Research Trends in Pavement Management during the First Years of the 21st Century: A Bibliometric Analysis during the 2000–2013 Period

Removal of Heavy Metals from Wastewaters and Other Aqueous Streams by Pressure-Driven Membrane Technologies: An Outlook on Reverse Osmosis, Nanofiltration, Ultrafiltration and Microfiltration Potential from a Bibliometric Analysis

A bibliometric study to analyze the scientific documents released until 2024 in the database Scopus related to the use of pressure-driven membrane technologies (microfiltration, ultrafiltration, nanofiltration and reverse osmosis) for heavy metal removal was conducted. The work aimed to assess the primary quantitative attributes of the research in this field during the specified period. A total of 2205 documents were identified, and the corresponding analysis indicated an exponential growth in the number of publications over time. The contribution of the three most productive countries (China, India and USA) accounts for more than 47.1% of the total number of publications, with Chinese institutions appearing as the most productive ones. Environmental Science was the most frequent knowledge category (51.9% contribution), followed by Chemistry and Chemical Engineering. The relative frequency of the keywords and a complete bibliometric network analysis allowed the conclusion that the low-pressure technologies (microfiltration and ultrafiltration) have been more deeply investigated than the high-pressure technologies (nanofiltration and reverse osmosis). Although porous low-pressure membranes are not adequate for the removal of dissolved heavy metals in ionic forms, the incorporation of embedded adsorbents within the membrane structure and the use of auxiliary chemicals to form metallic complexes or micelles that can be retained by this type of membrane are promising approaches. High-pressure membranes can achieve rejection percentages above 90% (99% in the case of reverse osmosis), but they imply lower permeate productivity and higher costs due to the required pressure gradients.

Innovative Membrane Technologies for the Treatment of Wastewater Polluted with Heavy Metals: Perspective of the Potential of Electrodialysis, Membrane Distillation, and Forward Osmosis from a Bibliometric Analysis

A bibliometric analysis, using the Scopus database as a source, was carried out in order to study the scientific documents published up to 2021 regarding the use of electrodialysis, membrane distillation, and forward osmosis for the removal of heavy metals from wastewater. A total of 362 documents that fulfilled the search criteria were found, and the results from the corresponding analysis revealed that the number of documents greatly increased after the year 2010, although the first document was published in 1956. The exponential evolution of the scientific production related to these innovative membrane technologies confirmed an increasing interest from the scientific community. The most prolific country was Denmark, which contributed 19.3% of the published documents, followed by the two main current scientific superpowers: China and the USA (with 17.4% and 7.5% contributions, respectively). Environmental Science was the most common subject (55.0% of contributions), followed by Chemical Engineering (37.3% of contributions) and Chemistry (36.5% of contribution). The prevalence of electrodialysis over the other two technologies was clear in terms of relative frequency of the keywords. An analysis of the main hot topics identified the main advantages and drawbacks of each technology, and revealed that examples of their successful implementation beyond the lab scale are still scarce. Therefore, complete techno-economic evaluation of the treatment of wastewater polluted with heavy metals via these innovative membrane technologies must be encouraged.

Artificial Neural Networks for Flexible Pavement

Transportation agencies are primarily responsible for building new roads and maintaining current roads. The main focuses of these agencies are to prioritize maintenance and make significant rehabilitation decisions to handle serious problems facing road authorities. Considerable efforts and an abundance of studies have been performed to determine the nature, mechanisms, test methods, and measurement of pavements for preservation and improvements of roadways. The presented study reports a state-of-the-art review on recent advances in the application of artificial intelligence in various steps of flexible pavement, including pavement construction, performance, cost, and maintenance. Herein, the challenges of gathering large amounts of data, parameter optimization, portability, and low-cost data annotating are discussed. According to the findings, it is suggested that greater attention should be paid to integrating multidisciplinary roadway engineering techniques to address existing challenges and opportunities in the future.

Mechanical-Empirical Pavement Design Guide Applied to Portuguese Pavement Structures

This paper describes the characteristics of the new pavement design method developed by the American Association of State Highway and Transportation Officials (AASHTO), known as AASHTOWare Pavement-ME®, and presents the results of its application to the flexible pavement structures presented in the Portuguese Manual of Pavement Structures for the national road network. The results obtained clearly show that it is a very useful tool for road engineers not only for designing new pavement structures but also for the analysis of their performance and for efficiently planning maintenance and rehabilitation interventions. According to the characteristics of the case study that was considered, rutting is the most critical distress, since it presents values close to its threshold value of 20.0 mm, a value that is defined in Portuguese Quality Control Plans.

Economic Evaluation of Cement Grouted Bituminous Mixes for Airport Pavements

The Cement Grouted Bituminous Mix (CGBM) is an innovative material that could be used to build airport pavements subjected to heavy concentrated loads or fuel and solvent leaks. CGBM is composed of a porous asphalt clogged with an expansive cement mixture, which fills the asphalt voids. This paper focuses on two airport pavements (i.e., a taxiway and a helipad one) to be paved in an Italian airport. For each surface, the construction and maintenance costs of a CGBM pavement and a traditional flexible pavement have been compared. The pavements should bear different traffic loads, while the weather, subgrade, and materials are the same: the fatigue and rutting verification gives structures whose cost analysis leads to different results. The CGBM solution for the taxiway has a cost comparable to that of the equivalent traditional flexible pavement (i.e., 73.87 €/m² vs. 73.20 €/m² during the service life). On the other hand, the overall discounted cost of the helipad surface paved with CGBM is higher than that obtained for the traditional pavement (i.e., 82.4 €/m² vs. 67.5 €/m²). Therefore, the study demonstrates that the economic opportunity of CGBM solutions strongly depends on traffic loads.

Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies

Maintenance and rehabilitation (M&R) scheduling for airport pavement is supported by the scientific literature, while a specific tool for heliport pavements lacks. A heliport pavement management system (HPMS) allows the infrastructure manager to obtain benefits in technical and economic terms, as well as safety and efficiency, during the analyzed period. Structure and rationale of the APSM could be replicated and simplified to implement a HPMS because movements of rotary-wing aircrafts have less complexity than fixed-wing ones and have lower mechanical effects on the pavement. In this study, an innovative pavement condition index-based HPMS has been proposed and implemented to rigid and flexible surfaces of the airport of Vergiate (province of Varese, Italy), and two twenty-year M&R plans have been developed, where the results from reactive and proactive approaches have been compared to identify the best strategy in terms of costs and pavement level of service. The result obtained shows that although the loads and traffic of rotary-wing aircrafts are limited, the adoption of PMS is also necessary in the heliport environment.

Self-Healing Asphalt: A Systematic Bibliometric Analysis for Identification of Hot Research Topics during the 2003-2018 Period

The use of self-healing asphalt is a good option to extend the lifetime of roads and to improve the sustainability of pavement management systems. A bibliometric analysis based on the Scopus database was carried out to review the global research related to self-healing asphalt from 2003 to 2018 and to identify relevant quantitative characteristics from the research in this period. The results from this analysis revealed that the number of accumulated publications followed an exponential growth, which confirmed the relevance that this research topic has gained during the last years. The study revealed that China was the most productive country, followed by the Netherlands, where the most prolific institution is located: Delft University of Technology. Some important research features of the two main approaches most frequently used to develop asphalt mixtures with enhanced self-healing abilities (external heating and encapsulated rejuvenating agents) are compiled in this work.

Automatic Detection of Cracks in Asphalt Pavement Using Deep Learning to Overcome Weaknesses in Images and GIS Visualization

The crack ratio is one of the indices used to quantitatively evaluate the soundness of asphalt pavement. However, since the inspection of pavement requires much labor and cost, automatic inspection of pavement damage by image analysis is required in order to reduce the burden of such work. In this study, a system was constructed that automatically detects and evaluates cracks from images of pavement using a convolutional neural network, a kind of deep learning. The most novel aspect of this study is that the accuracy was recursively improved through retraining the convolutional neural network (CNN) by collecting images which had previously been incorrectly analyzed. Then, study and implementation were conducted of a system for plotting the results in a GIS. In addition, an experiment was carried out applying this system to images actually taken from an MMS (mobile mapping system), and this confirmed that the system had high crack evaluation performance.

Influence of Pavement Structure, Traffic, and Weather on Urban Flexible Pavement Deterioration

Various studies have been recently conducted to predict pavement condition, but most of them were developed in a certain region where climate conditions were kept constant and/or the research focused on specific road distresses using single parameters. Thus, this research aimed at determining the influence of pavement structure, traffic demand, and climate factors on urban flexible pavement condition over time. To do this, the Structural Number was used as an indicator of the pavement capacity, various traffic and climate variables were defined, and the Pavement Condition Index was used as a surrogate measure of pavement condition. The analysis was focused on the calibration of regression models by using the K-Fold Cross Validation technique. As a result, for a given pavement age, pavement condition worsens as the Equivalent Single Axle Load and the Annual Average Height of Snow increased. Likewise, a cold Annual Average Temperature (5–15 °C) and a large Annual Average Range of Temperature (20–30 °C) encourage a more aggressive pavement deterioration process. By contrast, warm climates with low temperature variations, which are associated with low precipitation, lead to a longer pavement service life. Additionally, a new classification of climate zones was proposed on the basis of the weather influence on pavement deterioration.

European National Road Authorities and Circular Economy: An Insight into Their Approaches

The pavement engineering industry, having realized the significance of the impacts that it imposes on the environment through the production, construction and management of its products and assets, has been driven towards a more sustainable and circular way of operating. This has partly been through asphalt recycling, which is an area that many road authorities have prioritized. However, not all the National Road Authorities (NRAs) and/or sector stakeholders seem to be adequately familiar with the Circular Economy (CE) concept. This paper attempts to assist the transition of NRAs to a more circular way of doing business, by analyzing the current situation of CE within national/regional authorities and NRAs. To do so, a questionnaire was sent to different NRAs and an online search was conducted to identify the ways that NRAs communicate their CE practices. Findings indicate that, although the majority of the NRAs are familiar with CE as a concept, not many actions have been taken so far towards its holistic implementation. Finally, there is a significant lack of CE expertise and communication within these bodies.

IRI Performance Models for Flexible Pavements in Two-Lane Roads until First Maintenance and/or Rehabilitation Work

Pavement performance models play a vital role in any pavement management system. The Regional Government of Biscay (RGB) (Spain) manages a 1200 km road network and conducts pavement data collections, including the International Roughness Index (IRI) values. The aim of the paper is to develop an IRI performance model for two-lane roads with flexible pavement until the first maintenance and/or rehabilitation activity is performed. Due to the huge amount of available information, a deterministic model was selected. A literature review of deterministic models showed that, apart from age and traffic volumes, the pavement structure is a key factor. Therefore, it was decided to analyze the only road stretches whose entire pavement section was known (surface layer + base + subbase). Various variables related to age, traffic volumes and employed materials were introduced as possible factors. The multiple linear regression model with the highest coefficient of determination and all the variables significant included the real pavement age, the cumulated heavy traffic and the total thickness of bituminous layers. As the material employed in the surface layer could affect roughness progression, a qualitative variable was introduced to consider various surface materials. The model improved its accuracy, indicating that the surface layer material is also an influencing factor on IRI evolution.

Flexural Strength Prediction Models for Soil⁻Cement from Unconfined Compressive Strength at Seven Days

Soil⁻cement is an environmentally friendly road construction technique for base and subbase materials, which allows employing soils placed in the right-of-way of the road or in the surroundings, by improving its engineering properties. With this technique, it is possible to reduce the over-exploitation of quarries, the necessity of landfills and the pollutant gas emission due to the reduction of aggregate fabrication and transport. The manufacturing of soil⁻cement is generally controlled by means of the Uniaxial Compressive Strength (UCS) test at seven days, according to the regulations of each country. Nonetheless, one of the properties that best defines the performance of soil⁻cement is the Flexural Strength (FS) at long term, usually at 90 days. The aim of this paper is to develop new equations to correlate the UCS and the FS at long term and the UCS at seven days and at 90 days. Obtained results validate the proposed models and, hence, the flexural strength can be predicted from the Uniaxial Compressive Strength at seven days, allowing, if necessary, correcting measures (recalculation or rejection) in early stages of the curing time to be taken.

Alternatives for Chemical and Biochemical Lignin Valorization: Hot Topics from a Bibliometric Analysis of the Research Published During the 2000–2016 Period

A complete bibliometric analysis of the Scopus database was performed to identify the research trends related to lignin valorization from 2000 to 2016. The results from this analysis revealed an exponentially increasing number of publications and a high relevance of interdisciplinary collaboration. The simultaneous valorization of the three main components of lignocellulosic biomass (cellulose, hemicellulose, and lignin) has been revealed as a key aspect and optimal pretreatment is required for the subsequent lignin valorization. Research covers the determination of the lignin structure, isolation, and characterization; depolymerization by thermal and thermochemical methods; chemical, biochemical and biological conversion of depolymerized lignin; and lignin applications. Most methods for lignin depolymerization are focused on the selective cleavage of the β-O-4 linkage. Although many depolymerization methods have been developed, depolymerization with sodium hydroxide is the dominant process at industrial scale. Oxidative conversion of lignin is the most used method for the chemical lignin upgrading. Lignin uses can be classified according to its structure into lignin-derived aromatic compounds, lignin-derived carbon materials and lignin-derived polymeric materials. There are many advances in all approaches, but lignin-derived polymeric materials appear as a promising option.