2031 research outputs found
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Development of Oscillating Water Column Breakwater Model
Get PDFIntegrating coastal protection functions and wave energy conversion makes the OWC breakwater an environmentally friendly and material-efficient innovation compared to conventional breakwaters. This research aims to determine the wave runup height on the Sloped side of the OWC breakwater model and its internal pressure. Utilizing theoretical approaches, a 1:20 scale laboratory model, dimensional analysis, and parameter relationships, the study investigates the effects of wave interaction, model geometry, and water depth. The analysis reveals a positive correlation between the combined parameter value (𔜓) and relative pressure (P/Ïghs), highlighting the consistent influence of these parameters on pressure behavior. Results show that a lower slope angle increases pressure, while variations in inlet opening sizes (hs) significantly affect wave runup (Ru/Hi) and run-down (Rd/Hi). Larger inlet openings generally reduce the wave runup effect, though the magnitude of this impact depends on the slope angle. The optimal configuration for the OWC breakwater model is identified as an inlet opening size between 5 cm with a slope angle of 45° to 60°, providing relatively higher pressure while maintaining stability. This combination improves the system's efficiency in absorbing and using wave energy. Doi: 10.28991/CEJ-2025-011-04-02 Full Text: PD
Web-Crippling Behaviour of Cold-Formed Screw Fastened Rectangular Hollow Flange Z-Section Beams Under Two-Flange Load Cases
No full textThis study investigates to update the web-crippling coefficients of cold-formed screw-fastened hollow flange Z-section (SFHZ) beams under End-Two-Flange (ETF) and Interior-Two-Flange (ITF) loading conditions. As coefficients are available in AISI standards to estimate the web crippling capacity of Z-sections, experimental program is carried out on 48 number of SFHZ specimens. An extensive parametric study considering the effects of web slenderness, material strength, and support length is conducted for 240 finite element models. Both experimental results and Finite Element Analysis (FEA) were used to predict web-crippling capacities and verified with current AISI predictions. The findings reveal that existing specifications are un-conservative for both ETF and ITF load cases. The parameters such as web height-to-thickness, inside bend radius-to-thickness, and bearing length-to-thickness ratios are the key factors influencing the prediction of web crippling capacity of SFHZ sections. As a result, the study proposes updated web-crippling coefficients that offer improved accuracy in predicting SFHZ section performance under two-flange loading conditions
Soil Erosion Risk and Mitigation Strategies in Steep and Complex Forest Ecosystems
No full textThe soil erosion risk on the slopes in Luong Son District, Hoa Binh Province, Vietnam, was determined to inform sustainable land management and conservation planning. Remote sensing and geographic information system (GIS) technologies were integrated with the universal soil loss equation (USLE) model to generate thematic maps of rainfall erosivity (R), soil erodibility (K), topographic factors (LS), and vegetation cover. These maps were combined to produce a comprehensive soil erosion risk map. The results showed that 65.09% of the district (23,747.61 hectares), mainly flat and midland areas, had no erosion risk. Light, moderate, and severe erosion affected 19.95%, 7.61%, and 7.35% of the region, respectively. Higher erosion risk is concentrated in mid-level mountainous and limestone regions, characterized by steep slopes and sparse vegetation. These findings highlight the influence of slope gradient and length on erosion severity and spatial patterns. Remote sensing, GIS, and USLE were integrated to spatially assess soil erosion, providing a scientific basis for targeted interventions, such as reforestation and terrace farming. This study contributes to gaps in the literature by comprehensively analyzing spatial soil erosion risk and providing practical recommendations for mitigating soil erosion in vulnerable landscapes and supporting sustainable land use planning under climate change pressures
Examining Social Acceptability of Solar Innovations in Smart Cities
Get PDFObjective: The global challenge of climate change and the need for energy conservation have prompted a reevaluation of energy sources and policies worldwide. This study aims to investigate the societal acceptability of solar photovoltaic (PV) systems among citizens of smart cities, an aspect crucial yet underexplored in the context of renewable energy technologies. Methods/Analysis: A comprehensive survey was conducted involving 560 respondents to assess public perceptions, attitudes, and behaviors toward solar PV systems. The study also examined the moderating effects of area (urban/rural), gender, trust, and duration of use (experience) on societal acceptability. Findings: The results show that both independent and moderating variables significantly influence the social acceptability of solar innovations in smart cities. Key factors identified include the user-friendly design of solar systems, effective awareness campaigns highlighting their benefits, and compatibility with existing technologies. These elements are crucial in fostering positive attitudes and intentions towards the adoption of solar energy. Novelty/Improvement:This research provides valuable insights for policymakers, energy planners, and researchers, emphasizing the importance of considering demographic and experiential factors in policy-making. The findings suggest that societal acceptance of solar PV systems can be enhanced by targeting area-specific needs, leveraging trust, and promoting the benefits of prolonged usage experience. Doi: 10.28991/CEJ-2025-011-02-016 Full Text: PD
Experimental and Numerical Modeling for the Impact of Freezing Temperatures Reduction on the Mechanical Properties of Frozen Sand
No full textArtificial ground freezing (AGF) is an approach that uses heat extraction to congeal in situ soil to improve soil quality temporarily. This technology is ecologically sustainable and has minimal adverse effects on soil and groundwater. AGF is widely used in subterranean construction, providing temporary support and groundwater sealing. Nevertheless, precisely simulating the mechanical characteristics of frozen soils with dependable constitutive models presents significant challenges for scientists and engineers. Frozen soil, consisting of ice, liquid water, solid particles, and pore air, is a distinctive geological substance with heightened sensitivity to temperature and external influences. Experimental studies have shown that the mechanical properties of frozen soils are significantly influenced by temperature, confining pressure, strain rate, stress path, and stress level. Numerical simulation offers a superior approach for forecasting soil qualities, particularly in artificial frozen soil technologies for excavations like tunnels and mines. This research examines the impact of varying freezing temperatures and pressures on soil characteristics. This research employs experiments and numerical analysis using Mohr-Coulomb and hardening soil models. The experimental results indicated that the elastic modulus almost increases linearly by a rate of 90000 kN/m² with 1ºC drops below 0ºC. The unconfined compressive strength increased by 2068 kN/m² for each 1°C decrease from 0 to -2°C. Within the temperature range of -2°C to -10°C, the rate of increase is 529 kN/m². The apparent cohesion increased by 238.75 kN/m² for each 1°C decrease from 0 to -2°C. Within the temperature range of -2°C to -10°C, the rate of increase is 66.25 kN/m². A nonlinear association between temperature decrease and tensile stress rise was observed. Numerical analysis shows that as confined pressure increases and temperature decreases, materials can either get stronger or weaker; the Mohr-Coulomb and HS models show stress-strain curve behavior that matches what was found in experiments
Modeling of Geomechanical Processes from Open Pit to Underground Mining with Complex Morphology
Get PDFThe relevance of this study is the need to optimize the transition from open-pit to underground mining in mines with complex deposit morphologies, such as the Akzhal Mine. This is essential to ensure the safety of mining operations and to prevent adverse manifestations of rock pressure and mass cave-ins when changing the type of mining. This study aimed to develop a geomechanical basis for selecting an optimal mining system for the transition from open-pit to underground mining. Particular attention is paid to rock mass stability and its behavior during mining operations, which makes it possible to optimize the parameters of the mining system by considering the characteristics of a mine with a complex deposit morphology. This study used methods to assess the strength of the rock mass, including the concept of the geological structure of the natural environment, the methodology of determining the structural weakening coefficient, and the determination of the rock mass deformation modulus using the fracturing ratio and stability of the rock mass coefficient with an analytical functional relationship of geo-structural factors. The study results made it possible to systematize the rock mass by stability categories and proposed recommendations for the safe operation of deposits during the transition to underground mining, on the choice of mining system, and on the design of its elements. The novelty of this study lies in an integrated approach for predicting the behavior of rock mass and selecting the optimal mining system, which makes it possible to improve the safety and efficiency of production under difficult geological conditions
Gray Correlation Coefficient Analysis on the Mechanical Properties of Nylon Fiber Reinforced Recycled Aggregate Concrete with GGBS
Get PDFRapid urbanization and infrastructure development intensify the demand for aggregate in concrete production. One efficient technique to reduce demolition and construction waste and produce sustainable concrete is using recycled aggregates. However, previous studies on recycled aggregate concrete (RAC) demonstrated that the mechanical characteristics are remarkably affected due to the adhered previous layers of mortar with the aggregate. Incorporating fibers and supplementary cementitious materials (SCMs) in the concrete mix is a common practice that enhances the mechanical characteristics of concrete and ensures sustainability by reducing carbon footprint. Previous studies lack the combination of nylon fiber (NF) and ground granulated blast furnace slag (GGBS), a by-product of the iron industry and treated as solid waste. Moreover, the research regarding the combined effect of the SCMs and fiber needs to cover the sensitivity of these constituents individually, according to statistical analysis. Hence, the main purpose of this research is to deal with the influence of incorporating NF and GGBS on the mechanical properties of concrete where recycled concrete aggregate was used. Moreover, the sensitivity of the properties with the percentage of replacement of binder and volume fraction (Vf) of nylon fiber was assessed using the Gray correlation coefficient. Compressive strength was dropped by around 10% when recycled material was substituted for natural aggregate. In contrast, adding 0.1% nylon fiber and 10% cement replacement with GGBS increased the crushing strength by about 10.9% compared to the conventional mix. In Gray's analysis, flexural toughness ranked higher in correlation with the controlling factors. Considering the environmental sustainability and the synergetic effect of nylon fiber and GGBS on mechanical properties, recycled aggregate is employable in concrete compared with the conventional concrete of natural stone aggregate. Doi: 10.28991/CEJ-2025-011-03-07 Full Text: PD
Critical Construction Readiness Factors for Bridge Projects
Get PDFEgyptian investment in infrastructure projects is considerable, especially in bridge construction projects that commonly face delays, cost overruns, rework, and poor productivity. A proper construction readiness (CR) assessment can enhance project performance. This study aims to identify the critical factors that impact the CR of bridge projects in Egypt. Through a literature review and a pilot study with ten highly experienced professionals, a list of 43 construction readiness factors (CRFs) was prepared. To quantitatively rank these CRFs and identify the critical ones, a questionnaire was administered through structured interviews with 92 project managers and engineers experienced in bridge construction projects in Egypt. The participants represented the perspectives of contractors, owners, and consultants. A CRF with a normalized mean score greater than or equal to 0.5 was classified as a critical construction readiness factor (CCRF). For these CCRFs, agreement analysis among contractors, owners, and consultants was conducted using the Kruskal-Wallis test. The correlation strength was also investigated using Spearman's correlation. In total, 16 CCRFs were identified, with the top five: verification of underground utility locations, completion of land surveying work, issuance of clear and sufficient construction drawings, adequate geotechnical investigations, and obtaining all necessary permits and approvals from local authorities. This study provides practitioners with critical factors necessary for assessing the CR of bridge projects in Egypt. From an academic standpoint, it enhances understanding of CR, which is rarely discussed. Doi: 10.28991/CEJ-SP2024-010-015 Full Text: PD
Machine Learning and the GR2M Model for Monthly Runoff Forecasting
Get PDFThis article presents the results of an analysis of monthly rainfall into monthly runoff using Machine Learning algorithms, including Multiple Linear Regression, Multilayer Perceptron, and Support Vector Machine, which were compared with the GR2M hydrologic model to identify the most suitable approach for rainfall-runoff analysis in watersheds in the lower southern region of Thailand. This region is characterized by its unique geographic location at the border between Thailand and Malaysia. It faces challenges due to uncertainty in rainfall data, measured only on the Thai side, leading to a lack of corresponding data from Malaysia. The analysis found that the Machine Learning Support Vector Machine algorithm consistently provided the most accurate results across all sub-basins. Sub-basin TU02 achieved an MAE of 2.63 mm/month, while sub-basin X.119A had an MAE of 68.10 mm/month, sub-basin X.184 had an MAE of 145.05 mm/month, and sub-basin X.274 had an MAE of 66.08 mm/month. This research demonstrated the utility of advanced algorithms in rainfall-runoff analysis for areas with partial or incomplete data coverage. The findings confirm that the Machine Learning Support Vector Machine algorithm outperformed the Hydrologic Model (GR2M) in terms of accuracy and reliability. Therefore, this study concludes that applying the Machine Learning Support Vector Machine algorithm is an optimal approach for runoff prediction in the southern region of Thailand and provides a framework for potential applications in other areas with similar data and geographic challenges. Doi: 10.28991/CEJ-2025-011-01-022 Full Text: PD
A Study of Biomass Concrete Reinforced with Fiber Composites to Enhance Impact Load Capacity
Get PDFThis research investigates the energy absorption from impact forces of steel reinforced concrete using fly ash obtained from agricultural processes, reinforced with glass fiber-reinforced polymer (GFRP) bars, compared to steel reinforcement. The reinforcement pattern involves incorporating GFRP bars into a square grid pattern of 4, 9, and 12 openings within bio-steel concrete with dimensions (W í— L í— H) of 40 í— 40 í— 10 cm. The testing is conducted using a Drop Test impact testing machine with a 30 kg hammer head at a velocity of 7 m/s, employing two different hammer head configurations: flat and 45-degree angled, to study energy absorption (Ea), specific energy absorption (Es), and the pattern of deformation resulting from impacts. The study finds that CBRHA-10-fiber A concrete exhibits higher energy absorption and specific energy absorption compared to steel-reinforced (CBRHA-10-steel A) concrete in the same configuration by 18.82% and 26.83%, respectively, in the flat-headed hammer impact configuration. Similarly, in the 45-degree angled hammer head configuration, CBRHA-10-fiber A concrete demonstrates superior energy absorption and specific energy absorption compared to steel reinforcement in the same configuration by 6.10% and 14.92%, respectively. In conclusion, bio-steel reinforced concrete with glass fiber-reinforced polymer (GRFP) reinforcement exhibits good load-bearing capacity and suitability as an alternative to steel reinforcement in future applications. Doi: 10.28991/CEJ-2025-011-02-020 Full Text: PD