TY  - JOUR
AU  - Botella, Ramon
AU  - Lo Presti, Davide
AU  - Vasconcelos, Kamilla
AU  - Bernatowicz, Kinga
AU  - Martínez, Adriana
AU  - Miró, Rodrigo
AU  - Specht, Luciano
AU  - Arámbula Mercado, Edith
AU  - Menegusso Pires, Gustavo
AU  - Pasquini, Emiliano
AU  - Ogbo, Chibuike
AU  - Preti, Francesco
AU  - Pasetto, Marco
AU  - Jiménez del Barco Carrión, Ana
AU  - Roberto, Antonio
AU  - Orešković, Marko
AU  - Kuna, Kranthi
AU  - Guduru, Gurunath
AU  - Epps Martin, Amy
AU  - Carter, Alan
AU  - Giancontieri, Gaspare
AU  - Abed, Ahmed
AU  - Dave, Eshan
AU  - Tebaldi, Gabriele
PY  - 2022
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2659
AB  - This paper describes the development of novel/state-of-art computational framework to accurately predict the degree of binder activity of a reclaimed asphalt pavement sample as a percentage of the indirect tensile strength (ITS) using a reduced number of input variables that are relatively easy to obtain, namely compaction temperature, air voids and ITS. Different machine learning (ML) techniques were applied to obtain the most accurate data representation model. Specifically, three ML techniques were applied: 6th-degree multivariate polynomial regression with regularization, artificial neural network and random forest regression. The three techniques produced models with very similar precision, reporting a mean absolute error ranging from 12.2 to 12.8% of maximum ITS on the test data set. The work presented in this paper is an evolution in terms of data analysis of the results obtained within the interlaboratory tests conducted by Task Group 5 of the RILEM Technical Committee 264 on Reclaimed Asphalt Pavement. Hence, despite it has strong bonds with this framework, this work was developed independently and can be considered as a natural follow-up.
PB  - Springer
T2  - Materials and Structures
T1  - Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement
SP  - 112
VL  - 55
DO  - https://doi.org/10.1617/s11527-022-01933-9
ER  - 

@article{
author = "Botella, Ramon and Lo Presti, Davide and Vasconcelos, Kamilla and Bernatowicz, Kinga and Martínez, Adriana and Miró, Rodrigo and Specht, Luciano and Arámbula Mercado, Edith and Menegusso Pires, Gustavo and Pasquini, Emiliano and Ogbo, Chibuike and Preti, Francesco and Pasetto, Marco and Jiménez del Barco Carrión, Ana and Roberto, Antonio and Orešković, Marko and Kuna, Kranthi and Guduru, Gurunath and Epps Martin, Amy and Carter, Alan and Giancontieri, Gaspare and Abed, Ahmed and Dave, Eshan and Tebaldi, Gabriele",
year = "2022",
abstract = "This paper describes the development of novel/state-of-art computational framework to accurately predict the degree of binder activity of a reclaimed asphalt pavement sample as a percentage of the indirect tensile strength (ITS) using a reduced number of input variables that are relatively easy to obtain, namely compaction temperature, air voids and ITS. Different machine learning (ML) techniques were applied to obtain the most accurate data representation model. Specifically, three ML techniques were applied: 6th-degree multivariate polynomial regression with regularization, artificial neural network and random forest regression. The three techniques produced models with very similar precision, reporting a mean absolute error ranging from 12.2 to 12.8% of maximum ITS on the test data set. The work presented in this paper is an evolution in terms of data analysis of the results obtained within the interlaboratory tests conducted by Task Group 5 of the RILEM Technical Committee 264 on Reclaimed Asphalt Pavement. Hence, despite it has strong bonds with this framework, this work was developed independently and can be considered as a natural follow-up.",
publisher = "Springer",
journal = "Materials and Structures",
title = "Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement",
pages = "112",
volume = "55",
doi = "https://doi.org/10.1617/s11527-022-01933-9"
}

Botella, R., Lo Presti, D., Vasconcelos, K., Bernatowicz, K., Martínez, A., Miró, R., Specht, L., Arámbula Mercado, E., Menegusso Pires, G., Pasquini, E., Ogbo, C., Preti, F., Pasetto, M., Jiménez del Barco Carrión, A., Roberto, A., Orešković, M., Kuna, K., Guduru, G., Epps Martin, A., Carter, A., Giancontieri, G., Abed, A., Dave, E.,& Tebaldi, G.. (2022). Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement. in Materials and Structures
Springer., 55, 112.
https://doi.org/https://doi.org/10.1617/s11527-022-01933-9

Botella R, Lo Presti D, Vasconcelos K, Bernatowicz K, Martínez A, Miró R, Specht L, Arámbula Mercado E, Menegusso Pires G, Pasquini E, Ogbo C, Preti F, Pasetto M, Jiménez del Barco Carrión A, Roberto A, Orešković M, Kuna K, Guduru G, Epps Martin A, Carter A, Giancontieri G, Abed A, Dave E, Tebaldi G. Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement. in Materials and Structures. 2022;55:112.
doi:https://doi.org/10.1617/s11527-022-01933-9 .

Botella, Ramon, Lo Presti, Davide, Vasconcelos, Kamilla, Bernatowicz, Kinga, Martínez, Adriana, Miró, Rodrigo, Specht, Luciano, Arámbula Mercado, Edith, Menegusso Pires, Gustavo, Pasquini, Emiliano, Ogbo, Chibuike, Preti, Francesco, Pasetto, Marco, Jiménez del Barco Carrión, Ana, Roberto, Antonio, Orešković, Marko, Kuna, Kranthi, Guduru, Gurunath, Epps Martin, Amy, Carter, Alan, Giancontieri, Gaspare, Abed, Ahmed, Dave, Eshan, Tebaldi, Gabriele, "Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement" in Materials and Structures, 55 (2022):112,
https://doi.org/https://doi.org/10.1617/s11527-022-01933-9 . .

TY  - JOUR
AU  - Orešković, Marko
AU  - Menegusso Pires, Gustavo
AU  - Bressi, Sara
AU  - Vasconcelos, Kamilla
AU  - Lo Presti, Davide
PY  - 2020
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1770
AB  - The lack of understanding the mechanisms governing the interaction between reclaimed asphalt binder (RAb)1 and recycling agents is one of the technical issues that still need to be resolved when high amount of reclaimed asphalt (RA)2 is used in a new recycled asphalt mixture (RAM). Due to important role of RAb in that interaction and increased used of RA, it becomes necessary to have a way to classify RA, as any other material used in asphalt mixture production. It is very important to determine how much RAb is active by itself (DoA)3, but also to determine how much RAb can be considered available for a mix design of RAM (DoAv)4 when a recycling agent is used. Finally, since that RAM’s properties are strongly dependent on the degree of blending between RAb and recycling agent (DoB)5, it should evaluate to what extent RAb contributes to the final properties of RAM. These blending parameters (DoA, DoAv and DoB) are so crucial that identifying suitable methodologies for their assessment would be extremely important in performing a proper mix design due to dangerous of having a lack of active bitumen in RAM. This paper presents a literature review of methods which have been used for the evaluation and assessment of mentioned parameters, grouped in four macro-areas: mechanical, chemical, visualization and mechanistic approaches. Furthermore, summarized review of used methods was prepared together with their critical review, all with aim to find appropriate methods for determining these parameters.
PB  - Elsevier
T2  - Construction and Building Materials
T1  - Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review
VL  - 234
DO  - 10.1016/j.conbuildmat.2019.117323
ER  - 

@article{
author = "Orešković, Marko and Menegusso Pires, Gustavo and Bressi, Sara and Vasconcelos, Kamilla and Lo Presti, Davide",
year = "2020",
abstract = "The lack of understanding the mechanisms governing the interaction between reclaimed asphalt binder (RAb)1 and recycling agents is one of the technical issues that still need to be resolved when high amount of reclaimed asphalt (RA)2 is used in a new recycled asphalt mixture (RAM). Due to important role of RAb in that interaction and increased used of RA, it becomes necessary to have a way to classify RA, as any other material used in asphalt mixture production. It is very important to determine how much RAb is active by itself (DoA)3, but also to determine how much RAb can be considered available for a mix design of RAM (DoAv)4 when a recycling agent is used. Finally, since that RAM’s properties are strongly dependent on the degree of blending between RAb and recycling agent (DoB)5, it should evaluate to what extent RAb contributes to the final properties of RAM. These blending parameters (DoA, DoAv and DoB) are so crucial that identifying suitable methodologies for their assessment would be extremely important in performing a proper mix design due to dangerous of having a lack of active bitumen in RAM. This paper presents a literature review of methods which have been used for the evaluation and assessment of mentioned parameters, grouped in four macro-areas: mechanical, chemical, visualization and mechanistic approaches. Furthermore, summarized review of used methods was prepared together with their critical review, all with aim to find appropriate methods for determining these parameters.",
publisher = "Elsevier",
journal = "Construction and Building Materials",
title = "Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review",
volume = "234",
doi = "10.1016/j.conbuildmat.2019.117323"
}

Orešković, M., Menegusso Pires, G., Bressi, S., Vasconcelos, K.,& Lo Presti, D.. (2020). Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review. in Construction and Building Materials
Elsevier., 234.
https://doi.org/10.1016/j.conbuildmat.2019.117323

Orešković M, Menegusso Pires G, Bressi S, Vasconcelos K, Lo Presti D. Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review. in Construction and Building Materials. 2020;234.
doi:10.1016/j.conbuildmat.2019.117323 .

Orešković, Marko, Menegusso Pires, Gustavo, Bressi, Sara, Vasconcelos, Kamilla, Lo Presti, Davide, "Quantitative assessment of the parameters linked to the blending between reclaimed asphalt binder and recycling agent: A literature review" in Construction and Building Materials, 234 (2020),
https://doi.org/10.1016/j.conbuildmat.2019.117323 . .

TY  - JOUR
AU  - Lo Presti, Davide
AU  - Vasconcelos, Kamilla
AU  - Orešković, Marko
AU  - Menegusso Pires, Gustavo
AU  - Bressi, Sara
PY  - 2019
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1752
AB  - It is common practice to assume full blending of the aged binder of reclaimed asphalt (RA) within the design of new asphalt mixtures. Although being practical, this assumption has often led designers to asphalt mixtures lacking binder. Hence, going towards recycled asphalt mixtures (RAM) there is a need to have a better understanding of the blending phenomena, to have a general agreement on terminology and finally adapting RA classification and mix design procedures accordingly. This manuscript aims at being both a reference and stimulus for the scientific community to work in this direction and on this basis provides a nomenclature and a theoretical framework of the blending phenomena. The study is built upon a literature review on definitions, methods and influencing factors related with the blending phenomena and as a result, an intrinsic property of RA, the Degree of binder Activity (DoA), is introduced for the sake of improving RA classification. Furthermore, the two well-known concepts of the Degree of Blending (DoB) and the Degree of binder Availability (DoAv) are redefined, within the proposed framework, together with practical suggestions to introduce them in mix design procedures.
PB  - Taylor&Francis
T2  - Road Materials and Pavement Design
T1  - On the degree of binder activity of reclaimed asphalt and degree of blending with recycling agents
DO  - 10.1080/14680629.2019.1607537
ER  - 

@article{
author = "Lo Presti, Davide and Vasconcelos, Kamilla and Orešković, Marko and Menegusso Pires, Gustavo and Bressi, Sara",
year = "2019",
abstract = "It is common practice to assume full blending of the aged binder of reclaimed asphalt (RA) within the design of new asphalt mixtures. Although being practical, this assumption has often led designers to asphalt mixtures lacking binder. Hence, going towards recycled asphalt mixtures (RAM) there is a need to have a better understanding of the blending phenomena, to have a general agreement on terminology and finally adapting RA classification and mix design procedures accordingly. This manuscript aims at being both a reference and stimulus for the scientific community to work in this direction and on this basis provides a nomenclature and a theoretical framework of the blending phenomena. The study is built upon a literature review on definitions, methods and influencing factors related with the blending phenomena and as a result, an intrinsic property of RA, the Degree of binder Activity (DoA), is introduced for the sake of improving RA classification. Furthermore, the two well-known concepts of the Degree of Blending (DoB) and the Degree of binder Availability (DoAv) are redefined, within the proposed framework, together with practical suggestions to introduce them in mix design procedures.",
publisher = "Taylor&Francis",
journal = "Road Materials and Pavement Design",
title = "On the degree of binder activity of reclaimed asphalt and degree of blending with recycling agents",
doi = "10.1080/14680629.2019.1607537"
}

Lo Presti, D., Vasconcelos, K., Orešković, M., Menegusso Pires, G.,& Bressi, S.. (2019). On the degree of binder activity of reclaimed asphalt and degree of blending with recycling agents. in Road Materials and Pavement Design
Taylor&Francis..
https://doi.org/10.1080/14680629.2019.1607537

Lo Presti D, Vasconcelos K, Orešković M, Menegusso Pires G, Bressi S. On the degree of binder activity of reclaimed asphalt and degree of blending with recycling agents. in Road Materials and Pavement Design. 2019;.
doi:10.1080/14680629.2019.1607537 .

Lo Presti, Davide, Vasconcelos, Kamilla, Orešković, Marko, Menegusso Pires, Gustavo, Bressi, Sara, "On the degree of binder activity of reclaimed asphalt and degree of blending with recycling agents" in Road Materials and Pavement Design (2019),
https://doi.org/10.1080/14680629.2019.1607537 . .