Evaluation of workability and mechanical properties of asphalt binder and mixture modified with waste toner

Huang, Jiandong; Kumar, G. Shiva; Sun, Yuantian

doi:10.1016/j.conbuildmat.2020.122230

Cited by 70 publications

(17 citation statements)

References 23 publications

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“…Another reason for the lack of serious attention to RP is the low production price compared to active power [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. However, according to economics and market calculations, RP is not less valuable than active power [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. The management and control of RP both in traditional and competitive systems have been one of the main concerns of exploiters [ 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 ].…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources

Syah

Mianaei

Elveny

et al. 2021

Sensors

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The power system planning problem considering system loss function, voltage profile function, the cost function of FACTS (flexible alternating current transmission system) devices, and stability function are investigated in this paper. With the growth of electronic technologies, FACTS devices have improved stability and more reliable planning in reactive power (RP) planning. In addition, in modern power systems, renewable resources have an inevitable effect on power system planning. Therefore, wind resources make a complicated problem of planning due to conflicting functions and non-linear constraints. This confliction is the stochastic nature of the cost, loss, and voltage functions that cannot be summarized in function. A multi-objective hybrid algorithm is proposed to solve this problem by considering the linear and non-linear constraints that combine particle swarm optimization (PSO) and the virus colony search (VCS). VCS is a new optimization method based on viruses’ search function to destroy host cells and cause the penetration of the best virus into a cell for reproduction. In the proposed model, the PSO is used to enhance local and global search. In addition, the non-dominated sort of the Pareto criterion is used to sort the data. The optimization results on different scenarios reveal that the combined method of the proposed hybrid algorithm can improve the parameters such as convergence time, index of voltage stability, and absolute magnitude of voltage deviation, and this method can reduce the total transmission line losses. In addition, the presence of wind resources has a positive effect on the mentioned issue.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources

Syah

Mianaei

Elveny

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Other studies focused on the sustainable modification of asphalt binders to mainly improve the stiffness and the self-healing properties of asphalt mixtures using, for example, waste cooking oil [ 16 , 17 ], waste toner [ 18 ], or waste tire rubber [ 19 ]. Some researchers, like Wang et al [ 20 ], added 0.4% recycled basalt fibers with a length of 6 mm to a hot asphalt mixture; they tested the stiffness modulus of the mentioned fiber-modified mixture and a traditional hot asphalt mixture after 15 freeze–thaw cycles.…”

Section: Introductionmentioning

confidence: 99%

Life Cycle Assessment of Sustainable Asphalt Pavement Solutions Involving Recycled Aggregates and Polymers

et al. 2021

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The pursuit of sustainability in the field of road asphalt pavements calls for effective decision-making strategies, referring to both the technical and environmental sustainability of the solutions. This study aims to compare the life cycle impacts of several pavement solution alternatives involving, in the binder and base layers, some eco-designed, hot- and cold-produced asphalt mixtures made up of recycled aggregates in substitution for natural filler and commercial recycled polymer pellets for dry mixture modification. The first step focused on the technical and environmental compatibility assessment of the construction and demolition waste (CDW), jet grouting waste (JGW), fly ash (FA), and reclaimed asphalt pavement (RAP). Then, three non-traditional mixtures were designed for the binder layer and three for the base layer and characterized in terms of the stiffness modulus. Asphalt pavement design allowed for the definition of the functional units of Life Cycle Assessment (LCA), which was applied to all of the pavement configurations under analysis in a “from cradle to grave” approach. The LCA results showed that the best performance was reached for the solutions involving a cold, in-place recycled mixture made up of RAP and JGW in the base layer, which lowered all the impact category indicators by 31% on average compared to those of the traditional pavement solution. Further considerations highlighted that the combination of a cold base layer with a hot asphalt mixture made up of CDW or FA in the binder layer also maximized the service life of the pavement solution, providing the best synergistic effect.

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“…e recent research showed that the mechanical properties (such as strength and stiffness) of engineering materials can be accurately predicted by using artificial intelligence technology, reducing the cost of expensive and cumbersome laboratory tests [16][17][18]. Moreover, the prediction of engineering materials by artificial intelligence can replace the traditional mathematical model and improve the calculation rate and accuracy [19][20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Compressive Strength of Cemented Tailing Backfill through the Use of Firefly Algorithm and Random Forest Model

Wang

Jia

Huang

2021

Shock and Vibration

Self Cite

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Cemented tailings backfill is widely used in worldwide mining areas, and its development trend is increasing due to the technical and economic benefits. However, there is no reliable and simple machine learning model for the prediction of the compressive strength. In the present study, the research process to use artificial intelligence algorithms to predict the compressive strength of cemented tailing backfill was conducted, overcoming the shortcomings of traditional empirical formulas. Experimental tests to measure the compressive strength of cemented tailing backfill were conducted to construct the dataset for the machine learning. Five input parameters (tailing to cement ratio, percentage of fine tailings, cement type, curing time, and solid to water ratio) were considered for the design of the laboratory tests. The firefly algorithm (FA) was used to tune the random forest (RF) hyperparameters, and it was adopted to combine the RF model to improve the accuracy and efficiency for the prediction of the compressive strength of the cemented tailing backfill. By comparing the predicted and actual results, the reliability and accuracy of the prediction model proposed are confirmed. Tailing to cement ratio and curing time are the two most important parameters to the compressive strength of the cemented tailing backfill.

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Evaluation of workability and mechanical properties of asphalt binder and mixture modified with waste toner

Cited by 70 publications

References 23 publications

RETRACTED: A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources

RETRACTED: A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources

Life Cycle Assessment of Sustainable Asphalt Pavement Solutions Involving Recycled Aggregates and Polymers

Simulation of the Compressive Strength of Cemented Tailing Backfill through the Use of Firefly Algorithm and Random Forest Model

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