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Effects of workability modifiers blending on fresh properties of limestone metakaolin blended cement
No full textIt is widely acknowledged that metakaolin in blended cements improves engineering properties and durability. However, it reduces the blend’s fresh flowability and shortens slump retention time. In this investigation, three workability modifiers (WM) were used to fluidize a mixture of ASTM C595 Type IL cement containing 15 wt.% metakaolin, called limestone metakaolin-blended cement (LMC). The study aimed to use WMs and their combinations to curb the workability loss of the LMC system. Dosages of each WM and blends of them for the LMC system were determined in which the LMC reached neat-cement equivalent yield stress and similar flowability and workability retention. Compressive strength and heat of hydration were also studied to evaluate the impacts of the WMs on the LMC system. The results highlighted the possibility of using combinations of WMs to deal with the loss in the rheological performance of calcined clay limestone blended cement
Multicomponent Portland cement composites modified with graphene oxide: hydration and mechanical properties
No full textWe report here on the effect of the addition of graphene oxide on the basic properties of multicomponent Portland cements. Cement mortars incorporating two different dosages of graphene oxide (0.025 wt.% and 0.05 wt.%) were manufactured with the use of Portland cement containing limestone as well as cement containing granulated blast furnace slag, and, for comparison, ordinary Portland cement. We then further investigated the hydration heat by means of semi-adiabatic calorimetry, mechanical properties by means of flexural and compressive strength tests as well as comprehensive microstructural analysis of cement mortars at the age of 28 days, proving a considerable difference in the influence of graphene oxide on the performance of various Portland cements. In contrast to Portland cement type I, the addition of graphene oxide proved to affect negatively the formation of microstructure and mechanical properties of cement mortars made out of multicomponent cements
Computational Modelling of 3D Mesostructure of Recycled Aggregate Concrete
No full textRecycled aggregate concrete (RAC) has a complex mesostructure with heterogeneous compositions of aggregates, interfacial transition zones (ITZs), and mortar. It is still a big challenge to simulate the 3D mesostructure of RAC accounting for its inherent characteristics, which plays a crucial role in its mechanical properties and long-term durability. This study introduces an advanced computational framework based on Voronoi tessellation approach to generate the highly realistic 3D mesostructured of RAC. The proposed framework can address the key challenges in simulating irregular aggregate morphology and spatial distribution while effectively incorporating the multi-phase structure of RAC which consists of old and new aggregates, old and new ITZs, and mortar phases. A hierarchical clustering approach was employed to refine the Voronoi cell segmentation, ensuring precise control over particle size distribution, volume fractions, and morphological characteristics. The integration of geometric scaling and splining techniques was adopted to enhance the model\u27s accuracy, facilitating a more realistic representation of 3D microstructure of RAC. Validation of simulations against experimental data demonstrates strong alignment in particle morphology, particularly in sphericity and roundness indices, confirming the robustness of the computational model. Designed for compatibility with finite element analysis, this modelling framework enables comprehensive investigations into mechanical behaviour, failure mechanism, and mass transport properties. The research provides an essential tool for optimising the mix design of RAC, supporting sustainable construction practices, and improving the durability of recycled concrete structures
Bubbling Effect of Air-entraining Agents in NaOH-activated Slag
No full textSurfactants, particularly air-entraining agents (AEAs), significantly influence the pore structure of concrete, thereby determining its durability performance, in which their role in alkali-activated slag (AAS) materials remains unclear. This study systematically investigated the foaming behaviour, rheological properties, and pore structure effects of four typical AEAs, in terms of alpha-olefin sulfonate (AOS), didecyldimethylammonium chloride (DDAC), disodium lauroamphodiacetate (DSLA), decyl glucoside (DG), the representive anionic, cationic, amphoteric and non-ionic AEAs, in NaOH-activated slag systems. Results indicated that AOS exhibited the strongest foaming capability, while DSLA demonstrated excellent foam stability across various environments. AEAs notably enhanced paste fluidity; a 1.5% DSLA dosage increased fluidity to 227.5 mm and effectively reduced yield stress and plastic viscosity. However, DSLA and DG systems experienced bubble coalescence and delayed setting, whereas AOS maintained balanced bubble characteristics and suitable setting times. All AEAs reduced compressive strength, which further decreased with higher dosages. XCT further confirmed the crucial impact of pore characteristics on strength
Chloride Transport in Low Clinker Content Concretes and Modeling
No full textChloride ion transport behaviour has been reported to be significantly influenced by the use of supplementary cementing materials in concrete, both due to physical effects such as pore structure refinement and chemical effects including chloride binding. This paper provides experimental results on diffusion of chloride ions through concretes containing limestone calcined clay as a cement replacement material at ~50% replacement level, demonstrating the beneficial effects of high-volume replacement of cement with calcined clay. A numerical simulation framework that considers the pore structure of concrete, the concentration-dependence of diffusion coefficient, and Freundlich binding is also presented. The diffusion model is augmented with a scalar isotropic damage variable that accounts for random distribution of microcracks under fatigue loading (e.g., in a bridge deck). The modeling approach can be used to evaluate the influence of binder composition and damage on effective service life of chloride-exposed concrete structures, thereby aiding in binder selection
Machine Learning Based Analysis of Industrially Produced Concrete
No full textMachine learning (ML) has proven effective for predicting the compressive strength of laboratory-produced concrete, but industrially produced concrete exhibits greater variability and uncertainty, and remains less studied. This work analyses a dataset of 2,617 industrial concrete samples from a UK ready-mix supplier, spanning a full year of supply and demand. The study evaluates the impact of both mix proportions and categorical features—including cement type, admixture type, and mix specification—on model accuracy. A holistic model incorporating all curing ages outperforms single-age models, and the inclusion of categorical features, particularly mix specification, significantly enhances predictive performance. Five ML models were considered: CatBoost, LightGBM, Gradient Boosting, XGBoost, and Random Forest, with XGBoost achieving the highest performance (R2 of 0.75, R of 0.86) on the test data for the holistic model
Internal Tendon Damage Monitoring Technology of Prestressed Concrete Bridge using Acoustic Emission Method
No full textVarious non-destructive testing techniques are being applied for tendon maintenance and safety management of prestressed concrete (PSC) bridges, which became a social issue after the rupture of the external tension member of the Jeongneungcheon Viaduct in Seoul in 2016. Acoustic emission (AE) is one of the most effective non-destructive evaluation (NDE) methods for structural health monitoring (SHM) of large-scale infrastructure. It enables real-time monitoring of concrete cracks and damage to embedded rebar without causing structural failure. It is particularly suitable for detecting cracks in the tendons of PSC bridges. PSC bridges are structurally categorised into internal and external tendon systems based on how they are prestressed. While external tendons can be inspected through visual or acoustic methods, internal tendons are much more difficult to detect defects because they are embedded within the concrete. This research aims to develop an AE-based technique to detect fracture signals in internal tendons of PSC bridges, and to establish maintenance guidelines for safety inspection and field application. To this end, various simulated fracture tests are performed to build a database of AE signals related to tendon fracture. In addition, field experiments are conducted to evaluate the feasibility of real-world implementation. Based on the results of these field validation tests, maintenance guidelines for the AE-based monitoring of internal tendon fractures in PSC bridges are proposed
Investigation of Capillary Pressure Evolution and Early-Age Shrinkage in Concrete Using a High-Capacity Tensiometer
No full textShrinkage-induced cracking is a critical durability concern in concrete structures, particularly those with low volume-to-surface ratios, leading to increased maintenance costs and reduced service life. Early-age concrete is especially vulnerable to shrinkage cracking due to its limited strength development. Capillary pressure is a primary driver of early-age shrinkage; however, conventional measurement techniques are limited to pressures below 100 kPa and durations of approximately seven hours post-casting, restricting a comprehensive understanding of capillary pressure evolution and its correlation with shrinkage and cracking potential. This study utilises a novel high-capacity tensiometer (HCT) capable of measuring capillary pressures up to 2000 kPa, significantly extending the measurement range. The relationship between capillary pressure evolution and early-age shrinkage was investigated across different concrete mixtures, including a control mix, a mix incorporating ground granulated blast-furnace slag (GGBS), and shrinkage-reducing admixture (SRA). Additionally, experimentally measured early-age shrinkage values were compared with theoretical predictions based on the Gauss-Laplace equation and elasticity theory. A comprehensive experimental program was conducted, encompassing setting time determination, capillary pressure monitoring, early-age shrinkage measurement, and elastic modulus evaluation. The findings indicate that substantial shrinkage occurs during the initial and final setting phases while the concrete remains in a semi-plastic state, with minimal capillary pressure evolution. A notable discrepancy was observed between experimentally measured shrinkage values and theoretical predictions immediately after the final setting time across all mixtures. This divergence is attributed to the nonlinear stress-strain behaviour of concrete in the semi-plastic phase. However, as the concrete transitions to a hardened state, the experimental and theoretical shrinkage values converge, demonstrating the improved predictive accuracy of the model in later stages. These insights contribute to a deeper understanding of early-age shrinkage behaviour and provide a basis for optimizing mix designs to mitigate shrinkage-induced cracking in concrete structures
Field Test and Evaluation of A Smart Sprayer for Precision Weeding
No full textWeeds remain a major biological threat to agriculture, reducing crop yields and causing substantial economic losses. Conventional blanket herbicide applications are costly, environmentally damaging, and accelerate the evolution of herbicide resistance. Machine vision–based precision weeding offers a sustainable alternative by enabling site-specific weed localization and removal. This study advances plant perception through YOLOv10 detection models and leverages a 1-cm nozzle array to achieve precise weed targeting that maximizes treatment efficacy while minimizing crop contact. A dedicated weed–crop dataset curated from vegetable fields further enhances model performance. Field testing was conducted in a lettuce field, and it achieved an average 80.0% mAP@50 in plant detection, and an 84.5% weed hit rate, with a moderate crop hit rate of 17.6% in real fields. The system also reached a high weed precision of 90.3% and low crop/soil precision of 7.9% and 15.7%, respectively. These results demonstrate the effectiveness of integrating an AI-driven perception system with a high-precision sprayer
2025 Standard-sized Seedless Watermelon Cultivar Evaluation in Indiana
No full textIndiana ranked fifth in watermelon production in the United States. In 2024, Indiana growers planted approximately 8,100 acres of watermelons. Watermelon cultivar evaluation trials have been conducted annually at the Southwest Purdue Agricultural Center (SWPAC) in Vincennes, IN, for over 30 years. In 2025, 25 standard-sized seedless watermelons were evaluated, and yield and fruit quality parameters were assessed