Monitoring electrical resistance of concretes containing alternative cementitious materials to assess their resistance to chloride penetration

This is an invited contribution in a special issue of the Journal of Cement and Concrete Composites

'PERMIT' ion migration test for measuring the chloride ion transport of concrete on site

The ingress of chlorides into concrete is predominantly by the mechanism of diffusion and the resistance of concrete to the transport of chlorides is generally represented by its coefficient of diffusion. The determination of this coefficient normally requires long test duration (many months). Therefore, rapid test methods based on the electrical migration of ions have widely been used. The current procedure of chloride ion migration tests involves placing a concrete disc between an ion source solution and a neutral solution and accelerating the transport of ions from the source solution to the neutral solution by the application of a potential difference across the concrete disc. This means that, in order to determine the chloride transport resistance of concrete cover, cores should be extracted from the structure and tested in laboratories. In an attempt to facilitate testing of the concrete cover on site, an in situ ion migration test (hereafter referred to as PERMIT ion migration test for the unique identification of the new test) was developed. The PERMIT ion migration test was validated in the lab by carrying out a comparative investigation and correlating the results with the migration coefficient from the one-dimensional chloride migration test, the effective diffusion coefficient from the normal diffusion test and the apparent diffusion coefficient determined from chloride profiles. A range of concrete mixes made with ordinary Portland cement was used for this purpose. In addition, the effects of preferential flow of ions close to the concrete surface and the proximity of reinforcement within the test area on the in situ migration coefficients were investigated. It was observed that the in situ migration index, found in one working day, correlated well with the chloride diffusion coefficients from other tests. The quality of the surface layer of the cover concrete and the location of the reinforcement within the test area were found to affect the flow of ions through the concrete during the test. Based on the data, a procedure to carry out the PERMIT ion migration test was standardised.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

Full-Scale Marine Exposure Tests on Treated and Untreated Concretes Initial 7-Year Results

An extensive chloride profiling program was undertaken on concrete pier stems erected in the vicinity of the Dornoch Bridge located at the Dornoch Firth in Northeast Scotland. The pier stems were 2 m (6.562 ft) high and octagonal in plan with 0.66 m (2.165 ft) wide faces. The piers were constructed in sets of three with the lowest of each set in the tidal zone and the highest in the atmospheric zone. The pier stems were placed in such a way that they would represent the exposure conditions of the actual bridge piers of the Dornoch Bridge. In all, six of the pier stems were made using plain ordinary portland cement (OPC) concrete (with three of these having the surface treated with silane); the remaining three pier stems had a concrete containing caltite as an additive. Three exposurezones were studied: the tidal zone, the splash zone, and the atmospheric zone. The tidal zone was further subdivided into two levels defined as low-level and high-level. Chloride profiles were obtained from the different regimes over a period of 7 years for all nine pier stems. This paper describes the nature of chloride ingress and the usefulness of diffusion parameters in classifying each exposure regimes. Furthermore, the effectiveness of silane and caltite in protecting concrete from chloride ingress in different exposure zones was studied.

Incorporation of multiwalled carbon nanotubes to acrylic based bone cements: Effects on mechanical and thermal properties

Polymethyl methacrylate (PMMA) bone cement–multiwalled carbon nanotube (MWCNT) nanocomposites with a weight loading of 0.1% were prepared using 3 different methods of MWCNT incorporation. The mechanical and thermal properties of the resultant nanocomposite cements were characterised in accordance with the international standard for acrylic resin cements. The mechanical properties of the resultant nanocomposite cements were influenced by the type of MWCNT and method of incorporation used. The exothermic polymerisation reaction for the PMMA bone cement was significantly reduced when thermally conductive functionalised MWCNTs were added. This reduction in exotherm translated in a decrease in thermal necrosis index value of the respective nanocomposite cements, which potentially could reduce the hyperthermia experienced in vivo. The morphology and degree of dispersion of the MWCNTs in the PMMA matrix at different scales were analysed using scanning electron microscopy. Improvements in mechanical properties were attributed to the MWCNTs arresting/retarding crack propagation through the cement by providing a bridging effect into the wake of the crack, normal to the direction of crack growth. MWCNT agglomerations were evident within the cement microstructure, the degree of these agglomerations was dependent on the method used to incorporate the MWCNTs into the cement.

Liquid marble formation using hydrophobic powders

This work aims to investigate and quantitatively measure “liquid marble” phenomena using hydrophobic powders (granules). The hydrophobic powders based on a copper substrate were prepared by a silver deposition technique of particle sizes 9 µm, 20 µm and 320 µm and of contact angle with water approaching 160°. The hydrophobic powder poly-methylmethacralate (PMMA) particle size 42 µm and contact angle of 120° was also used to determine the effect of powder density on liquid marble stability. The experimental investigations indicated that for successful formation of liquid marbles a number of variables in addition to hydrophobicity need to be considered, namely: powder density; powder particle size; powder shape; liquid marble formation technique. It was found that liquid marbles were formed using all four powders to varying extents, with a low powder particle size forming more stable liquid marbles. In a series of gravimetric tests, adhered powder mass on liquid marbles was found to be directly proportional to the water droplet surface area. A more complete coverage of the water drops were found with PMMA powder than the hydrophobic granules. Moreover, a further procedure was developed to increase the mechanical strength of the liquid marble, by polymerising methylmethacrylate (MMA) on the surface of a PMMA powder – liquid marble, with the aim of maintaining water within a more robust PMMA – liquid marble shell. This technique may prove to be a novel way of encapsulating drug compounds, such as gentamicin sulphate, for PMMA bone cement.

Prediction of Fresh and Hardened Properties of Self-Consolidating Concrete Using Neurofuzzy Approach

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.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

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.

Transport Properties of Self-Consolidating Concrete

The permeability of concrete is influenced by the porosity and the interconnectivity of the pores in the cement paste and the microcracks in concrete, especially in the interface of paste-aggregate. The movements of gases, liquids, and ions through concrete is important because of their interactions with concrete constituents, including pore water, which can alter the integrity of concrete directly and indirectly, leading to the deterioration of structures. This study reports the findings from an investigation carried out to study the effect of the mixture variations on the durability of medium- and high-strength self-consolidating concrete (SCC). The mixture variations studied include the type of mineral admixtures, such as limestone powder (LSP) and pulverized fuel ash (PFA), and viscositymodifying admixtures (VMA) for both medium- and high-strength SCC. Air permeability, water permeability, capillary absorption, and chloride diffusivity were used to assess the durability of SCC mixtures in comparison with normal, vibrated concretes. The results showed that SCC mixtures, for medium- and high-strength grades using PFA followed by LSP, have lower permeability properties compared with normal concretes. SCC made with VMA had a higher sorptivity, air permeability, and water permeability compared with other SCC mixtures, which can be attributed to higher watercement ratio (w/c) and lack of pore filling effect. An in-place migration coefficient was obtained using the in-place ion migration test. This was used to compare the potential diffusivity of different concretes. The results indicated that SCC, for both grades of strength, made with PFA showed much lower diffusivity values in comparison with other mixtures, whereas the SCC mixtures with VMA showed higher diffusivity.

Assessment of Self-Compacting Concrete Immersed in Acidic Solutions

Ettringite and thaumasite can be found among the deterioration products of cementitious materials exposed to sulfate and hydrochloric attack. The results of a test program to investigate the acid resistance of self-compacting concrete (SCC) and conventional concrete (CC), immersed up to 18 weeks at 20°C in sulfuric and hydrochloric acid solutions, are described. The SCC was prepared with 47% carboniferous limestone powder, as a replacement for cement, and an ordinary portland cement. The CC was prepared with portland cement only. The water-binder ratios of the SCC and CC were 0.36 and 0.46, respectively. The parameter investigated was the time, in weeks, taken to cause 10% mass loss of fully immersed concrete specimens in a 1% solution of sulfuric acid and the same amount of loss in a 1% solution of hydrochloric acid. The investigation indicated that the SCC performed better than the CC in sulfuric solution but was slightly more vulnerable to hydrochloric acid attack compared to CC. The mode of attack between the two solutions was different.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

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.