Search Results (39)

This study presents a two-dimensional computational fluid dynamics analysis of a vertical-axis Savonius-type wind turbine under atmospheric conditions representative of an educational environment located in the Ecuadorian Andean region. Unlike previous studies conducted under sea-level meteorological conditions, this research is performed under high-altitude conditions (2723 m a.s.l.). The unsteady flow around the rotor was simulated using a two-dimensional approach based on the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations, discretized with the finite volume method and coupled with the k–ω Shear Stress Transport (SST) turbulence model. The rotor rotation was modeled using sliding mesh technique, employing a second-order implicit time scheme to ensure numerical stability and adequate temporal resolution. The numerical model was configured for a tip speed ratio of 0.8 and a wind speed of 3.9 m/s. The time step was defined based on a constant angular advancement of the rotor per time iteration, ensuring numerical stability and adequate temporal resolution. The aerodynamic torque was obtained by integrating the pressure and viscous forces acting on the blades, allowing the calculation of the mechanical power generated and the power coefficient. The results showed a periodic and stable torque behavior after the initial transient cycles, yielding an average torque of 0.7687 N·m and a mechanical power of 5.17 W, while the power coefficient reached a value of 0.2102. Analysis of the flow fields revealed the formation of a low-velocity wake downstream of the rotor, regions of high turbulent kinetic energy associated with periodic vortex shedding, and a significant pressure difference between the advancing and returning blades, confirming that turbine operation is dominated by drag forces. The numerical results were validated through comparison with previous studies, showing good agreement and demonstrating the reliability of the proposed Computational Fluid Dynamics (CFD) approach. This study highlights the potential of Savonius turbines for low-power applications in urban and educational environments, as well as the usefulness of CFD as a tool for evaluating and optimizing their aerodynamic performance. Full article

The rapid rise in cryptocurrencies has created an investment environment marked by unprecedented levels of information volume, fragmentation, and volatility. While prior research has examined drivers of trust and adoption in crypto markets, far less is known about the psychological consequences of information overload on investor decision-making. This study addresses this gap through nineteen semi-structured interviews with individual cryptocurrency investors, analyzed using an inductive, manually conducted thematic approach. Findings reveal four interconnected dynamics: decision fatigue and paralysis, heuristic reliance on influencers and peers, emotional strain characterized by anxiety and fear of missing out (FOMO), and diverse coping strategies ranging from selective filtering to withdrawal. These results demonstrate that crypto investing is not only a financial process but also a cognitively and emotionally taxing experience. By linking investor narratives to broader theories of decision fatigue, bounded rationality, and consumer vulnerability, the study contributes to interdisciplinary debates in marketing, behavioral finance, and consumer psychology. Practically, the findings highlight the need for clearer communication strategies, supportive platform design, and financial education initiatives that help investors manage cognitive strain and decision fatigue. In a market where credibility is fluid and decisions are often made under conditions of overload, understanding the psychological dimensions of investment behavior is essential. Full article

Background: Arterial stenosis produces nonlinear changes in vascular impedance that are challenging to investigate in real time using either benchtop flow phantoms or high-fidelity computational fluid dynamics (CFD) models. Objective: This study aimed to develop and evaluate a low-cost printed circuit board (PCB) analog capable of reproducing the hemodynamic effects of progressive arterial stenosis through an R–L–C mapping of vascular mechanics. Methods: A lumped-parameter (0D) electrical network was constructed in which voltage represented pressure, current represented flow, resistance modeled viscous losses, capacitance corresponded to vessel compliance, and inductance represented fluid inertance. A variable resistor simulated focal stenosis and was adjusted incrementally to represent progressive narrowing. Input U_in, output U_out, peak-to-peak V_pp, and mean V_avg voltages were recorded at a driving frequency of 50 Hz. Physiological correspondence was established using the canonical relationships. $R={\displaystyle \frac{8\mu l}{\pi r^4}}$, $L={\displaystyle \frac{pl}{\pi r^2}}$, $C={\displaystyle \frac{3\pi r^3}{2Eh}}$, where μ is blood viscosity, ρ is density, E is Young’s modulus, and h is wall thickness. A calibration constant was applied to convert measured voltage differences into pressure differences. Results: As simulated stenosis increased, the circuit exhibited a monotonic rise in U_out and V_pp, with a precise inflection beyond mid-range narrowing—consistent with the nonlinear growth in pressure loss predicted by fluid dynamic theory. Replicate measurements yielded stable, repeatable traces with no outliers under nominal test conditions. Qualitative trends matched those of surrogate 0D and CFD analyses, showing minimal changes for mild narrowing (≤25%) and a sharp increase in pressure loss for moderate to severe stenoses (≥50%). The PCB analog uses a simplified, lumped-parameter representation driven by a fixed-frequency sinusoidal excitation and therefore does not reproduce fully characterized physiological systolic–diastolic waveforms or heart–arterial coupling. In addition, the present configuration is intended for relatively straight peripheral arterial segments and is not designed to capture the complex geometry and branching of specialized vascular beds (e.g., intracranial circulation) or strongly curved elastic vessels (e.g., the thoracic aorta). Conclusions: The PCB analog successfully reproduces the characteristic hemodynamic signatures of arterial stenosis in real time and at low cost. The model provides a valuable tool for educational and research applications, offering rapid and intuitive visualization of vascular behavior. Current accuracy reflects assumptions of Newtonian, laminar, and lumped flow; future work will refine calibration, quantify uncertainty, and benchmark results against physiological measurements and full CFD simulations. Full article

In Shenzhen, a high-density city facing severe land scarcity, the proliferation of compact primary school campuses poses significant challenges to the outdoor wind environment, which is crucial for outdoor thermal comfort in a hot–humid climate. This study employs Computational Fluid Dynamics (CFD) to systematically evaluate wind comfort across a range of high-density primary school layouts. Typical design proposals are classified and analyzed based on three key planning aspects: education building forms, courtyard openness, and sports field configuration. Wind comfort area ratio and static wind zone area ratio are adopted as key performance indicators to evaluate outdoor wind performance. The findings demonstrate that decentralized teaching building forms, multi-courtyard layouts with openings oriented towards the prevailing summer wind, and juxtaposed sports field placement significantly enhance outdoor ventilation and comfort. Additionally, positioning the main entrance on the windward side and incorporating elevated voids or terraces to form coherent ventilation corridors are effective design strategies. This research provides theoretical guidance for designing high-density school campuses in hot–humid southern China. Full article

A digital twin (DT) is an automation strategy that integrates a physical plant with an adaptive, real-time simulation environment, with bidirectional communication between them. In process engineering, DTs promise real-time monitoring, prediction of future conditions, predictive maintenance, process optimization, and control. Dashboards for process monitoring are becoming increasingly relevant for tracking key metrics and supervising industrial units in real time. Supervisory Control and Data Acquisition (SCADA) systems are widely used for process automation, with ScadaBR, an open-source, freely licensed platform. This work presents the development of a computational tool that integrates the Aspen HYSYS/Python with the ScadaBR system for real-time monitoring and supervision of dynamic models. The virtual plant, which replicates the system’s physical behavior, was connected to the SCADA platform via the Modbus protocol, enabling bidirectional data exchange between the simulated model and the supervisory interface. The system supports operational analysis and control strategy validation. Two case studies were analyzed: (i) a simplified catalytic hydrocracking process, implemented in the Python environment, and (ii) a heat exchanger networks process, simulated using the HYSYS simulator. In the second case, the process was dynamically simulated, with real-time monitoring of a simple dynamic indicator that correlates the feed methane concentration with heat transfer fluids. The results demonstrate the feasibility and applicability of the proposed approach for educational purposes, operator training, and process engineering validation, fostering a more realistic and interactive simulation environment. Furthermore, the results show that the tool is promising for dynamic monitoring of environmental and energy indices, demonstrating that methane consumption relative to process feed can be evaluated and controlled over time. Full article

This study explores the fluidity of multilingual and intercultural identities among Australian university students participating in a study abroad (SA) program in China. It pilots a structured analytical framework to analyse visual metaphors created by the participants, examining how Chinese language learners depict their evolving identities, thereby uncovering their fluid nature. An analysis of three case studies of Australian students—one of Chinese heritage, one Australian-born of Serbian heritage, and one Japanese-born who moved to Australia in childhood—illustrates their unique trajectories of identity formation. Multimodal data reveals that while the visual metaphors of all three students point to fluidity, with sub-themes of dynamism, blending, and layeredness, the SA experience triggers diverse individual processes of identity negotiation and transformation. This study contributes to the fields of multilingual and intercultural education and SA through its innovative use of a visual metaphor analysis approach, which effectively captures and decodes the complexities of intercultural development among language learners in an SA environment. The study advocates visual metaphor as a valuable tool for both researching and understanding how multilinguals, especially those whose first and home language is not English, reflect on their multilingual and intercultural identity and experiences. Full article

Understanding how cognition develops as a result of collaboration is a continuing educational endeavour along with identifying effective strategies and understandings related to collaborative learning. With this endeavour in mind, this paper reports on findings from a research project that examined the mechanisms and processes utilised by teachers to enhance collaboration in a problem-based learning approach to school-based STEM education. The research involved purposive sampling of 35 teachers from 15 schools in two states within Australia. The study followed a longitudinal qualitative research design (2021–2024) and drew information from teacher round-table discussions that were then thematically analysed to reveal five key themes about collaboration as part of classroom learning: (1) collaboration requires active learning, (2) collaboration involves effective communication, (3) collaboration is purposeful and driven by shared goals, (4) collaboration is fluid and dynamic, and (5) collaboration values diversity. The findings of this research primarily contribute to the field through theoretical insights that propose a new framework for understanding the cognitive nature of effective collaboration, which when translated into an actionable assessment matrix can assist teachers as they work to implement effective learning through collaboration in the classroom. Full article

Vertical-Axis Wind Turbines (VAWTs) are efficient solutions for renewable energy generation, especially in regions with variable wind conditions. This study presents an optimized design of a small-scale H-type VAWT through the integration of Design of Experiments (DOE) and Computational Fluid Dynamics (CFD), using a fractional factorial 2^k−p approach to evaluate the influence of geometric and operational parameters on power output and power coefficient (Cp), which ranged from 0.15 to 0.35. The research began with a comprehensive assessment of renewable resources in Isla Fuerte, Colombia. Solar analysis revealed an average of 5.13 Peak Sun Hours (PSHs), supporting the existing 175 kWp photovoltaic system. Wind modeling, based on meteorological data and Weibull distribution, showed speeds between 2.79 m/s and 5.36 m/s, predominantly from northeast to northwest. Under these conditions, the NACA S1046 airfoil was selected for its aerodynamic suitability. The turbine achieved power outputs from 0.46 W to 37.59 W, with stabilization times analyzed to assess dynamic performance. This initiative promotes environmental sustainability by reducing reliance on Diesel Generators (DGs) and empowering local communities through participatory design and technical training. The DOE-CFD methodology offers a replicable model for energy transition in insular regions of developing countries, linking technical innovation with social development and education. Full article

This article presents a collection of schlieren visualizations captured using a custom-built, laboratory-based imaging system, designed to explore a wide range of flow and refractive phenomena. The experiments were conducted as a series of observational case studies, serving as educational bloc notes for students and researchers working in fluid mechanics, optics, and high-speed imaging. High-resolution images illustrate various phenomena including shockwave propagation from bursting balloons, vapor plume formation from volatile liquids, optical surface imperfections in transparent materials, and the dynamic collapse of soap bubbles. Each image is accompanied by brief experimental context and interpretation, highlighting the physical principles revealed through the schlieren technique. The resulting collection emphasizes the accessibility of flow visualization in a teaching laboratory, and its value in making invisible physical processes intuitively understandable. Full article

The real-time simulation of atmospheric clouds for the visualisation of outdoor scenarios has been a computer graphics research challenge since the emergence of the natural phenomena rendering field in the 1980s. In this work, we present an innovative method for real-time cumuli movement and transition based on a Recurrent Neural Network (RNN). Specifically, an LSTM, a GRU and an Elman RNN network are trained on time-series data generated by a parallel Navier–Stokes fluid solver. The training process optimizes the network to predict the velocity of cloud particles for the subsequent time step, allowing the model to act as a computationally efficient surrogate for the full physics simulation. In the experiments, we obtained natural-looking behaviour for cumuli evolution and dissipation with excellent performance by the RNN fluid algorithm compared with that of classical finite-element computational solvers. These experiments prove the suitability of our ontogenetic computational model in terms of achieving an optimum balance between natural-looking realism and performance in opposition to computationally expensive hyper-realistic fluid dynamics simulations which are usually in non-real time. Therefore, the core contributions of our research to the state of the art in cloud dynamics are the following: a progressively improved real-time step of the RNN-LSTM fluid algorithm compared to the previous literature to date by outperforming the inference times during the runtime cumuli animation in the analysed hardware, the absence of spatial grid bounds and the replacement of fluid dynamics equation solving with the RNN. As a consequence, this method is applicable in flight simulation systems, climate awareness educational tools, atmospheric simulations, nature-based video games and architectural software. Full article

Respirable crystalline silica is a well-established occupational hazard in construction work. Despite increased awareness, consistent exposure control remains a challenge, particularly in dynamic and resource-constrained environments. Respirable crystalline silica exposure in construction environments challenges the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being) and SDG 8 (Decent Work and Economic Growth). Respirable crystalline silica particles cause severe health complications, including silicosis, lung cancer, cardiovascular diseases, and autoimmune disorders, representing a significant barrier to achieving SDG 3.9’s target of reducing deaths and illnesses from hazardous chemical exposures by 2030. This systematic review evaluates two decades of advancements (2004–2024) in respirable crystalline silica identification, characterisation, and mitigation within construction, synthesising evidence from 143 studies to assess progress toward sustainable occupational health management. This review documents a paradigmatic shift from traditional exposure assessment toward sophisticated monitoring approaches incorporating real-time detection systems, virtual reality–Computational Fluid Dynamics simulations, and wearable sensor technologies. Engineering controls, including local exhaust ventilation, wet suppression methods, and modified tool designs, have achieved exposure reductions exceeding 90%, directly supporting SDG 8.8’s commitment to safe working environments for all workers, including migrants and those in precarious employment. However, substantial barriers persist, including prohibitive costs, inadequate infrastructure, and regional regulatory disparities that particularly disadvantage lower-resourced countries, contradicting the Sustainable Development Goals’ principles of leaving no one behind. The findings advocate holistic approaches integrating technological innovation with context-specific regulations, enhanced international cooperation, and culturally adapted worker education to achieve equitable occupational health protection supporting multiple Sustainable Development Goals’ objectives by 2030 and also highlighting potential areas for future research. Full article

Twin-screw compressors (TSCs) are widely used in various industries. Their performance is influenced by several parameters, such as rotor profiles, clearance gaps, operating speed, and thermal effects. Traditionally, optimizing these parameters relied on experimental methods, which are costly and time-consuming. However, advancements in computational tools, such as Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA), have revolutionized compressor analysis. This study presents a CFD analysis of a specific model of a TSC in a 5 male/6 female lobe configuration using the SolidWorks Flow Simulation environment—an approach not traditionally applied to such positive displacement machines. The results visually present internal flow trajectories, fluid velocities, pressure distributions, temperature gradients, and leakage behaviors with high spatial and temporal resolution. Additionally, torque fluctuations and isosurface visualizations revealed insights into mechanical loads and flow behavior. The proposed method allows for relatively easy adaptation to different TSC configurations and can also be a useful tool for engineering and educational purposes. Full article

Introduction: The purpose of this study is to provide foundational data for nursing care in patients with external ventricular drainage (EVD) by comparatively analyzing drainage volume in relation to intracranial pressure (ICP) and drainage catheter size. Methods: In this study, we conducted a volumetric analysis using the continuity and Bernoulli equations, considering friction forces under predefined conditions. In adults in the supine position with 37 °C CSF, the ventricular drainage volume was assessed based on the height of the EVD system, ICP levels, and EVD catheter sizes. Results: The results indicated that the CSF flow rate increased with larger catheter diameters and when the EVD system was positioned lower than the reference point (foramen of Monro). Across all catheter sizes, the minimum CSF flow occurred when the EVD system was 15 cm above the reference point, while the maximum flow was observed when it was 15 cm below the reference point. This multidisciplinary study, utilizing fluid dynamics, quantitatively estimates the drainage volume in EVD systems based on ICP and catheter size, contributing to the nursing care of EVD systems. The findings underscore the importance of developing specific nursing guidelines to improve patient safety in external ventricular drainage management and incorporating them into clinical education. Conclusions: A limitation of this study is that it does not compare with patients in clinical settings for clinical empirical validity. Therefore, a stepwise validation process is necessary. So, future studies will need to compare medical record data with the results of this study to confirm the validity of the equations presented. Full article

Intercultural sensitivity is crucial in today’s diverse society, and accurate assessment is key to developing effective intercultural programs in educational institutions and beyond. The Intercultural Development Inventory (IDI) is widely used for this purpose, yet its applicability to transnational individuals—those navigating multiple cultural and social systems—remains underexplored. This gap is important to address given the interconnected nature of our global society, where individuals frequently move across borders. To address this issue, this conceptual paper critically examines the underlying assumptions of the IDI regarding culture and identity through three interrelated frameworks: transnationalism, relational ontology, and intersectionality. Drawing on existing literature on these frameworks and the IDI, our analysis highlights how integrating these perspectives into the IDI and, by extension, other intercultural assessment tools can more accurately capture the complex, fluid, and dynamic nature of transnational experiences. This integration also shifts the discourse on intercultural assessment from a focus on individual competence to an emphasis on shared responsibility in fostering equitable, relationally grounded intercultural spaces. Implications for future research and practice are also discussed. Full article

Glioblastoma (GBM) is the most prevalent and aggressive primary central nervous system (CNS) tumor in adults. GBMs exhibit genetic and epigenetic heterogeneity, posing difficulties in surveillance and being associated with high rates of recurrence and mortality. Nevertheless, due to the high infiltrating ability of glioblastoma cells, and regardless of the considerable progress made in radiotherapeutic, chemotherapeutic, and surgical protocols, the treatment of GBM is still inefficient. Conventional diagnostic approaches, such as neuroimaging techniques and tissue biopsies, which are invasive maneuvers, present certain challenges and limitations in providing real-time information, and are incapable of differentiating pseudo-progression related to treatment from real tumor progression. Liquid biopsy, the analysis of biomarkers such as nucleic acids (DNA/RNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), or tumor-educated platelets (TEPs) that are present in body fluids, provides a minimally invasive and dynamic method of diagnosis and continuous monitoring for GBM. It represents a new preferred approach that enables a superior manner to obtain data on possible tumor risk, prognosis, and recurrence assessment. This article is a literature review that aims to provide updated information about GBM biomarkers in body fluids and to analyze their clinical efficiency. Full article