http://repositorio.ufc.br/handle/riufc/485 2026-06-11T10:36:34Z 2026-06-11T10:36:34Z Silva, Webert Brasil Cirilo da http://repositorio.ufc.br/handle/riufc/86397 2026-05-20T20:11:54Z 2026-01-01T00:00:00Z

Título: Analysis of the mechanical and environmental performance of concrete interlocking block pavement with by-products from the construction industry and waste from coconuts Autor(es): Silva, Webert Brasil Cirilo da Abstract: Urban road pavements made of concrete paving blocks (PB) and granular layers, such as base and sub-base, using industrial waste, are an improving sustainability goal for low to intermediate traffic areas due to the lack of helpful disposal of by-product generation. Then, this Dissertation aims to evaluate, by an innovative approach, the mechanical and environmental performance of concrete interlocking block pavement (CIBP) with by-products from the construction industry (construction and demolition waste – CDW) and waste from coconuts (coconut fibers – CF) for urban roads. Furthermore, a Life Cycle Cost Analysis (LCCA) was proposed for CIBP’s maintenance and reliability strategies. As this Dissertation was divided into four articles, a review paper was done first to compare CIBP skills with asphalt pavement (AP) for light-traffic urban roads. Regarding the second article, eighteen mixes for rectangular PB were used in Portugal with three water/cement ratios of 0.63, 0.73 and 0.83, CDW replacement rates of 50% and 75% by aggregate weight, and a CF adding percentage of 0.1% by concrete weight. Concerning the results, the CDW replacement of 75% by aggregate weight, CF adding of 0.1% and water/cement ratio of 0.73 were factors for providing PB for low-trafficked road pavements. About the third and fourth articles, a 175 m2–CIBP was built in Brazil with five experimental sections (S1, S2, S3, S4 and S5), four mixes for unistein PB with a CDW dust replacement rate of 50% by stone dust weight, and a CF dust adding percentage of 0.05% by concrete weight. Furthermore, eight granular mixtures made from non-plastic materials for base and sub-base layers were utilized with a CDW replacement rate of 100% and a CF adding percentage of 0.1% by mix weight. Regarding the third article, the air and surface temperatures from CIBP’s sections S1 to S5 were lower than the asphalt concrete from section S0. Furthermore, the CIBP construction stages showed average concentrations of particulate matter and carbon dioxide below the specifications. Concerning the fourth article, the CDW replacement of 50% by stone dust and CF adding of 0.05% were factors for concrete mixtures presented PB approved in specifications for water absorption and abrasion resistance tests. Also, the compressive and tensile strains from experimental CIBP in Brazil were lower than experimental AP in Portugal. About the LCCA on CIBP’s sections, S4 with CF and CDW materials showed costs lower than S2, S3 and S5 in 2045. These findings highlighted construction and coconut by-products for PB and sublayers as an alternative for the CIBP’s mechanical, environmental and economic feasibility. Tipo: Tese

2026-01-01T00:00:00Z Maia, Camila Lima http://repositorio.ufc.br/handle/riufc/85740 2026-04-10T11:46:12Z 2026-02-25T00:00:00Z

Título: Método integrado de análise econômica e ambiental do ciclo de vida de pavimentos aeroportuários brasileiros para apoio à tomada de decisão em manutenção e reabilitação Autor(es): Maia, Camila Lima Abstract: The growing demand for safety and operational efficiency in airports reinforces the need for more sustainable and economically efficient solutions for airport pavement management. In this context, Life-Cycle Cost Analysis (LCCA) emerges as a tool to support rational decision-making over time, allowing the evaluation of costs associated with different maintenance and rehabilitation (M&R) strategies. However, many LCCA studies focus primarily on functional parameters, such as the Pavement Condition Index (PCI), without incorporating indicators related to skid resistance, which are essential for the safety of landing and takeoff operations. In addition, LCCA does not incorporate the environmental impacts associated with M&R interventions. Given this context, this study aimed to develop an integrated economic and environmental analysis method for the design period of Brazilian airport pavements, combining Life-Cycle Cost Analysis (LCCA) and Life-Cycle Assessment (LCA), while considering functional, structural, and skid resistance parameters. Data from a Brazilian runway, provided by the National Civil Aviation Agency, covering the period from 2014 to 2023, were used, including PCI, friction coefficient, macrotexture, and the Cumulative Damage Factor (CDF), obtained using the FAARFIELD 2.1.1 software. Prediction models were developed in Python, using Gated Recurrent Unit (GRU) recurrent neural networks for the friction coefficient and macrotexture, and a deterioration rate model for PCI. The combination of performance predictions with the structural analysis performed in FAARFIELD 2.1.1 allowed the identification of M&R needs and the simulation of different intervention scenarios for time horizons of 20, 30, and 40 years through decision trees. The proposed method integrated both financial and environmental costs. The environmental impacts were estimated through an LCA conducted in the SimaPro Demo software, using the ReCiPe Midpoint (H) method, considering a functional unit of 1 m2 of runway, followed by the monetization of CO2 equivalent emissions. Additionally, a sensitivity analysis was carried out considering different discount rates. The friction coefficient and macrotexture models presented satisfactory performance, although the accuracy of the macrotexture model decreased for higher values. Preventive maintenance proved to be the most advantageous alternative in short-term horizons, reducing the Net Present Value (NPV) of M&R costs and postponing high-cost corrective interventions. However, in longer horizons, environmental impacts increased due to the recurrence of delayed corrective interventions, making the NPV of environmental costs more sensitive to the accumulation of emissions over time. Nevertheless, the NPV of total costs remained lower in the scenario prioritizing preventive maintenance, demonstrating its economic robustness. The sensitivity analysis of the discount rate showed that, over a 20-year horizon, the total NPV presented low variation, while over 30 years the difference between discount rates was moderate. Over a 40- year horizon, delayed costs—particularly environmental costs—made the total NPV more sensitive to variations in the discount rate. Overall, the proposed method demonstrates strong potential to support decision-making in defining M&R strategies. By integrating functional performance, skid resistance, structural behavior, and environmental impacts, this research contributes to more efficient and sustainable airport pavement management practices, aligned with the increasing demands for operational safety and economic rationality in Brazilian airports. Tipo: Tese

2026-02-25T00:00:00Z Aquino, Tiago Silveira de Andrade http://repositorio.ufc.br/handle/riufc/84650 2026-02-07T20:50:21Z 2025-01-01T00:00:00Z

Título: Modelo de classificação do coeficiente de atrito em pistas de pouso e decolagem com imagens aéreas e aprendizado profundo Autor(es): Aquino, Tiago Silveira de Andrade Abstract: The reliability of landing and takeoff operations depends directly on runway skid resistance, which is primarily ensured by maintaining adequate friction levels on the pavement surface —a condition that can be compromised by rubber buildup resulting from aircraft braking. Traditional methods for measuring runway friction require specialized equipment and trained personnel, potentially causing partial or total disruption of airport operations. Considering the wide availability, low cost, and increasing resolution of satellite imagery provided by Google Earth, this study proposes the development of a classification model for runway friction coefficients using such imagery, supported by Convolutional Neural Networks (CNNs). A dataset of approximately 7,000 satellite images of Brazilian aerodrome runways was assembled and linked to actual friction coefficient measurements. Three image preprocessing techniques (CLAHE, Gaussian filter, and Wavelet) and five neural network architectures (simple CNN, ResNet50, DenseNet121, InceptionV3, and VGG16) were evaluated. The combination of CLAHE and Gaussian filtering with the DenseNet121 architecture yielded the best performance, achieving over 74% accuracy in cross-validation. This result was obtained using a binary classification model based on a 0.71 threshold – a technical reference commonly adopted to distinguish between adequate and critical friction levels. External validation with unseen images from three separate field campaigns revealed spatial variations in accuracy across runway thirds and lateral zones, with increased errors near the thresholds, where rubber accumulation is more prevalent. An additional test using images captured by an Remotely Piloted Aircraft (RPA) demonstrated limitations in the model's generalization to visual domains different from those used during training. The proposed approach shows potential as a complementary tool for direct friction assessment, enabling proactive identification of runway segments at risk of reduced skid resistance and compromised pavement performance. Tipo: Tese

2025-01-01T00:00:00Z Araújo, Alessandro Macedo de http://repositorio.ufc.br/handle/riufc/84502 2026-01-27T17:48:51Z 2025-01-01T00:00:00Z

Título: Modelagem do impacto das motocicletas na fluidez do tráfego de interseções semaforizadas de Fortaleza Autor(es): Araújo, Alessandro Macedo de Abstract: Despite the significant growth in motorcycle usage in Brazilian cities and several other developing countries, traffic models still lack proper representation of this transport mode. One of the main challenges lies in modeling motorcycle infiltration behavior in queues at signalized intersections and its effects on traffic flow. This research aims to model the impacts of motorcycles on traffic flow at signalized intersections in Fortaleza, Brazil. Three specific objectives were pursued: (i) to propose an automated vehicle trajectory data collection procedure using computer vision; (ii) to define variables capable of representing the effects of motorcycles on signalized intersection traffic flow; and (iii) to estimate and analyze such effects based on real data. Data collection was carried out using drone-based aerial footage, applying the YOLOv10 object detector and the StrongSORT tracking algorithm. Automatic correction mechanisms were implemented to compensate for camera displacements due to flight instability. Case studies included intersections on two arterial roads in Fortaleza: Av. Carapinima (with and without exclusive motorcycle waiting areas, or ―motoboxes‖) and Av. Bezerra de Menezes (with motobox). The computer vision tool showed satisfactory performance for the most representative and visually distinct vehicle classes (cars, motorcycles, and trucks), and more limited accuracy for buses, vans, bicycles, and pedestrians. Validation against manual data collection using the RUBA software indicated high accuracy, with negligible differences (≤ 0.1 s) in vehicle passing times and headways. In the statistical modeling of headways for the first vehicles in the queue, the presence of motorcycles ahead of the first vehicle and between vehicles longitudinally was statistically significant, whereas motorcycles in the virtual corridor showed null or minimal impact. The estimated passenger car equivalents (PCEs) for motorcycles ranged from 0.07 to 0.09 motorcycles/PCE, reflecting the average effect of all motorcycles crossing the stop line, including those with no direct interaction with other vehicles — thus explaining the lower values compared to the literature. Scientifically, this study advances the modeling of multimodal urban traffic, particularly in contexts with high motorcycle volumes. From a practical standpoint, the findings support capacity and level of service analyses at signalized intersections and can enhance traditional traffic models, enabling more realistic and reliable analysis for decision-making at strategic, tactical, and operational levels. Tipo: Tese

2025-01-01T00:00:00Z