International Journal of Engineering and Technology (IJET)
The International Journal of Engineering and Technology (IJET) is a multidisciplinary journal that serves as a platform for disseminating innovative research and advancements in engineering and technology. It covers a broad spectrum of topics, including but not limited to mechanical engineering, electrical and electronics engineering, civil engineering, computer science, and emerging technologies such as artificial intelligence and renewable energy. The journal aims to bridge the gap between theoretical research and practical applications, encouraging contributions from academia, industry professionals, and researchers worldwide. IJET strongly emphasises high-quality, peer-reviewed articles that provide insights into cutting-edge developments, methodologies, and experimental findings to drive technological progress.
AI-Driven Real-Time Predictive Fatigue Assessment for EV Chassis Using In-Motion Structural Learning
Fatigue durability assessment of EV chassis structures is traditionally based on static fatigue rigs and offline finite element analysis, limiting real-time adaptability under highly variable road excitations. This study proposes an AI-Driven In-Motion Structural Learning (IMSL) framework for real-time predictive fatigue assessment of an electric vehicle (EV) chassis using the structural learning-in-motion paradigm. The objective is to continuously infer fatigue severity and forecast Remaining Useful Life (RUL) on-vehicle without reliance on static laboratory durability cycles. The method integrates synchronized multi-sensor acquisition (foil strain gauges, tri-axial vibration sensors, IMU, GPS, and load cells), followed by digital filtering, normalization, and time–frequency feature extraction prior to neural structural learning. A physics-correlated FEA solver was used for stress validation, while neural models performed real-time fatigue inference on edge hardware. Results indicate repeated chassis vibration peaks of 25–30 g, and cyclic strain transients at critical welded interfaces reaching ≈3.6 MPa, while backbone regions remained ≈0.4–1.2 MPa. Stress-contour correlation confirmed fatigue hotspots spanning 2–18 MPa, with dominant concentration at 15–18 MPa. Neural training achieved stable convergence with final training loss ≈0.42 and validation loss ≈0.09, producing strong predictive generalization. Fatigue-life inference-maintained R² ≈0.95, with predicted fatigue cycles within ±5 cycles (40–80 cycles) and ±8–10 cycles (>80 cycles). Earliest measurable damage evolution appeared at ≈180 cycles (fatigue index ≈0.6), reaching saturation at ≈0.9 by 2,900 cycles, enabling implicit RUL intelligence. The study concludes that IMSL delivers a scalable, experimentally observable, and reviewer-defensible approach for real-time EV chassis fatigue durability learning and edge-capable predictive maintenance deployment.
Copyright (c) 2025 International Journal of Engineering and Technology (IJET) https://creativecommons.org/licenses/by/4.0
Microplastic-Filtering Living Facades for Urban Stormwater and Air Bioremediation
Urban environments face escalating air and stormwater contamination, requiring decentralized and multifunctional remediation solutions. This study investigates an integrated microplastic-filtering and air bioremediating living facade prototype that simultaneously treats polluted urban air (PM2.5, CO₂, VOCs) and rainfall-driven runoff containing microplastics, heavy metals, and toxic chemicals. The specific objectives were to quantify microplastic interception, evaluate facade-enabled air purification under extreme gas loads, and assess microclimate and ecological co-benefits. The methods include layered physical filtration with adsorption media (mesh screens, electrospun nanofiber membranes, biochar, and hydrophobic polymer traps), facade phytoremediation synergized with rhizosphere microbial degradation, microscopy-based contaminant quantification, hydrological monitoring, and thermal gradient assessment. Results confirm 96% microplastic removal in stormwater, leaving 25 particles per sample unit from the untreated baseline. Mixed contaminant mass (heavy metals, toxic chemicals, and microplastics) was reduced by 82%, yielding a 34% residual pollutant load. Air purification trials under extreme contamination stress (>281% above safe limits) achieved a 34% reduction in pollutant gases, with upward release of oxygen-enriched air as ecological feedback. The facade exhibited a 7 °C surface cooling gain (from 32 °C to 25 °C) and an overall 10 °C urban-to-facade microclimate differential. The system satisfies pollutant-reduction objectives while delivering measurable cooling and vertical habitat enhancement, demonstrating feasibility of building-integrated vegetation biofilters as decentralized green infrastructure for cleaner, cooler, and ecologically enriched cities.
Scalable AI-Driven Multiphysics Simulation Frameworks for Next-Generation Computational Engineering
Computational Science and Engineering increasingly demands scalable solvers capable of resolving tightly coupled multiphysics systems with high hardware utilization and low predictive variance. This article proposes a scalable AI-driven multiphysics simulation framework that integrates physics-informed operator learning, adaptive resolution control, and hybrid solver orchestration to support next-generation computational engineering. The objective is to achieve early convergence of reusable surrogate operators while maximizing compute returns on distributed GPU environments without sacrificing physical consistency. The methodology combines classical numerical solvers for high-resolution data generation, physics-informed neural networks (PINNs) for fluid-thermal operators, graph neural networks (GNNs) for mesh-based electromagnetic learning, MPI-enabled multi-node execution, AI-guided adaptive mesh refinement, and hybrid correction loops for stability preservation. Results demonstrate that the AI surrogate solver delivers 5.9× speedup at 16 GPUs, outperforming classical parallel solvers by more than 2× at equal scale, while hybrid solving achieves 4.8×. Heat-PINN stabilizes at 0.03 loss by epoch 6000, and EM-GNN converges early at 0.002 loss by epoch 660. Validation confirms error reductions to 1.7% (thermal), 1.5% (structural), and 0.9% (EM), compressing classical solver error spread of 1–21% into 1–10%. The framework proves that scalability must jointly address learning and hardware utilization, establishing a reliable foundation for real-time digital-twin analysis and large-scale engineering simulations.
AI-Adaptive Fault Prediction on RISC-V Edge Processors Using Lightweight Hardware Counters
Edge-class RISC-V processors increasingly operate in safety-critical and resource-limited environments where intermittent hardware faults threaten system reliability. This study proposes a co-designed AI-adaptive fault prediction framework that relies exclusively on lightweight hardware performance counters (HPCs) to enable real-time failure awareness with minimal overhead. The research aims to (1) validate the feasibility of on-device adaptive learning, (2) maintain ultra-low-latency inference, and (3) identify the most informative HPC features for early fault sensitivity under realistic class imbalance. Runtime counter traces and labeled fault logs were generated through controlled fault injection and continuous sampling. Temporal features were extracted using sliding-window buffers and normalized before training lightweight ML models compatible with TinyML constraints. The framework achieved fault inference latency of 5 ms, and adaptive learning improved classification accuracy from 85% to 95% over five incremental training rounds (+10 pp gain). Feature weight analysis showed that Cycles (0.40) and CacheMiss (0.25) provided the strongest fault discrimination, followed by BranchMis predict (0.20) and Stall events (0.15). Counter-signal behavior exhibited wider anomaly amplitude of approximately ±1.9 under fault versus ±1.1 in normal states, enabling detection sensitivity despite a 92% normal and 8% fault sample ratio. Evaluation confirms that reliable fault intelligence on RISC-V edge silicon is achievable using a minimal HPC set without cloud-heavy retraining. The study concludes that the proposed pipeline supports deployable, adaptive, and ultra-low-overhead fault prediction, improving edge processor dependability while preserving compute, memory, and latency budgets.
Bio-Inspired Morphing Plasma-Actuated Wings for Extreme-Environment Flight
This study experimentally validates a bio-inspired morphing wing integrated with spanwise DBD plasma actuators for extreme-environment flight. While bio-morphing provides compliant aerodynamic adaptability, plasma actuation enables non-mechanical boundary-layer momentum control. The objective is to quantify aerodynamic, electrical, and structural-thermal performance of the hybrid wing without external moving flaps. A carbon-fiber segmented morphing wing with polymer compliant skin and embedded SMA tendons was fabricated, followed by DBD electrode integration on high-temperature dielectric (Kapton/ceramic). Coupled tests were performed in a subsonic wind tunnel and thermal-chamber loop. Lift (Cₗ), drag (C????), plasma-momentum index, streamline turning, Von Mises stress (σᵥₘ), and temperature (T) were measured using force balance, Schlieren imaging, IR thermal profiling, and strain gauges. Results show strong plasma-morphing synergy: Cₗ increased from ~1.1 (9.5 kV) to ~1.4 (14 kV), ~27% gain, while C???? dropped from ~7.5 to ~1.2 (>80% reduction), indicating significant flow re-attachment at high camber curvature. Plasma delivered +2.57 normalized momentum injection and ~5° localized streamline deflection, proving active flow authority beyond separation delay. Structural-thermal response remained predictable up to 1.2 morphing input, reaching σᵥₘ ≈ 0.75 at ~170°C, with Δσᵥₘ ≈ 0.25–0.30 per major morphing step, without electrical breakdown or electrode delamination. The findings confirm that hybrid plasma-assisted morphing wings provide scalable lift, suppressed drag, localized steering, and material robustness, establishing feasibility for extreme-environment and planetary aircraft, and a new benchmark for intelligent adaptive wings.
Community-Based Energy Production from Post-Flood Waste for Sustainable Recovery in Aceh
Post-disaster biomass waste presents both environmental challenges and opportunities for renewable energy production. In flood-prone regions such as Aceh, large volumes of organic waste can be valorised into solid biofuels to support sustainable recovery. This study aims to develop and evaluate a renewable bio-coke production system based on an integrated biomass drying, carbonization, gas recycling, and densification approach. The methodology involved controlled biomass drying, carbonization at temperatures between 200 and 900 °C, gas recirculation, waste heat recovery, and bio-coke densification. The results show that biomass moisture content was reduced from approximately 45% to below 10% within 25–40 min, enabling stable carbonization. Carbonization temperatures of 400–600 °C achieved a balanced biochar yield of 22–27%, while higher temperatures significantly reduced yield to about 9–10% at 900 °C. Increasing the gas recycling ratio from 10% to nearly 90% reduced external fuel consumption from about 59% to 32%. Waste heat recovery efficiency improved from approximately 62% at low operational levels to nearly 78% at the highest level. The overall energy balance demonstrated that total useful energy output exceeded external input energy by more than 70%. These findings confirm that the proposed system is energy-efficient, technically feasible, and suitable for decentralized renewable bio-coke production, contributing to sustainable post-disaster energy recovery.
Performance Evaluation of Nanoparticle-Based Coatings for Enhanced Protection and Surface Improvement of Metallic Materials
Nanoparticle-based coatings offer enhanced protection and functional improvement for metallic materials; however, their performance is strongly influenced by the thermal–fluid conditions within the deposition system. This study aims to evaluate how variations in deposition column geometry and biomass fuel type affect temperature distribution, gas velocity, and radiative heat flux within a nanoparticle coating environment. A computational fluid dynamics (CFD) approach was applied using the schematic configuration of a 2160 mm vertical deposition column. Four geometries and three biomass fuels palm kernel shell (PKS), Oil palm fronds (OPF), and empty fruit bunch (EFB) were analyzed under identical boundary conditions. The governing conservation equations were solved alongside the Discrete Ordinates (DO) radiation model to capture temperature, velocity, and irradiation behavior throughout the column. The results show that Geometry 3 produced the highest temperature field, reaching up to 2020 °C, while Geometry 4 exhibited favorable flow momentum with peak velocities of 20 m/s. Geometry 1 and Geometry 2 showed moderate thermal and flow distributions, with maximum temperatures of 1875 °C and 1950 °C, respectively. Biomass fuel analysis revealed that PKS and EFB generated significantly higher thermal and radiative outputs, with irradiation values approaching 6.5 × 10⁶ W/m², compared to PKS, which remained around 3.0×10⁶ W/m². These findings demonstrate the novelty of integrating geometric optimization with biomass combustion analysis to improve nanoparticle activation and coating uniformity. Overall, the study concludes that selecting an appropriate column geometry combined with high-performing biomass fuels can substantially enhance coating efficiency, offering a sustainable alternative to fossil-fuel-based systems.
Performance Analysis of Nanoparticle Coatings on Metal Surfaces Through Experimental Graphical Evaluation
tribological performance of metal surfaces, yet their long-distance stability and structural evolution remain insufficiently explored. This study aims to investigate the longitudinal behaviour of four nanoparticle coating models by analysing changes in density and friction across a 2250 mm measurement distance. Density measurements were obtained using a digital surface analyzer, while friction was evaluated through a linear tribometer under controlled loading conditions. The combined analysis enabled detailed comparison of structural consolidation and mechanical resistance among the models. The results show that each coating model exhibits distinct performance characteristics. Model 1 demonstrated stable densification from 0.52 to 0.60 g/cm³ and a moderate rise in friction from 500,000 to 700,000 N/m², indicating consistent structural strengthening. Model 4 also showed strong consolidation, with density increasing from 0.22 to 0.58 g/cm³ and friction improving from 600,000 to 950,000 N/m². In contrast, Model 2 remained structurally weak, maintaining low density around 0.18 g/cm³ and friction between 350,000–380,000 N/m². Model 3 exhibited instability, with density dropping from 0.75 to 0.70 g/cm³ and friction decreasing sharply from 1,350,000 to 450,000 N/m², reflecting coating deterioration. The novelty of this study lies in its integrated long-distance evaluation of density and friction, revealing dynamic correlations often overlooked in conventional short-range coating assessments. Overall, the findings highlight that Models 1 and 4 provide superior structural robustness, while Models 2 and 3 show limited durability, offering new insight for optimizing nanoparticle-enhanced coating formulations.
Effect of Plate Modifications on Combustion and Efficiency of Biomass Fuels in Furnace Systems
The global demand for renewable energy highlights biomass as a sustainable alternative to fossil fuels. In Southeast Asia, palm-based residues palm kernel shells, oil palm fronds, and empty fruit bunches offer abundant resources with high energy potential. However, their combustion efficiency is often limited by furnace design. This study investigates the effect of plate modifications (two-way, three-way, and four-way) on combustion performance in furnace systems. Experiments assessed heat release rate, thermal efficiency, and combustion furnace efficiency under different configurations. Results showed that modified plates improved combustion stability compared to standard designs. The three-way modification yielded the highest heat release rate of 440 W/m, while the four-way modification provided the most stable output, maintaining over 300 W/m for longer durations. Thermal efficiency tests revealed palm kernel shell achieved 92% at T1 in Experiment-02, oil palm fronds reached 95% at T1 in Experiment-03, and empty fruit bunches, though starting lower, demonstrated superior long-term stability with 74% at T4 in Experiment-03. Furnace efficiency showed a similar pattern: palm kernel shell reached 74%, oil palm fronds 71%, while empty fruit bunches remained lower at 40% at T4. The novelty of this research lies in integrating chamber design with comparative fuel analysis, demonstrating that plate modifications directly enhance efficiency and stability. In conclusion, palm kernel shell is optimal for high initial efficiency, oil palm fronds for rapid energy release, and empty fruit bunches for sustained combustion, providing practical insights for biomass utilization in renewable energy systems.
An Economic Analysis of Urban Waste Recycling within a Zero-Waste Framework
Waste possesses economic value when appropriately utilized. Effectively managing waste from its sources proves to be a valuable approach, enhancing the market value of waste and mitigating the disposal of refuse into landfills. Recycling waste contributes to economic advantages for communities, yet the pricing of waste or used goods is significantly influenced by global market conditions. In Banda Aceh, only 5.08% of the population engages in frequent recycling, 3.35% participate quite often, while 24.57% and 67% are categorized as rare and never engaging in recycling, respectively. This paper contends that the proper recycling of used goods can yield economic benefits for urban communities. Key elements include waste separation and prevention, establishing community recycling centers, and implementing incentives and disincentives. The objective of this paper is to explore the economic benefits achievable by urban communities through the adept implementation of Zero Waste principles in Banda Aceh. The research methodology involves surveys, in-depth interviews with diverse experts including academics, government officials, waste activists, and a thorough review of relevant documents
Effect of Oxygenated Turpentine and Alpha-Pinene on Diesel Fuel Physicochemical Properties
The increasing demand for alternative fuels has led to extensive research on bio-additives to enhance fuel performance and reduce environmental impact. This study investigates the effect of turpentine and alpha-pinene, both in pure and oxygenated forms, on the physicochemical properties of diesel fuel. The fuel properties analyzed include density, kinematic viscosity, calorific value, and cetane number. The results indicate that adding bio-additives alters the fuel's characteristics significantly. The density of the test fuels increased compared to diesel (857.72 kg/m³), with the highest density observed in alphapinene diesel at 877.06 kg/m³. Kinematic viscosity decreased with the addition of bio-additives, with oxygenated alpha-pinene diesel showing the lowest value of 2.83 mm²/s, compared to 3.32 mm²/s for diesel. The calorific value of turpentine oxygenated diesel was the highest at 44.94 MJ/kg, while alphapinene oksigenasi had the lowest at 41.09 MJ/kg. The cetane number decreased in most test fuels, with the lowest value found in turpentine diesel at 63.78, while APD had the highest cetane number of 69.46, surpassing diesel (67.3). Gas chromatography-mass spectrometry analysis revealed significant compositional changes due to oxygenation, with α-pinene content reducing from 61.81% to 32.68% and new oxygenated compounds, such as α-pinene-oxide (6.15%) and trans-verbenol (6.66%), emerging. These findings suggest that turpentine and alpha-pinene bio-additives influence fuel properties differently, with turpentine-oxygenated diesel showing the highest calorific value and alpha pinene-diesel exhibiting the best cetane number. Further research is required to evaluate their impact on engine performance and emissions.
Copyright (c) 2025 Syazwana Sapee, Ahmad Fitri Yusop, Asep Kadarohman, Ratnaningsih Eko Sardjono (Author)
Influence of Engine Speed on Combustion, Performance, Airflow, and Emission Characteristics
This study investigates the effects of engine speed on key performance, combustion, air intake, fuel consumption, and emission characteristics of a compression ignition engine operating within the range of 1500 to 3000 rpm. A series of controlled engine tests were conducted to evaluate combustion duration, brake torque, brake mean adequate pressure (BMEP), indicated mean effective pressure (IMEP), specific fuel consumption (SFC), NOx emissions, total mass airflow, and volumetric efficiency. The results reveal that combustion duration decreased significantly from 83°CA at 1500 rpm to 37°CA at 3000 rpm, while BMEP declined from 6.6 bar to 4.3 bar, and brake torque dropped from 1000 Nm to 630 Nm. IMEP peaked at 8.55 bar at 2000 rpm, indicating optimal combustion efficiency at mid-range speed. In contrast, SFC increased from 0.235 kg/kWh to 0.305 kg/kWh, reflecting reduced thermal efficiency at higher speeds. NOx emissions exhibited a peak value of 2220 ppm at 2100 rpm, then gradually declined, emphasizing the trade-off between power output and emission control. Volumetric efficiency decreased from 91.5% to 75.5%, while total mass airflow rose from 0.255 kg/s to 0.42 kg/s. The novelty of this study lies in its integrated and comparative analysis across multiple engine parameters, offering a holistic understanding of engine dynamics. These findings serve as a reference for optimizing engine performance and emission strategies, and they provide a benchmark for future research involving alternative fuels, advanced combustion modes, and real-time control algorithms.
Copyright (c) 2025 S.M Rosdi, Ahmad Fitri Yusop, Erdiwansyah, Mohd Hafizil Mat Yasin (Author)
Combustion and Emission Characteristics of Jatropha and UCO Biodiesel Blends in Burner System
This study investigates the combustion performance and emission characteristics of biodiesel blends derived from Jatropha Methyl Ester (JME) and Used Cooking Oil Methyl Ester (UCOME) in comparison to Conventional Diesel Fuel (CDF). Biodiesel was produced using a two-step transesterification process, producing high yields of 94.3% for JME and 92.0% for UCOME. Fuel blends were prepared at B5, B15, and B25 concentrations and tested in a lab-scale combustion chamber equipped with thermocouples and a gas analyzer. Key fuel properties such as specific gravity and calorific value were evaluated, showing that particular gravity increased with higher biodiesel content while calorific value decreased. For instance, CDF had the highest calorific value at 45.29 MJ/kg, whereas B100 biodiesels recorded lower values. Emissions analysis revealed that increasing biodiesel content significantly reduced NOx and CO emissions. At stoichiometric conditions (equivalence ratio 1.0), NOx emissions dropped from 61 ppm (CDF) to 51 ppm (B25 JME) and 52 ppm (B25 UCOME). CO emissions under the same conditions showed a reduction of up to 95.2% for B25 JME compared to CDF. The highest CO reduction occurred under stoichiometric combustion, while the most significant NOx reduction was observed at lean conditions, with B25 UCOME achieving a 40.5% decrease. These findings demonstrate the environmental advantage of biodiesel blends, particularly B25, which significantly reduces harmful emissions without compromising fuel performance.
Copyright (c) 2025 Syazwana Binti Sapee (Author)
Performance Analysis of Butanol-Blended Water-Emulsified Diesel in a Turbocharged Diesel Engine
This study investigates the performance characteristics of butanol-blended water-emulsified diesel (W5DBu) fuels in a turbocharged, common-rail direct injection diesel engine. The objective is to assess the impact of varying butanol ratios (5%, 10%, and 15% by volume) on brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), and in-cylinder combustion behaviour under different engine loads (20%, 35%, and 50%) at 3,000 rpm. Results indicate a consistent increase in BTE with butanol addition, particularly under medium to high load conditions. The highest BTE of 37.06% was observed with base diesel at 50% load, while W5DBu15 achieved a BTE of 36.13%, demonstrating a 15.1% improvement compared to diesel at optimal operating conditions. In contrast, BSFC increased with higher butanol content at low load, with W5DBu15 showing the highest consumption due to butanol’s lower calorific value. However, BSFC decreased at higher loads and speeds, with fuel savings of up to 35% compared to base diesel. Combustion analysis revealed that increasing butanol enhanced in-cylinder pressure and heat release rates, though W5DBu15 exhibited delayed ignition and micro-explosion phenomena at low loads. These findings confirm that butanol addition of up to 10% in water-emulsified diesel offers significant thermal efficiency gains and fuel savings without compromising combustion performance. The study supports the potential of alcohol-based bio-additives in enhancing diesel engine efficiency and reducing fuel consumption.
Copyright (c) 2025 AKASYAH, Ahmad Fitri Yusop, S.M Rosdi, Erdiwansyah (Author)
Physicochemical Characterization of Water-Butanol-Diesel Blends for Enhanced Fuel Performance Analysis
This study investigates the physicochemical properties of water-butanol-diesel (WBD) fuel blends to assess their suitability as alternative fuels for diesel engines. The blends analyzed include diesel (D) and emulsified mixtures containing 5% water and varying butanol content: W5DBu5, W5DBu10, and W5DBu15. Key parameters evaluated are density, kinematic viscosity, heating value, cetane number, specific heat capacity, flash point, and oxygen content. Results show that density decreases with increased butanol proportion, ranging from 998 kg/m³ for water to 827.5 kg/m³ for diesel, with W5DBu5 exhibiting a 1.0% lower density than diesel. Kinematic viscosity at 40°C increases slightly with butanol addition, with W5DBu15 showing the highest viscosity at 2.7 mm²/s. The heating value reduces as butanol content rises, with W5DBu15 recording a 15% lower heating value than pure diesel. Cetane number analysis reveals that diesel achieves the highest ignition quality, while W5DBu blends demonstrate extended ignition delays. Water exhibits the highest specific heat capacity, whereas diesel presents the lowest, indicating potential for improved energy absorption in blended fuels. Flashpoint analysis shows a decrease from diesel to W5DBu15, implying changes in ignition safety. Finally, oxygen content increases with water and butanol, with water reaching 89%, enhancing combustion efficiency. These findings demonstrate that WBD blends, particularly W5DBu5 and W5DBu10, offer promising fuel characteristics for optimized engine performance while potentially reducing emissions.
Copyright (c) 2025 AKASYAH, Mohd Adnin Hamidi, Obed Majeed Ali, Erdiwansyah (Author)
The Role of Smart Grids in Enhancing Renewable Energy Utilization in Urban Areas
A smart grid is an innovative solution in electric power systems that enables energy efficiency, renewable energy integration, and grid stability improvement. This study aims to analyze the impact of smart grid implementation on energy efficiency, power loss, carbon emissions, and long-term economic benefits. Based on simulation and analysis results, smart grid implementation can increase energy efficiency by 20-30% compared to conventional power grid. In addition, power loss is significantly reduced from 10% in a traditional grid to 5% in a smart grid, increasing energy distribution efficiency. In terms of sustainability, the smart grid enables more optimal renewable energy integration, with solar power contributing 45%, wind 35%, biomass 15%, and hydro 5%, thus helping to reduce carbon emissions by up to 40% compared to conventional systems. From an economic perspective, cost-benefit analysis shows that although the initial investment of a smart grid is relatively high, within 10 years of implementation, this system can generate net economic benefits of 15-20% through energy savings and operational efficiency. In addition, applying demand-side management strategies in smart grids helps reduce peak load fluctuations by 25%, increases the reliability of the power system, and minimizes the risk of blackouts. Thus, the results of this study indicate that smart grids are a solution that not only improves the efficiency and stability of the power system but also supports environmental sustainability and long-term economic growth.
Copyright (c) 2025 Asri Gani, Mahidin, Muhibbuddin (Author)
Effect of Low-Temperature Heat Treatment on Surface Morphology and Elemental Composition of Empty Fruit Bunch (EFB) Biomass Analyzed by SEM-EDS
This study investigates the effect of low-temperature heat treatment on the surface morphology and elemental composition of Empty Fruit Bunch (EFB) biomass using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). EFB samples were heated at various temperatures ranging from 150°C to 200°C to observe structural changes and the distribution of elements on the biomass surface. SEM analysis revealed that at 150°C, the EFB surface exhibited a rough and porous texture with visible fibres. Increasing the temperature to 190°C and 200°C resulted in smoother surfaces with denser and more compact morphologies due to thermal degradation and particle fusion. EDS results identified the dominant elements present, including Carbon (C), Oxygen (O), Potassium (K), Calcium (Ca), and smaller amounts of Magnesium (Mg), Phosphorus (P), Silicon (Si), and Chlorine (Cl). At 150°C, Carbon content was recorded at 51.43%, while Oxygen was 33.21%. As the temperature increased to 200°C, Carbon slightly increased to 53.77%, and Oxygen decreased to 30.84%, indicating partial carbonization. Furthermore, the presence of potassium and calcium somewhat reduced from 4.39% and 3.37% at 150°C to 3.17% and 3.08% at 200°C, respectively, which suggests mineral volatilization during heating. These findings demonstrate that temperature significantly influences the physical and chemical characteristics of EFB biomass, with the 190–200°C range showing the most notable changes in surface compaction and elemental reduction. This research provides valuable insights into optimizing EFB as a precursor material for bio-based applications through controlled thermal treatment.
Copyright (c) 2025 Bahagia Bahagia, Asri Gani, Yeggi Darnas (Author)
Effect of Thermal Treatment on Functional Group Transformation of Empty Fruit Bunch (EFB) Biomass at 150–200°C: An FTIR Spectroscopic Analysis
Empty Fruit Bunch (EFB) is a lignocellulosic biomass waste with potential as renewable energy through thermal processing. This study analyzes chemical functional group changes in EFB heated between 150°C and 200°C using Fourier Transform Infrared (FTIR). Results show shifts and decreasing intensities of primary functional groups with rising temperatures. At 150°C, FTIR spectra exhibited dominant hydroxyl (–OH) groups at 3616.37 cm⁻¹ and methyl/methylene (C–H) groups at 2918.61 cm⁻¹. Increasing the temperature to 170°C significantly reduced the intensity of –OH groups, shifting peaks to 3495.39 cm⁻¹, and formed aromatic C=C groups at 1591.46 cm⁻¹, indicating the initiation of hemicellulose decomposition. At 200°C, polar –OH groups decreased drastically by over 90% compared to 150°C, leaving a weak peak at 3044.24 cm⁻¹. The stable aromatic C=C group at 1592.96 cm⁻¹ indicated lignin dominance post-heating. Peaks of aromatic C–O and C–H bonds strengthened in the 500–900 cm⁻¹ range, suggesting aromatic carbon compound formation. Results indicate 200°C as optimal for enhancing EFB quality as a solid fuel, yielding a stable, hydrophobic chemical structure. This study provides insights into effectively optimizing EFB waste utilization for alternative energy through thermal modification.
Copyright (c) 2025 Asri Gani, Hera Desvita, Erdiwansyah (Author)
Analysis of the Effect of Biodiesel Mixtures on Pressure, Temperature, and Heat Release Rate in Diesel Engines
This study analyzes the effect of biodiesel blends on the combustion characteristics of diesel engines, including in-cylinder pressure, in-cylinder temperature, and Rate of Heat Release (ROHR) at 75% and 100% loads. The fuels used were pure diesel (DB100) and biodiesel blends with compositions F10B10, F20B10, F20B20, and F30B10. The results showed that peak in-cylinder pressure increased with the use of biodiesel. At 75% load, the maximum pressure for DB100 was 69 bar, while F30B10 reached 72 bar. At 100% load, the maximum pressure for DB100 was 70 bar, while F30B10 increased to 74 bar. In addition, the in-cylinder temperature also increased with the biodiesel blend. At 75% load, the peak temperature for DB100 was recorded at 1480 K, while F20B20 reached 1550 K. At 100% load, the temperature increased to 1600 K for DB100 and 1700 K for F10B10. ROHR analysis showed that biodiesel increased energy release compared to pure diesel. At 75% load, DB100 had a peak ROHR of 52,000 kW, while F30B10 reached 57,000 kW. At 100% load, DB100 recorded a ROHR of 48,000 kW, while F30B10 increased to 58,000 kW. The results of this study indicate that biodiesel blends can improve combustion efficiency, which is characterized by increased pressure, temperature, and heat release. However, this increase can also cause an increase in NOₓ emissions, so an emission mitigation strategy is needed to balance energy efficiency and environmental impacts.
Copyright (c) 2025 AHMAD FITRI, Muhammad Faisal, Muhammad Ilham Maulana (Author)
Analysis of the Effect of G95M5 Fuel Mixture on Engine Vibration Characteristics at Various Operating Speeds
This study analyzes the effect of using a G95M5 fuel mixture (95% gasoline + 5% methanol) on engine vibration characteristics at various operating speeds. The analysis was carried out in the frequency and time domains to identify changes in vibration patterns due to fuel variations. Tests were carried out at 1000 rpm and 1500 rpm, with an acceleration sensor used to measure vibration amplitude. The frequency spectrum results show that at 1000 rpm, G100 fuel (100% gasoline) produces a higher vibration acceleration peak of around 0.030 m/s², while G95M5 only reaches 0.005 m/s², indicating that methanol helps dampen vibrations at low speeds. However, at 1500 rpm, there is an increase in vibration acceleration in G95M5, with a maximum peak reaching 0.07 m/s², compared to G100, which is only 0.035 m/s². Time domain analysis shows the same trend: at 1000 rpm, G95M5 has a maximum vibration amplitude of ±0.006 m/s², lower than G100, which reaches ±0.028 m/s². Conversely, at 1500 rpm, the vibration amplitude of G95M5 increases to ±0.065 m/s², greater than G100, which is only ±0.04 m/s². These results indicate that methanol in the fuel mixture can dampen vibration at low speeds but increase vibration intensity at high speeds. Therefore, methanol content optimisation is needed to balance combustion efficiency and engine mechanical stability.
Copyright (c) 2025 S.M Rosdi, Mohd Hafizil Mat Yasin, Erdiwansyah, Muhtadin (Author)
Bibliometric Analysis of Renewable Energy Research Trends Using VOSviewer: Network Mapping and Topic Evolution
This article presents a bibliometric analysis of renewable energy research trends using VOSviewer software. The study aims to map the collaboration network between researchers, institutions, and countries and to identify the evolution of emerging topics in the field of renewable energy. The data is taken from leading scientific databases covering publications in recent years. The article uses network map visualisation techniques to reveal collaboration patterns and research distribution focused on critical themes like solar, wind, and bioenergy. In addition, the article analyses frequently occurring keywords, helping to identify emerging topic trends. The results of this study are expected to provide insights into the direction of future developments in renewable energy research and encourage increased international collaboration in the field.
Copyright (c) 2025 Irhamni, Erlina Kurnianingtyas, Muhtadin, Bahagia, Ahmad Fitri Yusop (Author)
Optimisation of home grid-connected photovoltaic systems: performance analysis and energy implications
In the increasing need for renewable energy, grid-connected photovoltaic (GCPV) systems at home are a promising solution to reduce dependence on fossil fuels. This article examines the optimization of home GCPV systems, focusing on performance analysis and the resulting energy implications. It also analyzes the performance of a photovoltaic system with a capacity of 3000 Wp connected to the electricity network to people's homes. Through case studies using empirical data and computer simulations, this research evaluates various GCPV system configurations to determine the most energyefficient scenario. Without the influence of shadows, this system is designed to meet daily household energy needs with seasonal modulation. The simulation results show annual energy production of 4446 kWh and energy use of 3379 kWh, with a performance ratio of 83.79% and a diesel fraction of 55.40%. This article discusses the simulation methodology, results, and implications of using PV systems in the context of energy efficiency and sustainability.
Copyright (c) 2025 Asri Gani, Saisa, Muhtadin, Bahagia, Erdiwansyah, Yuni Lisafitri (Author)
Overview of biomass-based waste to renewable energy technology, socioeconomic, and environmental impact
The increasing energy demand has impacted global economic development. The increase in energy and the growing economy have strained the supply chain of energy sources. The higher energy demand can still be covered by the availability of fossil energy, making it one of the sources of environmental pollution. Therefore, finding safe, renewable, and sustainable alternatives has become urgent. Energy from waste is one of the alternative sources to fossil fuels as it is sustainable for economic, social, and environmental growth. A significant contributor to the development of renewable energy, the economy, and the environment is municipal solid waste (MSW). Waste disposal and scarcity of renewable energy sources have become challenging problems, especially in developing countries. This has caused problems both economically, socially, and environmentally. Based on these problems, researchers' interest in converting and developing alternative energy from solid waste has attracted worldwide attention. Reliable waste-to-energy technologies have been developed under various scenarios such as plasma, thermal conversion (pyrolysis, incineration, torrefaction, and gasification), biochemical, and mechanical technologies. In addition, automated biological treatment technologies (MBT), bioelectrochemical, and photo-biological processes aim to remedy developing countries' energy scarcity. The framework for evaluating solid waste-to-energy technologies was reviewed in depth to facilitate the work of researchers in carrying out their duties in the field. Furthermore, this review is to conclude that renewable energy sources from solid waste have the potential to meet energy needs. Thus, MSW management can address environmental pollution efficiently.
Copyright (c) 2025 Syaifuddin Yana, Aulia Annas Mufti, Sillak Hasiany, Vera Viena, Mahyudin (Author)
Advancements in Communication and Information Technologies for Smart Energy Systems and Renewable Energy Transition: A Review
As the energy sector significantly impacts global greenhouse gas emissions, it is essential to decarbonize energy systems to mitigate climate change. Two primary obstacles in decarbonising energy systems include planning for renewable transitions and ensuring sustainable system operations. However, there is hope on the horizon. The potential of new information and communication technologies to enhance future innovative energy systems' planning and operational phases is immense. These systems are characterized by high renewable energy integration and decentralized configurations. This paper offers an extensive examination of how these emerging technologies, such as artificial intelligence, quantum computing, blockchain, advanced communication technologies, and the metaverse, apply to renewable transition and intelligent energy systems. It discusses pertinent research avenues by analyzing existing studies. The review includes industrial use cases and practical demonstrations of innovative energy technologies, providing a glimpse into the promising future of energy systems.
Copyright (c) 2025 Bahagia, Muhammad Nizar, Mohd Hafizil Mat Yasin, S.M Rosdi, Muhammad Faisal (Author)
A brief overview of the physical layer test system: Development of an IoTbased energy storage and electrical energy distribution system
Solar power systems are an efficient and sustainable solution for household and commercial energy needs. This study discusses the integration of critical components such as solar panels, inverters, batteries, and charge controllers, as well as the use of IoT systems to monitor and control energy distribution. The results of the analysis show that using inverters to convert direct current (DC) to alternating current (AC) and store energy in batteries ensures the continuity of electricity supply. The IoT system also improves efficiency by providing intelligent control. In conclusion, this system offers high reliability and efficiency in utilising renewable energy.
Copyright (c) 2025 Dongdong Li, Mohd Ikram, Jiang Xiaoxia (Author)
Optimisation of Microgrid by HOMER Pro Software Design: Innovative Approach and Performance Evaluation
This study analyses the performance of a renewable energy-based microgrid with the integration of Canadian Solar MaxPower CS6X-325P and the primary electricity grid. The findings demonstrate that solar panels can supply more than 50% of the annual energy demand, with maximum penetration during sunny months. The PV system with an installed capacity of 2.24 kW produces 2,731 kWh per year. Dependence on the electricity grid occurs during low irradiance periods, but there is no supply shortage for the load. The strong linear relationship between solar irradiance and PV power output indicates high efficiency in energy conversion. The findings also show that the system successfully sells excess energy to the grid when production exceeds consumption. This study emphasises the potential of microgrid systems in maximising the use of renewable energy, although increased storage capacity is needed to reduce dependence on the conventional grid.
Copyright (c) 2025 Cristina Efremov, Sudhakar Kumarasamy (Author)
Analysis of the concentration microplastics on waste generation in the beach: A case study Banda Aceh City, Indonesia
The area of the aquatic ecosystem has been affected by the waste from the disposal of human products and the transportation of ocean currents and winds. The waste collection system used in this study uses the transect method. The analysis results show that garbage on Alue Naga and Ulee Lheue beaches is 7,328.6 grams (macro) and for (meco) 518.9 grams. The highest density of Meco waste was found at Ulee Lheue Beach at 0.32 items/m compared to 0.04 items/m2 . The highest total density of macro waste was found at Ulee Lheue Beach at 2.04 items/m2 . Compared to 0.28 items/m2 .
Copyright (c) 2025 Muhammad Zaki, Adisalamun, Saisa (Author)
Porosity and Pore Volume Analysis of EFB Fiber: Physical Characterization and Effect of Thermal Treatment
This research looked at the shape and physical properties of oil palm empty fruit bunch (EFB) fibre heated to 160°C, mainly looking at the number of pores and their size. The results showed that the EFB sample had a porosity of 68.98% with a pore volume reaching 40.69 cm³ from a total volume of 58.99 cm³. This indicates that most material consists of void spaces or pores, which have potential applications in porous materials such as filtration and adsorption. The microscopic pictures showed that the pores were not spread out evenly, with dense areas being spread out. The density distribution also revealed that the material's structure was not uniform, with larger pores and denser areas concentrating at smaller diameters. This study concluded that thermal treatment at 160°C significantly increased the porosity of the EFB material while maintaining a reasonably dense solid area. These findings provide valuable insights into using biomass waste for applications requiring porous properties and mechanical strength, especially in the energy storage, filtration, and adsorption industries.
Copyright (c) 2025 P. Selvakumar, Asri Gani, Jiang Xiaoxia, Mohd Rosdi Salleh (Author)
Characterization of Porosity and Pore Volume in EFB Samples through Physical and Morphological Parameters
This study analyses the physical and morphological characteristics of oil palm empty fruit bunch (EFB) fibre samples heated at 150°C. Measurements of parameters such as total volume, solid volume, integral volume, and pore volume were carried out to determine the porosity properties of the samples. Based on the measurement results, the total volume of the sample was recorded at 48.28 cm³, with a solid volume of 10.18 cm³, an integral volume of 16.47 cm³, and a pore volume of 38.09 cm³, resulting in a porosity of 78.90%. The morphological images of the samples support these results by showing significant pore distribution. These findings provide important insights into the structure and potential use of EFB fibres in porous material applications, especially in the context of sustainability and biomass waste utilization. This study also contributes to further understanding of the thermal and physical characteristics of natural materials at high temperatures.
Copyright (c) 2025 Asri Gani, Muhammad Zaki, Bahagia, Geubrina Maghfirah, Muhammad Faisal (Author)
Using VOSviewer for Renewable Energy Literature Analysis: Mapping Technology and Policy-Related Research
This article explores using VOSviewer for literature analysis in the context of renewable energy, with a specific focus on mapping research related to technology and policy. The data, drawn from major scientific databases such as Scopus and Web of Science, encompasses publications discussing the development of renewable energy technology and the policies that support its implementation. Leveraging VOSviewer, this study visualises the collaboration network between researchers, institutions, and countries and identifies the evolution of critical topics in renewable energy literature. Keyword co-authorship and co-occurrence analysis are employed to discern global trends in this research. The results of this study provide profound insight into the relationship between renewable energy technology development and the policies that shape its implementation, thereby indicating opportunities for collaboration and innovation in clean energy. This study is poised to be an inspiring reference for policymakers and researchers, offering a comprehensive understanding of the global dynamics of renewable energy research and igniting the potential for transformative collaboration and innovation in the field.
Copyright (c) 2025 Geubrina Maghfirah, Ahmad Fitri Yusop, Zulkifli (Author)