Musharraf Zaman

Comparative Laboratory Study of Sasobit and Aspha-Min Additives in Warm-Mix Asphalt

Warm-mix asphalt (WMA), which reduces the production temperatures (mixing and compaction) while maintaining the advantages of hot-mix asphalt (HMA), is becoming an attractive paving material. In this study, rheological properties of two commonly used performance grade (PG) binders (PG 64-22 and PG 70-28) were evaluated, with and without Sasobit and Aspha-Min additives. For PG 64-22,2%, 3%, and 4% Sasobit additive reduced the mixing temperature of the pure binder from 163°C to 147°C (i.e., by 16°C). In case of the PG 70-28, the reductions are 10°C, 12°C and 13°C, respectively, for 2%, 3%, and 4% Sasobit additive. No significant decrease in mixing temperature by the Aspha-Min additive was observed in using the rotational viscometer. Evaluation of the binders on the basis of G*/sin(δ) demonstrates no negative effect on high-temperature grading due to high-temperature viscosity reduction. With the addition of 4% Sasobit additive, the high-temperature binder grading of PG 64 (actually PG 65) increases to PG 69, while 4% Sasobit additive improves the PG 70 (actually PG 75) to PG 80. No significant changes in grading were observed with the addition of the Aspha-Min additive. In fact, reduction in binder viscosity and improvement in binder grading without increasing the viscosity indicate two-way reductions (both direct and indirect) in production temperatures by the Sasobit additive. Finally, the Sasobit additive is found to decrease the asphalt pavement analyzer rut depths significantly, and these rut depths correlate well with the rutting factor G*/sin(δ). It was also observed that rutting potential decreases with decreasing mixing and compaction temperatures. Comparatively, a smaller reduction in rut depths was observed by adding the Aspha-Min additive.

Effect of Sasobit and Aspha-Min on Wettability and Adhesion Between Asphalt Binders and Aggregates

The influence of natural wax in asphalt binders and hot-mix asphalt has been studied for decades, with consideration of both negative and positive effects. Recent advances in warm-mix asphalt (WMA) have spurred interest in the use of commercial waxes such as Sasobit and Asphaltan B as additives in asphalt binders to achieve certain positive effects. Despite a number of previous studies, the effect of Sasobit on wettability and adhesion between asphalt binders and aggregates is not fully understood. Likewise, the effect of water vapor released from Aspha-Min, another WMA additive, at production temperatures is not adequately understood, although such water may negatively influence the behavior of WMA. In the present study, the effect of Sasobit and Aspha-Min on wettability and adhesion was investigated using the surface free energy (SFE) method. Dynamic advancing-wetting contact angles were measured for wettability (coating) and dewetting-receding contact angles were measured to evaluate adhesion. It was observed that Sasobit increases the wettability of asphalt binders over aggregates, as indicated by the change in the spreading coefficient. Conversely, a general trend is that Sasobit reduces the adhesion (free energy of adhesion) between asphalt binders and aggregates. In this study, moisture susceptibility is defined as the amount of spontaneously released free energy due to the breaking of the binder-aggregate bond with water. For PG 64-22, a small or no reduction in moisture susceptibility was observed; for PG 70-28, an increase in moisture susceptibility was observed. In case of the Aspha-Min, the overall SFE results are insignificant.

Correlation Between Resilient Modulus, Moisture Variation, and Soil Suction for Subgrade Soils

In recent years, interest in determining the influence of moisture changes on the resilient modulus (MR) of subgrade soils beneath a pavement has increased. This is because the 1993 AASHTO Guide for Design of Pavement Structures recommends using a single MR value. The design MR is expected to account for the seasonal variation in subgrade moisture content. This study was undertaken to evaluate the variation of MR with postcompaction moisture content and suction of selected subgrade soils in Oklahoma. A sandy soil (S-Soil) and a clayey soil (C-Soil) were used for laboratory testing. The C-Soil specimens to be subjected to wetting were prepared by a modified compaction method. The proposed method was expected to enhance the flow of water in a specimen during the wetting process. New laboratory procedures for wetting and drying of specimens were also introduced and were used to establish correlations among MR, moisture variation, and suction. Results indicate that MR-moisture content relationships for C-Soil exhibit a hysteretic behavior due to wetting and drying. A similar behavior was observed for S-Soil. The C-Soil was more susceptible than the S-Soil to moisture variation, as expected. It was also observed that changes in MR values and suction were influenced by the initial (compaction) moisture content.

Fracture toughness of a soft sandstone

Abstract Fracture toughness of a rock/material is important in the design of rock drilling/boring equipment, rock bursting, prediction of rock drilling forces, hydraulic fracturing, wellbore stability and stability of jointed rock masses. A series of fracture toughness tests under mode-I, mode-II and mixed-mode (I–II) loading conditions were conducted on straight-edge notch Brazilian disk (SENBD) specimens in an attempt to develop an empirical failure envelope under both tension-shear and compression-shear conditions. This series of tests is the first of its kind on a naturally weakly-cemented Antler sandstone. Even though there have been published data on artificially cemented sandstones, there are no data on mixed-mode fracture toughness of such soft formations. The SENBD specimen configuration used herein provides consistent failure patterns and development of a failure envelope in the compression-shear zone, as well. Microscopic studies using thin sections of tested and untested specimens were carried out to study the fracture propagation at micro-level.

Field and Laboratory Evaluation of Cement Kiln Dust as a Soil Stabilizer

A field and laboratory study was conducted to evaluate cement kiln dust (CKD) as a soil stabilizer. The performance of CKD from three different cement manufacturers was compared with that of quicklime. Field-work involved construction of test sections along a rural highway in Oklahoma. Observations were made to compare construction requirements for CKD and lime. Treated soil samples were collected from the field to prepare specimens for unconfined compression testing in the laboratory. In situ testing included dynamic cone penetration testing in the stabilized subbase and falling weight deflectometer testing after completion of the pavement. Chemical testing was conducted to determine the chemical makeup of each dust, and soil-CKD mixtures were tested for pH response. Chemical tests on the CKD and CKD-soil mixtures revealed aspects of the CKD composition that can be correlated with the degree of stabilization. Regarding strength improvements, results showed that CKD from one cement plant performed significantly better than lime and CKD from other plants. The laboratory and field test data showed that, overall, CKD was more effective than quicklime for stabilizing soil. Additional laboratory tests showed that the influence of CKD and lime on the plasticity index of soils was similar and that both additives imparted some resistance to freeze-thaw and wet-dry cycles. Observations indicate that treatment with CKD can be cost-effective and that it requires less construction time than treatment with quicklime.

A Laboratory and Statistical Evaluation of Factors Affecting Rutting

This research identifies the most significant factors from those factors evaluated which affect rut potential of Hot-Mix Asphalt (HMA). Mixture rut potential is determined using an Asphalt Pavement Analyzer (APA) in the laboratory. The experimental program employed in this study consists of three sets of tests and each set represents a matrix whose elements are rut factors. In Set A, seven factors, each at two levels, are examined using a mixture of limestone aggregates designed in accordance with Superpave method. The test results are analyzed statistically. The analysis results presented using Set A show that binders performance grade (PG), specimen type, test temperature and moisture in test specimen affect a mixtures rutting performance significantly. Wheel load, asphalt content and hose pressure at the selected levels in Set A are shown to be less significant. In Set B six factors, aggregate gradation, temperature, moisture, asphalt content, load and hose pressure, are investigated using one Hveem designed mixture with gravel aggregates. Gradation, temperature, asphalt content and moisture are found to be significant. The levels of asphalt content selected for Set B to be one at optimum and the other at one percent more than the optimum asphalt content. Similar results are found for the test Set C with five factors, temperature, gradation, moisture, load and hose pressure. A predicted rut depth and its range under the influence of the significant factors studied in Set A are also determined and verified by additional experiments. The paper developed and described a detail statistical procedure to analyze a designed experimental program to interpret test results without the need for a full factorial approach.

Applications of time-dependent pseudo-3D stress analysis in evaluating wellbore stability

Abstract Recent studies have shown that the coupled fluid-deformation effects may significantly influence stress and pore pressure distributions around the wellbore in fluid saturated porous media, as well as its stability. Therefore, the poroelastic effect must be considered in stability analysis of inclined wellbores, especially when time-dependent/delayed borehole failure is considered. However, a complicated numerical technique is required to evaluate stress and pore pressure distributions around the wellbore based on the poroelastic model. It may not be convenient to perform the aforementioned analysis of the deviated wellbore in industry applications without a computer aided engineering (CAE) software. A window based software, PBORE-3D, has been developed recently for poroelastic analysis of inclined boreholes. The applications and capabilities of PBORE-3D are described in the present paper. The poroelastic effects on the pore pressure and the stress concentration around the wellbore, and the wellbore stability, are analyzed using this friendly CAE software.

Gradation and Moisture Effects on Resilient Moduli of Aggregate Bases

Resilient modulus (M R ) which properly characterizes the load-deformation response of pavement materials under traffic loading, is evaluated. The M R values due to three different gradations and three different moisture contents were investigated for the Richard Spur and the Sawyer aggregates, which are commonly used in Oklahoma as the subbase or base materials of roadway pavements. The three gradations were finer limit, median, and coarser limit, as specified by the Oklahoma Department of Transportation for Type A aggregate. The three moisture contents selected are optimum moisture content (OMC), 2 percent below OMC, and 2 percent above OMC. To investigate the variability of the test results, six duplicate M R tests under identical conditions were performed for each case by using the AASHTO T294-94 method. Furthermore, the material properties, K1 and K2, which are required input in the AASHTO pavement design equation, were evaluated for the M R values obtained. Finally, multiple linear regression models for predicting the M R values of the two aggregates were established.

Neural Network–Based Intelligent Compaction Analyzer for Estimating Compaction Quality of Hot Asphalt Mixes

Continuous real-time estimating of compaction quality during the construction of a hot mix asphalt (HMA) pavement is addressed in this paper. The densification of asphalt pavements during construction usually is accomplished by using vibratory compactors. During compaction, the compactor and the asphalt mat form a coupled system whose dynamics are influenced by the changing stiffness of the mat. The measured vibrations of the compactor along with process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be used to predict the asphalt mat density. Contrary to existing techniques in the literature in which a model is developed to fit experimental data and to predict mat density, a neural network-based approach is adopted that is model-free and uses pattern-recognition techniques to estimate density. The neural network is designed to read the entire frequency spectrum of roller vibrations and to classify these vibrations into different levels. The intelligent asphalt c...

A Novel Neural Network-Based Asphalt Compaction Analyzer

Achieving the desired density during field compaction of asphalt mixes is critical to meeting the design specifications of an asphalt pavement. Existing techniques measure the density of asphalt mixes at a discrete number of points. As such, the process is cumbersome, time consuming, and is not indicative of the overall compaction achieved unless large amounts of data is collected and analyzed. In this paper, the concept of a novel neural network-based asphalt compaction analyzer capable of predicting the density continuously, in real time, during the construction of the pavement is presented. The concept is verified using laboratory data from an asphalt vibratory compactor (AVC). The compaction analyzer is based on the hypothesis that a vibratory compactor and the hot mix asphalt (HMA) mat form a coupled system having unique vibration properties. The measured vibrations of the compactor along with the process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be used to predict the density of the asphalt mat. Vibration data obtained during compaction of asphalt mixes in the laboratory is used to design and train the neural network (NN). The trained NN is then used to continuously predict the degree of compaction in real time. The proposed approach is validated through compaction studies in the laboratory. Preliminary field studies demonstrate the capability of the analyzer in predicting the density of an asphalt pavement during construction.