Search Results (4,807)

Pipeline transportation of petroleum products remains one of the safest and most efficient methods of bulk energy delivery, yet overpressure events continue to pose serious operational and regulatory challenges. Traditional fixed-gain PI controllers, commonly used with centrifugal pump drives, cannot adapt to varying product densities or transient disturbances such as valve closures that generate water hammer. This paper proposes a self-tuning adaptive controller based on Recursive Least Squares (RLS) parameter estimation to improve safety and efficiency in pipeline pump operations. A nonlinear simulation model of a centrifugal pump driven by an induction motor is developed, incorporating pipeline friction losses via the Darcy–Weisbach relation and pressure transients induced by rapid valve closures. The RLS algorithm continuously estimates effective loop dynamics, enabling online adjustment of proportional and integral gains under changing fluid and operating conditions. Simulation results demonstrate that the proposed RLS-based adaptive controller maintains discharge pressure within ±2% of the target setpoint under density variations from 710 to 900 kg/m³ and during severe transient events. Compared to a fixed-gain PI controller, the adaptive strategy reduced pressure overshoot by approximately 31.9% and settling time by 6%. Model validation using SCADA field data yielded an $R^2$ = 0.957, RMSE = 3.95 m³/h, and normalized NRMSE of 12.6% (by range), confirming strong agreement with measured system behavior. The findings indicate that RLS-based self-tuning provides a practical enhancement to existing pipeline control architectures, offering both improved robustness to abnormal transients and greater efficiency during steady-state operation. This work establishes a foundation for higher-level supervisory and game-theoretic coordination strategies to be explored in subsequent studies. Full article

Carbon dioxide emissions, particularly from large point sources such as fossil-fuel power plants, represent a primary driver of global warming. Although various carbon-based adsorbents have been developed for carbon capture applications, most existing materials exhibit limited CO₂ adsorption capacity at flue gas-relevant partial pressures and are susceptible to interference from impurity components. In this study, a series of nitrogen-doped carbons was prepared from commercial phenolic resin and melamine via a two-step carbonization–activation process. The effects of precursor-to-dopant ratio and thermal conditions on CO₂ adsorption were systematically investigated. The results indicated that CO₂ uptake was influenced by specific surface area, nitrogen content, micropore volume, and total pore volume, with a maximum adsorption capacity of 2.455 mmol·g⁻¹ and selectivity over 28 at 25 °C and 1 bar. The series also exhibited excellent cycling stability (<1% loss after 5 cycles) and fast kinetics (>90% uptake within 3 min), suggesting its potential applicability in flue gas CO₂ capture. Full article

In high-altitude highway tunnels, the efficiency of jet fans significantly impacts the performance and energy consumption of ventilation systems. To optimize jet fan efficiency under such conditions, this study combines outdoor model experiments with numerical simulations of physical models in longitudinal jet ventilation systems. A model was established using SpaceClaim (ANSYS 2022 R1), and numerical simulations were conducted using Fluent software (ANSYS 2022 R1) to obtain results. The effect of different mounting inclination angles (0° to 10°) on the performance of a jet fan was experimentally investigated, and a correlation formula for the lift pressure of the jet fan under different inclination angles was established. Comparative results demonstrate that the numerical simulations accurately capture the variation trend of fan lift pressure under different tilt angles observed in the experiments. Specifically, the lift pressure of the jet fan initially increases and then decreases with increasing tilt angle. Comparative analysis of pressure rise at installation angles of 0°, 2°, 3°, 4°, 5°, 6°, 8°, and 10° revealed that a peak pressure rise of 19.66 Pa was observed at 4° installation, demonstrating optimal performance at this angle. The velocity distribution indicates that tilt angles between 0° and 4° increase the airflow influence range, beyond which efficiency decreases due to kinetic energy loss at the base. The study determined that under these conditions, a jet fan installed at a 4° inclination angle exhibits optimal performance in high-altitude straight tunnels and is thus identified as the optimal installation angle. At this angle, both pressure-rise efficiency and airflow stability are effectively balanced; this configuration provides a critical design basis for energy-saving optimization in high-altitude tunnel ventilation systems. Full article

Sm₂TM₁₇ sintered magnets (TM = Co, Fe, Cu, Zr) are utilised in high-temperature rotor applications due to their stable magnetic properties at elevated temperatures of 200–350 °C. However, Sm and Co are critical elements, and the reliance on virgin material supply chains must be reduced. Hydrogen decrepitation (HD) could facilitate magnet-to-magnet recycling of scrap material, but the milling characteristics of the powders generated by HD requires investigation. Sm₂TM₁₇ sintered magnets were exposed to 18 bar and 2 bar hydrogen pressure at 100 °C for 72 h and then knife-milled, roller ball-milled, and planetary ball-milled for varying milling times utilising a variety of surfactants. The particle size and morphology of the powders were investigated, and sintered magnets manufactured from chosen powders were characterised in terms of composition, density, microstructure, and magnetic properties. Knife milling for two minutes showed major particle size reductions of 70 and 82% in D50 for 18 bar and 2 bar samples respectively. Roller ball milling trials showed that a cyclohexane and oleic acid mixture was the most effective at reducing particle size, reducing D10, 50, and 90 by 92, 91, and 80% respectively. Knife milling HD powder for two minutes and then planetary ball milling this powder in a cyclohexane and 1 wt.% oleic acid mixture generated a particle size distribution of 1.3–6.8 µm. This powder formed a sintered compact with a density 0.08 g/cm³ lower than the as-received material. Sm losses due to oxidation and sublimation in addition to carbon impurities from surfactant usage caused the precipitation of an α-Fe/Co phase and formed ZrC phases respectively. Sm-hydride additions of 2–3 wt.% mitigated the formation of the α-Fe/Co phase, but ZrC phases remained and likely prevented cell structure formation and inhibited domain wall pinning in recycled magnets. Full article

The growing demand for sustainable proteins has driven interest in Limnospira platensis (Spirulina) due to its high protein content. However, the presence of the cell wall limits the availability and recovery of proteins within it. Conventional alkaline extraction is widely applied but often results in low yields and excessive solvent consumption. This study compares the efficiency and functional properties of Spirulina proteins extracted using an alkaline method and high-pressure homogenisation (HPH) at 20, 50, 80 and 100 MPa. Following isoelectric precipitation, proteins were collected in precipitate and supernatant fractions and characterized for yield, solubility, phycobiliproteins content, emulsifying and foaming properties, water– and oil–holding capacity, thermal stability and rheological behaviour. Microscopy confirmed progressive cell disruption with increasing homogenization pressures. HPH at 50 MPa increased protein extraction by 28% compared to alkaline extraction and significantly (p < 0.05) improved solubility, oil-holding capacity, foaming and emulsion properties. Phycobiliproteins, particularly C–phycocyanin, were more efficiently recovered in HPH supernatants, achieving a higher purity index than the alkaline method. Rheological analysis showed weak gel-like network formation, whereas excessive mechanical stress reduced functionality. Overall, HPH emerges as an interesting method for obtaining Spirulina proteins with enhanced technological properties; however, pressure optimisation is required to avoid denaturation and functionality loss. Full article

Carbon Capture and Storage (CCS) is a critical technology for promoting carbon reduction and achieving the carbon neutrality goal. As a vital component of CCS projects, the injection process makes it especially important to clarify wellsite layout methods, wellbore parameters, and injection parameters for the safe and efficient storage of CO₂. This article presents a survey of engineering parameter design in typical domestic and international comprehensively compares and analyzes multi-dimensional parameters under different storage conditions such as saline aquifers and basalt, and clarifies the basic adaptation logic that storage types determine engineering parameters, the requirement that engineering designs should be formulated according to reservoir characteristics, and the need for dynamic adjustment of engineering parameters based on actual conditions. Meanwhile, the paper identifies various challenges, including geological hazards in wellsite selection, wellbore corrosion risks, loss of control over injection pressure, and storage safety, corrosion risks, and CO₂ leakage risks caused by thermodynamic phase transitions. It puts forward suggestions such as risk prevention and control strategies, wellbore integrity guarantee systems, injection optimization methods, and leakage prevention and control systems, providing a basis for the engineering design and safety assessment of CCS projects. Full article

The increasing demand for energy efficiency in manufacturing has driven the need for advanced modeling techniques to optimize the machining processes. The honing process, critical for achieving high-precision surface finishes in manufacturing, faces challenges in optimizing tool wear and material removal for enhanced sustainability and efficiency. This study develops a predictive modeling framework using machine learning techniques, including support vector regression (SVR), random forest (RF), and XGBoost, to forecast tool wear (h₁–h₈) and mass loss in honing processes. Experimental tests were conducted on EN-GJL-300 gray cast-iron workpieces using diamond abrasive blades (FEPA F120 and F240) under varied conditions (rotation speed, translation speed, and pressure). The models, trained with 5-fold cross-validation and hyperparameter tuning via GridSearchCV, achieved high accuracy, with SVR yielding R² values of 0.9609–0.9782 for wear predictions and XGBoost achieving R² of 0.9005 for mass predictions. Incorporating grain size as a predictor showed that finer grains (54 µm vs. 120 µm) reduced wear, thereby improving prediction reliability. The proposed models enable precise control of honing parameters, enhancing tool life and process efficiency, with implications for sustainable manufacturing in automotive and precision engineering applications. Full article

This study presents a computational–experimental assessment of two industrial centrifugal fans used in cement production, focusing on aerodynamic optimization and energy efficiency validation. The first case concerns a Farin Kiln Filter Fan initially constrained by existing inlet duct geometry, which caused vortex formation, flow asymmetry, and a pressure loss exceeding 15%. CFD analyses identified major inlet vortices and asymmetric splitter loading, guiding a redesigned configuration with an expanded fan body (1982–2520 mm), an increased outlet width (1808–1858 mm), and a vortex breaker to stabilize inlet flow. CFD simulations indicated a flow rate of 601,241 m³/h, static pressure of 2200 Pa, and total pressure of 2580 Pa, achieving an 83% efficiency. Field validation confirmed a 34.4% reduction in shaft power, 30% decrease in torque, and 4% gain in efficiency, corresponding to 449 MWh/year energy savings and 180 t CO₂/year emission reduction, assuming 8000 operational hours. The second case involves an Induced Draft (ID) Fan designed for 441,643 m³/h flow at 990 rpm. Transient CFD simulations using the SST k–ω model captured rotor–stator interaction and confirmed the effectiveness of the design revisions in suppressing swirl and flow separation. The optimized design achieved 8653 Pa static pressure, 9203 Pa total pressure, and 83% efficiency under design conditions. Field measurements showed a 26.2% drop in shaft power and 19.6% improvement in efficiency, yielding 2527 MWh/year energy savings and an estimated 1011 t CO₂/year emission reduction. Overall, the CFD-guided redesign framework demonstrated strong alignment between simulations and field measurements, highlighting the method’s practical relevance for improving fan performance and energy sustainability in industrial systems. Full article

Background: Surgical site infections (SSIs) following spinal and thoracic procedures are associated with prolonged hospitalization and increased morbidity, with incidence rates of 2–15% in spinal surgery and 3–12% in thoracic procedures. Multiple patient-related and procedure-specific factors contribute to wound complications, including diabetes mellitus, obesity, smoking, extended surgical time, excessive tissue dissection, and hardware implantation. Implementing evidence-based prevention and early intervention strategies is essential in high-risk surgical cohorts. Methods: This narrative review followed searches in PubMed, Scopus, ScienceDirect, Cochrane Library, and Embase for studies published between January 2000 and October 2025. Eligible peer-reviewed articles examined SSI incidence, risk factors, or prevention strategies in adult patients undergoing thoracic or spinal surgery. Data extraction focused on operative parameters, antibiotic prophylaxis regimens, negative-pressure wound therapy (NPWT) use, and patient outcomes. Results: Evidence from found recent studies was synthesized. Key findings demonstrated that operative duration > 4 h increased SSI odds by 41% per additional hour, and blood loss > 500 mL doubled infection risk. Prophylactic NPWT reduced deep SSI rates by 50% in high-risk patients (BMI ≥ 35, diabetes, multilevel instrumentation). Intrawound vancomycin powder reduced deep SSIs by 50–60%, particularly in multilevel fusions. Administering prophylactic antibiotics within 30 min of incision was significantly more effective than at 60 min, with a 23% relative risk reduction. Weight-adjusted antibiotic dosing in obese patients lowered SSI rates from 5.1% to 2.9%. Conclusions: Operative parameters strongly predict SSI risk. An integrated risk- and evidence-based approach to wound management following spinal and thoracic surgeries—combining optimized antibiotic prophylaxis, risk-stratified NPWT application, and operative technique modifications—can significantly reduce SSI incidence. Successful implementation requires institutional commitment, multidisciplinary collaboration, and continuous quality improvement to optimize patient outcomes. Full article

This study discusses the effect of different acceleration modes on the shaftless water-jet propulsion pump’s operational performance. Following the usage of Renault-time-mean Navier–Stokes (N-S) equations combined with an application of the shear stress transport (SST) k-ω turbulence mode and reinforced by an experimental test platform, the research explores internal energy loss shaftless water-jet propulsion pump flow behavior under exponential and linear acceleration processes. The results indicate that, compared to linear acceleration, the cavity volume within the impeller is marginally greater during the initial phase of exponential acceleration; however, this trend reverses in the subsequent stages; The amplitude of fluctuations in the pressure pulsation coefficient at both the mid-span and root regions of the blade, along with the amplitude corresponding to the primary frequency of the pressure pulsation, are comparatively reduced. Turbulent entropy production at the rim constitutes a significant component of energy loss; however, the total entropy production exceeds this contribution. Full article

This paper presents a novel pipeline leak diagnosis framework that combines Savitzky–Golay scalograms with a lightweight advanced deep learning architecture. Pipelines are critical for transporting fluids and gases, but leaks can lead to operational disruptions, environmental hazards, and financial losses. Leak events generate acoustic emissions (AE), captured as transient signals by AE sensors; however, these signals are often masked by noise and affected by the transported medium. To overcome this challenge, a fluid-independent detection approach is proposed that begins with acquiring AE data under various operational conditions, including multiple intensities of pinhole leaks and normal states. The transient signals are transformed into detailed scalograms using the Continuous Wavelet Transform (CWT), revealing subtle time–frequency patterns associated with leak events. To enhance these leak-specific features, a targeted Savitzky–Golay (SG) filter is applied, producing refined Savitzky–Golay scalograms (SG scalograms). These SG scalograms are then used to train a Convolutional Neural Network (CNN) and a newly developed lightweight Vision Transformer with streamlined self-attention (LViT-S), which autonomously learn both local and global features. The LViT-S achieves reduced embedding dimensions and fewer Transformer layers, significantly lowering computational cost while maintaining high performance. Extracted local and global features are merged into a unified feature vector, representing diverse visual characteristics learned by each network through their respective loss functions. This comprehensive feature representation is then passed to an Artificial Neural Network (ANN) for final classification, accurately identifying the presence, severity, and absence of leaks. The effectiveness of the proposed method is evaluated under two different pressure conditions, two fluid types (gas and water), and three distinct leak sizes, achieving a high classification accuracy of 98.6%. Additionally, a comparative evaluation against four state-of-the-art methods demonstrates that the proposed framework consistently delivers superior accuracy across diverse operational scenarios. Full article

Background/Objectives: Sleeve gastrectomy (SG) is the most commonly performed bariatric surgery worldwide. It results in significant weight loss and improves metabolic disorders such as hypertension. Weight loss is thought to be the main factor contributing to blood pressure (BP) reduction after SG. Small-intestinal hormones may also mediate the antihypertensive effects of SG. We aimed to investigate the mechanisms underlying the antihypertensive effects of SG through small-intestinal hormones independently of weight loss. Methods: This study involved male Sprague–Dawley rats that underwent a sham operation or SG, followed by a dietary intervention involving a standard diet, a high-fat and high-salt diet, or pair-feeding with SG. Results: Three weeks postoperatively, SG significantly reduced systolic blood pressure (SBP) and increased urinary sodium excretion. RNA sequencing of the small intestine revealed upregulation of the gene encoding prouroguanylin (proUGN). proUGN is a small-intestinal hormone that inhibits renal sodium reabsorption by converting sodium/hydrogen ion exchanger type 3 (NHE3) in the proximal tubules into the inactive phosphorylated form at Ser552 (pS552-NHE3). Furthermore, SG significantly increased proUGN levels in the ileum and plasma, as well as the levels of pS552-NHE3 in the renal cortex. The administration of exogenous uroguanylin, which is converted from proUGN, resulted in increased renal pS552-NHE3, increased urinary sodium excretion, and decreased SBP without body weight reduction. These effects were similar to those observed with SG. Conclusions: SG increases proUGN secretion from the small intestine, leading to increased blood concentration. This inhibits NHE3 activity in the proximal tubules, promotes natriuresis and reduces BP. Full article

Integrated additional cooling channels offer precise thermal management for solid-oxide fuel cells (SOFCs), mitigating temperature gradients. This research studies the thermal–hydraulic performance of cooling channels integrated between SOFC interconnectors, including a Diamond-type triply periodic minimal surface (TPMS), a conventional topology-optimized structure, and a topology-optimized lattice-filled structure. A conjugate heat transfer analysis is employed to investigate the influences of flow rate within the range of Reynolds numbers from 300 to 5000, and the effects of coolant type, including air and liquid metals, as well as the impacts of structural material. The results demonstrate that the topology-optimized lattice-filled structure, generating high turbulence mixing, achieves superior temperature uniformity, especially at high flow rates, despite having higher thermal resistance and pressure loss than the conventional topology-optimized design. The coolant types show the largest influence on thermal–hydraulic performance, and the use of liquid gallium in the conventional optimized design obtains the best temperature uniformity, yielding differences between the maximum and minimum temperatures of less than 5 K. Moreover, the higher-thermal-conductivity material improves temperature uniformity, even at low flow rates. Overall, the optimized-baffle designs in the conventional topology-optimized model, utilizing high-conductivity coolant and structural materials, could be the most suitable for thermal management of the SOFC. Full article

Existing pneumatic artificial muscle (PAM) static geometrical models based on the principle of virtual work provide only approximate force predictions since they neglect the effects of volume change and radial bladder deformation work loss. In this study, we propose an improved geometrical static model called the Accurate Volume and Bladder Deformation Loss (AVBDL) model. This model introduces a physically consistent calculation of muscle volume at different contractions and pressures and incorporates a new way of describing work losses due to radial deformation of the bladder. The hyperelastic properties of the bladder were experimentally characterized and modeled using the Mooney–Rivlin formulation. The AVBDL model was validated against experimental data from four types of pneumatic muscles and compared with three established analytical models. Results show that the AVBDL model significantly improves force prediction accuracy, achieving a normalized root mean square (NRMS) error of 6.7–16.4%, compared to 20–68% for existing models. Due to its analytical transparency, reduced error, and broad applicability, the AVBDL model provides a robust basis for accurate simulation and control of pneumatic artificial muscles. Full article

Grain breakage serves as a primary causative factor for microbial infestation and oxidative deterioration, significantly diminishing product value and resulting in substantial grain waste and economic losses. The grain discharging process represents the most extensively involved and primary breakage-inducing stage throughout harvest handling and processing operations. However, impact and impact-induced breakage behavior during grain discharge are still poorly understood. To elucidate the impact-induced breakage behavior during grain discharge, this study first employed the discrete element method (DEM) to numerically simulate the discharging process, thereby quantifying the variation patterns of grain kinematic characteristics (e.g., velocity and attitude). Building upon the simulated kinematic data, a dedicated impact testing platform was constructed to investigate single-grain breakage. This enabled the determination of critical unit mass impact energy (along 90°: 106.4 J kg⁻¹; along 0°: 57.28 J kg⁻¹) and critical breakage velocity (along 90°: 14.59 m s⁻¹; along 0°: 10.70 m s⁻¹) under two extreme impact attitude conditions. By integrating the DEM-derived kinematics with the experimentally obtained breakage thresholds, a breakage probability zoning diagram for both large-scale and small-scale discharge processes was developed. Finally, leveraging this comprehensive understanding of the flow and breakage mechanics, theoretical models were successfully established to predict key engineering design parameters, including mass flow rate, impact force, and impact pressure. All models were validated and demonstrated excellent predictive capabilities. The research result is of guiding significance for the design of relevant parameters of discharge systems to minimize grain breakage loss to the greatest extent possible. Full article