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Comparative Analysis of the Performance of Palm Oil MES Surfactant and Pine Wood SLS Surfactant on Berea Sandstone in the Imbibition Process Using Neutron Computed Tomography Application
Surfactant flooding is one of the enhanced oil recovery (EOR) methods aimed at increasing crude oil production in Indonesia. This method is implemented after primary and secondary recovery phases, by reducing the interfacial tension (IFT) in reservoir system, when a significant amount of oil remains trapped and cannot be mobilized. This study employs two types of bio-based surfactants: palm oil-derived MES (Methyl Ester Sulfonate) and pinewood-derived SLS (Sodium Lauryl Sulphate). Both are considered promising alternatives to conventional synthetic surfactants. The methodology used involves experimental and analytical laboratory research. Compatibility tests were conducted on MES and SLS solutions with concentrations ranging from 0.5% to 2% at salinities between 5,000 and 10,000 ppm, using Berea sandstone cores and light crude oil samples. The surfactants were characterized at an EOR laboratory, focusing on compatibility testing, which included aqueous stability and phase behaviour evaluations. Further analyses comprised interfacial tension measurements, IFT stability tests, and both static and dynamic adsorption assessments. Core flooding experiments were then performed on Berea cores using injection and imbibition techniques. In addition, neutron tomography imaging was utilized during core flooding to visualize surfactant distribution within the core samples, allowing identification of surfactant flow zones. Analytical calculations were conducted to validate and enhance the interpretation of the recovery factors obtained through both imbibition and injection processes.
Copyright (c) 2026 Muhammad Furqon Haryono Bimantoro, Rini Setiati, Fahrurrozi Akbar, Muhammad Taufiq Fathaddin, Sulistioso Giat Sukaryo, Bharoto Bharoto, Iwan Sumirat, Pauhesti Pauhesti, Priagung Rakhmanto, Refa Amelia Angelica https://creativecommons.org/licenses/by/4.0
Numerical Modelling of Slope Stability for a Placer Deposit: Case Study of the Motronivskyi Open-Pit Mine, Ukraine
Open-pit development of placer deposits in moisture-sensitive, layered sediments requires slope designs that explicitly account for transient hydrology. This study assesses the stability of the eastern non-working wall at the Motronivskyi open-pit mine at Malyshevske zircon-rutile-ilmenite placer deposit (Vilnohirsk, Ukraine) composed of loams, clays, and Sarmatian sands. The research integrated engineering-geological survey data with stratigraphy and laboratory-measured strength parameters for “Northern”, “Central”, and “Southern” pit-wall profiles considering their geometry and hydrogeologic conditions. Numerical analyses used the Phase2 (Rocscience Inc.) finite-element method with a Mohr-Coulomb model and shear-strength reduction to obtain safety factors supported by a classification of landslide hazard levels. Under natural moisture, the safety factor values indicate generally stable conditions: “Northern” – 1.65, “Central” – 1.52, and “Southern” – 1.62. When water-saturated rock massif due to rainfall impact or groundwater rise, the safety factors drop to 1.20, 1.05, and 1.18, respectively. The analysis of shear strains and total displacements in the rock mass represents how wetting sharply lowers effective strength and shifts failure modes from shallow sloughing to coherent bench-scale slides, which can guide operational slope design and water-management strategies in similar placer-deposit settings.
Copyright (c) 2026 Oleksandr Kovrov, Borys Sobko https://creativecommons.org/licenses/by/4.0
Risk Management in the Construction of Metropolitan Running Tunnels Using Emulsion Explosives: Case Study
This study proposes a methodology for calculating the drilling-and-blasting parameters used in the construction of metropolitan running tunnels employing emulsion explosives within an integrated risk-management framework. Drilling-and-blasting operations in metropolitan tunnel construction require high precision in blast-hole design to ensure stable fragmentation and to minimize technical and operational risks. This study aims to develop a risk-oriented methodology for calculating drilling-and-blasting parameters for running tunnels based on the rational spatial arrangement of blast holes and controlled rock fragmentation. The proposed methodology is grounded in elasticity theory and quasi-static and wave-based hypotheses of rock failure under explosive loading. Blast holes are arranged in groups according to tunnel face areas using contour retreat principles. Straight cuts are designed based on the crushing zone radius, followed by calculations of the line of least resistance, explosive consumption, hole spacing, charge per hole, and total explosive expenditure. A power-law relationship is employed to define blast-hole geometry as a function of explosion pressure, hole diameter, uniaxial compressive strength, rock structure, jointing, and geostatic stress conditions. Numerical simulations confirmed the formation of stable inelastic deformation zones and uniform rock fragmentation, significantly reducing the occurrence of oversized blocks at the tunnel face. The study integrates analytical blast-design calculations with numerical stress–strain modelling within a unified risk-management framework for metropolitan tunnelling. Implementation of the proposed methodology improves blasting efficiency and safety, enables up to 14% savings in excavation resources, and reduces technical and operational risks associated with drilling-and-blasting works in urban underground construction.
Copyright (c) 2026 Maksym Kononenko, Oleh Khomenko, Serhii Hapieiev, Roman Tereshchuk, Roman Dychkovskyi https://creativecommons.org/licenses/by/4.0
Seismic Microzonation Based on Microtremor Data for Mapping the Damage Caused by an Earthquake on Bawean Island, Gresik, East Java, Indonesia
Bawean Island in Gresik is classified as an earthquake-prone area due to fault activity in the Java Sea. An example was the earthquake of March 22nd, 2024, which damaged thousands of houses and displaced tens of thousands of residents. The focus of this research is to carry out seismic microzonation utilizing the Horizontal to Vertical Spectral Ratio method with microtremor data to identify soil characteristics and vulnerability zones in the area. The microtremor data were processed through standard HVSR procedures, including signal windowing, frequency filtering, spectral analysis, and inversion, to obtain site specific seismic parameters. The results showed that the dominant frequency (f0) ranged from 0.65 to 4.55 Hz and H/V amplitude (A0) from 2.01 to 6.81 to reflect variations in impedance contrast. The seismic vulnerability index (Kg) was also from 1.04 to 29.54 s/cm², while the average shear-wave velocity up to a depth of 30 meters (V̅S30) was from 112.3 to 927.28 m/s. The correlation between damage data and Kg values showed that low damage corresponded to Kg values of 0-4.8, moderate to 4.8–15, and high to >15. The four parameters, including f0, A0, Kg, and V̅S30 were subsequently used in Fuzzy C-Means (FCM) clustering analysis to classify the area into three vulnerability zones. A microzonation map was also generated using 148 measurement points to show the strong correlation between Kg and the observed damage levels. The results are expected to support disaster mitigation efforts and resilient spatial planning.
Copyright (c) 2026 Maulida Krisna Dewi, Tasya Okta Irwanda, Juan Pandu Gya Rochman, Amien Widodo, Firman Syaifuddin https://creativecommons.org/licenses/by/4.0
Hybrid Luus–Jaakola and Levenberg–Marquardt inversion for magnetic anomalies over 2D fault-like structures
This study presents a shortened summary focusing on the hybrid Luus–Jaakola–Levenberg–Marquardt inversion and its superior performance on both synthetic and Perth Basin data. In this study, a hybrid approach is introduced and evaluated for estimating the geometric and physical parameters of 2D fault structures from magnetic data. This method integrates the global search capability of the Luus–Jaakola (LJ) algorithm with the rapid convergence of the Levenberg–Marquardt (LM) algorithm, enhanced by two components: a multi-start strategy and a controlled perturbation scheme. This combination overcomes the limitations of initial value dependency and the instability of certain parameters, particularly the effective inclination angle (). The performance of the proposed method was assessed using both synthetic and real-world data. The results demonstrate that the hybrid approach provides higher accuracy and stability in parameter estimation compared to each individual algorithm, especially under noisy conditions. Perturbation experiments and sensitivity analysis revealed a clear parameter hierarchy: depth parameters exhibit the strongest amplitude influence (approximately 200–267% variation), followed by the amplitude coefficient (approximately 85%) and the effective magnetization angle (approximately 63%), while the fault dip angle shows minimal amplitude sensitivity (approximately 5%). The analysis of the effective magnetization angle demonstrated its critical role in identifying optimal starting regions for stable estimations, with the location of these regions contingent on the state of other parameters. In the real-data application, the hybrid method yielded parameters consistent with plausible geological models of the area. The findings of this study offer a practical framework for improving magnetic data inversion, particularly in noise-contaminated environments. In this study, a hybrid approach combining the Luus–Jaakola (LJ) and Levenberg–Marquardt (LM) algorithms is introduced for estimating the geometric and physical parameters of 2D fault structures from magnetic data. The method leverages the global search capability of LJ and the rapid convergence of LM, while incorporating a multi-start strategy and controlled perturbation to overcome initial value dependency and instability in critical parameters such as the effective inclination angle (α). The performance was assessed using both synthetic and real-world data. For synthetic data with 15% noise, the hybrid method achieved an RMS of 4.45 nT, significantly outperforming standalone LJ (17.44 nT) and LM (4.60 nT), while reducing the estimation error of α from 25.40% to 9.39% through controlled perturbation. When applied to real magnetic data from the Perth Basin, Australia, the hybrid approach yielded an RMS of 1.33 nT compared to 2.16 nT (LJ) and 10.61 nT (LM), producing parameters consistent with the plausible geological model of the area. These findings demonstrate that the hybrid framework offers superior accuracy and stability for magnetic data inversion, particularly under noisy conditions.
Applied Mathematics, Physics, Space Sciences
Copyright (c) 2026 Mojtaba Babaei, Mohammad Rezaie https://creativecommons.org/licenses/by/4.0
Shear wave modelling from conventional well logs using integrated deep learning Integrated Convolutional Neural Network (I-CNN)
Shear-wave velocity (Vs), together with compressional wave velocity, provides a crucial source of information for both geomechanical and geophysical studies. Vs data are often unavailable. Moreover, direct measurement of Vs remains relatively costly. Four machine learning algorithms were created to predict Vs from traditional well logs in order to get around these restrictions: Probability Neural Network (PNN), Multilayer Feed-Forward Neural Network (MLFFNN), Deep Feed-Forward Neural Network (DFFNN), one-dimensional Convolutional Neural Network (1D-CNN), and an Integrated Convolutional Neural Network (I-CNN). The dataset consists of two wells (19,121 data points were gathered) of authentic industrial wireline logs from two anonymized wells, provided with formal authorization from the data owner exclusively for academic research purposes, including model training, testing, and validation. There were three primary parts in the methodology: (1) pre-processing the data to get rid of noise and change it into the right format; (2) using domain knowledge to drive feature engineering and selection; and (3) training, testing, and optimizing the model. The results demonstrated that the I-CNN model in RCW-1 well achieved the best performance, with an R2 value of 0.971. When applied to the blind well (RCW-2), the I-CNN model maintained strong generalization capability, achieving an average R2 value of 0.956. These findings indicate that the I-CNN outperforms other methods in handling complex, nonlinear relationships in Vs prediction. Overall, this study contributes to the growing body of literature on machine learning applications in petrophysical analysis by introducing an integrated deep learning framework that surpasses traditional approaches.
Copyright (c) 2026 Rahmat Wibowo, Ida Bagus Suananda Yogi, Indra Arifianto, Muh Sarkowi https://creativecommons.org/licenses/by/4.0
Numerical Simulation and Regression-Based Prediction of Rotary Disc Cutter Forces in TBM Rock Cutting
This study introduces a computational framework for estimating disc cutter forces during rotary cutting in Tunnel Boring Machines (TBMs), combining LS‑DYNA with a Smoothed Particle Galerkin (SPG) approach and the Riedel–Hiermaier–Thoma (RHT) material model. A total of 58 simulations were performed to examine how cutter forces vary with radial installation position, rock strength, contact area, and cutter spacing. The results demonstrate that normal, rolling, and side forces increase with rock compressive strength and contact interface size, but decrease as the cutter’s installation radius grows. Regression analysis based on natural logarithmic transformations yielded predictive equations with high accuracy (R² = 0.80–0.91). Each fitted parameter is reported with its standard error and 95% confidence interval, ensuring transparency, reproducibility, and statistical robustness.
Copyright (c) 2026 Ebrahim Farrokh, Hamid Rokhy, Davood Lotfi https://creativecommons.org/licenses/by/4.0
Fall cone test calibration for slope stability analysis
Undrained shear strength is considered as an essential factor to assess the stability of natural slopes and embankments. Traditionally, this parameter is determined through laboratory tests, which are often costly and time-consuming. Recently, geotechnical research has shifted toward using the Fall Cone Test (FCT) for short-term strength estimation. However, prior studies focusing on pure clay soils have often overlooked the combined impact of soil texture and stress conditions on the reliability of FCT-derived values. To address this gap, undrained shear tests were conducted using both the FCT and pocket vane shear devices on samples exhibiting various degrees of consolidation and different textures. The findings demonstrate that applying a constant cone factor of 0.8 in the FCT yields inconsistent results compared to vane shear tests, as this factor fails to reflect the soil's consolidation state and the texture effect. To overcome this limitation, a new empirical expression for the cone factor, based on the overconsolidation ratio and fines content, is suggested. The results indicate that this approach significantly improves the accuracy of undrained resistance calculations by the FCT, thus providing a refined methodology for better risk management related to slope and embankments instability.
Copyright (c) 2026 Youssouf Chalabi, Aissaoui Soufyane, Zadjaoui Abdeldjalil, Aissa Mamoune Sidi Mohammed https://creativecommons.org/licenses/by/4.0
Integrated Gravity–Seismicity Approach to Fault Mapping in the Suoh Depression, Sumatra
The Suoh Depression (West Lampung, southern Sumatra) is an active volcanic basin along the Great Sumatran Fault (GSF), characterized by high seismicity and active geothermal manifestations. This study integrates satellite gravity data and regional seismicity to delineate the subsurface fault architecture that controls deformation in Suoh. We used 3,098 gravity points from the GGMPlus model and topographic information from the 30 m SRTM DEM. Earthquake data were compiled from the BMKG catalogue (1900–2024). Gravity processing included the calculation of the complete Bouguer anomaly (CBA), separation of regional and residual components, and the application of edge-enhancement filters such as horizontal gradients and second vertical derivatives. 2-D forward modelling and 3-D density inversion were subsequently conducted to resolve the geometry of the major fault strands. Seismicity was analyzed to validate gravity-derived structures and identify active segments. The CBA varies from ~35 to ~85 mGal, reflecting major density contrasts across the Suoh basin. The West and East Semangko Faults are the two main strands of the Semangko segment, as shown by derivative maps and inversion results. Additionally, there is a local Penetoh Fault that strikes northwest and extends to a depth of about 6 km. Earthquake clusters coincide with these structures, confirming their current activity. These findings demonstrate that Suoh is an actively deforming pull-apart depression governed by strike-slip kinematics. The updated fault configuration provides critical input for seismic-hazard mitigation, geothermal assessment, and land-use planning in West Lampung.
Copyright (c) 2026 Rahmi Mulyasari, Muh Sarkowi, Angga Jati Widiatama, Hari Wiki Utama, Andri Kurniawan, Rizky J Sianturi https://creativecommons.org/licenses/by/4.0
Three-Dimensional Seepage Back Analysis of Dam Foundation and Abutments: a Case Study of the Karkheh Dam
The foundation of the Karkheh Dam comprises a heterogeneous geological profile of highly permeable conglomerate layers interbedded with relatively impervious mudstones. Following the extreme flood events of March and April 2019, the reservoir first reached its normal water level (NWL) of 220 m above sea level and subsequently rose by approximately 5 m, peaking at 224.82 m on April 5. Although the dam crest is at 234 m, these conditions raised concerns regarding structural stability and potential seepage hazards, particularly during future floods. To mitigate these risks, strict operational measures were implemented to limit the hydraulic gradient within allowable design values, thereby reducing the likelihood of internal erosion and piping in the foundation and abutments. A three-dimensional seepage model of the foundation and abutment system was developed using FEFLOW 3D, incorporating six conglomerate layers at four reservoir levels. The model was calibrated against monitored seepage discharges by adjusting hydraulic conductivity coefficients and validated with piezometric data. The key results included the identification of the uplift pressure distribution beneath the spillway chute and pinpointing the location of maximum uplift pressure, which is critical for implementing new drainage wells. In addition, the analyses determined a threshold reservoir elevation above which the maximum average hydraulic gradient increases to levels that pose a heightened risk of internal erosion in the foundation and abutments. These findings, along with refined permeability parameters and hydraulic gradient distributions, provide deeper insight into the dam’s hydro‑geotechnical response under extreme hydrological loading and support targeted hydraulic safety management.
Copyright (c) 2026 Mohammad Salehinik, Ali Asghar Mirghasemi, Ahmadreza Tabibnejad https://creativecommons.org/licenses/by/4.0
Geographic Information System Application for Prospecting the Sandstone-type Uranium Deposit in the Melawi Region, West Kalimantan, Indonesia
The Melawi region in Indonesia has been identified as a metamorphic-hosted uranium deposit. The occurrence of sedimentary formations in the downstream area suggests the potential for sandstone-type uranium deposits. Previous studies have concentrated on metamorphic-hosted mineralization, resulting in limited exploration of the sedimentary rocks. Geographic Information System (GIS) technology offers valuable support for mineral prospectivity analysis, including uranium exploration. Among various techniques, fuzzy logic has been demonstrated to be effective in generating prospectivity maps to guide uranium resource development. This research aims to develop a prospectivity map for a sandstone-type uranium deposit in the Melawi region. A GIS-based analysis is performed using available spatial datasets, including geological maps, digital elevation models, and uranium occurrences in Melawi. These datasets served as input for constructing a fuzzy logic model based on the genetic model of sandstone-type uranium deposits. The datasets were reclassified, assigned suitability scores, and operated within a fuzzy logic framework to generate a prospectivity map. The results indicate that 36.64% of the Melawi area is high prospectivity zones, 25.34% is medium prospectivity zones, and 38.02% is the low prospectivity zones. The northern part of Melawi exhibits the most favourability for sandstone-hosted uranium mineralization. This study demonstrates fuzzy logic as a practical tool to delineate the favourable area of a sandstone-type uranium deposit in Melawi. Nevertheless, incorporating more diverse spatial datasets and implementing systematic field validation is necessary to locate uranium deposits accurately.
Copyright (c) 2026 Tyto Baskara Adimedha, Roni Cahya Ciputra, Frederikus Dian Indrastomo, I Gde Sukadana, Heri Syaeful, Yoshi Rachael https://creativecommons.org/licenses/by/4.0
Remote sensing of radioactive alteration zones using Sentinel-2 and SPAD chlorophyll measurements in Mamuju, Indonesia
This study investigates natural radioactive mineralization (uranium–thorium) in Mamuju, West Sulawesi, particularly within the fault-controlled Adang Volcanics, an area known for anomalous natural radiation. The objective was to evaluate vegetation stress as a proxy for radioactive mineralization by integrating satellite data and field validation. We processed Sentinel-2A data using band ratios (4/2 iron oxide, 4/3 ferric iron, 11/12 clay) and false colour composites to delineate alteration zones. The Red Edge Vegetation Index (REVI; B3, B4, B6) was calculated to detect vegetation stress. Fieldwork in December 2023 collected 68 SPAD chlorophyll measurements from ferns, interpolated with inverse distance weighting, and compared with independent radiation dose rates. The results show a strong correlation between REVI and SPAD (R² = 0.76), confirming the sensitivity of red-edge bands to chlorophyll variability. SPAD values decreased significantly in high-radiation zones, showing a strong negative correlation with dose rate (R² = 0.90). Values of 4–40 were typical in anomalous radiation areas, while >40 characterized lower exposure. Vegetation stress anomalies and satellite-derived Chlorophyll Index overlapped spatially with alteration zones and were concentrated in the Adang Volcanics along structural controls. Species differences among ferns indicated varied sensitivity to radiation. This integrated approach demonstrates the effectiveness of Sentinel-2 alteration composites, REVI, and SPAD validation as a rapid, low-cost framework for early exploration of radioactive minerals while also contributing to environmental radiation hazard assessment.
Copyright (c) 2026 Nuraisyiah Pertiwi Kamsir, Asep Saepuloh, Very Susanto, Eka Djatnika Nugraha https://creativecommons.org/licenses/by/4.0
Management of Frame-Anchor Fastening Parameters for Preparatory Excavations in Monorail-Based Heavy Cargo Delivery
This article presents a comprehensive study on the management and optimization of frame-anchor support systems for seam preparatory excavations designed for the transportation of large-tonnage cargo via suspended monorail transport. With the intensification of underground mining operations and the increasing use of heavy mechanized transport, ensuring the stability and safety of mine workings under dynamic load conditions has become a critical challenge for engineering. The research proposes an innovative support technology based on the combined fastening of monorail systems to the crowns of metal arches and directly to the roof using deep-embedded anchors. This approach aims to reduce dynamic impacts on the excavation roof and improve the overall reliability of the support system. To evaluate the effectiveness of the proposed support design, a numerical modelling method was employed to simulate the interaction of components within the dynamic system “suspended monorail – support – rock mass.” The stress-strain behaviour of the frame-anchor structure under real load scenarios was analyzed using SolidWorks Simulation software. During the simulation, various parameters were systematically varied, including the spacing of support frames, the length and anchorage depth of the rock bolts, and the mechanical properties of the surrounding rock mass. The results of the analysis enabled the identification of rational design parameters that minimize deformation and enhance load-bearing capacity. In particular, optimal combinations of frame spacing and anchor configurations were found to significantly reduce stress concentrations and improve the stability of preparatory workings under dynamic loading from moving monorail trains. The study demonstrates that effective management of support system parameters can lead to improved safety, reduced material consumption, and faster development of mining panels. The findings have practical significance for the design of underground transport routes and can be incorporated into normative documents governing support systems in dynamically loaded mine environments.
Copyright (c) 2026 Andrii Herasymenko, Leonid Shyrin, Rostyslav Yegorchenko, Ivan Iniutkin, Yuliya Pazynich https://creativecommons.org/licenses/by/4.0
RAM measure of hydraulic powered roof supports in underground longwall coal mines
Mining operations in underground coal mines, particularly those using the longwall method, require continuous progress and the avoidance of interruptions, as any stoppage can lead to roof collapse. Given the mechanization of coal mining and the underground extraction of this mineral, the use of powered supports is essential to prevent roof collapse. To maintain continuity in mining operations, increase production, and simultaneously control and reduce costs caused by downtime and failures of roof support systems, it is necessary to assess their reliability. This paper aims to analyze the reliability, maintainability, and availability (RAM) of powered support equipment. To achieve this, the hydraulic powered support system was selected for data collection and analysis. The results indicate that the time between failures (TBF) and time to repair (TTR) data of the subsystems followed a renewal process, except for the TBF data of the hydraulic subsystem, which followed a non-homogeneous Poisson process (NHPP). The reliability of the subsystems decreased to 85% after 25 hours. The maintainability analysis showed that most failures of the powered roof supports are repaired within 1 hour. Furthermore, the powered support systems operate under desirable conditions with 99.58% availability. However, in order to create an efficient and easy-to-manage maintenance schedule, it was suggested that preventive maintenance activities be performed at the end of each working day.
Copyright (c) 2026 Mohammad Javad Rahimdel https://creativecommons.org/licenses/by/4.0
Experimental Investigation of the Effects of Temperature and Oil Composition on CO2-Crude Oil Swelling, Extraction Mechanisms, and Displacement Performance
CO₂ flooding has several advantages for enhancing oil recovery, including a reduction in crude oil viscosity, a decrease in interfacial tension, and an increase in oil volume through swelling. Although the mechanisms of oil swelling and extraction in CO₂–crude oil systems have been widely studied, the combined effects of temperature and oil composition on these mechanisms—and their influence on CO₂ displacement efficiency in porous media—remain insufficiently understood, especially under high reservoir temperatures. Therefore, this study investigates how temperature and crude oil composition affect swelling-extraction behaviour and CO₂ displacement efficiency. High-pressure and high-temperature (HPHT) PVT tests were conducted to evaluate swelling and extraction phenomena, while slim tube experiments were used to assess oil recovery performance. Tests were carried out at 70°C and 90°C using two light dead oils from an Indonesian field under varying injection pressures. Compositional analysis of produced oils was performed using Gas Chromatography (GC) and further interpreted through SARA fractions (saturates, aromatics, resins, and asphaltenes). Results show that lower temperatures enhance CO₂ extraction efficiency due to higher CO₂ density, leading to more pronounced swelling and miscibility effects. The miscibility was observed within the extraction region, emphasizing the role of hydrocarbon extraction in the miscibility mechanism. Higher temperatures were found to improve oil recovery, primarily due to viscosity reduction. Additionally, increasing CO₂ injection pressure reduced resin and asphaltene content, with evidence of asphaltene precipitation in the porous medium—particularly at lower temperatures. These findings provide valuable insight into how temperature and oil composition influence CO₂–oil interactions and support more effective implementation of CO₂ flooding at elevated reservoir temperatures.
Copyright (c) 2026 Kartika Hartono, Asep K Permadi, Ucok W. R. Siagia, Andri L Hakim, Sumadi Paryoto, Ahlul H. Resha, Syaeful A. Satya, Reno Pratiwi, Maman Djumantara, Dina A. Chusniah https://creativecommons.org/licenses/by/4.0
Magnetic characteristics and mineralogy of cave sediments from Solek Cave, West Sumatra: Implications for paleoenvironmental processes within the cave
Cave sediments are essential as they preserve valuable archives of past environmental and climate conditions that physical and chemical measurements can reveal. In this study, we explore the magnetic characteristics of the cave sediments collected from Solek Cave, West Sumatra, Indonesia to understand environmental processes within the cave. We employed rock magnetic methods, including magnetic susceptibility, isothermal remanent magnetization (IRM), anhysteretic remanent magnetization (ARM), and Curie temperature measurements. Additionally, we used X-ray diffraction (XRD) and scanning electron microscopy (SEM) in order to analyze the magnetic mineralogy and morphology of the cave sediments. The results show a high concentration of magnetic minerals, specifically ferrimagnetic groups, indicated by high magnetic susceptibility ranging between 210.7 and 1301.2 × 10-8 m3/kg, with a mean value of 602.7 × 10-8 m3/kg. The calculated χFD (%) values ranged from 0.2 to 6.6, mostly less than 2%, indicating coarse-grained, multidomain ferrimagnetic minerals. Moreover, results from IRM, ARM and XRD show that the magnetic minerals are dominated by coarse-grained magnetite with a grain size of around 20 to 110 μm. Curie temperature measurements also exhibit various titanium proportions, forming a titanomagnetite phase. The morphology and chemical compositions of the magnetic minerals, determined by SEM and energy-dispersive X-ray spectroscopy (EDS), also support the previous analyses, showing that titanomagnetite is the dominant phase, characterized by coarse grain size and angular shape. The uniformity of the magnetic characteristics and mineralogy suggests a titanomagnetite mineral source likely driven by lithogenic processes such as erosion and fluvial events.
Copyright (c) 2026 Hamdi Rifai, Rizaldi Putra, Wilda Febi Rahmadhani, Nilam Sari, Dessupri Niarti, Wardina Nasution, Erni Erni , Christopher M. Wurster https://creativecommons.org/licenses/by/4.0
Evaluation of a new composition for enhanced demulsification and deposit control in resinous heavy oil emulsions
This study investigates the demulsification performance, deposit formation tendencies, and rheological behaviour of highly resinous crude oils and their blended systems using both an individual demulsifier and a newly formulated laboratory composition. Crude oils X (27% water), Y (32% water), and Z (48% water), along with the mixed emulsions A (31% water) and B (41% water), were examined under various temperatures, reagent dosages, and a demulsification duration of 120 minutes. The individual demulsifier ND-12 and the newly developed W composition were evaluated by determining their optimal dosages and comparing the resulting amounts of residual and ballast water after treatment. Under conditions of 60°C and 120 minutes, the optimal ND-12 dosage was found to be 200 g/t for X, 800 g/t for Y, and 1000 g/t for the highly stable Z emulsion, reducing ballast water to 0.05%, 0.07%, and 0.8%, respectively. Owing to its strong aggregative and kinetic stability, the Z emulsion was also analyzed at 85°C, where the required ND-12 dosage decreased to 750 g/t, and ballast water was reduced fourfold to 0.2%. For the mixed A (X+Z) and B (Y+Z) systems, the optimal ND-12 dosages at 60°C were 1300 g/t and 1100 g/t, achieving ballast water levels of 0.3% and 0.2%, respectively. Compared with individual reagents, the laboratory-prepared W composition showed higher demulsification efficiency, reduced sediment formation related to asphaltenes, resins and paraffins, and a significant decrease in viscosity. The required reagent dosage for treating mixed oil emulsions A and B was reduced by about 2.5 times, while viscosity decreased by approximately six times. In addition, the application of the composition produced a multifunctional inhibiting effect on crude-oil complications by preventing the formation of a structural network of C17–C40 fractions, which are prone to rapid solidification.
Copyright (c) 2026 Aysel Gasimzade, Vali Nurullayev https://creativecommons.org/licenses/by/4.0
Integrated Geoscience, and Geospatial Analysis for Hydrocarbon Exploration in the Khewari Block, Sindh, Pakistan
The Khewari Block, located in the structurally complex Lower Indus Basin of Sindh, Pakistan, occupies a tectonically favorable yet insufficiently explored sector of a Mesozoic–Cenozoic rifted basin known for its hydrocarbon prospectivity. This study employs an integrated geophysical geospatial workflow to confine subsurface architecture and assess reservoir potential. Extensive interpretation of 2D seismic profiles identifies a system of NE-SW-oriented normal faults, horsts, grabens, and local compressional structures, producing a wide range of trap geometries, including fault-bounded closures, rollover anticlines, and tilted fault blocks. Time and depth structure mapping refines horizon geometries and identifies structurally isolated blocks with enhanced trapping potential. Bouguer and residual gravity anomaly maps further resolve density differences associated with uplifted carbonate platforms and sediment-filled troughs, confirming segmentation of the structure based on seismic data. Surface dataset complements, such as DEM-based elevation, slope models, and land-use classification, offer further limitations on terrain accessibility, drainage systems, and operational capabilities. The integration of surface and subsurface datasets reduces the uncertainty in the interpretation process, improves the delineation of traps, and contributes to the most effective well-placement planning. The multidisciplinary approach illustrates the effectiveness of integrating seismic reflection, gravity modelling, and surface-based GIS analysis to create a coherent structural framework of frontier basins. The workflow is transferable to other data-limited regions and provides a robust foundation for evidence-based hydrocarbon exploration and decision-making.
Copyright (c) 2026 Muhammad Junaid, Muhammad Sajid, Taimoor Ahmad, Eko Kusratmoko, Reza Syahputra, Shaukat Khan, Muhammad Kashif https://creativecommons.org/licenses/by/4.0
Modelling the effects of lateral loading on a bent strike-slip fault system: A case study from the Palu-koro and Matano faults, Indonesia
The Palu–koro and Matano faults form a major bent strike-slip fault system in central Sulawesi, Indonesia, accommodating significant crustal deformation associated with regional plate interactions. In this study, we investigate the mechanical response of this fault system using three-dimensional numerical modelling to evaluate how different lateral loading configurations influence fault slip and stress patterns. Dirichlet (displacement-rate) boundary conditions, inferred from regional plate velocities, are applied to the model domain at the x-face, y-face, and in combined x- and y-face configurations. Models with pure x-face or y-face loading generate lateral slip patterns that are mechanically compatible with idealized Riedel shear kinematics; however, the resulting slip sense differs from the present day tectonic motion of the Palu–koro and Matano faults. In contrast, models with combined boundary conditions reproduce first-order characteristics of the observed fault behaviour. In particular, scenarios with dominant lateral loading at the x-face (e.g. 70% x-face and 30% y-face) produce predominantly sinistral slip along both faults and higher slip concentrations along the Palu–koro Fault, consistent with tectonic and geodetic observations. The combined loading models also exhibit a subtle rotation of the maximum principal stress orientation from WNW–ESE along the Palu–koro Fault to NE–SW along the Matano Fault, which is qualitatively consistent with stress orientations inferred from focal mechanism inversions. Overall, the results suggest that combined regional lateral loading, with a dominant north–south lateral movement, provides a plausible mechanical framework for understanding deformation localization and stress rotation within the Palu–koro–Matano fault system.
Copyright (c) 2026 Dian Kusumawati, David P. Sahara, Nanang T. Puspito, Mudrik R. Daryono, Andri D. Nugraha, Andrean V. H. Simanjuntak, Maulidia Ain Bening, Faiz Muttaqy https://creativecommons.org/licenses/by/4.0
Statistical, Geostatistical and Spatial Analysis of Technology-Critical Elements in the Trepça Mine
This study investigates the presence, concentration, and spatial distribution of Technology-Critical Elements (TCEs) in the Trepça Mine, focusing on ore body horizons VIII-XI. During research in the relevant archives (Trepça, ICMM, GSK), it was noted that no statistical, geostatistical or spatial studies have been conducted in the Trepça Mine for Technology-Critical Elements. Mineralizations in Trepça mainly occur as vein structures known as ore bodies. In this study, all existing ore bodies from horizons VIII-XI, were sampled. Representative samples were collected from each active ore body and analysed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to quantify elements including Bi, Co, Ge, V, W, Li, Ga, In, Te, and Nb. Statistical and geostatistical analyses were performed using Microsoft Excel, R Studio, and Golden Software Surfer to assess variability, correlations, and spatial trends. The highest concentrations were observed for Bi (avg. 98.81 ppm; max. 610.4 ppm), W (avg. 28.68 ppm), and Co (avg. 28.47 ppm), with significant variability across horizons. Correlation analyses revealed strong positive relationships between several elements, such as W–V (r = 0.70), W–Ge (r = 0.65), and Bi–W (r = 0.60), suggesting possible common geological origins. These findings highlight the potential for the sustainable recovery of strategic elements from Trepça’s polymetallic ore zones and underscore the mine’s relevance, not only for traditional metals, but also for critical raw materials essential to low-carbon and high-tech industries.
Copyright (c) 2026 Berat Sinani, Blazo Boev, Arianit Reka, Bahri Sinani, Ivan Boev https://creativecommons.org/licenses/by/4.0
Digital Petrographic Approach to Carbonate Reservoir Evaluation in MATLAB
Porosity is a crucial parameter in the characterization of carbonate reservoirs, as it directly influences fluid storage and flow behaviour. Conventional techniques for porosity assessment, such as core analysis and well logging, are often labour-intensive, time-consuming, and costly. This study proposes an automated method for porosity estimation through petrography and image analysis techniques using MATLAB. Thin-section photographs of carbonate rocks are processed through image segmentation, feature extraction, and classification procedures to quantitatively determine porosity. The estimation process relies on RGB-based image analysis, in which variations in colour intensity between the rock matrix and pore spaces are used to distinguish pore regions accurately. The RGB image analysis approach in MATLAB achieves an accuracy of 60.9% when compared with Routine Core Analysis (RCAL) data, indicating a strong correlation between the estimated and measured porosity values. This digital petrography method demonstrates higher accuracy and consistency than conventional manual image analysis, which is often influenced by human interpretation and subjectivity. By automating the image processing workflow, the method enables objective, rapid, and cost-effective porosity estimation. Despite the absence of complex computational algorithms, the MATLAB-based digital petrography technique provides a reliable and efficient alternative for preliminary carbonate reservoir characterization, especially when laboratory or well-log data are limited.
Copyright (c) 2026 Nita Ariyanti, Sugeng Sapto Surjono, Salahuddin Husein, Marsha Khairia Alfany, Firman Syaifuddin, M. Irfan Mashudi https://creativecommons.org/licenses/by/4.0
Stress Transfer and Seismicity Along the Southern Great Sumatran Fault: Insights from the 1994 Liwa Earthquake
The February 15, 1994 Mw 6.8 Liwa earthquake ruptured the southern Great Sumatran Fault (GSF), yet its static stress legacy and relation to subsequent seismicity remain weakly quantified. We integrate high-precision double-difference relocation with Coulomb failure stress (ΔCFS) modelling to evaluate post-1994 stress transfer along the Semangko sector. Using ~16,000 P/S picks and identical inversion settings, we test two 1-D velocity models; CRUST1.0 yields near-zero, narrow differential-time residuals (± 0.3–0.4 s) compared with broader heavy tails for AK135 (± 0.7–0.8 s) and are adopted for the final catalogue. Since phase archives are sparse before 2010, events from 1994 – 2009 are treated as background, whereas 2010–2024 earthquakes are relocated; quality control retains 416 events. Relocation suppresses the artificial ~10 km depth band and collapses epicenters into coherent clusters that delineate the West/East Semangko Faults and Semangko Bay. ΔCFS was computed for depths of 5–20 km and μ′ = 0.2–0.8. All scenarios produce the expected four-lobed right-lateral pattern with maxima >0.10 MPa around WSF-B, ESF-A, and the Kumering Fault. Relocated events preferentially occupy positively loaded regions: ~74% fall at ΔCFS > 0 and ~73% at ΔCFS ≥ 0.01 MPa (10 kPa), robust to μ′ and depth. The results indicate unresolved post-1994 loading on multiple Semangko branches and adjacent segments, highlighting the potential for cross-segment triggering. We advocate expanding seismic and geodetic monitoring and targeted paleoseismic surveys in the Semangko–Kumering corridor to refine recurrence estimates and update physics-based hazard models for southern Sumatra.
Copyright (c) 2026 Andri Kurniawan, Nicolas Silaen, Khalil Ibrahim, Arsy Nurrochman, Ridho Destawan; Nanda Hanyfa Maulida; Irfan Prasetyo, Ahmad Zaenudin, Adhi Wibowo https://creativecommons.org/licenses/by/4.0
Predicting Peak Particle Velocity Induced by Mining Blasting Using Optimized Deep Learning with Coronavirus Herd Immunity Algorithm
One of the most important economic sectors is mining. Open-pit mines are the most common form, and blasting is the most efficient method. This method can cause significant damage due to vibrations. Thus, monitoring and controlling vibrations is important. This research aims to predict vibrations based on the distance and quantity of explosives. To study this, vibrations were estimated using Peak Particle Velocity from seismograph devices. Measurements were done in two large Iranian mines, providing approximately 1000 data points. Considering the data complexity, a deep learning method was selected for modelling. Deep learning has numerous hyperparameters, and their correct adjustment impacts efficiency. The Coronavirus Herd Immunity Optimizer (CHIO) was used to find optimal values. Various criteria were used to test the model efficiency. The results indicate the optimization method improved predictions by at least 4%. The coefficient of determination for random forest, basic deep learning, and optimized methods was 0.861, 0.932, and 0.972. The root means square error values are 3.687, 2.338, and 1.146. The absolute mean percentage error indices are 0.169, 0.128, and 0.068. It is concluded that deep learning has acceptable performance. Its efficiency can be increased by optimization algorithms. The results show an excellent response to the integration of the CHIO method, demonstrating its good capability.
Copyright (c) 2026 Davood Mohammadi Sargini, Mohammad Ataei, Reza Mikaeil, Akbar Esmaeilzadeh https://creativecommons.org/licenses/by/4.0
Integrated Mathematical and Physical Modelling of Salt Ions Leaching from Coal-Mining Waste: Implications for Ecological Safety and Civil Protection
Coal-mining waste heaps represent a significant source of dissolved salts that can be mobilised by precipitation, posing risks to ecological safety and civil protection. This study focuses on the Chervonohrad Central Concentration Plant spoil heap in western Ukraine, where both thermally altered and unaltered argillite were tested. Laboratory column experiments were performed on 100 g samples flushed with deionised water to simulate leaching under controlled conditions. The cumulative leachate volumes reached approximately 432 L, allowing quantification of total dissolved solids and ion-specific contributions. We flushed 100 g columns for 24 h at 300 mL·min⁻¹ (8.5 L recirculated; ≈ 432 L passed), which yielded final filtrate total dissolved solids of 462 vs. 185 mg·L⁻¹ for burnt and unburnt argillite and cumulative leached masses of 3.93 vs. 1.57 g (≈ 2.5× higher for burnt). Early-time contrast was also strong: after 2 h (≈ 0.7 L), burnt reached 183 mg·L⁻¹ vs. 50 mg·L⁻¹ (≈3.7×). Physical observations were combined with a mathematical modelling approach to establish a precipitation-response relationship linking annual rainfall to total dissolved solids release. The results indicate a strong linear increase of annual salt release with precipitation, with burnt materials exhibiting markedly higher fluxes. This integrated framework demonstrates how laboratory data and simple models can be applied to anticipate pollutant releases, supporting ecological safety and informing civil protection measures in coal-mining regions prone to hydrological extremes.
Copyright (c) 2026 Vasyl Karabyn, Iryna Kochmar, Oksana Karabyn, Clint Sutherland, Valentyna Loboichenko, Andrii Khorolskyi https://creativecommons.org/licenses/by/4.0
Ore Genesis and Hydrothermal Evolution of the Cheshmeh-Hadi Stratabound (Manto-type) Copper Deposit in the Volcanic-Plutonic Belt North of the Doruneh Fault, East of the Sepid-Sarve copper deposit (NW Bardeskan, Central Iran): Evidence from Geology, Geochemistry, Fluid Inclusions, and Stable S and O Isotopes
The Cheshmeh-Hadi copper deposit is part of an Eocene volcano-sedimentary sequence located in the southern Sabzevar Zone. The lithostratigraphic sequence, from oldest to youngest, comprises basalt, basaltic andesite, andesite and pyroxene andesite, conglomerate, limestone, siltstone, gypsiferous marl, and Pliocene conglomerate. The mineralized zone occurs within the conglomerate and at the contact between the conglomerate and andesite. The ore minerals consist of malachite-azurite, chalcocite, bornite, covellite and occasionally native copper. The associated hydrothermal fluids show moderate to high salinities, ranging from 3.09 to 13.39 wt.% NaCl equivalent, with homogenization temperatures between 89 and 387°C, indicating fluid mixing during ore formation. Chalcocite is rarely accompanied by quartz, suggesting low silica content in the ore-forming fluids. The δ³⁴S values of sulfide samples from the study deposit range from −24.1‰ to −2.6‰, while δ³⁴S values of hydrothermal H₂S range from −24.3‰ to −2.6‰. The δ¹⁸O values of hydrothermal fluids associated with mineralization fall within the range of basaltic rocks, meteoric waters, and sedimentary rocks. Geochemical variations in major and trace elements suggest the involvement of continental crustal contamination in the magmatic evolution. The studied volcanic rocks fall within the calc-alkaline to shoshonitic fields, formed in a continental arc setting, and are derived from an enriched mantle source influenced by subduction-related fluids. These rocks are characterized by HREE depletion, moderate LREE enrichment, and a weak negative Eu anomaly. Based on the results, the Cheshmeh-Hadi deposit is classified as a stratabound copper sulfide deposit, formed in a volcano-sedimentary setting associated with a subduction-related magmatic arc environment.
Copyright (c) 2026 Morteza Esform, Hasan Zamanian, Alireza Zarasvandi, Alireza Almasi, Mahya Manouchehry Nia https://creativecommons.org/licenses/by/4.0
Detrital Zircon U-Pb Geochronology Reveals Sediment Pathways and Depositional Systems for Lower Miocene Reservoirs, Cuu Long Basin, Vietnam
The oil and gas industry faces increasing challenges in replenishing reserves. Enhancing exploration efficiency requires the integration of diverse datasets to build robust geological models. This study investigates the provenance and depositional systems of Lower Miocene sandstone reservoirs in the Cuu Long Basin (CLB), offshore Vietnam. We integrate 3D seismic, wireline log, conventional core, and detrital zircon U-Pb geochronological data to build a comprehensive source-to-sink model. Our findings reveal that the clastic components of the Lower Miocene sandstones (formations BI.1 and BI.2) predominantly originate from Cretaceous (ca. 105–108 Ma) magmatic rocks of the adjacent Dalat Zone on the Vietnamese mainland, with minor contributions from recycled older crustal sources. Seismic and well data show deposition occurred in environments ranging from alluvial-fluvial plains to more marine-influenced deltaic and coastal plain settings. This work provides new, high-resolution constraints on the provenance, depositional systems, and tectonic controls that influenced reservoir development in the Early Miocene CLB, offering crucial insight for future hydrocarbon exploration in the region.
Copyright (c) 2025 Xuan K. Nguyen, Van X. Tran, Nguyen Tuan, Huynh T. Nguyen, Huu X. Mai, Quoc T. Truong, Dang Truong An https://creativecommons.org/licenses/by/4.0
Hydraulic Connectivity Between the Sava River and Lake Jarun During Drought: A High-Resolution Monitoring and Time Series Approach
This study offers the first detailed insight into the hydraulic relationship between the Sava River and Lake Jarun, an urban lake formed from a former river meander in Zagreb, Croatia. The main objective was to quantify and understand the temporal variability of their hydraulic connectivity under drought conditions. Continuous, high-resolution (hourly) water level monitoring of Lake Jarun, established in April 2022, was combined with interpolated Sava River water levels derived from national gauging stations. Using a suite of statistical tools – Pearson correlation, linear regression, cross-correlation, and the sliding window correlation method – the study assessed the strength, direction, and timing of river–lake interactions. The results revealed a clear but dynamic subsurface connection, with the lake typically responding to river fluctuations after a delay of five to six days. During the exceptional drought in the summer of 2022, this response weakened significantly, and the time lag extended beyond 21 days, indicating reduced hydraulic connectivity. The sliding window approach further revealed temporal variability, with sharp declines in correlation during low-flow periods and rapid recovery during high-water events. These findings highlight the non-stationary nature of hydraulic connectivity in regulated floodplains and the sensitivity of such systems to hydrological extremes. In addition to providing the first high-resolution dataset for Lake Jarun, this study introduces a time-adaptive analytical framework that enhances the understanding of short-term river–lake interactions and supports future management of urban water systems under increasing climatic pressure.
Copyright (c) 2026 Jelena Parlov, Filip Šegović, Kristijan Posavec, Zoran Kovač https://creativecommons.org/licenses/by/4.0
Enhanced desorption of Cobalt from contaminated sandy silty-clay soils
In the present study, we investigated the potential for enhancing the desorption of cobalt contamination in a sandy silty-clay soil contaminated with Cobalt(II)-chloride-hexahydrate. In soils containing silt–clay fractions, effective remediation is primarily prevented by strong surface binding and adsorption processes. Overcoming these limitations requires the establishment of favourable conditions for desorption. In contrast to industrial practices, the potential for desorption was investigated under gradually alkalinizing and reducing conditions. Based on the results, the decrease in the ORP of the saturated system, together with the increase in pH, initiated cobalt desorption. Consequently, within the range above a redox potential from 0 mV to -80 mV and above pH 7.8, the [Co(H₂O)₆]²⁺ cobalt-complex initially formed. Further alkalinization and decreasing redox potential led to the precipitation of the remaining contaminant as Co(OH)₂ cobalt hydroxide. As a result of treatment, an average of 7.33 mg of cobalt was desorbed from the silty-clay surface within 29 days from the initiation of the desorption treatment, corresponding to about 12% of the contaminant present in the system. Furthermore, a lognormal distribution-based prediction function series (average R² = 0.941) was fitted to the obtained concentration data. The results indicate, that the applied procedure is capable of desorbing approximately 15% of cobalt contaminant, which presumably indicates the desorption capacity of the system. The applied method is widely accessible, cost-effective, and environmentally friendly which qualities that are essential for industrial application. The proposed novel approach represents an efficient and effective complementary technique for the future remediation of certain heavy metal compounds.
Copyright (c) 2026 Tamás Bacsó, Márton Tóth https://creativecommons.org/licenses/by/4.0
Predicting the weight and type of drilling mud by machine learning method
Selecting the optimal drilling fluid, defined by its weight and chemical type, is critical for preventing costly wellbore instability and catastrophic accidents. Traditional methods often rely on trial-and-error, past experience or simplified models that fail to capture the complex rock-fluid interactions. While data mining offers a promising alternative, a research gap exists in simultaneously predicting both mud weight and type. This study introduces a novel machine learning framework that concurrently predicts these essential properties. Utilizing a comprehensive dataset extracted from 50 years of daily drilling reports across 20 oil wells, we trained and compared three nature-inspired algorithms: Ant Colony (ACO), Bee Colony (BCO), and Emperor Penguins Colony (EPC) optimization. The results demonstrate that all models achieved high predictive accuracy, with the Bee Colony Optimization (BCO) algorithm emerging as the most precise, yielding a correlation coefficient (R²) of 0.9841 and a root-mean-square error (RMSE) of 0.0245. Furthermore, sensitivity analysis revealed that the Rate of Penetration (ROP) is the most influential parameter on mud properties, surpassing other drilling variables. A key practical finding was the consistent model consensus, with 79-87% confidence, that sea water-based mud with polymer and soltex additives (SW-PO-SX) is the optimal fluid for the studied field. This research provides a robust, data-driven solution that enables a systematic and proactive approach to drilling fluid selection, significantly enhancing operational safety and efficiency.
Copyright (c) 2026 Amin Tohidi, Alireza Afradi https://creativecommons.org/licenses/by/4.0
A review on recent studies in the area of conjugate heat transfer modelling in transformers
The exact position and the value of the hot-spot temperature in a transformer could be estimated by calculation using computational fluid dynamics. However, this approach requires the usage of significant computational resources. In this paper, a review on some recent investigations on this topic is made, focusing thereby primarily on the investigation in which the field distribution of the dependent variables is taken into consideration in a conjugate heat transfer problem. Still, the determination of the hot-spot temperature in the transformer is an open problem. Furthermore, a review on some fundamental aspects related to the heat transfer in the transformer was made, and some new approaches for the calculation of heat transfer in the transformer were proposed: smoothed-particle hydrodynamics, two-fluid model and the application of T-Flows computational software. Thus, the smoothed-particle hydrodynamics is found as a convenient approach, since it is traditionally related to laminar flow, that is present in the transformer; the two-fluid model significantly saves the computational resources, while the application of the computational software T-Flows is free and extremely powerful for computation of conjugate heat transfer and parallel computation. The conducted research defined the guidelines for the future work in numerical modelling of heat transfer in transformers.
Copyright (c) 2025 Alen Cukrov, Ivanka Boras, Martin Jurina, Dino Kovačević, Branimir Ćućić https://creativecommons.org/licenses/by/4.0