Factors Influencing the Determination of a Subgrade Resilient Modulus Value

Factors Influencing the Determination of a Subgrade Resilient Modulus Value
Author: Khaled Ksaibati
Publisher:
Total Pages: 38
Release: 1993
Genre: Pavements
ISBN:

This report describes a study jointly conducted by the University of Wyoming and the Wyoming Department of Transportation to examine the factors influencing the determination of a subgrade resilient modulus value. The objectives of this study were to first, investigate the importance of several fundamental soil properties in determining a design subgrade resilient modulus value; and second, to define the actual relationship between back calculated and laboratory based resilient modulus values for typical cohesive subgrade soils in Wyoming. This study consisted of selecting nine test sites with cohesive subgrade soils in the state of Wyoming, conducting laboratory testing on subgrade cores obtained in 1992 and 1993, determining several fundamental soil properties on these cores, and using deflection data from these nine sites to determine resilient modulus values from three back calculation programs. The data analysis resulted in several important conclusions about factors that influence the selection of a design subgrade resilient modulus value.

Measurement of the Resilient Modulus of Subgrade Materials for Mechanistic-empirical Pavement Design Guide in Wyoming

Measurement of the Resilient Modulus of Subgrade Materials for Mechanistic-empirical Pavement Design Guide in Wyoming
Author: Zachary R. Henrichs
Publisher:
Total Pages: 319
Release: 2015
Genre: Pavements
ISBN: 9781321982947

To improve the pavement design and construction in Wyoming, the Wyoming Department of Transportation (WYDOT) is adopting the Mechanistic-Empirical Pavement Design Guide (MEPDG). Calibration of local subgrade materials are needed to implement the MEPDG. This thesis describes the measurement of resilient modulus (Mr) of subgrade materials and prepares a catalog of representative subgrade properties. As part of the comprehensive testing program, subgrade soil samples were collected from 12 locations throughout the state for standard laboratory tests and Mr test. A testing protocol for Mr was developed by modifying the AASHTO Designation: T-307 to incorporate WYDOT practices. Test results show that Mr changes with axial loads, confining pressures, soil types, and depths beneath the pavement. Regression models were developed using statistical methods and design charts were established for estimating Mr-values. The outcomes of this research will facilitate the full implementation of the MEPDG in the state of Wyoming.

Back-calculation of Subgrade Resilient Modulus for Mechanistic-empirical Pavement Design in Wyoming

Back-calculation of Subgrade Resilient Modulus for Mechanistic-empirical Pavement Design in Wyoming
Author: Daniel K. Hellrung
Publisher:
Total Pages: 103
Release: 2015
Genre: Pavements
ISBN: 9781321892161

In an effort to build more cost effective and robust pavement structures, the Wyoming Department of Transportation (WYDOT) is in the transition of adopting the Mechanistic-Empirical Pavement Design Guide (MEPDG) instead of the 1993 AASHTO Pavement Design Guide. The University of Wyoming is currently conducting a comprehensive research study to facilitate the implementation of the MEPDG in the state. This thesis describes using a Falling Weight Deflectometer (FWD) as a non-destructive testing method for data collection and the development of a back-calculation testing protocol for estimating the resilient modulus of subgrade soils in Wyoming. During the summer of 2013, FWD testing was performed at 32 test sites throughout the state of Wyoming. Deflection measurements were collected and used to back-calculate the resilient modulus of the subgrade at each test site. The back-calculation protocol was developed by modifying the user guide of MODTAG, a back-calculation software, to achieve consistent and realistic back-calculated modulus results. Additionally, using these back-calculation results and laboratory measured modulus results for the same test site, two linear regression models were developed to correct the back-calculation results to laboratory equivalent values. The sum of square error (SSE) was used to compare the models and then select the most suitable one. The findings of this research will facilitate the MEPDG calibration which will help with the implementation of the MEPDG in the state of Wyoming.

Determination of Resilient Modulus Values for Typical Plastic Soils in Wisconsin

Determination of Resilient Modulus Values for Typical Plastic Soils in Wisconsin
Author: Hani Hasan Titi
Publisher:
Total Pages: 316
Release: 2011
Genre: Pavements
ISBN:

The objectives of this research are to establish a resilient modulus test results database and to develop correlations for estimating the resilient modulus of Wisconsin fine-grained soils from basic soil properties. A laboratory testing program was conducted on representative Wisconsin fine-grained soils to evaluate their physical and compaction properties. The resilient modulus of the investigated soils was determined from the repeated load triaxial (RLT) test following the AASHTO T307 procedure. The laboratory testing program produced a high-quality and consistent test results database.

Intelligent and Soft Computing in Infrastructure Systems Engineering

Intelligent and Soft Computing in Infrastructure Systems Engineering
Author: Kasthurirangan Gopalakrishnan
Publisher: Springer
Total Pages: 330
Release: 2009-11-23
Genre: Computers
ISBN: 3642045863

The term “soft computing” applies to variants of and combinations under the four broad categories of evolutionary computing, neural networks, fuzzy logic, and Bayesian statistics. Although each one has its separate strengths, the complem- tary nature of these techniques when used in combination (hybrid) makes them a powerful alternative for solving complex problems where conventional mat- matical methods fail. The use of intelligent and soft computing techniques in the field of geo- chanical and pavement engineering has steadily increased over the past decade owing to their ability to admit approximate reasoning, imprecision, uncertainty and partial truth. Since real-life infrastructure engineering decisions are made in ambiguous environments that require human expertise, the application of soft computing techniques has been an attractive option in pavement and geomecha- cal modeling. The objective of this carefully edited book is to highlight key recent advances made in the application of soft computing techniques in pavement and geo- chanical systems. Soft computing techniques discussed in this book include, but are not limited to: neural networks, evolutionary computing, swarm intelligence, probabilistic modeling, kernel machines, knowledge discovery and data mining, neuro-fuzzy systems and hybrid approaches. Highlighted application areas include infrastructure materials modeling, pavement analysis and design, rapid interpre- tion of nondestructive testing results, porous asphalt concrete distress modeling, model parameter identification, pavement engineering inversion problems, s- grade soils characterization, and backcalculation of pavement layer thickness and moduli.

Resilient Modulus Prediction Employing Soil Index Properties

Resilient Modulus Prediction Employing Soil Index Properties
Author:
Publisher:
Total Pages: 64
Release: 2004
Genre:
ISBN:

Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical specimens. Because the test is complex and time-consuming, in-situ tests would be desirable if reliable correlation equations could be established. Alternately, MR can be obtained from correlation equations involving stress state and soil physical properties. Several empirical equations have been suggested to estimate the resilient modulus. The main focus of this study is to substantiate the predictability of the existing equations and evaluate the feasibility of using one or more of those equations in predicting resilient modulus of Mississippi soils. This study also documents different soil index properties that influence resilient modulus. Correlation equations developed by the Long Term Pavement Performance (LTPP), Minnesota Road Research Project, Georgia DOT, Carmichael and Stuart, Drumm et al., Wyoming DOT, and Mississippi DOT are studied/analyzed in detail. Eight road (subgrade) sections from different districts were selected, and soils tested (TP 46 Protocol) for MR in the laboratory. Other routine laboratory tests were conducted to determine physical properties of the soil. Validity of the correlation equations are addressed by comparing measured MR to predicted MR. In addition, variations expected in the predicted MR due to inherent variability in soil properties is studied by the method of point estimates. The results suggest that LTPP equations are suited for purposes of predicting resilient modulus of Mississippi subgrade soils. For fine grain soils, even better predictions are realized with the Mississippi equation. A sensitivity study of those equations suggests that the top five soil index properties influencing MR include moisture content, degree of saturation, material passing #200 sieve, plasticity index and density.