885 resultados para Cement and Concrete


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Slurries with high penetrability for production of Self-consolidating Slurry Infiltrated Fiber Concrete (SIFCON) were investigated in this study. Factorial experimental design was adopted in this investigation to assess the combined effects of five independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of superplasticiser (SP) and viscosity agent (VA), and water-to-binder ratio (w/b). A two-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behaviour of fresh cement slurry and compressive strength. The models are valid for mixes with 10 to 50% LSP as replacement of cement, 0.02 to 0.06% VA by mass of cement, 0.6 to 1.2% SP and 50 to 150% sand (% mass of binder) and 0.42 to 0.48 w/b. The influences of LSP, SP, VA, sand and W/B were characterised and analysed using polynomial regression which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding and compressive strength as functions of LSP, SP, VA, sand and w/b. The estimated results of mini-slump, induced bleeding test and compressive strength from the derived models are compared with results obtained from previously proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mix optimization to secure a highly penetration of slurry with low compressive strength

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The removal of water from three Portland cement grouts by pressure filtration is examined, and the consolidation behaviour of the filtered material clarified. The filtration takes place by the laying down of a very stiff filter cake through the removal of excess water. The behaviour due to further loading resembles that of a re-constituted silt. For stress levels above the filtration pressure the calculated permeability values are similar to those from the filtration phase only if the data sampling rate was sufficiently rapid to discriminate the first portion of the observed primary consolidation curve. The change in void ratio for incremental loading is roughly linear with the change in the logarithm of the vertical effective stress. The characterisation of fresh cement paste using standard soil mechanics models is both appropriate and useful, at least during the first few hours after mixing.

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Self-consolidating concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work conditions and also reduce the impact on the environment by elimination of the need for compaction. This investigation aimed at exploring the potential use of the neurofuzzy (NF) approach to model the fresh and hardened properties of SCC containing pulverised fuel ash (PFA) as based on experimental data investigated in this paper. Twenty six mixes were made with water-to-binder ratio ranging from 0.38 to 0.72, cement content ranging from 183 to 317 kg/m3 , dosage of PFA ranging from 29 to 261 kg/m3 , and percentage of superplasticizer, by mass of powder, ranging from 0 to 1%. Nine properties of SCC mixes modeled by NF were the slump flow, JRing combined to the Orimet, JRing combined to cone, V-funnel, L-box blocking ratio, segregation ratio, and the compressive strength at 7, 28, and 90 days. These properties characterized the filling ability, the passing ability, the segregation resistance of fresh SCC, and the compressive strength. NF model is constructed by training and testing data using the experimental results obtained in this study. The results of NF models were compared with experimental results and were found to be quite accurate. The proposed NF models offers useful modeling approach of the fresh and hardened properties of SCC containing PFA.

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Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m3 of cement content, 29–261 kg/m3 of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.

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This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

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Durability of concrete is a great concern to all designers, owners and users of reinforced concrete structures. As a result, more restrictive regulations are being introduced in various Codes of Practice dealing with the design of these structures. Attempts are being made by various researchers to develop performance based specification. For this to be successful standard non destructive tests are required which will be used to assess the durability of concretes. In parallel with this approach, a research team in Queen’s University Belfast, U. K., investigated the effect of different mix parameters on workability, strength and various permeation properties. Furthermore, durability parameters such as freeze-thaw salt scaling resistance and carbonation depth were also investigated. The research was part funded by the Department of Environment, Transport and the Regions (DETR). This paper reports of the findings from this study. The results from this investigation showed that some of the non destructive tests used were reasonably well correlated with carbonation and freeze-thaw salt scaling resistance of CEM I concrete. If the mix parameters such as aggregate-cement ratio or water-cement ratio are known, better correlation can be obtained. Further investigation is required varying other mix parameters including various aggregates, admixtures and air entrainments before the result can be used for developing mix design methods for durable concretes. Also long term site tests are required to validate the results obtained from the accelerated laboratory tests used to study the carbonation resistance and freeze-thaw salt scaling resistance.

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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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Concrete is a universal material in the construction industry. With natural resources like sand and aggregate, fast depleting, it is time to look for alternate materials to substitute these in the process of making concrete. There are instances like exposure to solar radiation, fire, furnaces, and nuclear reactor vessels, special applications like missile launching pads etc., where concrete is exposed to temperature variations In this research work, an attempt has been made to understand the behaviour of concrete when weathered laterite aggregate is used in both conventional and self compacting normal strength concrete. The study has been extended to understand the thermal behaviour of both types of laterised concretes and to check suitability as a fire protection material. A systematic study of laterised concrete considering parameters like source of laterite aggregate, grades of Ordinary Portland Cement (OPC) and types of supplementary cementitious materials (fly ash and GGBFS) has been carried out to arrive at a feasible combination of various ingredients in laterised concrete. A mix design methodology has been proposed for making normal strength laterised self compacting concrete based on trial mixes and the same has also been validated. The physical and mechanical properties of laterised concretes have been studied with respect to different variables like exposure temperature (200°C, 400°C and 600°C) and cooling environment (air cooled and water cooled). The behaviour of ferrocement elements with laterised self compacting concrete has also been studied by varying the cover to mesh reinforcement (10mm to 50mm at an interval of 10mm), exposure temperature and cooling environment.