Recycled asphalt mixtures produced with high percentage of different waste materials

The use of sustainable solutions in construction is not just an option, but is increasingly becoming a need of the Society. Thus, nowadays the recycling of waste materials is a growing technology that needs to be continuously improved, namely by researching new solutions for waste valorisation and by increasing the amount of wastes reused. In the paving industry, the reuse of reclaimed asphalt (RA) is becoming common practice, but needs further research work. Thus, this study aims to increase the incorporation of RA and other waste materials in the production of recycled asphalt mixtures in order to improve their mechanical, environmental and economic performance. Recycled mixtures with 50% RA were analysed in this study, including: i) RA selection, preparation and characterization; ii) incorporation of other waste materials as binder additives or modifiers, like used motor oil (UMO) and waste high density polyethylene (HDPE); iii) production of different mixtures (without additives; with UMO; with UMO and HDPE) and comparison of their performance in order to assess the main advantages of each solution. With this study it was concluded that up to 7.5 % of UMO and 4.0 % of HDPE can be used in a new modified binder for asphalt mixtures with 50 % of RA, which have excellent properties concerning the rutting with WTS = 0.02 mm/103 cycles, the fatigue resistance with ε6 = 160.4, and water sensitivity with an ITSR of 81.9 %.

Embedded Through-Section shear strengthening technique using steel and CFRP bars in RC beams of different percentage of existing stirrups

The Embedded Through-Section (ETS) technique is a promising technique for the shear strengthening of existing (RC) elements. According to this technique, holes are drilled through the beam section, and bars of steel or FRP material are introduced into these holes and bonded to the concrete with adhesive materials. An experimental program was carried out with RC T-cross section beams strengthened in shear using the ETS steel bars and ETS CFRP rods. The research is focused on the evaluation of the ETS efficiency on beams with different percentage of existing internal transverse reinforcement (ρsw=0.0%, ρsw=0.1% and ρsw=0.17%). The effectiveness of different ETS strengthening configurations was also investigated. The good bond between the strengthening ETS bars and the surrounding concrete allowed the yield initiation of the ETS steel bars and the attainment of high tensile strains in the ETS CFPR rods, leading to significant increase of shear capacity, whose level was strongly influenced by the inclination of the ETS bars and the percentage of internal transverse reinforcement.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.