983 resultados para Prestressed concrete


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Research has shown that fibre reinforced polymer (FRP) wraps are effective for strengthening concrete columns for increased axial and flexural load and deformation capacity, and this technique is now used around the world. The experimental study presented in this paper is focused on the mechanics of FRP confined concrete, with a particular emphasis on the influence of the unconfined concrete compressive strength on confinement effectiveness and hoop strain efficiency. An experimental programme was undertaken to study the compressive strength and stress-strain behaviour of unconfined and FRP confined concrete cylinders of different concrete strength but otherwise similar mix designs, aggregates, and constituents. This was accomplished by varying only the water-to-cement ratio during concrete mixing operations. Through the use of high-resolution digital image correlation to measure both axial and hoop strains, the observations yield insights into the mechanics of FRP confinement of concretes of similar composition but with varying unconfined concrete compressive strength.

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A method of manufacturing a composite concrete article comprising forming a textile structure, removing material from regions of the textile structure to create voids in the textile structure and incorporating the textile structure into a body of wet uncured concrete such that the concrete flows into the voids created in the textile structure, embedding the textile structure into the concrete, whereby the textile structure defines at least a portion of a surface of the cured concrete article.

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Alkali activated binders, based on ash and slag, also known as geopolymers, can play a key role in reducing the carbon footprint of the construction sector by replacing ordinary Portland cement in some concretes. Since 1970s, research effort has been ongoing in many research institutions. In this study, pulverized fuel ash (pfa) from a UK power plant, ground granulated blast furnace slag (ggbs) and combinations of the two have been investigated as geopolymer binders for concrete applications. Activators used were sodium hydroxide and sodium silicate solutions. Mortars with sand/binder ratio of 2.75 with several pfa and ggbs combinations have been mixed and tested. The optimization of alkali dosage (defined as the Na2O/binder mass ratio) and modulus (defined as the Na2O/SiO2 mass ratio) resulted in strengths in excess of 70 MPa for tested mortars. Setting time and workability have been considered for the identification of the best combination of pfa/ggbs and alkali activator dosage for different precast concrete products. Geopolymer concrete building blocks have been replicated in laboratory and a real scale factory trial has been successfully carried out. Ongoing microstructural characterization is aiming to identify reaction products arising from pfa/ggbs combinations.

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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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Hemp-lime concrete is a sustainable alternative to standard building wall materials, with low associated embodied energy. It exhibits good hygric, acoustic and thermal properties, making it an exciting, sustainable building envelope material. When cast in temporary shuttering around a timber frame, it exhibits lower thermal conductivity than concrete, and consequently achieves low U-values in a primarily mono-material wall construction. Although cast relatively thick hemp-lime walls do not generally achieve the low U-values stipulated in building regulations. However assessment of its thermal performance through evaluation of its resistance to thermal transfer alone, underestimates its true thermal quality. The thermal inertia, or reluctance of the wall to change its temperature when exposed to changing environmental temperatures, also has a significant impact on the thermal quality of the wall, the thermal comfort of the interior space and energy consumption due to space heating. With a focus on energy reduction in buildings, regulations emphasise thermal resistance to heat transfer with only less focus on thermal inertia or storage benefits due to thermal mass. This paper investigates dynamic thermal responsiveness in hemp-lime concrete walls. It reports the influence of thermal conductivity, density and specific heat through analysis of steady state and transient heat transfer, in the walls. A novel hot-box design which isolates the conductive heat flow is used, and compared with tests in standard hot-boxes. Thermal diffusivity and effusivity are evaluated, using experimentally measured conductivity, based on analytical relationships. Experimental results evident that hemp-lime exhibits high thermal inertia. They show the thermal inertia characteristics compensate for any limitations in the thermal resistance of the construction material. When viewed together the thermal resistance and mass characteristics of hemp-lime are appropriate to maintain comfortable thermal indoor conditions and low energy operation.

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Carbonation and chloride ingress are the two main causes of corrosion in reinforced concrete structures. An investigation to monitor the ingress of chlorides and carbonation during a 9 month wetting and drying exposure regime to simulate conditions in which multiple mode transport mechanisms are active was conducted on a variety of binders. The penetration was evaluated using water and acid soluble chloride profiles, and phenolphthalein indicator. X-ray diffraction was also used to determine the presence of bound chlorides and carbonation. The results indicated that acid extraction of chlorides is quantitatively reliable and practical for assessing penetration. The effect of carbonation on binding capability was observed and the relative quantity of chlorides also showed a correlation with the amount of chlorides bound in the form of Friedel’s salt.

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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.

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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.