Journal of Engineering and Technological Sciences

An Experimental Study on the Structural Behavior of RC Columns when Using Crumb Rubber Concrete Combined with Recycled Steel Fibers

2025-11-13T08:56:37+07:00

The growing demand for vehicles has spurred an increase in tire production. However, the improper disposal of these waste tires poses a significant environmental and health hazard. To address this, recent research has explored the integration of recycled steel fibers (RSF) and crumb rubber (Cr) from used tires into concrete formulations to create innovative rubberized and fibrous concrete. A notable study specifically examined the impact of adding RSF of varying lengths and a fixed volume fraction into rubberized concrete containing different proportions of Cr, where Cr partially replaced natural sand. Through the fabrication and testing of 18 reinforced concrete columns under axial compression, the findings demonstrated that RSF alone significantly enhanced the concrete’s properties, including density, compressive strength, and tensile strength, by remarkable percentages of 100.27%, 116.84%, and 107.25%, respectively. Conversely, the exclusive use of Cr resulted in a decline in these properties as its content increased. Notably, the "Co5" columns, which incorporated RSF into a concrete mix containing Cr, exhibited superior performance, showing improved displacement and ductility by a degree of approximately 44.67% and 15.65%, respectively, alongside a significant reduction in crack widths by about 29.45% compared to standard rubberized concrete (Co1&Co2). The properties and attributes of columns display promising performance as well as displacement and ductility when RSF is incorporated into concrete mix that includes Cr compared to rubberized concrete.

Influence of Heat and Mechanical Treatments on the Mechanical and Structural Characteristics of Molded Manganese Steels

2025-11-13T08:57:40+07:00

This paper presents a study to improve the performance of Fe-Mn-C cast steels containing 1.7% and 2.7% Cr by weight, using two treatment methods (thermal and mechanical) applied separately to two different steel grades. This approach enables an extended service life for components such as crusher liners, mill hammers, and level crossings, without requiring complete recasting. The experimental techniques used for characterization included spark optical emission spectroscopy, optical microscopy, scanning electron microscopy, as well as micro- and macro-hardness testing. Steel 1, with a composition of 15.51% Mn, 2.68% Cr, and 1.29% C, was heat-treated at 1070 °C and quenched in water, using different holding times and thicknesses. It was found that increasing the holding time from 30 to 50 minutes and reducing the thickness from 150 to 100 millimeters led to a complete and homogeneous dissolution of carbides. As a result, Steel 1 exhibited increased ductility. Steel 2 contains 13.45% Mn, 1.72% Cr, and 1.21% C. It underwent manual mechanical treatment, which resulted in surface hardening due to the transformation of austenite into martensite.

Polyoxometalates as Catalysts for Biomass Conversion: Properties, Applications, and Regenerability

2025-10-17T12:46:46+07:00

Polyoxometalates (POMs) have emerged as exceptionally versatile catalysts for green chemical reactions, demonstrating significant potential in the sustainable valorization of biomass. Their tunable Brønsted/Lewis acidity and redox properties enable a broad range of chemical transformations, offering remarkable flexibility in process design. This mini review provides a summary of recent advances in the thermocatalytic conversion of biomass using POMs, addressing their utilization as both homogeneous and heterogeneous catalysts. Key reaction pathways, including solvolysis, oxidation, esterification, and condensation, are highlighted as fundamental processes in biomass valorization. A central focus is placed on the crucial challenge of catalyst regenerability and stability, examining strategies to ensure the long-term viability and economic feasibility of these systems while facing the apparent low-temperature stability challenge of POMs. Finally, this review synthesizes current regeneration methods and presents a forward-looking perspective on the future challenges and opportunities in the field of biomass conversion catalyzed by polyoxometalates.

Design and Development of a Water Flow Monitoring Device using Mitsubishi FX3U-14MT PLC

2025-11-13T09:30:26+07:00

Efficient water management is essential for ensuring sustainability and reducing operational costs, especially in small to medium-scale buildings such as schools, health clinics, and office facilities. This paper presents the design and implementation of a cost-effective automated water flow monitoring system, integrating a Mitsubishi FX3U-14MT PLC with an Arduino module to facilitate real-time flow measurement and precise control of solenoid valves. The PLC is programmed using ladder logic, while the Arduino is responsible for processing sensor data, thereby enhancing measurement accuracy and contributing to overall system flexibility. In contrast to conventional industrial automation solutions, this system is specifically designed for small-scale applications, offering an effective balance of affordability, simplicity, and reliability. Experimental testing demonstrates that the system achieves high measurement accuracy, operational stability over extended use, and optimized energy efficiency, ensuring long-term reliability in water flow management. Additionally, the system’s modular design enables straightforward adaptation to various facility sizes and plumbing configurations. These findings validate the proposed system as an accessible yet effective automation solution, particularly suitable for environments where implementing large-scale industrial control systems may be impractical. Future research could focus on incorporating adaptive control algorithms and enhancing sensor integration to further improve system performance and flexibility.

Optimizing Evaporator Design in ORC Systems for Waste-to-Energy Conversion Using FAST Diagram and Value Engineering

2025-09-25T10:24:51+07:00

The global waste crisis necessitates innovative solutions for sustainable energy conversion. This study presents a comprehensive optimization framework for evaporator design in Organic Rankine Cycle (ORC) systems utilized in waste-to-energy conversion. This research integrates the Function Analysis System Technique (FAST) diagram with Value Engineering (VE) principles to assess the logical hierarchy and cost analysis components of system effectiveness. Evaluation of the 887 kW shell-and-tube evaporator showed tubes, baffles, and shells account for 90% of production costs and are the most thermally efficient components. Further strategic redesign under VE principles resulted in 23% cost reduction with 15% efficiency improvements, demonstrating resource expenditure without performance compromise. The proposed approach offers a foundational methodology for advancing enduring ORC system design while harnessing high waste-to-value electrical energy conversion at low expenses, fostering the circular economy.

Enhanced Finite Element Numerical Analysis of Rigid Inclusion Lateral Resistance for Embankment on Slightly Overconsolidated Soft Clay

2025-10-20T14:11:31+07:00

Soft clay soils represent a significant challenge for embankment construction due to high compressibility, low shear strength, low bearing capacity, and excessive settlement potential. This study presents an enhanced finite-element model to evaluate the performance of Mortar Column Inclusion (Inklusi Kolom Mortar, or IKM) as a rigid inclusion supporting embankments over slightly overconsolidated soft clays, as implemented in the Serang-Panimbang Toll Road Project (STA 75+600 to STA 75+800). The propose approach integrates depth-dependent multilinear lateral resistance with structural “dummy” plate elements to capture soil arching within the Load Transfer Platform (LTP) and lateral column-soil interaction—an approach not previously applied in rigid inclusions modeling for soft clays. Studies on numerical modeling of IKM systems in slightly overconsolidated soft clays remain limited. Finite element analyses are conducted using PLAXIS 2D and 3D with axisymmetric, unit-cell, and plane strain approaches. The results show that the "dummy" plate simulates soil arching in the LTP and improves the representation of negative skin friction, neutral-plane transition, and axial load distribution. Depth-dependent lateral resistance enhances predictions of column bending moments and horizontal deformation within varying soil layers. Field validation indicates good agreement, with inclinometer displacement predicted at 40.79 mm (difference < 10%). Predicted vertical settlements of 20.71 cm (centerline) and 19.38 (edge) are also consistent with settlement plate readings of 15.80 and 11.00 cm, respectively. These findings confirm that the enhanced model provides a comprehensive evaluation of stress distribution, pile deformation, and global stability for ground improvement design in soft clays

Improving Single-Phase Induction Motor Speed Control Using Model Reference Adaptive System and Fuzzy-Pid Regulator

2025-10-31T15:47:49+07:00

As industries strive to enhance their applications to meet growing market demand, accurate speed control of single-phase induction motors (SPIMs) remains a crucial concern. This paper presents the modelling and simulation of SPIM speed control based on a hybrid Model Reference Adaptive System (MRAS) integrated with a Fuzzy–PID regulator. Superior performance was achieved by integrating MRAS with a fuzzy-PID regulator using an adaptive self-tuning mechanism. The purpose of this integration was to leverage the adaptive nature of MRAS and the robustness of the Fuzzy-PID regulator to enhance performance and reliability in SPIM drives without the need for physical sensors. The SPIM speed was modelled using differential equations representing both electrical and mechanical dynamics. MRAS was implemented using motor voltage equations, with an adaptive model estimating the rotor speed. The Fuzzy-PID regulator optimized control performance by processing the error and its rate of change through a fuzzy controller, with the output fed into a PID controller to ensure error stabilization. A review of relevant literature on SPIM and associated control theories was conducted, and several journal papers were analyzed. Simulation of the proposed MRAS–Fuzzy-PID approach in MATLAB demonstrated that sensorless speed regulation considerably reduced rise time, enabling the motor to reach the desired speed quickly while eliminating steady-state error compared to systems without controllers. The results indicate that the rise time was reduced by 65.5%, the overshoot decreased by 58.9%, the steady-state error decreased by 71.8%, and the Integral of Absolute Error (IAE) was minimized. These improvements ensured stable operation under varying load conditions, with minimal fluctuations in speed. Integrating MRAS with a Fuzzy-PID controller further enhances the speed stability, robustness, and adaptability of SPIM drives.

An Enhanced Fuzzy Logic-Particle Swarm Optimization Algorithm for the Strategy Control of Self-driving Electric Vehicles

2025-11-04T11:30:07+07:00

With the current rapid advancement of science and technology, there is an increasing focus on comprehensive research and the development of practical solutions for self-driving electric cars to address challenges, including environmental pollution, renewable energy utilization, emission control, and battery recycling. In this study, automatic direction control is achieved for electric vehicles by implementing line-tracing autonomous vehicles equipped with computer vision-based cameras, utilizing Particle Swarm Optimization (PSO), the Takagi–Sugeno Fuzzy model, and the PID control system. Line-tracing autonomous vehicles are devices capable of recognizing and tracking black or painted lines on the road. The lines are designed to be easily recognizable with a clear contrast, such as a white line on a black background. The autonomous vehicle follows a distinct, marked line to guide its journey. In this study, we integrate computer vision techniques with Particle Swarm Optimization (PSO) and a Takagi–Sugeno fuzzy control system for automatic direction control. Additionally, the speed and turning direction of the electric vehicle are regulated by a controller that combines proportional, integral, and derivative (PID) stages. According to real-world experiments with road-following autonomous vehicles using camera image processing, the highest success rate of 99.8% is achieved when the car employs intelligent algorithms to navigate turns of 10, 20, 30, and 40 degrees. Likewise, tests have demonstrated that the electric vehicle can achieve a perfect success rate of 100% when driving on a straight road.

Digital Value Engineering for Sustainable Commercial Buildings: A BIM and Life Cycle Cost-Based Decision-Making Framework

2025-09-25T16:09:18+07:00

Sustainable commercial buildings require cost-effective and environmentally responsible design solutions. Traditional Value Engineering (VE) methods, while effective in cost reduction, often lack integration with digital tools, limiting their ability to optimize sustainability and performance. This study develops a Digital Value Engineering Model (DVEM) that aligns with Industry 4.0 principles, incorporating Building Information Modeling (BIM), Life Cycle Cost (LCC) analysis, and a weighted evaluation matrix to enhance decision-making transparency, cost efficiency, and environmental impact assessment. The model was implemented in Autodesk Revit and applied to a real-life commercial building project in Malaysia, systematically following six VE phases. The results demonstrate a 28% cost reduction while optimizing material selection, energy efficiency, and lifecycle performance. Unlike conventional VE, DVEM enables automated cost analysis, real-time sustainability assessment, and function-based decision modeling. By bridging traditional VE with modern digital workflows, this study provides a replicable, data-driven approach to optimizing commercial building design. The findings contribute to the construction industry by introducing a structured, scalable framework that enhances decision-making efficiency, resource utilization, and sustainability compliance in commercial building projects.

Comparative Analysis of Photogrammetry Tools for Monitoring Trench and Pipeline Progress Towards Sustainable Construction

2025-09-11T11:26:17+07:00

The construction of trenches and pipelines is essential to the infrastructure sector, but because of safety and technical concerns, progress monitoring is difficult. This study assesses how well photogrammetry, a cost-effective and adaptable Industry 4.0 technology, can improve safety and sustainability in construction monitoring. The graphical user interface, computational efficiency, point cloud density, model quality, percent completion, and noise in the produced 3D models were the criteria used to evaluate the six photogrammetry tools: Autodesk Recap Pro, Agisoft Metashape Pro, COLMAP, VisualSFM, Meshroom, and Regard 3D. Performance under specified conditions was examined using a trench and pipeline dataset. The results show that Agisoft Metashape Pro and Autodesk Recap Pro performed exceptionally well, offering thorough and precise 3D reconstructions with excellent models and low noise. This research promotes the use of photogrammetry by emphasizing its advantages over conventional methods in terms of affordability and sustainability. It highlights photogrammetry's contribution to resilient and sustainable practices and provides industry experts with advice on how to choose appropriate methods for tracking building progress. The results help stakeholders feel more confident about implementing photogrammetric technologies that are suited to various building settings.