Challenge Journal Publications (TULPAR Academic Publishing)
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Utilization of expired cement and aged roof tile powder in the production of sustainable geopolymer: Mechanical and physical properties
Full text linkThis study deals with the production of geopolymer mortar in order to promote the recycling of waste materials as sustainable building materials. The use of waste materials such as expired cement and aged roof tiles powders in cementitious systems is of great importance in terms of increasing environmental sustainability and reducing industrial waste. Recycling these materials and using them as alternative binders contributes to more environmentally friendly and economical concrete and mortar production by reducing natural resource consumption. Expired cement and aged roof tile powder were used as binder materials and mortar specimens were produced by activating these materials with alkalis such as NaOH and Na2SiO3 at different ratios. Within the scope of the experimental studies, mechanical and physical properties such as unit weight, ultrasonic pulse velocity, compressive strength and bending strength were investigated in detail. The results showed that the expired cement specimens performed better especially in unit weight, ultrasonic pulse velocity and compressive strength tests, while the roof tile powder had superior properties in terms of bending strength. It was also found that the specimens activated with sodium hydroxide (NaOH) exhibited generally higher strength and performance than those activated with sodium silicate (Na2SiO3). These findings prove that waste materials such as both expired cement and roof tile powder can be valuable alternatives in the construction industry in terms of sustainability and waste management and reveal the potential of using these materials in geopolymer mortar production
Exploring deflection challenges: A case study on the influence of heavy concrete weight on profiled steel deck slabs
Full text linkThis paper presents a case study of a deflection challenge in a profiled steel deck slab subjected to heavy concrete loads, as observed during a field investigation. In recent decades, such slabs have gained popularity in both the construction and industrial sectors due to advantages such as being lightweight, cost-effective, quick to install, and capable of resisting natural disasters. However, field observations indicate that when these slabs are subjected to heavy concrete weight, they may experience significant deflection, raising concerns about long-term performance, durability, and serviceability. Excessive deflection can lead to cracking, reduced structural stability, and increased maintenance costs. It is therefore critical to understand the factors influencing deflection by examining key parameters such as material properties, slab geometry, reinforcement detailing, and load distribution characteristics. This study provides a comprehensive assessment of the structural response of such slabs. Field observations suggest that optimizing the L-angle section and C-channel section in areas where the concrete width increases can effectively reduce structural deflection. This approach helps structural elements resist excessive flexural behavior, and when combined with the use of lightweight materials, offers an innovative structural solution that highlights the importance of modern construction practices
Design of reactive powder concrete mortar mixes through high strength and durability
Full text linkThis research investigates the characteristics of reactive powder concrete (RPC) through comprehensive analysis. The primary methodology involved evaluating both fresh (uncured) and hardened RPC specimens. The initial phase incorporated silica fume (SF) as a cement replacement at concentrations of 5, 10, 15, 20, and 25%, fly ash (FA) substitution at levels of 5, 10, 20, 25, and 30% of the cement content, plus binary combinations where SF constituted 10% cement replacement while FA proportions ranged from 10 to 30%. Material behavior was assessed through slump flow testing procedures. Hardened concrete evaluation encompassed dry density measurements, compressive strength analysis conducted at 7, 28, 56, and 90-day intervals, along with tensile splitting strength and flexural strength determination at 28 days. Results demonstrate that FA substitution alone provides superior workability compared to SF+FA combinations and pure SF, whereas SF replacement individually exhibits enhanced compressive, tensile splitting, and flexural strength performance relative to standalone FA and binary SF+FA mixtures. The subsequent investigation phase examined the influence of nano-silica (NS) on fresh and hardened RPC characteristics. NS replaced cement at 1, 2, 3, 4, and 5% levels, combined with 10% SF and 20% FA. Findings revealed that increased NS content diminishes workability due to elevated water demand for hydration and mixing processes as particle fineness increases. Regarding hardened properties, the optimal composition comprises 10% SF, 20% FA, and 3% NS, attributed to NS’s effective interaction with calcium hydroxide generated during cement hydration, which facilitates additional C-S-H formation through enhanced pozzolanic reactions. This mechanism results in improved mixture performance and strength development
Compressive strength and fire resistance of mortar containing spent garnet as partial sand replacement
Full text linkThe increasing demand for sand in construction, driven by rapid urbanization, has led to unsustainable sand mining and significant environmental degradation. This study addresses the urgent need for sustainable alternatives by investigating the use of spent garnet, a waste by-product from abrasive blasting, as a partial replacement for fine aggregate in mortar. Despite its widespread disposal in landfills, spent garnet has potential as a viable substitute due to its high bulk density and angular particle structure. This research explores the effects of substituting sand with spent garnet at 10%, 20%, 30%, and 40% replacement levels. The novelty of this study lies in its integrated evaluation of workability, mechanical strength, and thermal resistance of mortar incorporating spent garnet. Results from flow table tests showed a progressive increase in flowability, with the 40% garnet mix achieving a maximum flow of 142%, compared to 68.3% for the control mix. Density increased from 4958 kg/m³ (0% garnet) to 5180 kg/m³ (40% garnet), enhancing packing efficiency. The highest compressive strength was recorded in the 20% replacement mix, with values of 37.95 MPa at 7 days and 50.99 MPa at 28 days, an increase of 12.5% and 42.3%, respectively, over the control mix. Thermal analysis revealed the lowest mass loss in 10% and 20% replacement mixes, with the 20% mix also showing improved fire resistance. These findings indicate that a 20% spent garnet replacement offers the optimal balance between workability, mechanical performance, and thermal stability. This approach not only enhances mortar properties but also promotes sustainable waste management and reduces reliance on natural river sand
Deep serratus anterior plane block vs. rhomboid intercostal plane block for analgesia after breast cancer surgery: A prospective, double-blind randomized study
Full text linkBackground: Ultrasound-guided interfascial plane blocks are widely used in breast cancer surgery, but direct comparisons of deep serratus anterior plane block (SAPB) and rhomboid intercostal plane block (RIPB) are limited.Materials and Methods: Single-center, prospective, randomized, double-blind trial of 40 women (ASA I–III) undergoing oncologic breast surgery. Participants were allocated to SAPB or RIPB, both as single-shot, ultrasound-guided adjuncts to standardized multimodal analgesia. The primary outcome was 24-hour morphine consumption; secondary outcomes were pain scores (NRS at rest and with 90° arm abduction at prespecified times), time to first analgesic request, and adverse events.Results: All randomized patients completed follow-up. Baseline features were comparable except for higher body weight in the SAPB group. The primary outcome did not differ between groups; pain scores were low throughout and showed no between-group differences. Time to first analgesic was similar (log-rank p=0.439). No block-related serious adverse events occurred.Conclusions: Within a standardized multimodal pathway, SAPB and RIPB provided similar early analgesia with low opioid use and a reassuring safety profile. Although the study was not designed for non-inferiority, the findings support RIPB as a practical alternative to SAPB in routine breast cancer surgery. Larger, procedure-stratified studies‒including quality-of-recovery and longer-term outcomes‒are warranted
Performance evaluation of compressive strength of concrete using different machine learning algorithms
Full text linkAccurately predicting the compressive strength of concrete is crucial for ensuring structural integrity, optimizing material usage, and reducing construction costs. Conventional experimental methods, though reliable, are often labour-intensive and time-consuming. To address these limitations, this study investigates the effectiveness of machine learning (ML) algorithms as efficient alternatives for predicting concrete compressive strength. Four ML algorithms—Linear Regression (LR), Multilayer Perceptron (MLP), M5 Rule-Based Model, and Support Vector Machines (SVM)—were evaluated based on their predictive performance. A comprehensive dataset comprising 350 concrete samples was prepared, with compressive strength tests conducted in accordance with Indian standard 516. The models were trained on experimental data and were tested using varying data splits of 50%, 40%, 30%, 20%, and 10% to assess their prediction accuracy. Among the evaluated models, the MLP demonstrated superior performance, achieving a correlation coefficient (CC) of 0.98 with a 20% testing split, outperforming the other algorithms. To further validate the predictive capability of the MLP model, multiple linear regression analysis was employed, confirming its robustness and generalization ability. The findings underscore the potential of machine learning techniques, particularly the MLP model, in providing accurate, reliable, and time-efficient predictions of concrete compressive strength. This study contributes to the growing body of research focused on leveraging machine learning for enhanced decision-making in construction material design, ultimately promoting more sustainable and cost-effective construction practices
