2031 research outputs found
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The Influence of Precursor to Activator Ratio and Curing Temperature on Geopolymer Paste with One-Part Method
Get PDFGeopolymer is an eco-friendly material that serves as a sustainable alternative to Portland cement in construction. This binder reduces carbon dioxide emissions from cement production. However, its manufacturing process remains complex and requires professional expertise. This study explores an environmentally friendly cement produced through the “One-Part Method” (or the “just add water” method), which simplifies geopolymer application, making it as user-friendly as Portland cement. However, research on the performance of one-part geopolymers with varying activator contents and curing temperatures remains limited. In this study, Class F fly ash was used as a precursor, combined with a dry activator made from geothermal sludge and sodium hydroxide (NaOH). Two compositions were tested with precursor-to-dry activator ratios of 5:1 (OPG-F5F) and 7:1 (OPG-F7F). The compressive strength was significantly influenced by the Si/Al, Na/Si, Na/Al, and water/solid ratios derived from the precursor and activator. Mechanical properties were analyzed at three curing temperatures: ambient, 40°C, and 60°C. Results showed that OPG-F7F achieved the highest strength at 60°C, reaching 76.1 MPa at 28 days. Mineral analysis before and after steam curing revealed no changes in composition, while morphological analysis indicated that higher temperatures produced a denser geopolymer matrix. These findings demonstrate the strong potential of geopolymer cement as a viable Portland cement replacement using the One-Part Method
Alternative Method for Determining Manning's Roughness Coefficient Using Two-Point Velocity in Equilibrium and Nonequilibrium Sediment Transport
Get PDFUnderstanding flow resistance equations, such as Manning’s roughness equation, is essential for river design and improvement. Estimating Manning’s roughness coefficient becomes more complicated when sediment transport is involved. This study takes an alternative approach by using velocity profiles to examine how sediment transport affects Manning’s roughness coefficient. To achieve this goal, 1200 velocity profiles with sediment-feeding (SF) and non-sediment-feeding (NSF) flows are evaluated to determine the (composite) Manning’s roughness coefficient. Sediment-feeding flows describe sediment flow under equilibrium conditions, whereas non-sediment-feeding flows represent sediment flow under nonequilibrium conditions. A Sontek 16-MHz Acoustic Doppler Velocimeter is used to measure the velocity (and turbulence) profiles. In addition to the present data, 225 secondary velocity profile data sets are analyzed in this study. The research findings indicate that the composite Manning’s roughness coefficient nco can be determined from Manning’s roughness coefficient nz/B at z/B in the transversal direction, using two points of the velocity profile at y/H = 0.2 and 0.4 in the vertical direction. The differences in the velocity profile shape (u/U) due to sediment feeding, particularly in inner regions (y/H ≤ 0.2), affect the value of nz/B. nco for sediment-feeding flows are generally higher than the cross-section Manning roughness coefficient n. As nco (based on nz/B) is based on the velocity profile, the nco values change with sediment transport. Meanwhile, the n values remain unchanged because the equation variables cannot detect the presence of sediment transport. For non-sediment-feeding flow, the differences in nco with n are 14.80% for a fixed bed (FB) and 18.17% for a movable bed (MB). The differences are even more pronounced for sediment-feeding flow at 33.01% for a fixed bed and 36.52% for a movable bed. The point where nz/B/nco = 1 occurs at z/B = 0.2 from the channel sidewall. This suggests that nz/B, measured at z/B = 0.2 from the channel sidewall, provides a good representation of nco for the section
Numerical Analysis of the Shear Behavior of Shallow-Wide Concrete Beams via the Concrete Damage Plasticity Model
Get PDFShallow reinforced concrete beams are broadly used in buildings for their aesthetic and economic benefits, but their shear performance remains insufficiently known, especially considering the impact of stirrups. While experimental investigations provide a good understanding, they are expensive and provide limited insight, creating a gap in the understanding of the complex shear behavior of shallow RC beams. This study bridges this limitation by conducting finite element analysis and calibrating the critical concrete damage plasticity parameters such as the dilation angle, Kc values, eccentricity, damage parameters, and loading time. Additionally, the numerical model validated the experimental results by accounting for the effects of the stirrup spacing, width, and longitudinal-to-stirrup ratio to achieve the ultimate load and corresponding deflection differences within 1.69% and 10.7%, respectively. The findings revealed that increasing the stirrup spacing enhanced ductility without increasing strength, whereas increasing the beam width and longitudinal-to-stirrup ratio increased strength and ductility. Finally, a comparison with design codes and machine learning revealed greater accuracy of FEA prediction, presenting new insight into upgrading the design code for shallow RC beams. Doi: 10.28991/CEJ-2025-011-02-022 Full Text: PD
Treatment of Industrial Wastewater of Variable Quality Using Ultrasound Irradiation
Get PDFThis paper investigated the use of ultrasound irradiation to treat real mixed industrial wastewater under various conditions, including single and dual frequencies, variable wastewater strengths, and different operating conditions, including flow rates/residence times. This work is important to evaluate the organics' removal efficiency and to identify operational control bottlenecks under actual wastewater conditions. The highest removal efficiencies were 69.5% and 31.9% for COD and TOC, respectively, for the high-strength wastewater, which were found to occur at 16 kHz frequencies and 500 ml/min flow rate. The removal efficiencies were slightly less in the case of medium-strength wastewater (66.7 and 25.3% for COD and TOC, respectively). They were found to occur at dual frequencies of 16/20 kHz and 1500 and 1000 ml/min, respectively. For the low-strength wastewater, the efficiencies reached 78.6 and 9.1% for COD and TOC, respectively, at the same frequency and flow rates as the medium-strength wastewater. These findings demonstrated the effectiveness of dual frequency in medium- to low-strength wastewater. Among the organics monitored, chloroform (CHCl3), tetrachloroethene (C2Cl4), 1,4 dichlorobenzene (C6H4Cl2), and dichloromethane (CH2Cl2) exhibited variable removal, and in some cases, the removal was found to be negative, indicating intermediary products as a result of incomplete oxidation of organics. Besides the frequency and flow rate, it was found that the concentration of metals and organics are mostly positive influencers on organics removal. At the same time, TDS and pH have mixed effects, but they positively influence organics' removal at higher flows in a few instances. Additionally, as the residence time decreased, the concentration of organics and the pH negatively influenced organics removal. Doi: 10.28991/CEJ-2025-011-04-013 Full Text: PD
Engineering and Microstructure Properties of Soft Clay Improved with Ordinary Portland Cement and Polymers
Get PDFThis study investigated properties of soft Bangkok clay stabilized with ordinary Portland cement (OPC) and various polymers. Variables included initial water content (1.0LL, 1.5LL, and 2.0LL; LL = liquid limit), polymer type (polyvinyl alcohol (PVA), polyethylene glycol (PEG), and polyvinylpyrrolidone (PVP), polymer concentration (1%, 3%, 5% and 7%), and curing time. The unconfined compressive strength (UCS), consolidation, permeability, and microstructure were analyzed. UCS decreased with increasing water content due to delayed polymer bonding; however, at 1.0LL, polymers effectively bonded clay particles, resulting in higher UCS. A 3% polymer concentration yielded the highest UCS, while 5–7% led to non-homogeneous structures and reduced UCS. The UCS of the sample with PEG outperformed those with PVA and PVP. At 1.0LL and 3% polymer, 28-day UCS values were 1.20 MPa (PEG), 1.12 MPa (PVA), and 1.04 MPa (PVP), all exceeding the Department of Highways' standard 1.0 MPa. Higher polymer concentrations decreased void ratios and permeability by forming hydrogel layers and thin films, increasing soil density. SEM/EDS analysis confirmed 3% polymers formed uniform films enhancing soil bonding, while 7% resulted in thicker, irregular films, reducing UCS. These findings suggest that polymers could be a promising alternative to OPC in environmentally friendly deep mixing applications. Doi: 10.28991/CEJ-2025-011-04-022 Full Text: PD
Glow-Wire Analysis of Polypropylene Blends for Mechanical and Marine Engineering Applications
Get PDFPolymer materials are widely used due to their versatility; however, their vulnerability to fire is a significant concern, especially under electrical influences on engineered mechanical designs and marine structure applications. This study examines the fire resistance of a polypropylene (PP) blend using Glow-Wire Flammability Index (GWFI) and Glow-Wire Ignition Temperature (GWIT) tests. While previous research typically relies on flame-retardants to address flammability, this work proposes using a simple 1:1 weight ratio blend of two distinct PP types. This specific PP blend was selected to provide balanced material properties and improved processing consistency. The results from glow-wire tests were compared with previous findings to evaluate flammability performance. Our findings reveal that although the PP blend offers enhanced fire resistance compared to neat PP, it remains inferior to PP-containing flame-retardant additives. The outcomes suggest that this blended PP may be suitable for applications where mechanical properties, cost-effectiveness, and recyclability precede fire resistance, such as engineered automotive interiors, mechanical design of marine transportation, and low-risk electrical components in engineering infrastructure. This initial research contributes valuable insights into the fire behavior of PP blends. Moreover, it establishes a foundation for future investigations into polymer fire resistance, encouraging additional glow-wire testing on other polymer systems
Driving Economic Value: Assessing the Financial Impact of Dynamic Message Signs on Freeways
Get PDFDynamic Message Signs (DMSs) are an integral feature of any Intelligent Transportation System (ITS), providing drivers with real-time information such as travel time, incidents, routes, and weather conditions. This study aims to estimate the economic impacts associated with DMS use for route choice, weather advisories, and work zone management on freeways. Several freeway locations with varying levels of traffic congestion were selected to ensure a comprehensive evaluation under diverse conditions. Travel time savings and speed reductions were used as performance metrics to assess Benefit-Cost Ratios (BCRs) for each application. The findings show that DMSs yield substantial economic advantages across all use cases. For route guidance messages with a 35% diversion rate, the BCR was 1.032, indicating a cost-effective investment. Weather advisory messages recommending speed reduction achieved a notably higher BCR of 6.0, reflecting strong safety and financial benefits. Work zone applications using Portable Changeable Message Signs (PCMS) projected a BCR of 1.22. This study offers a data-driven justification for DMS deployment and contributes to the literature by focusing on financial performance, supporting strategic investment decisions beyond qualitative or operational assessments
Development of Novel Surrogate Models for Stress Concentration Factors in Composite Reinforced Tubular KT-Joints
Get PDFCircular hollow section (CHS) joints are among the most critical components in offshore jackets, often requiring rehabilitation to maintain structural integrity. The structural stress approach, based on stress concentration factors (SCFs) for hot-spot stress (HSS) calculations, is commonly used to estimate the fatigue life of critical structural elements such as CHS joints. Various empirical models exist for the rapid estimation of SCF in composite-reinforced CHS joints; however, most studies focus on SCF at the crown and saddle positions under uniplanar loading. This limitation reduces their applicability to multi-planar loading conditions, potentially leading to the underestimation of HSS. This study investigates the use of fiber-reinforced polymer (FRP) composites to strengthen CHS KT-joints under complex loading, focusing on reducing SCF and improving fatigue life. A total of 5,429 finite element simulations were conducted to examine the effects of geometric and reinforcement parameters on SCF. The simulation data were used to train artificial neural networks (ANNs), which were incorporated into a computational tool for the rapid approximation of hot-spot stress in FRP-reinforced KT-joints. The application of composites to CHS joints significantly reduces SCF, particularly with an increased number of reinforcement layers, a higher elastic modulus, and an orthogonal fiber orientation to the weld toe. This study presents a novel methodology for developing efficient models to estimate SCF in composite-reinforced CHS joints under complex loading, addressing a key gap in fatigue design for such joints. The developed computational tool enables the rapid calculation of hot-spot stress in CHS joints. Doi: 10.28991/CEJ-2025-011-04-012 Full Text: PD
Design a No-Fine Concrete Using Epoxy in Pavement
Get PDFNo-fines concrete is an advanced pavement material known for its strong drainage capabilities, making it a widely used rigid road surface. With growing demand for reduced cement content due to industrial advancements, researchers have explored epoxy resin as a partial or total cement replacement. This study examines the mechanical properties of no-fines concrete with varying epoxy replacement levels and applies KENSLAB analysis for pavement thickness design. Seven concrete mixes were prepared with epoxy replacing cement at 100%, 95%, 75%, 55%, 35%, and 15%. Mechanical tests, including compressive strength, flexural strength, modulus of elasticity, bulk density, water absorption, and durability (wet-dry), were conducted after 7 and 28 days of curing. Additionally, the PerviousPave system was used to optimize pavement integrity by adjusting slab thickness, subbase layer thickness, and stormwater management. Results showed that the 55% and 100% epoxy replacement mixes performed best. Compressive strength increased by 2.44% and 33.44%, respectively, at 28 days compared to the reference mix. Flexural strength reached 5.99 MPa for 100% epoxy and 4.69 MPa for 55% epoxy at 28 days. Structural analysis demonstrated that increased slab and subgrade stiffness reduced tensile stresses, improving pavement durability and extending service life. These findings highlight the potential of epoxy-modified no-fines concrete for enhanced pavement performance in traffic and environmental conditions. Doi: 10.28991/CEJ-2025-011-05-021 Full Text: PD
Improving Efficiency and Accuracy in Construction Sales Valuation via Random Search Optimization
Get PDFThe valuation of construction project sales depends on various economic variables and indices. While accurate cost predictions support financial planning and risk management, traditional grid-search optimization-based machine learning techniques often demand extensive computational resources for training and optimization, especially when large datasets require comprehensive machine learning models. Recent investigations highlighted that random search optimization can shorten the training time of ensemble machine learning methods. Nevertheless, its effectiveness for construction project cost valuation, especially when examining model accuracy and training time, is still unclear. This research examines the usability of random search optimization for machine learning models in construction project sales valuation and compares it with the standard grid search approach. A large dataset with 103 inputs from 372 construction projects is used as the basis of the investigation. Six different machine learning models are designed and optimized under grid search and random search approaches to evaluate training time and predictive accuracy. The study results indicate that random search optimization cuts training time by up to 70% and preserves a high level of accuracy, with the best-performing model achieving an R² of 0.98 on the test set. These findings highlight random search optimization as a strong alternative to grid search, providing significant computational savings without harming model performance. The study offers guidance on effective hyperparameter tuning methods that may facilitate scalable and budget-friendly predictive models for construction project valuation