2031 research outputs found
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Effect of Cu and SiO₂ on a Remelted-Recycled Piston Alloy Under Vertical Centrifugal Casting Conditions
No full textFunctionally graded aluminum matrices produced by means of centrifugal casting offer a route to location-specific properties, yet sustainable feedstocks and dual-density reinforcements are less well explored. In this work, we evaluate vertical centrifugal casting (VCC) of a remelted, recycled piston alloy reinforced with silica (SiO₂) and copper (Cu) particulates selected for their contrasting densities relative to the matrix. Castings were produced at 1000 rpm for 5 minutes using a 500 °C preheated mold and an 800 °C pour temperature. Cu was added at 1–4 wt.% and SiO₂ was added at 0–9 wt.%. Bulk density/porosity measurements, Vickers hardness testing, and optical/SEM microstructural analysis were employed to characterize the resulting gradients. The density increased with the radial distance from the rotation axis, accompanied by a monotonic decrease in porosity, consistent with centrifugal separation. Microstructurally, SiO₂ concentrated toward the inner region near the rotation center; in comparison, Cu was enriched at the outer periphery. Correspondingly, hardness exhibited a spatial gradient: SiO₂-reinforced zones were hardest near the inner region, whereas Cu-rich outer zones were hardest at the external rim. These results demonstrate that VCC of a recycled Al–Si feedstock can be used to reliably tailor its microstructure and properties through density-driven particle segregation, enabling controllable, bidirectional functional grading using environmentally friendly starting materials
Performance Evaluation and Model of GFRP Reinforced Concrete Filled GFRP Tube Column under Accelerated Aging
No full textConventional reinforced concrete structures exposed to aggressive environments show a risky tendency toward performance degradation due to concrete deterioration and reinforcement corrosion. Consequently, the use of fiber-reinforced polymer (FRP) materials in concrete structures as one of the alternative potential materials for mitigating serious durability issues in structural applications has gained increasing acceptance. The study aims to evaluate the performance and durability of GFRP-reinforced concrete-filled GFRP tube columns under accelerated aging. Three different column specimens, 1) GFRC-F-GFT, 2) GFRC, and 3) C-F-GFT, were immersed under water at 80°C for 12 hrs (wet phase), followed by specimen placement above water at ambient room temperature for 12 hrs (dry phase) in each aging cycle. The behavior and performance of the specimens were experimentally investigated through uniaxial compressive loading. The experimental results were evaluated to develop a strength capacity model that incorporated the environmental exposure effect through the strength reduction factors (C0, h1, and h2). To establish the correlation between accelerated and natural aging, field investigation data under the tropical marine environment and the simplified time-invariant model were utilized to predict structural performance. Based on this study, the GFRC-F-GFT specimen degradation under accelerated wet-dry aging at 290 cycles can reduce axial column capacity up to 50%, which is equivalent to the predicted degradation under a natural tropical marine environment over 50 years
Comparison Between the Calcium-Based Stabilizer and Non-Organic Agents on the Stabilization of Contaminated Soil
No full textThis study was conducted to investigate the properties of nickel- and copper-contaminated soil and to determine the potential use of calcium stabilizers and inorganic agents as soil improvement methods. The soil was classified as loamy sand (SM) with a low plasticity index (PI = 4%), medium permeability, and high silica content (>33%). X-ray fluorescence (XRF) testing revealed nickel oxide concentrations of 1.5% and copper oxide concentrations of 2.5% in the soil. Nickel and copper contamination based on added nitrate salts was estimated at 1,500 ppm and 2,500 ppm, respectively. X-ray Diffraction (XRD) results showed that quartz and kaolinite were the most abundant, and the contaminants were likely present in an amorphous or surface-adsorbed manner. Unconfined Compressive Strength (UCS) results indicated a significant improvement in compressive strength: from 96 kPa (2% cement, 7 days) to over 12,445 kPa (7% cement, 28 days). The 20% fly ash yielded a strength of 934.5 kPa after 28 days, due to natural pozzolanic reaction and mineral adsorption. Overall, strength improved, and stability was achieved with increased curing time. These results demonstrate that cement and fly ash improved both the mechanical properties and environmental performance of sandy soils contaminated with heavy metals. However, the accelerated strength improvement for cement was significantly greater (over 12,445 kPa) than for fly ash (934.5 kPa, with 20% fly ash) after 28 days of curing. This result suggests that cement-based materials have superior load-bearing performance in applications, but fly ash may be less effective and potentially more environmentally friendly
Comprehensive Characterization of Fly Ash as a Sustainable Supplementary Cementitious Material
No full textSustainable development seeks to meet present needs without harming future generations. Rising energy demand from coal-fired power plants increases CO₂ emissions and produces fly ash (FA). The cement industry, responsible for about 7% of global CO₂ emissions, also consumes large amounts of energy. Incorporating FA as a partial or complete substitute for cement in concrete provided both environmental and performance advantages. Hence, this study focused on exploring the potential of FA from Nagan Raya (FANR) as a cementitious material for cement replacement. FANR was analyzed using XRF, XRD, FTIR, SEM, and EDS. It mainly contained SiO₂ (48.04%), Al₂O₃ (27.62%), and Fe₂O₃ (11.78%), meeting ASTM Class F fly ash standards. XRD analysis confirmed the presence of amorphous phases along with quartz and mullite crystals. FTIR showed silicate hydration products (C–S–H and C–A–H gels) at different water–cement ratios. SEM showed spherical particles with rough surfaces, which enhance reactivity but also increase water absorption and reduce workability. EDS confirmed silicate and aluminosilicate compositions. These results highlight FANR’s potential as a sustainable cement replacement, despite workability issues
Six Sigma Based Management Approach to Minimize Material Losses in Building Construction
No full textThis study aims to reduce material variability, minimize losses, and improve construction performance in multifamily building projects by applying the Six Sigma DMAIC methodology in a Peruvian regional context. The research was conducted in Huancayo using a multifamily structure as a reference to compare theoretical material consumption with actual quantities registered on site. The methodological approach combined statistical analysis with Minitab, logistics modelling with Arena Simulation, data processing through Excel and Power Query, and real-time monitoring using Google Colab connected to Telegram. The analysis identified overconsumption patterns between six and nine percent in concrete, steel, and bricks, which contributed to an estimated delay of about thirty days. After implementing the DMAIC stages, cost deviations were reduced to ten percent or less, schedule performance improved by twelve percent, and operational efficiency reached ninety percent, with ninety-five percent of deliveries made on time. The study introduces a hybrid digital control framework that links Telegram with Google Colab and Power BI, allowing real-time tracking of key performance indicators in projects with limited budgets and low technology adoption. The findings provide one of the first documented applications of Six Sigma for material control in regional Peruvian construction and contribute to the adaptation of Lean Six Sigma principles to the Latin American context by offering practical, field-based evidence of their effectiveness
Ensemble and Hybrid Machine Learning Models for Seasonal Water Consumption Forecasting Under Climate Variability
No full textThe objective of this paper is to improve the forecasting of monthly water consumption under climate variability by combining ensemble and hybrid modelling with a season-aware design. Monthly consumption and meteorological data from 2003 to 2024 were utilized in this study. Four models were evaluated: (i) a stacking ensemble with STL-trend plus residual learning; (ii) a hybrid machine-learning–physics model with differentially-evolved weights; and (iii–iv) season-specific stacked models for wet and dry periods. Robustness was assessed with time-aware validation and residual diagnostics (Shapiro–Wilk, Breusch–Pagan, Durbin–Watson, Ljung–Box). The findings indicate that across models, ensembles captured nonlinear climate–demand variations while maintaining linear structure. The ensemble and hybrid model achieved strong accuracy with low errors while the season-specific models attained high fit (wet R²≈0.998; dry R²≈0.991) with stable residual behavior. Sensitivity to temperature and humidity aligns with expected physical behavior. Precipitation shows a diminishing-returns effect on water use, where moderate rainfall leads to higher consumption, while heavy rainfall tends to reduce demand. The framework innovatively combines decomposition-assisted stacking, physics-informed hybridization, and seasonal ensemble modelling. Overall, the approach provides highly accurate, interpretable, and climate-aware water demand forecasts for tropical regions, offering a practical basis for utility-scale implementation
Scour Morphology Comparison Around Oblong Bridge Pier: Clear-Water and Live-Bed Flow Conditions
No full textBridge pier scour is a significant contributor to structural instability in riverine infrastructure, particularly in sediment-laden tropical rivers. Streamlined shapes such as oblong piers generally produce smaller scour depths than bluff-body piers, offering potential safety advantages. However, the morphological evolution of scour under different sediment-transport regimes and its implications for structural stability remain insufficiently documented. This study experimentally compares clear-water (CW) and live-bed (LB) scour around an oblong pier, with emphasis on equilibrium depth, temporal development, three-dimensional morphology, velocity structure, and safety relevance. Flume tests were performed using a 5-cm × 10-cm oblong pier under steady subcritical flow (Q = 50 L/s, h = 10 cm, d50 = 2.21 mm, Fr < 1), with CW simulated by eliminating upstream sediment supply and LB by continuous sediment recirculation. Velocity measurements using an Acoustic Doppler Velocimeter (ADV) were conducted at equilibrium scour geometry to characterize flow structures. Results show CW scour reached a deeper equilibrium (z/D = 1.70), developed 36.4% faster (T* = 666 min) than LB (z/D = 1.52, T* = 909 min). CW formed a symmetric, steep-walled scour hole with 14.1% greater volume and 15.6% wider planform area, creating an immediate risk of vertical undermining. LB produced a shallower, more elongated scour with partial downstream backfilling, leading to gradual longitudinal undermining and slower foundation settlement. Velocity measurements revealed stronger vertical and lateral fluctuations under LB, explaining its more irregular scour morphology. Although the reduced scour depth confirms previous findings for streamlined piers, the elongated downstream scour and partial backfilling under LB provide new insights for countermeasure design. Among the tested predictors, Sheppard's Equation performed best with 8% (CW) and 3% (LB) deviations. These findings confirm that streamlined oblong piers reduce the maximum scour depth compared with circular shapes, but reveal contrasting mechanisms: CW promotes rapid, concentrated erosion, whereas LB induces slower, more widespread scour. The results emphasize that countermeasure design must explicitly account for the sediment-transport regime to ensure long-term foundation stability
Reliability Design of a New Masonry Bridge: An Approach Based on RBDO and Rigid Block Analysis
No full textThe objective of this study is to establish a reliability-based design framework for new masonry arch bridges, providing a rational alternative to the empirical rules that traditionally governed their construction. The proposed methodology integrates Reliability-Based Design Optimization (RBDO) with the rigid block limit analysis method to optimize key geometric parameters under uncertain loading conditions. The probabilistic formulation incorporates the variability of geometric and load parameters, which are identified as the dominant sources of uncertainty during the design phase of new masonry bridges. Two RBDO strategies are employed: the Performance Measure Approach (PMA) and Sequential Optimization with Reliability Assessment (SORA), both coupled with a linear programming formulation of equilibrium and yield constraints. The approach is applied to the reconstruction of the historical Dar El Makina bridge in Fes, Morocco, to determine the optimal geometric configuration that satisfies target reliability requirements. The results indicate that the optimized design achieves a 27% reduction in arch thickness and a 13% increase in rise compared to the existing structure, leading to a safer and more material-efficient configuration. Compared with classical empirical formulas, the proposed approach provides a rational and quantitative basis for the design of masonry bridges, combining structural safety, material efficiency, and heritage preservation
Seepage Control in Zoned Earth Dams Using Lime–Fly Ash Treated Sandy Soil
No full textSeepage control is a critical factor in ensuring the stability of earth dams, particularly those constructed with permeable soils. Uncontrolled seepage and increased pore pressures within the dam body are typically associated with instability, internal erosion, and potential failure. This study aims to evaluate the effectiveness of lime–fly ash mixtures in controlling seepage through earth dams constructed with sandy soil, using experimental modelling and numerical simulation. A physical model of a zoned earth dam was built using untreated sandy soil as the control model, along with treated models in which the sandy core was stabilized with progressively higher lime–fly ash proportions. The results of laboratory permeability tests demonstrated significant reductions in hydraulic conductivity with increasing additive content, resulting in delayed steady-state conditions and a reduction of up to 98.2% in seepage rate compared with the control model. Numerical simulations, validated against experimental results (coefficient of determination, R²>0.98), accurately reproduced phreatic lines and seepage rates and were further used to examine the influence of core slope geometry. The results showed that a core slope of 0.75:1 provided nearly equivalent hydraulic performance to that of the baseline 1:1 slope, offering a more cost-effective alternative. These findings highlight the potential of lime–fly ash–sand mixtures as sustainable and cost-efficient alternatives for dam cores, particularly in regions where clay resources are limited
Hierarchical Learning-Based System Decomposition for Time-Dependent Structural System Reliability Assessment
No full textTime-dependent reliability assessment of structural systems is challenging when degradation and multiple interacting failure modes govern failure. Under these conditions, the system limit state function (LSF) may be highly nonlinear, non-smooth, and available only implicitly through high-fidelity analysis. This paper proposes a system decomposition and hierarchical learning (DHL) framework to construct an evaluable surrogate system LSF for degradation-driven, time-variant reliability analysis. The structural system is decomposed into dominant failure modes and their connectivity. Artificial neural networks are trained hierarchically to learn the decomposed relationships. Mode-level surrogates approximate the LSF of each failure mode. A system-level surrogate then integrates the mode-level performance quantities and time to capture mode interaction and mechanism switching. The resulting surrogate is combined with Monte Carlo simulation and the probability density evolution method to compute time-dependent failure probabilities and, when required, the evolution of the system performance probability density. Two benchmark problems—a highly nonlinear parallel system and a rigid–plastic portal frame with correlated collapse mechanisms under degrading capacities—are used to evaluate the approach. DHL improves system-level surrogate fidelity relative to direct system-level ANN learning, with mean reliability prediction errors below 3.1% and 1.23% in the two benchmarks, respectively, while remaining compatible with both sampling-based and density-evolution propagation schemes