these two measuring methods. These results will be very useful to both researchers and practitioners who develop or use reliability-based pavement design procedures.

Comparison of As-Constructed and As-Designed Flexible Pavement Layer Thicknesses

2003 ◽  
Vol 1853 (1) ◽  
pp. 165-176 ◽  
Author(s):  
Goran Mladenovic ◽  
Y. Jane Jiang ◽  
Olga Selezneva ◽  
Susanne Aref ◽  
Michael Darter
Keyword(s):  
Layer Thickness ◽  
Flexible Pavement ◽  
Target Thickness ◽  
Pavement Performance ◽  
Design Values ◽  
The Mean ◽  
Design Value ◽  
Thickness Deviation ◽  
The Individual ◽  
Distribution Type

Sound pavement design is important for improving pavement performance, but construction is equally critical. Because of variations in pavement construction, the as-constructed pavement layer thickness varies spatially within a pavement section, and the mean constructed pavement layer thickness often deviates from the designed values. The as-constructed pavement layer thicknesses are compared to their design values by using data from the newly constructed flexible pavement sections in the Long-Term Pavement Performance program. First, the distribution type of the mean layer thickness deviation was investigated, and a combined statistical test for skewness and kurtosis showed that the mean thickness deviations may be assumed to be normally distributed for a given layer type and target thickness. Typical thickness deviation summary statistics values were derived to estimate the extent of deviations from the design thicknesses. Second, the analysis showed that elevation thickness data differ from the core examination data. Furthermore, as-constructed layer thickness values were compared to their design values by looking into the percentage of the individual measurements falling into specified ranges from the design values and by using two-sided and one-sided t-tests to compare the mean constructed thicknesses and the design values. The analyses showed that the mean constructed layer thicknesses tend to be above the design value for the thinner layers and below the design value for the thicker layers for the same layer and material type. Results from the study will be useful as inputs for reliability-based design procedures.

scholarly journals Variability in Pavement Design

2015 ◽  
Vol 16 (2) ◽  
pp. 50-67 ◽  
Author(s):  
Paola Dalla Valle ◽  
Nick Thom
Keyword(s):  
Pavement Design ◽  
Pavement Performance ◽  
Design Parameters ◽  
Probability Density Distribution ◽  
Analysis And Design ◽  
The Subject ◽  
The Mean ◽  
Subgrade Modulus ◽  
Input Variables ◽  
The Uk

Abstract This paper presents the results of a review on variability of key pavement design input variables (asphalt modulus and thickness, subgrade modulus) and assesses effects on pavement performance (fatigue and deformation life). Variability is described by statistical terms such as mean and standard deviation and by its probability density distribution. The subject of reliability in pavement design has pushed many highway organisations around the world to review their design methodologies, mainly empirical, to move towards mechanistic-empirical analysis and design which provide the tools for the designer to evaluate the effect of variations in materials on pavement performance. This research has reinforced this need for understanding how the variability of design parameters affects the pavement performance. This study has only considered flexible pavements. The sites considered for the analysis, all in the UK (including Northern Ireland), were mainly motorways or major trunk roads. Pavement survey data analysed were for Lane 1, the most heavily trafficked lane. Sections 1km long were considered wherever possible. Statistical characterisation of the variation of layer thickness, asphalt stiffness and subgrade stiffness is addressed. A sensitivity analysis is then carried out to assess which parameter(s) have the greater influence on the pavement life. The research shows that, combining the effect of all the parameters considered, the maximum range of 15th and 85th percentiles (as percentages of the mean) was found to be 64% to 558% for the fatigue life and 94% to 808% for the deformation life.

Rational Selection of Factors of Safety in Reliability-Based Design of Flexible Pavements in Saudi Arabia

1996 ◽  
Vol 1540 (1) ◽  
pp. 39-47 ◽  
Author(s):  
A. Samy Noureldin ◽  
Essam Sharaf ◽  
Abdulrahim Arafah ◽  
Faisal Al-Sugair
Keyword(s):  
Saudi Arabia ◽  
Performance Prediction ◽  
Flexible Pavement ◽  
Pavement Design ◽  
Pavement Performance ◽  
Design Performance ◽  
Reliability Based Design ◽  
Pavement Engineering ◽  
Pavement Performance Prediction ◽  
Selection Of

Explicit applications of reliability in pavement engineering have been of interest to pavement engineers for the last 10 years. Variabilities in parameters affecting pavement design performance result in variability in pavement performance prediction and thus affect the reliability of how long the pavement will last. Rational quantification of those variabilities is essential for incorporating reliability and selecting the proper factors of safety in the pavement design performance process. The prevailing methodology in Saudi Arabia of quantifying the variability in pavement performance due to the variabilities of the parameters affecting that performance is demonstrated. Factors of safety for flexible pavement design at various reliability levels and based on those prevailing variabilities are presented. These factors of safety are recommended for flexible pavement design in Saudi Arabia.

scholarly journals Permafrost temperature and active-layer thickness of Yakutia with 0.5-degree spatial resolution for model evaluation

2013 ◽  
Vol 5 (2) ◽  
pp. 305-310 ◽  
Author(s):  
C. Beer ◽  
A. N. Fedorov ◽  
Y. Torgovkin
Keyword(s):  
Layer Thickness ◽  
Spatial Resolution ◽  
Active Layer ◽  
Land Surface ◽  
Grid Cell ◽  
Active Layer Thickness ◽  
East Siberia ◽  
Permafrost Temperature ◽  
Surface Models ◽  
The Mean

Abstract. Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. The gridded datasets can be accessed at the PANGAEA repository (doi:10.1594/PANGAEA.808240). Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

2003 ◽  
Vol 1855 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Weng On Tam ◽  
Harold Von Quintus
Keyword(s):  
Pavement Design ◽  
Vehicle Classification ◽  
Pavement Performance ◽  
Traffic Data ◽  
Design Procedures ◽  
Load Spectra ◽  
State Highway ◽  
Pavement Structures ◽  
Empirical Design

Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under NCHRP require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

On shock-induced light-fluid-layer evolution

2021 ◽  
Vol 933 ◽  
Author(s):  
Yu Liang ◽  
Xisheng Luo
Keyword(s):  
Layer Thickness ◽  
Coupling Effect ◽  
Fluid Layer ◽  
Nonlinear Models ◽  
Interfacial Instability ◽  
Dimensional Theory ◽  
One Dimensional ◽  
Helium Gas ◽  
Wave Patterns ◽  
Thickness Variations

Shock-induced light-fluid-layer evolution is firstly investigated experimentally and theoretically. Specifically, three quasi-one-dimensional helium gas layers with different layer thicknesses are generated to study the wave patterns and interface motions. Six quasi-two-dimensional helium gas layers with diverse layer thicknesses and amplitude combinations are created to explore the Richtmyer–Meshkov instability of a light-fluid layer. Due to the multiple reflected shocks reverberating inside a light-fluid layer, the speeds of the two interfaces gradually converge, and the layer thickness saturates eventually. A general one-dimensional theory is adopted to describe the two interfaces’ motions and the layer thickness variations. It is found that, for the first interface, the end time of its phase reversal determines the influence of the reflected shocks on it. However, the reverberated shocks indeed lead to the second interface being more unstable. When the two interfaces are initially in phase, and the initial fluid layer is very thin, the two interfaces’ spike heads collide and stabilise the two interfaces. Linear and nonlinear models are successfully adopted by considering the interface-coupling effect and the reverberated shocks to predict the two interfaces’ perturbation growths in all regimes. The interfacial instability of a light-fluid layer is quantitatively compared with that of a heavy-fluid layer. It is concluded that the kind of waves reverberating inside a fluid layer significantly affects the fluid-layer evolution.

Comparative Analysis of Retinal Nerve Fiber Layer Thickness between Normal and Mild to Moderately Myopic Eyes

2021 ◽  
Vol 37 (4) ◽  
Author(s):  
Gul Nasreen ◽  
Shaheer Suhail Sarwar ◽  
Irfana Bibi ◽  
Muhammad Arslan Ashraf
Keyword(s):  
Optical Coherence Tomography ◽  
Nerve Fiber ◽  
Layer Thickness ◽  
Retinal Nerve Fiber Layer ◽  
Fiber Layer ◽  
Nerve Fiber Layer ◽  
Nerve Fiber Layer Thickness ◽  
Rnfl Thickness ◽  
The Mean ◽  
Retinal Nerve Fiber

Purpose:  To determine the difference between mean retinal nerve fiber layer (RNFL) thickness in myopic eyes (up to -6.00D) and normal eyes. Study Design:  Descriptive observational study. Place and Duration of the Study:  Eye department of Mayo hospital Lahore, from February 2019 to April 2019. Methods:  We compared the mean RNFL between 58 myopic eyes (up to -6.00 D) and age matched 60 normal eyes. The age of the participants was between 12 to 42 years. Complete ocular examination was done and RNFL thickness was measured by using Optical coherence tomography (NIDEX RS-33.0, software-ex 1.5.2).Data was analyzed by independent sample t-test by using SPSS; with P < .05 as significant. Results:  The mean difference among these groups was 5.852 µm with (SE: 1.929). Mean RNFL thickness in myopic group was (95.93 ± 10.158µm) with (SE: 1.334). The result for mean RNFL thickness in myopic eyes was distributed normally as P < .03. Mean RNFL in normal group was (101.78 ± 10.774 µm) with (SE: 1.391), and the result of mean RNFL thickness measured in normal eyes was not distributed normally as P < .20. The results showed that there is a statistically significant difference between mean RNFL thickness measured in normal versus myopic eyes as (P < .003). Conclusion:  There is a significance difference between mean RNFL thickness between myopic eyes and normal eyes as measured by OCT. Careful interpretation of RNFL data in myopic eyes is recommended to avoid misdiagnosis with glaucoma. Key Words:  Retinal Nerve Fiber Layer thickness, Myopia, Optical Coherence Tomography.

The structure of a highly decelerated axisymmetric turbulent boundary layer

2021 ◽  
Vol 929 ◽  
Author(s):  
N. Agastya Balantrapu ◽  
Christopher Hickling ◽  
W. Nathan Alexander ◽  
William Devenport
Keyword(s):  
Boundary Layer ◽  
Pressure Gradient ◽  
Shear Layer ◽  
Layer Thickness ◽  
Boundary Layer Thickness ◽  
Large Scale ◽  
Convection Velocity ◽  
Mean Flow ◽  
Mean Velocity ◽  
The Mean

Experiments were performed over a body of revolution at a length-based Reynolds number of 1.9 million. While the lateral curvature parameters are moderate ( $\delta /r_s < 2, r_s^+>500$ , where $\delta$ is the boundary layer thickness and r s is the radius of curvature), the pressure gradient is increasingly adverse ( $\beta _{C} \in [5 \text {--} 18]$ where $\beta_{C}$ is Clauser’s pressure gradient parameter), representative of vehicle-relevant conditions. The mean flow in the outer regions of this fully attached boundary layer displays some properties of a free-shear layer, with the mean-velocity and turbulence intensity profiles attaining self-similarity with the ‘embedded shear layer’ scaling (Schatzman & Thomas, J. Fluid Mech., vol. 815, 2017, pp. 592–642). Spectral analysis of the streamwise turbulence revealed that, as the mean flow decelerates, the large-scale motions energize across the boundary layer, growing proportionally with the boundary layer thickness. When scaled with the shear layer parameters, the distribution of the energy in the low-frequency region is approximately self-similar, emphasizing the role of the embedded shear layer in the large-scale motions. The correlation structure of the boundary layer is discussed at length to supply information towards the development of turbulence and aeroacoustic models. One major finding is that the estimation of integral turbulence length scales from single-point measurements, via Taylor's hypothesis, requires significant corrections to the convection velocity in the inner 50 % of the boundary layer. The apparent convection velocity (estimated from the ratio of integral length scale to the time scale), is approximately 40 % greater than the local mean velocity, suggesting the turbulence is convected much faster than previously thought. Closer to the wall even higher corrections are required.

Evaluation of Seasonal Effects on Subgrade Soils

2003 ◽  
Vol 1821 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Andrew G. Heydinger
Keyword(s):  
Seasonal Variations ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Test Site ◽  
Pavement Design ◽  
Seasonal Effects ◽  
Pavement Performance ◽  
Climatic Effects ◽  
Subgrade Soils ◽  
Frost Penetration

One objective of the FHWA’s Long-Term Pavement Performance (LTPP) program is to determine climatic effects on pavement performance. The LTPP instrumentation program includes seasonal monitoring program (SMP) instrumentation to monitor the seasonal variations of moisture, temperature, and frost penetration. Findings from the SMP instrumentation are to be incorporated into future pavement design procedures. Data from SMP instrumentation at the Ohio Strategic Highway Research Program Test Road (US-23, Delaware County, Ohio) and other reported results were analyzed to develop empirical equations. General expressions for the seasonal variations of average daily air temperature and variations of temperature and moisture in the fine-grained subgrade soil at the test site are presented. An expression for the seasonal variation of resilient modulus was derived. Average monthly weighting factors that can be used for pavement design were computed. Other factors such as frost penetration, depth of water table, and drainage conditions are discussed.

scholarly journals Estimating Parametersof Gumbel Distribution For Maximum Values By using Simulation

2016 ◽  
Vol 13 (4) ◽  
pp. 707-713
Author(s):  
Baghdad Science Journal
Keyword(s):  
Gumbel Distribution ◽  
Estimation Methods ◽  
Sample Sizes ◽  
Random Data ◽  
The Real ◽  
The Mean ◽  
Distribution Type

In this research estimated the parameters of Gumbel distribution Type 1 for Maximum values through the use of two estimation methods:- Moments (MoM) and Modification Moments(MM) Method. the Simulation used for comparison between each of the estimation methods to reach the best method to estimate the parameters where the simulation was to generate random data follow Gumbel distributiondepending on three models of the real values of the parameters for different sample sizes with samples of replicate (R=500).The results of the assessment were put in tables prepared for the purpose of comparison, which made depending on the mean squares error (MSE).

Sign in / Sign up

Export Citation Format

Share Document