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.

Effect of Free-Fall Height in Water on Performance of Flowable Concrete

Concrete placed under water should be proportioned to flow readily into place with minimum materials separation. Unlike concrete cast for deep tremie seals, the use of concrete in repairs often necessitates some free fall of the mixture through water. Such placement conditions lead to greater risk of water erosion and segregation, and should be addressed in proportioning highly flowable underwater concrete. This paper evaluates the effect of free-fall height (FFH) of concrete through water on resulting in-place properties. Concrete was cast in blocks measuring 0.54 x 0.44 x 1 m with the initial FFH in water ranging between 0.25 and 0.60 m. In-place compressive and splitting tensile strengths, unit weight, and depth of washed-out and sedimentation materials were determined. In total, 24 highly flowable mixtures with slump flows greater than 500 mm were investigated. The evaluated mixtures were prepared with various hydraulic binders, including conventional Type 10 cement, a binary mixture with 10% of silica fume (SF), and a ternary binder incorporating 20% of fly ash (FA) and 6% of SF. The mixtures were proportioned with water-binder ratios (w/b) ranging between 0.41 and 0.47. Test results show that the increase of FFH of fresh concrete in water can greatly decrease the residual strength and significantly increase the thickness of washed out and sedimentation materials. The incorporation of 10% of SF, or 20% of FA and 6% of SF, and the reduction of the w/b from 0.47 to 0.41 can, however, lead to a significant increase in washout resistance and residual strength. A relationship between residual strength and the coupled factor of free-fall drop of concrete in water and washout resistance is established.

Deactivation mechanism of a Au/CeZrO4 catalyst during a low-temperature water gas shift reaction

On-stream deactivation during a water gas shift (WGS) reaction over gold supported on a ceria-zirconia catalyst was examined. Although the fresh catalyst has very high low temperature (<200 degrees C) for WGS activity, a significant loss of CO conversion is found under steady-state operations over hours. This has been shown to be directly related to the concentration of water in the gas phase. The same catalyst also undergoes thermal deactivation above 250 degrees C, and using a combined experimental and theoretical approach, a common deactivation mechanism is proposed. In both cases, the gold nanoparticles, which are found under reaction conditions, are thought to detach from the oxide support either through hydrolysis, <200 degrees C, or thermally, > 200 degrees C. This process reduces the metal-support interaction, which is considered to be critical in determining the high activity of the catalyst.

Modelling the response of fresh groundwater to climate and vegetation changes in coral islands

In coral islands, groundwater is a crucial freshwater resource for terrestrial life, including human water supply. Response of the freshwater lens to expected climate changes and subsequent vegetation alterations is quantified for Grande Glorieuse, a low-lying coral island in the Western Indian Ocean. Distributed models of recharge, evapotranspiration and saltwater phytotoxicity are integrated into a variable-density groundwater model to simulate the evolution of groundwater salinity. Model results are assessed against field observations including groundwater and geophysical measurements. Simulations show the major control currently exerted by the vegetation with regards to the lens morphology and the high sensitivity of the lens to climate alterations, impacting both quantity and salinity. Long-term changes in mean sea level and climatic conditions (rainfall and evapotranspiration) are predicted to be responsible for an average increase in salinity approaching 140 % (+8 kg m-3) when combined. In low-lying areas with high vegetation density, these changes top +300 % (+10 kg m-3). However, due to salinity increase and its phytotoxicity, it is shown that a corollary drop in vegetation activity can buffer the alteration of fresh groundwater. This illustrates the importance of accounting for vegetation dynamics to study groundwater in coral islands.

Effect of Nanosilica on Rheology, Fresh Properties, and Strength of Cement-Based Grouts

The effect of colloidal nanosilica on the fresh and rheological parameters, plastic shrinkage, heat of hydration, and compressive strength of cement-based grouts is investigated in this paper. The fresh and rheological properties were evaluated by the minislump flow, Marsh cone flow time, Lombardi plate cohesion meter, yield value, and plastic viscosity. The key parameters investigated were the dosages of nanosilica and superplasticizer and temperature of mixing water. Statistical models and isoresponse curves were developed to capture the significant trends. The dosage of nanosilica had a significant effect on the results. The increase in the dosage of nanosilica led to increasing the values of flow time, plate cohesion meter, yield stress, plastic viscosity, heat of hydration at 1 day and 3 days, and compressive strength at 1 day, while reducing the minislump, plastic shrinkage up 24 h, and compressive strength at 3, 7, and 28 days. Conversely, the increase in the dosage of superplasticizer led to decreasing the values of flow time, plate cohesion meter, yield stress, plastic viscosity, heat of hydration at 1 day and 3 days, and compressive strength at 1 day, while increasing the minislump, plastic shrinkage, and compressive strength at 3 and 7 days. Increasing the temperature of mixing water led to a notable increase in the results of minislump, flow time, plastic viscosity, heat of hydration at 3 days, and compressive strength at 1 day, while it reduced the plate cohesion, compressive strength at 3, 7, and 28 days. The statistical models developed in this study can facilitate optimizing the mixture proportions of grouts for target performance by reducing the number of trial batches needed.

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.