Degree Type


Date of Award


Degree Name

Doctor of Philosophy


Civil, Construction, and Environmental Engineering

First Advisor

Kejin Wang

Second Advisor

Peter C. Taylor


A well-proportioned self-consolidating concrete (SCC) mixture can be achieved by controlling the aggregate system, paste quality, and paste quantity. The work presented in this dissertation involves an effort to study and improve particle packing of the concrete system and reduce the paste quantity while maintaining concrete quality and performance. This dissertation is composed of four papers resulting from the study: (1) Assessing Particle Packing Based Self-Consolidating Concrete Mix Design; (2) Using Paste-To-Voids Volume Ratio to Evaluate the Performance of Self-Consolidating Concrete Mixtures; (3) Image Analysis Applications on Assessing Static Stability and Flowability of Self-Consolidating Concrete, and (4) Using Ultrasonic Wave Propagation to Monitor Stiffening Process of Self-Consolidating Concrete. Tests were conducted on a large matrix of SCC mixtures that were designed for cast-in-place bridge construction. The mixtures were made with different aggregate types, sizes, and different cementitious materials.

In Paper 1, a modified particle-packing based mix design method, originally proposed by Brouwers (2005), was applied to the design of self-consolidating concrete (SCC) mixs. Using this method, a large matrix of SCC mixes was designed to have a particle distribution modulus (q) ranging from 0.23 to 0.29. Fresh properties (such as flowability, passing ability, segregation resistance, yield stress, viscosity, set time and formwork pressure) and hardened properties (such as compressive strength, surface resistance, shrinkage, and air structure) of these concrete mixes were experimentally evaluated.

In Paper 2, a concept that is based on paste-to-voids volume ratio (Vpaste/Vvoids) was employed to assess the performance of SCC mixtures. The relationship between excess paste theory and Vpaste/Vvoids was investigated. The workability, flow properties, compressive strength, shrinkage, and surface resistivity of SCC mixtures were determined at various ages. Statistical analyses, response surface models and Tukey Honestly Significant Difference (HSD) tests, were conducted to relate the mix design parameters to the concrete performance.

The work discussed in Paper 3 was to apply a digital image processing (DIP) method associated with a MATLAB algorithm to evaluate cross sectional images of self-consolidating concrete (SCC). Parameters, such as inter-particle spacing between coarse aggregate particles and average mortar to aggregate ratio defined as average mortar thickness index (MTI), were derived from DIP method and applied to evaluate the static stability and develop statistical models to predict flowability of SCC mixtures.

The last paper investigated technologies available to monitor changing properties of a fresh mixture, particularly for use with self-consolidating concrete (SCC). A number of techniques were used to monitor setting time, stiffening and formwork pressure of SCC mixtures. These included longitudinal (P-wave) ultrasonic wave propagation, penetrometer based setting time, semi-adiabatic calorimetry, and formwork pressure.

The first study demonstrated that the concrete mixes designed using the modified Brouwers mix design algorithm and particle packing concept had a potential to reduce up to 20% SCMs content compared to existing SCC mix proportioning methods and still maintain good performance. The second paper concluded that slump flow of the SCC mixtures increased with Vpaste/Vvoids at a given viscosity of mortar. Compressive trength increases with increasing Vpaste/Vvoids up to a point (~150%), after which the strength becomes independent of Vpaste/Vvoids, even slightly decreases. Vpaste/Vvoids has little effect on the shrinkage mixtures, while SCC mixtures tend to have a higher shrinkage than CC for a given Vpaste/Vvoids. Vpaste/Vvoids has little effects on surface resistivity of SCC mixtures. The paste quality tends to have a dominant effect. Statistical analysis is an efficient tool to identify the significance of influence factors on concrete performance.

In third paper, proposed DIP method and MATLAB algorithm can be successfully used to derive inter-particle spacing and MTI, and quantitatively evaluate the static stability in hardened SCC samples. These parameters can be applied to overcome the limitations and challenges of existing theoretical frames and construct statistical models associated with rheological parameters to predict flowability of SCC mixtures. The outcome of this study can be of practical value for providing an efficient and useful tool in designing mixture proportions of SCC. Last paper compared several concrete performance measurement techniques, the P-wave test and calorimetric measurements can be efficiently used to monitor the stiffening and setting of SCC mixtures.


Copyright Owner

Xuhao Wang



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199 pages

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Engineering Commons