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.

Use of Long Term Pavement Performance-Seasonal Monitoring Program Data to Develop and Validate a Generalized Regression Model to Predict the In-Situ Resilient Modulus of Subgrade Soils for Pavement Design and Evaluation

2020 ◽  
Vol 2674 (5) ◽  
pp. 673-684
Author(s):  
Mohamed Elshaer ◽  
Christopher DeCarlo ◽  
Wade Lein ◽  
Harshdutta Pandya ◽  
Ayman Ali ◽  
...  
Keyword(s):  
Prediction Model ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Pavement Design ◽  
Pavement Performance ◽  
Regression Approach ◽  
Seasonal Monitoring ◽  
Generalized Regression

Resilient modulus (Mr) is a critical input for pavement design as it is the main property used to evaluate the contribution of subgrade to the overall pavement structure. Considering this, practitioners need simple and accurate ways to determine the Mr of in-situ subgrade without the need for expensive and time-consuming testing. The objective of this study is to develop a generalized regression prediction model for in-situ Mr of subgrades, compare it with established prediction models, and assess the model’s predictions on pavement performance using the Mechanistic-Empirical Pavement Design Guide (Pavement ME). The prediction model was built using field data from 30 pavement sections studied in the Long Term Pavement Performance (LTPP) Seasonal Monitoring Program where backcalculated modulus from falling weight deflectometer testing, in-situ moisture contents, and subgrade material properties were considered in the model. Based on the results, it was found that liquid limit, plasticity index, WPI (the product of percent passing #200 and plasticity index), percent coarse sand, percent fine sand, percent silt, percent clay, moisture content, and their respective interactions were significant predictors of in-situ Mr values. The findings showed that the generalized regression approach was able to predict Mr more accurately than predictions from the Witczak model. To assess the application of the predictive model on pavement performance, three LTPP sections located in New York, South Dakota, and Texas were analyzed to predict the rutting performance based on Mr values obtained from the developed generalized prediction model and those obtained from the current Pavement ME model and then compared with rut depths measured in the field. The findings showed that, for coarse-grained subgrades that have a low degree of plasticity, the generalized regression model predicted rutting performance similar to the embedded Pavement ME model. For fine-grained subgrades, the developed model tends to predict lower rut depths which were closer to the field measured rut depths. Overall, the generalized regression approach was successfully applied to create a simple, practical, cost-effective and accurate Mr prediction model that can be used to estimate the stiffness of subgrades when designing and evaluating pavements.

Using Time Series to Incorporate Seasonal Variations in Pavement Design

1996 ◽  
Vol 1539 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Hesham A. Ali ◽  
Neville A. Parker
Keyword(s):  
Time Series ◽  
Structural Properties ◽  
Seasonal Variations ◽  
Monitoring Program ◽  
Statistical Technique ◽  
Pavement Design ◽  
Seasonal Monitoring ◽  
Program Data ◽  
Series Technique

Analysis of the seasonal monitoring program data of the long term pavement performance program indicated that some pavement structural properties often follow predictable seasonal patterns. Time series is a statistical technique that may be used to develop periodic functions to predict the values of such properties as a function of time. The application of time series technique in characterizing the seasonal variations of pavement structural properties as simulated functions is presented. In addition, the incorporation of such variations in both empirical and mechanistic-empirical methods of flexible pavement design is demonstrated. To this end, a computer program, seasonal variation in pavement design, was written to carry out the required calculations and to facilitate the comparison between empirical and mechanistic-empirical design methods.

Weighting Factor for Seasonal Subgrade Resilient Modulus

1998 ◽  
Vol 1619 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Yun Guan ◽  
Eric C. Drumm ◽  
N. Mike Jackson
Keyword(s):  
Environmental Factors ◽  
Seasonal Variations ◽  
Resilient Modulus ◽  
Effective Means ◽  
Cost Effective ◽  
Weighting Factor ◽  
Pavement Design ◽  
Different Seasons ◽  
Subgrade Modulus

Subgrade resilient modulus is highly dependent on water content, which can vary significantly with a number of seasonal environmental factors. Because the determination of seasonal resilient modulus is cumbersome, it is difficult to include environmental factors in pavement design. The use of a weighting factor for flexible pavement design to include the effects of monthly changes in the subgrade resilient modulus is described. The weighting factor, which was derived from Miner’s linear damage concept and the 1993 AASHTO design equation for flexible pavements, is used to designate a design season. Instead of using multiple values of resilient modulus in the pavement design process, the pavement design may be performed with a single value of subgrade modulus corresponding to this design season. A pavement design based on this design season then is assumed to reflect the seasonal variations in subgrade modulus and the corresponding relative damage that the pavement would sustain over al seasons of the year. The weighting factor can be calculated from laboratory tests of resilient modulus over the range of water contents that may be encountered in the subgrade over different seasons. Alternatively, the weighting factor can be obtained from the resilient modulus backcalculated from seasonal nondestructive tests. The determination of the weighting factor and the design season resilient modulus was demonstrated in three examples and shown to be consistent with the recommendations of the 1993 AASHTO guide. The use of the weighting factor should provide a cost-effective means of including seasonal variations in subgrade properties while minimizing the required number of laboratory resilient modulus tests.

scholarly journals Integrated approaches for predicting soil-water characteristic curve and resilient modulus of compacted fine-grained subgrade soils

2017 ◽  
Vol 54 (5) ◽  
pp. 646-663 ◽  
Author(s):  
Zhong Han ◽  
Sai K. Vanapalli ◽  
Wei-lie Zou
Keyword(s):  
Moisture Content ◽  
Soil Water ◽  
Resilient Modulus ◽  
Characteristic Curve ◽  
Experimental Studies ◽  
Pavement Design ◽  
Soil Water Characteristic Curve ◽  
Subgrade Soils ◽  
Fine Grained ◽  
Integrated Approaches

This paper combines a series of approaches for predicting the soil-water characteristic curve (SWCC) and the variation of the resilient modulus (MR) of compacted fine-grained subgrade soils with moisture content, which is the key information required in mechanistic pavement design methods. The presented approaches for the SWCC and MR are integrated, as (i) they are developed following the same philosophy, (ii) they require only the measurements of the suction and moisture content or MR at saturated and optimum moisture content conditions for prediction, and (iii) the predicted SWCC is used for predicting the MR – moisture content relationship. Experimental studies have been performed on five fine-grained subgrade soils that were collected from different regions in Ontario, Canada, to determine their MR at various external stress levels and post-compaction moisture contents, as well as their SWCCs after the MR tests. Experimental measurements are predicted using the integrated approaches and the empirical approaches currently used in the mechanistic–empirical pavement design guide (MEPDG). It is demonstrated that the integrated approaches are easy to use and show improved reliability in predicting both the SWCC and MR for the investigated subgrade soils in spite of using limited experimental data.

Effects of full-time v. part-time grazing on seasonal changes in milk coagulation properties and fatty acid composition

2021 ◽  
pp. 1-6
Author(s):  
Franziska S. Akert ◽  
Michael Kreuzer ◽  
Carmen Kunz ◽  
Beat Reidy ◽  
Joel Berard
Keyword(s):  
Fatty Acid ◽  
Seasonal Variations ◽  
Milk Fat ◽  
Seasonal Effects ◽  
Full Time ◽  
Fa Composition ◽  
Part Time ◽  
Milk Coagulation ◽  
The Impact ◽  
Feeding Systems

Abstract For this research communication our objective was to investigate to what extent milk coagulation properties and milk fatty acid (FA) composition were affected by different feeding systems, season and their interaction. Eighteen cows in total were subjected to one of three different feeding system treatments: full-time grazing or part-time grazing combined with indoor feeding of fresh grass with low or high concentrate supplementation. Milk was sampled in spring, summer and autumn. Milk coagulation time was 15.0, 19.0 and 17.7 min, coagulation dynamics 1.67, 3.41 and 1.79 min, and curd firmness 52.7, 32.4 and 47.0 mm in spring, summer and autumn, respectively. Thus, milk coagulation properties of the milk were lower during summer. There were strong seasonal effects on milk FA proportions, but there were not always changes with progressing season, or changes were different with respect to the impact of the feeding systems (system × season interaction). The milk fat was favourably rich in oleic acid, conjugated linoleic acid and α-linolenic acid and had a low n-6/n-3 fatty acid ratio in all systems. Factors like seasonal variations in grass composition and the energy balance of the cows were considered relevant for the milk FA composition. Overall, seasonal variations in milk quality were less pronounced with part-time grazing with fresh grass indoors as compared to full-time grazing without concentrate.

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