State Of Gas Research Articles

Second-order Sobolev gradient flows for computing ground state of ultracold Fermi gases

Based on density functional theory, the ground state for ultracold Fermi gases with dipole–dipole interaction is a functional minimization problem with orthonormality constraints. Many methods such as direct minimization, self-consistent iteration method and first-order gradient flow had been proposed to solve such problem. In this paper, we introduce the second-order Sobolev gradient flows, solve them to the steady state and get the ground state of ultracold Fermi gases numerically. Two contributions have been made: firstly we extend the usual first-order gradient flows to the second-order gradient flows; secondly, we extend the usual L2 gradient to the Sobolev gradient and get the Sobolev gradient flows. We prove that the second-order Sobolev gradient flows have the properties of orthonormality preserving and ‘modified’ energy diminishing, which are desirable for the computation of the ground state solution. Several numerical techniques have been used to discretize the time-dependent second-order Sobolev gradient flows. These include explicit leap-frog method and stabilized semi-implicit method for temporal discretization and Fourier pseudo-spectral method for spatial variables. Extensive numerical examples for the ground state are reported to demonstrate the power of the numerical methods.

Огляд і бібліометричне дослідження надкритичних енергетичних циклів CO2. Поточний стан досліджень і розробок

Recent decades have been characterized by growing interest in research into improving the efficiency of these cycles. The purpose of this work is a bibliometric analysis based on Scopus data (2001-2024) and an overview of the main trends associated with supercritical cycles operating in the region of the carbon dioxide critical point. The objective is to provide a comprehensive overview of research productivity, impact, and trends in supercritical carbon dioxide cycling research over the past two decades, providing useful information for strategic research planning. The methods used were from the Scopus database due to its extensive collection of documents. The review of work lasted from 2001 to 2024, covering a significant time in this area. The literature search was conducted for the following specific keywords: “Supercritical”, “Cycle”, “Carbon dioxide”, “Equation of State”, “Energy Cycle”. The results show growing research interest in this area, which is mainly led by the United States, China, the United Kingdom, Canada, Italy, and Germany. Covering a variety of industries such as engineering, energy, and the environment, this research delves into technical areas such as supercritical carbon dioxide cycles and the real gas equation of state, which allow modeling of the flow of a working fluid in a compression loop. Conclusions. The bibliometric analysis presented in this work offers information on the evolution of research on supercritical carbon dioxide cycles and the equations of state of real gas in the metastable region of carbon dioxide from both academic and industrial viewpoints. By exploring the industry context and the relationships between the findings and the scope of key journals, this analysis illuminates the significance of the findings and their practical implications. New topics identified through keyword analysis can stimulate research planning in the scientific sector. Thus, this comprehensive bibliometric study serves as an independent reference for technology forecasting and monitoring.

Research on coal mine longwall face gas state analysis and safety warning strategy based on multi-sensor forecasting models

Intelligent computing is transforming safety inspection methods and response strategies in coal mines. Due to the significant safety hazards associated with mining excavation, this study proposes a multi-source data based predictive model for assessing gas risk and implementing countermeasures. By examining the patterns of gas dispersion at the longwall face, utilizing both temporal and spatial correlation, a predictive model is crafted that incorporates safety thresholds for gas concentrations, four-level early warning method and response strategy are devised by integrating weighted predictive confidence with these correlations. Initially tested using a public dataset from Poland, this method was later verified in coal mine in China. This paper discusses the validity and correlation of multi-source monitoring data in temporal and spatial correlation and proposes a risk warning mechanism based on it, which can be applied not only for safety warning but also for regulatory management.

Composite 2D Material-Based Pervaporation Membranes for Liquid Separation: A Review.

Today, chemistry and nanotechnology cover molecular separations in liquid and gas states by aiding in the design of new nano-sized materials. In this regard, the synthesis and application of two-dimensional (2D) nanomaterials are current fields of research in which structurally defined 2D materials are being used in membrane separation either in self-standing membranes or composites with polymer phases. For instance, pervaporation (PV), as a highly selective technology for liquid separation, benefits from using 2D materials to selectively transport water or other solvent molecules. Therefore, this review paper offers an interesting update in revising the ongoing progress of PV membranes using 2D materials in several applications, including solvent purification (the removal of water from organic systems), organics removal (the removal of organic molecules diluted in water systems), and desalination (selective water transport from seawater). In general, recent reports from the past 3 years have been discussed and analyzed. Attention has been devoted to the proposed strategies and fabrication of membranes for the inclusion of 2D materials into polymer phases. Finally, the future trends and current research gaps are declared for the scientists in the field.

Release of high-pressure hydrogen from type III tank in a fire scenario: Analysis and prediction of jet flame length and thermal response characteristics

In this paper, the thermal response and jet flame behaviour of a typical type III high-pressure hydrogen storage tank with nominal working pressure (NWP) and volume of 70 MPa and 48 L were analysed at fire scenarios. The tank was discharged at a critical internal pressure 77.4 MPa, which was ca. 110 % of NWP. The pressure drop rates of type III tanks were greater than 1 MPa/s during the initial 15 s after venting. The length and width of jet flame were 4.93 and 1.65 m at the critical moment, which fluctuated downward over time. A thermokinetic model was employed to predict the variation of hydrogen gas state parameters and the maximum length of jet flame. The calculation results indicated that the maximum flame length of hydrogen released from a valve of 2 mm was around 2–6.5 m under a pressure range of 10–80 MPa. The error between the predicted results and the experimental values was less than 5 %. It was found that the flame length was enlarged by an increase of aperture. The length of flame increased by 6 m after the aperture changed from 2 to 5.08 mm at the equivalent pressure.

Rheology of granular particles immersed in a molecular gas under uniform shear flow.

Non-Newtonian transport properties of a dilute gas of inelastic hard spheres immersed in a molecular gas are determined. We assume that the granular gas is sufficiently rarefied, and hence the state of the molecular gas is not disturbed by the presence of the solid particles. In this situation, one can treat the molecular gas as a bath (or thermostat) of elastic hard spheres at a given temperature. Moreover, in spite of the fact that the number density of grains is quite small, we take into account their inelastic collisions among themselves in its kinetic equation. The system (granular gas plus a bath of elastic hard spheres) is subjected to a simple (or uniform) shear flow. In the low-density regime, the rheological properties of the granular gas are determined by solving the Boltzmann kinetic equationby means of Grad's moment method. These properties turn out to be highly nonlinear functions of the shear rate and the remaining parameters of the system. Our results show that the kinetic granular temperature and the non-Newtonian viscosity present a discontinuous shear thickening effect for sufficiently high values of the mass ratio m/m_{g} (m and m_{g} being the mass of grains and gas particles, respectively). This effect becomes more pronounced as the mass ratio m/m_{g} increases. In particular, in the Brownian limit (m/m_{g}→∞) the expressions of the non-Newtonian transport properties derived here are consistent with those previously obtained by considering a coarse-grained approach where the effect of gas phase on grains is through an effective force. Theoretical results are compared against computer simulations, showing an excellent agreement.

Multi-objective Bayesian active learning for MeV-ultrafast electron diffraction

Ultrafast electron diffraction using MeV energy beams(MeV-UED) has enabled unprecedented scientific opportunities in the study of ultrafast structural dynamics in a variety of gas, liquid and solid state systems. Broad scientific applications usually pose different requirements for electron probe properties. Due to the complex, nonlinear and correlated nature of accelerator systems, electron beam property optimization is a time-taking process and often relies on extensive hand-tuning by experienced human operators. Algorithm based efficient online tuning strategies are highly desired. Here, we demonstrate multi-objective Bayesian active learning for speeding up online beam tuning at the SLAC MeV-UED facility. The multi-objective Bayesian optimization algorithm was used for efficiently searching the parameter space and mapping out the Pareto Fronts which give the trade-offs between key beam properties. Such scheme enables an unprecedented overview of the global behavior of the experimental system and takes a significantly smaller number of measurements compared with traditional methods such as a grid scan. This methodology can be applied in other experimental scenarios that require simultaneously optimizing multiple objectives by explorations in high dimensional, nonlinear and correlated systems.

A novel automatic Siamese neural network for hyperspectral image classification

Hyperspectral image is gradually becoming the main medium in satellite observations. It provides rich spectral information of different channels to help explore various gas states. Its classification problem is among the most significant tasks on the hyperspectral image processing and application. But the classification often faces the difficulty of imbalanced data and differentiated intra-class/inter-class difference. A lot of deep learning methods have attempted to solve this problem by designing different kinds of networks, but they suffer from the query of whether the network is optimal. This paper provides an automatically framework to deal with the above problem. First of all, we introduced siamese framework to reduce the impact of imbalanced data and various intra-class/inter-class difference. Then, we designed a multi-branch search space with several convolutional operators, especially a gradient-based updating rules to search the architecture. After using ”time [Formula: see text] performance” criterion, we obtain the model on two public hyperspectral image dataset. The experimental results outperformed all other compared algorithms.

Variation of the stellar initial mass function in semi-analytical models

Context. In our previous work, we derived the CR-IGIMF, which is a new scenario for a variable stellar initial mass function (IMF) that combines numerical results on the role played by cosmic rays (CR) in setting the thermal state of star-forming gas with the analytical approach of the integrated galaxy-wide IMF (IGIMF). Aims. In this work, we study the implications of this scenario for the properties of local early-type galaxies (ETG) as inferred from dynamical, photometric, and spectroscopic studies. Methods. We implemented a library of CR-IGIMF shapes in the framework of the galaxy evolution and assembly (GAEA) model. GAEA provides predictions for the physical and photometric properties of model galaxies and for their chemical composition. Our realization includes a self-consistent derivation of the synthetic spectral energy distribution for each model galaxy, which allows a direct derivation of the mass fraction in the mean IMF of low-mass stars (i.e., the dwarf-to-giant ratio, fdg) and a comparison with IMF-sensitive spectral features. Results. The predictions of the GAEA model implementing the CR-IGIMF confirm our previous findings: It correctly reproduces both the observed excess of z ∼ 0 dynamical mass (mass-to-light ratio) with respect to spectroscopic (photometric) estimates assuming a universal MW-like IMF, and the observed increase in [α/Fe] ratios with stellar mass in spheroidal galaxies. Moreover, this realization reproduces the increasing trends of fdg and IMF-sensitive line strengths with velocity dispersion, although the predicted relations are significantly shallower than the observed ones. Conclusions. Our results show that the CR-IGIMF is a promising scenario that reproduces at the same time dynamical, photometric, and spectroscopic indications of a varying IMF in local ETGs. The shallow relations found for spectral indices suggest that either a stronger variability as a function of galaxy properties or additional dependences (e.g., as a function of star forming gas metallicity) might be required to match the strength of the observed trends.

Research on ultra-sensitive gas refractive index sensing technology based on double cavity matching in batteries

An ultrasensitive refractive index sensor for measuring the refraction index of gas inside the battery is proposed and demonstrated. The theoretical model of ultrasensitive parallel Fabry-Pérot interferometer (PFPI) is established, and the sensitivity amplification mechanism of the PFPI is analyzed in details. According to the matching conditions of optical path, a prefect matching scheme for measuring the refractive index of gas inside the battery is designed, and an ultra-high sensitivity gas refractive index sensor is fabricated. The sensitivity of the sensor is calibrated accordingly, and a preliminary test carried out inside the battery. The experimental results obtained show that the matching method realizes an ultra-high gas refractive index sensitivity of −120506.046 nm/RIU, and the amplification sensitivity is up to 78 times, and it has good response in detecting the gas state inside the cell, and can effectively detect the gas precipitation inside the cell, which can effectively, directly and in real time reflect the internal state of the battery. This technique of direct detection without the aid of other media has potential theoretical significance and practical application value in the field of gas precipitation detection in batteries.

Analyses of gas pulsation characteristics in the discharge pipeline of a hyper compressor

For the analysis of gas pulsation characteristics in the pipeline systems of low density polyethylene (LDPE) hyper compressors, a time-domain calculation method for compressor pipeline gas pulsation based on real gas properties is proposed. First the thermophysical property tables are prepared with gas state parameters as independent and dependent variables. Then one-dimensional unsteady flow equations and characteristic equations for pipeline flow are established based on real gas properties. After setting pipeline parameters and boundary conditions, the flow equations are discretized using a two-step method at the inner points of the pipeline. The characteristic equations are discretized using the trapezoidal integration method at the boundary points. Thus, the time-domain solving of pulsating flow field in the pipeline is realized. A self-developed numerical code was used to conduct the time-domain calculation and analysis of gas pulsation in the discharge pipeline of a two-stage hyper compressor. The calculated pressure pulsation curves based on real gas properties are in good agreement with experimental data, with a maximum difference lower than 4% of the local average pressure, which is smaller than the difference between the results calculated based on the plane wave theory and the measured data. The analysis of gas pulsation characteristics shows that the pressure pulsation in the main pipeline is mainly contributed by the fundamental and second harmonics. The pressure pulsation in the safety valve branch is higher than that in the main pipeline, and the harmonic components falling into the acoustic resonance frequency range of this branch have significant amplitudes. The acoustic resonance frequency of the branch pipeline is not affected by the main pipeline. Pressure pulsation varies with changes in rotational speed and back pressure, and the pulsation level is more significantly affected by rotational speed compared to back pressure. The renovation scheme of connecting the safety valve branch and expansion tube in series can effectively reduce the pressure pulsation levels of the main pipeline and branch pipeline.

Modeling and Simulation of a Gas-Exhaust Design for Battery Thermal Runaway Propagation in a LiFePO4 Module

The release of flammable gases during battery thermal runaway poses a risk of combustion and explosion, endangering personnel safety. The convective and diffusive properties of the gas make it challenging to accurately measure gas state, complicating the assessment of the battery pack exhaust design. In this paper, a thermal resistance network model is established, which is used to calculate the battery thermal runaway propagation. Gas accumulation after thermal runaway venting of a LiFeO4 module is studied using ANSYS Fluent under different venting schemes. The results show that the scheme of battery inversion and simultaneous exhaust from the side and bottom of the module is optimal. The methods and results presented can guide the design of LiFeO4 cell pack runners.

Study on the mechanism of methane “solid–liquid–gas” conversion controlled by the evolution of coal micro- and nanopore structure

Currently, the utilization of coalbed methane resources in the Guizhou region faces challenges such as complex reservoir structure, high gas content, and microporous development. Based on these, the pore structure and adsorption capacity of Guizhou tectonic deformed coals (TDCs) were evaluated using a suite of integrated diagnostic techniques including low-temperature nitrogen adsorption (LT-N2A), mercury intrusion porosimetry (MIP), methane isothermal adsorption. Through the above methods, the pore structure and adsorption characteristics of the samples were characterized; The samples were divided into the range of joint pores by combining the results of MIP and LT-N2A; Using the molecular simulation software, the 2 nm, 4 nm, 10 nm pores affecting the methane endowment state were investigated respectively, and from the perspective of the heat of adsorption and energy, the concept of the three-phase transition of methane was proposed, and explore the change of the pore spacing affecting the endowment state of methane from the solid state pore to the gas state pore. The results provide new ideas for the in-depth study of gas storage in tectonic coal reservoirs in Guizhou Province.

Spin–orbit-coupled Bose gas with Rydberg interactions confined in a two-dimensional optical lattice

We consider the ground state of Rydberg-dressed Bose gas with spin–orbit coupling and confined in a two-dimensional optical lattice. The effects of system’s parameters, especially the nonlocal Rydberg interaction and spin–orbit coupling, on the ground-state structure of such a system are explored in full parameter space. It is found that in the absence of spin–orbit coupling, the ground-state structure of the system changes from the initial optical lattice structure to a two-dimensional periodic one with the cell size decreasing with the strength of Rydberg interaction. In the presence of spin–orbit coupling, both the phase and the internal structure of unit cell show strong dependence on the strength of spin–orbit coupling. Finally, the strong interacting gas is also considered.

2023 Development and production review

Geopolitical uncertainty remained high in 2023 with Israeli actions in the Gaza strip, the continuing war in Ukraine and tension between China and several neighbouring countries. However, global inflationary pressures, surprisingly, eased during the year, and the prospect of a global recession faded from where it had been in 2022. In Australia continued activism around climate change issues, has impacted project developments and sentiment in the industry remained subdued. This paper looks back at the oil and gas production and development activities in Australia in 2023 providing historical context and trying to understand future implications for the industry. Liquefied natural gas (LNG) production in Australia remained close to record high levels although, not without problems. Both the Scarborough/Pluto 2 LNG project and the Barossa project continued to have legal and approval hurdles resulting in suspension of some execution activities. Elsewhere other projects continued with their plans, including the Kipper field in the Gippsland Basin, the Crux project in the Browse Basin and the Walyering project in the Perth Basin which was brought online in September 2023. The domestic markets also continued to have unique issues with major concerns about gas supply in the East, stalled developments and failing supply in the Northern Territory, and a renewed ban on any exports (including to other states) of gas from Western Australia.

A transient gas pipeline network simulation model for decoupling the hydraulic-thermal process and the component tracking process

The metering mode is gradually changing from volumetric metering to energy metering under the open-access operation of gas pipelines. The gas component tracking by operating simulation is an effective method to realize the energy metering of gas networks. In this paper, coupling and decoupling transient component tracking models of gas networks are proposed. The pipeline governing equations, compressor equations, valve equations, and node relationship equations are considered in the proposed models. The implicit central difference method and the damped Newtonian method are adopted to solve the models. The coupling model considers the component tracking part and hydraulic-thermal simulation as a whole, while the decoupling model splits the whole process into the gas component tracking part, the parameters calculation part, and the hydraulic-thermal simulation part. In the component tracking part, the spatiotemporal variation of the gas mass fraction and density can be obtained through the input velocity of each node. Then, the parameters in the gas state equation can be solved, the hydraulic-thermal simulation can be performed, and the new velocity of each node can be calculated. The iteration for each time step ends if the deviation of flow velocity in the component tracking process and the hydraulic-thermal process satisfies the requirements. Two cases are studied to verify the effectiveness of the proposed models, and the boundary condition adaptability of the transient simulation models is analyzed. The proposed models can efficiently simulate the spatiotemporal variation of the operating variables and gas components, providing a reference in the operation of natural gas pipeline networks.

An ultra-sensitive optical H2S sensor based on thermal conversion combined with UV-DOAS: Dynamic detection from ppm to ppb level

Hydrogen sulfide (H2S) as a common gas plays an important role in both industrial production and clinical pathology. Therefore, the realization of dynamic detection of trace H2S gas is of great significance. In this paper, an ultra-sensitive optical H2S sensor based on thermal conversion and ultraviolet differential optical absorption spectroscopy (UV-DOAS) is developed for dynamic measurement of H2S concentration. The H2S concentration can be derived from the measurement of the change in sulfur dioxide (SO2) concentration before and after conversion. First, the evaluation method of SO2 concentration based on UV-DOAS is presented, and the performance indicators of SO2 concentration measurement are given. Second, the conversion characteristics of H2S under different temperatures and flow rates are investigated, and H2S can be efficiently converted to SO2 in the flowing gas state by controlling the conversion conditions. Finally, the performance indicators of H2S sensor are evaluated. The sensor realizes H2S measurements with a detection limit of 14 ppb * m, while its sensitivity and reliability of measuring H2S concentration increase tenfold, making it suitable for dynamic measurements of trace H2S. In addition, the feasibility of the sensor for applications in atmospheric monitoring and human exhaled breath detection is demonstrated by practical tests.

Analysis of the flow and thermal-fluid–solid coupling of crude oil in circular pipe caused by variable pressure gradient

Abstract Globally, enhanced oil recovery (EOR) has become a pressing issue as the demand for crude oil continues to increase. This study investigates the flow and thermal-fluid–solid coupling of crude oil in a rod pump during hot water recovery and obtains the maximum recovery of crude oil in a vertical pipeline through numerical analysis. The pressure gradient in the pump barrel was first developed and deduced based on the ideal gas state equation and Bernoulli’s equation. According to the rheological experiment results, it was proven that the light crude oil conforms to the Newtonian constitutive equation. Subsequently, the momentum equation of crude oil flowing in the pipeline and fluid–solid coupling heat transfer equations were established and solved using the finite difference method. The effects of the thermal recovery temperature T w , wall thickness c, and stroke time n of the rod pump on flow Q are discussed. In particular, the flow Q within 1 min first increases and then slows down with the increase in stroke time n and reaches its maximum value at n = 7 r/min. Furthermore, flow Q decreases with an increase in c but increases as T w increases; c = 1.2 cm, T w = 363 K is the best oil recovery scheme.

Transferable Anisotropic Mie Potential Force Field for Alkanediols.

The development of force fields for polyfunctional molecules, such as alkanediols, requires a careful account of different average intramolecular conformations for gas states compared to dense liquid states, where intra- and intermolecular hydrogen bonds compete. In the present work, the transferable anisotropic Mie (TAMie) potential is extended to 1,n-alkanediols. Using the convention that intramolecular nonbonded interactions up to and including the third neighbor are excluded, all force field parameters developed previously for 1-alcohols were transferred to 1,5-pentanediol and beyond, with good agreement with experimental phase equilibrium data. To obtain trans-gauche ratios of 1,2-ethanediol and 1,3-propanediol that are consistent with experimental results, the propensities for intra- and intermolecular hydrogen bonds had to be balanced. This was achieved by parameterizing the intramolecular dihedral energy functions governing the O-C-C-O and O-C-C-C angles while intramolecular charge-charge interactions were active. All partial charges belonging to a functional group are collected in a charge group and all interactions among two charge groups are evaluated even if they are separated by less than three bonds. With this approach, it is possible to apply the nonbonded parameters from 1-alcohols to alkanediols without further refinement. The agreement with experimental phase equilibrium and shear viscosity data is of similar quality as for the 1-alcohols and the trans-gauche ratio agrees with literature results from spectroscopic measurements and ab initio calculations.

A Reduced Kinetics Model for the Oxidation of Transcritical/Supercritical Gasoline Surrogate/Ethanol Mixtures Using Real Gas State Equations

ABSTRACT Efforts to combat the harmful effects of vehicle emissions on our environment and health include exhaust emissions and fuel efficiency regulations. One promising solution is direct fuel injection in supercritical conditions, where the fuel mixture is above critical temperature and pressure. This study presents a reduced kinetics mechanism (129 species and 1015 reactions) utilizing real gas equations to simulate the combustion of supercritical/transcritical gasoline surrogate/ethanol blends. It was developed by combining two reduced models – a Toluene reference fuel (TRF) with a Diisobutylene (DIB) and an ethanol model – and validated through simulations of ignition delay time (IDT). The Arrhenius parameters of key reactions for each fuel component were modified to improve accuracy. An adjusted Redlich-Kwong cubic state equation was employed to segregate each surrogate mixture tested as supercritical, transcritical, or subcritical. The new mechanism was then validated against experimental results using high-pressure conditions and the cubic Peng-Robinson and Redlich-Kwong equation of state parameters. Critical properties of each species were obtained through Joback’s Group Method and the Ambrose-Walton vapor pressure equation. The TRF/DIB/E mechanism results were consistent with shock tube experimental data at high pressure, indicating a potential for modeling combustion in ultra-high pressure direct injection engines.