Concentrations Of Gas Components Research Articles

Analysing the Impact of Second Gas Component on Pulse Pirani Gauge

Abstract This numerical study investigates the influence of a second gas component concentration on Pirani gauge readings. The analysis aims to provide insights into how the presence of additional gas components affects the accuracy and reliability of Pirani gauge measurements. By simulating different gas mixtures and examining the resulting readings, this study sheds light on the complex interactions between gases in Pirani gauge applications.

Multi-pass Cavity-Enhanced Raman Spectroscopy of Complex Natural Gas Components

BackgroundThe concentration of natural gas components significantly impacts the transportation, storage, and utilization of natural gas. Consequently, implementing online monitoring and leak detection systems is vital to guarantee the efficient use of natural gas and to uphold its safe and stable operation. Raman spectroscopy offers distinctive benefits, including high selectivity, superior precision, and the capability to detect multiple gas components simultaneously using a single-wavelength laser. Nevertheless, the inherent weakness of the Raman effect in gases results in limited detection sensitivity for Raman spectroscopy, which may not suffice for specific practical applications. ResultsThis paper presents a study investigating the detection of natural gas's complex components using a high-sensitivity multi-cavity enhanced Raman spectroscopy technique. An enhanced folded Z-shaped multi-pass cavity has been constructed to amplify the interaction length between the laser and the gas, thereby significantly boosting the Raman signal intensity by 1000 times. The detection limits for CH4, C2H6, C3H8, n-C4H10, i-C4H10, n-C5H12, i-C5H12, and n-C6H14 gases reached 0.12, 0.53, 0.55, 0.67, 0.28, 0.46, 0.34, and 0.71 ppm, respectively. The least squares method was utilized to establish quantitative relationships between the characteristic peak heights and the concentrations of gases, encompassing both single-component and mixed multi-component systems. Additionally, the natural gas samples were configured and subsequently detected and analyzed. SignificanceAs proposed in this paper, the results indicate that the MPC-CERS system boasts several advantages, including a low detection limit, high quantitative accuracy, excellent detection repeatability, and robust system stability. Furthermore, its capability for real-time monitoring is well-suited to meet the gas detection requirements in practical applications. Consequently, the research presented in this paper offers innovative insights for the online tracking and leak detection of distributed energy natural gas systems.

OIL AND GAS RESERVOIR CHARACTERISATION OF ALTYGUYI DEPOSIT, TURKMENISTAN BASED ON PROPERTY ASPECTS AND PRODUCTION RESULTS

This study investigated the geological structure and hydrocarbon potential of the Altyguyi field, Turkmenistan using advanced analytical techniques to optimise future extraction strategies. An in-depth analysis was performed on the geological structure and hydrocarbon production potential of the oil and gas reservoirs. An integrated approach combined geochemical, geophysical and drilling data analyses. Petroleum component analysis identified diverse compounds such as asphaltenes, resins, paraffins and sulphur, indicating the field developmental potential. Geochemical analysis delineated gas and oil component concentrations across various geological formations. Hydrochemical studies of reservoir water established its nature and origin, crucial for assessing production capabilities and environmental impacts. A methodological approach was developed to utilise isotherm creation and estimate condensate content in gas reservoirs, proving valuable for forecasting and optimising production processes. The study confirmed significant hydrocarbon deposits in the Altyguyi field, highlighting its high production potential and promising development outlook. These insights are essential for devising optimal production strategies and managing oil, gas and condensate extraction effectively.

Mathematical Modelling of Hydrogen-Enriched Combustion

This article presents a mathematical model developed in ANSYS CFX 17.2 software to analyse the combustion process of hydrogen-enriched natural gas. The study investigates the concentrations of various flue gas components at hydrogen enrichments of 10% and 20%, compared to a baseline of pure natural gas. A three-dimensional model of the experimental setup was created allowing for detailed simulation of combustion dynamics under controlled conditions. The model incorporates the governing equations for mass conservation, momentum, energy, and turbulence, facilitating comprehensive analysis of combustion behaviour and pollutant formation. The simulations reveal that increased hydrogen enrichment raises combustion temperatures but also leads to higher carbon monoxide (CO) emissions due to incomplete combustion. The results indicate a corresponding decrease in carbon dioxide (CO₂) emissions, showcasing the environmental implications of hydrogen mixing. However, nitrogen oxide (NOx) emissions increase significantly with higher combustion temperatures. The mathematical model was validated against experimental data, demonstrating less than 10% deviation in temperature measurements and providing accurate predictions for pollutant concentrations.

Comparative Study on the Vertical Column Concentration Inversion Algorithm of Tropospheric Trace Gas Based on the MAX-DOAS Measurement Spectrum

The tropospheric vertical column concentration (VCDtrop) of NO2, SO2, and HCHO was retrieved, respectively, by employing the geometric method (Geomtry), simplified model method (Model), and look-up table method (Table) with the observation spectra of the multi-axis differential absorption spectroscopy instrument (MAX-DOAS). The correlation and relative differences of the inversion results obtained by these three algorithms, as well as the changes in quantiles, were explored. The comparative analysis reveals that the more concentrated the vertical distribution height of gas components is in the near-surface layer, the better the conformity of the VCDtrop retrieved by different algorithms. However, the increase in relative differences is also related to the diurnal variation of gas components. The influence of aerosols on the inversion of the VCDtrop is greater than the change in the vertical distribution height of the gas component itself. The near-surface concentration and distribution height of gas components are the internal factors that give rise to relative differences in the inversion of the VCDtrop by different algorithms, while aerosols are one of the extremely important external reasons. The VCDtrop inverted by Geomtry without considering the influence of aerosols is generally larger except for NO2. Model sets up aerosols in accordance with the height and meteorological conditions of the atmospheric environment. Table can invert the aerosol profile in real time. Compared with Model, it shows a significant improvement in the refined setting of aerosols. Moreover, while obtaining the vertical distribution of aerosols, it can invert the diurnal variation of the VCDtrop. The VCDtrop inverted by Table is the smallest, and the relative difference with Model is on average about 10% smaller. The relative difference of the VCDtrop for the same height (aerosol optical thickness) quantile is 7–15% (about 25% lower on average). When comparing the inversion results of Table with the Ozone Monitoring Instrument (OMI) satellite product, the MAX-DOAS inversion results of NO2, SO2, and HCHO are all larger than the OMI product. This is related to the different observation methods of the MAX-DOAS and OMI and the configuration between the aerosol layer and the distribution height of gas components.

AI-based data mining approach to control the environmental impact of conventional energy technologies

Environmental pollution remains one of the foremost existential threats to human well-being, despite the concerted efforts and implementation of various programmes aimed at fostering cleaner air. The contemporary global economic and energy landscape, characterised by multifaceted challenges, has undeniably hindered the efficacy of efforts to kerb air pollutant emissions. Solid fuels persist as primary sources of energy production in numerous countries, serving both the residential and industrial sectors. However, combustion of such fuels, particularly within domestic heating units (DHUs), engenders the release of a diverse array of organic compounds characterised by intricate structures and potent mutagenic and environmentally hazardous properties.However, the combustion process, if properly regulated, can be carried out in an environmentally sustainable manner. The intricate interplay of myriad factors that influence the composition and quality of chimney flue gases underscores the complexity inherent in controlling the combustion process. Artificial intelligence (AI) has emerged as a versatile tool with applications that span various domains, including environmental monitoring systems. In this study, we posit the utilisation of artificial neural networks (ANNs) as a sophisticated data mining technique to control the emission of flue gases contingent on the specific boiler and fuel utilised. Feed forward predictive models with back propagation were utilized for AI-based data mining aiming at the prediction of the concentration of flue gas components. The highest coefficients of model fit goodness were obtained for CO2, NOx and SO2 with R2 equal to 0.99, 0.98 and 0.99, respectively. The study demonstrated the feasibility and effectiveness of using AI-based data mining to predict emissions from conventional energy technologies. By leveraging the predictive capabilities of ANNs, it is possible to significantly reduce the environmental impact of solid fuel combustion, contributing to cleaner air and improved public health.

Thermodynamic simulation of hydrogen production from the nano-CaO reactive sorption enhanced biomass steam reforming

Based on the principles of thermodynamic reaction equilibrium, a simulation method enhanced by the nano-CaO reactive sorption CO2 for hydrogen production from biomass steam reforming has been established. MATLAB R2022b software has been utilized to calculate the composition concentration of the product gas. Detailed simulations have been conducted to understand the changes in gas component concentration and yield under various reaction conditions, includes temperatures, steam to biomass (S/B) molar ratios, and CaO to carbon (CaO/C) molar ratios. The result demonstrated that temperature plays a significant role in both the concentration and yield of hydrogen. At an optimal reaction temperature of 650 °C, the concentration of H2 in the product reaches 77% (S/B = 2 and CaO/C = 0.5). S/B molar ratio over 2 is necessary to increase the H2 concentration. The study also reveals CaO/C molar ratio 0.5 enable successful removal of CO2 generated by reaction. The application of nano-CaO notably enhanced the efficiency of hydrogen production from biomass steam reforming, leading to a 25% increase in H2 concentration and a boost in H2 yield to 50 mL/gBiomass, and reaction temperature decrease 200 °C compared to the case without CaO.

Experimental study of gas composition in the equilibrium state of a light alkane combustion reaction

Oil field-associated gas is typically a mixture of light alkanes. To ensure production safety, it is essential to investigate the combustion characteristics and the reaction mechanism of light alkane gas mixtures to uncover the underlying mechanisms of the combustion reaction. This paper investigates the equilibrium gas component concentrations resulting from the reaction of a gas mixture of methane, ethane, and propane at specific ratios through experimental tests. The study's results demonstrate that the equilibrium concentrations of methane, ethane, and propane initially decrease and then increase with the rise of the equivalence ratio under the same initial pressure conditions. In oxygen-poor conditions, the equilibrium concentration ratio of methane gradually increases in proportion to the equilibrium ratio, confirming that ethane and propane are the preferred participants in the reaction. Furthermore, a study of the equilibrium concentration of the critical intermediate product, ethylene, revealed that it does not completely oxidize in the combustion reaction. It can persist under both oxygen-rich and oxygen-poor conditions, with an equilibrium concentration of approximately 0.02%. The findings of this paper can serve as a theoretical supplement to the research on explosive gas combustion and explosions.

Numerical simulation of altering the raw meal inlet position in a novel swirl precalciner

Conducted a numerical simulation to model a novel swirl precalciner, investigating how altering in the position of the raw meal inlet affects the internal gas flow, temperature field, and component concentration field within the precalciner. Applied the Realizable k-? two-equation turbulent model to the continuous phase. For the particle phase (pulverized coal), employed the Discrete Particle Model and the discrete random walk model. Simulated the combustion of pulverized coal and the decomposition of calcium carbonate by using the Species Transport model combined with the Finite-Rate/Eddy-Dissipation model. Modeled the generation of NOx using a NOx model. The results show that, in comparison to the condition with four raw meal inlets, the six raw meal inlets condition has a better coupling of pulverized coal combustion and raw meal decomposition. The decomposition rate of raw meal has seen a slight improvement, and there is a significant improvement in the occurrence of localized high temperatures within the precalciner, resulting in a reduction of the outlet NOx concentration from 1251 ppm to 225 ppm.

Methanol infrared spectral characteristics in offshore gas logging

Methanol infrared spectral characteristics in offshore gas logging. Methanol was found in the logging gases during offshore gas logging by infrared spectra. Logging gas spectra from over 300 offshore wells and 1,000 onshore wells were processed and analyzed, and methanol characteristics were prevalent in the offshore logging gases but not onshore logging gases. The spectra of instruments Alpha111829 and Alpha111834 are studied as examples. The methanol concentrations in some areas exceeded 1 vol%, seriously interfering with the other measurements of alkane gases. Moreover, there are rapid changes in the trends of methanol concentrations. It indicates that methanol does not originate from drilling fluid additives. The results of the correlation analysis show that there are no strong correlations between methanol and the other logging gas component concentrations. Therefore, methanol may be neither a judgmental indicator component gas for natural gas nor oil but a separate energy source. We believe methanol in the offshore logging gases originates from strata. The discovery and analysis of methanol in offshore logging gases are significant in atmospheric and marine environments, oil and gas exploration, geochemistry, and energy.

Experimental study on the displacement effect and inerting differences of inert gas in loose broken coal

The pre-injection of inert gas before coal self-ignition is a common key measure for preventing and controlling spontaneous coal combustion in a goaf. Previous studies have mainly considered inerting to reduce the concentration of ambient gas components and explored the influence of oxygen or inert gas concentration on the inerting effect of loosely broken coal, but seldom considered the replacement of oxygen by an inert gas, especially the replacement of adsorbed oxygen. Here, we quantitatively investigated the difference in room-temperature inerting of loosely broken coal by N2 and CO2 by conducting one-factor experiments on replacing oxygen in coal with an inert gas at room temperature and pressure. The results reveal that the replacement process can be divided into three stages and that the different adsorption capacities of coal for N2 and CO2 are the main reasons for the asynchrony of each replacement stage. The stronger the adsorption capacity, the stronger the displacement of adsorbed oxygen in the adsorbed state by the inert gas. CO2 exhibits an inerting strength 2.3–2.6 times higher than N2 and 5.7–8.8 times higher than He. The experiments also revealed that optimizing the key parameters of inert fire protection technology should consider the adsorption effect.

Study of the effectiveness of diagnostic method for respiratory system diseases by analyzing the exhaled air using a gas analytical complex

Aim: To study in patients the dependence of the exhaled air composition on pathological processes occurring in the respiratory system, including: lung cancer, community-acquired pneumonia and COVID-19.Material and Methods. The studies were carried out on the basis of a gas analytical complex using the method of neural network data analysis. The gas analytical complex includes semiconductor sensors that measure the concentrations of gas components in exhaled air with an average sensitivity of 1 ppm. Based on signals from sensors, the neural network classifies and identifies patients with certain pathological processes.Results. The statistical data set for training the neural network and testing the method included samples from 173 patients. Our study collected exhaled air samples from groups of patients with lung cancer, pneumonia, and COVID-19. In the case of lung cancer, the parameters of the diagnostic device have been determined at the level of sensitivity – 95.24%, specificity – 76.19%. For pneumonia and COVID-19, these parameters were 97.36% and 98.63, respectively.Conclusion. Taking into account the known value of diagnostic methods such as computed tomography (CT) and magnetic resonance imaging (MRI), the sensitivity and specificity indicators of the gas analytical complex achieved during the study reflect the promise of the proposed technique in the diagnosis of tumor processes in patients with lung cancer, COVID-19 and community-acquired pneumonia.

Research on an Ultraviolet Spectral Denoising Algorithm Based on the Improved SVD Method

The utilization of ultraviolet (UV) absorption spectroscopy for monitoring the concentration of specific decomposition gas components in gas-insulated switchgear (GIS) can provide a means to assess its insulation status. Nevertheless, UV optical modules currently deployed in the field are susceptible to external interferences like ambient noise and equipment vibrations. Real-time spectral data acquisition often suffers from significant noise contamination, directly impinging on subsequent feature extraction and detection accuracy. This paper presents an optimized singular value decomposition (SVD) noise reduction method for mitigating noisy spectral signals. First, each singular value within the noisy signal is transformed into a component signal. Next, the highest frequency value in the signal serves as an indicator to characterize the signal. Finally, the primary frequency values are arranged based on the decreasing singular values of the original noisy signal. The singular value corresponding to the first primary frequency value surpassing a preset threshold is selected as the effective order for denoising. Random noise with varying intensities was intentionally introduced to the UV spectral signal of sulfur dioxide (SO2), followed by noise reduction procedures. It is shown that the improved SVD noise reduction algorithm proposed in this paper enhances the signal-to-noise ratio (SNR) by 18.02% and 16.86%, and reduces the root-mean-square error (RMSE) by 15.13% and 14.92%, respectively, compared with the singular value difference spectrum (SVDS) denoising method and wavelet transform denoising method under the condition of low SNR. Furthermore, there exists a linear relationship between the concentration of SO2 samples and the eigenvalues of the UV spectra, demonstrating a higher linear goodness with a coefficient of 0.99735. The denoising method proposed in this paper does not require the manual setting of various types of parameters, and has a better ability to deal with the noise of UV spectral signals in engineering sites with complex environments.

Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements.

We report on the use of quartz-enhanced photoacoustic spectroscopy (QEPAS) for multi-gas detection. Photoacoustic (PA) spectra of mixtures of water (H2O), ammonia (NH3), and methane (CH4) were measured in the mid-infrared (MIR) wavelength range using a mid-infrared (MIR) optical parametric oscillator (OPO) light source. Highly overlapping absorption spectra are a common challenge for gas spectroscopy. To mitigate this, we used a partial least-squares regression (PLS) method to estimate the mixing ratio and concentrations of the individual gasses. The concentration range explored in the analysis varies from a few parts per million (ppm) to thousands of ppm. Spectra obtained from HITRAN and experimental single-molecule reference spectra of each of the molecular species were acquired and used as training data sets. These spectra were used to generate simulated spectra of the gas mixtures (linear combinations of the reference spectra). Here, in this proof-of-concept experiment, we demonstrate that after an absolute calibration of the QEPAS cell, the PLS analyses could be used to determine concentrations of single molecular species with a relative accuracy within a few % for mixtures of H2O, NH3, and CH4 and with an absolute sensitivity of approximately 300 (±50) ppm/V, 50 (±5) ppm/V, and 5 (±2) ppm/V for water, ammonia, and methane, respectively. This demonstrates that QEPAS assisted by PLS is a powerful approach to estimate concentrations of individual gas components with considerable spectral overlap, which is a typical scenario for real-life adoptions and applications.

Methods to investigate the temperature distribution of heated ceramic gas sensors for high-temperature applications

Abstract. The temperature-dependent properties of sensor films for measuring the concentration of various gas components affect, to a large extent, the sensor characteristics of planar gas sensors. Therefore, it is important to know the temperature distribution of the gas-sensitive films of such sensors precisely. Using screen-printed thermocouples and a thermal-imaging camera, two principles for determining the temperature profile of gas sensors inside of a protection cap are shown and compared in this study. The data agree well, and the results can be used in future to determine the influences of varying flow and temperature conditions on the temperature profile of a sensor and to reduce such effects by adapting the periphery, e.g., by designing appropriate protection caps.

Combustion behaviour of plastic waste – A case study of PP, HDPE, PET, and mixed PES-EL

Plastic production is skyrocketing due to convenience needs and thus, the amount of plastic waste is increasing. There are several different methods to handle plastic waste, within which waste-to-energy processes are viable options in certain settings. However, the combustion of materials is a complicated and complex process that can take place in a number of ways. When exposed to heat, different polymers behave differently (e.g. have different emission factors) and thus, not all types of plastic waste recommended to be handled through combustion. Therefore, it is vital to achieve a deeper understanding of these processes in order to decide on the end use of plastic materials. Four common types of polymers were studied: polypropylene (PP), high-density polyethylene (HDPE), polyethylene terephthalate (PET), and polyester-elastane (PES-EL) mixture. The combustion properties of the plastic materials were investigated. The experiments were carried out in a laboratory electric resistance tube furnace at two different temperatures (650 and 900 °C). The behavior of these mainly single-use plastic wastes and the changes in the concentrations of CO, CO2, NOx, and O2 flue gas components generated during combustion was studied to determine the quality of potential waste-to-energy processes.

GEOCHEMICAL PATTERNS OF DISTRIBUTION OF DISPERSED GAS COMPONENTS IN THE SHALLOW SUBSURFACE OF WEST SIBERIA

Despite the modern trends for the decarbonization of power engineering, transportation, and industry, fossil fuels remain in high demand. On the other hand, the gas and oil industries are also interested in energy efficiency and reduced environmental impact. Drilling of the wells is one of the most environmental danger processes, and reducing the number of wells is an important task that also provides an increase in the overall energy efficiency of the oil/gas mining technological process. Deposit exploration is a necessary part of the petroleum mining industry that determines the presence of fuel resources. The reliable and fast identification of the oil/gas deposits allows for a decrease in the number of drilled research holes. The authors of this article investigated the depth distribution of the hydrocarbon and non-hydrocarbon components of dispersed gas sampled from the cores of West Siberia shallow wells to quickly refine the boundaries of the layers using a priori information in the form of geochemical correlation. The correlations were established based on the amount of methane, the sum of homologs of methane, hydrogen, and olefines. The results show a decrease in the concentrations of gas components at the boundaries of layers with different lithologies. The term "geochemical seal" is introduced to describe such a phenomenon.

Insights into the gas sensor materials: Synthesis, performances and devices

Recently, the intelligent, smart gas sensing devices have shown great prospects in applications of gas component recognition and concentration detection, which largely depends on the precise structures and compositions of sensing layers. Various synthetic strategies are promising for the scalable production and performance optimization of the sensing materials. In this review, different gas sensing materials with controlled preparation such as wet-chemical synthesis, electrospinning method, vapor-phase synthesis and exfoliation routes are summarized. Then, the representative design strategies and gas sensing performances in gas sensors are also discussed. Finally, the recent progress of some gas sensing devices is presented, with the emphasis on their device structure, circuit design, and applications. It is believed that this review will provide some guidelines for designing novel gas sensing materials with controllable synthetic methods and sensing behaviors for advanced gas sensors.

A Thermal-Hydrological-Mechanical-Chemical Coupled Mathematical Model for Underground Coal Gasification with Random Fractures

In this paper, in order to understand the development process and influencing factors of coal underground gasification, taking the two-dimensional underground gasification area of the plane as the simulation object, the characteristics of the multi-physical field coupling process of exudate mass heat transfer and combustion gasification reaction in the process of horizontal coal seam underground gasification are analyzed, and a two-dimensional mathematical model of thermal-hydrological-mechanical-chemical coupling of a porous medium is established. The temperature distribution of coal rock from the gasification point, the distribution of gas water vapor pressure and stress-strain, the temperature contour distribution of fractured coal rocks of different densities of heterogeneity, and the influence of different water-oxygen ratios and different fractured coal rocks on the gas components generated by the gasification reaction were studied. The results show that the tensile damage caused by the tensile strain volume expansion of the coal underground gasification center, the shear damage caused by the compression of the edge compressive strain volume, and the temperature conduction rate decrease with the increase in the coal rock fracture, but in the heterogeneous coal rock, the greater the fracture density, the faster the temperature conduction rate, which has a certain impact on the gasification combustion reaction. The ratio of CO2, H2 and CO in the case of simulating that the water-to-oxygen ratio is 1:2, 1:1, and 2:1 is 1:0.85:0.73, 1:1.1:0.97, and 1:1.76:1.33, respectively. At a water-oxygen ratio of 2:1, the concentration ratio is the most ideal, and the main gases, CO, CO2, and H2, are 32%, 21%, and 37%. Furthermore, the reaction rate increases with the increase of fracture density. The gas component concentration simulated in this paper has good consistency with the results of the previous experimental data, which has important guiding significance for the underground coal gasification project.

Influence of Compartment Fire Behavior at Ignition and Combustion Development Stages on the Operation of Fire Detectors

This paper presents experimental research findings for those involved in the early phase of fire in office buildings. Class A model fires with a reaction area from 5 cm2 to 300 cm2 were chosen for investigation. To mock up a fire, the following combustible materials typical of offices were used: wood pieces, heat-insulated linoleum, paper and cardboard. The main characteristics of a model fire were recorded: temperature in the combustion zone, heat release, time of complete burnout and concentration of flue gas components. Typical trends and histograms of changes of these characteristics over time were presented; stages of ignition, flame combustion and smoldering were illustrated. The key characteristics of fire detector activation at different stages of model fire combustion were analyzed. Dead bands and operation conditions of a group of detectors (smoke, heat, optical, flame), their response time and errors were identified. It has been established that the most effective detectors are flame and smoke detectors. Specific operational aspects of detectors were established when recording the ignition of different types of model fires. The viability of combining at least two detectors to record fire behavior was established. Recommendations were made on using the obtained findings when optimizing the systems for detecting and recording the start of a compartment fire.