Search Results (1,988)

This paper provides an in-depth analysis of the microstructural characteristics and the chemical content of Polybutylene Terephthalate (PBT) composites that have different contents of Glass Fiber (GF). Blending of VALOX 420 (30 wt% GF/PBT) with unreinforced VALOX 310 allowed the composites to be prepared, with control of the concentration and distribution of the GF. The GF reinforcement and PBT matrix were characterized by an advanced microstructural spectrum and spatial analysis to show the influence of fiber density, dispersion, and chemical composition on performance. Findings indicate that GF content has a profound effect on microstructural properties and damage processes, especially traction effects in various regions of the specimen. These results highlight the significance of accurate control of GF during fabrication to maximize durability and performance, which can be used to inform the design of superior PBT/GF composites in challenging engineering applications. The implications of these results are relevant to a number of high-performance sectors, especially in automotive, electrical, and consumer electronic industries, where PBT/GF composites are found in extensive use because of their outstanding mechanical strength, dimensional stability, and thermal resistance. The main novelty of the current research is both the microstructural and chemical assessment of PBT/GF composites in different fiber contents, and this aspect is rather insufficiently studied in the literature. Although the mechanical performance or macro-level aging effects have been previously assessed, the Literature usually did not combine elemental spectroscopy or spatial microstructural mapping to correlate the fiber distribution with the damage mechanisms. Further, despite the importance of GF reinforcement in achieving the right balance between mechanical, thermal, and electrical performance, not much has been conducted in detail to describe the correlation between the microstructure and the evolution of damage in short-fiber composites. Conversely, this paper will use the superior spatial elemental analysis to bring out the effects of GF content and dispersion on micro-mechanisms like interfacial traction, cracking of the matrix, and fiber fracture. We, to the best of our knowledge, are the first to systematically combine chemical spectrum analysis with spatial mapping of PBT/GF systems with varied fiber contents—this allows us to give actionable information on material design and optimized manufacturing procedures. Full article

The rising level of atmospheric carbon dioxide (CO₂) is a major driver of climate change, highlighting the need to develop carbon capture and storage (CCS) technologies quickly. This paper offers a comparative review of three main groups of porous adsorbent materials—zeolites, metal–organic frameworks (MOFs), and activated carbons—for their roles in CO₂ capture and long-term storage. By examining their structural features, adsorption capacities, moisture stability, and economic viability, the strengths and weaknesses of each material are assessed. Additionally, five different methods for delivering these materials into depleted oil and gas reservoirs are discussed: direct suspension injection, polymer-assisted transport, foam-assisted delivery, encapsulation with controlled release, and preformed particle gels. The potential of hybrid systems, such as MOF–carbon composites and polymer-functionalized materials, is also examined for improved selectivity and durability in underground environments. This research aims to connect materials science with subsurface engineering, helping guide the selection and use of adsorbent materials in real-world CCS applications. The findings support the optimization of CCS deployment and contribute to broader climate change efforts and the goal of achieving net-zero emissions. Key findings include CO₂ adsorption capacities of 3.5–8.0 mmol/g and surface areas up to 7000 m²/g, with MOFs demonstrating the highest uptake and activated carbons offering cost-effective performance. Full article

Technical drawing is a foundational university course typically taught in the first semester of most technical and engineering programmes. A thorough understanding of the course content and the ability to prepare high-quality technical documentation require basic knowledge of the technological processes applied in product manufacturing. However, these aspects are usually not part of the standard curriculum. The main goal of this research was to examine how the working methodology used during the project task (PT) affects students’ learning outcomes and social interactions. This study explores three different active learning methods applied during the realisation of the PT, involving one individual group and two teamwork groups, in one of which the students had the opportunity to manufacture a final product based on their technical documentation. In all three groups, student-centred and project-based learning methods were employed. This study uses a combination of two quantitative evaluations: one based on the difference in students’ pre- and post-test results and one supported by a survey performed at the end of the semester to capture the students’ experiences during the project and their satisfaction. The results demonstrate that the learning method that allows students to gain hands-on experience in manufacturing their own products significantly improves learning outcomes. Additionally, it enhances students’ satisfaction by fostering social interactions among them. Full article

Heave compensation is crucial for the improvement of marine engineering. However, there remain two main drawbacks in existing methods. One drawback is that the output accuracy of heave information is insufficient. The other drawback is that the consideration of lever arm effect errors is inadequate. To address these challenges, a new heave compensation algorithm is proposed in this paper. Firstly, a vessel’s center of gravity acceleration model incorporating lever arm effect dynamics is established. Secondly, a modified high-pass filter is presented using complementary techniques. A comparative error analysis demonstrates its superiority over traditional digital filters in real-time performance. Thirdly, the algorithm independently updates solutions of the heave of the vessel’s center of gravity and the heave caused by the lever arm vector and the vessel’s attitude to avoid oscillating temporarily. Simulation results verified the better heave measurement accuracy of the proposed algorithm. This algorithm is pivotal to marine engineering. Full article

Modern advanced aero-engine bearing systems typically exhibit structural and loading characteristics with high DN values. The harsh thermal environment and multi-physics loads under operating conditions render the reliability of bearing structural systems particularly sensitive to lubrication efficiency and bearing chamber temperature. This study performs simulation analyses of oil return processes and their influencing factors in an aero-engine main bearing chamber with complex structural features. The results show two primary causes of reduced scavenging performance. On the one hand, the local low-speed region at the inlet of the scavenge pipe causes some oil to fail to enter the scavenge pipe normally. On the other hand, the air in the bearing chamber is disturbed by the rotation of the rotor, which makes oil enter the oil sump with a tendency to return to the oil collection annulus, thereby causing poor oil return. Furthermore, two structural improvements of the oil sump are proposed. These improvements avoid the disruptive effects of circumferential fluid motion in the oil collection annulus on the pressure and velocity distribution within the bearing chamber, thereby improving scavenging performance. Full article

To facilitate the development of next-generation gas turbine cooling systems, the present study systematically investigates the influence of inlet temperature differentials on the aerothermal characteristics and mass flow distribution within multi-inlet, multi-outlet corotating-disc cavities, for which inlet temperature differentials of 10 K, 30 K, and 50 K were applied. Steady-state Reynolds-averaged Navier–Stokes (RANS) simulations using the Shear Stress Transport (SST) k-ω model were performed across a range of flow conditions corresponding to Rossby numbers from 0.01 to 0.10, by varying the rotational and axial Reynolds numbers. This study finds that the inlet temperature differentials are a secondary driver of the aerothermal characteristics in the corotating cavity. Meanwhile, Rossby number dictates the main flow structure of radially stratified vortices and governs the thermal mixing between hot and cold streams. A higher Rossby number enhances mixing, causing the radial outlet temperature to rise significantly, while the axial outlet remains cool. A larger inlet temperature differential can induce secondary vortices at high Rossby numbers. Furthermore, the differential is revealed to increase cavity pressure, slightly reducing the radial outlet’s mass flow by up to 2.5% and its discharge coefficient by nearly 5% at high Rossby numbers. These insights allow engine designers to develop more precise and optimized cooling strategies. Full article

Seagoing marine propulsion analysis in terms of main engine performance and fixed-pitch propeller hydrodynamics is an engineering problem that has not been exactly defined to date. This study utilizes an original and comprehensive mathematical approach—involving the approximate representation of one function by another—to define this problem in mathematical terms and solve it. This is achieved by imperatively applying an original and sophisticated hybrid combination of an existing, formidable and ingenious, mathematical methodology with different original comprehensive functional systems. These original functional systems approximately represent the operations of vessels under seagoing conditions, including the thermo-fluid and frictional processes of vessels’ main engines in terms of fuel oil consumption, as well as the hydrodynamic performance of the respective vessels in terms of the shaft propulsion power and the rotational speed of the fixed-pitch propellers driven by these engines. Based on the least-squares criterion, this original and sophisticated hybrid combination systematically attains remarkably close approximate representations under seagoing conditions. Apart from this novel exact definition in mathematical terms and the significance of the above original representations, this combination is also applicable for the approximation of the baselines demarcating the standard engineering context representing the ideal reference (sea trials) conditions, from the seagoing conditions. Full article

The compressive strength (Fc) of cement mortar (CM) is a key parameter in ensuring the mechanical reliability and durability of cement-based materials. Traditional testing methods are labor-intensive, time-consuming, and often lack predictive flexibility. With the increasing adoption of machine learning (ML) in civil engineering, data-driven approaches offer a rapid, cost-effective alternative for forecasting material properties. This study investigates a wide range of supervised linear and nonlinear ML regression models to predict the Fc of CM. The evaluated models include linear regression, ridge regression, lasso regression, decision trees, random forests, gradient boosting, k-nearest neighbors (KNN), and twelve neural network (NN) architectures, developed by combining different optimizers (L-BFGS, Adam, and SGD) with activation functions (tanh, relu, logistic, and identity). Model performance was assessed using the root mean squared error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). Among all models, NN_tanh_lbfgs achieved the best results, with an almost perfect fit in training (R² = 0.9999, RMSE = 0.0083, MAE = 0.0063) and excellent generalization in testing (R² = 0.9946, RMSE = 1.5032, MAE = 1.2545). NN_logistic_lbfgs, gradient boosting, and NN_relu_lbfgs also exhibited high predictive accuracy and robustness. The SHAP analysis revealed that curing age and nano silica/cement ratio (NS/C) positively influence Fc, while porosity has the strongest negative impact. The main novelty of this study lies in the systematic tuning of neural networks via distinct optimizer–activation combinations, and the integration of SHAP for interpretability—bridging the gap between predictive performance and explainability in cementitious materials research. These results confirm the NN_tanh_lbfgs as a highly reliable model for estimating Fc in CM, offering a robust, interpretable, and scalable solution for data-driven strength prediction. Full article

The effect of surface roughness in laminar flow has been the focus of recent research related to drag reduction. However, although particle transport is governed by laminar flow in most applications, the effect of surface texture on the drag of a sphere has mostly been addressed in the transitional and turbulent regimes. The aim of the present study is to explore the drag behavior of rough spherical micro-particles in laminar flow. The spheres’ roughness has been structured based on a 3D complex Weaire–Phelan model, as well as on a simpler orthogonal lattice one, and quantified as per various definitions. The emerging surface roughness comprises irregular elements in terms of shape and size. The investigation has been performed at Reynolds numbers ranging from 2 to 8. The drag coefficient is found to drop quadratically with increasing roughness. Relative roughness can reduce the total drag on the particle by over 21%. The key physical mechanism is explained by the particles’ surface cavities, which contain recirculating, nearly stagnant fluid, thus creating a self-lubricating effect that reduces skin friction, as the main flow skims over the top without entering the cavities. A reduction in total drag arises when skin friction drag reduction is larger than the increase in form drag. Understanding the drag behavior of spherical particles with irregular surface texture provides new and useful insight into low Reynolds number transport phenomena related to a variety of engineering applications. Full article

This article focuses on the study of elastic beams with fractional-order inertial damping structures at both ends, with the aim of exploring their dynamic characteristics, damping effects, and parameter selection rules in depth, providing theoretical and practical support for engineering applications. Firstly, using the generalized Hamilton principle, two dynamic models of an elastic beam are established for two different boundary conditions. Next, using the complex modal analysis method, a design method for the critical damping of the first and second modes of an elastic beam was proposed for the first time, and the accuracy of the critical damping calculation formula was verified. Simulation analysis shows that the higher the derivative order and inertance, the lower the main resonance frequency, and the greater the critical damping. Then, using the main resonance amplitude and frequency attenuation rate (R_A and R_Ω) as indicators, an analysis was conducted on the impact of damper parameters on vibration suppression effects. The results indicate that the introduction of fractional-order inerter can reduce the main resonance amplitude and frequency, and critical damping plays a significant role in the vibration suppression process. Based on the optimal average R_A range (95–98%) and higher cost-effectiveness, selecting a damping value of 0.05~0.6 times the critical damping ensures better overall vibration suppression performance, providing an important reference for the vibration suppression design of elastic beams in practical engineering. Full article

The gas reservoir of the Sinian Dengying Formation (Member 4) in Sichuan Basin exhibits extensive development of inter-clast dissolution pores and vugs within its carbonate reservoirs, characterized by low porosity (average 3.21%) and low permeability (average 2.19 mD). With the progressive development of the Moxi (MX)structure, the existing stimulation techniques require further optimization based on the specific geological characteristics of these reservoirs. Through large-scale true tri-axial physical simulation experiments, this study systematically evaluated the performance of three principal acid systems in reservoir stimulation: (1) Self-generating acid systems, which enhance etching through the thermal decomposition of ester precursors to provide sustained reactive capabilities. (2) Gelled acid systems, characterized by high viscosity and effectiveness in reducing breakdown pressure (18~35% lower than conventional systems), are ideal for generating complex fracture networks. (3) Diverting acid systems, designed to improve fracture branching density by managing fluid flow heterogeneity. This study emphasizes hybrid acid combinations, particularly self-generating acid prepad coupled with gelled acid systems, to leverage their synergistic advantages. Field trials implementing these optimized systems revealed that conventional guar-based fracturing fluids demonstrated 40% higher breakdown pressures compared to acid systems, rendering hydraulic fracturing unsuitable for MX reservoirs. Comparative analysis confirmed gelled acid’s superiority over diverting acid in tensile strength reduction and fracture network complexity. Field implementations using reservoir-quality-adaptive strategies—gelled acid fracturing for main reservoir sections and integrated self-generating acid prepad + gelled acid systems for marginal zones—demonstrated the technical superiority of the hybrid system under MX reservoir conditions. This optimized protocol enhanced fracture length by 28% and stimulated reservoir volume by 36%, achieving a 36% single-well production increase. The technical framework provides an engineered solution for productivity enhancement in deep carbonate gas reservoirs within the G-M structural domain, with particular efficacy for reservoirs featuring dual low-porosity and low-permeability characteristics. Full article

The destabilizing damage of rock structures in coal beds engineering is greatly influenced by the bearing rupture features and energy evolution laws of rock–coal assemblages with varying height ratios. In this study, we used PFC3D to create rock–coal assemblages with rock–coal height ratios of 2:8, 4:6, 6:4, and 8:2. Uniaxial compression simulation was then performed, revealing the expansion properties and damage crack dispersion pattern at various bearing phases. The dispersion and migration law of cemented strain energy zoning; the size and location of the destructive energy level and its spatiotemporal evolution characteristics; and the impact of height ratio on the load-bearing characteristics, crack extension, and evolution of multiple energies (strain, destructive, and kinetic energies) were all clarified with the aid of a self-developed destructive energy and strain energy capture and tracking Fish program. The findings indicate that the assemblage’s elasticity modulus and compressive strength slightly increase as the height ratio increases, that the assemblage’s cracks begin in the coal body, and that the number of crack bands inside the coal body increases as the height ratio increases. Also, the phenomenon of crack bands penetrating the rock through the interface between the coal and rock becomes increasingly apparent. The total number of cracks, including both tensile and shear cracks, decreases as the height ratio increases. Among these, tensile cracks are consistently more abundant than shear cracks, and the proportion between the two types remains relatively stable regardless of changes in the height ratio. The acoustic emission ringing counts of the assemblage were not synchronized with the development of bearing stress, and the ringing counts started to increase from the yield stage and reached a peak at the damage stage (0.8${\sigma }_{\mathrm{c}}$) after the peak of bearing stress. The larger the rock–coal height ratio, the smaller the peak and the earlier the timing of its appearance. The main body of strain energy accumulation was transferred from the coal body to the rock body when the height ratio exceeded 1.5. The peak values of the assemblage’s strain energy, destructive energy, and kinetic energy curves decreased as the height ratio increased, particularly the energy amplitude of the largest destructive energy event. In order to prevent and mitigate engineering disasters during deep mining of coal resources, the research findings could serve as a helpful reference for the destabilizing properties of rock–coal assemblages. Full article

The aim of this study is to explore the role of virtual reality in engineering education. Specifically, it analyzed 342 studies that were published during 2010–2025 following a systematic approach. It examined how virtual reality is used in engineering education, explored the document main characteristics, and identified emerging topics. The study also revealed existing limitations and suggested future research directions. According to the outcomes, the following six topics emerged: (i) Immersive technologies in engineering education, (ii) Virtual laboratories, (iii) Immersive and realistic simulations, (iv) Hands-on activities and practical skills development, (v) Engineering drawing, design, and visualization, and (vi) Social and collaborative learning. Virtual reality was proven to be an effective educational tool which supports engineering education and complements existing learning practices. Using virtual reality, students can apply their theoretical knowledge and practice their skills within low-risk, safe, and secure learning environments characterized by high immersion and interactivity. Virtual reality through the creation of virtual laboratories can also effectively support social, collaborative, and experiential learning and improve students’ academic performance, engagement, interaction, and motivation. Learning using virtual reality can also enhance students’ knowledge acquisition, retention, and understanding. Improvements on students’ design, planning, and implementation skills and decision making, problem-solving skills, and visual analytic skills were also observed. Finally, when compared to physical laboratories, virtual reality learning environments offered lower costs, reduced infrastructure requirements, less maintenance, and greater flexibility and scalability. Full article

Solid-state lithium batteries (SSLBs) have emerged as a promising alternative to conventional lithium-ion systems due to their superior safety profile, higher energy density, and potential compatibility with lithium metal anodes. However, a major challenge hindering their widespread deployment is the formation and growth of lithium dendrites, which compromise both performance and safety. This review provides a comprehensive and structured overview of recent advances in dendrite suppression strategies, with special emphasis on the role played by the nature of the solid electrolyte. In particular, we examine suppression mechanisms and material innovations within the three main classes of solid electrolytes: sulfide-based, oxide-based, and polymer-based systems. Each electrolyte class presents distinct advantages and challenges in relation to dendrite behavior. Sulfide electrolytes, known for their high ionic conductivity and good interfacial wettability, suffer from poor mechanical strength and chemical instability. Oxide electrolytes exhibit excellent electrochemical stability and mechanical rigidity but often face high interfacial resistance. Polymer electrolytes, while mechanically flexible and easy to process, generally have lower ionic conductivity and limited thermal stability. This review discusses how these intrinsic properties influence dendrite nucleation and propagation, including the role of interfacial stress, grain boundaries, void formation, and electrochemical heterogeneity. To mitigate dendrite formation, we explore a variety of strategies including interfacial engineering (e.g., the use of artificial interlayers, surface coatings, and chemical additives), mechanical reinforcement (e.g., incorporation of nanostructured or gradient architectures, pressure modulation, and self-healing materials), and modifications of the solid electrolyte and electrode structure. Additionally, we highlight the critical role of advanced characterization techniques—such as in situ electron microscopy, synchrotron-based X-ray diffraction, vibrational spectroscopy, and nuclear magnetic resonance (NMR)—for elucidating dendrite formation mechanisms and evaluating the effectiveness of suppression strategies in real time. By integrating recent experimental and theoretical insights across multiple disciplines, this review identifies key limitations in current approaches and outlines emerging research directions. These include the design of multifunctional interphases, hybrid electrolytes, and real-time diagnostic tools aimed at enabling the development of reliable, scalable, and dendrite-free SSLBs suitable for practical applications in next-generation energy storage. Full article

Fin analysis is crucial to improve the rate of heat transfer. The main objective of this research is to investigate various fin designs in order to enhance the heat transfer efficiency of cooling fins through modifications in the geometry of the cylinder fins. The investigation of thermal analysis of the cylinder through variation in material, geometry, number, and size of the fins is carried out. Different materials are considered to design the fins, including cast iron, aluminum alloy 6061, and copper. The design of the engine, featuring various fins, is modeled with CATIA, and analysis is performed with ANSYS 2023 R2. The findings indicate that for the modified design-2, the total heat flux is more for aluminum alloy 6061 compared to the other two materials. Additionally, the use of aluminum alloy 6061 results in lower weight, making it a better choice compared to cast iron and copper. Full article