Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

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.

Evolving techniques for monitoring geotechnical risk on the Antrim Coast Road.

The interaction between problematic geology and environmental variables along the Antrim Coast Road results in frequent instances of geotechnical instability. During such instances of instability, mudslide debris encroaches on the carriageway posing a hazard to motorists, causing lengthily tailbacks. This paper examines some of the geotechnical and spatial analysis techniques currently being implemented to monitor slope stability on this key transport route.

Identification of Road Irregularities via Vehicle Accelerations

A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

Dynamic axle force and road profile identification using a moving vehicle

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.

Review of João M. Cabrita, Mozambique. The Tortuous Road to Democracy.

Book review in Lusotopie, 2002, no.1 of João M. CABRITA, Mozambique. The Tortuous Road to Democracy, Basingstoke (G.-B.) et New York (E.U.A.), Palgrave (St. Martin’s Press), 2000, 311p., ISBN 0-333-92001-5.

The impact of hydrogeology on the instability of a road cutting through a drumlin in the North of Ireland

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.