Gas Pressure Research Articles

On a quasilinear parabolic–hyperbolic system arising in MEMS modeling

AbstractA coupled system consisting of a quasilinear parabolic equation and a semilinear hyperbolic equation is considered. The problem arises as a small aspect ratio limit in the modeling of a MEMS device taking into account the gap width of the device and the gas pressure. The system is regarded as a special case of a more general setting for which local well-posedness of strong solutions is shown. The general result applies to different cases including a coupling of the parabolic equation to a semilinear wave equation of either second or fourth order, the latter featuring either clamped or pinned boundary conditions.

Ion Moblity Mass Spectrometry in Multi-omics Studies

Mass spectrometry (MS) as an analytical technique enables the identification and quantitative determination of proteins, metabolites, or lipids in a studied sample. However, this method has limitations regarding the number of molecules that can be identified at a given time. To increase the number of identifications, the application of ion mobility spectrometry (IMS) can be employed. This technique allows the separation of ions based on their mobility while traversing the analyser in a gradient of an electromagnetic field and opposing gas pressure. The separation is performed in conjunction with MS analysis, adding another dimension to the analysis, resulting in a significant improvement in the number of identified compounds and a reduction in noise. Alternatively, while maintaining the same number of identifications, analysis can be performed in a shorter time period. It is crucial to pay special attention to the type of IMS analyser used, as its specific implementation dictates further stages of analysis and ion detection capabilities.

Dynamic laser ablation loading of a linear Paul trap

We present a detailed method for accumulating Ca+ ions controllably in a linear Paul trap. The ions are generated by pulsed laser ablation and dynamically loaded into the ion trap by switching the trapping potential on and off. The loaded ions are precooled by buffer gas and then laser-cooled to form Coulomb crystals for verifying quantity. The number of ions is controlled by manipulating the trapping potential of the ion trap, partial pressure of buffer gas and turn-on time of the entrance end cap voltage. With single-pulse laser ablation, the number of trapped ions ranges from tens to ten thousand. The kinetic energy of loaded ions can be selected via the optimal turn-on time of the entrance end cap. Using multiple-pulse laser ablation, the number is further increased and reaches about 4×104 . The dynamic loading method has wide application for accumulating low-yielding ions via laser ablation in the ion trap.

Particle-in-cell simulations of EUV-induced hydrogen plasma in the vicinity of a reflective mirror

Abstract Particle-In-Cell (PIC) simulations were performed in this work to study the dynamics of the EUV induced hydrogen plasma. Monte-Carlo Collision (MCC) model was employed to deal with the collisions between charged particles and background gas molecules. The dynamic evolution of the plasma sheath, as well as the flux and energy distribution of ions impact on the mirror surface, was discussed. It was found that the emission of secondary electrons under the EUV irradiation on the ruthenium coating of mirrors creates a positively charged wall and then prevents the ion from impacting onto the mirror and therefore changes the flux and energy distribution of ions reach the mirror. Furthermore, gas pressure has notable effect on the plasma sheath and the characteristics of the ions impinging on the mirrors. With greater gas pressure, the sheath potential decreases more rapidly. The flux of ions received by the mirror grows approximately linearly and the energy corresponding to the peak flux decreases slightly in the meantime. Meanwhile, EUV source intensity barely changes the sheath potential and its influence on the ion impact is mainly limited to the approximate linear increase of ion flux.

Investigation on desulfurization and ground granulated blast furnace slags reutilization for carbon dioxide sorption in a fluidized bed reactor

BackgroundThe atmospheric CO2 concentration is significantly increasing due to the utilization of fossil fuel in various activities. Implementation of steel slag is considered as a promising strategy for carbon capture MethodsIn this study, the slags from desulfurization (De-S) and ground granulated blast furnace (GGBS) processes in the steel company waste were applied as the sorbent in CO2 removal using a fluidized bed system. Various operating conditions were applied to determine the influence of operating parameters on sorbent performance. Moreover, examination on sorbent characteristic change and kinetics calculation were also carried out in this study. Significant findingOptimum operating temperature was reached by the application of 600 and 500 °C for De-S and GGBS slag, respectively. The higher CO2 concentration and 5 % water vapor improved the sorbent utilization. However, excessive water vapor and low fluidized velocity decreased the performance of sorbent. De-S slag performed better on overall CO2 capture process compared to GGBS slag. Therefore, upscaled study with 10 times greater size was further conducted with the 150–300 µm De-S slag for the CO2 capture from oxy-fuel and air combustion. The higher CO2 partial pressure in the flue gas of oxy-fuel combustion increased the capture process efficiency.

Fabry-Pérot photothermal interferometry in a hollow-core antiresonant fiber for gas detection in mid-infrared

Hollow-core antiresonant fiber can simultaneously act as a miniature gas cell and the light guidance with broad wavelength range, introducing an powerful tool to photothermal spectrosocpy and sensitive gas detection. Photothermal interferometry (PTI) is a spectroscopic tehcnique that employs an interferometer to finely measure the photothermal signal of trace gas. By splicing the HC-ARF between solid core fibers, a Fabry-Pérot (F-P) cavity is formed and enables PTI with a brief in-line design. However, the previous structure commonly adopted single-mode solid core fibers and might introduce large optical loss due to mode field mismatch, particularly for MIR pump laser. This could lead to significant decrease in sensitivity. Besides, the gas pressure effect on the HC-ARF-based PTI gas sensor had not been fully studied. In this work, we demonstrated the PTI for 13CO2 detection at 4.35 µm by employing an HC-ARF with a 100-µm core. An InF3 multimode fiber was utilized for the efficient delivery of MIR pump beam and successfully enhanced the pump power by a factor of 6.7. The limit of detection was determined to be 0.4 ppb at the integration time of 240 s. Finally, the relationship between gas pressure and photothermal signal was experimentally studied and compared with theoretical results.

Time evolution of radius of bubble comprising carbon dioxide and air

The dynamics of a single bubble in an aqueous solution of carbon dioxide (CO2) and air were theoretically investigated. The time evolution of the bubble radius and that of the partial pressures of CO2 gas and air in the bubble were studied by solving the simultaneous time evolution equations for these variables analytically and numerically. It was shown that bubbles comprising CO2 gas and air, the solubilities of which in water were significantly different, exhibited peculiar behaviors that could not be expected from classical nucleation theory. The bubble radii, expressed as a function of time, exhibited peaks, kinks, and plateaus. Bubbles smaller or larger than the critical bubble radius could grow and diverge or shrink and vanish, respectively.

Investigating different carbon-based target materials: Can we improve ionization in HiPIMS for the deposition of diamondlike carbon films?

Investigating different carbon-based target materials: Can we improve ionization in HiPIMS for the deposition of diamondlike carbon films?

2D analysis of sputtered species transport in high-power impulse magnetron sputtering (HiPIMS) discharge

Among the numerous advantages of the high-power impulse magnetron sputtering (HiPIMS) technique, the most important is the enhanced ionization degree of sputtered species contributing to the film growth. Consequently, the quality of deposited thin films is highly improved. Still, the optimization process is challenging due to the complexity associated with the intricate transport of the sputtered species, ionized or neutrals. The scarce knowledge available on the spatial distribution of these species when operating a HiPIMS discharge makes the quantitative prediction of any deposition feature particularly difficult. In this paper, we discuss the influence of experimentally controllable quantities, such as gas pressure and target current density, on the transport of sputtered titanium in non-reactive (argon) HiPIMS, namely, on the behavior of metal atoms and metal ion fluxes intercepting the substrate. Systematic quantitative measurements were performed in a diameter normal plane on a circular planar target. Hence, the 2D spatial distribution of the ionized flux fraction (IFF) and the total flux of titanium sputtered particles (deposition rate) are evaluated by biasing a quartz crystal microbalance equipped with an electron magnetic filter. The wide range of parameters we examined allows us to predict and optimize the flux of sputtered species based on complete mapping of the IFF of sputtered particles.

Application of artificial intelligence in mine ventilation: a brief review

In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems. A mine ventilation network presents a complex system with numerous interconnected processes, some of which pose challenges for deterministic simulation methods. The utilization of machine learning techniques and evolutionary algorithms offers a promising avenue to address these complexities, resulting in enhanced monitoring and control of air parameter distribution within the ventilation network. These methods facilitate the timely identification of resistance faults and enable prompt calculation of ventilation parameters during emergency scenarios, such as underground explosions and fires. Furthermore, evolutionary algorithms play a crucial role in the advancement of methods for visual analysis of ventilation systems. However, it is essential to acknowledge that the current utilization of AI technologies in mine ventilation is limited and does not encompass the full spectrum of challenging-to-formalize problems. Promising areas for AI application include analyzing changes in air distribution caused by unaccounted thermal draft and gas pressure, as well as developing novel approaches for calculating shock losses. Moreover, the application of AI technologies in optimizing large-scale mine ventilation networks remains an unresolved issue. Addressing these challenges holds significant potential for enhancing safety and efficiency in mine ventilation systems.

CHANG-ES. XXX. 10 kpc Radio Lobes in the Sombrero Galaxy

We report the discovery of the 10 kpc scale radio lobes in the Sombrero galaxy (NGC 4594), using data from the Continuum Halos in Nearby Galaxies—an Expanded Very Large Array Survey project. We further examine the balance between the magnetic pressure inside the lobes and the thermal pressure of the ambient hot gas. At the radii r of ∼(1–10) kpc, the magnetic pressure inside the lobes and the thermal pressure of the ambient hot gas are generally in balance. This implies that the jets could expand into the surroundings to at least r ∼ 10 kpc. The feedback from the active galactic nucleus jet responsible for the large-scale lobes may help to explain the unusually high X-ray luminosity of this massive quiescent isolated disk galaxy, although more theoretical work is needed to further examine this possibility.

Pressure Balance and Energy Budget of the Nuclear Superbubble of NGC 3079

Superbubbles in the nuclear region of galaxies could be produced by active galactic nuclei (AGN) or nuclear starburst via different driving forces. We report analysis of the multiwavelength data of the kiloparsec-scale nuclear superbubble in NGC 3079 in order to probe the mechanisms driving the expansion of the superbubble. Based on the Chandra X-ray observations, we derive the hot-gas thermal pressure inside the bubble, which is about 1 order of magnitude higher than that of the warm ionized gas traced by optical lines. We derive a [C ii]-based star formation rate (SFR) of SFR ∼ 1.3 M ⊙ yr−1 from the nuclear region using the SOFIA/FIFI-LS observation. This SFR infers a radiation pressure toward the bubble shells much lower than the thermal pressure of the gases. The Very Large Array radio image infers that magnetic pressure at the northeast cap above the superbubble is less than the thermal pressure of the hot gas enclosed in the bubble but has a clearly larger extension. The magnetic field may thus still help to reconcile the expansion of the bubble. The observed thermal energy of the hot gas enclosed in the bubble requires an energy injection rate of ≳1042 erg s−1 within the bubble’s dynamical age, which is probably larger than the power provided by the current nuclear starburst and the parsec-scale jet. If this is true, stronger past AGN activity may provide an alternative energy source to drive the observed bubble expansion.

Energy dissipation and crack propagation in gas-containing coal under impact loading: An experimental study

Gas-containing coal seams are highly susceptible to coal and gas outburst and composite dynamic disaster due to dynamic loads generated by roof breaks and blasting. This is an energy-driven state destabilization phenomenon, and is intricately correlated to the development of the cracks (i.e. damage evolution) within the coal. To accurately understand the energy evolution and damage principle of gas-containing coal under impact loading condition, we conducted impact compression experiments on the coal body under varying gas pressures. We analyzed the compression energy dissipation characteristics of the coal body under different gas pressures. Additionally, we utilized the CT scanning system to obtain the fracture evolution laws of gas-containing coal under the impact loading condition, and we explored the damage law of the gas to the coal body. In addition, the energy required for crack energy dissipation density (CEDD) is introduced to quantitatively characterize the relationship between energy dissipation and crack propagation.

Self-pulsing of dielectric barrier discharges at low driving frequencies

This paper investigates the self-pulsing of dielectric barrier discharges (DBDs) at low driving frequencies. In particular, (a) the dependence of current on the product pd of gas pressure p and the gas gap length d, (b) the effects of lossy dielectrics (in resistive discharges) and large dielectric permittivity (in ferroelectrics) on current dynamics, (c) the transition from Townsend to a dynamic capacitively coupled plasma (CCP) discharge with changing pd values, and (d) the transition from Townsend to a high-frequency CCP regime with increasing the driving frequency. A one-dimensional fluid model of argon plasma is coupled to an equivalent RC circuit for lossy dielectrics. Our results show multiple current pulses per AC period in Townsend and CCP discharge modes which are explained by uncoupled electron–ion transport in the absence of quasineutrality and surface charge deposition at dielectric interfaces. The number of current pulses decreases with an increasing applied frequency when the Townsend discharge transforms into the CCP discharge. The resistive barrier discharge with lossy dielectrics exhibits Townsend and glow modes for the same pd value (7.6 Torr cm) for higher and lower resistances, respectively. Finally, we show that ferroelectric materials can amplify discharge current in DBDs. Similarities between current pulsing in DBD, Trichel pulses in corona discharges, and subnormal oscillations in DC discharges are discussed.

Study on the Damage Mechanism of Coal under Hydraulic Load

Hydraulic fracturing is extensively utilized for the prevention and control of gas outbursts and rockbursts in the deep sections of coal mines. The determination of fracturing construction parameters based on the coal seam conditions and stress environments merits further investigation. This paper constructs a damage analysis model for coal under hydraulic loads, factoring in the influence of the intermediate principal stress, grounded in the unified strength theory analysis approach. It deduces the theoretical analytical equation for the damage distribution of a coal medium subjected to small-flow-rate hydraulic fracturing in underground coal mines. Laboratory experiments yielded the mechanical parameters of coal in the study area and facilitated the fitting of the intermediate principal stress coefficient. Leveraging these datasets, the study probes into the interaction between hydraulic loads and damage radius under assorted influence ranges, porosity, far-field crustal stresses, and brittle damage coefficients. The findings underscore that hydraulic load escalates exponentially with the damage radius. Within the variable range of geological conditions in the test area, the effects of varying influence range, porosity level, far-field stress, and brittle damage coefficient on the outcomes intensify one by one; a larger hydraulic load diminishes the impact of far-field stress variations on the damage radius, inversely to the influence range, porosity, and brittle damage. The damage radius derived through the gas pressure reduction method in field applications corroborates the theoretical calculations, affirming the precision of the theoretical model. These findings render pivotal guidance for the design and efficacy assessment of small-scale hydraulic fracturing in underground coal mines.

Low energy femtosecond pulsed laser ablation of Nd:YAG laser crystal in high-pressure oxygen and nitrogen background gas

A low-energy femtosecond (fs) pulsed laser was utilized to ablate the Nd:YAG laser crystal target in high-pressure oxygen (O2) and nitrogen (N2) background gases. Only minute amounts of neodymium (Nd), yttrium (Y), and aluminum (Al) were detected in the deposited material due to the thermalization resulting from low laser pulse energy and significant scattering caused by the high background gas pressure. We used a collision-based model and peak-fitting method of the angular distribution of the plume to explain the result. The collision-based model was used to explain and determine the probability distribution of the elements arriving from the target to the substrate. The magnitude of the probability distribution obtained with O2 background gas is higher as compared to N2 background gas owing to the former’s higher collision frequency. The peak-fitting method of the angular distribution of Nd, Y, and Al provided better approximations of the ratio of atoms arriving after ablation as compared to the collision-based model. Further improvements can be carried out to better predict the deposited material ratio.

Research on the Vibration Response Characteristics of PE Gas Pipeline Aimed for Third-Party Damage Monitoring

Third-party damage (TPD) incidents account for over 73% in China, becoming the primary cause of urban buried gas pipeline disruption. Therefore, real-time monitoring of TPD holds significance. This passage introduces a novel method for third-party damage monitoring of urban gas pipeline networks without excavation. The approach involves installing acoustic sensors in the pipeline to detect abnormal signals caused by construction activities. While the effectiveness of this method has been confirmed for buried steel pipelines, the propagation patterns, frequency characteristics, and the impact of fluid flow within PE pipelines remain unclear. To this end, this study explores these issues through experiments and simulations. According to the research, sound waves are the primary mode of signal propagation. The impact of gas pressure can be disregarded, but if the flow is reversed, the signal will weaken by 26%. The signal energy is concentrated in the 0-2kHz range, decreasing exponentially as the distance increases. Moreover, a positive linear correlation exists between the signal energy and the load size to the power of 0.1. This research provides theoretical support for studying third-party damage monitoring technology and identifying and localizing damage types.

Design and Analysis of Piston by using Ansys Workbench

Abstract: In this study, structural analysis is investigated on conventional piston made of cast iron. Secondly analysis are performed on piston made of aluminum, titanium alloy , structural steel and fiber glass. The material used for the design of piston should have light weight, low cost, structurally and thermally withstand at very high pressure and temperature condition that will occur in combustion process. In this project, It has been decide to study a particular piston design And its capability for maximum gas pressure. In this work, initial planning is to make piston model using solid modeling software CATIA V5. It has been decided to mesh the geometry analyze using ANSYS. For the analysis of piston input conditions and process of analysis, a lot of literature survey has been done. High combustion gas pressure will act as a mechanical loads and causes major stresses in the critical region of the piston. Detailed static structural analysis is carried out for various loading conditions like maximum gas pressure load.

PRODUCTION OF Ni-HARD ALLOY POWDERS BY GAS ATOMIZATION

Ni-Hard cast iron materials are frequently used in equipment where high wear resistance is required in industrial applications. Generally, Ni-Hard is produced by conventional casting techniques. In this study, it was aimed to produce Ni-Hard powders to produce Ni-Hard cast iron materials with additive manufacturing techniques. To produce spherical and fine raw materials for additive manufacturing techniques, the gas atomization technique with a close-coupled nozzle system was preferred for the production of Ni-Hard powders. Ni-Hard alloy was melted in a high-frequency 10kW induction furnace under a protective atmosphere integrated into the gas atomization system. During the atomization process, 150 °C superheating was applied to prevent the liquid metal from freezing and clogging the melt delivery tube. In terms of the continuity of the atomization process, the negative pressure (aspiration pressure) values formed at the end of the melt delivery tube at different gas pressures were measured. An aspiration pressure of -50 mbar was obtained under an atomization pressure of 35 bar. Particle size distributions, hall flow behaviour and angle of repose properties of the produced powders were determined. Finally, the characterization of the powders was carried out by scanning electron microscopy. It was determined that the powders obtained as a result of atomization exhibited a spherical morphology and a narrow size range. The Hall flow rate test result of Ni-Hard powders was measured as 22 seconds for 50 g.

Prediction Model of Coal Gas Permeability Based on Improved DBO Optimized BP Neural Network.

Accurate measurement of coal gas permeability helps prevent coal gas safety accidents effectively. To predict permeability more accurately, we propose the IDBO-BPNN coal body gas permeability prediction model. This model combines the Improved Dung Beetle algorithm (IDBO) with the BP neural network (BPNN). First, the Sine chaotic mapping, Osprey optimization algorithm, and adaptive T-distribution dynamic selection strategy are integrated to enhance the DBO algorithm and improve its global search capability. Then, IDBO is utilized to optimize the weights and thresholds in BPNN to enhance its prediction accuracy and mitigate the risk of overfitting to some extent. Secondly, based on the influencing factors of gas permeability, effective stress, gas pressure, temperature, and compressive strength, they are chosen as the coupling indicators. The SPSS 27 software is used to analyze the correlation among the indicators using the Pearson correlation coefficient matrix. Additionally, the Kernel Principal Component Analysis (KPCA) is employed to extract the original data. Then, the original data is divided into principal component data for the model input. The prediction results of the IDBO-BPNN model are compared with those of the PSO-BPNN, PSO-LSSVM, PSO-SVM, MPA-BPNN, WOA-SVM, BES-SVM, and DPO-BPNN models. This comparison assesses the capability of KPCA to enhance the accuracy of model predictions and the performance of the IDBO-BPNN model. Finally, the IDBO-BPNN model is tested using data from a coal mine in Shanxi. The results indicate that the predicted outcome closely aligns with the actual value, confirming the reliability and stability of the model. Therefore, the IDBO-BPNN model is better suited for predicting coal gas permeability in academic research writing.