Mix Asphalt Research Articles

Досвід застосування стабілізуючої добавки АРОН-БВ для щебенево-мастикових асфальтобетонних сумішей

The article covers the issue of development, approval, implementation and further use of a domestic stabilizing additive for the production of stone-mastic asphalt mixes. The prerequisite for the creation of such a project was the development of the latest technologies and road construction materials, both on the world and Ukrainian industry markets, as well as the annual growth in the need for such materials during the implementation of infrastructure projects. Based on the results of the work, it was established that the quality of the domestically produced stabilizing additive corresponds to the level of quality of similar imported goods, and its cost is somewhat lower compared to foreign analogues. The total period of implementation of this project is eight years, taking into account the time for: development and approval of the necessary technical and permit documents; launch of a production technological line; approval and introduction of a stabilizing additive; observation for 6-7 years of implemented objects in the first year of implementation of the material; implementation of new facilities using the developed stabilizing additive. The results of this work can be used during the implementation of future infrastructure projects for the restoration and development of public highways, both in terms of ensuring the availability of domestic materials on the domestic market, and in terms of supporting and developing the domestic economy of Ukraine at the appropriate level. Keywords: wastepaper, stabilizing additive, technical and economic indicator, cellulose fiber, stone-mastic asphalt mixes, stone-mastic asphalt.

Use of Recycled Asphalt and Waste Materials in Production of High-Performance Asphalt Mixtures

The research has been conducted to test the asphalt produced in Latvia using local mineral materials and local recycled modifiers (fiberglass, crumb rubber), as well as the recycled asphalt used in the production of high-modulus asphalt mix, which will meet the local Latvian road construction specifications and will be economically, environmentally and technically more attractive. In the theoretical part, the available sources were studied to establish a theoretical framework, assess possibilities for using recycled materials, define the concept of fiberglass, and consider its performance in asphalt mixes. During the experimental stage of the research, different asphalt mix formulas with glass fiber, crushed rubber, RAP, and other additives used to stabilize asphalt mixtures for surface and base layers were designed in the laboratory; they were compared to the reference mixes using performance tests. Then the mixtures with the best results were used in the test section of a high-intensity local road. The samples of the asphalt layers of the paved test section were tested as well. Two asphalt mixes were designed according to local Latvian road-building specifications, using fiberglass reinforcement 0.15% + 30% RAP for the base layer and crushed rubber 15% and RAP 30%+EVOFLEX CA© variable for the surface layer. The aim of the research is to offer solutions for reducing new asphalt pavement production allowing for the use of recycled asphalt mixes in local road building. The performance tests of the test asphalt mixes showed that recycled asphalt pavement fully meets the requirements of the local Latvian road-building specifications.

Enhancing the thermal conductivity of hot-mix asphalt

Conductive hot-mix asphalt is recommended for enhancing the solar energy collection performance of an asphalt solar collector. This type of collector consists of embedded tubes with circulating water or air inside pavement construction to generate power. This work intends to shed light on the selection of novel components for the preparation of conductive asphalt mixes. Lee's disc method was used to determine the thermal conductivity of this composite material. A comprehensive examination was conducted to prepare reference and conductive asphalt discs by manufacturing asphalt mixtures in a laboratory specified for this work. New Iraqian natural resource materials, including quartzite sandstones and silica sands, and Iraqian industrial waste materials, such as slag stones, steel wool fibres and metallic waste powder, were employed as conductive components. The results showed that the conductive materials increase the thermal conductivity of the reference asphalt mixture up to 42.75% and 66.65% for quartzite and slag combinations, respectively. Slag aggregates should not be utilized as conductive material in asphalt mixes without increasing the binder ratio. Proportions of 4% and 38% of steel wool fibres and metallic waste powder additives, respectively, were found to produce the optimal results for thermal conductivity enhancement. The air void contents and fracturing ratio of conductive discs were decreased when using conductive novel components, which is an indication of the importance of current findings in improving asphalt mixtures in heat storage and transfer applications.

Evaluation of Emissions by Different Analysis Method at Hot Mix Asphalt Plant Combustion Source

The combustion process for the asphalt mixing in hot mix asphalt (HMA) plant can produce harmful flue gases emission into the atmosphere. Combustion activities produce heat for industrial usage whenfuel reacts with oxygen in the air under suitable conditions. High concentrations of undesirable emissions can be formed if the combustion is not properly controlled during the reaction. This paper gives an overview on the method and measurement of these emissions in combustion analysis by focusing on the three types of analysis methods which are laboratory testing analysis, on-site emission analysis, and theoretical analysis. Three types of data were prepared in order to achieve the objective of the study, which are literaturestudy, site visit, and laboratory analysis. The result shows that there areslightly different emission results even though they came from the same source. Clearly, the analysis shows thatthe air-fuel ratio during combustion can havea significant effect on the emission result. The excess air supplied can cause dilution to the emission and leads to a low emission value.

Marshall Stability Prediction with Glass and Carbon Fiber Modified Asphalt Mix Using Machine Learning Techniques.

Pavement design is a long-term structural analysis that is required to distribute traffic loads throughout all road levels. To construct roads for rising traffic volumes while preserving natural resources and materials, a better knowledge of road paving materials is required. The current study focused on the prediction of Marshall stability of asphalt mixes constituted of glass, carbon, and glass-carbon combination fibers to exploit the best potential of the hybrid asphalt mix by applying five machine learning models, i.e., artificial neural networks, Gaussian processes, M5P, random tree, and multiple linear regression model and further determined the optimum model suitable for prediction of the Marshall stability in hybrid asphalt mixes. It was equally important to determine the suitability of each mix for flexible pavements. Five types of asphalt mixes, i.e., glass fiber asphalt mix, carbon fiber asphalt mix, and three modified asphalt mixes of glass-carbon fiber combination in the proportions of 75:25, 50:50, and 25:75 were utilized in the investigation. To measure the efficiency of the applied models, five statistical indices, i.e., coefficient of correlation, mean absolute error, root mean square error, relative absolute error, and root relative squared error were used in machine learning models. The results indicated that the artificial neural network outperformed other models in predicting the Marshall stability of modified asphalt mix with a higher value of the coefficient of correlation (0.8392), R2 (0.7042), a lower mean absolute error value (1.4996), and root mean square error value (1.8315) in the testing stage with small error band and provided the best optimal fit. Results of the feature importance analysis showed that the first five input variables, i.e., carbon fiber diameter, bitumen content, hybrid asphalt mix of glass-carbon fiber at 75:25 percent, carbon fiber content, and hybrid asphalt mix of glass-carbon fiber at 50:50 percent, are highly sensitive parameters which influence the Marshall strength of the modified asphalt mixes to a greater extent.

Prediction models for marshall mix parameters using bio-inspired genetic programming and deep machine learning approaches: A comparative study

This research study utilizes four machine learning techniques, i.e., Multi Expression programming (MEP), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Ensemble Decision Tree Bagging (DT-Bagging) for the development of new and advanced models for prediction of Marshall Stability (MS), and Marshall Flow (MF) of asphalt mixes. A comprehensive and detailed database of 343 data points was established for both MS and MF. The predicting variables were chosen among the four most influential, and easy-to-determine parameters. The models were trained, tested, validated, and the outcomes of the newly developed models were compared with actual outcomes. The root squared error (RSE), Nash-Sutcliffe efficiency (NSE), mean absolute error (MAE), root mean square error (RMSE), relative root mean square error (RRMSE), regression coefficient (R2), and correlation coefficient (R), were all used to evaluate the performance of models. The sensitivity analysis (SA) revealed that in the case of MS, the rising order of input significance was bulk specific gravity of compacted aggregate, Gmb (38.56 %) > Percentage of Aggregates, Ps (19.84 %) > Bulk Specific Gravity of Aggregate, Gsb (19.43 %) > maximum specific gravity paving mix, Gmm (7.62 %), while in case of MF the order followed was: Ps (36.93 %) > Gsb (14.11 %) > Gmb (10.85 %) > Gmm (10.19 %). The outcomes of parametric analysis (PA) consistency of results in relation to previous research findings. The DT-Bagging model outperformed all other models with values of 0.971 and 0.980 (R), 16.88 and 0.24 (MAE), 28.27 and 0.36 (RMSE), 0.069 and 0.041 (RSE), 0.020 and 0.032 (RRMSE), 0.010 and 0.016 (PI), 0.931 and 0.959 (NSE), for MS and MF, respectively. The results of the comparison analysis showed that ANN, ANFIS, MEP, and DT-Bagging are all effective and reliable approaches for the estimation of MS and MF. The MEP-derived mathematical expressions represent the novelty of MEP and are relatively simple and reliable. Roverall values for MS and MF were in the order of DT-Bagging >MEP >ANFIS >ANN with all values exceeding the permitted range of 0.80 for both MS and MF. Hence, all the modeling approaches showed higher performance, possessed high generalization and predication capabilities, and assess the relative significance of input parameters in the prediction of MS and MF. Hence, the findings of this research study would assist in the safer, faster, and sustainable prediction of MS and MF, from the standpoint of resources and time required to perform the Marshall tests.

Study of Anti-Stripping Measures to Improve the Adhesion of Asphalt to Granite Aggregates

Granite is very widely distributed in the world, but granite is an acidic aggregate with poor adhesion to asphalt. In untreated asphalt mixtures, asphalt pavement water damage and loose disease are more prominent, affecting the service life of the pavement and service level. Enhancing the road performance of granite asphalt mixture generally improves the adhesion properties of asphalt and granite. Qingchuan rock asphalt, anti-stripping agent KH5, aliphatic amine anti-stripping agent AJ-1 and two groups of the composite anti-stripping agents were used to modify the asphalt and analyze the effect of different anti-stripping agents on the improvement of asphalt-granite aggregate adhesion properties based on the surface free energy (SFE) theory. Second, the effect of anti-stripping agents on the rheological properties of asphalt were analyzed by rheological tests, and the modification effect of granite asphalt mixture road performance was evaluated by Marshall tests. The aging of asphalt and asphalt mixture was simulated by thermal oxygen aging, and the durability of different anti-stripping agents was investigated by comparing the performance of asphalt and asphalt mixtures before and after aging. The results showed that Qingchuan rock asphalt can effectively enhance the high-temperature stability and anti-aging properties of asphalt mixes, but the low temperature performance was relatively poor. KH5 and AJ-1 can make up for the lack of low temperature performance of rock asphalt, but the water stability of asphalt mixes decreases after aging. All five groups of anti-stripping agents improve the adhesion of granite-asphalt and the water stability of the asphalt mixture to some extent. Considering the aging effect, the order of granite-asphalt mixture water stability is: KH/RAMA > AJ/RAMA > RAMA > KHMA > AJMA.

Effect of aggregate gradation and asphalt mix volumetrics on the thermal properties of asphalt concrete

The objective of this study is to investigate the impact of aggregate gradation and Superpave volumetrics on thermal properties of asphalt mixtures. Thirty asphalt concrete specimens with three different Nominal Maximum Aggregate Sizes (NMAS) of 19.0, 12.5 and 9.5 mm and two levels of gradation coarseness: fine gradation (FG) and coarse gradation (CG) were prepared. The Transient Plane Source (TPS) method was used to determine thermal properties. Based on the analyses performed, it was concluded visually that heat transfer is highly dependent on the contact area which, in turn, is related to air void volume. Unlike NMAS, the gradation coarseness (G) has some effect on thermal conductivity (TC) (p-value = 0.008 < 0.05). On the contrary, the NMAS, unlike gradation coarseness, has a significant effect on thermal diffusivity (TD) with a p-value of 0.025. Both gradation coarseness and NMAS have a significant effect on thermal diffusivity (p-value = 0.029 < 0.05) and do not have much effect on specific heat (SH) where p-value is greater than 0.05. Nevertheless, it was noticed that the thermal diffusivity increased linearly with an increase in aggregate size from 85.64 mm2/s to 125.79 mm2/s at 9.5 NMAS FG and 19 mm NMAS FG, respectively. Whereas the specific heat and thermal conductivity increase as the asphalt content (AC) increases. Consequently, the highest average values of thermal conductivity and specific heat are 2 W/m.K and 0.025 M.J/m3. K, respectively, at the highest asphalt content of 6.1%. Multiple linear regression, non-linear regression and deep learning (MLR, NLR and DL) equations were developed. The non-linear regression resulted relatively in the best predictive power of all equations. Finally, larger datasets are needed to predict thermal properties with higher confidence.

Development of a Laboratory Operations-Friendly Long-Term Loose Mix Aging Protocol for New Asphalt Pavements

New asphalt pavements are often designed to last 15 to 20 years without a major rehabilitation. However, an asphalt mix gets stiffer and more brittle with pavement service life because of aging. As cracking resistance decreases at higher aging levels, pavement structural design and performance verification need to consider the long-term aging characteristics of asphalt mixes. The research presented in this paper developed long-term loose mix aging protocols that are more friendly to routine laboratory operations. Based on a theoretical aging model and the IDEAL cracking test, two aging protocols are equivalent to the 3- and 6-day loose mix aging durations at 95°C provided by NCHRP 9-54, which are 20 h at 110°C and 20 h at 120°C, respectively. These new long-term aging protocols were then confirmed by the Texas Overlay Test and the Illinois Flexibility Index Test. The integration of these protocols into a comprehensive framework for mix design, pavement performance verification, and production testing is discussed. In brief, these new long-term aging protocols would be employed for evaluating cracking resistance only in the pavement performance verification stage, whereas the short-term aging protocol, namely, 2 h at the compaction temperature, would be applied to Superpave volumetric evaluation, balanced mix design (BMD), and production testing. These two new aging protocols combined with BMD rapid performance tests and performance prediction tests make this comprehensive framework very practical and efficient.

Evaluating the engineering properties of asphalt mixtures containing RAP aggregates incorporating different wastes as fillers and their effects on the ageing susceptibility

Ageing of asphalt mixtures occurs by intrinsic variables (properties and quantity of the binder and air voids) and extrinsic variables (environmental factors) during production and service life. This topic has been studied extensively in the existing literature, but the potential of alternate filler on the ageing resistance of asphalt mixes and the influence of the interaction between filler and asphalt binder has not been thoroughly examined. The underlying objective of this study was to evaluate the ageing resistance potential of four waste fillers, Jarosite (JS), Hydrated Lime mud (HL), Fly Ash (FA) and Sugarcane Ash (SA), compared to conventional fillers, Stone Dust (SD) on the recycled mix. The recycled mixes were prepared with 50% Reclaimed Asphalt Pavement (RAP) material, locally available natural aggregate, VG-10 grade asphalt binder and studied fillers. The performance properties, including cracking resistance, moisture susceptibility, resilient modulus, rutting, and fatigue resistance of unaged and long-term aged recycled asphalt mix, were evaluated in this study. The results indicated that the ageing resistance of recycled mixtures was highly affected by filler type. HL possesses the highest ageing resistance potential, followed by JS, FA, SA, and SD. The results demonstrated that JS and HL filler significantly improved moisture, rutting, and crack resistance in unaged and long-term aged recycled mix, which are critical factors in extending the durability of pavement. JS and HL filler showed lower fatigue life of recycled mix while tested at higher strain levels due to their higher stiffness. In contrast, FA and SA fillers resulted in a mixed value of properties of the recycled mix compared to SD filler. SA filler showed the lowest cracking resistance (Indirect tensile strength value 1420 kPa for unaged mix and 1573 kPa for aged mix) and moisture resistance (Tensile strength ratio value 78% for unaged mix and 75% for aged mix) among all fillers. The recycled asphalt mix containing SA was found to be highly susceptible to moisture damage, cracking and ageing. The overall conclusions of this study ascertain that the ageing resistance potential of HL was highest among the studied waste fillers for all the studied properties due to its fineness, higher porosity, presence of calcite and increased asphalt film thickness of the mix. • Ageing resistance potential of hydrated lime mud was highest among the studied fillers due to its fineness and the presence of calcite. • Jarosite and hydrated lime mud filler significantly improved moisture, rutting, and crack resistance. • Hydrated lime mud possesses the highest ageing resistance potential among waste fillers, followed by jarosite, fly ash, and sugarcane ash. • Sugarcane ash filler showed the lowest cracking resistance and moisture resistance.

ПІДВИЩЕННЯ ЯКОСТІ РЕГЕНЕРОВАНОГО АСФАЛЬТОБЕТОНУ

. Asphalt concrete regeneration is a technology for processing old asphalt-concrete milled material, restoration involving and characteristics improvement for reuse during coating installation, as well as for other road works. Old asphalt concrete processing is a resource-saving technology that can significantly reduce, material consumption of road repairs and work related with road surfaces installations. The regenerated asphalt mix, in addition to arranging layers of pavement, can also be used to create road base upper layers. Depending on the method of regeneration and volume of old material used in the regenerated mixture preparation, it is possible to reduce the cost of restoring pavement by 30% compared to traditional technology, when work using a new asphalt mix, is performed. The main methods of asphalt concrete regeneration in [1 - 5]. Old asphalt concrete material regeneration can be carried out in two main ways: - at an asphalt concrete plant, when old asphalt material processing previously removed (by cold or hot milling) is carried out in stationary or mobile mixing plants; - at the working place, when the regeneration of the old asphalt material is carried out directly in the process of laying the coating with the help of special road construction equipment (thermoprofilers, remixers, recyclers, etc.). Old asphalt pavement milling can be carried out in a cold or hot way. In the case of hot milling, infrared heaters are used to preheat asphalt concrete. There are several basic regeneration methods of old asphalt concrete at the work site: - hot regeneration; - method of thermoplasticization - hot regeneration of old asphalt material with addition to its composition a plasticizer; - thermomixing method - hot regeneration of old asphalt material with addition a new asphalt mix, as well as rubble, bitumen binder and plasticizer; - thermoprofiling method - hot regeneration of old asphalt material without adding a new asphalt mix. - cold regeneration - restoration of old asphalt material without heating with addition organics and mineral binders, stone material, as well as various impurities that improve regenerated material characteristics.

Utilization of production shingle waste in hot mix asphalt and warm mix asphalt

Shingle material can appear as an excess usage due to defective production problems or at the end of their service life. Especially the reuse of shingle materials in bitumen has brought a different approach in terms of sustainability. In this study, the utilization of production shingle waste material in asphalt pavement were investigated. Mechanical properties of hot mix and warm mix asphalt samples involving different amount of production shingle waste (1-6% by weight of the aggregate) were evaluated. Following the determination of optimum rate of shingle waste bitumen content is reduced to decrease both hazardous effects of bitumen and production cost. Marshall Mix Design criteria was employed on determination of maximum reduction on bitumen content and the amount of shingle utilization within the asphalt pavement. As a final analysis, indirect tensile tests were performed on the specimens prepared with determined bitumen content and shingle waste. As a result, it is concluded that, utilization of waste shingles within the asphalt mixture not only benefits the environment and cost but also improves Marshall stability and Marshall quotient of the mixtures.

Improving asphalt mix design considering international roughness index of asphalt pavement predicted using autoencoders and machine learning

Scientific asphalt mix design can improve the engineering properties of asphalt mixture, thus further slowing the growth of international roughness index (IRI). To avoid the occurrence of high IRI values in pavement design life, this study improved the current asphalt mix design by introducing a machine learning (ML) model to predict pavement IRI. The data relating to the IRI of flexible pavements were collected from the long-term pavement performance (LTPP) program database. A total of 37 input features about climate condition, traffic, pavement structure, and pavement materials properties were selected based on backward elimination and recursive feature elimination methods. The effect of five different dimensionality reduction techniques on the performance of ML models was analyzed. Six different ML algorithms including support vector regression (SVR), random forest, artificial neural networks (ANN), Gaussian process regression (GPR), Extra-trees, and gradient boosting (GB) were trained to predict IRI, and the performance metrics (R2, RMSE, MAE, MAPE, and SI) of these ML models were computed and compared. The IRI criterion and the best IRI prediction model were then added to the asphalt mix design procedure. The results showed that compared to other dimensionality reduction methods, the combination of autoencoders makes ANN and GB perform better. The AE-GPR was the best approach to predicting IRI (R2 = 0.94). The proposed mix design procedure was operated to design the asphalt concrete for the surface layer of a construction project. The predicted IRIs of the initial trial blends (including the traditionally designed mix) do not exceed the range of the IRI criterion in the procedure, and the recommended mixture remains the same as the traditionally designed one.

Investigating the Mechanical Properties and Durability of Asphalt Mixture Modified with Epoxidized Natural Rubber (ENR) under Short and Long-Term Aging Conditions.

Modifiers such as fibers, fillers, natural and synthetic polymer extenders, oxidants and anti-oxidants, and anti-stripping agents are added to produce modified asphalt. However, polymers are the most widely utilized modifiers to enhance the function of asphalt mixtures. The objective of this research was to evaluate the mechanical properties and durability of epoxidized natural rubber (ENR)-modified asphalt mix under short- and long-term aging conditions. The physical and rheological characteristics of the base asphalt and ENR-modified asphalt (ENRMA) were tested. In order to evaluate the mechanical properties and durability of the modified mixtures, the resilient modulus of the ENR-asphalt mixtures under unaged, and short- and long-term aging conditions at various temperatures and frequencies was obtained. Furthermore, the resistance to moisture damage of asphalt mixtures was investigated. The findings showed that the stiffness of the ENR-asphalt mixes increased because of the mutual influence of short- and long-term aging on the mixes. In addition, ENR reduced the susceptibility to moisture damage. The stiffness of the mixes was influenced by the temperature and frequencies. By using mathematical modelling via the multivariable power least squares method, it was found that temperature was the dominant factor among all other factors. The results suggested that the durability of asphalt pavements is improved by using ENR.

Analysis of possible carcinogenic compounds in recycled plastic modified asphalt

The incorporation of recycled plastics in asphalt mixtures is getting a growing interest, however, exposing recycled plastics to the high working temperatures of asphalt has posed health and safety concerns. Few studies have paid attention to assessing health and environmental risks concerning recycled plastic-modified asphalt. This study investigates the release of 6 carcinogenic compounds from asphalt modified with recycled plastics, 4 volatile organic compounds (VOCs) and 2 polycyclic aromatic hydrocarbons (PAHs). The concentration of each compound was quantified by GC–MS. Human health risk assessments were conducted using probabilistic methods to assess the risk for an average Australian construction worker to get non-carcinogenic and carcinogenic health issues when exposed to conventional and plastic-modified asphalt fumes. Results showed that non-carcinogenic and carcinogenic risks related to VOC carcinogens (benzene, trichloroethylene, tetrachloroethylene and styrene) are negligible while PAHs (benzo[a]pyrene and dibenz[a,h]anthracene) constitute a possible non-carcinogenic risk and low carcinogenic risk for workers exposed to asphalt fumes. Overall the incorporation of recycled plastic in asphalt reduced the risk for workers to get non-carcinogenic and carcinogenic health issues compared to conventional asphalt mixes. Environmental implicationWith increasing trends of using recycled plastics as road materials, concerns about the exposure of workers to carcinogenic gaseous emissions have been raised. This study demonstrates a non-carcinogenic and carcinogenic risk assessment on exposure to recycled plastic modified asphalt fumes. The findings suggest that recycled plastics decrease non-carcinogenic and carcinogenic risks compared to conventional asphalt.

Comparison of Environmental Loads of Fibers Used in the Manufacture of Hot Mix Asphalt (HMA) and Stone Mastic Asphalt (SMA) Mixes Using a Life Cycle Assessment (LCA)

Several authors have demonstrated improvements in the mechanical performance of asphalt mixes by including the use of fibers. However, it has also been reported that environmental assessments must address fiber use in asphalt mixes from the point of view of sustainability. In this study, a life cycle assessment is used to compare the use of four different fibers (fiberglass, polyester fiber, aramid fiber, and cellulose fiber) commonly used in hot mix asphalt (HMA) and stone mastic asphalt (SMA) mixes. Additionally, the use of textile fibers from end-of-life tires (FiTyre) is included in the comparison. The results show that in the five selected impact categories (climate change, terrestrial acidification, human toxicity, particulate matter emissions, and the exhaustion of nonrenewable fossil fuels), the use of FiTyre and cellulose fibers is more advantageous than existing traditional fibers (fiberglass, polyester fiber, and aramid fiber).

Improving asphalt mix design by predicting alligator cracking and longitudinal cracking based on machine learning and dimensionality reduction techniques

• Reasonable asphalt mixture design can mitigate the cracking problems. • Alligator cracking (AC) and longitudinal (LC) cracking are predicted from asphalt mixture properties. • The effect of three different dimension reduction methods on the performance of ML models is analyzed. • ML algorithms includes Support vector regression, Artificial Neural Networks, Kernel ridge regression, Gradient boosting, Extra-trees, eXtreme Gradient Boosting. • The paper improves the current asphalt mix design by adding the criteria of AC and LC and ML models. The asphalt mix design based on traditional laboratory fatigue cracking tests of asphalt mixture is not reasonable due to the difficulty of simulating the circumstance where asphalt mixture experiences in the pavement structure and under realistic climate and traffic conditions. The study aims to mitigate the cracking problems during the pavement design life, by improving the asphalt mix design process by introducing machine learning (ML) models, which are used to predict alligator cracking (AC) and longitudinal cracking (LC), and their criteria (required ranges). The data containing AC and LC were extracted from the NCHRP 1-37A report and the long-term pavement performance (LTPP) program. A total of 33 input features about climate condition, traffic, pavement structure, and materials properties of each pavement layer were selected. Support Vector Regression (SVR), Artificial Neural Networks (ANN), Kernel ridge regression (KRR), Gradient boosting (GB), Extra-trees, and eXtreme Gradient Boosting (XGBoost) were used. Meanwhile, three dimensionality reduction approaches, including Auto-Encoder (AE), Principal Component Analysis (PCA), and Recursive feature elimination with Random Forest, were combined with the six ML algorithms (18 hybrid models produced) in order to decrease the computation complexity and search for the optimum model. The 24 models (6 basic ML models plus 18 hybrid models) were trained, and their hyperparameters were tuned using Bayesian optimization. Different evaluation criteria R 2 , RMSE, MAE, SMAPE, and SI are calculated to evaluate the performance of these models. The results of the study showed that except for ANN and SVR, the basic ML models can get better for predicting AC and LC when they are combined with PCA or AE. Based on the performance indices, the optimum among these developed models proved to be PCA-ANN for predicting AC (R 2 = 0.84) and LC (R 2 = 0.83). Compared to other pavement layers, the asphalt surface course is the highest contributor to AC and LC. The improved mix design process was implemented to determine the mix proportion for the asphalt surface course of a construction project and Mix-2 with 5.1 % asphalt content was recommended.

Evaluating Asphalt Mix Ingredients by Moisture Susceptibility: The Development of a New Modified Boiling Test Procedure Based on Digital Imaging

Evaluating Asphalt Mix Ingredients by Moisture Susceptibility: The Development of a New Modified Boiling Test Procedure Based on Digital Imaging

The Effect of Using Ceramic Waste Powder as a Filler on the Performance of Bitumen Mastic and Hot Asphalt Mix

The use of raw resources is increasing due to the continuous increase of world population and rapid industrialization; while natural resources are being depleted day by day. The use of waste or manufactured materials in road construction has significant environmental and economic benefits. In this study, the use of ceramic powder as mineral filler in hot asphalt mix as an alter- native method to traditional crushed stone was investigated. The optimal amount of bitumen was determined using Marshall Mix Design method or using four different amounts of bitumen 4.5%, 5% and 5.5%. With the optimal amount of bitumen, two different types of corroded mineral fillers, ceramic and stone powder with three different filler ratios (4%, 6%, and 8%) were used to prepare asphalt mixture samples. The samples were subjected to Marshall Resistance Test, flow, determination of empty space percentage and percentage of empty space filled with bitumen and the results were compared. Also, to evaluate the type and amount of filler on the performance of bitumen, penetration degree test, softening point and ductility test of pure bitumen and bitumen containing two materials of calcareous filler and ceramic powder with different percentages were performed. The results show that the Marshall and flow strength of mixtures containing calcareous filler is about 5% higher and 12% less than the mixture containing the waste filler, respectively, and with increasing the percentage of filler in asphalt samples, the average degree of penetration and elasticity are about 30% and 4.5%, respectively decreases and softening point increases 7%; These changes are more severe in asphalt samples containing calcareous fillers. In general, it can be concluded that ceramic waste powder can be used in asphalt mixture as a mineral filler to replace crushed rock dust, because the use of this material as filler in road construction is appropriate in terms of economic and environmental factors.

Evaluation of the Effect of Recycled Waste Plastic Bags on Mechanical Properties of Hot Mix Asphalt Mixture for Road Construction

Abstract: The use of recycled waste materials in road pavements is currently seen as a viable solution not just in terms of environmental sustainability, but also in terms of improving service performance.[1] This is particularly true when it comes to recycled plastics. Thin plastic bags are primarily composed of low-density Polyethylene and it’s commonly used for packaging, protecting and many other applications. Nevertheless, disposal of waste plastic bags in large quantities constitutes an environmental problem, as they considered non-biodegradable materials. Hence, there is a real need to find useful applications for these growing quantities of wastes. In this research, Waste Plastic Bags (WPB) as one form of polymers are used to investigate the potential prospects to enhance asphalt mixture properties. Research aims include studying the effect of partial replacing of different percentages of WPB pieces of the bitumen as binder modifiers on the properties of asphalt mix comparing it with conventional mix properties, besides identifying the optimum percent of WPB to be added in the hot mix asphalt. WPB were presented in the asphalt mixture in pieces with size (2 x 5 mm2 ). Marshal mix design procedure was used, first to determine the Optimum Bitumen Content (OBC) and then further to test the modified mixture properties. In total, (39) samples were prepared, 15 samples were used to determine the OBC and the remaining were used to investigate the effects adding different WPB percentages to asphalt mix. The OBC was 5.6 % by weight of asphalt mix. Seven proportions of WPB by weight of OBC were tested (2, 4, 8, 12, 16, 20 and 24%), besides testing of ordinary asphalt mix. Tests include the determination of stability, bulk density, flow and air voids