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Stability Analysis of Dam with Asphalt Core in Static and Pseudo-Static Conditions
No full textManikin Dam was constructed to address the issue of raw water shortage in Kupang Regency and Kupang City. However, there were challenges due to clay materials that did not meet the required specifications. Therefore, this study aimed to use asphalt core design as an alternative by analyzing the stability of the embankment body under both static and pseudo-static conditions. To achieve the aim, the Bishop method was applied using the GeoStudio SLOPE/W application, along with manual calculations. The results showed that the safety factor (SF) at the end of construction without seismic loads met the minimum value of 1.300. Under various water level conditions (FWL, NWL, LWL), SF consistently met the minimum required value of 1.500. Furthermore, the seismic analysis considered both operational base earthquakes (OBE) with a return period of 100 years and maximum design earthquakes (MDE), which had a return period of 5,000 years. Even under OBE and MDE seismic loading conditions, SF exceeded the minimum required value. This implied that the use of an asphalt core could be considered safe in terms of preventing potential landslides under both static and pseudo-static conditions. Based on this outcome, asphalt core became a practical alternative for future dam construction, particularly in areas where clay could be scarce or unstable for technical reasons
Statistics on Small Networks in Construction Design Offices
No full textThis study explores communication structures in construction design offices using social network analysis (SNA) to compare directed and undirected networks. The objective is to understand how these network types influence hierarchy, information flow, and collaboration within small design teams. Data were collected from nine construction design offices, constructing both directed and undirected networks based on survey responses. Various graph theory metrics, including clustering coefficient, network diameter, centrality, and connectivity, were analyzed to assess communication efficiency. The results show that directed networks emphasize hierarchical structures with limited reciprocal exchanges, while undirected networks confirm mutual interactions, fostering collaboration. Despite variations in size, most networks exhibit small-world properties, indicating that key individuals act as bridges, ensuring effective communication. These findings highlight that network structure, rather than size, plays a crucial role in team coordination. This study contributes to Architecture, Engineering, and Construction (AEC) research by providing insights into optimizing team dynamics, balancing hierarchical control with flexible collaboration, and improving project management strategies. Doi: 10.28991/CEJ-2025-011-03-02 Full Text: PD
Flexural Behaviour of Prestressed Post-Tension Voided Biaxial Slab Under Uniformly Distributed Load
No full textThis study examines the flexural behavior of prestressed post-tensioned voided biaxial slabs under uniformly distributed loads (UDL) to evaluate structural performance, quantify material efficiency, and validate finite element models. Four full-scale slabs”solid and voided, with and without post-tensioning (PT)”were experimentally tested under UDL using a multi-level steel beam system to simulate uniform loading. Parameters such as crack initiation, deflection, and failure modes were monitored. Nonlinear finite element analysis (FEA) in ANSYS, employing Solid65 and Link180 elements, replicated material behavior and boundary conditions. The results showed that PT-voided slabs retained 96% of PT-solid yield capacity while reducing concrete volume by 22%, achieving a 21% self-weight reduction. Post-tensioning enhanced stiffness by 21% compared to non-PT voided slabs and delayed crack initiation. FEA predictions closely matched experimental data, with ≤10% deviation in load-deflection responses and consistent crack patterns. The novelty lies in demonstrating that PT effectively mitigates stiffness reductions (6% vs. PT-solid) caused by cuboidal voids, enabling high-performance, lightweight designs. This integration of PT with voided systems offers a sustainable solution, reducing material usage by up to 22% while maintaining structural integrity, thereby advancing eco-efficient construction practices. Findings provide critical insights for optimizing voided slab applications in modern infrastructure. Doi: 10.28991/CEJ-2025-011-05-09 Full Text: PD
Mechanical and Physical Evaluations of Fine Sand-RAP Blends for Subgrade and Subbase Applications
No full textFine sand has a low load-bearing capacity and tends to deform easily, limiting its use in road construction. Recycled asphalt pavement (RAP) may offer a sustainable solution to improve these properties. Accordingly, the primary objective is to assess how varying RAP content affects the gradation, compaction, bearing capacity, and California Bearing Ratio (CBR) of sand-RAP blends. RAP contents ranged from 0% to 100% by weight. The results show that integrating RAP improves sand gradation, making it suitable for subgrade layers, with mixtures containing 40%-60% RAP meeting subbase requirements. CBR increases significantly with RAP, from 8.78% in fine sand to 41.67% at 100% RAP. Dry density also improves by 12%-16% with 40%-60% RAP, while optimum moisture content (OMC) decreases by over 30%. Bearing capacity increases significantly with RAP content. At 40%-60% RAP, increases range from 299.53% to 411.83% (Dr = 60%) and 243.69% to 318.43% (Dr = 90%). RAP inclusion enhances stiffness, peaking at 530% (Dr = 60%) and 326% (Dr= 90%) between 40%-60% RAP. Initial gains are steady at 10%-30% RAP, but diminishing returns occur beyond 50% RAP. Generally, notable performance is achieved at 40% RAP, while 50% RAP ensures optimal stiffness and structural integrity, with diminishing returns afterward. Doi: 10.28991/CEJ-2025-011-05-017 Full Text: PD
Assessing the Effects of Freeze-Thaw Cycles and Traffic Load on Pavement Resilience
No full textThis study examines the impact of freeze-thaw cycles on the performance of flexible pavements, focusing on a specific road in Morocco. The primary objectives are assessing pavement resilience under varying climatic conditions and investigating the combined effects of freeze-thaw cycles, traffic speed (ranging from V1 to V4), and temperature fluctuations (from T1 min to T2 max) on pavement durability and structural integrity. The methodology involves comprehensive data collection on traffic loads, local climate conditions, and soil characteristics. These data inform the pavement design process, helping determine the optimal thickness and selection of materials to withstand environmental stresses. The study also examines the effects of freeze-thaw cycles, assessing frost-resistant materials and comparing frost indices to enhance durability. Advanced modeling techniques simulate pavement performance under real-world conditions, optimizing resilience. The methodology investigates the interaction between traffic speed and pavement behavior, focusing on strain (εz), displacement (Uz), and stress (σz). The findings reveal a significant correlation between freeze-thaw cycles and pavement deterioration, with strain and displacement increasing as traffic speed decreases while stress intensifies with higher traffic speeds. This research provides valuable insights into the effects of traffic speed on flexible pavements, contributing to more effective maintenance strategies and design solutions for durable, weather-resilient roadways. Doi: 10.28991/CEJ-2025-011-04-024 Full Text: PD
Energy Optimization in Residential Buildings: Evaluating PCM-CLT Wall Systems Across U.S. Climate Zones
No full textBuildings consume approximately 43% of their electricity for space heating and cooling, emphasizing the need for energy-efficient solutions. Among the strategies to reduce this demand, phase change materials (PCM) have been recognized for their potential to enhance thermal performance. While PCM has been extensively studied in building envelopes, its integration with cross-laminated timber (CLT) remains unexplored. Additionally, the optimal placement of PCM within wall assemblies lacks consensus, as previous studies have reported inconsistent findings. This study addresses these research gaps by investigating the performance of PCM-integrated CLT (PCM-CLT) wall systems across 17 climate zones in the United States. Using EnergyPlus simulation, five wall configurations were analyzed, including three PCM-CLT configurations with PCM positioned at different locations within the assembly. The results demonstrate that the PCM-CLT system significantly enhances energy efficiency, achieving cooling energy savings of up to 72.48% and heating energy savings of up to 96.94% in certain locations. Moreover, the findings reveal that placing PCM on the interior side of CLT walls consistently outperforms other configurations across all climate zones. Furthermore, PCM-CLT walls help reduce peak energy loads, alleviating stress on power grids. This research contributes to enhancing building energy performance through PCM-CLT integration, providing valuable insights for both retrofitting and new construction, and advancing sustainable building design. Doi: 10.28991/CEJ-2025-011-05-05 Full Text: PD
Machine Learning and the GR2M Model for Monthly Runoff Forecasting
No full textThis 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
Landslide Susceptibility Assessment Using Combined TRIGRS and Flow-R
No full textLandslides were addressed as one of the natural hazards that can create extensive disasters. Effective assessment to locate potential landslide events is crucial for planning and risk mitigation. This study, which is located in the Sumitro watershed, Kulon Progo, Yogyakarta, presents a novel approach to landslide susceptibility assessment by integrating the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) with the Flow-R model. Five key parameters, namely slope, soil properties, groundwater level, soil thickness, and rainfall, were used to create the landslide susceptibility zonation. TRIGRS was used to identify the landslide initiation, while Flow-R was used to create the run-out area. The result was then validated through statistical evaluation using Area Under Curve (AUC) based on the landslide inventory. Results show that landslide susceptibility zonation created from TRIGRS alone resulted in an AUC value of 0.679, while the combination of TRIGRS-Flow-R susceptibility zonation shows a better AUC value of 0.728. The increase of the AUC value of almost 0.05 has enhanced the correlation between the landslide susceptibility zonation and landslide inventory from "acceptable” to "excellent” correlation. This result demonstrates that integrating Flow-R with TRIGRS improves the performance of landslide susceptibility zonation. This study offers a new perspective on creating landslide susceptibility zonation by combining two methods, yielding more reliable results. Doi: 10.28991/CEJ-2025-011-03-020 Full Text: PD
Methodology of Studies for Construction of Water Reservoir Dams in Countries Prone to Landslide Hazard
No full textConstruction of water reservoirs often has significant geomorphological and environmental impacts, particularly in regions prone to landslides. This study addresses the critical issue of slope stability in the context of the construction of a planned water reservoir in Astghadzor, Gegharkunik Marz, Armenia. The primary objectives are to investigate the stability of slopes, identify potential landslide triggers, and evaluate seismic impacts using advanced numerical modeling techniques. GeoStudio SLOPE/W software was employed, with calculations performed using the Morgenstern-Price and Spencer methods, which ensure rigorous equilibrium conditions for mountainous terrains. Field investigations and laboratory tests provided input data, forming an engineering-geology model for the analysis. The results reveal that the slopes remain stable under static loading conditions; however, seismic loading renders them unstable, particularly in soils related to Category III. Stability factors decrease by approximately 68% under adverse soil conditions. These findings underline the necessity for incorporating advanced stabilization measures and soil-specific interventions into the design of water reservoir dams. This study contributes to optimizing design methodologies, improving the safety of reservoirs, and guiding future research in landslide-prone and geologically challenging regions. Doi: 10.28991/CEJ-2025-011-01-016 Full Text: PD
Fire Resistance of Crushed Brick-Based Alkali-Activated Mortars
No full textThis study investigates the fire resistance of alkali-activated mortar incorporating crushed brick as both a precursor and aggregate. The optimal alkaline activator was identified as a combination of KOH and Na₂SiO₃, with a curing period of 3 days at 70 °C. Two mortar series were produced, each exhibiting different workability: on series comprised cement mortar, while the other included three alkali-activated mortars, with variations in the molarity of the KOH solution. The mortar samples were subsequently heated to 600°C, and their mechanical properties and mass were measured to determine residual values/losses. The best-performing alkali-activated and cement mortars underwent visual assessments of cross-sections to evaluate the impact of mortar consistency on fire resistance. Additionally, changes in mineralogy and microstructure were followed by instrumental techniques to clarify the results before and after heating. While cement mortars had superior mechanical properties at room temperature, alkali-activated mortars retained a higher percentage of their mechanical properties post-heating, demonstrating better fire resistance. Mortars with plastic consistency showed better fire resistance than those with fluid consistency. These findings suggest that brick-based alkali-activated mortars could be developed into fire protection boards for structural members. Doi: 10.28991/CEJ-2025-011-04-05 Full Text: PD