Search Results (294)

The Citarum River Basin (DAS Citarum) in Indonesia faces significant challenges in waste management, necessitating a circular economy-based approach to reduce land-based pollution, which is critical for achieving the sustainability goals of the blue economy in the basin. This study addresses the complexity and inherent uncertainty in decision-making processes related to this challenge by developing a novel hybrid model, namely the Weighted Fuzzy N-Soft Set combined with the COmbinative Distance-based Assessment (CODAS) method. The model synergistically integrates the weighted 10R strategies in the circular economy, obtained via the Analytical Hierarchy Process (AHP), the capability of Fuzzy N-Soft Sets to represent uncertainty granularly, and the robust ranking mechanism of CODAS. Applied to a case study covering 16 types of waste in the Citarum River Basin, the model effectively processes expert assessments that are ambiguous regarding the 10R criteria. The results indicate that single-use plastics, particularly plastic bags (HDPE), styrofoam, transparent plastic sheets (PP), and plastic cups (PP), are the top priorities for intervention, in line with the high AHP weights for upstream strategies such as Refuse (0.2664) and Rethink (0.2361). Comparative analysis with alternative models, namely Fuzzy N-Soft Set-CODAS, Weighted Fuzzy N-Soft Set with row-column sum ranking, and Weighted Fuzzy N-Soft Set-TOPSIS, confirms the superiority of the proposed hybrid model in producing ecologically rational priorities, free from purely economic value biases. Further sensitivity analysis shows that the model remains highly robust across various weighting scenarios. This study concludes that the WFN-SS-CODAS framework provides a rigorous, data-driven, and reliable decision support tool for translating circular economy principles into actionable waste management priorities, directly supporting the restoration and sustainability goals of the blue economy in river basins. The findings suggest that targeting the high-priority waste types identified by the model addresses the dominant fraction of riverine pollution, indicating the potential for significant waste volume reduction. This research was conducted to directly contribute to achieving multiple targets under SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 14 (Life Below Water). Full article

The environmental impact of the construction sector underscores the urgent need for sustainable solutions to extend the service life of existing structures. This study explores High-Performance Fiber-Reinforced Concrete (HPFRC) for strengthening reinforced-concrete (RC) columns subjected to axial compression. Twelve RC columns were tested, each 1200 mm high and with varying cross-sectional shapes (circular, square, and rectangular). Strengthening was achieved using thin HPFRC jackets (less than 30 mm thick), applied without additional internal reinforcement and following simple surface preparation techniques such as sandblasting. Full-height jacketing significantly improved axial load capacity. Its effectiveness did not decrease with the shape of the cross-section, with square columns showing up to a 105% increase and rectangular ones up to 87%, compared to unstrengthened columns with the same concrete strength. The highest improvement was observed in the square column with full-height jacketing and the most significant geometric strengthening ratio (52.6%), which doubled its axial capacity. This ratio was directly related to performance gains. Although ductility gains were limited, the full-jacketed specimens did not fail explosively: their failure mode was progressive, providing a useful warning before collapse. HPFRC jacketing can be especially effective for non-circular columns, outperforming FRP jacketing and eliminating the need for additional protective layers against impact or fire. Full article

Research on the configuration and mechanical performance of arch-column-tie beam joints, which combine features of arch-tie beam joints and tubular joints, remains limited, particularly for long-span structures subjected to heavy loads at high building stories. This study focuses on a joint in an engineering structure comprising a circular arch beam, a square-section inclined column, and a tie beam, where both the arch and the inclined column are concrete-filled steel tube (CFST) members. A novel joint configuration was proposed, then a refined finite element model was established. The joint’s mechanical mechanism and failure mode under axial compression in the arch beam were investigated, considering two conditions: the presence of prestressed high-strength rods and the failure of the rods. Subsequently, a parametric study was conducted to investigate the influence of variations in the web thickness of the tie beam, the steel tube wall thickness of the arched beam, the steel tube wall thickness of the supporting inclined column, and the strength grades of steel and concrete on the bearing capacity behavior and failure modes. Numerical simulation results indicate that the joint remains elastic under the design load for both conditions, meeting the design requirements. The joint reaches its ultimate capacity when extensive yielding occurs in the tie beam along the junction region with the circular arch beam, as well as in the steel tube of the arch beam. At this stage, the steel plates and concrete within the joint zone remain elastic, ensuring reliable load transfer. The maximum computed load of the model with prestressed rods was 2.28 times the design load. The absence of prestressed rods could lead to a significant increase in the high-stress area within the web of the tie beam, decreasing the joint’s stiffness by 12.4% at yielding, but have a limited effect on its maximum bearing capacity. Gradually increasing the wall thickness of the arch beam’s steel tube shifts the failure mode from arch-beam-dominated yielding to tie-beam-dominated yielding along the junction region. Increasing the steel strength grade is more efficient in enhancing the bearing capacity than increasing the concrete strength grade. Finally, a design methodology for the joint zone was established based on three aspects: local stress transfer at the bottom of the arch beam, force equilibrium between the arch beam and the tie beam, and the biaxial compression state of the concrete in the joint zone. Furthermore, the construction process and mechanical analysis methods for various construction stages were proposed. Full article

This study aims to investigate the performance of the combined machine learning (ML) models and tiering technique for predicting the compressive strength of FRP-strengthened circular concrete columns. A dataset consisting of 725 experimental results has been assembled from available research studies to evaluate the prediction models. Pearson’s correlation analysis has been carried out to investigate the relationship between seven input parameters and the target parameter. The Taylor diagram has been plotted to deter-mine the best design-oriented strength model. The prediction performance of the combined ML models and tiering technique was compared with that of single ML models and ten design-oriented strength models. The research outcomes revealed that applying the tiering technique significantly improved the prediction accuracy of the ML models. It was also found that the best ML model for predicting the compressive strength of FRP-strengthened circular concrete columns was the combined random forest model and tiering technique, which outperformed single ML and design-oriented strength models. Full article

This study presents a machine learning framework for predicting the axial compressive strength of circular concrete-filled steel tube (CFST) columns subjected to concentric and eccentrically applied axial loads. A harmonized database of 1287 test specimens was compiled, encompassing diverse material strengths, geometric configurations, and eccentricity levels. Among the trained models, the CatBoost (CatB) algorithm exhibited the highest predictive performance. A 300-run Monte Carlo simulation yielded a mean R² of 0.966 (Min: 0.804; Max: 0.996), with a mean RMSE of 588.8 kN and MAPE of 8.36%, demonstrating accuracy and robustness across repeated randomized splits. Comparative benchmarking against current design equations revealed that CatBoost substantially reduced prediction scatter, improving the mean ratio and reducing the COV from 70–75% (ACI/AIJ/Wang) to 5.43%, while maintaining a nearly unbiased mean prediction ratio of 1.00. In addition, inverse prediction models based on CatBoost achieved test-set R² values of 0.908 for compressive strength and 0.945, 0.900, and 0.816 for key design parameters (D, t, L), indicating promising capability for supporting preliminary sizing and parameter selection. The outcomes of this study highlight the potential of data-driven modelling to complement existing design provisions and assist engineers in early-stage decision-making for axially loaded circular CFST columns. Full article

To investigate the effect of column form on the hydrodynamic performance of semi-submersible truss fishery aquaculture platforms, this study focused on an active semi-submersible aquaculture platform located in the South China Sea. Three platform models featuring distinct column structures were established. Employing three-dimensional potential flow theory and Morrison’s equations, numerical simulation methods were utilised to analyse the dynamic response of the three types of column platforms in both the frequency and time domains under wind, wave, and current action. Consequently, relevant conclusions regarding the influence of column form on the hydrodynamic performance of semi-submersible platforms were derived. The results show that: The quasi-elliptical column platform exhibits superior frequency-domain response characteristics, with the circular column platform following, while the square column platform demonstrates the poorest performance. When subjected to the combined effects of waves and currents, the circular column platform shows the most favourable time-domain dynamic response, with the quasi-elliptical column platform next, and the square column platform lagging behind. In contrast, under the combined influence of wind, waves, and currents, the quasi-elliptical column platform excels in time-domain dynamic response, followed by the square column platform, with the circular column platform being the least effective. These variations in time-frequency dynamic response characteristics among the three column platforms are attributed to their distinct structural forms. Full article

Circular concrete-filled steel tube columns prepared with 100% recycled aggregate concrete (RACFST) are of interest for sustainable, carbon-neutral construction. However, recycled aggregates typically have higher water absorption and lower stiffness, raising concerns about seismic performance. This paper investigates the low-cycle cyclic behavior and displacement ductility of circular RACFST columns. Ten short columns were tested under an axial load ratio of ≈0.20, with varying diameters of 165 and 219 mm and concrete strengths of C30, C40, and C50, along with companion natural-aggregate CFST control specimens. A three-dimensional finite element model was developed and calibrated based on the test results, and parametric simulations were conducted to study the effects of geometry and material parameters. Two distinct flexural failure modes with outward bulging at the base were observed. These two distinct flexural failure modes refer to (1) local outward bulging of the steel tube accompanied by buckling near the base (e.g., specimens RACFSTC40-165-1 and RACFSTC30-219-1) and (2) flexural yielding with extensive concrete crushing around the base region (e.g., specimens RACFSTC50-219-2 and FSTC40-219-2). The first mode was characterized by early steel local deformation and shell instability, while the second showed more distributed plasticity with crushing of recycled aggregate concrete. These modes underline the influence of D/t and concrete strength on failure progression. The results indicate that RACFST columns attain a peak strength comparable to conventional CFST, while achieving significantly greater drift ductility and energy dissipation; the equivalent viscous damping ratio was found to increase with drift at ≈0.04–0.08 for low drifts and ≈0.10–0.18 for moderate drifts, suggesting that existing CFST design provisions are applicable, with only a minor ~3–5% reduction in core concrete strength recommended for stability. Full article

Concrete-filled steel tube (CFST) columns are composite structural elements preferred in various engineering structures due to their superior properties compared to those of traditional structural elements. However, fire resistance analyses are complex due to CFST columns consisting of two components with different thermal and mechanical properties. Significant challenges arise because current design codes and guidelines do not provide clear guidance for determining the time-dependent fire performance of these composite elements. This study aimed to address the existing design gap by investigating the fire behavior of circular long CFST columns under axial compressive load and developing robust, accurate, and reliable design models to predict their fire performance. To this end, an up-to-date database consisting of 62 data-points obtained from experimental studies involving variable material properties, dimensions, and load ratios was created. Analytical design models were meticulously developed using two advanced soft computing techniques: artificial neural networks (ANNs) and genetic expression programming (GEP). The model inputs were determined as six main independent parameters: steel tube diameter (D), wall thickness (t_s), concrete compressive strength (f_c), steel yield strength (f_sy), the slenderness ratio (L/D), and the load ratio (μ). The performance of the developed models was comprehensively compared with experimental data and existing design models. While existing design formulas could not predict time-based fire performance, the developed models demonstrated superior prediction accuracy. The GEP-based model performed well with an R-squared value of 0.937, while the ANN-based model achieved the highest prediction performance with an R-squared value of 0.972. Furthermore, the ANN model demonstrated its excellent prediction capability with a minimal mean absolute percentage error (MAPE = 4.41). Based on the nRMSE classification, the GEP-based model proved to be in the good performance category with an nRMSE value of 0.15, whereas the ANN model was in the excellent performance category with a value of 0.10. Fitness function (f) and performance index (PI) values were used to assess the models’ accuracy; the ANN (f = 1.13; PI = 0.05) and GEP (f = 1.19; PI = 0.08) models demonstrated statistical reliability by offering values appropriate for the expected targets (f ≈ 1; PI ≈ 0). Consequently, it was concluded that these statistically convincing and reliable design models can be used to consistently and accurately predict the time-dependent fire resistance of axially loaded, circular, long CFST columns when adequate design formulas are not available in existing codes. Full article

Carbon Fiber-Reinforced Polymers (CFRPs) are gaining popularity as a reliable strengthening technique for reinforced concrete (RC) columns. Several efficient models were developed to predict the stress–strain (σ-ε) curve of CFRP-confined concrete based on experiment findings. The ultimate strength is a crucial parameter for accurate (σ-ε) behavior prediction, since it constitutes an initial step in estimating the corresponding axial strain, as it provides a direct indication of the desired increase in strength. Literature analytical models often produce inconsistent results due to errors in estimating the confinement pressure or effectively confined area or the lack of a strong and stable correlation between ultimate strength and confinement parameters. This study looked at a large collection of experimental results from existing research. It used a statistical method (Pearson’s coefficient) to see how well ultimate strength correlated with various confinement factors. For normal-strength concrete columns with circular sections, there was a strong linear correlation between ultimate strength and the thickness of the CFRP jacket. This correlation weakened for high-strength concrete (HSC) and for rectangular columns. A sensitivity analysis was performed to identify the most influential confinement parameters, showing that the number of CFRP layers (n $\times$ t) is the most dominant factor, particularly with normal-strength concrete (NSC) in circular columns, accounting for the vast majority of the variance in ultimate strength. Using multiple linear regression equations to predict ultimate strength was also explored; this method demonstrated the best performance with HSC in circular sections, but the results were less promising with NSC. Artificial Neural Networks (ANNs) were developed and trained on the built database, and four statistical metrics were computed for evaluation (R², RMSE, MAE, MRAE), proving highly accurate and superior to linear regression equations, with mean relative absolute errors MRAEs between 2.4–7.2% for ultimate strength prediction, opening new avenues for optimizing CFRP-strengthened element designs. Full article

In this study, two native microalgae, Chlorella sp. MC18 (CH) and Scenedesmus sp. MJ23-R (SC) were cultivated in bubble column photobioreactors for wastewater treatment. Domestic wastewater (DWW) was used as the main culture medium, alone (100%) and blended (10%) with vinasse, whey, or agro-food waste (AFW), respectively. Both species thrived in 100% DWW, achieving significantly high removal efficiencies for chemical oxygen demand, total nitrogen, and total phosphorus. Mineral removal exceeded 90% in all blended systems, highlighting the strong nutrient uptake capacity of both strains. The maximum specific growth rate (µ_max) in 100% DWW was higher for SC than in standard BG11 medium, and supplementation with vinasse, whey, or AFW further increased µ_max for both species. Blending DWW significantly enhanced microalgal biomass and lipid production compared to 100% DWW. Lipid production (max., 374 mg L⁻¹), proximate lipid composition (max., 30.4%), and lipid productivity (max., 52.9 mg L⁻¹ d⁻¹) significantly increased in all supplemented cultures relative to DWW alone, demonstrating the potential of co-substrate supplementation to optimize microalgal cultivation. This study contributes to reducing the water footprint and fills a gap in the bioprocessing potential of algae-based systems, highlighting wastewater blending as a circular economy-aligned approach that supports sustainable bioprocesses and resource recovery. Full article

This study introduces an innovative connection to improve the seismic performance of I-beam–to–concrete-filled circular column joints. The concept employs a steel box with optimized internal and external stiffeners, eliminating continuity and doubler plates to simplify construction. Calibrated finite-element analyses were first conducted to select three configurations for experimental testing under cyclic quasi-static loading, measuring energy dissipation, stiffness, ultimate moment, panel-zone rotation, and strain distribution. The best-performing specimen was then identified, followed by a numerical parametric study varying beam and column dimensions to determine the minimum steel-box thickness beyond which further increases offer negligible benefit and to assess its effect on connection rigidity. Experimentally, stiffeners aligned with beam flanges significantly improved moment capacity, stiffness, and energy dissipation. Based on parametric analyses, connections with appropriate box-to-flange thickness ratios achieved over 95% of the maximum flexural strength and stiffness, confirming the reliability of the proposed non-dimensional design approach. Numerical analyses showed that the proposed non-dimensional thickness ratios accurately predict connection behavior, where appropriate flange-to-box proportions ensure over 95% of maximum flexural strength and stiffness, leading to stable and rigid joint performance. Overall, the proposed detailing offers a constructible alternative to conventional plate-intensive solutions while achieving superior cyclic behavior. Full article

This study establishes a refined numerical model of circular concrete-filled steel tube (CFST) columns using finite element software, and its effectiveness was verified through simulation of low-cycle reciprocating load tests. Based on this, a systematic analysis was conducted to investigate the effects of three key parameters—axial compression ratio (0.1–0.3), slenderness ratio (22.2–46.8), and confinement coefficient (0.65–1.56)—on the seismic performance of CFST columns, including failure modes, hysteretic behavior, skeleton curves, ductility, and energy dissipation capacity. The local buckling behavior was also studied. The results indicate that increasing the axial compression ratio slightly enhances the bearing capacity but reduces ductility, increasing the slenderness ratio significantly reduces the bearing capacity but improves ductility, and increasing the confinement coefficient substantially improves the bearing capacity, ductility, and energy dissipation capacity simultaneously. Based on the parametric analysis, the existing calculation formula for the local buckling length of circular CFST columns was modified. The average error between the predicted and simulated values is only 10%, demonstrating high engineering applicability. This research provides a theoretical basis and a practical calculation method for the seismic design and performance evaluation of CFST building and bridge columns. Full article

This study presents a comprehensive evaluation of levulinic acid purification schemes from a circular economy perspective, integrating resource-based indicators with economic and environmental metrics. Twelve alternatives, ranging from conventional distillation sequences to intensified hybrid systems, were assessed using indicators such as Relative Material Impact, total annual cost, Eco-Indicator 99, fuel demand, and CO₂ emissions. The novelty of this work lies in extending the assessment beyond purification infrastructure to include upstream systems that supply energy demand, such as fuel extraction and steam generation. The configurations considered incorporate thermal couplings, dividing wall columns, and decanters, which influence energy efficiency, process complexity, and resource depletion. Among these, the TDWS-D configuration (Thermally Coupled Double Dividing Wall Column System with Decanter) exhibits the highest values in DMR, TAC, and CO₂ emissions, driven by its elevated energy demand and complex infrastructure. Conversely, the TCS2 configuration (Thermally Coupled Sequence, featuring selective heat integration between distillation columns) achieves the lowest impact across all metrics, demonstrating that selective and strategic intensification (rather than maximalist design) can yield superior sustainability outcomes. Across all scenarios, the boiler stage was identified as the main contributor to material depletion, followed by fuel extraction and purification equipment. Notably, some conventional designs proved superior to intensified ones in terms of circularity, challenging the assumption that intensification inherently guarantees sustainability. Overall, the integration of circular economy indicators enables a multidimensional evaluation framework that supports more responsible and resource-efficient process design. Full article

Blast damage to structural members poses serious risks to both buildings and people, making it important to understand how these elements behave under extreme loads. Columns in reinforced concrete (RC) structures are especially critical, as their sudden failure can trigger progressive collapse, unlike beams or slabs that have more redundancy. This state-of-the-art review brings together the current knowledge of the blast response of RC columns, focusing on their failure patterns, dynamic behavior, and key loading mechanisms. The studies covered include experiments, high-fidelity numerical simulations, emerging machine learning approaches, and analytical models for columns of different shapes (square, rectangular, circular) and strengthening methods, such as fiber reinforcement, steel-concrete composite confinement, and advanced retrofitting. Composite columns are also reviewed to compare their hybrid confinement and energy-absorption advantages over conventional RC members. Over forty specific studies on RC columns were analyzed, comparing the results based on geometry, reinforcement detailing, materials, and blast conditions. Both near-field and contact detonations were examined, along with factors like axial load, standoff distance, and confinement. This review shows that RC columns respond very differently to blasts depending on their shape and reinforcement. Square, rectangular, and circular sections fail in distinct ways. Use of ultra-high-performance concrete, steel fibers, steel-concrete composite, and fiber-reinforced polymer retrofits greatly improves peak and residual load capacity. Ultra-high-performance concrete can retain a significantly higher fraction of axial load (often >70%) after strong blasts, compared to ~40% in conventional high-strength RC under similar conditions. Larger sections, closer stirrups, higher transverse reinforcement, and good confinement reduce spalling, shear failure, and mid-height displacement. Fiber-reinforced polymer and steel-fiber wraps typically improve residual strength by 10–15%, while composite columns with steel cores remain stiff and absorb more energy post-blast. Advanced finite element simulations and machine learning models now predict displacements, damage, and residual capacity more accurately than older methods. However, gaps remain. Current design codes of practice simplify blast loads and often do not account for localized damage, near-field effects, complex boundary conditions, or pre-existing structural weaknesses. Further research is needed on cost-effective, durable, and practical retrofitting strategies using advanced materials. This review stands apart from conventional literature reviews by combining experimental results, numerical analysis, and data-driven insights. It offers a clear, quantitative, and comparative view of RC column behavior under blast loading, identifies key knowledge gaps, and points the way for future design improvements. Full article

With the increasing demand for lightweight, high-strength, and ductile structural systems in modern infrastructure, the hybrid composite column has emerged as a promising solution to overcome the limitations of single-material members. This paper proposes an innovative variant of double-skin tubular columns (DSTCs), termed as square double-skin hybrid concrete bar columns (SDHCBCs), composed of one square-shaped outer steel tube, small-diameter concrete-infilled glass FRP tubes (SDCFs), interstitial mortar, and an inner circular steel tube. A series of axial compression tests were conducted on eight SDHCBCs and one reference DSTC to investigate the effects of key parameters, including the thicknesses of the outer steel tube and GFRP tube, the substitution ratio of SDCFs, and their distribution patterns. As a result, significantly enhanced performance is observed in the proposed SDHCBCs, including the following: ultimate axial bearing capacity improved by 79.6%, while the ductility is increased by 328.3%, respectively, compared to the conventional DSTC. A validated finite element model was established to simulate the mechanical behavior of SDHCBCs under axial compression. The model accurately captured the stress distribution and progressive failure modes of each component, offering insights into the complex interaction mechanisms within the hybrid columns. The findings suggest that incorporating SDCFs into hybrid columns is a promising strategy to achieve superior load-carrying performance, with strong potential for application in high-rise and infrastructure engineering. Full article