Using various thermal analytical methods for bitumen characterization

Fiedlerová, Marcela; Jíša, Petr; Kadlec, David; Velvarská, Romana; Štěpánek, K.

doi:10.1007/s42947-020-0157-2

Cited by 5 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Constants 1 С and 4 С are found from the system of equations ( 9), (10) transformed taking into account equalities (12)…”

Section: Statement Of the Problemmentioning

confidence: 99%

“…Very complex processes of thermal deformation and thermal destruction are observed in the structures of asphalt concrete pavements of roads and bridges [3,9,13,16,17,19,20]. The issues of determining the reduced thermomechanical characteristics of asphalt concrete materials reinforced with particles, fibers and rods are considered in publications [5,7,12,14]. Here, however, these tasks become more complicated, since it is possible to create materials with directional (anisotropic) properties.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modelling negative thermomechanical effects in reinforced road structures with thermoelastic incompatibility of coating and reinforcement materials

Gulyayev

Mozgovyy²,

Shlyun³

et al. 2022

SRIT

View full text Add to dashboard Cite

The phenomena of the formation of local defects and cracks in asphalt concrete pavements of roads and bridges are most often observed in climatic zones with large temperature differences during their seasonal and daily changes. To a large extent, this is due to the heterogeneity of the thermomechanical properties of the materials of the coating layers and the base. To prevent these phenomena, reinforcing rods and meshes are introduced into the coating structure. In this work, using the theory of thermoelasticity, it is shown by the method of mathematical modelling that in cases of incompatibility of the thermomechanical characteristics of asphalt concrete materials and reinforcement, additional localized thermal stresses arise in its small vicinity, which, even at moderate temperatures, can reach critical values and lead to local defects and cracks. Since these defects are latent, they cannot always be detected in practice. The presented results of analytic calculation validated these conclusions. They can be used in both road building and composite design.

show abstract

“…Constants 1 С and 4 С are found from the system of equations ( 9), (10) transformed taking into account equalities (12)…”

Section: Statement Of the Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling negative thermomechanical effects in reinforced road structures with thermoelastic incompatibility of coating and reinforcement materials

Gulyayev

Mozgovyy²,

Shlyun³

et al. 2022

SRIT

View full text Add to dashboard Cite

show abstract

“…Murugan et al 17 observed two stages in the thermal analysis of Athabasca bitumen, with the second stage having double the activation energy as compared to the first stage but a much lower reaction order. More recently, Fiedlerováet al 18 conducted modulated differential scanning calorimetry and thermochemical analysis in addition to TGA to characterize bitumen binders, but suggested that the laboratory techniques were time-consuming and not cost-effective. Most importantly, sample preparation takes a lot of time and characterization instruments are a major source of human error.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Thermogravimetric Data for Asphaltenes Extracted from Deasphalted Oil Using Machine Learning Techniques

Sivaramakrishnan,

Tannous,

Chandrasekaran

2023

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Thermogravimetric analysis (TGA) has been extensively used in the bitumen literature to investigate its thermal stability and various stages of thermal decomposition. The primary aim of these studies has been to calculate the kinetic parameters, such as activation energy and the pre-exponential factor of each thermal event. However, in our current paper, we explore the application of three machine learning (ML) techniques, namely, support vector regression (SVR), random forest (RF), and gradient booster regression (GBR), to predict the TGA data for the asphaltenes extracted from the feed and products of visbreaking of three types of materials: (i) deasphalted oil (DAO), (ii) DAO doped with 5.55 wt % indene, and (iii) DAO doped with 11.11 wt % indene. The addition of indene was shown to significantly affect the free-radical chemistry of DAO in a previous work, and the key contribution of our work in this paper was to minimize the requirement of the TGA instrument to obtain the mass loss curves by employing ML techniques on available experimental data. This will reduce the human errors involved in sample preparation and data collection as well as decrease the process time in obtaining the TGA data as compared to experimentation. We observed that the regression techniques based on decision trees, i.e., RF and GBR, showed the best performance and highest prediction accuracy of >0.99 for predicting the TGA data of the asphaltenes extracted from the feed and products obtained by reacting the feedstocks at visbreaking reaction times of 30, 45, and 60 min. A number of inputs were considered for the ML models, such as the temperature of the TGA chamber and sample, heat supplied to the sample, visbreaking time, and time spent inside the TGA chamber. The novelty of our work lies in the fact that no previous study has reproduced the TGA data for asphaltenes extracted from DAO and indene-added DAO and their visbroken products through ML approaches, and we believe that the results of this work will help in fastening the process times in the heavy oil industry by eliminating the need for offline measuring instruments.

show abstract

“…The analysis of the evolved gases by FTIR reveals the evolution of small molecules such as CO2 and water that are not generally acquired when using a mass spectrometer as a detector of pyrolysis products. However, despite all the positive aspects of both thermal analysis and analytical pyrolysis, such techniques are rarely reported in the study of bitumen and archaeological bitumen [30,31].…”

Section: Introductionmentioning

confidence: 99%

Analytical pyrolysis and thermal analysis to chemically characterise bitumen from Italian geological deposits and Neolithic stone tools

Nardella

Duce

Ribechini

2021

Journal of Analytical and Applied Pyrolysis

View full text Add to dashboard Cite

Using various thermal analytical methods for bitumen characterization

Cited by 5 publications

References 13 publications

Modelling negative thermomechanical effects in reinforced road structures with thermoelastic incompatibility of coating and reinforcement materials

Modelling negative thermomechanical effects in reinforced road structures with thermoelastic incompatibility of coating and reinforcement materials

Prediction of Thermogravimetric Data for Asphaltenes Extracted from Deasphalted Oil Using Machine Learning Techniques

Analytical pyrolysis and thermal analysis to chemically characterise bitumen from Italian geological deposits and Neolithic stone tools

Contact Info

Product

Resources

About