The construction and maintenance of UK roads consume large amounts of quarried aggregates. The use of secondary (recycled), instead of primary (virgin), materials helps easing landfill pressures and reducing demand of extraction. However, concerns over inferior road performance and additional costs have hindered the widespread use of secondary aggregates in such applications. This is especially the case in surface layers of asphalt pavements that may represent a value application for recycled solid waste materials (SWM). Waste glass, steel slag, tyres and plastics are selected for this study, which reviews standards and literature for technical requirements, as well as the performance of asphalt pavements constructed using such recycled materials. Waste arising and management indicates that although there is a large potential for supplying secondary materials, a few factors have effectively depressed such recycling activities. Such barriers are described here and may also apply to the secondary use of other SWM. After identifying and quantifying such barriers a brief discussion suggests ways of their removal.

A review of the use of recycled solid waste materials in asphalt pavements

Rheological properties and chemical analysis of nanoclay and carbon microfiber modified asphalt with Fourier transform infrared spectroscopy

Laboratory investigation of the recycled asphalt concrete with stable crumb rubber asphalt binder

A Literature Review on Cold Recycling Technology of Asphalt Pavement

A transit route network design (TRND) problem for urban bus operation involves the determination of a set of transit routes and the associated frequencies that achieve the desired objective. This can be formulated as an optimization problem of minimizing the total system cost, which is the sum of the operating cost and the generalized travel cost. A review of previous approaches to solve this problem reveals the deficiency of conventional optimization techniques and the suitability of genetic algorithm (GA) based models to handle such combinatorial optimization problems. Since GAs are computationally intensive optimization techniques, their application to large and complex problems is limited. The computational performance of a GA model can be improved by exploiting its inherent parallel nature. Accordingly, two parallel genetic algorithm (PGA) models are proposed in this study. The first is a global parallel virtual machine (PVM) parallel GA model where the fitness evaluation is done concurrently in a parallel processing environment using PVM libraries. The second is a global message passing interface (MPI) parallel GA model where an MPI environment substitutes for the PVM libraries. An existing GA model for TRND for a large city is used as a case study. These models are tested for computation time, speedup, and efficiency. From the study, it is observed that the global PVM model performed better than the other model.

Transit route network design using parallel genetic algorithm

The paper presents the details of various investigations conducted for the laboratory evaluation of the performance of crumb–rubber modified asphalt mixes. Crumb rubber (CR) obtained from discarded truck and bus tires was used to modify 80/100 penetration grade asphalt cement. Fatigue and permanent deformation characteristics, temperature and moisture susceptibility, and oxidative aging are some of the performance indicators of mixes evaluated. A static indentation test was adopted for assessing the relative permanent deformation characteristics of different mixes. Three aggregate gradations: (1) superpave; (2) gradation specified by the Ministry of Surface Transport, India for asphalt concrete; and (3) one gap gradation, were considered in the investigation. Compared to normal mixes, CR modified mixes were found to have improved fatigue and permanent deformation characteristics. They also showed lower temperature susceptibility and greater resistance to moisture damage compared to normal mixes. Superpave mixes gave better overall performance compared to the mixes having other aggregate gradations.

Laboratory evaluation of crumb rubber modified asphalt mixes

Backcalculation of pavement layer moduli refers to the process of evaluating the pavement layers using pavement surface deflections. The genetic algorithm (GA) technique was successfully used in the past for backcalculation. The BACKGA model developed by the Indian Institute of Technology, Kharagpur is one such program used for backcalculation using the GA technique. Though GA-based backcalculation models are considered to be robust due to the search algorithm adopted in the process, they require more computational time due to the large number of times the surface deflections are computed using different sets of layer moduli. In the present work, artificial neural network (ANN) models have been developed for computing surface deflections using elastic moduli and thicknesses of pavement layers as inputs. The ANN models have been used in BACKGA for forward calculation of surface deflections to combine the computational efficiency of ANNs with the robustness of the GAs. The performance of the resulting model...

Artificial Neural Networks—Genetic Algorithm Based Model for Backcalculation of Pavement Layer Moduli

In the context of pavement evaluation, backcalculation is the process of estimation of elastic properties of pavement layers using measured structural responses. A number of backcalculation programs are available for estimating effective pavement layer moduli from surface deflections. Different optimization techniques have been used in the development of these backcalculation models. Genetic algorithm (GA) has been used successfully in the recent past for backcalculation of pavement layer moduli. Selection of appropriate GA parameters is important for the efficient performance of the GA-based algorithm. However, there are no general guidelines available at present for the selection of GA parameters. This paper presents a study conducted for the selection of optimal GA parameters to be adopted for backcalculation of pavement layer moduli. The parameters have been selected on the basis of the level of accuracy desired and the corresponding computational effort (CE). The performance of the GA-based program w...

Selection of genetic algorithm parameters for backcalculation of pavement moduli

Evaluation of asphalt binder rutting parameters

Rutting in bituminous layers is a major mode of distress, especially in pavements with thick bituminous layers. Different binder and mix rutting specifications are adopted by agencies worldwide to ...

K. Sudhakar Reddy

Papers

Laboratory evaluation of crumb rubber modified asphalt mixes

Artificial Neural Networks—Genetic Algorithm Based Model for Backcalculation of Pavement Layer Moduli

Selection of genetic algorithm parameters for backcalculation of pavement moduli

Evaluation of asphalt binder rutting parameters

Evaluation of wheel tracking and field rutting susceptibility of dense bituminous mixes