Refinement of the Hot-Mix Asphalt Ignition Method for High-Loss Aggregates

2005 ◽  
Vol 1907 (1) ◽  
pp. 128-134
Author(s):  
Graham C. Hurley ◽  
Brian D. Prowell
Keyword(s):  
Standard Deviation ◽  
Standard Method ◽  
Aggregate Size ◽  
Maximum Aggregate Size ◽  
High Loss ◽  
Ignition Furnace ◽  
Aggregate Breakdown ◽  
Furnace Control ◽  
Asphalt Content ◽  
Glass Cleaning

Four methodologies for determining the asphalt content of mixtures containing high-loss aggregates in the ignition furnace were evaluated: the standard method using the Thermolyne furnace (control), the Troxler NTO infrared furnace, the Ontario method, and a Tempyrox glass-cleaning oven. Six aggregate sources with high ignition furnace aggregate corrections were obtained from around the country: four dolomites, a basalt, and a serpentine/chlorite. Calibration factors were determined for each method at optimum asphalt content. Additional samples were then tested at optimum plus 0.5% asphalt content, and the measured asphalt content was calculated by using the correction factor determined for that method and aggregate source. The Tempyrox Pyro-Clean furnace, commonly used for cleaning laboratory glassware, produced the lowest aggregate correction factors. The standard method and the Ontario method, both using the Thermolyne ignition furnace, produced the smallest bias or error in measured asphalt content. The standard deviation of the corrected asphalt contents for these high-loss sources was higher than the within-laboratory standard deviation reported for AASHTO T308. The only exception was the Alabama source using the standard method. The Ontario method and Tempyrox oven generally reduced the variability of asphalt content measurements for high-loss aggregates. None of the methods evaluated statistically reduced aggregate breakdown on the nominal maximum aggregate size and 4.75-mm sieves. The Ontario method significantly reduced, but did not eliminate, aggregate breakdown on the 0.075-mm sieve. The Ontario method is the best method for immediate implementation for determining the asphalt content by the ignition method for high-loss aggregates.

Evaluation of Infrared Ignition Furnace for Determination of Asphalt Content

2003 ◽  
Vol 1861 (1) ◽  
pp. 44-50 ◽  
Author(s):  
Graham C. Hurley ◽  
Brian D. Prowell
Keyword(s):  
Aggregate Size ◽  
Maximum Aggregate Size ◽  
Correction Factors ◽  
Ignition Furnace ◽  
Aggregate Breakdown ◽  
Significant Difference ◽  
Asphalt Content ◽  
Aggregate Loss ◽  
Separate Calibration

The Troxler Model 4730 infrared ignition furnace was compared with a standard Thermolyne ignition furnace. Comparisons conducted with a single unit of each furnace type were based on the correction factor for aggregate loss during ignition, accuracy, and the variability of the measured asphalt content and aggregate degradation during ignition. Forty-eight samples representing two nominal maximum aggregate sizes (9.5 and 19.0 mm), four aggregate types (granite, crushed gravel, limestone, and dolomite), and two asphalt contents (optimum and optimum plus 0.5% asphalt content) were tested in each furnace. The results indicated that the correction factors for aggregate loss during ignition were significantly different for each type of furnace, thus requiring a separate calibration for each type of furnace. In practical terms, the differences for all but the 9.5-mm nominal maximum aggregate size (NMAS) limestone and both dolomite mixtures were less than 0.1%. The samples with the optimum plus 0.5% asphalt content were tested by using the calibration factors developed for a particular mix–furnace combination. The results were analyzed in terms of accuracy (bias) and variability (standard deviation). Neither the measured biases nor the standard deviations for the two types of furnaces were significantly different. The results obtained with four sieve sizes (NMAS and 4.75, 2.36, and 0.075 mm) were evaluated for aggregate breakdown. A comparison of the aggregate gradations recovered from both furnaces indicated no significant difference in the degree of aggregate degradation. A round-robin investigation should be conducted to confirm that the precision of the infrared furnace is similar to the precision of the standard furnace.

scholarly journals Developing Laboratory Performance Models for Thin Asphalt Overlay Mixtures

2019 ◽  
Vol 27 (1) ◽  
pp. 382-395
Author(s):  
Mousa Zeki ◽  
Shakir Al-Busaltan
Keyword(s):  
Tensile Strength ◽  
Statistical Modeling ◽  
Statistical Models ◽  
Performance Enhancement ◽  
Aggregate Size ◽  
Experimental Program ◽  
Maximum Aggregate Size ◽  
Durability Properties ◽  
Asphalt Overlay ◽  
Asphalt Content

Statistical modeling is utilized effectively to development relation/s between the dependent variables and independent variables. In other words, it describes how one or more random variables are related to one more other variables. Building verified models can help in predicting performance characteristics, and saving time and money. This study aims to present a statistical models which help to understand the significance of the different parameters in characterizing the performance of the Thin Asphalt Overlay (TAO). The experimental program included: design the thin asphalt overlay mixtures using one gradation type (9.5 Nominal Maximum Aggregate Size NMAS), three filler types (conventional mineral filler, Ordinary Portland Cement, and Quick lime), and five percentages of asphalt content to identify the optimum asphalt content. Then, Styrene Butadiene Styrene (SBS) modified polymer binder was introduced for performance enhancement. Performance tests were used to evaluate TAO mixture in term of some main namely, volumetric, mechanical, and durability properties are (bulk density, indirect tensile strength and tensile strength ratio). Statistical Product and Service Solutions (SPSS) software (Version 24) was used as a tool for models building. To find the most accurate statistical models, linear and nonlinear regression was achieved. This study demonstrates that the using statistical modeling is achievable and offer a vital tool to describe the characteristics and performance of the TAO mixture in term volumetric, mechanical and durability properties.

Analysis of Quality Control and Quality Assurance Data for Superpave Mixes

2000 ◽  
Vol 1712 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Frazier Parker ◽  
M. Shabbir Hossain ◽  
Jiansheng Song
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Aggregate Size ◽  
Mix Design ◽  
Maximum Aggregate Size ◽  
Air Voids ◽  
Density Measurements ◽  
Control Quality ◽  
Asphalt Content ◽  
Mat Density

Asphalt content, voids, and mat density quality control–quality assurance data were collected for selected Marshall and Superpave mixes during 1997 and for selected Superpave mixes during 1998 and 1999. Analyses indicate that the accuracies and variabilities of asphalt content measurements for Marshall and Superpave mixes are comparable. However, analyses also indicate that the accuracies and variabilities of voids and mat density measurements are not comparable. Moreover, variabilities for Superpave mixes are much higher, and measurements for Superpave mixes are more off target than those for Marshall mixes. The effects of gyratory compactor use, mix design range for an equivalent single-axle load, and maximum aggregate size were investigated to explain the observed differences. Although few consistent trends were observed, all these factors seem to affect the variabilities and accuracies of air voids and mat densities of Superpave mixes.

Effect of Aging on Resilient Modulus of Hot Mix Asphalt Mixtures

2013 ◽  
Vol 723 ◽  
pp. 291-297 ◽  
Author(s):  
Mohd Khairul Idham ◽  
Hainin Mohd Rosli ◽  
Haryati Yaacob ◽  
M. Naqiuddin M. Warid ◽  
Mohd Ezree Abdullah
Keyword(s):  
Aging Process ◽  
Hot Mix Asphalt ◽  
Resilient Modulus ◽  
Aggregate Size ◽  
Asphalt Mixtures ◽  
Maximum Aggregate Size ◽  
Porous Asphalt ◽  
Asphalt Content ◽  
The Difference ◽  
Air Void

Asphalt hardens as a result of an aging process. This study was undertaken to determine the effect of field aging simulated by laboratory aging method of different hot mix asphalt (HMA) mixture. Three types HMA mixtures were used for this study namely Asphaltic Concrete with 10 mm nominal maximum aggregate size (AC 10), Aspaltic Concrete 28 mm (AC 28) and Porous Asphalt 10 mm (PA 10). The resilient modulus test was carried out as an indicator of the performance at a 25 °C and 40 °C. Generally, all samples show similar trend which aged mixture produced slightly higher resilient modulus compared to unaged mixture while an increase in temperature from 25 °C to 40 °C might reduced the resilient modulus up to 88%. This study also found that the difference increment of resilient modulus after the aging process attributed by asphalt content, air void and gradation of respective mixtures.

Determination of alcohols in mixtures by 19F NMR spectroscopy using hexefluoroacetone reagent

1982 ◽  
Vol 47 (7) ◽  
pp. 1973-1978 ◽  
Author(s):  
Jiří Karhan ◽  
Zbyněk Ksandr ◽  
Jiřina Vlková ◽  
Věra Špatná
Keyword(s):  
Standard Deviation ◽  
Nmr Spectroscopy ◽  
Standard Method ◽  
Internal Standard ◽  
Internal Standard Method ◽  
Concentration Region ◽  
Experimental Conditions ◽  
Curve Method ◽  
Sample Preparation Procedure

The determination of alcohols by 19F NMR spectroscopy making use of their reaction with hexafluoroacetone giving rise to hemiacetals was studied on butanols. The calibration curve method and the internal standard method were used and the results were mutually compared. The effects of some experimental conditions, viz. the sample preparation procedure, concentration, spectrometer setting, and electronic integration, were investigated; the conditions, particularly the concentrations, proved to have a statistically significant effect on the results of determination. For the internal standard method, the standard deviation was 0.061 in the concentration region 0.032-0.74 mol l-1. The method was applied to a determination of alcohols in the distillation residue from an oxo synthesis.

scholarly journals Distance variable improvement of time-series big data stream evaluation

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ari Wibisono ◽  
Petrus Mursanto ◽  
Jihan Adibah ◽  
Wendy D. W. T. Bayu ◽  
May Iffah Rizki ◽  
...  
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Standard Method ◽  
Time Series Data ◽  
Series Data ◽  
Percentage Error ◽  
Traffic Demand ◽  
Incremental Model ◽  
Chernoff Bound ◽  
The Mean

Abstract Real-time information mining of a big dataset consisting of time series data is a very challenging task. For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy of the existing fast incremental model tree with the drift detection (FIMT-DD) algorithm. The standard FIMT-DD algorithm uses the Hoeffding bound as its splitting criterion. We propose the further use of the mean distance and standard deviation, which are used to split a tree more accurately than the standard method. We verify our proposed method using the large Traffic Demand Dataset, which consists of 4,000,000 instances; Tennet’s big wind power plant dataset, which consists of 435,268 instances; and a road weather dataset, which consists of 30,000,000 instances. The results show that our proposed FIMT-DD algorithm improves the accuracy compared to the standard method and Chernoff bound approach. The measured errors demonstrate that our approach results in a lower Mean Absolute Percentage Error (MAPE) in every stage of learning by approximately 2.49% compared with the Chernoff Bound method and 19.65% compared with the standard method.

Using Large Linked Field Data Sets to Investigate Density’s Impact on the Performance of Washington State Department of Transportation Asphalt Pavements

2021 ◽  
pp. 036119812110061
Author(s):  
Ryan Howell ◽  
Stephen Muench ◽  
Milad Zokaei Ashtiani ◽  
James Feracor ◽  
Mark Russell ◽  
...  
Keyword(s):  
Aggregate Size ◽  
Large Data ◽  
State Department ◽  
Washington State ◽  
Maximum Aggregate Size ◽  
Test Case ◽  
Data Sets ◽  
Department Of Transportation ◽  
Clear Trend ◽  
Washington State Department

Large data sets of Washington State Department of Transportation (WSDOT) pavement construction and condition data are linked together and used to investigate an implemented change in in-place density to lower specification limit (LSL) from 91% to 92%. This serves as a test case for using such large in-service data sets to create analysis value for a state DOT. Findings include: (1) WSDOT field density has remained relatively steady at 93% for over 20 years; (2) raising the density LSL to 92% will likely result in more contractor effort to achieve higher densities; (3) no clear trend links density with better pavement condition; (4) raising the density LSL will likely result in fewer problematically low densities; and (5) there is no evidence of differing pavement performance based on asphalt content, gradation, or nominal maximum aggregate size.

scholarly journals Enhancing the Flexural Strength of Concrete using Recycled Iron and Steel Slag Aggregate

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
A. A Raheem
Keyword(s):  
Tensile Strength ◽  
Flexural Strength ◽  
Concrete Beams ◽  
Steel Slag ◽  
Aggregate Size ◽  
Mineralogical Composition ◽  
Maximum Aggregate Size ◽  
Considerable Effort ◽  
Iron And Steel ◽  
Coefficient Of Uniformity

Concrete is strong in compression but weak in tension hence, considerable effort is required to improve concrete’s tensile strength by the use of pre-stressed concrete and addition of admixtures or additives. In this study, the use of recycled iron and steel slag (RISS) aggregate to improve the tensile strength of concrete was considered. The paper assessed the mineralogical composition of RISS and granite aggregates, and gradation. It also determines the effects of RISS aggregate on the flexural strength of concrete beams of 150 × 150 × 600 mm containing 0, 10, 20, 40 and 60% RISS aggregate replacement in mix ratios 1:1½:3, 1:2:4 and 1:3:6 with water cement ratios 0.65,0.60 and 0.55 respectively. Diffractograph of RISS and granite aggregate showed that RISS contains Magnetite, Ilmenite and Quartz, while granite contains Quartz, Annite, Microcline and Albite as the predominant minerals. The coefficient of uniformity and concavity of RISS and granite aggregate for maximum aggregate size of 37.5 mm are 4.35 and 1.33; and 4.64 and 1.76 respectively. Both aggregates contain quartz as the predominant mineral and are well graded. The result of the Flexural strength at 28 days curing is within 0.135 – 0.250 MPa specified byBS8500 – 2:2015. Flexural strength of concrete beams cast with RISS aggregate is relatively higher than concrete cast with granite aggregate. Flexural strength, a measure of tensile strength of concrete is improved as percentage RISS aggregate increased.

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