10 resultados para highways

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This paper describes the testing of a novel flexible masonry concrete arch system which requires no centering in the construction phase or steel reinforcement in the long-term. The arch is constructed from a 'flat pack' system by use of a polymer reinforcement for supporting the self-weight of the concrete voussoirs and behaves as a masonry arch once in the arch form. The paper outlines the construction of a prototype arch and load testing of the backfilled arch ring. Some comparisons to the results from analysis software have been made. The arch had a load carrying capacity far in excess of the current Highways Agency (United Kingdom) design wheel loads.

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Winter deicing operations occur extensively in mid- to high-latitude metropolitan regions around the world and result in a significant reduction in road accidents. Deicing salts can, however, pose a major threat to water quality and aquatic organisms. In this paper we examine the utility of Arcellacea (testate amoebae) for monitoring lakes that have become contaminated by winter deicing salts, particularly sodium chloride. We analysed 50 sediment samples and salt-related water-property variables (chloride concentrations; conductivity) from 15 lakes in the Greater Toronto Area and adjacent areas of southern Ontario, Canada. The sampled lakes included lakes in proximity to major highways and suburban roads, and control lakes in forested settings away from road influences. Samples from the most contaminated lakes, with chloride concentrations in excess of 400 mg/l and conductivities of >800 μS/cm, were dominated by species typically found in brackish and/or inhospitable lake environments and by lower faunal diversities (lowest Shannon Diversity Index values) than samples with lower readings. Q-R-mode cluster analysis and Detrended Correspondence Analysis (DCA) resulted in the recognition of four assemblage groupings. These reflect varying levels of salt contamination in the study lakes, along with other local influences, including nutrient loading. The response to nutrients can, however, be isolated if the planktic eutrophic indicator species Cucurbitella tricuspis is removed from the counts. The findings show that the group have considerable potential for biomonitoring in salt-contaminated lakes, and through application to lake sediment cores, may provide significant insights into long-term benthic community health, which is integral for remedial efforts.

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In [M. Herty, A. Klein, S. Moutari, V. Schleper, and G. Steinaur, IMA J. Appl. Math., 78(5), 1087–1108, 2013] and [M. Herty and V. Schleper, ZAMM J. Appl. Math. Mech., 91, 763–776, 2011], a macroscopic approach, derived from fluid-dynamics models, has been introduced to infer traffic conditions prone to road traffic collisions along highways’ sections. In these studies, the governing equations are coupled within an Eulerian framework, which assumes fixed interfaces between the models. A coupling in Lagrangian coordinates would enable us to get rid of this (not very realistic) assumption. In this paper, we investigate the well-posedness and the suitability of the coupling of the governing equations within the Lagrangian framework. Further, we illustrate some features of the proposed approach through some numerical simulations.

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The papers in this special issue focus on the topic of location awareness for radio and networks. Localization-awareness using radio signals stands to revolutionize the fields of navigation and communication engineering. It can be utilized to great effect in the next generation of cellular networks, mining applications, health-care monitoring, transportation and intelligent highways, multi-robot applications, first responders operations, military applications, factory automation, building and environmental controls, cognitive wireless networks, commercial and social network applications, and smart spaces. A multitude of technologies can be used in location-aware radios and networks, including GNSS, RFID, cellular, UWB, WLAN, Bluetooth, cooperative localization, indoor GPS, device-free localization, IR, Radar, and UHF. The performances of these technologies are measured by their accuracy, precision, complexity, robustness, scalability, and cost. Given the many application scenarios across different disciplines, there is a clear need for a broad, up-to-date and cogent treatment of radio-based location awareness. This special issue aims to provide a comprehensive overview of the state-of-the-art in technology, regulation, and theory. It also presents a holistic view of research challenges and opportunities in the emerging areas of localization.

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A tactful ionic-liquid (IL)-assisted approach to in situ synthesis of iron fluoride/graphene nanosheet (GNS) hybrid nanostructures is developed. To ensure uniform dispersion and tight anchoring of the iron fluoride on graphene, we employ an IL which serves not only as a green fluoride source for the crystallization of iron fluoride nanoparticles but also as a dispersant of GNSs. Owing to the electron transfer highways created between the nanoparticles and the GNSs, the iron fluoride/GNS hybrid cathodes exhibit a remarkable improvement in both capacity and rate performance (230 mAh g-1 at 0.1 C and 74 mAh g-1 at 40 C). The stable adhesion of iron fluoride nanoparticles on GNSs also introduces a significant improvement in long-term cyclic performance (115 mAh g-1 after 250 cycles even at 10 C). The superior electrochemical performance of these iron fluoride/GNS hybrids as lithium ion battery cathodes is ascribed to the robust structure of the hybrid and the synergies between iron fluoride nanoparticles and graphene. © 2013 American Chemical Society.

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Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

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The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.

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This paper describes the hydrogeological processes which caused unexpected instability and quick conditions during the excavation of a 25m deep cutting through a drumlin in County Down, Northern Ireland. A conceptual hydrogeological model of the cutting, based on pore pressures monitored during and after the excavation demonstrates how quick conditions at the toe of the cutting caused liquefaction of the till. Stability of the cutting was re-established by draining the highly permeable, weathered Greywacke which underlies the drumlin, through the use of a deep toe drain. In spite of this drainage, the cutting was only marginally stable due to the presence of a low permeability zone in the till above the bedrock which limits the reduction of elevated pore pressures within the upper to mid-depths of the drumlin. The factor of safety has been further improved by the addition of vertical relief drains at the crest and berm of the cutting to relieve the pore-pressures within the upper till by intercepting the weathered bedrock. The paper also highlights the importance of carrying out an adequate site investigation compliant with Eurocode 7 and additional monitoring in excavations in stiff, low permeability till.