Volume 17 Issue 4

S.No.	Article Title & Authors (Volume 17, Issue 4, August - 2024)	Page Nos.	Status
1.	Numerical Analysis of Steel Fiber-Reinforced Concrete Beams from Techniques of Topology Optimization Matheus Barbosa Moreira Cedrim, Eduardo Nobre Lages, Aline da Silva Ramos Barboza International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 289-302, August 2024. ABSTRACT This work contributes to the fundamentals of structural design aided by topology optimization techniques. Numerical analysis was conducted using the finite element method in ABAQUS® software, employing homogenization models for steel fiber-reinforced concrete (SFRC) in conjunction with the SIMP method. Examples are validated for beam analysis. The results show the influence of optimization procedure parameters, mix proportions, and design requirements. To establish a methodology of analysis that allows for the use of lighter and stronger elements without the traditional incorporation of steel bars into concrete, the case study revealed that, for conventional concretes, reinforcements are necessary to ensure ductile failure.	289-302	Online
2.	Smart Sensor Based on the IEEE 1451 Standard for Monitoring Coastal Areas Sensitive to Fuel Leakage Yan Ferreira da Silva, Victor Guimarães Furtado and João Viana da Fonseca Neto International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 303-316, August 2024. ABSTRACT Oriented to detect and classify fuels in coastal areas, a methodology for designing a smart sensor device, based on the IEEE 1451 standard and decision tree, is presented in this article. The physical elements of the proposed device are sensors for signal acquisition, and a microcontroller for processing, classification and communication. The software elements of smart sensor are the classification algorithm and communication protocol. Signals captured by the sensors include hydrogen potential, turbidity, temperature, pressure, location and colors. The microcontroller process these signal that are used to detect and classify the presence of polluting fuels in the water. Additionally, the smart sensors are encapsulated to prevent damage caused by the deteriorating characteristics of fuels. For monitoring and evaluation purposes, the signals/data and classifications are sent to a cloud using Internet of Things (IoT) techniques, and monitored using ThingSpeak®. The performance of the smart sensor was evaluated in the laboratory using appropriate materials. The measurement and classification tests were conducted using containers with solutions of water and fuel.	303-316	Online
3.	Automated Fuel Vending Machine Kush Desai International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 317-329, August 2024. ABSTRACT This paper introduced an Automated Fuel Vending Machine system meticulously designed to address fuel dispensing challenges in developing countries. Traditional vending machines entail significant yearly installation costs and substantially burden economies with limited resources. This system emerged as a practical solution to alleviate long queues at petrol pumps, particularly in densely populated regions such as India. The system reduced labor costs and simplified fuel dispensing by eliminating the need for a salesperson. The design focused on creating a cost-effective and easily installable solution, meeting the modern demand for efficient and rapid service. The automated system proved a feasible alternative, offering convenience and operational efficiency. It successfully demonstrated how automation could address economic constraints while enhancing service speed and accessibility, making it a valuable contribution to automated fuel dispensing technology.	317-329	Online
4.	Monitoring Horizontal Displacements in Landfills Using Instrumentation and Geostatistics Daniel Epifânio Bezerra, Victor Emmanue, Avelino Gomes Bahia, Ana Letícia Ramos Bezerra, Cláudio Luis de Araujo Neto, Veruschka Escarião Dessoles Monteiro, Márcio Camargo de Melo International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 330-340, August 2024. ABSTRACT Geotechnical monitoring encompasses the inspection of vertical and horizontal displacements, pore pressures, shear resistance, leachate, and gas flows. Moreover, the monitoring includes visual inspections, ensuring environmental preservation and the safety of the landfill site. Accordingly, this research aims to evaluate and spatialize the magnitude of horizontal displacements over a period of 1 year in a landfill located at Fazenda Logradouro II, district of Catolé de Boa Vista, in the municipality of Campina Grande, state of Paraíba - Brazil. The horizontal displacements were monitored with surface markers through weekly measurements conducted with a total station. After calculating the displacements, spatialization was performed using geostatistics with heat maps (Kernel density estimation), and the computed data was verified against literature data. The results indicated that cumulative horizontal displacements, horizontal displacement speed, and actual displacements are smaller than the values reported in the literature. The spatialization of displacement data using geostatistics has proven to be effective in better visualizing the distribution of displacements in regions of the sanitary massif. The displacement data do not behave uniformly due to waste heterogeneity and other operational factors such as compaction and the execution of the cover soil layer. Thus, geostatistical analysis can be considered as a technique that can help predict and manage these displacements, improving the stability and useful life of the landfill.	330-340	Online
5.	Study to Obtain UHPC with Addition of Silica and MGW Priscila de Souza Maciel, Maria Luiza Malta da Rocha Silva, Ingrid Vieira Fernandes Monteiro and Paulo Cesar Correia Gomes International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 341-354, August 2024. ABSTRACT Ultra-high performance concrete (UHPC) is a specialized concrete with high durability and compressive strength due to its dense structure and low porosity. This study investigated UHPC mixtures with mineral and chemical additions to meet the regulatory parameters for classification as UHPC at 56 days: spread of 270 mm, flexural tensile strength of 6 MPa, and compressive strength of 120 MPa. Variations in Marble and Granite Waste (MGW), silica, superplasticizer, and water were studied. MGW and sand characterization was performed. Consistency and volumetric/mass variation were analyzed in the fresh state, while flexural tensile and compressive strengths were examined in the hardened state. The best-performing mix, with 50% MGW, 20% silica, 1.5% superplasticizer, and w/b=0.25, had the best performance, exhibiting minimum values at 56 days, reaching 130 MPa compressive strength at 91 days, highlighting the potential of MGW and silica in UHPCs.	341-354	Online
6.	Artificial Marble Produced with Biomass Ash Jéssica Beatriz Dantas and José Henrique da Silva International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 355-364 August 2024. ABSTRACT In Brazil, the state of Pernambuco stands out nationally in the clothing sector, especially due to industrial activities in the Agreste region. Many laundries use large amounts of firewood monthly to generate steam in boilers, resulting in the production of biomass ash and causing disposal problems due to irregular dumping. An alternative for managing these wastes is to incorporate them into an economically viable production process. Artificial stones, which are highly profitable composites that mimic natural ornamental stones, present a promising solution for the waste from laundry boilers. In this context, the objective of this study is to produce synthetic marble pieces using mesquite wood ash as a filler in a polyester matrix. For this, pieces were developed with 40% mesquite wood ash and 60% by weight of crystal orthophthalic polyester resin, plus 1% catalyst. The material was placed in a metal mold and subjected to constant pressure of 1 ton for 24 hours. The characterization tests included granulometry, X-ray diffraction, apparent density, compressive strength, and flexural strength. The mechanical strength results indicated that the composite material developed is similar to the natural marble described in the literature, demonstrating that the material has great potential for use in civil construction.	355-364	Online
7.	A Comprehensive Survey of Techniques and Methods for Credit Card Fraud Detection Dinesh Dhandore, Chetan Agrawal and Pooja Meena International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 365-375, August 2024. ABSTRACT Fraud involving credit cards poses significant risks to individuals, businesses, and the overall economy. It encompasses a range of illicit activities where credit cards are used for unauthorized transactions, leading to substantial financial losses, compromised credit ratings, and tarnished reputations. As the reliance on credit cards grows, so does the prevalence of fraud, making robust fraud detection systems crucial. Credit card fraud can be broadly classified into three categories: application fraud, account takeover fraud, and transaction fraud. Application fraud occurs when a person provides false information to fraudulently apply for credit cards. This often involves identity theft, where the perpetrator uses stolen personal information to secure a credit card under someone else's name. Account takeover fraud, on the other hand, involves gaining control of an existing credit card account through methods such as phishing, hacking, or social engineering. Once the fraudster gains access, they can make unauthorized purchases or changes to the account, causing significant harm to the legitimate account holder. The primary focus of this discussion is transaction fraud, a type of fraud where stolen credit card information is used to carry out fraudulent transactions or cash advances. This form of fraud is particularly challenging because it often involves the use of sophisticated techniques to evade detection. Fraudsters may employ tactics such as making small, seemingly innocuous purchases to test the validity of the card before proceeding with larger fraudulent transactions. Detecting fraudulent transactions effectively is essential for mitigating risks and protecting all parties involved, including customers, merchants, and financial institutions. Various fraud detection systems have been developed and deployed to identify and prevent fraudulent activities. These systems leverage a combination of rule-based approaches, machine learning algorithms, and real-time analytics to analyze transaction patterns and flag suspicious activities. However, each system comes with its own set of advantages and limitations.	365-375	Online
8.	Close Traverse with Total Station in a Calibration Baseline Using Different Reflective Surfaces Isaac Ramos Junior, Andrea de Seixas, Sílvio Jacks dos Anjos Garnés International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 376-387 August 2024. ABSTRACT This article examines three different traverses, measured with three different types of reflective surfaces, of a calibration baseline at the Recife campus of the Federal University of Pernambuco, Brazil. The baseline, which has seven pillars, labeled with P1 to P7, with forced centering devices, has a slight misalignment that made the traverse analysis possible. Due to this, it was used a close traverse formed by the pillar sequence P1, P3, P4, P7, P6, P5, P2, P1, opening up the possibility for various types of comparisons. Field data were first subjected to preliminary statistical analysis, and after that, the traverses calculations were made using the least square method. After that, three comparisons were made using one of the targets as reference, referring to angles, distances and coordinates. No cases were found in which differences between quantities exceeded significantly those predicted by least squares estimates. The next step was to use the adjusted coordinates of the reference target to calculate the distances between the pillars, in pairs, so that they could be compared with previous work. This comparison was made, and the largest difference between the distances was -2.2 mm, which is not beyond the estimated linear precision for any of the distances involved. Furthermore, among future works, it is recommended that high-precision geometric leveling of the base be carried out, so that the vertical component can be studied.	376-387	Online
9.	Evaluating the Impacts and Challenges of Autonomous Vehicles in Urban Transportation Towards Multi-Modal Safety Pyla Srinivasa Rao, Tiruveedula Gopi Krishna, Mohamed Abdeldaiem Abdelhadi Mahboub International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 388-398, August 2024. ABSTRACT Self-driving vehicles still have a lot of potential to change transportation. But keeping them safe amid the chaos created by multiple drivers is a significant task. This review research presents the argument that a comprehensive strategy beyond automotive AI is necessary for safety. It demonstrates a multimodal safety strategy that is entirely dependent on expertise cooperation and polite communication between autonomous vehicles and all other users of the road. Combining sensor data verbal communication between the vehicle and everything and a well-thought-out human-device interface are some of the important aspects that have been investigated. In addition to stepped forward pedestrian protection reduced injury rates and improved traffic flow this study highlights the application of multi-modal safety. However, examine the difficulties in implementing those rules.	388-398	Online
10.	Dimethyl Ether from Syngas Derived from Vinasse: Economic and Environmental Benefits of Process Energy Integration Gabriela de França Lopes, Caroline Teixeira Rodrigues, Gabrielly Mylena Benedetti Tonial, Luiz Mario de Matos Jorge, Paulo Roberto Paraíso International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 399-405 August 2024. ABSTRACT Dimethyl ether (DME) stands out as a clean fuel for various applications, especially as a substitute for diesel and LPG. The feasibility of its production has been investigated, with process integration potentially contributing new dimensions of sustainability to the process, both environmentally and economically. In the context of the need to seek alternatives that are advantageous in technical, economic, and environmental aspects, energy integration plays an important role. This study aims to achieve energy integration in the direct synthesis process of dimethyl ether from syngas derived from vinasse, assessing the benefits for the process with the network of heat exchangers generated. Integration calculations were performed using Aspen HYSYS® software with its Aspen Energy Analyzer tool, and cost evaluations of the integrated process were carried out with the Aspen Process Economic Analyzer tool. With energy integration, costs for hot utility are eliminated by 100% and cold utility by 13.6%. This resulted in a reduction of carbon equivalent emissions by approximately 9,850 tons per year and a reduction in the cost of the simulated DME stage by about 4.8 per ton, leading to a final unit cost of $248.12/t considering all production stages. Thus, this study contributes to advancing the feasibility of producing this important biofuel, providing significant economic and environmental benefits.	399-405	Online
11.	Automated Landslide Detection Using Artificial Neural Networks and Sentinel-2 Imagery: A Case Study in Mariana, Brazil Mateus Oliveira Xavier1 and César Falcão Barella International Journal of Advances in Engineering & Technology (IJAET), Volume 17 Issue 4, pp. 406-420, August 2024. ABSTRACT Landslide inventories are crucial for risk management and for developing and validating susceptibility and hazard models. Traditional methods, like visual interpretation of aerial photos and satellite imagery, field mapping, topographic surface interpretation, and literature reviews, are often time-consuming, costly, and subjective. Automated methods are becoming more important for saving time and resources. In this study, we used an Artificial Neural Network (ANN) classification algorithm to detect landslide scars caused by rain events in Mariana, Minas Gerais, Brazil. Input parameters included the slope from local topography and products from change detection techniques using Sentinel-2 images taken before and after the landslides. These images provided data on visible and near-infrared spectral bands and four vegetation indices. Sixteen ANN models were trained using various dataset configurations in binary point formats representing landslide and non-landslide data. The optimal dataset included 25 points on five pre-selected landslides and 50 non-landslide points from diverse land uses. This model achieved 89.41% precision, 90.48% sensitivity, and an F1-Score of 0.8994. These results were derived by comparing 84 landslides in a restricted portion of the study area and juxtaposing individual landslide detection using the automated model with a manually created inventory based on high spatial resolution images from a Remotely Piloted Aircraft System (RPAS) and fieldwork. The automated inventory matched well with the manual inventory, demonstrating the effectiveness of the ANN in quickly, safely, and cost-effectively detecting landslides using free satellite images and open-source machine learning tools.	406-420	Online