In this study, a procedure for interpreting impact-echo data in an automated, simple manner for detecting defects in concrete bridge decks is presented. Such a procedure is needed because it can be challenging for inexperienced impact-echo users to correctly distinguish between sound and defective concrete. This data interpretation procedure was developed considering the statistical nature of impact-echo data in a manner to allow impact-echo users of all skill levels to understand and implement the procedure. The developed method predominantly relies on conducting segmented linear regression analysis of the cumulative probabilities of an impact-echo data set to identify frequency thresholds distinguishing sound concrete from defective concrete. The accuracy of this method was validated using two case studies of five slab specimens and a full-scale bridge deck, each containing various typical defects. The developed procedure was found to be able to predict the condition of the slab specimens containing shallow delaminations without human assistance within 3.1 percentage points of the maximum attainable accuracy. It was also able to correctly predict the condition of the full-scale bridge deck containing delaminations, voids, corrosion damage, concrete deterioration, and poorly constructed concrete within 3.5 percentage points of the maximum attainable accuracy.

Concrete mixture design is the foundation of cement and concrete research. Innovations in concrete materials could, should, and would inevitably be incorporated into new mixture designs. Thus, a rigorous method for concrete mixture design can better bridge the research community and the construction industry with high reliability and high fidelity. However, current methods for concrete mixture design vary a lot in the literature, thus compromising the accuracy and consistency in interpreting the properties of concrete subject to changes in its raw ingredients. Moreover, the extraneous variables in controlled experiments are not always controlled well. To solve this old but critical problem, this paper summarizes the prevalent concrete mixture design methods in the literature and in practice. By contrast, the volume-based mixture design method is superior to the mass ratio-based mixture design method in terms of simplicity, accuracy, and consistency. Further discussion on packing density measurement and water or slurry film thickness (SFT) as a basis of volume-based mixture design is elaborated. Mathematically, the hardened properties were linked to the particle packing behavior and fresh properties of concrete. This research contributes to a unified volume-based design method to bridge the research community and the construction industry. In the end, it is conducive to upgrading from concrete technology to science.

This work investigated the effects of substrate surface moisture condition and texture on ultra-high-performance concrete overlay bond strength. This investigation was performed in three parts that studied extreme substrate moisture conditions, partially dried substrate moisture conditions, and surface texture. These studies investigated the effects of substrate surface moisture conditions, from dry to a surface with a thin layer of free moisture, and surface textures that provided various aggregate exposure conditions on overlay bond strength. Direct tension pull-off tests were conducted to assess overlay bond strength. Results for specimens with exposed fine aggregate surface textures showed that visibly moist substrate surfaces facilitated development of excellent bond strengths, and adequate bond was achieved for conditions with a thin layer of free moisture. For specimens with saturated surface-dry conditions, acceptable bond was achieved with a slightly exposed fine aggregate texture and increasing bond strength was observed with increasing aggregate exposure.

Shape memory alloys (SMAs), with their unique ability to undergo large deformations and recover to their initial shapes through the removal of stress without significant residual strain, have become attractive materials in bridge engineering. In this study, nine samples of bridge piers are reinforced by two types of SMA (NiTi and Cu-Al-Mn) in plastic hinge regions where high-performance fiber-reinforced concrete (HPFRC) is additionally used to enhance the ductility of piers. To investigate the effects of SMAs and HPFRC on seismic performance of concrete bridge piers, 28 near-field ground-motion record pairs are selected. Then, the models are analyzed using the incremental dynamic analysis (IDA) method and fragility curves are derived. The results show that using SMAs leads to the reduction of residual drift. Also, using HPFRC increases the capacity of the models. Furthermore, the model with HPFRC and NiTi shows the best performance in terms of capacity and residual drift reduction.

A new mixture proportioning method is developed for performance-based concrete with supplementary cementitious materials (SCMs). The method is based on the thermodynamic calculations of the properties for concrete and identifying the mixtures that satisfy a predefined set of performance criteria. This new approach considers the chemical composition and reactivity of SCMs while proportioning concrete mixtures. Performance criteria examples are shown for a bridge deck (corrosion and freezing-and-thawing damage), an unreinforced pavement (salt damage), and a foundation (moderate sulfate and alkali-aggregate reaction). The method is used to proportion concrete mixtures satisfying these three performance criteria using four ashes per mixture. Experiments show that these mixtures met the targets. The proposed approach can proportion mixtures that are optimized for predefined performance using a wide range of SCMs, which can be useful in reducing the cost and carbon footprint of concrete.