Search Results (118)

Non-catalytic partial oxidation (POX) of natural gas is gaining importance in low-carbon energy systems for methane conversion to acetylene, syngas, and olefins. However, uncontrolled polycyclic aromatic hydrocarbons (PAHs) and soot formation remain challenges. This work developed a Hierarchical-Integrated Mechanism (HI-Mechanism) by constructing detailed C₀-C₆, C₅-C₁₅ and C₁₆ mechanisms, and then hierarchically simplifying C₅-C₁₅ subsystems, ultimately integrating them into a final mechanism with 397 species and 5135 reactions. The HI-Mechanism accurately predicted shock tube ignition delays and major species concentrations. Microkinetic analyses, including production rates and reaction sensitivity, revealed key pathways and enabled reliable product distribution prediction. The HI-Mechanism provides theoretical guidance for optimizing POX of natural gas processes and can be extended to complex systems like heavy oil cracking, supporting clean energy technology development. Full article

This study innovatively proposes a pipeline-type pneumatic lift sediment removal device for cleaning pollutants at the bottom of fish breeding tanks and conducts hydrodynamic characteristic analysis on its core component, the pneumatic lift pipeline structure, which consists of a horizontal circular tube with multiple micro-orifices at the bottom and an upward-inclined circular tube. The pipeline has an inner diameter of 20 mm and a vertical length of 1.2 m, with the orifice at one end of the horizontal tube connected to the gas supply line. During operation, compressed gas enters the horizontal tube, generating negative liquid pressure that draws solid–liquid mixtures from the tank bottom into the pipeline, while buoyant forces propel the gas–liquid–solid mixture upward for discharge through the outlet. Under a constant gas flow rate, numerical simulations investigated efficiency variations through three operational scenarios: ① different pipeline orifice diameters, ② varying orifice quantities and spacings, and ③ adjustable pipeline bottom clearance heights. The results indicate that in scenario ①, an orifice diameter of 4 mm demonstrated optimal efficiency; in scenario ②, the eight-orifice configuration achieved peak efficiency; and scenario ③ showed that the proper adjustment of the bottom clearance height enhances pneumatic efficiency, with maximum efficiency observed at a clearance of 10 mm between sediment suction pipe and tank bottom. Full article

Hydrogen is a potential source of imminent clean energy in the future, with its transportation playing a crucial role in allowing large-scale deployment. The challenge lies in selecting an effective, sustainable, and scalable transportation alternative. This study develops a multi-criteria decision-making (MCDM) framework based on the intuitionistic fuzzy analytic hierarchy process (IF-AHP) to evaluate land-based hydrogen transportation alternatives across Canada. The framework includes uncertainty and decision-maker hesitation through the application of triangular intuitionistic fuzzy numbers (TIFNs). Seven factors, their subsequent thirty-three subfactors, and three alternatives to hydrogen transportation were identified through a literature review. Pairwise comparison was aggregated among factors, subfactors, and alternatives from three decision makers using an intuitionistic fuzzy weighted average, and priority weights were computed using entropy-based weight. The results show that safety and economic efficiency emerged as the most influential factors in the evaluation of hydrogen transportation alternatives, followed by environmental impact, security, and social impact and public health in ascending order. Among the alternatives, tube truck transport obtained the highest overall weight (0.3551), followed by pipelines (0.3272) and rail lines (0.3251). The findings suggest that the tube ruck is currently the most feasible transport option for land-based hydrogen distribution that aims to provide a transition of Canada’s energy mix. Full article

Cleaning operations in narrow pipelines are often hindered by limited maneuverability and low efficiency, necessitating the development of a high-performance and highly adaptable robotic solution. To address this challenge, this study proposes a pipeline-cleaning robot specifically designed for the heat-exchange tubes of industrial heat exchangers. The robot features a dual-wheel cross-drive configuration to enhance motion stability and integrates a gear–rack-based alignment mechanism with a cam-based propulsion system to enable autonomous deployment and cleaning via a flexible arm. The robot adopts a modular architecture with a separated body and cleaning arm, allowing for rapid assembly and maintenance through bolted connections. A vision-guided control system is implemented to support accurate positioning and task scheduling within the primary pipeline. Experimental results demonstrate that the robot can stably execute automatic navigation and sub-pipe cleaning, achieving pipe-switching times of less than 30 s. The system operates reliably and significantly improves cleaning efficiency. The proposed robotic system exhibits strong adaptability and generalizability, offering an effective solution for automated cleaning in confined pipeline environments. Full article

Energy storage technology is crucial for promoting the replacement of traditional energy with renewable energy and regulating the energy supply–demand relationship. This paper investigates a triplex-tube thermal energy unit storage to solve the intermediate heat storage and heat transfer problem of hot water supply and demand in clean heating systems. A multi-objective optimization method based on the elitist non-dominated sorting genetic algorithm (NSGA-II) was utilized to optimize the geometric dimensions (inner tube radius $r_1$, casing tube radius $r_2$, and outer tube radius $r_3$), focusing on heat transfer efficiency ($\epsilon$), heat storage rate ($P_t$), and mass (M). On this basis, the influence of the optimization variables was analyzed. The optimized configuration ($r_1=0.014$ m, $r_2=0.041$ m, and $r_3=0.052$ m) was integrated into a modular design, achieving a 2.12% improvement in heat transfer efficiency and a 73.23% increase in heat storage rate. Experimental results revealed that higher heat transfer fluid (HTF) temperatures significantly reduce heat storage time, while HTF flow rate has a minimal impact. Increasing the heat release temperature extends the phase change material (PCM) heat release duration, with the flow rate showing negligible effects. The system’s thermal supply capacity is susceptible to heat release temperature. Full article

Ground-source heat pump (GSHP) systems with medium-depth and deeply buried pipes in cold regions are highly important for addressing global climate change and the energy crisis because of their efficient, clean, and sustainable energy characteristics. However, unique geological conditions in cold climates pose serious challenges to the heat transfer efficiency, long-term stability, and adaptability of systems. This study comprehensively analyses the effects of various factors, including well depth, inner-to-outer tube diameter ratios, cementing material, the thermal conductivity of the inner tube, the flow rate, and the start–stop ratio, on the performance of a medium-depth coaxial borehole heat exchanger. Field tests, numerical simulations, and sensitivity analyses are combined to determine the full-cycle thermal performance and heat-transfer properties of medium-depth geological formations and their relationships with system performance. The results show that the source water temperature increases by approximately 4 °C and that the heat transfer increases by 50 kW for every 500 m increase in well depth. The optimization of the inner and outer pipe diameter ratios effectively improves the heat-exchange efficiency, and a larger pipe diameter ratio design can significantly reduce the flow resistance and improve system stability. When the thermal conductivity of the cementing cement increases from 1 W/(m·K) to 2 W/(m·K), the outlet water temperature at the source side increases by approximately 1 °C, and the heat transfer increases by 13 kW. However, the improvement effect of further increasing the thermal conductivity on the heat-exchange efficiency gradually decreases. When the flow rate is 0.7 m/s, the heat transfer is stable at approximately 250 kW, and the system economy and heat-transfer efficiency reach a balance. These findings provide a robust scientific basis for promoting medium-deep geothermal energy heating systems in cold regions and offer valuable references for the green and low-carbon transition in building heating systems. Full article

Polyetherketoneketone (PEKK) exhibits satisfactory mechanical properties and biocompatibility, with an elastic modulus closely resembling that of natural bone. This property reduces the stress-shielding effect associated with bone implants. However, the biological inertness of the PEKK surface remains a significant limitation for its application in bone tissue engineering. The objective of this study was to create a superhydrophilic 3D porous structure on the surface of PEKK to enhance biocompatibility, in terms of vascularization and bone remodeling. A combination of mechanical, chemical, and physical surface treatments was employed to modify the PEKK surface. Initially, mechanical sandblasting was used to create a rough surface to promote mechanical interlocking with bone tissue. Subsequently, chemical acid etching and physical low-temperature atmospheric plasma cleaning were applied to develop a superhydrophilic 3D porous surface. The modified surfaces were characterized for morphology, roughness, hydrophilicity, and functional groups. Cellular responses, including vascularization and bone remodeling, were evaluated to assess the potential for improved biocompatibility. The combination of acid etching and low-temperature atmospheric plasma cleaning, with or without prior sandblasting, successfully created a superhydrophilic 3D porous structure on the PEKK surface. This modified surface enhanced the tube formation in human umbilical vein endothelial cells. It also promoted the adhesion and mineralization of human bone marrow mesenchymal stem cells and slightly reduced tartrate-resistant acid phosphatase expression and F-actin ring size in mouse macrophage cells. This study introduces an innovative and effective surface modification strategy for PEKK surface, combining mechanical, chemical, and physical treatments to enhance biocompatibility. The modified PEKK surface promotes angiogenic and osteogenic responses while slightly inhibiting osteoclastic activity, making it a potential alternative for dental and orthopedic PEKK implant applications. Full article

Coiled tubing (CT) plays a pivotal role in oil and gas well intervention operations due to its advantages, such as flexibility, fast mobilization, safety, low cost, and its wide range of applications, including well intervention, cleaning, stimulation, fluid displacement, cementing, and drilling. However, CT is subject to fatigue and mechanical damage caused by repeated bending cycles, internal pressure, and environmental factors, which can lead to premature failure, high operational costs, and production downtime. With the development of CT properties and modes of application, traditional fatigue life prediction methods based on analytical models integrated in the tracking process showed, in some cases, an underestimate or overestimate of the actual fatigue life of CT, particularly when complex factors like welding type, corrosive environment, and high-pressure variation are involved. This study addresses this limitation by introducing a comprehensive machine learning-based approach to improve the accuracy of CT fatigue life prediction, using a dataset derived from both lab-scale and full-scale fatigue tests. We incorporated the impact of different parameters such as CT grades, wall thickness, CT diameter, internal pressure, and welding types. By using advanced machine learning techniques such as artificial neural networks (ANNs) and Gradient Boosting Regressor, we obtained a more precise estimation of the number of cycles to failure than traditional models. The results from our machine learning analysis demonstrated that CatBoost and XGBoost are the most suitable models for fatigue life prediction. These models exhibited high predictive accuracy, with R² values exceeding 0.94 on the test set, alongside relatively low error metrics (MSE, MAE and MAPE), indicating strong generalization capability. The results of this study show the importance of the integration of machine learning for CT fatigue life analysis and demonstrate its capacity to enhance prediction accuracy and reduce uncertainty. A detailed machine learning model is presented, emphasizing the capability to handle complex data and improve prediction under diverse operational conditions. This study contributes to more reliable CT management and safer, more cost-efficient well intervention operations. Full article

Biomass clean energy is widely used as an alternative to fossil fuels due to its advantages of low carbon emissions, cleanliness, and renewability. Biomass fuel exchangers are important equipment for heat exchange between air and exhaust gasses after biomass combustion, and the air flow rate and structural characteristics of the exchanger have a significant impact on the heat transfer performance. In order to investigate the effect of Reynolds number on the heat transfer performance of the exchanger when air flows through, a serpentine tube heat exchange test bench was constructed, and numerical calculations were performed using the Realizable k-ε turbulence model for the entire channel. By changing the diameter and pitch of the serpentine tube, the effects of geometric parameters on the heat transfer performance were studied, and the flow characteristics of exhaust gasses and air inside the exchanger under various operating conditions were deduced. Subsequently, experimental validation was conducted by referring to the boundary conditions of numerical calculations, obtaining corresponding test data, and comparing the numerical and experimental results, showing that the errors in various physical quantities were within 5%. Through comprehensive analysis of the data, it was found that when the serpentine tube diameter is 80 mm and pitch is 300 mm, the Nusselt number (Nu) increased most significantly with Reynolds number (Re) by 25.17%, indicating the best heat transfer performance. Additionally, reducing tube diameter, increasing serpentine tube pitch, enlarging air-inlet flow velocity can enhance Re, increase fluid disturbance, and improve convective heat transfer intensity, thereby increasing Nu and strengthening the heat transfer performance of the serpentine tube exchanger. Full article

Thisstudy introduces a new model for detecting insults in Roman Urdu, filling an important gap in natural language processing (NLP) for low-resource languages. The transliterated nature of Roman Urdu also poses specific challenges from a computational linguistics perspective, including non-standardized grammar, variation in spellings for the same word, and high levels of code-mixing with English, which together make automated insult detection for Roman Urdu a highly complex problem. To address these problems, we created a large-scale dataset with 46,045 labeled comments from social media websites such as Twitter, Facebook, and YouTube. This is the first dataset for insult detection for Roman Urdu that was created and annotated with insulting and non-insulting content. Advanced preprocessing methods such as text cleaning, text normalization, and tokenization are used in the study, as well as feature extraction using TF–IDF through unigram (Uni), bigram (Bi), trigram (Tri), and their unions: Uni+Bi+Trigram. We compared ten machine learning algorithms (logistic regression, support vector machines, random forest, gradient boosting, AdaBoost, and XGBoost) and three deep learning topologies (CNN, LSTM, and Bi-LSTM). Different models were compared, and ensemble ones were proven to give the highest F1-scores, reaching 97.79%, 97.78%, and 95.25%, respectively, for AdaBoost, decision tree, TF–IDF, and Uni+Bi+Trigram configurations. Deeper learning models also performed on par, with CNN achieving an F1-score of 97.01%. Overall, the results highlight the utility of n-gram features and the combination of robust classifiers in detecting insults. This study makes strides in improving NLP for Roman Urdu, yet further research has established the foundation of pre-trained transformers and hybrid approaches; this could overcome existing systems and platform limitations. This study has conscious implications, mainly on the construction of automated moderation tools to achieve safer online spaces, especially for South Asian social media websites. Full article

The aircraft cabin provides a unique indoor environment compared to other building environments. Tetrachloroethylene (PCE) is widely found in cabins and has clear adverse health impacts. This study investigated the PCE pollution characteristics in 56 aircraft cabins using on-flight Tenax-TA tube sampling and GC-MS analysis. PCE was detected at a high rate of 79% in sampled flights, indicating widespread contamination within the cabins. The mean concentration of PCE was 10.12 μg/m³, exceeding the 2.06 μg/m³ observed in residences in a previous study. The positive matrix factorization (PMF) model was used to identify potential sources of PCE in cabins. Six categories of sources were determined, including in-cabin cleaning products, aircraft cleaning/maintenance, cabin interior material, aircraft and vehicle exhaust, non-fuel oil and ozone-associated chemical reactions. The biggest PCE source in cabins was attributed to in-cabin cleaning products (45.30%), followed by cabin interior materials (24.90%), and aircraft cleaning/maintenance (19.82%). The findings of this study are beneficial to improving aircraft cabin air quality, reducing harmful pollutant exposure for cabin crew and passengers. Full article

Pre-heat trains (PHTs) significantly reduce refinery fuel consumption and carbon emissions. However, these benefits are diminished by fouling in heat exchangers (HEXs). Current methods for optimizing cleaning schedules often report high computation times due to the transient nature of the fouling process and do not consider shell-side fouling, which can be significant for some oil fractions. This paper addresses these issues by adding shell-side fouling to the model and by transforming cleaning time variables into integers, reducing the problem of optimizing cleaning schedules to an integer nonlinear programming (INLP) problem. The reformulated problem is solved using integer particle swarm optimization (PSO) coupled with a simple search strategy, where the number of cleaning actions is preset and their timing is optimized. The adopted approach achieved up to 84% lower computation times compared to previous ones. Additionally, the relationship between cleaning actions and PHT performance is nonlinear, with diminishing returns from additional cleaning, and optimal cleaning schedules are often asymmetric for different HEXs within the same PHT. The proposed approach effectively reduces operating costs and provides a framework for future optimization enhancements. Full article

Coated metallic stents are the next generation of metallic stents with improved surface properties. To evaluate the degradation behavior of stents in vitro, different in vitro degradation models can be applied: (i) static immersion test: degradation under static fluid condition, (ii) fluid dynamic test: degradation under flowing fluid, and (iii) electrochemical corrosion test: degradation under the influence of electric potential. During these experimental procedures, stents interact with the simulated blood plasma, and degradation products are formed in the form of depositions on the stent surface, likewise in vivo experiments. These deposited crystals act as a hindrance to the application of important characterization techniques (e.g., mass loss measurement for the calculation of corrosion rate and examining the adhesion of the coating to metallic stents after fluid dynamic exposure). Therefore, to better characterize the coatings, the removal of these depositions is significant. In this work, we investigate the influence of in vitro test conditions in fluid dynamic biostability tests on the biostability of titanium oxynitride (TiO_XN_Y) coated stainless steel stents by adapting various fluid dynamic experimental parameters. The experimental conditions are based on modification in the components of fluid dynamic setup (e.g., tubings), simulated body fluid (SBF), with and without Ca⁺⁺ and Mg⁺⁺ ions, and the cleaning procedure (use of water, acetone, and isopropanol). Four different experiments were conducted under various experimental parameter sets. SEM and EDX measurements were used for the identification of degradation products after each experiment. This study highlights the importance of optimized experimental conditions showing negligible depositions when utilizing Puriflex tubing or a comparable artificial vessel, SBF devoid of Ca⁺⁺ and Mg⁺⁺ ions, and performing sample cleaning with distilled water in an ultrasonic bath. The presented conditions were optimized for titanium oxynitride coated samples. A similar approach could be applied to other samples with or without some small variation. Full article

This paper presents a comprehensive holistic methodology implemented for sustainable lighting systems in educational institutions. The proposed methodology is aligned with the Sustainable Development Goals (SDGs), particularly with SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), and it follows international standards. The six-step process includes viability analysis, project design simulation using DIALux 4.13 software, the installation of LED lighting systems, and the redesign of some electrical circuits, followed by an analysis of return on investment and the monitorization of CO₂ and energy consumption. The proposed methodology results in significant return on investment (ROI), primarily achieved through energy savings and reduced maintenance costs. The implementation of LED tubes, combined with occupancy and natural light sensors, leads to a 66% reduction in energy consumption and a reduction of 15.63 tons (metric tons) of CO₂ annually, translating into a quick payback period of approximately 2.36 years. Additionally, the system includes Long-Term Monitoring, which ensures that energy consumption and lighting levels are continuously tracked. Full article

Offshore wind power is a new type of clean energy with broad development prospects. Accurate analysis of the uplift capacity of offshore wind turbine foundations is a crucial prerequisite for ensuring the safe operation of wind turbines under complex hydrodynamic conditions. However, current research on the uplift capacity of suction caissons often neglects the high-sensitivity characteristics of marine soils. Therefore, this paper first employs the freeze–thaw cycling procedure to prepare high-sensitivity saturated clay. Subsequently, a single−tube foundation for wind turbines is constructed within a centrifuge through a penetration approach. Ten sets of centrifuge model tests with vertical cyclic pullout are conducted. Through comparative analysis, this study explores the pullout capacity and its variation patterns of suction caisson foundations in clay with different sensitivities under cyclic loading. This research indicates the following: (1) The preparation of high-sensitivity soil through the freeze−thaw procedure is reliable; (2) the uplift capacity of suction caissons in high−sensitivity soil rapidly decreases with increasing numbers of cyclic loads and then tends to stabilize. The cumulative displacement rate of suction caissons in high-sensitivity soil is fast, and the total number of pressure–pullout cycles required to reach non-cumulative displacement is significantly smaller than that in low-sensitivity soil; (3) the vertical cyclic loading times and stiffness evolution patterns of single-tube foundations, considering the influence of sensitivity, have been analyzed. It was found that the secant stiffness exhibits a logarithmic function relationship with both the number of cycles and sensitivity. The findings of this study provide assistance and support for the design of suction caissons in high-sensitivity soils. Full article