Journal of Engineering and Technological Sciences

Assessment of Groundwater Contamination around Bakung Landfill, Lampung, Indonesia Using Geoelectrical Resistivity and Hydrogeochemical Data

2025-10-06T16:29:16+07:00

This study investigates groundwater contamination caused by leachate migration at the Bakung landfill during the wet and dry seasons using geoelectrical resistivity and hydrogeochemical methods. The objective is to describe groundwater contamination resulting from leachate and assess groundwater quality from nearby wells along the edge of the Bakung landfill. 1D resistivity sounding (vertical electrical sounding (VES)) survey was conducted at eight sounding points using the Schlumberger configuration, and four lines of 2D resistivity imaging (electrical resistivity tomography (ERT)) were acquired inside and outside the landfill site using the Wenner configuration. The 1D resistivity inversion model show that subsurface resistivity values lower than 40 Ωm are likely associated with tuff rocks, whereas resistivity values greater than 40 Ωm are associated with volcanic breccia. The 2D resistivity imaging model indicates a leachate plume. Migrating into the lower layers of the landfill occurs from the northeast and northwest, suggesting potential contamination of shallow groundwater systems as the landfill ages. The hydrogeochemical assessment of groundwater samples followed APHA standards, identifying hydrogeochemical facies using the Piper diagram and interpreting hydrogeochemical processes using the Gibbs and Gaillardet diagrams. The Piper diagram shows the presence of mixed Ca-Mg-Cl, Ca-HCO3, and Na-Cl facies, with the Na-Cl type found only in well W1, which contains leachate. Contaminated areas exhibit slight increases in ionic concentrations. To prevent contamination from migrating into the aquifer, contaminated zones must be identified.

The Presence of Organochlorine and Organophosphate Pesticide Residue in Groundwater at the Upper Citarum Watershed

2025-10-31T16:13:38+07:00

Chemical residue, particularly pesticide from agricultural activities at the Citarum Upper Watershed, is considered an evolving contaminant due to the presence in groundwater samples. Therefore, this qualitative study aims to identify four pesticide residues from organophosphate (OPP) and organochlorine (OCP). Groundwater grab sampling method was applied to collect 31 samples from each location. Extraction was then carried out using the QuEChER preparation technique, followed by gas chromatography-mass spectrometry (GC-MS) analysis. The results showed that Dichlorodiphenyltrichloroethane (DDT) had the highest concentration at 0.1062 mg/L. Chlorpyrifos had the highest detection above the limit of detection (LOD) in 13 groundwater samples, with concentrations ranging from 0.0116 to 0.2469 mg/L. Lindane and diazinon were also detected, with maximum concentrations of 0.03209 mg/L and 0.0698 mg/L, respectively. Risk assessment was further carried out to determine the chronic and acute Hazard Quotient (HQ) for all residue. Dichlorodiphenyltrichloroethane and lindane scored > 1 at maximum concentration in adults, while diazinon was at an acceptable level for all scenarios. However, when children-specific parameters were applied, chlorpyrifos demonstrated HQ>1, suggesting additional health risk for children in the area. Immediate studies of pesticide exposure on public health, specifically in children from the site, are essential due to the critical stages in life.

Two-electron CO2 Reduction Reaction Mechanism on Nickel Cobalt Phosphate Surface Doped by Transition Metal: A DFT Study

2025-10-20T16:15:06+07:00

In this study, we explore the activity and selectivity of the CO2 reduction reaction (CO2RR) to CO and HCOOH on pure and transition metal-doped NiCoPO(100) surfaces using density functional theory (DFT) calculations. The novelty of this work lies in demonstrating that substitutional doping with Mn, Fe, and Cu significantly alters the thermodynamic landscape of CO₂RR, particularly in enhancing selectivity toward HCOOH. While CO remains the dominant product on most surfaces, Mn-doped NiCoPO(100) uniquely reverses this trend by reducing the limiting potential for HCOOH formation to a value lower than that for CO production. Furthermore, Mn doping suppresses the competitive hydrogen evolution reaction (HER), steering the reaction pathway more selectively toward formic acid. These findings introduce Mn-doped NiCoPO as a promising and tunable catalyst platform for selective CO₂ to HCOOH conversion, providing valuable insights for designing efficient catalysts for sustainable carbon utilization.

Data-driven Analysis and Optimization of Combined Cycle Power Plants using Machine Learning Models

2025-09-11T11:26:03+07:00

The current global energy demand relies more on Combined Cycle Power Plants (CCPPs) for their high efficiency and reduced environmental footprint. However, the performance of these plants is very sensitive to several environment parameters including temperature, pressure, humidity, and exhaust vacuum. This paper is intended to use machine learning (ML) approach to model and optimize CCPP energy production based on these factors. The proposed method uses a dataset with hourly environmental measurements, to provide detailed analysis using ML techniques including Random Forests and Neural Networks to identify any potential nonlinear relationships and predict energy output. The results showed that ambient temperature has the most significant influence on energy production, followed by vacuum, pressure, and humidity. In addition, this paper also highlighted optimal environmental conditions that maximize energy output, which can help and support power plant operators in optimizing their operation factors. In summary, the recommendations and outcomes of this paper provide necessary steps for integrating advanced ML techniques into CCPP operations, enhancing both efficiency and sustainability.

The Influence of Magnetically Treated Lubricating-cooling Fluids on Turning AISI 1045

2025-11-11T14:29:38+07:00

This study investigates a novel approach for using cutting fluids (CFs) under the influence of a permanent magnetic field during the turning of AISI 1045 steel with an AISI M2 high-speed steel (HSS) tool. Lubricating and cooling capacities are among the most critical characteristics of CFs. This research analyses the effect of magnetically treated CFs on tool wear and machining temperature. Two types of water-based CFs were employed in the experimental investigation: synthetic and emulsion. To assess the impact of magnetically treated CFs on machining performance, the flank wear (VB) of the cutting tool and cutting temperature were examined under four external cutting conditions: dry-machining, conventional flood cooling, and two magnetically treated CF scenarios. The cutting speed (V) was varied from 25 m/min to 60 m/min, while the feed rate and depth of cut were kept constant at 0.45 mm/rev and 1 mm, respectively. Among the four cutting environments tested, the magnetically treated CFs demonstrated superior wear resistance. The results revealed that applying both magnetically treated CFs during turning reduced tool flank wear by 218% and 188% at the highest cutting speed compared with the conventional use of both CF types. Furthermore, the cutting temperature decreased on average by 9% and 8% when using the two magnetically treated CF types, relative to their traditional counterparts.

Hybrid Ultrasound and Advanced Oxidation Process Regeneration of Spent FCC Catalysts: Optimization and Their Catalytic Performance

2025-10-30T09:01:54+07:00

This study investigated the regeneration of spent fluid catalytic cracking (FCC) catalysts, which become inactive due to the accumulation of poisons at active sites. The objective of the study was to enhance acidity by regenerating spent FCC catalysts through ultrasonic and oxidation processes (UAOPs) and evaluate their effectiveness in synthesizing glycerol monostearate (GMS). The results demonstrate that spent FCC catalysts regenerated with UAOPs can significantly increase catalyst acidity, which plays a crucial role in GMS synthesis. The optimal conditions identified were temperature X1 (60 °C), regeneration time X2 (50 minutes), and flow rate X3 (9 L/h). This optimization was conducted using the Statistica 10 software, resulting in an optimal acidity value of 0.08460 mmol/gram. The GMS yield achieved was 25.33%, which was slightly higher than the yield reported in previous studies utilizing ZSM-5 and dealuminated Y catalysts for the synthesis of glycerol monostearate. Overall, this study suggests that spent FCC catalysts have potential applications in GMS synthesis