A Novel Approach for Axle Detection in Bridge Weigh-In-Motion Systems

Bridge weigh-in-motion (B-WIM), a system that uses strain sensors to calculate the weights of trucks passing on bridges overhead, requires accurate axle location and speed information for effective performance. The success of a B-WIM system is dependent upon the accuracy of the axle detection method. It is widely recognised that any form of axle detector on the road surface is not ideal for B-WIM applications as it can cause disruption to the traffic (Ojio & Yamada 2002; Zhao et al. 2005; Chatterjee et al. 2006). Sensors under the bridge, that is Nothing-on-Road (NOR) B-WIM, can perform axle detection via data acquisition systems which can detect a peak in strain as the axle passes. The method is often successful, although not all bridges are suitable for NOR B-WIM due to limitations of the system. Significant research has been carried out to further develop the method and the NOR algorithms, but beam-and-slab bridges with deep beams still present a challenge. With these bridges, the slabs are used for axle detection, but peaks in the slab strains are sensitive to the transverse position of wheels on the beam. This next generation B-WIM research project extends the current B-WIM algorithm to the problem of axle detection and safety, thus overcoming the existing limitations in current state-of–the-art technology. Finite Element Analysis was used to determine the critical locations for axle detecting sensors and the findings were then tested in the field. In this paper, alternative strategies for axle detection were determined using Finite Element analysis and the findings were then tested in the field. The site selected for testing was in Loughbrickland, Northern Ireland, along the A1 corridor connecting the two cities of Belfast and Dublin. The structure is on a central route through the island of Ireland and has a high traffic volume which made it an optimum location for the study. Another huge benefit of the chosen location was its close proximity to a nearby self-operated weigh station. To determine the accuracy of the proposed B-WIM system and develop a knowledge base of the traffic load on the structure, a pavement WIM system was also installed on the northbound lane on the approach to the structure. The bridge structure selected for this B-WIM research comprised of 27 pre-cast prestressed concrete Y4-beams, and a cast in-situ concrete deck. The structure, a newly constructed integral bridge, spans 19 m and has an angle of skew of 22.7°.

Influence of service loading and the resulting micro-cracks on chloride resistance of concrete

Chloride-induced corrosion of steel in reinforced concrete structures is one of the main problems affecting their durability, but most previous research projects and case studies have focused on concretes without cracks or not subjected to any structural load. Although it has been recognised that structural cracks do influence the chloride transport and chloride induced corrosion in reinforced concrete structures, there is little published work on the influence of micro-cracks due to service loads on these properties. Therefore the effect of micro-cracks caused by loading on chloride transport into concrete was studied. Four different stress levels (0%, 25%, 50% and 75% of the stress at ultimate load – fu) were applied to 100 mm diameter concrete discs and chloride migration was measured using a bespoke test setup based on the NT BUILD 492 test. The effects of replacing Portland cement CEMI by ground granulated blast-furnace slag (GGBS), pulverised fuel ash (PFA) and silica fume (SF) on chloride transport in concrete under sustained loading were studied. The results have indicated that chloride migration coefficients changed little when the stress level was below 50% of the fu; however, it is desirable to keep concrete stress less than 25% fu if this is practical. The effect of removing the load on the change of chloride migration coefficient was also studied. A recovery of around 50% of the increased chloride migration coefficient was found in the case of concretes subjected to 75% of the fu when the load was removed.

Modelling the fresh properties of self-compacting concrete using support vector machine approach

The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.

Effect of Cyclic Carbonation on Chloride Ingression in GGBS Concrete

Carbonation and chloride ingress are the two main causes of corrosion in reinforced concrete structures. An investigation to monitor the ingress of chlorides and the effect of carbonation on chloride ingression during an accelerated 12 month cyclic wetting and drying exposure regime that simulates conditions in which multiple mode transport mechanisms are active was conducted on ground granulated blast furnace slag (GGBS) concrete. The penetration of chloride and carbon dioxide was evaluated using water and acid soluble chloride profiles and phenolphthalein indicator, respectively. The results indicated that when chloride and carbon dioxide ingress concomitantly the effects can be adverse. Carbonation has a detrimental effect on the binding capacity of the concrete, increasing the concentration of free (water soluble) chlorides. This contributed to greater concentration and greater penetration of chlorides and thus an increased corrosion risk.

Development of Seismic Fragility Functions for a Moment Resisting Reinforced Concrete Framed Structure

Understanding the seismic vulnerability of building structures is important for seismic engineers, building owners, risk insurers and governments. Seismic vulnerability defines a buildings predisposition to be damaged as a result of an earthquake of a given severity. There are two components to seismic risk; the seismic hazard and the exposure of the structural inventory to any given earthquake event. This paper demonstrates the development of fragility curves at different damage states using a detailed mechanical model of a moment resisting reinforced concrete structure typical of Southern Europe. The mechanical model consists of a complex three-dimensional finite element model of the reinforced concrete moment resisting frame structure and is used to define the damage states through pushover analysis. Fragility curves are also defined using the HAZUS macroseismic methodology and the Risk-UE macroseismic methodology. Comparison of the mechanically modelled and HAZUS fragility curve shows good agreement while the Risk-UE methodology shows reasonably poor agreement.

Heat Activated Prestressing of Shape Memory Alloys for Active Confinement of Concrete Sections

This paper presents the results from the experimental investigation on heat activated prestressing of Shape Memory Alloy (SMA) wires for active confinement of concrete sections. Active confinement of concrete is found to be much more effective than passive confinement which becomes effective only when the concrete starts to dilate. Active confinement achieved using conventional prestressing techniques often faces many obstacles due to practical limitations. A class of smart materials that has recently drawn attention in civil engineering is the super elastic SMA which has the ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of SMAs can be utilized to develop a convenient prestressing technique for active confinement of concrete sections.
In this study a series of experimental tests are conducted to study Heat Activated Prestress (HAP) in SMAs. Three different types of tests are conducted with different loading protocol to determine parameters such as HAP, residual strain after heating and range of strain that can be used for effective active confinement after HAP. Test results show a maximum HAP of about 500 MPa can be achieved after heating and approximately 450MPa is retained at 25oC in specimens pre-strained by 6%. A substantial amount of strain recovery upon unloading and after heating the SMA wires is recorded. About 2.5% elastic strain recovery upon unloading from 6% strain level is observed. In the specimen pre-strained by 6%, a total of 4% strain is recovered when unloaded after heating. A strain range of 3% is found available for effective confinement after HAP. Test results demonstrate that SMAs have unique features that can be intelligently employed in many civil engineering applications including active confinement of concrete sections.

Monitoring the durability of marine concrete structures

New techniques based on embedded sensors have been developed for monitoring reinforced concrete structures for assessing their durability, which can be used instead of the conventional non-destructive test techniques. The continuous monitoring of concrete for its durability with various types of sensors allows not only early assessment of the potential durability of structures, but also a prediction of their service life. Effrosyni Tzoura and Muhammed Basheer of University of Leeds, Sreejith Nanukuttan and Danny McPolin of Queen's University Belfast, John McCarter of Heriot-Watt University, Ken Grattan and Tong Sun of City University London and Sudarshan Srinivasan of Mott MacDonald report.