Search Results (1,830)

Bearings are essential components in mechanical systems, with ceramic ball bearings increasingly adopted in turbine, automotive, and aerospace applications due to their superior strength and durability. Despite these advantages, bearings are subjected to significant cyclic loading, which can accelerate plastic deformation and lead to sudden catastrophic failure. Current approaches for predicting bearing lifespan rely on time-consuming theoretical and experimental methods. This study proposes a more efficient finite element (FE) approach to predict fatigue behaviour in silicon nitride ball bearings operating under lubricated conditions. In this research, a 12.7 mm diameter silicon nitride ball bearing was analysed under a Hertzian contact pressure of 3 GPa using SolidWorks Simulation 2023(SWS). Friction coefficients ranging from 0.00 to 1.00 were investigated to represent different lubrication conditions. The results indicate that the stress amplitude remained below the fatigue limit of 1.02 GPa for friction coefficients up to 0.80, while fatigue failure was predicted at a coefficient of 1.00, corresponding to 1.086 × 10⁴ cycles. Full article

This paper presents a systematic parametric study of how incremental titanium additions (0.1, 0.2, and 0.3 wt.%) alter the thermal conductivity, grain morphology, hardness, and tensile behaviour of Al6061 alloy intended for electronic heat sink service. Unlike prior investigations focused primarily on the Al6063–Ti system or on ceramic-phase reinforced aluminium composites, the present work isolates the grain-refinement and intermetallic-formation pathways in the 6xxx series with lower alloying additions (≤0.3 wt.%), manufactures specimens via stir casting followed by controlled homogenisation and T6-equivalent ageing, and evaluates performance against a thermal resistance index (TRI) to enable direct cross-study comparison. Thermal conductivity measurements were conducted according to ASTM E1225 across a 27–500 °C window. The results confirm a monotonic rise in conductivity from a baseline of 181 W/mK (undoped alloy) to 221.42 W/mK at 0.2 wt.% Ti—a 22.3% improvement—driven by quantifiable grain refinement (grain size reduced from 85 μm to 48 μm) and the associated redistribution of Mg and Si solute atoms. Brinell hardness increased from 98 to 120 BHN and ultimate tensile strength climbed from 250 MPa to 285 MPa across the same composition range, confirming thermal–mechanical co-enhancement. The study defines a composition window of 0.2–0.3 wt.% Ti as optimal for heat sink grade Al6061 and provides quantitative benchmarks against published Ti-doped aluminium alloy. Full article

In recent years, unmanned aerial vehicles (UAVs) and Big Data analytics have both emerged as increasingly important approaches in advanced traffic monitoring. UAVs provide high-resolution spatial data and operational flexibility, supporting automated vehicle detection and the construction of origin–destination (O/D) matrices through video processing. Conversely, Big Data offers a passive and non-invasive approach based on heterogeneous sources such as mobile devices, satellite navigation systems, and digital applications, ensuring continuous temporal coverage for mobility pattern analysis. This study evaluates the combined use of UAVs and Big Data for traffic flow monitoring as an alternative to traditional manual methods. Focusing on two case studies in Trapani (Italy), the research assesses the advantages and limitations of each technology and their complementary use. Results show that Big Data effectively captures large-scale temporal dynamics but lacks accuracy for detailed O/D estimation, while UAVs provide precise spatial and behavioural information despite operational constraints. A key objective of this study is to investigate the potential complementarity between UAV observations and Big Data traffic monitoring technologies, highlighting the main strengths and limitations of each method under complex study sites and challenging operational conditions for traffic data acquisition using UAVs. Full article

The increasing demand for sustainable materials has intensified efforts to enhance the performance of recycled polymers for engineering applications. This study investigates the effect of nanoclay reinforcement on the mechanical properties of recycled high-density polyethylene (rHDPE). Nanoclay was incorporated into rHDPE at varying loadings through melt blending, and the resulting composites were evaluated in terms of tensile, flexural, impact, and hardness properties. The tensile strength and tensile modulus improved significantly with increasing nanoclay content, reaching maximum values of 31.27 MPa and 2.39 GPa, respectively, at 1.5 wt% nanoclay, corresponding to increases of 23.11% and 47.53% relative to unreinforced rHDPE. Similarly, the flexural strength and flexural modulus attained peak values of 25.88 MPa and 1105.08 MPa at 1.5 wt% nanoclay, representing improvements of 12.57% and 15.49%, respectively. Impact strength exhibited a different trend, achieving a maximum value of 73.58 kJ/m² at 0.5 wt% nanoclay before decreasing at higher loadings, indicating a transition towards more brittle behaviour. Hardness increased progressively with nanoclay addition and reached a maximum value of 68.06 Shore D at 1.5 wt%, exceeding both unreinforced rHDPE and virgin HDPE. The overall results demonstrate that nanoclay effectively compensates for the mechanical degradation associated with recycling by enhancing stiffness, strength, and surface hardness. Among the investigated formulations, 1.5 wt% nanoclay provided the optimum balance of mechanical performance, while higher loadings led to reduced reinforcement efficiency due to particle agglomeration. These findings highlight the potential of nanoclay-reinforced rHDPE as a sustainable, high-performance material for applications in packaging, construction, and automotive components, thereby supporting circular economy initiatives and resource-efficient material development. Full article

Background: Maternal postpartum hospital readmissions represent profound implications for maternal health outcomes and potential gaps in quality of maternal care. Objective: This study aims to synthesise evidence on risk factors for maternal postpartum hospital readmissions within 42 days of discharge following birth hospitalisation. Methods: An electronic database search utilised CINAHL, EMBASE (Ovid), and MEDLINE for relevant studies published from 1 January 2010 to 30 June 2024. The studies that investigated the prevalence and risk factors for 42-day postpartum maternal readmission and reported risk estimates, published in English, were included. The risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) for case-control studies and cohort studies. The PRISMA guidelines were followed in reporting this review. The review protocol was registered on PROSPERO (CRD42023442269). Results: A total of 7758 articles were retrieved, ultimately including 60 studies. The rate of maternal postpartum readmissions varied from 0.1236‰ to 26%. Significant risk factors were extracted and categorised into five groups: maternal demographic and socio-economic factors; behavioural and lifestyle factors; health institution structural factors; obstetric and delivery characteristics; as well as maternal morbidity The most frequently cited risk factors which contributed to maternal postpartum hospital readmissions were age, race/ethnicity, substance use, caesarean delivery, length of maternal hospital stay, premature birth, and all maternal morbidities, especially mental health disorders, severe maternal morbidity, and hypertensive disorders of pregnancy. Conclusions: This systematic review identified complex and diverse risk factors associated with maternal postpartum hospital readmissions within 42 days after discharge following birth hospitalisation. This helps our understanding of the risk factors and the strength of association with maternal postpartum hospital readmissions. Future research should develop a multidimensional risk assessment framework to guide clinical practice in adopting holistic individualised approaches for postpartum risk evaluation, thereby reducing readmission rates and improving maternal health outcomes. Full article

Kauri dieback, caused by Phytophthora agathidicida Weir, Beever, Pennycook & Bellgard, poses a major threat to the ecological and cultural significance of Aotearoa New Zealand’s kauri forests. Visitor behaviour, particularly boot-cleaning and adherence to track-use guidelines, is a key transmission pathway. Using the COM-B framework and audience segmentation, we surveyed 451 visitors to the Waitākere and Hunua Ranges to identify behavioural drivers, barriers, and segment-specific intervention needs. Stepwise regressions accounted for 52% of the variance in self-reported boot-cleaning compliance and 56% in track-use compliance within this sample (adjusted R²). Boot-cleaning compliance was enhanced by habit strength, worry about spreading the pathogen, awareness of correct procedures, and reliance on functional cleaning stations, while inconvenience and chemical aversion reduced compliance. Track-use compliance was lowered by perceived low likelihood of spread, doubts about mitigation effectiveness, time-cost concerns, and strong forest-use identity, whereas protection motivation and habitual rule-following increased compliance. Latent profile analyses produced three segments per behaviour: boot-cleaning—Conflicted, Receptive, Engaged; and track-use—Identity-Driven Forest Users, Uncommitted, Engaged—which differed systematically in knowledge, concern, and compliance. We outline potential intervention implications informed by these findings and prior literature. Full article

Plant-based food systems increasingly rely on heat-induced gelation of protein–starch mixtures, yet no focused synthesis has linked legume protein composition to mixed gel structure and function. This review critically analyses heat-induced gelation mechanisms in legume protein–starch systems, using the legumin-to-vicilin (L:V) ratio and starch origin as integrating design parameters. Legume storage proteins range from legumin-rich faba bean and Lupinus angustifolius, which form dense, disulfide-stabilised networks with high storage moduli, to vicilin-dominated mung bean, which produces weaker gels reliant on starch reinforcement. Pulse starches, characterised by high amylose content (24–45%), C-type crystallinity, and rapid amylose retrogradation upon cooling, act as a parallel gel-forming phase whose contribution scales inversely with protein network strength. Four protein–starch interaction modes, namely segregative phase separation, water competition, granule filler effects, and molecular complexation, jointly determine microstructure and rheological behaviour. A three-axis compositional framework defined by the L:V ratio, starch amylose content, and protein-to-starch ratio maps the gel design space. Variables favouring plant-based meat analogue performance, including high elastic modulus, yield stress, and hardness, are systematically opposed by dysphagia food requirements, including low yield stress, adequate lubrication, and soft fracture. This demonstrates that both application domains traverse the same compositional space in opposite directions. Critical research gaps include chickpea and lentil performance in meat analogue systems, mechanistic modelling of protein-matrix-mediated starch digestibility, and retrogradation kinetics during food storage. Full article

Among a broad range of promising applications, the use of cellular solids as lightweight structural components is an important field of research that requires reliable predictions of their stiffness and strength. Predictive and general models should not depend on extensive parameter-fitting experiments and should not rely on computationally intensive numerical calculations for each new set of geometric parameters and loading conditions. An overview of models for 2D, 2.5D, and three-dimensional structures will be presented. Most 2D and 2.5D models neglect out-of-plane behaviour and the face sheets used in sandwich panels. 3D studies, mainly by finite element models (FEMs), are often limited to a narrow set of geometries and simple loading conditions. Elastic anisotropy is well covered, but calculating yield surfaces remains a challenge. Simplified models based on structural mechanics are rare and often limited in scope. They offer a flexible, computationally efficient approach for simulating truss-based materials. For more advanced designs, parameter-based FEMs must be developed for any loading condition to facilitate the generalised incorporation of 3D cellular solids in mechanical design. Artificial intelligence and machine learning are promising approaches for making optimal use of experimental and FEM results across multidimensional parameter spaces. Full article

Magnetostrictive patch transducers (MPTs) are highly efficient for generating and detecting ultrasonic waves for non-destructive evaluation (NDE), though their use on cementitious media and fibre-reinforced concrete has not yet been investigated. In this study, a COMSOL simulation, validated with laser-Doppler vibrometry, was first used to quantify patch deformation for use in subsequent simulation of wave propagation in samples. The MPT system was then validated on thin glass plates, producing tunable A₀, S₀, and SH₀ modes through frequency-wavelength matching. In cementitious mortar plates, SH₀ and SH₁ modes were demonstrated experimentally for the first time using MPTs. The validated COMSOL model was then used to interpret complex signals in quasi-plate and half-space cementitious mortar prisms, showing that MPTs generate Rayleigh, bulk SH, and surface-skimming SH modes. In steel fibre-reinforced concrete, surface-skimming SH wave speed correlated with increases in breaking strength even in the presence of surface features such as notches. Notably, Rayleigh wave speeds could not be measured in the presence of surface features, and the Rayleigh velocities measured in the same sample, but not in the local tested area did not correlate with SH speed. This behaviour is likely due to the non-uniform distribution of material constituents, including fibre-reinforcement and coarse aggregate, combined with the different propagation paths and depth sensitivities of the reported wave modes. Overall, racetrack-coil MPTs enable multimodal inspection of cementitious media, providing information on the presence of geometric features and material properties. Full article

Multi-criteria group decision making (MCGDM) under linguistic uncertainty remains a fundamental challenge in applied mathematics, where decision makers seldom assign crisp numerical evaluations and frequently exhibit heterogeneous risk attitudes shaped by behavioural factors. An integrated mathematical framework, hereafter PLR-3WBC (Probabilistic Linguistic Regret-driven Three-Way Bayesian Consensus), is developed to systematically integrate four methodological components that have each been individually validated in the MCGDM literature: representation of decision information with explicit probability mass on linguistic terms; quantification of decision-maker regret and rejoice psychology under linguistic uncertainty; classification of alternatives into three actionable decision regions rather than a single-valued ranking; and group consensus reaching with credal weight aggregation. Each component has demonstrated its effectiveness in its respective domain; the present framework capitalises on their complementary strengths by embedding them within a single pipeline equipped with formal guarantees, an integration that has not been previously reported. The framework integrates five methodological components: probabilistic linguistic term sets (PLTS) for information representation; the Bayesian best–worst method (BBWM) for credal criterion weighting; a regret–rejoice value function adapted to the linguistic domain for behavioural evaluation; three-way decision (3WD) thresholds derived from a loss-function model for actionable classification; and a distance-based consensus reaching process with feedback mechanism for group convergence. A case study on age-friendliness evaluation of twelve aging urban residential communities under an indicator system of five dimensions and eighteen criteria, with four expert decision makers, demonstrates that PLR-3WBC delivers an actionable three-way classification, recovers a transparent group consensus, and produces rankings broadly consistent with classical TOPSIS, VIKOR, PROMETHEE-II, and BWM-TOPSIS (Spearman rank correlation exceeding 0.97), thereby confirming that the integrated framework preserves the ordinal reliability of these established methods, while additionally delivering three outputs that arise from the methodological integration: an actionable three-way classification enabling discrete budget-aligned decisions, credal weight intervals quantifying the depth of expert agreement on criterion importance, and a behavioural reordering of borderline non-dominated alternatives that reflects the loss-averse psychology of the decision panel and would remain hidden under single-method deployment. Sensitivity analyses with respect to the regret aversion coefficient, the loss function parameters, and the consensus threshold confirm that the qualitative classification is stable across a wide parameter envelope, supporting the practical deployment of PLR-3WBC in age-friendly community renewal programmes. Full article

This paper provides a comprehensive review of recent studies on event-triggered control schemes for DC microgrids. Several event-triggered mechanisms (ETMs) are thoroughly discussed, including static, dynamic, self-triggered, and edge-based algorithms. Considering the strengths and weaknesses of these algorithms, it is found that although such ETMs can decrease communication burden in the system, they are also susceptible to communication delays, Zeno behaviour, sensitivity to control parameter changes in triggering conditions, and inability to adapt to the fluctuating nature of renewable energy sources (RESs). Furthermore, this article examines implementation challenges, including data packet loss, quantisation effects, actuator faults, and a lack of cybersecurity measures, to provide readers with a clear vision of future trends in this field. Based on the main findings of the investigation, this review paper proposes possible areas for future research, highlighting the need for event-triggered control schemes that operate in discrete time, handle delays, and adapt to varying operating conditions. Other concepts, including adaptive control parameters for triggering conditions based on machine learning, the adoption of advanced cybersecurity measures, and data-aware transmission approaches that consider both communication frequency and total data volume, are also discussed. To conduct a comprehensive review of all the above-mentioned ETMs, several databases, including IEEE Xplore, Elsevier, and MDPI, were searched using the main keywords in this field, such as event-triggered, self-triggered, and edge-based ETMs, in conjunction with DC microgrids. This facilitated an in-depth analysis of such control schemes, including their strengths and weaknesses, providing readers with a strong basis for selecting a proper control scheme suited to their future research. Full article

This study investigates the influence of PLA flowability and talc content on the performance of compostable thermoplastic starch/poly(butylene succinate) (TPS/PBS)-based systems for rigid applications. Different PLA grades with varying melt flow index (PLA23, PLA8 and PLA70) and talc contents (0, 5 and 10 wt%) were incorporated. Twelve formulations were compounded by twin-screw extrusion and processed by injection moulding. FTIR confirmed the coexistence of TPS, PBS and PLA phases without evidence of chemical interactions. Morphological analysis showed that PLA flowability plays a key role in phase distribution, with higher-flow PLA promoting improved dispersion and interfacial adhesion, while talc addition (5 and 10 wt%) increased structural heterogeneity; at higher loadings, particularly, DSC analysis revealed that talc acted as a nucleating agent for the PBS phase, increasing crystallisation temperatures from approximately 73 °C to 81 °C depending on formulation. Mechanical results showed that Young’s modulus increased from approximately 1.4 GPa to 2.7 GPa with decreasing PLA flowability and increasing talc content. Formulations containing low-flow PLA reached tensile strengths close to 32 MPa, although elongation at break decreased to values near 2%. In contrast, high-flow PLA formulations exhibited a more balanced mechanical response, with elongation values up to approximately 8%, associated with improved phase dispersion. Hybrid PLA systems showed intermediate behaviour, reaching elongations up to 22% while maintaining modulus values around 1.8 GPa. Talc provided additional reinforcement but reduced deformation capacity. HDT values remained relatively constant, indicating limited improvement in thermomechanical resistance despite increased stiffness. These results demonstrate that the combined control of PLA molecular characteristics and talc content enables tuning of the mechanical and thermomechanical performance of TPS/PBS/PLA/talc systems for rigid packaging applications. Full article

Electrospinning (ES) can produce nonwoven fibrous mats with high surface area and interconnected porosity, making them attractive for biomedical and functional material applications. However, conventional ES often relies on volatile organic solvents, raising safety, environmental, and translational concerns. Fully aqueous (“green”) ES offers an appealing alternative, although many water-soluble polymers remain difficult to spin and may show limited stability under hydrated conditions. In this study, two fully aqueous binary systems, poly(vinylpyrrolidone)–sodium alginate (PVP–SA) and poly(vinylpyrrolidone)–riboflavin (PVP–RF), were investigated to decouple the roles of sodium alginate (SA) and riboflavin (RF) on solution behaviour, fibre formation, morphology, dry-state mechanical properties, and surface chemistry. Aqueous PVP solutions (20% w/v; molecular weight 1.3 MDa) were blended with SA (1–5 wt% relative to PVP) or RF (1–10 wt% relative to PVP). Electrical conductivity and rheological properties were evaluated prior to ES under controlled conditions, with simultaneous ultraviolet (UV) exposure at 344 nm during fibre collection. RF did not significantly alter conductivity (~0.74–0.75 µS·cm⁻¹), whereas SA increased conductivity up to 2.75 ± 0.03 µS·cm⁻¹ at 5 wt%. All formulations exhibited shear-thinning behaviour, while 10 wt% RF increased the zero-shear viscosity relative to neat PVP. Morphological analysis showed that low SA contents produced uniform fibres, whereas higher SA levels (4–5 wt%) led to bead defects and reduced fibre diameter (down to 85 ± 25 nm). Dry-state mechanical performance decreased with increasing SA content, while 10 wt% RF improved tensile strength and toughness, reaching an ultimate tensile strength of 5.21 ± 0.15 MPa and toughness of 40.51 ± 1.53 MJ·m⁻³. Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) indicated subtle UV-driven redistribution of surface chemical states, consistent with mild photo-oxidative microstructural modification rather than extensive covalent network formation. Because the UV irradiance was not directly measured and wet-state stability was not assessed, the UV-related findings are interpreted as preliminary chemical evidence rather than confirmation of stabilized fibre mats. Overall, this work establishes a solvent-free aqueous ES platform in which ionic and photoactive additives can be used to tailor fibre morphology, dry-state mechanical behaviour, and surface characteristics without toxic reagents. Full article

Stenting is a minimally invasive treatment used in managing peripheral artery disease (PAD). However, clinical challenges persist, including in-stent thrombosis and restenosis, primarily driven by axial foreshortening or elongation and suboptimal balance between radial stiffness and flexibility inherent to conventional stent designs. This study proposes an innovative arrow-shaped geometry exhibiting zero Poisson’s ratio (ZPR) behaviour for 3D-printed self-expanding Nitinol stents. The complete stent deployment process was modelled using finite element analysis (FEA), including radial crimping and subsequent expansion to enable systematic parametric investigation while accounting for µ-3D printing constraints. Response surface methodology (RSM) rigorously evaluated mechanical performance, defining peak stress, chronic outward force (COF), radial resistive force (RRF), and foreshortening (FS) as constraint and objective functions within the optimisation framework. The optimised ZPR stent achieved favourable performance: extremely low foreshortening (|FS| ≤ 0.12%), representing outstanding axial stability compared with previously reported self-expanding stents, and a well-balanced radial response with ~50% higher radial strength than positive Poisson’s ratio (PPR) structures, while 16.67% lower than negative Poisson’s ratio (NPR) counterparts. These results highlight the ZPR stent’s capability to minimise axial deformation while maintaining adequate radial support, highlighting substantial potential for precise, stable deployment in PAD applications. Full article

Conventional rock blasting produces large rock masses that do not fully meet engineering construction requirements. Therefore, mechanical crushing technology is necessary to reduce these masses into crushed stone of a specific particle size. Consequently, enhancing the comprehensive utilisation rate of excavated materials and exploring new application avenues has become critical. Initial crushing experiments were conducted on limestone of varying strengths. Based on the measured parameters, simulation experiments were performed to analyse the accuracy of crushing particles of different strengths. Cube specimens confirmed that the created crushing model accurately reflects the actual crushing behaviour of particles with different strengths. A Structure Sensor 3D scanner was used to scan representative shapes of rock particles. Software processing yielded the true three-dimensional apparent morphology of the rock material. Combined with physical crushing tests and simulation experiments, this confirmed that the developed crushing model accurately reflects the actual crushing behaviour of rock particles when their true morphology is considered. The research findings demonstrate that the digital crushing model can accurately depict the crushing process and particle size distribution of rock materials with different lithological characteristics and true morphology. Full article