Type Of Gas Research Articles

Computational Model of the Effective Thermal Conductivity of a Bundle of Round Steel Bars

During the heat treatment of round steel bars, a heated charge in the form of a cylindrically formed bundle is placed in a furnace. This type of charge is a porous granular medium in which a complex heat flow occurs during heating. The following heat transfer mechanisms occur simultaneously in this medium: conduction in bars, conduction within the gas, thermal radiation between the surfaces of the bars, and contact conduction across the joints between the adjacent bars. This complex heat transfer can be quantified in terms of effective thermal conductivity. This article presents the original model of the effective thermal conductivity of a bundle of round steel bars. This model is based on the thermo-electric analogy. Each heat transfer mechanism is assigned an appropriate thermal resistance. As a result of the calculations, the impact of the following parameters on the intensity of heat transfer in the bundle was examined: temperature, the thermal conductivity of the bars, the thermal conductivity of the gas, diameter, and emissivity of the bar, and bundle porosity. Calculations were performed for a temperature range of 25–800 °C, covering a wide spectrum of variables, including bar diameters, bundle porosity, and type of gas. The knowledge obtained thanks to the calculations performed will facilitate the optimization of heat treatment processes for the considered charge. The greatest scientific value of the presented research is the demonstration that, thanks to the developed computational model, it is possible to analyze a very complex heat transfer phenomenon using relatively simple mathematical relationships.

Solution for Environmentally Friendly Silver Surface Magnetron Sputtering Color Titanium Film Layer Technology

Silver is an elegant white precious metal, but it is easily oxidized by O3, SO2, and H2S in the air, turning yellow or dark, which affects its decorative effect. The existing silver coating, primarily prepared through the electroplating process, poses serious environmental pollution problems. It is necessary to seek new, green, and environmentally friendly coating processes while also enhancing the color palette of silver jewelry coatings. Titanium film layers were deposited on Ag925 and Ag999 surfaces using magnetron sputtering coating technology. The effects of sputtering time, substrate surface state, reaction gas type and time, and film thickness on the color of the film layers were studied, and the anti discoloration performance of the obtained film layers under the optimal process was tested. The experimental results show that when the sputtering time varies from 5 to 10 minutes, injecting argon, oxygen, and nitrogen into the coating chamber yields rich colors such as purple with a red tint, blue, yellow green, yellowish purple, and blue purple. The precise control of gas injection time has a significant impact on the color of the film layer. In terms of anti tarnish performance, the film showed good stability in the artificial sweat immersion test. From an environmental perspective, the magnetron sputtering titanium film process has no harmful gas or liquid emissions, which aligns with the sustainable development trend of the jewelry industry and holds great promise for application. This study has improved the visual effect and practical performance of the product, providing important theoretical basis and experimental data support for the application of environmentally friendly silver surface vacuum magnetron sputtering titanium thin film coating technology.

Screening of Lactic Acid Bacteria Isolated from Fermented Cowpea and Optimization of Biomass Production Conditions

Considering the four characteristics of strains, including acid production, acid tolerance, salt tolerance, and nitrite degradation rate, Pediococcus pentosaceus NCU006063 was selected as the fermentation agent, and the medium composition of Pediococcus pentosaceus NCU006063 was optimized using Plackett–Burman and central composite rotational design. Three of the seven factors studied in the Plackett–Burman design significantly affected the viable counts. A central composite rotational design was used to optimize the significant factors and generate response surface plots. Using these response surface plots and point predictions, the optimal factors were soy peptone (38.75 g/L), FeSO4 (0.10 g/L), and VB7 (20 g/L). In addition, the optimized incubation conditions were a temperature of 39 °C, an initial pH value of 7, and an inoculation volume of 3%. The optimized biomass production parameters were a constant pH (6.5), neutralizing agent types (25% NH3·H2O), and gas types (N2). Under these optimal conditions, Pediococcus pentosaceus NCU006063 exhibited a great viable bacterial count of up to 2.65 × 1010 CFU/mL, which is 9.71 times higher than that of MRS broth (2.73 × 109 CFU/mL). These results demonstrated that the Pediococcus pentosaceus NCU006063 strain has excellent potential as a fermentation agent and can provide a theoretical base for the in-depth exploration and promotion of fermented cowpea use in human diets.

Machine-Learning-Driven Optimization of Cold Spray Process Parameters: Robust Inverse Analysis for Higher Deposition Efficiency

Cold spray technology has become essential for industries requiring efficient material deposition, yet achieving optimal deposition efficiency (DE) presents challenges due to complex interactions among process parameters. This study developed a two-stage machine learning (ML) framework incorporating Bayesian optimization to address these challenges. In the first stage, a classification model predicted the occurrence of deposition, while the second stage used a regression model to forecast DE values given deposition presence. The approach was validated on Aluminum 6061 data, demonstrating its capability to accurately predict DE and identify optimal process parameters for target efficiencies. Model interpretability was enhanced with SHAP analysis, which identified gas temperature and gas type as primary factors affecting DE. Scenario-based inverse analysis further validated the framework by comparing model-predicted parameters to literature data, revealing high accuracy in replicating real-world conditions. Notably, substituting hydrogen as the gas carrier reduced the required gas temperature and pressure for high DE values, suggesting economic and operational benefits over helium and nitrogen. This study demonstrates the effectiveness of AI-driven solutions in optimizing cold spray processes, contributing to more efficient and practical approaches in material deposition.

A Systematic Approach to Optimizing Regional Industrial Networks for High Eco-Efficiency Transformation.

Industrial networks have become intricately interwoven, utilizing material resources to meet humanity's needs. Recently, sustainable technologies have been pursued to enhance industrial efficiency and reduce environmental and resource impacts. However, current research lacks a comprehensive methodology and typical cases for constructing efficient resource-based industrial networks. Hence, this study employs a comprehensive approach to identify and construct efficient industrial networks from a holistic perspective. Using the Qinghai Saline Lake industrial zone as an example, this research elaborates on establishing and evaluating highly efficient regional industrial networks. It evaluates the eco-efficiency of 184 technologies based on resource development and constructs an efficient resource industry network for the development of the Qinghai Salt Lake using natural resources such as coal, oil, natural gas, and various types of ores as the initial stage and analyzes the characteristics of the industry network with different efficiencies. The research findings emphasize that solely scrutinizing technological efficiency and focusing on either the upstream raw processing network or the downstream deep-processing network while neglecting interactions within the industrial network can constrain the network's overall efficiency and hinder synergy between resources and the environment throughout the entire network. The method applies to constructing, evaluating, and optimizing industrial zones with resource endowments.

Green Hydrogen Blending into the Tunisian Natural Gas Distributing System

It is likely that blending hydrogen into natural gas grids could contribute to economy-wide decarbonization while retaining some of the benefits that natural gas networks offer energy systems. Hydrogen injection into existing natural gas infrastructure is recognised as a key solution for energy storage during periods of low electricity demand or high variable renewable energy penetration. In this scenario, natural gas networks provide an energy vector parallel to the electricity grid, offering additional energy transmission capacity and inherent storage capabilities. By incorporating green hydrogen into the NG network, it becomes feasible to (i) address the current energy crisis, (ii) reduce the carbon intensity of the gas grid, and (iii) promote sector coupling through the utilisation of various renewable energy sources. This study gives an overview of various interchangeability indicators and investigates the permissible ratios for hydrogen blending with two types of natural gas distributed in Tunisia (ANG and MNG). Additionally, it examines the impact of hydrogen injection on energy content variation and various combustion parameters. It is confirmed by the data that ANG and MNG can withstand a maximum hydrogen blend of up to 20%. The article’s conclusion emphasises the significance of evaluating infrastructure and safety standards related to Tunisia’s natural gas network and suggests more experimental testing of the findings. This research marks a critical step towards unlocking the potential of green hydrogen in Tunisia.

An Enhanced Gas Sensor Data Classification Method Using Principal Component Analysis and Synthetic Minority Over-Sampling Technique Algorithms.

This study addresses the challenge of multi-dimensional and small gas sensor data classification using a gelatin-carbon black (CB-GE) composite film sensor, achieving 91.7% accuracy in differentiating gas types (ethanol, acetone, and air). Key techniques include Principal Component Analysis (PCA) for dimensionality reduction, the Synthetic Minority Over-sampling Technique (SMOTE) for data augmentation, and the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms for classification. PCA improved KNN and SVM classification, boosting the Area Under the Curve (AUC) scores by 15.7% and 25.2%, respectively. SMOTE increased KNN's accuracy by 2.1%, preserving data structure better than polynomial fitting. The results demonstrate a scalable approach to enhancing classification accuracy under data constraints. This approach shows promise for expanding gas sensor applicability in fields where data limitations previously restricted reliability and effectiveness.

Gas-compensated thermal flow sensor using an integrated velocity-independent gas properties meter

Abstract A gas-compensated thermal flow sensor is presented that measures the flow rate in real-time, independent of the type of gas, by simultaneously measuring and compensating for the thermal conductivity and volumetric heat capacity of the gas. The thermal flow sensor consists of two free-hanging, heated wires, forming a calorimetric flow meter. The temperature difference between the two wires is a function of the flow rate and the fluid thermal properties. An additional heated wire is integrated on the same chip and used to measure the gas properties. This wire is suspended over a shallow V-groove cavity, and oriented perpendicular to the flow direction, so that it is only affected by the gas properties and not by the flow. DC excitation is used to measure the thermal conductivity, and AC excitation with the 3$\omega$ method is used to determine the volumetric heat capacity. The output of the thermal flow sensor is automatically corrected for the medium using these measured parameters. Measurements were performed with 11 different gases and gas mixtures, and in all cases the deviation between the applied flow rate and measured flow rate is less than 10\%.

Elektryfikacja miast województwa poznańskiego w okresie międzywojennym

During the partitions, electric energy was used in approximately 30 of the 129 towns of the Poznań Province, as the vast majority of towns used various types of gas. However, due to World War I, many gasoline and coal gasworks ceased to exist, and their deficit was compensated by local and small municipal direct current power plants. At the same time, attempts were made to develop a more economical district energy system based on several large plants supplying electricity to neighboring towns and villages. In the 1920s, the concept of electrification of the province was also renewed, based on district power plants and electric power stations of Greater Poland sugar factories, generating alternating current collectively. Nevertheless, until the outbreak of World War II, small power stations predominated in the towns, and the level of advancement of long-distance (district) electrification was low. At the end of 1938, electric energy was used by the population of approximately 65 out of 101 towns in the province.

Study on the gas composition of hydrate phase and unreacted liquid phase for hydrate-based gas separation

Hydrate-based gas separation (HBGS) method is an environment-friendly gas separation technique. At the end of the hydrate formation stage, the system usually consists of gas phase, hydrate phase and residual unreacted liquid phase. The separation efficiency of HBGS is usually determined by measuring the gas composition of gas phase before and after hydrate formation. It is currently unclear the gas composition of hydrate phase and residual unreacted liquid phase, and how they will affect the gas separation efficiency of HBGS separately. This work developed a novel method for efficiently separating the hydrate phase and the unreacted liquid phase, making it possible to directly measure the gas composition in the hydrate phase and residual unreacted liquid phase for the gas mixture hydrate system. The influence factors, such as operation conditions, gas composition of feed gas and types of guest gas on the gas composition of liquid and hydrate phases were studied. The experimental results show the mole fraction of CO2 in both hydrate phase and liquid phase are higher than that in the feed gas. The increase of system pressure and the mole fraction of CO2 in feed gas will obviously lead to the increase of the mole fraction of CO2 in hydrate phase, while slightly affect the mole fraction of CO2 in the liquid phase. When the mole fraction of CO2 in feed gas exceeds 80 %, the mole fraction of CO2 in the water phase will reach over 96 %, resulting in other influence factors being negligible. The mole fraction of N2 in hydrate phase is higher than that of H2, while the mole fraction of N2 in water phase is close to H2.

Optimization of the blow-off efficiency of kerosene adhering to the inner wall of chambers with complex structures

The research objective of this paper is to obtain an efficient space engine chamber wall adherent kerosene blow-off solution, the research methodology uses computational fluid dynamics method and experiments are conducted to verify the numerical calculation accuracy. The effect of gas pressure, gas temperature, ambient temperature, and gas type on the blow-off efficiency was obtained, in which increasing the pressure and temperature of the blow-off gas increased the treatment efficiency by 14.16% and 9.85%, respectively, and the blow-off efficiency was significantly improved. Increasing the operating ambient temperature and changing the type of purge gas increased the treatment efficiency by 4.76% and 5.88%, respectively. Finally, the removal scheme was optimized by increasing the blow-off gas pressure and temperature, and the treatment efficiency of the optimized scheme was improved by 37.5% compared to the original scheme. The findings of this paper provide important guidance for the efficient blow-off off of kerosene adhering to the inner wall of complex structural cavities.

Instability and collapse mechanisms of O2 and N2 nanobubble gas–liquid interfaces: A molecular dynamics simulation study

Nanobubbles, with their stability and oxidative properties, are widely applied in biomedicine, flotation, and environmental remediation. While experimental studies have explored their application effects, the dynamic behavioral characteristics of gas-containing nanobubbles during collapse remain insufficiently investigated. This study employs molecular dynamics simulation to examine nanobubble collapse under various conditions, including impact velocities, gas types, bubble sizes, and gas densities. Results show that increasing bubble size expands the microjet radiation area, while higher impact velocities increase microjet velocities. Gas types affect the jet radiation area due to differences in van der Waals forces and solubility. Vacuum nanobubbles exhibit higher maximum jet velocities than nitrogen and oxygen nanobubbles. Gas cushioning and compression rebound significantly influence maximum jet velocity. Microjets induce vortex structures, gas surface changes, and local pressure increases, leading to secondary water hammer impacts. Simulation results align well with theoretical calculations. This study provides the theoretical foundation for the industrial-scale implementation of nanobubble cavitation technology.

Vision-Centric BEV Perception: A Survey.

In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant interest from both industry and academia due to its inherent advantages, such as providing an intuitive representation of the world and being conducive to data fusion. The rapid advancements in deep learning have led to the proposal of numerous methods for addressing vision-centric BEV perception challenges. However, there has been no recent survey encompassing this novel and burgeoning research field. To catalyze future research, this paper presents a comprehensive survey of the latest developments in vision-centric BEV perception and its extensions. It compiles and organizes up-to-date knowledge, offering a systematic review and summary of prevalent algorithms. Additionally, the paper provides in-depth analyses and comparative results on various BEV perception tasks, facilitating the evaluation of future works and sparking new research directions. Furthermore, the paper discusses and shares valuable empirical implementation details to aid in the advancement of related algorithms.

Gaseous Object Detection.

Object detection, a fundamental and challenging problem in computer vision, has experienced rapid development due to the effectiveness of deep learning. The current objects to be detected are mostly rigid solid substances with apparent and distinct visual characteristics. In this paper, we endeavor on a scarcely explored task named Gaseous Object Detection (GOD), which is undertaken to explore whether the object detection techniques can be extended from solid substances to gaseous substances. Nevertheless, the gas exhibits significantly different visual characteristics: 1) saliency deficiency, 2) arbitrary and ever-changing shapes, 3) lack of distinct boundaries. To facilitate the study on this challenging task, we construct a GOD-Video dataset comprising 600 videos (141,017 frames) that cover various attributes with multiple types of gases. A comprehensive benchmark is established based on this dataset, allowing for a rigorous evaluation of frame-level and video-level detectors. Deduced from the Gaussian dispersion model, the physics-inspired Voxel Shift Field (VSF) is designed to model geometric irregularities and ever-changing shapes in potential 3D space. By integrating VSF into Faster RCNN, the VSF RCNN serves as a simple but strong baseline for gaseous object detection. Our work aims to attract further research into this valuable albeit challenging area.

Hydrogen injection and withdrawal performance in depleted gas reservoirs

Residual gas trapping in porous media is a key indicator of hydrogen storage and recovery performance. The injection scheme of cushion and working gases helps maintain pressure and reduce losses. However, this information is limited in the literature. This work explores core flooding experiments (using electrical resistivity for in-situ saturation monitoring) on Bandera Grey sandstones under reservoir conditions (42 °C, 1400 psi, and 5 wt% NaCl), investigating cushion gas type and injection rate effects on storage and recovery performance. Results indicate that CO2 injection ahead of hydrogen yielded the highest storage capacity with Sgi=0.255, then CH4: Sgi=0.226 and finally, N2: Sgi=0.216. At lower injection rates (0.2–0.6 cc/min), CH4 cushion gas exhibited the highest recovery (42%), whereas at higher injection rates (1.2–10 cc/min), CO2 resulted in the highest, with 33%. These findings emphasize cushion gas's role in enhancing hydrogen storage capacity and production efficiency in depleted gas reservoirs.

Bacterial biofilm inactivation by plasma activated nanobubble water

This research developed novel plasma activated nanobubble water (PANBW) by integrating atmospheric cold plasma and nanobubble water (NBW) technologies. Mixing of plasma reactive species with NBW to generate the PANBW makes it an effective solution for microbial biofilm inactivation and water treatment, possibly by leveraging the benefits of both technologies. Selected properties of PANBW, including the concentrations of reactive oxygen and nitrogen species (RONS) were characterized, and the stability of RONS during storage for 7 days were evaluated. The combination of argon and air as feed gases was used to determine the influence of feed gas type on RONS production and the effect of the generated PANBW on biofilm reduction. The effectiveness of PANBW in inactivating mixed-species bacterial biofilms was assessed against NBW, plasma activated water (PAW), and their combinations. This comparison involved treating biofilms of Salmonella enterica Typhimurium ATCC 13311 and Aeromonas australiensis, that were grown on stainless steel coupons by these solutions. The PANBW treatment was most effective in the inactivation of the tested mixed species biofilms with a reduction of >2 log CFU/cm2 in the biofilm population. The confocal laser scanning microscopy analysis was consistent with the bacterial inactivation results. This study highlights the potential of atmospheric cold plasma when combined with nanobubble technology, as a novel and efficient method for biofilm control and food safety applications.

The effect of assist gas type on nitinol microsecond laser cut edges: a study on the use of oxygen, argon, nitrogen, helium, and compressed air

Abstract Historically, the published literature for laser cutting atomically balanced nickel-titanium alloy (Nitinol) tubular devices assumes slow cut rates with an inert argon assist gas. Herein, a novel application of an exothermic reactive oxygen assist gas was employed during Nitinol laser micromachining, which enabled a 38.1 mm s−1 cut rate, a 4.5-times improvement from traditional argon cutting. Furthermore, this led to the realization of improved cut quality: 2-times less dross, a 2-times lower surface roughness, and a minimal heat-affected zone. Of the tested assist gases (oxygen, argon, nitrogen, helium, and compressed air), oxygen was found to provide the best cut quality, achieving dross-free cuts. Additionally, oxygen was shown to produce a relatively low arithmetic mean average surface roughness of 0.48 μm, when compared to argon at 0.85 μm. A decrease in surface roughness was found to be associated with an increase in cut rate. These findings suggest that assist gas melt flow dynamics has a higher contributing factor than laser pulse energy parameters. In-situ thermographic monitoring of the melt flow during processing demonstrated a clear difference in the melt flow pattern between a reactive oxygen assist gas and inert argon assist gas. Furthermore, with the culmination of nanoindentation analysis and microstructural characterization, it was concluded that long-pulse laser micromachining can produce cuts with negligible microstructural alterations to the bulk material. This study quantitatively demonstrates the benefits observed during laser cutting Nitinol with a reactive oxygen assist gas when compared to previous studies that employ an inert argon assist gas.

Navigating Greenhouse Gas Emission Unknowns: A Hydroacoustic Examination of Mediterranean Climate Reservoirs

AbstractInland aquatic systems, such as reservoirs, contribute substantially to global methane (CH4) emissions; yet they are among the most uncertain contributors to the total global carbon budget. Reservoirs generate significant amounts of CH4 within their bottom sediment, where the gas is stored and can easily escape via ebullition. Due to the large spatial and temporal variability associated with ebullition, CH4 fluxes from these aquatic systems are challenging to quantify. To address these uncertainties, six different water storage reservoirs, with average flux rates ranging between 20 and 678 mg CH4 m−2 d−1, were hydro‐acoustically surveyed using a previously established technique to investigate the spatial variability of free gas stored at the sediment surface that could be released as bubbles. Sediment samples and vertical profiles of temperature and dissolved oxygen were also collected to understand their respective influences on sediment gas formation. We found that the established relation used to determine sediment gas storage via the sonar technique, which relied solely on acoustic backscatter (Svmax), tended to underestimate gas storage in shallower, siltier sediment zones and overestimate gas storage in coarser (>2 mm) sediment zones. In response, we introduce an improved model, incorporating gas and sediment type as correction factors for gas attenuation effects on Svmax values. The extended model is able to elucidate patterns within the gas volume data, revealing clearer trends across different sediment types. This research provides valuable data and methodological insights that can enhance the accuracy of greenhouse gas modeling and budget assessments for reservoirs.

Integrated assessment of farm-level mitigation measures for gaseous emissions

ContextSome gaseous emissions continue to pose a serious threat to human health and the environment locally, regionally and globally. This has resulted in several studies advocating for the implementation of mitigation measures to reduce the emissions of harmful gases. ObjectiveWhile the vast majority of studies focus on a single type of gas, much less attention has been paid to the complementary or conflicting effects of mitigation measures across multiple harmful gaseous emissions dimensions. MethodsTo address this research gap, this study uses Irish farm-level data to assess the holistic costs and benefits of a suite of mitigation measures that have the potential to abate greenhouse gases, ammonia or both. A cost-benefit analysis framework is employed to assess the impact of the mitigation measures across five different farm system types. Results and conclusionsResults indicate that the relative effectiveness of the mitigation measure varies depending on the gaseous emission dimension being examined. SignificanceAnalyses that fail to account for such synergistic and antagonistic relationship impacts may lead to flawed policy decisions.

Effect of Injected Gas type on Condensate Recovery of Gas Reservoirs Using 3D Compositional Modeling

Effect of Injected Gas type on Condensate Recovery of Gas Reservoirs Using 3D Compositional Modeling