Modeling Stress- and Moisture-Induced Variations in Pavement Layer Moduli

2003 ◽  
Vol 1860 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Cheryl Richter ◽  
Charles W. Schwartz
Keyword(s):  
Moisture Content ◽  
Constitutive Model ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Elastic Theory ◽  
Pavement Materials ◽  
Seasonal Basis ◽  
Stress States ◽  
Stress Dependent ◽  
Moisture Conditions

The in situ moduli of unbound pavement materials vary on a seasonal basis as a function of temperature and moisture conditions. The development of empirical models to predict backcalculated pavement layer moduli as a function of moisture content and stress state is addressed. The work is based on data collected via the Seasonal Monitoring Program of the Long-Term Pavement Performance Program. This research identified fundamental incompatibilities between the stress states computed from layer moduli backcalculated using linear layered-elastic theory and those used in laboratory resilient modulus testing. Important implications of this finding are that (a) application of laboratory-derived constitutive model coefficients in combination with stress states computed using linear layered-elastic theory may yield inaccurate stress-dependent modulus values and (b) meaningful advances in the state of the art for backcalculation of pavement layer moduli cannot be achieved without addressing the inaccuracies and limitations inherent in the use of linear layered-elastic theory to model nonlinear pavement response. Other important findings include the following: (c) variation in moisture content is not always the most important factor causing seasonal variations in pavement layer moduli and (d) a constitutive model form suitable for approximately incorporating the stress and moisture sensitivity of layer moduli backcalculated using linear layered-elastic procedures for practical design purposes is identified.

Seasonal Variation of Backcalculated Subgrade Moduli

1997 ◽  
Vol 1577 (1) ◽  
pp. 70-80 ◽  
Author(s):  
Bing Long ◽  
Mustaque Hossain ◽  
Andrew J. Gisi
Keyword(s):  
Seasonal Variation ◽  
Moisture Content ◽  
Temperature Effect ◽  
Resilient Modulus ◽  
Natural Soil ◽  
Temperature Regimes ◽  
Almost All ◽  
Moisture Conditions ◽  
Falling Weight ◽  
And Behavior

Seasonal variations in pavement material properties and behavior due to variations in temperature and moisture conditions are known to affect the structural performance of pavement. Temperature, subgrade moisture content, and falling weight deflectometer (FWD) deflection data were collected monthly on four asphalt pavement test sections for a year. Subgrade moduli were backcalculated using the elastic layer theory with two calculation schemes and pavement models. Backcalculation of subgrade moduli by subdividing the subgrade into a compacted subgrade layer and a natural soil subgrade layer resulted in compacted subgrade moduli that are more sensitive to the seasonal variation for all sites. It was found that for almost all sites, the patterns of subgrade response, in terms of subgrade moduli versus subgrade moisture content, simulated sine-shaped forms signifying a temperature effect. The temperature effect was confirmed by the strong correlation between backcalculated subgrade moduli and pavement surface temperature during FWD tests. The lowest backcalculated subgrade moduli were obtained for two sections during months when asphalt surface temperatures were excessively high (greater than 40°C). Both backcalculation schemes showed similar trends in variation of subgrade moduli over seasons. When the AASHTO relative damage concept was used to compute the effective roadbed soil resilient modulus for design, similar values were found for both schemes for most of the sites. The minimum frequency of FWD testing to capture the seasonal variation of subgrade was found to be three tests per year, or testing every fourth month, assuming that unusually high temperature regimes could be avoided.

Experimental Verification of Resilient Deformation for Granular Subgrades

1998 ◽  
Vol 1639 (1) ◽  
pp. 12-22 ◽  
Author(s):  
W. Virgil Ping ◽  
Zenghai Yang
Keyword(s):  
Moisture Content ◽  
Laboratory Test ◽  
Resilient Modulus ◽  
Soil Samples ◽  
Load Test ◽  
Experimental Program ◽  
Rigid Plate ◽  
Plate Load Test ◽  
Reconstituted Soil ◽  
Moisture Conditions

Results of an experimental program utilizing the repetitive rigid plate load test in a test-pit facility and the laboratory resilient modulus test are presented for five typical subgrades in Florida. The subgrade materials were tested in the test pit under three different moisture conditions, that is, (1) optimum, (2) drained and dried, and (3) soaked. Laboratory resilient modulus tests were conducted on reconstituted soil samples simulating the various moisture conditions. The resilient modulus was significantly affected by the moisture content of granular subgrades. A comparison between the deformations measured from the test-pit test and the deformation calculated from the laboratory test was made. It was experimentally verified that the resilient modulus resulting from the laboratory triaxial test could be used to predict the resilient deformation of pavement subgrade layers.

Use of an Artificial Neural Network Approach for the Prediction of Resilient Modulus for Unbound Granular Material

2018 ◽  
Vol 2672 (52) ◽  
pp. 23-33 ◽  
Author(s):  
Sajib Saha ◽  
Fan Gu ◽  
Xue Luo ◽  
Robert L. Lytton
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Moisture Content ◽  
Physical Properties ◽  
Regression Models ◽  
Resilient Modulus ◽  
Base Materials ◽  
Ann Models ◽  
Artificial Neural ◽  
Stress Dependent

The resilient modulus ( MR) is a fundamental material property that has a direct effect on the design and analysis of pavement structures. Many regression models have been developed previously to predict the coefficients of the MR model from physical properties of base materials. However, the predicted model coefficients are confined to either a limited number of base materials or result in poor accuracy. To overcome this issue, a moisture- and stress-dependent model is adopted in this study to precisely estimate MR of unbound base materials in unsaturated conditions, and a set of artificial neural network (ANN) models is developed to predict the coefficients of this model from base physical properties. The developed ANN models consist of seven input variables, ten hidden neurons, and one output variable. A large unbound base dataset was collected from the Long Term Pavement Performance (LTPP) database and used to train and generalize the network. Soil physical properties such as gradation (percent passing No. 3/8 sieve, percent passing No. 200 sieve), gradation shape parameter and scale parameter, index properties (i.e., plastic limit and plasticity index), maximum dry density, optimum moisture content, and test moisture content were selected as inputs for the ANN model. The MR values estimated using the predicted coefficients were compared with the experimental data collected from LTPP and showed an R2 value above 0.9, which is much higher than the MR values computed using regression models. Finally, the MR test results from different sources were used to validate the developed ANN models.

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 Spatial and temporal variation of methane emissions in drained eutrophic peat agro-ecosystems: drainage ditches as emission hotspots

2008 ◽  
Vol 5 (2) ◽  
pp. 1237-1261 ◽  
Author(s):  
A. P. Schrier-Uijl ◽  
E. M. Veenendaal ◽  
P. A. Leffelaar ◽  
J. C. van Huissteden ◽  
F. Berendse
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Water Table ◽  
Soil Moisture Content ◽  
Explanatory Variable ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Ch4 Emissions ◽  
Intensively Managed ◽  
Moisture Conditions

Abstract. Our research investigates the spatial and temporal variability of methane (CH4) emissions in two drained eutrophic peat areas (one intensively managed and the other less intensively managed) and the correlation between CH4 emissions and soil temperature, air temperature, soil moisture content and water table. We stratified the landscape into landscape elements that represent different conditions in terms of topography and therefore differ in moisture conditions. There was great spatial variability in the fluxes in both areas; the ditches and ditch edges (together 27% of the landscape) were methane hotspots whereas the dry fields had the smallest fluxes. In the intensively managed site the fluxes were significantly higher by comparison with the less intensively managed site. In all the landscape element elements the best explanatory variable for CH4 emission was temperature. Neither soil moisture content nor water table correlated significantly with CH4 emissions, except in April, where soil moisture was the best explanatory variable.

scholarly journals Experimental Study on Dynamic Resilient Modulus of Lime-Treated Expansive Soil

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zheng Lu ◽  
Yang Zhao ◽  
Shaohua Xian ◽  
Hailin Yao
Keyword(s):  
Moisture Content ◽  
Environmental Changes ◽  
Resilient Modulus ◽  
Expansive Soils ◽  
Expansive Soil ◽  
Confining Pressure ◽  
Triaxial Tests ◽  
The Stability ◽  
Compaction Degree

Dynamic resilient modulus is the design index of highway subgrade design code in China, which is significantly affected by the traffic loads and environmental changes. In this study, dynamic triaxial tests were conducted to investigate the influence of moisture content, compaction degree, cyclic deviator stress, and confining pressure on lime-treated expansive soil. The suitability of UT-Austin model to lime-treated expansive soils was verified. The results indicate that the dynamic resilient modulus of lime-treated expansive soils increases nonlinearly with the increase of compaction degree, while decreases nonlinearly with the increase of dynamic stress level. The dynamic resilient modulus decreases linearly with the increase of moisture content and increases linearly with the increase of confining pressure. Moreover, the moisture content has a more significant effect on the dynamic resilient modulus of lime-treated expansive soil. Therefore, it is necessary to ensure the stability of soil humidity state and its excellent mechanical properties under long-term cyclic loading for the course of subgrade filling and service. Finally, the calculated results of the UT-Austin model for dynamic resilient modulus show a good agreement with the test results.

Evaluate the Importance of Shear Modulus in Dynamic FEM of Flexible Pavement Considering AC Cross-Anisotropy

2016 ◽  
Author(s):  
Mesbah U. Ahmed ◽  
Rafiqul A. Tarefder
Keyword(s):  
Shear Modulus ◽  
Resilient Modulus ◽  
Vertical Plane ◽  
Element Model ◽  
Tire Pressure ◽  
Stress Strain ◽  
Viscoelastic Parameters ◽  
Cross Anisotropy ◽  
As Stress ◽  
Stress Dependent

Goal of this study is to evaluate the effect of shear modulus variation on pavement responses, such as stress-strain, under dynamic load incorporating the AC cross-anisotropy. A dynamic Finite Element Model (FEM) of an instrumented asphalt pavement section on Interstate 40 (I-40) near Albuquerque, New Mexico, is developed in ABAQUS to determine stress-strain under truck tire pressure. Laboratory dynamic modulus tests were conducted on the AC cores to determine the temperature and frequency varying modulus values along both vertical and horizontal directions. The test outcomes are used to produce cross-anisotropic and viscoelastic parameters. Resilient modulus tests are conducted on granular aggregates from base and subbase layer to determine the nonlinear elastic and stress-dependent modulus values. These material parameters are integrated to the FEM through a FORTRAN subroutine via User Defined Material (UMAT) in the ABAQUS. The developed FEM is validated using the pavement deflections and stress-strain data under Falling Weight Deflectometer (FWD) test. The validated dynamic FEM is simulated under the non-uniform vertical tire contact stress. For the parametric study to investigate the effect of shear modulus variation on pavement responses, the validated FEM is simulated by varying the shear modulus in the AC layer. The results show that the variation in shear modulus along a vertical plane barely affects the tensile strain at the bottom of the AC layer and vertical compressive strains in both AC and unbound layers.

Hygrothermal Behavior of Advanced Polymers Above Water Boiling Temperatures

2014 ◽  
Vol 136 (1) ◽  
Author(s):  
Changsoo Jang ◽  
Bongtae Han
Keyword(s):  
Thermal Expansion ◽  
Moisture Content ◽  
Coefficient Of Thermal Expansion ◽  
Measurement Data ◽  
Hybrid Procedure ◽  
Boiling Temperature ◽  
Hygrothermal Behavior ◽  
Expansion Behavior ◽  
Wide Range ◽  
Moisture Conditions

Hygroscopic and thermal expansion behavior of advanced polymers is investigated when subjected to combined high temperature and moisture conditions. An enhanced experimental–numerical hybrid procedure is proposed to overcome the limitations of the existing methods when used at temperatures above the water boiling temperature. The proposed procedure is implemented to measure the hygrothermal strains of three epoxy molding compounds and a no-filler underfill over a wide range of temperatures including temperatures beyond the water boiling temperature. The effects of moisture content on the glass transition temperature (Tg) and coefficient of thermal expansion (CTE) are evaluated from the measurement data. A formulation to predict the Tg change as a function of moisture content is also presented.

scholarly journals Modeling the Resilient Modulus Variation of In Situ Soils due to Seasonal Moisture Content Variations

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Kevin Gaspard ◽  
Zhongjie Zhang ◽  
Gavin Gautreau ◽  
Khalil Hanifa ◽  
Claudia E. Zapata ◽  
...  
Keyword(s):  
Moisture Content ◽  
Resilient Modulus ◽  
Optimum Moisture Content ◽  
Test Method ◽  
Large Scatter ◽  
Controlling Parameter ◽  
Base Course ◽  
The Relationship ◽  
Level 2

LTRC is conducting a research project to determine the seasonal variation of subgrade resilient modulus (MR) in an effort to implement PavementME. One objective of that project, which is presented in this paper, was to locally calibrate the Enhanced Integrated Climate Model’s (EICM Fenv) curve for seasonal subgrade MR changes. Shelby tube sampling was conducted on six different roadways to a depth of approximately 7.92 m beneath the shoulder pavement’s base course. The AASHTO T-99 MR test method was used on all samples with an additional eight specimens being tested with NCHRP 1–28A MR test method. Four soils from Louisiana which were not from the six roadways were also tested and included in the analyses. Once the MR tests were completed and plotted, it was noticed that there was a rather large scatter (R2 = −0.266) around the EICM Fenv curve. The authors hypothesized that this occurred due to the density differences between in situ and remolded specimens. Further analyses confirmed this hypothesis. LTRC developed a new method based on the EICM Fenv method to determine the relationship between changes in subgrade MR as a function of changes in moisture content with the in situ moisture content and MR used as the control. This method differs from the EICM Fenv in that the EICM Fenv uses optimum moisture content as the controlling parameter. The LTRC method can be used for design purposes as well as level 2 inputs into the EICM.

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