Search Results (81)

This work presents a high-fidelity two-way coupled Fluid-Structure Interaction (FSI) simulation framework for wind turbine blades, developed using the Arbitrary Hybrid Turbulence Modelling (AHTM) implemented through Very Large Eddy Simulation (VLES) in the DAFoam solver. By integrating VLES with the Toolkit for the Analysis of Composite Structures (TACS) structural solver via the OpenMDAO/MPhys framework, this work aims to accurately model the complex aeroelastic characteristics of wind turbines, specifically focusing on the NREL Phase VI wind turbine. The numerical model accounts for the effects of transient, turbulent, and unsteady aerodynamic loading, incorporating the impact of structural deflections. A comparison of the calculated results with experimental data demonstrates strong agreement in key performance metrics, including blade tip displacements, power output, and pressure distribution. This alignment confirms that the proposed model is effective at predicting wind turbine performance. One of the significant advantages of this study is the integration of advanced turbulence modeling with shell element structural analysis, enhancing the design and performance predictions of modern wind turbines. Although computationally intensive, this approach marks a significant advancement in accurately simulating the aeroelastic response of turbines, paving the way for optimized and more efficient wind energy systems. Full article

Isobaric vapor-liquid equilibrium (VLE) data for binary mixtures of biomass–derived ethyl levulinate and ethanol were measured using an apparatus comprising a modified Rose-Williams still and a condensation system. Measurements were taken at temperatures ranging from 329.58 K to 470.00 K and pressures of 40.0, 60.0 and 80.0 kPa. The thermodynamic consistency of the VLE data was evaluated using the Redlich-Kister area test, the Fredenslund test and the Van Ness point-to-point test. The data was correlated using three activity coefficient models: Wilson, NRTL and UNIQUAC. The Gibbs energy of mixing of the VLE data was analyzed to verify the suitability of the binary interaction parameters of these models. The activity coefficients and excess Gibbs free energy, calculated from the VLE experimental data and model correlation results, were analyzed to evaluate the models’ fit and the non–ideality of the binary system. The accuracy of the regression results was also assessed based on the root mean square deviation (RMSD) and average absolute deviation (AAD) for both temperature and the vapor phase mole fraction of ethyl levulinate. The results indicate that the NRTL model provided the best fit to the experimental data. Notably, the experimental data showed strong correlation with the predictions of all three models, suggesting their reliability for practical application. Full article

Vapor–liquid equilibrium (VLE) experimental data are reported for three binary systems: isobutanol + 1-butanol, isobutanol + 2-ethyl-1-hexanol, and 1-butanol + 2-ethyl-1-hexanol. Due to the limited and incomplete data available in the literature, we determined the p-T-x experimental VLE data for these binaries using an equilibrium apparatus, designed and built in our laboratory, which had been used extensively in various determinations. The temperature and pressure ranges for determining the VLE data are as follows: (305.15–388.15) K and (2.284–99.779) kPa for the isobutanol + 1-butanol system, (305.15–455.15) K and (2.284–99.779) kPa for the isobutanol + 2-ethyl-1-hexanol, and (320.15–455.15) K and (3.635–98.039) kPa for the 1-butanol + 2-ethyl-1-hexanol. The experimental VLE data for these binary systems were regressed using the nonrandom two-liquid (NRTL) model. The results indicate a reasonably good agreement between the model and the experimental data, with maximum deviations of 7% in the liquid-phase composition of the most volatile component from the binary and 4.5% in pressure. Full article

The purpose of this study was to analyse educators’ decisions on the continued use of the virtual learning environment (VLE) Blackboard and its associated e-learning technologies in the classroom within the public school system. This cross-sectional descriptive quantitative research collected 306 responses from educators in 30 public schools in Gauteng Province, South Africa. The results revealed that the empirical data’s mean performance expectancy (PEY) was lower than the ‘agree’ range of the hypothesised population, implying that the educators’ assumption is that the deployed technology does not improve their work performance. Furthermore, the results showed that learning tradition (LTD) has a complementary partial mediation effect on the relationship between PEY and continued use intention (CUI). Additionally, facilitating conditions (FCCs) also have a complementary partial mediation effect on the relationship between PEY and CUI. Conditional mediation (CoMe) from the path SOI x PEY -> LTD -> CUI was statistically significant. In probing the conditional indirect effect, the results showed that, if the social influence (SOI) increased, the mediation effect of LTD decreases. On the contrary, if it decreased, the mediation effect of LTD increased. This was also evident in the Johnson-Neyman plot. SOI did not moderate the mediation effect of FCC on the relationship between PEY and CUI. This study concludes that social and operational factors highly influence the dynamics of continued use of VLE and its associated e-learning technologies and cannot be discounted by practitioners and policy-makers in their quest to increase technology use in the school system. This study contributes to the unified technology acceptance and use theory model (UTAUT), advancing the idea that facilitating conditions and learning traditions can be mediators and social influence moderators within certain contexts and research settings. Full article

Virtual field trips in zoogeomorphology can allow students to explore the dynamic influence of beaver activity within the landscape. Education theory-informed virtual learning experiences (VLEs) of zoogeomorphologic topics, such as ecosystem engineers, are still underdeveloped for natural science learning communities. Through dam-building activities, beavers significantly alter stream hydrology, sediment transport, and vegetation organization and structure, promoting landscape heterogeneity. To effectively communicate this complexity of landscape modification, we developed an immersive virtual reality (VR) environment using historical photographs and detailed field notes to visualize the temporal and spatial transformations caused by beaver activity. A design and development process (TECCUPD), a philosophical framework for physical geography (TREE-PG), and a planning tool (VRUI conceptual model) are used to guide VLE architecture. Collectively, this information serves as a virtual proxy of an abandoned beaver pond field site to support student evaluation of the influence of sediment trapping and flooding on vegetation patterns on the landscape. This virtual place-based, experiential narrative environment is a proxy to capture the complexity of beaver-modified landscapes through ecological and geomorphological interactions. The integration of immersive VR technologies and generative artificial intelligence (AI) in higher education with learning theories that guide VR application design and development is applied in virtual field trips to support pedagogical goals and improve learning outcomes. Finally, we use an evaluation scale (TIPS) to assess the fidelity of learning theory implementation in a virtual field trip. Virtual field experiences in zoogeomorphology, informed by theory and utilizing immersive landscapes and scientific educational tools, can help students discern the effects of beavers on stream hydrology and geomorphic processes, as well as their potential role in mitigating water insecurity in climate adaptation efforts. Full article

The vapor–liquid equilibrium (VLE) data of the ternary system methanol–methyl formate–methylal was measured at atmospheric pressure using a modified Rose equilibrium kettle with vapor–liquid double circulation method. The experiment data were correlated with the NRTL, UNIQUAC, and Wilson activity coefficient model equations. The results shown that the root mean square deviation (RMSD) between the calculated and simulated values of the three models followed the order: UNIQUAC ≈ NRTL < Wilson, and except for the RMSD (T) in the range of 0.4–0.5, the others are less than 0.01. In addition, the NRTL model was selected to link with Aspen Plus software to simulate the separation process of polyformaldehyde (POM) waste liquid. The simulation results show that the methyl formate in POM waste stream can be purified by simple distillation, while the methylal separated from the POM waste liquid, which was affected by factors like the azeotropic behavior of binary components, necessitates a complex distillation process. Under optimal operating conditions, the recovery yield of methyl formate through direct distillation can reach 99.7%, with an economic benefit of 6960.1 CNY per ton of waste liquid. Although the economic benefit of the multi-component distillation reach 7281.2 CNY, the increase in the number of equipment and the complexity of the process have negative impacts. Full article

In this study, vapor–liquid equilibrium (VLE) experimental data were measured for two binary solvents based on 1,8-diazabicyclo(5.4.0)undec-7-ene (DBU), which can be used as a new CO₂-binding organic liquids (CO₂-BOLs) solvent. No experimental data are available in the literature and are fundamental to determine whether the considered mixtures are suitable to be possible alternatives to traditional amine solutions for CO₂ removal. The bubble point data of 1,2-propanediol+1,8-diazabicyclo(5.4.0)undec-7-ene (DBU) and 1,4-butanediol+DBU mixtures were measured at 30 kPa. The experimental determination was carried out in an all-glass dynamic recirculation still at the Process Thermodynamics laboratory (PT lab) of Politecnico di Milano. The thermodynamic modeling of the VLE behavior of two DBU-based mixtures was performed considering the NRTL, the UNIQUAC, and the Wilson models, and binary interaction parameters of the NRTL activity coefficients model were regressed on the basis of the measured experimental data. Full article

CO₂ removal, especially the one applied to reduce the emissions of CO₂ to the atmosphere (carbon capture, utilization, and storage), is one of the main research topics nowadays because of its great contribution to the reduction in climate change and to making many industrial processes sustainable. In this regard, alternative solvents to the traditional ones are under study with the aim of employing a more sustainable solvent for the environment, health, and society, in comparison with the traditional amine aqueous solutions that are toxic and corrosive. The CO₂-binding organic liquids (CO₂-BOLs) are a class of components of interest. In this work, the vapor–liquid equilibrium (VLE) data for two newly selected binary mixtures based on CO₂-BOLs, 1,3-Propanediol+DBU and DBU+Sulfolane, have been experimentally determined at the Process Thermodynamics laboratory (PT lab) of Politecnico di Milano to evaluate the suitability of these mixtures for being a solvent for CO₂ removal. All the experiments have been carried out by using the Fischer^® Labodest^® VLLE 602 unit at a constant pressure of 30 kPa. The densities of the mixtures for all the considered compositions have been determined at atmospheric pressure with a density meter (Mettler Toledo Densito Density2Go). No data on the VLE of these mixtures can be found in the literature. This is the first work focusing on mixtures of these components that could be employed as solvents for CO₂ removal as alternative solvents to the monoethanolamine (MEA) aqueous solution in the process of chemical absorption. The collected experimental data have then been used for the definition of the thermodynamic model by considering different possible theories (NRTL, Wilson, and UNIQUAC) that could be employed for the representation of the two systems. Full article

This paper presents the modeling of the existing crude oil separation process in a system consisting of two rectification columns with side drafts operating at higher pressure. The composition of the crude oil was approximated by a model mixture of hydrocarbons. The installation calculations have been performed for two different model compositions containing 32 and 10 different hydrocarbons. The whole technological process was based on the assumption that the feed stream, containing a model crude oil, was introduced to the first column, and then the other expected products (different petroleum fractions), characterized by their respective boiling points, were collected (side drafts) from the appropriate trays of the distillation columns. The obtained calculation results for both of the model crude oils were compared with the results obtained in the existing petroleum process and discussed from the point of view of their practical applications. The detailed data concerning size, composition, and process parameters for all the streams of the investigated installations, as well as the necessary energy expenditure for each of the columns, have been determined. Moreover, some recommendations are presented for the modeling and optimization of industrial distillation processes of very complex, multi-component systems using simpler model compositions. Full article

Integrating Virtual Reality (VR) with developing technology has become crucial in today’s schools to transform in-the-moment instruction. A change in perspective has occurred because of VR, enabling teachers to create immersive learning experiences in addition to conventional classes. This paper presents a systematic literature review with an in-depth analysis of the changing environment of immersive learning. It discusses advantages and challenges, noting results from previous researchers. VR facilitates more profound knowledge and memory of complex subjects by allowing students to collaborate with digital structures, explore virtual landscapes, and participate in simulated experiments. Developing VR gear, like thin headsets and tactile feedback mechanisms, has democratised immersive engineering learning by making it more approachable and natural for a broader range of students. This study sheds light on the revolutionary potential of immersive learning via VR integration with new technologies in real-time education by examining current trends, discussing obstacles, and an outlook on future directions using the new Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study used four databases: Scopus, IEEE, Springer, and Google Scholar. During the selection, 24 articles were added during the review, and 66 studies were selected. It clarifies best practices for adopting VR-enhanced learning environments through empirical analysis and case studies, and it also points out directions for future innovation and growth in the field of immersive pedagogy. Full article

In this study, we aim to develop advanced machine learning regression models for the prediction of hydrate temperature based on the chemical composition of sweet gas mixtures. Data were collected in accordance with the BOTAS Gas Network Code specifications, approved by the Turkish Energy Market Regulatory Authority (EMRA), and generated using DNV GasVLe v3.10 software, which predicts the phase behavior and properties of hydrocarbon-based mixtures under various pressure and temperature conditions. We employed linear regression, decision tree regression, random forest regression, generalized additive models, and artificial neural networks to create prediction models for hydrate formation temperature (HFT). The performance of these models was evaluated using the hold-out cross-validation technique to ensure unbiased results. This study demonstrates the efficacy of ensemble learning methods, particularly random forest with an R² and Adj. R² of 0.998, for predicting hydrate formation conditions, thereby enhancing the safety and efficiency of gas transport and processing. This research illustrates the potential of machine learning techniques in advancing the predictive accuracy for hydrate formations in natural gas pipelines and suggests avenues for future optimizations through hybrid modeling approaches. Full article

The growing demand for more sustainable routes and processes in the mixture separation and purification industry has generated a need to search for innovations, with new solvent alternatives being a possible solution. In this context, a new class of green solvents, known as deep eutectic solvents (DESs), has been gaining prominence in recent years in both academic and industrial spheres. These solvents, when compared to ionic liquids (ILs), are more environmentally friendly, less toxic, low-cost, and easier to synthesize. In addition, they have significantly lower melting points than their precursors, offering a promising option for various applications in this industrial sector. Understanding and studying the thermodynamic behavior of systems composed of these substances in purification and separation processes, such as liquid–liquid extraction and azeotropic distillation, is extremely important. This work aimed to study the phase behavior of liquid–liquid equilibrium (LLE) and vapor–liquid equilibrium (VLE) of water + 1-butanol + DES (choline chloride + glycerol) systems with a molar ratio of 1:2. Experimental LLE data, obtained at 298.15 K and 101.3 kPa, and VLE data, obtained at 101.3 kPa and in the temperature range of 364.05 K–373.85 K, were submitted to the thermodynamic quality/consistency test, proposed by Marcilla et al. and Wisniak, and subsequently modeled using the gamma–gamma approach for the LLE and gamma–phi for the VLE. The non-random two-liquid (NRTL) model was used to calculate the activity coefficient. The results are presented for the VLE in a temperature–composition phase diagram (triangular prism) and triangular phase diagrams showing the binodal curve and tie lines (LLE). The separation and distribution coefficients of LLE were determined to evaluate the extractive potential of the DES. For the VLE, the values of the relative volatility of the system were calculated, considering the entrainer free-basis, to evaluate the presence or absence of azeotropes in the range of collected points. From these data, it was possible to compare DES with ILs as extracting agents, using data from previous studies carried out by the research group. Therefore, the results indicate that the NRTL model is efficient at correlating the fluid behavior of both equilibria. Thus, this study serves as a basis for future studies related to the understanding and design of separation processes. Full article

This work demonstrates the potential of CO₂ + SiCl₄ binary mixture as a working fluid for power generation cycle. Recompression Brayton cycle configuration is considered due to its proven record of high performance for medium- to high-temperature sources. The objective of this study is to assess the thermodynamic performance of a recompression Brayton cycle using a CO₂ + SiCl₄ binary mixture as a working fluid, particularly under warm climate conditions. The cycle is simulated using the Peng–Robinson equation of state in Aspen Hysys (v11) software, and the model is validated by comparing VLE data against experimental data from the literature. The analysis involves the assessment of cycle’s thermal efficiency and exergy efficiency under warm climatic conditions, with a minimum cycle temperature of 40 °C. The results demonstrate a notable improvement in the cycle’s thermodynamic performance with CO₂ + SiCl₄ binary mixture compared to pure CO₂. A small concentration (5%) of SiCl₄ in CO₂ increases the thermal efficiency of the cycle from 41.7% to 43.4%. Moreover, irreversibility losses in the cooler and the heat recovery unit are significantly lower with the CO₂ + SiCl₄ binary mixture than with pure CO₂. This improvement enhances the overall exergy efficiency of the cycle, increasing it from 62.1% to 70.2%. The primary reason for this enhancement is the substantial reduction in irreversibility losses in both the cooler and the HTR. This study reveals that when using a CO₂ + SiCl₄ mixture, the concentration must be optimized to avoid condensation in the compressor, which can cause physical damage to the compressor blades and other components, as well as increase power input. This issue arises from the higher glide temperature of the mixture at increased SiCl₄ concentrations and the limited heat recovery from the cycle. Full article

Virtual learning environments (VLEs) in physical geography education offer significant potential to aid students in acquiring the essential skills for the environmental interpretation of glacial and periglacial environments for geoscience careers. Simulated real-world field experiences aim to help the student evaluate landscapes for natural hazards, assess their intensity, and translate and communicate this information to various stakeholders in human systems. The TREE-PG framework and VRUI model provide a philosophical and practical foundation for VLE architects, aiming to cultivate students’ knowledge, skills, and identity as geoscientists, specifically as physical geographers and geomorphologists. These frameworks emphasize the importance of translating scientific knowledge from physical features into engaging, accessible online lessons, exemplified by landscapes like those in Glacier National Park, Montana. Open-source software and open educational resources (OERs) can broaden access and incorporate diverse perspectives in these experiences, which are necessary to address the impacts of vulnerable communities to global deglaciation. Designing and creating virtual proxies of field-based education may help address issues associated with inclusion and belonging within geoscience disciplines to connect all students with dynamic physical environments beyond the classroom. Ethical AI approaches and discipline-specific repositories are needed to ensure high-quality, contextually accurate VLEs. AI’s tendency to produce output necessitates using domain-specific guardrails to maintain relevance and precision in virtual educational content. Full article

Immersive virtual learning environments (iVLEs), particularly serious games and virtual simulations, typically ignore psychomotor skills development, partly due to the difficulty and cost associated with accurately replicating touch. Simulating touch, also known as haptics, requires specialized haptic devices that are not widely accessible at the consumer-level. Using visual (and/or auditory) cues, pseudo-haptics aims to mimic touch sensations without haptic devices. Although pseudo-haptics has predominantly focused on visual cues, a 2019 review by Collins and Kapralos on pseudo-haptics emphasized the role of auditory cues and cross-modal interactions. Since then, great advancements, notably during the COVID-19 pandemic’s shift to remote learning, have been made. Here, we build upon the work of Collins and Kapralos with a narrative review on audio-based pseudo-haptics. This narrative review explores 17 articles obtained from the Google Scholar, RefSeek, Scopus, and PubMed databases, with the aim of providing a comprehensive summary of the progress in this field since 2019. Pseudo-haptics presents a viable alternative to simulate various aspects of touch, including weight, stiffness, roughness, dampness, force, and glossiness, when haptic devices are unavailable, enhancing immersion and providing the potential to improve psychomotor skill training within iVLEs. Full article