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.

Space and phase resolved plasma parameters in an industrial dual-frequency capacitively coupled radio-frequency discharge

The dynamics of high energetic electrons (>= 11.7 eV) in a modified industrial confined dual-frequency capacitively coupled RF discharge (Exelan, Lam Research Inc.), operated at 1.937 MHz and 27.118 MHz, is investigated by means of phase resolved optical emission spectroscopy. Operating in a He-O-2. plasma with small rare gas admixtures the emission is measured, with one-dimensional spatial resolution along the discharge axis. Both the low and high frequency RF cycle are resolved. The diagnostic is based on time dependent measurements of the population densities of specifically chosen excited rare gas states. A time dependent model, based on rate equations, describes the dynamics of the population densities of these levels. Based on this model and the comparison of the excitation of various rare gas states, with different excitation thresholds, time and space resolved electron temperature, propagation velocity and qualitative electron density as well as electron energy distribution functions are determined. This information leads to a better understanding of the dual-frequency sheath dynamics and shows, that separate control of ion energy and electron density is limited.

Absolute atomic oxygen density profiles in the discharge core of a microscale atmospheric pressure plasma jet

The micro atmospheric pressure plasma jet is an rf driven (13.56 MHz, ~20 W) capacitively coupled discharge producing a homogeneous plasma at ambient pressure when fed with a gas flow of helium (1.4 slm) containing small admixtures of oxygen (~0.5%). The design provides excellent optical access to the plasma core. Ground state atomic oxygen densities up to 3x1016 cm-3 are measured spatially resolved in the discharge core by absolutely calibrated two-photon absorption laser-induced fluorescence spectroscopy. The atomic oxygen density builds up over the first 8 mm of the discharge channel before saturating at a maximum level. The absolute value increases linearly with applied power.

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.

Casting of Self-Compacting Concrete

Increased productivity and improved working environment have had high priority in the development of concrete construction over the last decade. Development of a material not needing vibration for compaction—i.e. selfcompacting concrete (SCC)—has successfully met the challenge and is now increasingly being used in routine practice. The key to the improvement of fresh concrete performance has been nanoscale tailoring of molecules for surface active admixtures, as well as improved understanding of particle packing and of the role of mineral surfaces in cementitious matrixes. Fundamental studies of rheological behaviour of cementitious particle suspensions were soon expanded to extensive innovation programmes incorporating applied research, site experiments, instrumented full scale applications supporting technology, standards and guides, information efforts as well as training programmes. The major impact of the introduction of SCC is connected to the production process. The choice and handling of constituents are modified as well as mix design, batching, mixing and transporting. The productivity is drastically improved through elimination of vibration compaction and process reorganisation. The working environment is significantly enhanced through avoidance of vibration induced damages, reduced noise and improved safety. Additionally, the technology is improving performance in terms of hardened material properties like surface quality, strength and durability.

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.

Filling Ability and Plastic Settlement of Self-Compacting Concrete

The use of self-compacting concrete (SCC) facilitates the placing of concrete by eliminating the need for compaction by vibration. Given the highly flowable nature of such concrete, care is required to ensure excellent filling ability and adequate stability. This is especially important in deep structural members and wall elements where concrete can block the flow, segregate and exhibit bleeding and settlement which can result in local defects that can reduce mechanical properties, durability and quality of surface finish. This paper shows results of an investigation of fresh properties of self-compacting concrete, such as filling ability measured by slump flow and flow time (measured by Orimet) and plastic fresh settlement measured in a column. The SCC mixes incorporated various combinations of fine inorganic powders and admixtures. The slump flow of all SCCs was greater than 580 mm and the time in which the slumping concrete reached 500 rnm was less than 3 s. The flow time was less than 5 s. The results on SCCs were compared to a control mix. The compressive strength and splitting tensile strength of SCCs were also measured. The effects of water/powder ratio, slump and nature of the sand on the fresh settlement were also evaluated. The volume of coarse aggregate and the dosage of superphsticizer were kept constant. It can be concluded that the settlement of fresh self-compacting concrete increased with the increase in water/powder ratio and slump. The nature of sand influenced the maximum settlement.