2031 research outputs found
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An Automated Assessment Technique for Pavement Defects Using a Laser Scanner and Deep Machine Learning
Get PDFRoads are vital arteries and main links between and within cities. They are considered the main auxiliary factor in shortening travel time and achieving users' comfort and safety. Governments strive to provide ideal conditions on the roads to achieve the highest levels of satisfaction, which are reflected in the quality of rides provided. Despite the variety of monitoring and evaluation methods, achieving the best and most accurate diagnosis of the condition of the roads and determining the severity of defects and appropriate and rapid maintenance methods are still lacking. This study aims to monitor and evaluate the state of some roads in Aswan City, Egypt, to identify defects and address them promptly. To achieve this goal, a laser scanner was used to evaluate pavement conditions by measuring the coordinates of the road surface and determining the differences in the measured values on the three axes. A built-in camera was also used in the laser device to monitor the type and severity of defects and match them with the measurements of the laser scanner device. Finally, a deep machine learning system, including LSTM, GRU, RF, SVM, and DT, was used to identify and classify the type and severity of defects. The prediction models showed significant accuracy with about 93%, 91%, 85%, 84%, and 82%, respectively. Doi: 10.28991/CEJ-2025-011-03-015 Full Text: PD
Advanced Reclaimed Asphalt Pavement Treatment for Sustainable Pervious Concrete: Optimizing Strength, Hydraulic Performance and Long-Term Durability
Get PDFThe increasing depletion of natural aggregates and escalating construction waste necessitate the implementation of environmentally friendly substitutes in concrete production. This study explores the incorporation of treated Reclaimed Asphalt Pavement (RAP) as an eco-efficient alternative to traditional coarse aggregates in pervious concrete (PC) matrices by evaluating its structural integrity, permeability, durability, and microstructural characteristics. A comprehensive multi-stage treatment process involving solar heating, natural oxidation, and mechanical roughening was employed to enhance aggregate bonding and bitumen reduction. The treatment of RAP was conducted for three treatment durations: 0-month, 12 months, and 24 months. Coarse aggregates were substituted with 0%, 25%, 50%, 75%, and 100% RAP by weight, and all mixtures were cured for 90 days. The investigation focused on evaluating essential functional characteristics, including density, porosity, hydraulic conductivity, compressive and flexural responses, as well as durability under abrasion and chemical exposure to sulphate and chloride environments. Microstructural analysis utilizing Energy Dispersive X-ray Analysis (EDAX) demonstrated a substantial reduction in bitumen content, as evidenced by a declining carbon peak with increased treatment duration. Additionally, Scanning Electron Microscopy (SEM) micrographs revealed fewer voids, increased C-S-H formation, and improved bonding, with minor Interfacial Transition Zone (ITZ) variations across 12-month and 24-month treatments. The findings highlight that extended RAP treatment significantly improves density, reduces porosity, enhances compressive and flexural strength, and lowers permeability. Furthermore, 24-month treated RAP demonstrated superior durability, exhibiting enhanced abrasion and chemical resistance due to improved aggregate cohesion and matrix integration. This study establishes that pervious concrete with more than 50% RAP content, previously considered unviable, is structurally feasible when suitable treatment and gradation techniques are used, thereby advancing sustainable construction materials. Doi: 10.28991/CEJ-2025-011-04-019 Full Text: PD
Examining the Compressive Behavior of SFRC and SCC Using Finite Element and Experimental Methods
Get PDFThe compressive behavior of various kinds of concrete, including plain concrete, steel fiber-reinforced concrete (SFRC), and self-compacting concrete (SCC), was investigated experimentally in this paper and simulated using finite element analysis through ABAQUS software. Thirty specimens were cast and tested with two concrete compressive strengths (20 and 30 MPa). Steel fibers were added at volume fractions of (0, 0.4, and 0.75)%, while SIKA-VISCOCRETE-5930 IQ was incorporated at (0.8 and 1.8)% by weight of cement. The results showed that the compressive strength of the tested specimens increased with the increase of fibers and SIKA-VISCOCRETE-5930 IQ dosages. The FEA results exhibited a good agreement with those from the experimental work in terms of the stress-strain relationships for plain, SFRC, and SCC. A Student's t-test was performed on both experimental and FE analysis outcomes, and the difference among them was found to be statistically insignificant. The accuracy of numerical modeling in predicting concrete behavior under compression is supported by the findings of this study, and the effectiveness of steel fibers and SIKA-VISCOCRETE-5930 IQ in developing the compressive strength of concrete is also highlighted. Doi: 10.28991/CEJ-2025-011-03-017 Full Text: PD
Street Networks and Urban Sustainability by Quantifying Connectivity, Accessibility, and Walkability for Resilient Cities
No full textStreet networks are crucial in shaping the quality of urban life. Through their impact on mobility and social interaction, they play a critical role in shaping how people move around the city and determine the connectivity, accessibility, safety, and convenience of different areas. Thus, it is essential to develop a systematic understanding of street networks to create livable, sustainable, accessible, and equitable cities. The aim of this study is to analyze and develop the role of street networks in shaping urban mobility, connectivity, and accessibility, and thereby enhance sustainable urban living by creating people-centric cities. Quantitative techniques and measures are employed to examine urban structure metrics to understand both physical and spatial characteristics at micro and macro scales. Three primary parameters for the configuration of street patterns - grid pattern ratio (GPR), pedestrian route directness factor (PRD/PRF), and ped-shed (PS) and effective walking area (EWA) - are selected to compute the formational attributes of selected streets in Baghdad, Iraq. The evaluation employs different arithmetic methods linked with a Geographical Information System (GIS) to quantify and compare two examined areas, and the results reveal a contradiction in the spatial configuration of the sample street patterns. From these findings, the paper offers specific recommendations and urban design guidelines to improve the quality of similar urban areas. The paper concludes that in-depth knowledge of a street’s role in its urban context helps to optimize spatial configuration processes in the built environment
Effect of Signal Filtering on Metaheuristic-Based Structural Parameter Identification in Shear Building Models
No full textThis study evaluates the effectiveness of three metaheuristic algorithms—Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO)—for identifying lateral interstory stiffness and the modal damping ratio in two-dimensional shear building models. The main objective is to estimate these parameters using time-domain displacement, velocity, and acceleration data, assuming known floor masses and unknown input excitation that primarily excites translational vibration modes. Three structural configurations with 2, 3, and 5 stories are analyzed to assess the scalability and robustness of each algorithm. To assess the effect of signal filtering on the performance of the algorithms, white noise is added to the synthetic response data at six levels ranging from 0% to 5% of the root mean square (RMS) amplitude. A sixth-order Butterworth filter is applied to evaluate the effect of signal preprocessing, and results obtained with and without filtering are compared. The results show that all three algorithms achieve acceptable levels of accuracy, even under noisy conditions. Filtering consistently improves identification accuracy, especially in high-noise conditions. In the most challenging case (5% noise, 5-story model), the average identification errors were 5.042% for GA, 5.106% for DE, and 5.035% for PSO. The findings underscore the practical value of integrating signal filtering with metaheuristic optimization for robust structural system identification in noise-contaminated environments. To account for the random nature of the algorithms, all results reported correspond to the average of 10 independent runs per identification scenario to ensure reliable performance evaluation
Analysis of Influence Factor of Soil-Structure Interaction Considered in Pile Analysis using Finite Element Analysis
Get PDFThis study evaluates two often‑overlooked factors in pile analysis (passive earth pressure and the pile-soil contact method) and quantifies their combined influence on load–settlement response, shaft friction, and stress distribution. Conventional finite element analyses rarely consider both passive earth pressure and pile–soil slip simultaneously. This research quantifies the influence of these two factors on the load–settlement behavior, shaft friction, and stress transfer mechanisms of a single square pile. A laboratory model test was conducted using a 50 × 50 × 150 mm model pile embedded in loose sand with a relative density of 25%, and the same conditions were replicated using a 3D FEM model in ANSYS. The soil was modeled using the Mohr–Coulomb model, with parameters obtained from direct shear tests, and the pile was defined as a linear elastic material. The lateral boundaries were defined under two conditions: a general roller-type boundary and a new boundary condition incorporating depth-dependent passive earth pressure. Interface behavior was analyzed with both bonded and frictional contacts. The passive earth pressure boundary condition reduced post-yield settlement error from 22% to 6% and increased calculated shaft friction by 4%, resulting in a post-yield settlement curve that closely matched the experimental results. Bonded contact overestimated the bearing capacity by 17% and produced unrealistic stress concentrations, while Frictional contact accurately reproduced the observed slip surface and ultimate bearing capacity within a 3% margin of error. Parametric analysis revealed that the elastic modulus governed pre-yield stiffness, whereas the friction coefficient primarily influenced plastic deformation behavior. By combining the depth-dependent passive earth pressure boundary with experimentally calibrated frictional contact, this study successfully captured both lateral confinement effects and interface slip, which are typically analyzed separately. Consequently, the predictive accuracy for settlement and bearing capacity of friction piles in sandy soils was empirically improved
The Use of Electronic Initiation Systems for Wall Control Blasting at an Open Pit Mine
No full textThis study investigates the effectiveness of electronic initiation systems (EIS) for wall control blasting in open-pit mining, with a specific focus on their influence on ground vibrations and rock fragmentation. The primary objective of the study is to evaluate whether EIS can achieve comparable or superior results in fragmentation quality while reducing seismic impact compared to non-electric initiation systems (NEIS). Experiments were conducted at an open-pit gold mine. During the experiments, EIS and NEIS were used. There was assessed seismicity of each blast during the experiments. Peak Particle Velocity (PPV) was measured at multiple points near the pit benches, and fragmentation of the blasted rock mass was analyzed through visual inspection and image analysis techniques. A statistical evaluation of the collected data revealed that EIS provided similar fragmentation outcomes while significantly reducing PPV values. Due to the ability to precisely time blasts and allow for optimized delay sequences and energy distribution, EIS can reduce blast vibrations. These findings suggest that EIS is a viable and efficient solution for wall control blasting, particularly in cases where pre-splitting or other conventional techniques cannot be applied due to geological or operational conditions. In this study, for the first time,the PPV was measured at the closest distance (6.57 m to the blasted block). The authors tried to find out the combination of two controversial outcomes of blasting work, rock fragmentation and ground vibrations, in this study
Mechanical Characteristics of Prestressed Concrete Cylinder Pipe Strengthened by EPS and CFRP Liner
No full textPrestressed concrete cylinder pipe (PCCP) has been applied in many large-scale hydraulic engineering projects around the world. And the prestressed wire breakage is the most common form of PCCP damage. Traditional carbon fiber reinforced polymer (CFRP) liner techniques fail to fully exploit the tensile performance of CFRP. Therefore, the method of using EPS cushion and CFRP liner to strengthen the PCCP with broken wire is proposed in this study. To clarify the effect of the proposed method, a finite element three-dimensional model is established and validated using experimental data. Subsequently, the effects of EPS thickness, CFRP thickness, and wire breakage ratio on the stress-strain response of the PCCP are analyzed. Based on different failure modes of the pipe, the influence of EPS and CFRP thickness on the internal pressure bearing capacity is discussed. The study reveals that the synergistic action of the EPS cushion can effectively enhance the internal pressure bearing capacity of the PCCP. As the thickness of EPS cushion and CFRP increases, the bearing capacity almost linearly increases. Under the influence of internal pressure, visible cracks first appear in the concrete core, followed by yielding of the steel cylinder, and finally the steel wire stress reaches its ultimate strength
Effect of Air Pressure on Changes in Parameters and Soil Settlement Behavior in Very Soft Soils
Get PDFAn effective soil improvement method is essential in soft soil due to the poor bearing capacity for construction loads. To address the challenge, the use of the staged air pressure method with Suction Assisted Vacuum Preloading (SAVP) has shown significant potential when applied through Geosystem Air Booster Vacuum Preloading (GAVP), specifically designed with a sensor system as a real-time measuring tool for soil parameter changes. Therefore, this research aims to examine the effectiveness of the SAVP method in relation to the discharge of drained water from prefabricated vertical drains (PVD) on changes in soil parameters due to air pressure and vacuum using the GAVP tool. The method used five PVDs in large-diameter soil sample tubes, applying air pressure and vacuum simultaneously and selectively. This experimental setup was designed to examine the fundamental aspects of soil parameter changes, namely permeability, consolidation, and volume compression coefficient. The results showed that soil parameters during testing interacted with each other, where air pressure balanced with vacuum caused changes and optimized settlement and consolidation efficiency. Decreasing air pressure enhanced vacuum performance, causing a corresponding rise in soil settlement and consolidation degree. However, increasing air pressure decreased soil settlement and the degree of consolidation
Projections of Land-Cover Change in a Tropical High-Andean Lake
Get PDFLand use and land cover change is one of the main drivers transforming high Andean ecosystems in Colombia. This study examines the spatial dynamics of land use in the La Cocha Ramsar Wetland between 1989 and 2020 and projects land cover scenarios to the year 2050 using spatial modeling techniques. Land cover maps for 1989 and 2020 were developed using satellite imagery and photo-interpretation, following the CORINE Land Cover methodology adapted for Colombia. A transition matrix and change indicators defined by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) were used for multitemporal analysis, allowing the identification of processes such as forest fragmentation and recovery, agricultural expansion, and the spread of pastures. Future projections were modeled with the Land Change Modeler (LCM) module in the IDRISI Selva software, incorporating biophysical and socioeconomic variables with significant association (Cramér’s V > 0.4). Eight dominant transitions were identified, and change potential maps were generated. The model was validated through random field sampling and a confusion matrix analysis, yielding a Kappa index of 0.76, indicating strong agreement between simulated and observed data. Results show that 91.06% of the area remained unchanged, while 8.94% underwent transformations attributed to human activities. A net increase of 66.75 ha in dense forest is projected by 2050, along with growth in fragmented forest areas and agro-pastoral mosaics