Search Results (651)

Analyzing the two-phase flow behavior in bearing lubrication is crucial for understanding friction and wear mechanisms, optimizing lubrication design, and improving bearing operational efficiency and reliability. However, the complexity of oil–air two-phase flow in high-speed bearings poses significant research challenges. Currently, there is a lack of comparative studies employing different simulation strategies to address this issue, leaving a gap in evidence-based guidance for selecting appropriate simulation approaches in practical applications. This study begins with a comparative analysis between experimental and simulation results to validate the reliability of the adopted simulation approach. Subsequently, a comparative evaluation of different simulation methods is conducted to provide a scientific basis for relevant decision-making. Evaluated from three dimensions—adaptability to rotational speed conditions, research focuses (oil distribution and power loss), and computational economy—the findings reveal that FVM excels at medium-to-high speeds, accurately predicting continuous oil film distribution and power loss, while MPS, leveraging its meshless Lagrangian characteristics, demonstrates superior capability in describing physical phenomena under extreme conditions, albeit with higher computational costs. Economically, FVM, supported by mature software ecosystems and parallel computing optimization, is more suitable for industrial design applications, whereas MPS, being more reliant on high-performance hardware, is better suited for academic research and customized scenarios. The study further proposes that future research could adopt an FVM-MPS coupled approach to balance efficiency and precision, offering a new paradigm for multi-scale lubrication analysis in bearings. Full article

In order to improve the lubrication efficiency in the bearing cavity, this study establishes a simulation model of the fluid domain of the bearing cavity based on the computational fluid dynamics (CFD) method and systematically studies the flow characteristics of the lubricant and its lubrication mechanism in the high-speed rotary bearing. In the process of high-speed bearing operation, the lubricant is subject to the combined effect of centrifugal force and contact pressure, gradually spreads to both sides of the steel ball, and forms a stable oil film after injection from the nozzle. However, due to the influence of high pressure distribution in the contact area, the actual formation of the oil film coverage is relatively limited. In order to further optimize the lubrication effect, this study focuses on investigating the influence law of different injection speeds and rotational speeds on the bearing air curtain effect. The results of the study show that when the air curtain effect is enhanced, there will be significant shear interference on the trajectory of the lubricant, which is manifested in the phenomenon of “buckling” at the end of the lubricant, thus reducing the lubrication efficiency. To address this problem, this study innovatively proposes the air curtain obstruction coefficient K as a quantitative evaluation index, and through numerical simulation, it is found that the lubricant can effectively overcome the air curtain obstruction and achieve a better lubrication coverage when the value of K is reduced to below 0.4. Based on this finding, the study further confirmed that the lubrication efficiency of bearings can be significantly improved under different operating conditions by rationally regulating the injection rate. Full article

The Threshold Pressure Gradient (TPG) phenomenon exerts a profound influence on fluid flow dynamics in heavy oil reservoirs. However, the discrepancies between the True Threshold Pressure Gradient (TTPG) and Pseudo-Threshold Pressure Gradient (PTPG) significantly impede accurate residual oil evaluation and rational field development planning. This study proposes a dual-exponential conversion model that effectively bridges the discrepancy between TTPG and PTPG, achieving an average deviation of 12.77–17.89% between calculated and measured TTPG values. Nonlinear seepage simulations demonstrate that TTPG induces distinct flow barrier effects, driving residual oil accumulation within low-permeability interlayers and the formation of well-defined “dead oil zones.” In contrast, the linear approximation inherent in PTPG overestimates flow initiation resistance, resulting in a 47% reduction in recovery efficiency and widespread residual oil enrichment. By developing a TTPG–PTPG conversion model and incorporating genuine nonlinear seepage characteristics into simulations, this study effectively mitigates the systematic errors arising from the linear PTPG assumption, thereby providing a scientific basis for accurately predicting residual oil distribution and enhancing oil recovery efficiency. Full article

The converter transformer is subjected to AC/DC composite voltage during operation, and the sealed and time-varying internal state makes its electric field distribution and charge accumulation unable to be monitored in real-time experiments. In this paper, aiming at the influence of bubbles in the oil passage of the converter transformer on charge accumulation before discharge, a simulation model in a laminar flow environment is established, and four different calculation conditions are set to simulate the charge accumulation in 1 s. It is found that under laminar flow conditions, the trapped bubbles on the insulation paper wall play an obvious role in intensifying the charge accumulation in transformer oil, and the extreme range of charge density will increase by about 10⁴ times. Bubbles aggravate the electric field distortion, and the insulation strength of bubbles is lower, which becomes the weak link of insulation. In the laminar flow environment, the oil flow will take away part of the accumulated charge in the oil, but in the case of trapped bubbles, the charge accumulation in the insulating paper will increase from the order of 10⁻² to 10⁻¹. In the case of no bubbles, the transformer oil layer flow will increase the charge accumulation in the insulation paper by 4–5 orders of magnitude. Therefore, it can be seen that the flow of transformer oil will increase the deterioration level of insulation paper. And when the transformer oil is already in the laminar flow state, the influence of laminar flow velocity on charge accumulation is not obvious. The research results in this paper provide a time-varying simulation reference state for the charge accumulation problem that cannot be measured experimentally under normal charged operation conditions, and we obtain quantitative numerical results, which can provide a valuable reference for the study of transformer operation and insulation discharge characteristics. Full article

As the key non-electric protection equipment of an oil-immersed transformer, the gas relay plays an important role in ensuring the safe operation of the transformer. To further enhance the sensitivity of gas relays for the heavy gas alarm, this paper takes the BF type double float gas relay as the research object and proposes a new method for heavy gas setting, which is based on the internal oil flow acceleration characteristics of the gas relay. Firstly, the analytical derivation of the force acting on the gas relay baffle is carried out, and through theoretical analysis, the internal mechanism of heavy gas action under transient oil flow excitation is revealed. Then, the numerical simulation and experimental research on the variation of oil flow velocity and acceleration under different fault energies are carried out. The results show that with the increase of fault energy, the oil flow velocity fluctuates up and down during heavy gas action, but the oil flow acceleration shows a linear correlation. The oil flow acceleration can be set as the threshold of heavy gas action, and the severity of the fault can be judged. At the same time, the alarm time of the heavy gas setting method based on the oil flow acceleration characteristics is greatly shortened, which can reflect the internal fault of the transformer in time and significantly improve the sensitivity of the heavy gas alarm. Full article

Background/Objectives: Basil essential oil exhibits a wide range of biological activities, including strong antimicrobial and anti-inflammatory effects. Considering the health benefits of basil essential oil (BEO) and the favorable properties of alkyl polyglucoside emulsifiers, novel Montanov™-68-based O/W creams containing BEO were developed and characterized. Additionally, the influence of the emulsifier content on the cream’s properties was evaluated. Methods: The physicochemical properties were evaluated by organoleptic examination, physical stability test, and pH and electrical conductivity measurement. The mechanical properties were investigated by rheological, textural, and consistency analyses. In addition, a sensory evaluation protocol was applied. Results: The cream formulations containing 5% and 7% Montanov™ 68 demonstrated physical stability, with no evidence of phase separation during the observation period or following accelerated aging. The pH values remained within the acceptable range for topical use, and a gradual decrease in electrical conductivity over time was observed. The rheological analyses confirmed the non-Newtonian pseudoplastic behavior with thixotropic flow characteristics. The textural analyses demonstrated that the higher emulsifier content led to increased firmness, consistency, cohesiveness, and index of viscosity. The sensory analysis revealed differences between the alkyl polyglucoside (APG)-based cream formulations only in terms of the elasticity and stickiness. Conclusions: Although the rheological analyses suggested the better spreadability of the formulation with 5% emulsifier, this was not confirmed by the sensory analysis. However, the APG-based formulations performed significantly better than the synthetic surfactant-based formulation in terms of the absorption, stickiness, and greasiness (during and after application). These results are encouraging for the further evaluation of APG-based creams containing basil essential oil for topical application. Full article

Naturally fractured reservoirs (NFRs) account for a significant portion of the world’s oil and gas reserves. Among them, corridor-type NFRs, characterized by discrete fracture corridors, exhibit complex flow behavior that challenges conventional development strategies and reduces recovery efficiency. A review of previous studies indicates that failing to identify these corridors often leads to suboptimal recovery, whereas correctly detecting and utilizing them can significantly enhance production. This study introduces a well-testing technique designed to identify fracture corridors and to evaluate well placement for improved recovery prediction. A simplified modeling framework is developed, combining a local model for matrix/fracture wells with a global continuous-media model representing the corridor network. Diagnostic pressure and derivative plots are used to estimate corridor properties—such as spacing and conductivity—and to determine a well’s location relative to fracture corridors. The theoretical analysis is supported by numerical simulations in CMG, which confirm the key diagnostic features and flow regime sequences predicted by the model. The results show that diagnostic patterns can be used to infer fracture corridor characteristics and to approximate well positions. The proposed method enables early-stage structural interpretation and supports practical decision-making for well placement and reservoir management in corridor-type NFRs. Full article

Due to factors such as low porosity and permeability, thin sand body thickness, and strong interlayer heterogeneity, the fluid flow in the tight reservoir (beach-bar sandstone reservoir) exhibits obvious nonlinear seepage characteristics. Considering the time-varying physical parameters of different types of sand bodies, a nonlinear seepage coefficient is derived based on permeability and capillary force, and a low-velocity nonlinear seepage model for beach bar sand reservoirs is established. Based on core displacement experiments of different types of sand bodies, the low-velocity nonlinear seepage coefficient was fitted and numerical simulation of low-velocity nonlinear seepage in beach-bar sandstone reservoirs was carried out. The research results show that the displacement pressure and flow rate of low-permeability tight reservoirs exhibit a significant nonlinear relationship. The lower the permeability and the smaller the displacement pressure, the more significant the nonlinear seepage characteristics. Compared to the bar sand reservoir, the water injection pressure in the tight reservoir of the beach sand is higher. In the nonlinear seepage model, the bottom hole pressure of the water injection well increases by 10.56% compared to the linear model, indicating that water injection is more difficult in the beach sand reservoir. Compared to matrix type beach sand reservoirs, natural fractures can effectively reduce the impact of fluid nonlinear seepage characteristics on the injection and production process of beach sand reservoirs. Based on the nonlinear seepage characteristics, the beach-bar sandstone reservoir can be divided into four flow zones during the injection production process, including linear seepage zone, nonlinear seepage zone, non-flow zone affected by pressure, and non-flow zone not affected by pressure. The research results can effectively guide the development of beach-bar sandstone reservoirs, reduce the impact of low-speed nonlinear seepage, and enhance oil recovery. Full article

The development of inter-well channeling pathways has become a major challenge restricting the effectiveness of the thermal recovery process for heavy oil reservoirs, which leads to non-uniform sweep and reduced oil recovery. This is especially true for the characteristics of the higher injection–production intensity in offshore operations, making the issue more prominent. In this study, a quick and widely applicable approach is proposed for channeling identification, utilizing the static reservoir parameters and injection–production performance. The results show that the cumulative injection–production pressure differential (CIPPD) over the cumulative water equivalent (CWE) exhibits a linear relationship when connectivity exists between the injection and production wells. Thereafter, the seepage resistance could be analyzed quantitatively by the slope of the linear relationship during the steam injection process. Simultaneously, a channeling identification chart could be obtained based on the data of injection–production performance, dividing the steam flooding process into three different stages, including the energy recharge zone, interference zone, and channeling zone. Then, the established channeling identification chart is applied to injection–production data from two typical wells in the Bohai oilfield. From the obtained channeling identification chart, it is shown that Well X1 exhibits no channeling, while Well X2 exhibited channeling in the late stage of the steam flooding process. These findings are validated against the field performance (i.e., the liquid rate, water cut, flowing temperature, and flowing pressure) to confirm the accuracy. The channeling identification approach in this paper provides a guide for operational adjustments to improve the effect of the thermal recovery process in the field. Full article

The deep and ultra-deep oil and gas resources often have the characteristics of high temperature and high pressure, with complex pressure systems and narrow safety density windows, so risks such as gas invasion and overflow are easy to occur during the drilling. In response to the problems of low management efficiency and large gas kick by traditional gas invasion treatment methods, this paper respectively established and compared three intelligent control models for bottom hole pressure (BHP) based on a PID controller, a fuzzy PID controller, and a fuzzy neural network PID controller based on the non-isothermal gas–liquid–solid three-phase transient flow heat transfer model in the annulus. The results show that compared with the PID controller and the fuzzy PID controller, the fuzzy neural network PID controller can adjust the control parameters adaptively and optimize the control rules in real-time; the efficiency of the fuzzy neural network PID controller to deal with a gas kick is improved by 45%, and the gas kick volume in the process of gas kick is reduced by 63.12%. The principal scientific novelty of this study lies in the integration of a fuzzy neural network PID controller with a non-isothermal three-phase flow model, enabling adaptive and robust bottom hole pressure regulation under complex gas invasion conditions, which is of great significance for reducing drilling risks and ensuring safe and efficient drilling. Full article

For cold venting processes frequently employed in oil and gas fields, precisely predicting the instantaneous diffusion process of the vented explosive and/or toxic gases is of great importance, which cannot be captured by the Reynolds-averaged Navier–Stokes (RANS) method. In this paper, the large eddy simulation (LES) method is introduced for gas diffusion in an open space, and the diffusion characteristics of the sulfur-containing natural gas in the cold venting process is analyzed numerically. Firstly, a LES solution procedure of compressible gas diffusion is proposed based on the ANSYS Fluent 2022, and the numerical solution is verified using benchmark experiments. Subsequently, a computational model of the sulfur-containing natural gas diffusion process under the influence of a wind field is established, and the effects of wind speed, sulfur content, the venting rate and a downstream obstacle on the natural gas diffusion process are analyzed in detail. The results show that the proposed LES with the DSM sub-grid model is able to capture the transient diffusion process of heavy and light gases released in turbulent wind flow; the ratio between the venting rate and wind speed has a decisive influence on the gas diffusion process: a large venting rate increases the vertical diffusion distance and makes the gas cloud fluctuate more, while a large wind speed decreases the vertical width and stabilizes the gas cloud; for an obstacle located closely downstream, the venting pipe makes the vented gas gather on the windward side and move toward the ground, increasing the risk of ignition and poisoning near the ground. The LES solution procedure provides a more powerful tool for simulating the cold venting process of natural gas, and the results obtained could provide a theoretical basis for the safety evaluation and process optimization of sulfur-containing natural gas venting. Full article

Deep-sea hydraulic systems, powering a wide range of numerous deep-sea operating equipment, employ many poppet valves to adjust the pressure and flow rate, thereby realizing precise movements of the actuators. With greater depths and ambient pressures, the hydraulic oil viscosity increases exponentially, leading to a significant difference in the performance of the poppet valve compared to on-land usage and across varying depths. Based on the shear stress transport (SST) k-$\omega$ turbulence model and the dynamic mesh method, a computational fluid dynamics (CFD) model of the poppet valve was established. With the viscosity–pressure characteristics considered, the performance of the poppet valve was analyzed under different depths, different inlet flow rates, and different cracking pressures. The results indicate significant performance deterioration in poppet valves at increased depths, characterized by increased pressure loss and extended response rise time. At 11 km underwater, the pressure loss can be 7 MPa larger than the preset cracking pressure of 10 MPa, and the rise time is doubled compared with the land condition. It is recommended to use hydraulic oils with a lower initial viscosity and a slower increase in viscosity with pressure in deep sea conditions. Full article

Improving the reliability and durability of internal combustion engines in marine vessels is a complex issue. The vibrations generated in these engines significantly affect their proper operation. One of the current research challenges is identifying effective methods to reduce, among other things, torsional vibrations generated within the crank–piston system. To mitigate these vibrations, viscous dampers are commonly used. The selection of a viscous damper for a high-power multi-cylinder engine, such as those in marine power plants, requires a thorough understanding of the thermo-hydrodynamic properties of oil films formed in the spaces between the damper housing and the inertial mass. The description of the phenomena involved is complicated by the variable positioning of the inertial mass center relative to the housing during operation. Most previous studies assume a concentric alignment between these components. The main novelty of this work lies in highlighting the combined effect of the eccentric motion of the inertial ring on both hydrodynamic resistance and thermal characteristics, which has not been fully addressed in existing studies. This article defines the oil flow resistance coefficients and develops static characteristics of the dampers. Additionally, it evaluates the impact of the size of the frontal and cylindrical surfaces of the damper on its heat dissipation capacity. The presented characteristics can be utilized to assess the performance parameters of this type of damper. Full article

In this paper, the concept of symmetry is utilized to evaluate the distribution characteristics of flow fields—that is, flow fields with balanced displacement generally exhibit good spatial symmetry. In the late stage of water-flooding reservoir development, identifying flow field distribution and implementing targeted adjustments are crucial for improving development efficiency and enhancing oil recovery. This study establishes a quantitative evaluation index system integrating both static geological and dynamic production factors to comprehensively characterize flow field distribution in ultra-high water-cut reservoirs. The system incorporates residual oil potential abundance, water-flooding ratio, and water influx intensity as key indicators. A flow field classification method based on the K-Means clustering algorithm was proposed, with the Davies–Bouldin index applied to evaluate clustering validity. The approach was validated using the Egg model, where the flow field was effectively classified into four types: inefficient retention field, effective displacement field, dominant displacement field, and extreme displacement field. Adjustment measures were then applied based on classification results. The findings demonstrate that the proposed method weakens dominant displacement areas while expanding effective and inefficient displacement zones, leading to a 1.1 percentage point increase in recovery factor. This research provides a practical and quantitative tool for flow field diagnosis and adjustment, offering valuable technical guidance for managing ultra-high water-cut reservoirs. Full article

Deep coalbed methane (CBM) is rich in resources and is an important replacement resource for tight gas in China. Accurate prediction of post-fracture production and dynamic change characteristics of fractured wells of partial CBM is of great significance in predicting the final recovery rate. In terms of predicting time-series production, the problem one encounters is low prediction accuracy and poor generalisation ability under limited sample conditions. In this paper, we propose a hybrid deep neural network (AT-GRU-MTL) production prediction model based on the combination of an attention mechanism gated recurrent neural network (GRU) and multi-task learning (MTL), where the AT-GRU is responsible for capturing the nonlinear pattern of the production change, while introducing an MTL method that includes a cross-stitch network (CSN) and a weighted loss using homoskedasticity uncertainty to automatically determine the degree of sharing between multiple tasks and the weighting ratio of the total loss function. The model is applied to several typical deep CBM fracturing wells in China, and the accuracy of gas production prediction reaches 90%, while the accuracy of water production prediction is 68%. The experimental results show that, for the blocks with a very large difference in the order of magnitude of the gas and water production, it is very easy for a certain small order of magnitude to be suppressed from learning during the two-way multi-task learning process, which leads to deterioration of its prediction effect; at the same time, the adaptability of the model is evaluated, and it is found that the model is more advantageous for the wells that have been produced for approximately one year. Meanwhile, the evaluation of the model adaptability shows that the model is more dominant in the prediction of wells with production of about one and a half years. Based on the two test wells with shorter (380 days) and longer (709 days) spans, the results indicate that the model may have insufficient sensitivity to the sudden change of the ratio of gas to water and the failure of the dynamic generalisation of the matrix shrinkage–desorption coupling, and the introduction of physical constraints (such as bottomhole flow pressure, etc.) or the division of the data into the production stages may be attempted to deal with the case subsequently. The research results in this paper provide a theoretical basis for dynamic production prediction and analysis in oil and gas field sites. Full article