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Static Compressive Behaviour of a Novel Functionally Graded 3D Re-entrant Lattice Reinforced High Performance Concrete
No full textThis study systematically studies the static mechanical properties of high-performance concrete (HPC) reinforced with a 3D re-entrant lattice structure, considering the effect of functionally gradient design. The uniform 3D re-entrant lattice (U) and the corresponding vertically positively and negatively graded lattices (FG1 and FG2) were designed and manufactured with 3D printing. The plain HPC (P-HPC) and HPC reinforced with U (U-HPC), FG1 (G1-HPC) and FG2 (G2-HPC) were fabricated accordingly. Static compressive tests were then conducted to investigate the static compressive behaviour of 3D re-entrant lattice and corresponding lattice reinforced HPC. Results indicate that all 3D re-entrant structures exhibit clear NPR effects under loading. The elastic modulus, yield strength, first peak stress of the FG1 and FG2 specimens under static compression are around 9.5-30.0%, 47.8-56.5%, and 43.3-47.9% lower than that of the uniform structures (U), respectively, while the energy absorption of FG1 and FG2 up to densification is about 26.7% and 19.2% respectively higher than that of U. The static compressive strength of HPC specimens is slightly improved owing to re-entrant lattice reinforcement, while the static dissipated energy of P-HPC is 55.7%, 53.2% and 57.5% lower than that of U-HPC, G1-HPC and G2-HPC, respectively
Experimental Study on Freeze–Thaw Cycles Response in Mortar under Controlled Partially Saturated Conditions
No full textFreeze–thaw cycle (FTC) deterioration is one of the major durability concerns for concrete structures in cold climates. While many studies focus on fully saturated conditions, real structures often undergo FTCs under unsaturated conditions, where damage mechanisms are not well understood. This study investigates FTC damage in mortar under controlled unsaturated conditions to improve understanding of moisture-driven deterioration. Mortar specimens with water-to-cement (W/C) ratios of 0.50 and 0.75 were cast in thin specimens (100 mm × 100 mm × 10 mm) to promote rapid thermal response and enhance moisture redistribution, allowing for early detection of expansion. Specimens were preconditioned to specific degrees of saturation derived from preliminary simulations, and hermetically sealed to prevent moisture loss. Expansion and temperature were continuously monitored during FTCs using embedded mould gauges. Mercury intrusion porosimetry and image analysis were conducted to evaluate porosity, pore size distribution, and air content. Results indicate that both the degree of saturation and W/C ratio affect FTC damage under unsaturated conditions. In all samples, expansion increased with saturation. At 84% saturation, small but measurable expansion was observed, which increased progressively to 97% saturation. The fully saturated specimens exhibited the highest expansion, reaching approximately 600 and 950 μm for the 0.50 and 0.75 W/C mortars, respectively. Mortars with a 0.75 W/C ratio exhibited earlier and more severe expansion than those with a 0.50 W/C ratio. These findings suggest that FTC deterioration can begin well below full saturation due to ice formation in capillary pores. Therefore, durability assessments should consider unsaturated conditions to reflect in-service performance more accurately
Comparison of Mechanical and Durability Properties of Concretes Containing Copper Heap Leach Residue
No full textThis paper presents comparative properties of concretes containing washed and un-washed copper heap leach residue (CHLR) as partial replacement of natural aggregates at 25 to 75%. The mechanical and durability properties of the concrete are evaluated with unwashed saturated surface dried (SSD) CHLR and these properties are compared with the 60 min rigorously washed-SSD CHLR concretes. The mechanical properties of control concrete containing natural aggregates showed 46.7 MPa of compressive strength, 3.61 MPa of indirect tensile strength, and 4.80 MPa of flexural strength at 28 days, while the durability properties of the specimen indicated 450 μɛ of drying shrinkage, 5.8% of volume of permeable voids, and 3x10-3 mm/sec0.5 of primary sorptivity at 90 days. The relative values of mechanical properties for unwashed 50% CHLR concretes were decreased by 21%, 21%, and 25%, while the relative values of durability properties were increased by 102%, 157%, and 183%, respectively. Nonetheless, the mechanical properties of washed 50% CHLR CA concrete specimen were decreased by -1.3%, 2.5%, and 27% compared to the control, however, the relative values of the durability properties of the specimen were increased by 47%, 41%, and 80%. Therefore, a 60 min rigorously washed CHLR graded CA reduced silt-clay, weak particles, highly soluble reactive ions and a 50% incorporation of these aggregates provided better mechanical and durability performance compared to the unwashed CHLR at the same replacement
Impact of Systematic Classification and Identification of Treatment Methods of Mine Tailings on Concrete Durability
No full textThe rapid increase in mine tailings generation poses significant environmental challenges, with current disposal methods often unsustainable and leading to catastrophic failures such as tailing pond collapses or toxic slurry spills, resulting in fatalities and severe environmental damage. The urgency for sustainable construction materials is clear, particularly as the global focus shifts toward net-zero emissions and circular economies. Concrete, a primary construction material, traditionally depends on natural resources, making it imperative to explore alternatives that reduce environmental impacts. Mine tailings, with their rich elemental and oxide composition, present a promising option for partial replacement in concrete. Despite this potential, the mechanisms enabling the effective use of tailings remain unclear due to a lack of systematic classification and treatment methods. Literature shows that the chemical and mineral diversity of tailings, coupled with the absence of standardized protocols, has limited their commercial use, unlike established pozzolans. Treatment methods such as mechanical, thermal, and chemical activation are often applied without a clear understanding of underlying mechanisms, resulting in inconsistent outcomes. This study aims to classify mine tailings and investigate how proper treatments affect concrete durability. Through literature review and database analysis, the research evaluates how tailing properties and treatments influence durability. Findings show that appropriate classification and treatment are essential to improving performance, enabling more sustainable construction practices and supporting the circular economy. This work highlights the importance of standardizing treatment approaches and systematically exploring the potential of mine tailings in concrete, advancing environmental sustainability and long-term material viability
Life Cycle Assessment of Semi-Submerged Offshore Wind Turbines’ Foundation Materials: Concrete versus Steel
No full textThe offshore wind-generation energy sector in Australia has been growing steadily in lieu of non-renewable energy sources, towards addressing national calls for greenhouse gas emission reductions. However, the industry in Australia is still somewhat fledgling, hence localised studies on environmental impact are scarce. In this context, the work here analyses greenhouse gas emissions by comparing like-for-like steel versus concrete materials as the main components in the foundation element of an offshore wind turbine throughout its lifecycle, using an adapted Life Cycle Assessment (LCA) method. This paper details a cradle-to-cradle LCA of the two alternative specifications for semi-submerged foundations supporting a 15MW power-rated wind-turbine, one made predominately of concrete and the other made predominately of steel, intended to be installed 100km off-the-coast of Bunbury, Western Australia. The functional unit here is the delivery of 1 kWh of electricity to the onshore grid across an initial 25-year lifetime. The estimated carbon intensity for the concrete foundation was calculated explicitly at 32g CO2-eq/kWh, whilst the steel foundation was pegged at 27g CO2-eq/kWh. Despite the concrete foundation having a greater impact on global warming, it is noted here that every kilogram of steel records higher overarching impacts than every kilogram of concrete. This work presents end-of-life scenarios for residual recycling of materials for combinations of steel and concrete, in light of the 10,000-year return-period for engineering and risk used in standards like ISO 19900
Effect of using Recycled Returned Concrete Aggregate on the Strength and Durability Aspects of Concrete
No full textA considerable amount of concrete is returned from construction sites due to various reasons such as excess quantity remaining after casting, not meeting the site specifications and cancellation of orders. In this study, the hardened returned concrete was crushed and used as recycled aggregate to produce new concrete. However, due to young age and inadequate compaction, the properties crushed returned concrete aggregate (CRCA) are different from those of commonly used recycled aggregates obtained from construction and demolition wastes. CRCA was used as 50% and 100% replacements of natural coarse aggregate (NCA). The effect of CRCA was evaluated by workability, strengths, shrinkage and water penetration under pressure. Decreases of 28 days compressive strength by 10% and 30% were observed in 50% and 100% CRCA concrete mixtures compared to 39 MPa for the control. The correlation between splitting tensile strengths and compressive strengths were found to be the same as that for NCA concrete. At 28 days, the water penetration depth increased by 33% and 67%, water absorption increased by 9% and 52%, and the drying shrinkage increased by 16% and 49% in the 50% and 100% CRCA concretes, respectively. The declines in strength and durability aspects are attributed to the adhered porous mortar and fines content of CRCA. Overall, the results show that CRCA could be used to replace natural aggregates by a substantial percentage helping conservation of natural resources
Optical Fibre Raman Spectroscopy: A Potential Novel Sensor System for Monitoring the Durability of Concrete Structure
No full textConcrete during its service lifetime, is exposed to and also interacts with the environment (such as CO2, SO42- & Cl-), which would trigger deterioration mechanisms and subsequent durability degradation. Recent decades have witnessed an increased worldwide interest in the development and application of built-in sensor networks for the purpose of continuous Structural Health Monitoring (SHM) of concrete structures. However, the existing sensors face some challenges such as the limited long-term stability and impossibility of recalibration of some optical fibre sensors. Raman spectroscopy is a vibrational technique, demonstrating unique advantages of ‘spectroscopic fingerprint’, fast response and nondestructive nature. During the past more than 10 years, the authors have been taking the initiative to explore the potential of developing a Raman spectroscopy based optical fibre sensor system for monitoring and assessing the concrete durability on site. Two bespoke optical fibre Raman systems have been successively established, which are capable of monitoring cement chemistry and concrete durability. Furthermore, built upon the success from Portland cement-based systems, the authors have also recently extended the work to novel low-carbon cementitious materials. The minerals of the cutting edge Sulphosilicate cement, and the hydration products, especially the unique carbonation behaviour, of magnesium phosphate cement (MPC), have been systematically investigated, which has shown a great potential for recognising the hydration and carbonation mechanisms of low-carbon cementitious materials. Based on the results obtained so far, the potential of developing a Raman spectroscopy based optical fibre system for monitoring the durability of concrete structure is fully verified
“I (Still) Need Help on Many Things”: A Writing Center Replication Study of First-Generation College Students’ Writing Challenges and Cultural Capital
No full textResearch has increasingly addressed first-generation (FG) students both in and outside the center (Baelemian & Feng, 2013; Bond, 2019; Denny et al., 2018; Ward et al., 2012), but there remains a need to address this unique student population from the perspective of critical theory. In a replication study of Bond’s 2019 “‘I Need Help on Many Things, Please’: A Case Study Analysis of First-Generation College Students’ Use of the Writing Center,” we examined the needs and perceptions of self-reported FG students in a writing center at a large, regional, public R2 university in the Midwest. We gathered preexisting digital data from WCOnline, consultants’ postsession notes, and our office of institutional research. Using thematic analysis, we coded, categorized, and compared FG college student and non-first- generation student data to better understand their unique needs. Thereafter, we corroborated our qualitative findings using quantitative analyses, specifically the Pearson chi-square test. Situated within the framework of cultural community wealth, our findings illustrate that FG students bring their own forms of cultural capital to the academy, challenging prior deficit-oriented narratives (Bourdieu & Passeron, 1977; Yosso, 2005). Our study can be used to better address the academic needs of FG college students and to extend replicable, aggregable, and data-driven (RAD) writing center research (Driscoll & Wynn Perdue, 2012; Haswell, 2005) into conversations of justice, equity, and inclusion
Geospatial Modeling of Spatiotemporal Variability in Farm-Scale Soil Organic Matter Dynamics
No full textSoil organic matter (SOM) is a key indicator of soil health, which is vital for maintaining future crops and income. Furthering our understanding of long-term variability in SOM and digital soil mapping methods of SOM will help farmers make management decisions supporting stable yields. While SOM dynamics have been studied in some regional-scale and plot-level studies, their spatiotemporal variability at farm scale is largely unstudied. In this research, we used geospatial models to identify and interpret long-term trends (2015-2024) in SOM at farm scale using the Purdue University research farm in West Lafayette, Indiana as a case study. Our SOM model input data included 2021-2022 soil sample data (mean 3.7% OM), satellite-derived soil and vegetation indices such as Bare Soil Index, topographic derivatives such as slope, and USDA NRCS soil survey data such as percent clay content. Preliminary analysis suggests that of the models tested, including Random Forest, Extreme Gradient Boosting, and kriging with external drift, Extreme Gradient Boosting performs the best for predicting SOM, with a concordance correlation coefficient (CCC) of 0.70, coefficient of determination (R2) of 0.54, and root mean square error (RMSE) of 0.73. Preliminary analysis also shows that the majority of the research farm area had -25% to 25% change in SOM levels over the study period. Future analysis will include the Mann-Kendall Test and other trend analyses to quantify the spatiotemporal trends in SOM across the farm. Findings from our analysis will inform critical management decisions in increasingly variable farming conditions
PREDICTING SOIL HEALTH PARAMETERS AT FIELD SCALE USING GEOSPATIAL ANALYTICS
No full textResilient agricultural practices are crucial for the sustainability of agroecosystems, crop productivity, and biodiversity conservation. In Fall 2023, research sites were established at Purdue Agricultural Centers across Indiana to compare conventional and resilient agricultural practices (e.g., cover cropping and no-tillage) for long-term changes in soil health, biodiversity, and crop yield. This research conducted baseline soil health assessments at four of these experimental sites using predictive digital soil mapping. In Fall 2024, we collected soil samples using a 25 x 25 m grid from all four sites at depths of 0–7.5 cm and 7.5–15 cm. We also produced a geodatabase that includes a LiDAR-derived digital elevation model, time-series Sentinel-2 satellite images, and soil survey variables. Soil, vegetation indices, and terrain variables were generated using this extensive geodatabase to predict maps of multiple soil health parameters, such as soil organic matter, pH, cation exchange capacity (CEC), nitrogen, phosphorus, and potassium. We employed machine learning models (Random Forest, Extreme Gradient Boosting, Gradient Boosting Machine) along with geostatistical models (Kriging with external drift and Regression Kriging) to predict different soil properties. Our preliminary analysis focused on soil organic matter, where geostatistical models, especially Regression Kriging, showed the most consistently accurate performance across sites (e.g., ACRE RK R² = 0.68, CCC = 0.805). Accuracy generally declined with depth, most significantly at SEPAC and DPAC (e.g., SEPAC RK R² dropped from 0.60 at 0–7.5 cm to 0.31 at 7.5–15 cm; DPAC XGB declined from 0.62 to 0.39), while ACRE remained stable across depths (e.g., KED R² 0.72 → 0.74). We also identified that topographic indices (e.g., valley bottom flatness, elevation) and early-season satellite image indices (e.g., NDVI, Soil Brightness Index) were among the strongest predictors