Search Results (594)

Thermal overload in internal combustion engines may progressively destabilize lubricant-film integrity and promote severe tribological deterioration within highly stressed contact interfaces. This study investigates the thermo-tribological degradation sequence of a high-mileage gasoline engine subjected to prolonged idle operation under impaired cooling conditions, ultimately resulting in engine seizure. The investigated engine had accumulated 356,724 km, while the lubricant had remained in service for approximately 26,724 km prior to the experiment. The post-failure investigation combined teardown inspection, geometrical camshaft assessment, reverse gravimetric reconstruction, hydraulic tappet surface profiling, XRF surface characterization, laboratory oil analysis, and SEM/EDS evaluation of wear debris. The results demonstrated strongly localized degradation concentrated primarily within the cam–tappet interfaces. Severe non-uniform camshaft wear was accompanied by pronounced hydraulic tappet surface damage and evidence of unstable boundary-lubrication conditions. Laboratory oil analysis revealed elevated wear-metal concentrations, depletion of the alkaline reserve, increased oxidation indicators, and a final Class D oil condition assessment. SEM/EDS characterization identified Fe-bearing wear debris associated with sustained material removal and debris recirculation during the final degradation stage. The combined evidence supports a coupled thermo-tribological degradation mechanism involving lubricant deterioration, boundary-lubrication instability, adhesive wear acceleration, oxidative surface degradation, and debris-assisted surface damage preceding final engine seizure. The present case study provides experimentally documented evidence of lubrication collapse under real-engine thermal runaway conditions and highlights the critical role of lubricant condition in maintaining tribological stability under severe thermal loading. Full article

This paper reviews recent advances in modular permanent magnet (PM) machines and their associated thermal management strategies. It begins by examining developments in conventional PM machines and highlighting their limitations, particularly in fault tolerance and manufacturability. To overcome these challenges, modular stator configurations have been extensively investigated over the past decade. The review discusses the key advantages of modular PM machines, including improved torque density, efficiency, operational reliability, and enhanced fault-tolerant capability, supported by findings from recent studies. The paper then presents a comprehensive review of state-of-the-art thermal management techniques for PM machines, emphasizing their importance in maintaining performance, reliability, and durability under increasingly high-power densities and thermal stresses. Both passive and active cooling approaches are considered, including air cooling, liquid cooling, heat pipes, oil-spray cooling, shaft cooling, and emerging ferrofluid-based cooling technologies. Advances in thermal modelling and coupled electromagnetic–thermal optimization are also highlighted as important enablers for improving machine performance and efficiency. Furthermore, the review explores the interaction between stator modularity and thermal management, with particular attention to how modular machine architectures affect heat generation, thermal paths, cooling integration, and overall thermal performance. Finally, the paper identifies key research challenges and outlines future opportunities for the development of high-performance, thermally robust PM machines for next-generation energy and transportation applications. Full article

This article describes the development of a compact and affordable variable-temperature NMR instrument designed primarily to measure dynamic molecular motion in solids and liquids. The instrument consists of Lab-Tools’ Mk4 palm-top time-domain NMR spectrometer fitted with a Peltier-cooled variable-temperature probe inside a shimmed Halbach magnet. Measurement of NMR relaxation times T₁, T₂, and ${\mathrm{T}}_1\rho$ is possible over the temperature range −20 °C to 70 °C with cooling and heating rates, and data acquisition is controlled from an integrated mini-PC. The overall footprint of the instrument is roughly that of a shoe box, making both in-the-field and bench-top measurements possible. Applications of this instrument include measuring pore-size distribution in porous rocks, the viscosity of oils and tars trapped in porous rock, the properties of polymers, and the viscosity of the liquid components of foods (e.g. fruits, vegetables and seeds). Results of test measurements for calibrated oils and olive oil are presented together with measurements of molecular mobility in a solid polymer. Full article

This study investigates non-isothermal laminar flow of waxy crude oil in a pipe. Due to heat exchange with the surroundings, the flow cools along the pipe length, resulting in a gradual transformation of the oil rheology from Newtonian to viscoplastic behavior. The mathematical model is based on the generalized Navier–Stokes equations coupled with the Shvedov–Bingham rheological model and the effective viscosity approach. The governing equations were solved numerically using the control volume method in the velocity–pressure formulation. The numerical simulations produced velocity, temperature, and effective viscosity fields, as well as pressure-drop data characterizing the rheological state of the waxy crude oil throughout the pipe flow domain. It was established that, in the central region of the inlet flow, the oil retains Newtonian behavior, whereas viscoplastic behavior begins to develop near the pipe wall. Further downstream, the flow progressively transforms into a viscoplastic state over the entire pipe cross-section, accompanied by the formation of stagnant near-wall regions and a plug-flow core. Full article

During heavy oil development, the gathering and transportation of low-temperature wellhead-produced fluids are often accompanied by high viscosity, pipe-wall deposition, and high flow resistance, threatening the continuous and stable operation of gathering systems. Existing studies on wellhead heating mainly focus on overall steady-state heating performance, while variable-flow heat transfer and start–stop control in local heating systems remain insufficiently explored. This study aims to evaluate the steady-state heating capacity, transient thermal response, and start–stop control performance of a localized electric heating section under variable-flow conditions. A 3D fluid–solid-coupled heat-transfer model of the heating element, pipe wall, and internal fluid was developed using COMSOL Multiphysics. The steady-state temperature field, transient heating and cooling behavior, and start–stop control characteristics were analyzed under different flow rates. The results show that, at a heating power of 15 kW and a flow rate of 20 m³/d, the maximum outer-wall temperature reached 564 K, and the average outlet fluid temperature reached 308.83 K, indicating effective heating performance. As the flow rate increased from 10 m³/d to 30 m³/d, the maximum pipe-wall temperature and fluid temperature rise both decreased, whereas the average fluid-side heat-transfer coefficient increased from approximately 700 W/(m²·K) to 1800 W/(m²·K), demonstrating enhanced convective heat transfer. Under a dual-threshold control strategy of 463.15–483.15 K, the system maintained the target temperature near 473.15 K under all tested conditions, while the load factor increased from 37.83% to 86.15%. These findings provide theoretical references and engineering support for optimizing power configuration and improving temperature control strategies in local heating systems for wellhead-produced fluids. Full article

The rapid growth in the electric vehicle sector has increased demand for advanced battery thermal management systems (BTMSs) with high heat-dissipation capacity and temperature uniformity. Immersion cooling using dielectric fluids has recently been recognized as a promising alternative technology to conventional indirect liquid cooling methods. This study investigates the thermal and hydrodynamic behaviour of a sixteen-lithium-ion cell battery (LIB) module immersed in low-viscosity dielectric fluids using three-dimensional computational fluid dynamics simulations. In this context, a total of twenty dielectric fluids are evaluated using the ANSYS Fluent solver, with particular emphasis on the effects of key thermophysical properties, including viscosity, density, specific heat capacity, and thermal conductivity. The simulation findings reveal that mineral oil and PAO4 yield the lowest maximum LIB cell temperatures, with a reduction of approximately 4 K compared to the least effective dielectric fluids, such as undecane and cumene. Moreover, in terms of temperature uniformity, mineral oil, Novec 7000, and PAO4 exhibit the most homogeneous temperature distributions among the twenty dielectric fluids. In addition, they show an improvement in the temperature uniformity index of approximately 32.4% compared with the least effective dielectric fluid, cumene. On the other hand, mineral oil and PAO4 generate significantly higher pressure drops because of their relatively high viscosities, which increases hydraulic resistance and pumping power requirements. These findings demonstrate that excellent thermal performance does not necessarily correspond to optimal overall thermo-hydraulic behaviour. Overall, the results confirm that immersion-BTMS performance is governed by a complex interaction between dielectric fluid thermophysical properties and flow behaviour, highlighting the importance of coupled thermo-hydraulic optimization in the selection of dielectric fluids for next-generation immersion-cooled battery systems. Full article

This study systematically investigated the effects of air-cooled pre-hardening and oil-quenched quenching-and-tempering processes on the microstructure, mechanical properties, and polishing performance of P20 plastic mold steel. Increasing the austenitizing temperature from 820 °C to 940 °C resulted in a more uniform carbide distribution, a slight improvement in hardness, and enhanced polishing performance for both processes. However, grain coarsening at 940 °C reduced the impact toughness from 157.6 J to 111.7 J. After tempering at 650 °C, both processes yielded a tempered sorbite microstructure. However, in the air-cooled samples, the carbides were aligned along the bainite lath direction, whereas in the oil-quenched samples, they exhibited an equiaxed, non-directional distribution owing to the complete recovery of the matrix. Austenitizing at 940 °C followed by air cooling and tempering at 550 °C provides the optimal balance of hardness, toughness, and polishing performance. Mitigating elemental segregation and narrowing the segregation bands represent key strategies for further enhancing polishing performance. Full article

Stainless steel pipes are critical components in industrial systems such as oil and gas transportation and nuclear power cooling. Surface defects can severely degrade their mechanical performance and operational safety. However, existing inspection methods still face challenges including difficult feature extraction, strong reflection interference, and limited accuracy in small-target detection. To address these issues, this paper proposes an improved detection algorithm termed YOLOv8s-BISW (incorporating BiFPN, SGE attention, and WIoU loss), which introduces multidimensional optimizations based on the YOLOv8s baseline. First, an image enhancement module combining Gamma correction and Contrast Limited Adaptive Histogram Equalization (CLAHE) is designed to mitigate uneven illumination and blurred defect imaging. Second, a Bidirectional Feature Pyramid Network (BiFPN) structure is introduced to strengthen multi-scale feature fusion and improve adaptability to defects of different sizes. Meanwhile, a Spatial Group-wise Enhance (SGE) attention module is embedded into the backbone to enhance defect feature representation while suppressing background interference. Furthermore, the Wise Intersection over Union (WIoU) loss function replaces Complete IoU (CIoU) to improve bounding box regression for irregular defects. Experimental results show that the proposed model achieves an mAP of 0.979 on a self-constructed Stainless-steel Tube Flaw (STF) dataset. Compared with the original YOLOv8s, precision, recall, and mAP are improved by 0.007, 0.010, and 0.033, respectively, while the average detection time per image is only 3.7 ms, achieving a favorable balance between accuracy and real-time performance. Compared with mainstream algorithms such as SSD, YOLOv3, and Faster R-CNN, the proposed method demonstrates superior overall performance, providing reliable technical support for automated surface defect detection of stainless steel pipes and offering practical value for intelligent manufacturing quality control. Full article

Coke deposition on the inner wall of helical coils in organic heat carrier (OHC) furnaces imposes additional thermal resistance, which impairs heat transfer and may trigger tube over-temperature failure. However, the quantitative coupling among the coking degree, flow conditions, and wall temperature response in helical coils remains insufficiently characterized. To address this gap, a three-dimensional steady-state conjugate heat-transfer model that resolves the additional thermal resistance of the coke layer is established using computational fluid dynamics (CFD). A dimensionless coking degree ω, defined as the ratio of coke layer thickness to inner tube radius, is introduced to parameterize the deposition state. Parametric simulations are performed at ω = 0–20%, with oil inlet velocities of 1–3 m/s. As ω increases from 0% to 20%, the maximum outer wall temperature rises by 66.1% (344 °C to 572 °C), whereas the maximum inner wall temperature decreases by 6.5%. The inner–outer wall temperature difference increases by over two orders of magnitude (1.61 °C to 251 °C), and the heat absorption of thermal oil declines by 53.4%. Raising the inlet velocity lowers the outer-wall temperature under clean-wall conditions, whereas this cooling effect is markedly diminished under severe coking. These findings provide a quantitative basis for the early-stage diagnosis of coking and safety evaluation of OHC furnaces. Full article

In a context of greenhouse-gas-reduction for climate-change mitigation, Optical Gas Imaging (OGI) is cited by US and EU regulations as a key technology for detecting methane leaks in the oil and gas industry. The paper outlines the principles of OGI, covering specificity of both high-performance cooled cameras and cost-effective thermal infrared uncooled cameras. It explains camera design, the optical-radiometric theory of contrast and sensitivity, and provides a comprehensive description of the key performance indicators (KPIs) such as NETD, NECL, and MDLR; together with parameters that influence them. These theoretical concepts are supported by measurements taken under laboratory conditions and outdoors, with wind and complex scenes. Finally, video-processing methods for visualizing gas leaks are presented, showing how they increase visual sensitivity and reduce the user’s cognitive load. Full article

Vapor compression refrigeration systems account for substantial global electricity consumption, and improving compressor efficiency offers significant potential for energy conservation and climate change mitigation. Linear compressor technology, particularly moving magnet configurations, has attracted attention for its oil-free operation and reduced friction losses, yet comprehensive experimental data under realistic refrigeration cycle conditions remain limited. This study experimentally evaluates the operational characteristics and performance of a moving magnet linear compressor integrated into a complete R134a vapor compression refrigeration system. The investigation systematically varies compressor load from 65% to 85% and pressure ratio from 2.0 to 3.5 while maintaining a fixed condenser temperature of 45 °C. Key parameters, including resonant frequency, piston offset, matching capacitance, power input, mass flow rate, motor and volumetric efficiencies, refrigerant mass distribution, cooling capacity, and coefficient of performance (COP) were measured and analyzed. Results indicate that piston offset remains nearly constant under varying compressor loads, fluctuating around 0.39 mm, but increases by 36% as pressure ratio rises from 2.0 to 3.5, necessitating careful pressure ratio control to prevent mechanical interference. Motor efficiency decreases from 87.7% to 82.4% as the compressor load increases, suggesting favorable part-load operation for domestic energy consumption reduction. This potential remains to be verified through long-term cyclic tests and a full annual energy assessment. The condenser consistently stores over 70% of the refrigerant charge, with distribution most sensitive to operating condition changes. Cooling capacity reaches a maximum of 434.6 W at 85% load and a pressure ratio of 2.0, while the COP achieves approximately 4.5 under the same conditions and decreases to 2.4 at a pressure ratio of 3.5. Normalized COP remains relatively stable at approximately 0.33 across the tested conditions. These experimental findings provide a robust baseline for the design, integration, and control of moving magnet linear compressors in energy-efficient refrigeration applications. Full article

Pour point depressants (PPDs) based on functionalized polyolefins were obtained and evaluated for their efficiency in pour point reducing of Kumkol waxy crude oil (Kazakhstan), which contains 15.2 wt.% paraffin and has a pour point of +17 °C. An ethylene–propylene copolymer (EPR-505A) was treated through grafting of maleic anhydride (MA-g-PO) and then converted into three different derivatives that had an identical polymer backbone: an ester-functionalized, an amide-functionalized, and a combined ester–amide additive. The obtained products were tested at 500 g/t through kinematic viscosity measurements, equilibrium and kinetic interfacial tension analysis, pour point determination, cooling curve analysis, and optical microscopy. The ester derivative reduced the pour point by 7 °C, the amide derivative did so by 5 °C, and the combined additive achieved a 10 °C pour point reduction and a more than twofold decrease in kinematic viscosity at 0 °C. Interfacial tension measurements and adsorption kinetics allowed us to assume that ester groups govern macromolecular solubility and diffusion mobility, while amide groups enhance adsorption affinity at paraffin crystal surfaces. Their combined action shifts crystallization from a collective to a dispersed regime. These findings establish structure–activity relationships between polar group architecture and PPD efficiency. Full article

The hot-spot temperature in oil-immersed 3D wound core transformer has a significant impact on its performance. The complexity of the winding structure and the characteristics of oil flow increase the difficulty of temperature field analysis. To address this challenge, this study aims to propose a comprehensive thermal network model for oil-immersed 3D wound core transformers to accurately calculate the winding average temperature rise and local hot-spot temperature rise with high efficiency. First, based on the principle of constant thermal resistance, a detailed model of high- and low-voltage winding is calculated using 2D finite element simulation technology. An equivalent model is established to obtain the equivalent thermal conductivity. This model considers various variables, including wire diameter, external insulation dimensions, and the vertical and longitudinal spacing of the windings. Next, multiple types of thermal resistance are defined using the thermoelectric analogy method, and a global thermal network model of the oil-immersed 3D wound core transformer is constructed. Using the Gauss–Seidel method and relevant heat transfer theory, factors such as the flow of transformer cooling oil are taken into account, which allows for the calculation of the average temperature rise and local hot-spot temperature rise in the windings. This approach effectively reduces calculation time while ensuring accuracy. Finally, a 50 kVA oil-immersed amorphous alloy 3D wound core transformer is used as a case study, and temperature field experimental tests are conducted to verify the accuracy of the proposed analytical model. Full article

Pipe networks are essential components of modern building infrastructure, including heating, ventilation, and air conditioning (HVAC) water systems, water distribution networks (WDNs), and district heating and cooling (DHC) systems. Leakage in these systems can lead to increased energy consumption, loss of thermal efficiency, and unstable system operation, thereby affecting indoor environmental quality and overall building performance. Despite differences in scale and application, similar leakage mechanisms are also observed in other pipe network systems, such as oil and gas pipelines and liquid cooling networks. These shared characteristics motivate a unified analytical perspective across different applications. This review provides a systematic analysis of leakage diagnosis methods, with a focus on machine learning (ML) approaches. The results indicate that ML methods have become a dominant research direction due to their ability to capture nonlinear relationships and process high-dimensional data. However, their effectiveness is often constrained by the limited availability of labeled leakage data, sensitivity to dynamic operating conditions, and insufficient physical interpretability. This review provides a structured framework for understanding ML-based leakage diagnosis and offers insights into the integration of data-driven and physics-based approaches for pipe network systems. In addition, the potential role of reinforcement learning (RL) is briefly discussed as an emerging direction for handling dynamic and adaptive scenarios. Compared with ML-based methods, RL has not yet been systematically explored in leakage diagnosis and remains at an early stage of development. This review synthesizes current methodologies, identifies key challenges, and outlines future research directions. Full article

Martensitic chromium-molybdenum steels such as 15Kh5M are widely used in high-temperature oil and gas equipment, but their weldability is limited by high hardenability and susceptibility to cold cracking, which usually necessitate energy-intensive preheating. This study evaluates an alternative route based on the combination of root-pass mechanical vibration (50 Hz, ~1 mm amplitude) and post-pass water-air jet cooling during mechanized GMAW. Three welding variants were compared: conventional preheated welding, vibration-assisted welding without preheating, and hybrid thermo-vibrational welding with active cooling. Among the tested conditions, the hybrid route produced the narrowest heat-affected zone, reducing its width from about 7 mm to about 3 mm, which is consistent with a compressed thermal cycle. Microhardness in the heat-affected zone decreased from 380 to 440 HV in the preheated condition to 330–370 HV in the hybrid condition. Optical microscopy further indicated a finer and more homogeneous transformed microstructure in the hybrid case. Results indicate that simultaneous vibro-treatment and controlled cooling effectively mitigate harmful metallurgical effects typically induced by rapid cooling, enabling preheat-free fabrication of thick-walled components. The proposed hybrid approach may offer energy savings, shorter production cycles, and improved automation compatibility in field welding applications. Full article