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15 results on '"Christopher Williams, R."'

1. Effect of Soybean Oil Derived Additives on Improved Performance of Polymer-Modified Asphalt Binder and Mix Containing 50% Fine-Graded RAP

Author

Podolsky, Joseph, Hohmann, Austin, Chen, Conglin, Sotoodeh-Nia, Zahra, Manke, Nicholas, Saw, Barrie, Hernandez, Nacu, Ledtje, Paul, Forrester, Michael, Christopher Williams, R., Cochran, Eric, Huisman, Theodore, Di Benedetto, Hervé, editor, Baaj, Hassan, editor, Chailleux, Emmanuel, editor, Tebaldi, Gabriele, editor, Sauzéat, Cédric, editor, and Mangiafico, Salvatore, editor

Published
2022
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2. Effect of Soybean Oil Derived Additives on Improved Performance of Polymer-Modified Asphalt Binder and Mix Containing 50% Fine-Graded RAP

Author

Podolsky, Joseph, primary, Hohmann, Austin, additional, Chen, Conglin, additional, Sotoodeh-Nia, Zahra, additional, Manke, Nicholas, additional, Saw, Barrie, additional, Hernandez, Nacu, additional, Ledtje, Paul, additional, Forrester, Michael, additional, Christopher Williams, R., additional, Cochran, Eric, additional, and Huisman, Theodore, additional

Published
2021
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10. Modeling rutting susceptibility of asphalt pavement using principal component pseudo inputs in regression and neural networks

Author

Ghasemi, Parnian, Aslani, Mohamad, Rollins, Derrick K., Christopher Williams, R., and Schaefer, Vernon R.

Abstract

Permanent deformation is a major load-associated distress occurring in flexible pavement systems and increases with load repetitions affecting road roughness, serviceability, and the international roughness index (IRI). Early detection of rutting is necessary for maintenance and rehabilitation activities, but due to the complex behavior of asphalt mixtures, accurately predicting the permanent deformation of asphalt pavement is difficult. Historically, multivariate regression modeling and recently, artificial neural networks (ANNs) are used widely for material properties prediction. The ability to model accurately the response variable is adversely affected when inputs have pairwise correlations. To overcome this barrier, principal component analysis (PCA), as a dimensionality reduction technique, can be used to produce uncorrelated linear combinations of the original inputs as illustrated in this work using 83 (i.e., samples) laboratory compacted specimens from the State of Wisconsin. Asphalt binder, aggregate, and mix properties are obtained and used as the model inputs. The response parameter is the accumulated strain at the corresponding flow number. Using the developed pseudo inputs from PCA, a multivariate regression and an ANN model are generated and were able to fit the test cases with rfitof 0.8 and 0.97 respectively. The developed machine learning-based framework is shown to be a capable tool in estimating the rutting behavior of asphalt mixture.

Published
2024
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13. Improving Asphalt Mixture Performance by Partially Replacing Bitumen with Waste Motor Oil and Elastomer Modifiers.

Author

Fernandes, Sara, Peralta, Joana, Oliveira, Joel R. M., Christopher Williams, R., and Silva, Hugo M. R. D.

Subjects
ASPHALT, BITUMEN, LUBRICATING oils
Abstract

The environmental concern about waste generation and the gradual decrease of oil reserves has led the way to finding new waste materials that may partially replace the bitumens used in the road paving industry. Used motor oil from vehicles is a waste product that could answer that demand, but it can also drastically reduce the viscosity, increasing the asphalt mixture's rutting potential. Therefore, polymer modification should be used in order to avoid compromising the required performance of asphalt mixtures when higher amounts of waste motor oil are used. Thus, this study was aimed at assessing the performance of an asphalt binder/mixture obtained by replacing part of a paving grade bitumen (35/50) with 10% waste motor oil and 5% styrene-butadiene-styrene (SBS) as an elastomer modifier. A comparison was also made with the results of a previous study using a blend of bio-oil from fast pyrolysis and ground tire rubber modifier as a partial substitute for usual PG64-22 bitumen. The asphalt binders were tested by means of Fourier infrared spectra and dynamic shear rheology, namely by assessing their continuous high-performance grade. Later, the water sensitivity, fatigue cracking resistance, dynamic modulus and rut resistance performance of the resulting asphalt mixtures was evaluated. It was concluded that the new binder studied in this work improves the asphalt mixture's performance, making it an excellent solution for paving works. [ABSTRACT FROM AUTHOR]

Published
2017
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15. Development of an Innovative Bio-Binder Using Asphalt-Rubber Technology.

Author

Peralta, Joana, Silva, Hugo M. R. D., Christopher Williams, R., Rover, Marjorie, and Machado, Ana V.A.

Subjects
*FLEXIBLE pavements, *ASPHALT-rubber, *BINDING agents, *BITUMEN, *PETROLEUM & the environment
Abstract

This research work evaluates several parameters that can affect Asphalt Rubber (AR) binder performance and applies the AR technology to the development of an innovative renewable bio-binder that can fully and cost-effectively replace asphaltic bitumen derived from petroleum in flexible pavement construction. The "Binder Accelerated Separator" method was used to divide the constituents of the Asphalt Rubber and bio-binder (residual binder and swelled rubber). The physical and chemical changes in the Asphalt Rubber and bio-binder and in the residual binders (residual bitumen and residual bio-oil) were evaluated. The results demonstrate that the produced bio-binder is suitable for use in flexible pavements with properties comparable to those of conventional and Asphalt Rubber binders [ABSTRACT FROM AUTHOR]

Published
2013
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