Thermal and mechanical properties of demolition wastes in geothermal pavements by experimental and machine learning techniques

Ghorbani, Behnam; Arulrajah, Arul; Narsilio, Guillermo A.; Horpibulsuk, Suksun; Bo, Myint Win

doi:10.1016/j.conbuildmat.2021.122499

Cited by 25 publications

(12 citation statements)

References 43 publications

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“…The test results indicated that RCA exhibit a Group A response at all temperatures. Alnedawi and Rahman 89 showed that RCA shakedown ranges varied from Group A to Group B. Similarly, Saberian and Li 90 reported that the examined RCAs were in Group B, meaning that they showed plastic creep.…”

Section: Experimental Studymentioning

confidence: 94%

The effect of RCA pavements on the liquefaction-induced settlement

Akbaş¹,

Subasi²,

İyisan³

2023

Sci Rep

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The use of recycled concrete aggregates (RCA) not only reduces the demand for natural aggregates (NA) but also might improve the behavior of soil under earthquake loading. In this study, the behavior of the pavement constructed using 100% RCA and NA on a sandy soil layer with high liquefaction potential under dynamic loads was investigated by numerical analysis and compared with free field conditions. For this purpose, first, the classical geotechnical properties of 100% RCA and NA materials were obtained, and then the stiffness properties were determined by resilient modulus and permanent deformation tests. In the second stage, three different models were created with pavement with NA and RCA and without pavement on high liquefaction potential sand, and dynamic analyses were carried out by PM4Sand. Numerical analyses show that constructing a subbase and base layers significantly reduces liquefaction-induced settlement on the surface of flexible pavements built on liquefied soils. Moreover, when the case of using RCA instead of NA in the subbase and base layers built on the liquefied soil is examined, the liquefaction-induced settlement values on the surface are obtained either lower or very close. Consequently, this study proposes a new alternative to the use of RCA waste materials instead of NA. It is expected the use of these waste materials will reduce the need for storage space and also reduce the negative environmental effects associated with storage.

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Section: Experimental Studymentioning

confidence: 94%

The effect of RCA pavements on the liquefaction-induced settlement

Akbaş¹,

Subasi²,

İyisan³

2023

Sci Rep

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“…Various researchers selected different test temperatures and test stress levels. Ghorbani et al [ 7 , 9 ] assessed the temperature effects of mixtures at 5, 20, 35, and 50 °C. Cheng et al [ 24 ] analyzed the viscoelastic properties of different mixtures from 10 to 50 °C at 10 °C increments.…”

Section: Uniaxial Compression Static Creep Testmentioning

confidence: 99%

“…The theoretical and experimental studies on the mechanical behaviors of asphalt mixtures provide a crucial basis for designing pavement layers [ 6 , 7 ]. Creep behavior is amongst the mechanical characteristics of asphalt mixtures [ 8 ], and it is strongly related to the rutting formation of the pavement structure [ 3 , 9 ]. Therefore, it is important to establish a constitutive model that can accurately predict the creep behavior of asphalt mixtures.…”

Section: Introductionmentioning

confidence: 99%

Viscoelastic Damage Characteristics of Asphalt Mixtures Using Fractional Rheology

Zhang

et al. 2021

Materials

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The mechanical behavior of asphalt mixtures at high stress levels are characterized by non-linear viscoelasticity and damage evolution. A nonlinear damage constitutive model considering the existence of creep hardening and creep damage mechanisms in the entire creep process is proposed in this study by adopting the fractional rheology theory to characterize the three-stage creep process of mixtures. A series of uniaxial compressive creep tests under various stresses were conducted at different temperatures to verify the model. The results indicated that the model predictions were in good agreement with the creep tests. The relationship between the model parameters and applied stresses was established, and the stress range in which the mixture exhibited only creep consolidation was obtained. The damage to the asphalt mixture was initiated in the steady stage; however, it developed in the tertiary stage. A two-parameter Weibull distribution function was used to describe the evolution between the damage values and damage strains at different stress levels and temperatures. The correlation coefficients were greater than 0.99 at different temperatures, indicating that a unified damage evolution model could be established. Thus, the parameters of the unified model were related to material properties and temperature, independent of the stress levels applied to the mixtures.

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“…However, the use of expensive software for FEM analysis significantly limits their application (Kim et al 2012). In recent times, the use of machine learning techniques has been widely used in mapping the non-linear relationships between the input and output variables (e.g., Ahmadi et al 2019;Yekani Motlagh et al 2019;Aamir et al 2020;Dorosti et al 2020;Ghorbani et al 2021;Kaloop et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

2022

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Settlement estimation of a footing located over a buried conduit in a sloping terrain is a challenging task for practicing civil/geotechnical engineers. In the recent past, the advent of machine learning technology has made many traditional approaches antiquated. This paper investigates the viability, development, implementation, and comprehensive comparison of five artificial intelligence-based machine learning models, namely, multi-layer perceptron (MLP), Gaussian processes regression (GPR), lazy K-Star (LKS), decision table (DT), and random forest (RF) to estimate the settlement of footing located over a buried conduit within a soil slope. The pertaining dataset of 3600 observations was obtained by conducting large-scale numerical simulations via the finite element modelling framework. After executing the feature selection technique that is correlation-based subset selection, the applied load, total unit weight of soil, constrained modulus of soil, slope angle ratio, hoop stiffness of conduit, bending stiffness of conduit, burial depth of conduit, and crest distance of footing were utilized as the influence parameters for estimating and forecasting the settlement. The predictive strength and accuracy of all models mentioned supra were evaluated using several well-established statistical indices such as Pearson's correlation coefficient (r), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), scatter index (SI), and relative percentage difference (RPD).The results showed that among all the models employed in this study, the multi-layer perceptron model has shown better results with r, RMSE, NSE, SI, and RPD values of (0.977, 0.298, 0.937, 0.31, and 4.31) and (0.974, 0.323, 0.928, 0.44 and 3.75) for training and testing dataset, respectively. The sensitivity analysis revealed that all the selected parameters play an important role in determining the output value. However, the applied load, constrained modulus, unit weight, slope angle ratio, hoop stiffness have the highest strength with the relative importance of 18.4%, 16.3% and 15.3%, 13.8%, 11.4%, respectively. Finally, the model was translated into a functional relationship for easy implementation and can prove useful for practitioners and researchers in predicting the settlement of a footing located over a buried conduit in a sloping terrain.

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Thermal and mechanical properties of demolition wastes in geothermal pavements by experimental and machine learning techniques

Cited by 25 publications

References 43 publications

The effect of RCA pavements on the liquefaction-induced settlement

The effect of RCA pavements on the liquefaction-induced settlement

Viscoelastic Damage Characteristics of Asphalt Mixtures Using Fractional Rheology

Load-settlement response of a footing over buried conduit in a sloping terrain: a numerical experiment-based artificial intelligent approach

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