Gas Pressure Research Articles

Design and Failure Analysis of Piston Using Ansys

A piston is a component of reciprocating engines. The purpose of piston is to transfer force from expanding gas in the cylinder to the crankshaft via a piston rod and a connecting rod. It is one of the most complex components of an automobile. In This project we are describes the Thermal analysis by using finite element method (FEM). The specifications used for designing the piston belong to four stroke single cylinder engine of piston. Modeling of piston is done using SOLID EDGE v20. static structural, Thermal and fatigue analysis is performed by using ANSYS WORKBENCH 2022 R1. The parameters used for the simulation are operating gas pressure, material properties of piston. The results predict the maximum stress and strain on pistons using FEA. The best material is selected based on static structural, thermal and fatigue analysis. The analysis results are used to optimize piston geometry of best two Materials

Effects of the chirp rate on single-shot coherent Rayleigh-Brillouin scattering

Single-shot coherent Rayleigh-Brillouin scattering (CRBS) is modeled using direct simulation Monte Carlo (DSMC). In CRBS, an optical lattice generated by the interference of two pump lasers traps the neutral particles via the dipole force. The gradient of refractive index due to the trapped particles of the gaseous media leads to coherent scattering of a probe beam, resulting in the CRBS signal. Additionally, using a chirped laser beam, CRBS signals can be obtained in a single laser shot, shortening the measurement time of the gas flow (on the order of 100 ns). The DSMC results of single-shot CRBS assuming Maxwellian velocity distribution functions (VDFs) show good agreement with experimental data, including argon, carbon dioxide, and xenon, for different gas pressures. One of the key observations obtained from the present simulations is that the CRBS signals become asymmetric when using a fast chirp rate due to finite time for collisionless trapping and collisional thermalization. Published by the American Physical Society 2024

Collision of liquid drops: bounce or merge?

Whether colliding drops will merge with or bounce off each other is critical to numerous processes, and the physics involved is notoriously complex. In particular, experiments show that both sufficiently slow and fast head-on drop collisions lead to merging, but that there is often an intermediate regime in which bouncing is observed; these transitions in behaviour were recently discovered to be surprisingly sensitive to the radius of the drops and the ambient gas pressure. We show here that these transitions between bouncing and merging are governed by nanoscale phenomena; namely, gas-kinetic and disjoining pressure effects. To capture these crucial effects, a novel, open-source computational model is developed for the simulation of colliding drops. The model uses a hybrid approach, based on solving the Navier–Stokes equations in the drop with a lubrication approach for the unconventional physics of the gas film. Our simulations show remarkably good agreement with experiments of head-on collisions and also provide new experimentally verifiable predictions.

Phenomenological Study of the Atomization Process in Pre‐Filming Nozzles Typically Used for Steel Atomization

Liquid steel atomization using close‐coupled nozzles is highly dependent on the relationship between momentum flux ratio, gas–liquid ratio, aspiration pressure, and operating pressure of inert gases. A strong correlation between these parameters and the final powder must be assumed. Understanding these parameters, their influence on the process, and their interactions with each other is indispensable for efficient powder production. In particular, the industrial application of close‐coupled atomization nozzles, which develop a thin pre‐film on the nozzle tip, is not yet fully understood. A model experiment is presented to investigate interactions between the flow conditions of the gaseous and liquid phases, focusing on recirculation phenomena inside the atomization zone. The experiments show the influence of liquid and gas flow conditions on the spray geometry and the liquid core length, as well as the strong dependence of the liquid mass flux on the gas flow. The aspiration pressure below the liquid nozzle is sensitive to gas pressure and has a major influence on the development of the liquid core and the pre‐film, as it increases the liquid mass flux. For practical application, the results confirm an optimal operating point of interacting system parameters, which leads to high‐quality atomization with minimal use of resources.

Influence of Central Coke Ratio on the Internal State of Blast Furnace

Central coke charging (CCC) is a widely used burden distribution method for blast furnaces (BFs). Adjusting the central coke ratio can change the burden temperature field and affect the smooth operation of BF. This study presents a coupled physical and mathematical model, incorporating particle motion, gas flow, and heat transfer between the burden and gas in two 5500 m3 BFs. The central coke ratios of the blast furnace A (BFA) and blast furnace B (BFB) is 15% and 20%, respectively. The root positions of the cohesive zone in the BFA and BFB are in the lower part of the stack and bosh zones, respectively. In the central area of the BF, the gas flow rate, gas temperature, and burden temperature of the BFB are higher. In the edge area of the BF, the gas flow rate, gas temperature, and burden temperature of the BFA are higher. The actual top gas temperature and gas pressure verify the accuracy of the proposed model. This model investigates the influence of the central coke ratio on the position of the cohesive zone, gas flow rate, gas temperature, and burden temperature, providing a cost‐effective method for studying the effect of the burden distribution matrix on the internal state of the BF.

Decoupling and predicting natural gas deviation factor using machine learning methods

Accurately predicting the deviation factor (Z-factor) of natural gas is crucial for the estimation of natural gas reserves, evaluation of gas reservoir recovery, and assessment of natural gas transport in pipelines. Traditional machine learning algorithms, such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM), often lack accuracy and robustness in various situations due to their inability to generalize across different gas components and temperature-pressure conditions. To address this limitation, we propose a novel and efficient machine learning framework for predicting natural gas Z-factor. Our approach first utilizes a signal decomposition algorithm like Variational Mode Decomposition (VMD), Empirical Fourier Decomposition (EFD) and Ensemble Empirical Mode Decomposition (EEMD) to decouple the Z-factor into multiple components. Subsequently, traditional machine learning algorithms is employed to predict each decomposed Z-factor component, where combination of SVM and VMD achieved the best performance. Decoupling the Z-factors firstly and then predicting the decoupled components can significantly improve prediction accuracy of all traditional machine learning algorithms. We thoroughly evaluate the impact of the decoupling method and the number of decomposed components on the model’s performance. Compared to traditional machine learning models without decomposition, our framework achieves an average correlation coefficient exceeding 0.99 and an average mean absolute percentage error below 0.83% on 10 datasets with different natural gas components, high temperatures, and pressures. These results indicate that hybrid model effectively learns the patterns of Z-factor variations and can be applied to the prediction of natural gas Z-factors under various conditions. This study significantly advances methodologies for predicting natural gas properties, offering a unified and robust solution for precise estimations, thereby benefiting the natural gas industry in resource estimation and reservoir management.

Numerical simulation of hydrate flow in gas-dominated undulating pipes considering nucleation and deposition behaviors

The distribution and deposition of hydrates in deep-water gas transportation pipelines are crucial for safety. Current simulations of hydrate flow based on the population balance model have predominantly focused on water-dominant systems and neglect the nucleation and deposition of hydrates. By establishing a model for a hydrate flow in a gas-dominant system that considers the uneven distribution of the liquid film on the wall, hydrate nucleation, gas–liquid mass transfer, particle adhesion and aggregation, and dynamic deposition, we achieved simulation of the entire process of hydrate formation, aggregation, breakage, and deposition. Simulations in undulating pipelines were carried out to investigate the effects of gas velocity, liquid injection, pressure, and pipeline structure on distribution patterns. The results showed increasing the gas velocity enhanced the dispersion of particles and increasing the pressure increased the rate of aggregation. The formation of blocky aggregates posed significant risk in the rear section of the lower-bend pipe.

Improvement of titanium film uniformity by magnetron sputtering with electromagnetic coil design

A novel magnetron assembly based on a combination of permanent magnet and adjustable electromagnetic coil is proposed for improved uniformity of the magnetron sputtering deposition process. The design of the magnetron sputtering system containing a rotating substrate and an off-axis arranged magnetron. A numerical framework has been developed to describe the evolution of the plasma density and distribution of sputtered particles. Specifically, the finite element method (FEM) was used to calculate the magnetic field and to model the magnetron sputtering discharge, and binary-collision Monte Carlo method was used to determine the transport of sputtered atoms to the substrate. Through parametric analyses, it was found that increasing the substrate-to-target distance, gas pressure, and coil current intensity benefits the uniform distribution of particles. The condition where the off-axis displacement of the magnetron effectively enhances uniformity. A strategy for optimizing deposition uniformity by combining adjustable current with an off-axis magnetron arrangement was proposed, which reduce the non-uniformity of film thickness by 77.6 % compared to the traditional fixed magnetic field model.

PSXII-29 Effect of tannins level and diet type on in vitro ruminal fermentation and methane production

Abstract The objective of the study was to evaluate the effect of four levels of a commercial product based on quebracho that contains tannins (Table 1) on three types of diets: Feedlot, Dairy Cattle, and Grazing, using the in vitro gas production technique on ruminal fermentation, dry matter digestibility and methane (CH4) production to determine its potential use as a greenhouse gas mitigation strategy in ruminants. An in vitro trial was carried out in a completely randomized block design with a factorial arrangement of 4 [dose: 0, 0.25, 0.50, and 0.75 % of Protein Enhancer (PE)] x 3 [diet types: low (LFD), medium (MFD) and high forage (HFD)]. The fermentation of each treatment was carried out in triplicate in 120 mL amber antibiotic bottles, containing 0.5 g of substrate previously deposited in nylon bags (24 µm pore size) and 60 mL of a mixture of medium and rumen fluid from three Holstein cows. Incubations were replicated in two independent runs (blocks). The gas pressure (PSI) was recorded at 1, 2, 3, 6, 9, 12, 18, 24, 30, 36, 48, 60 and 72 hours of incubation. Gas pressure data were converted to gas volume (y = mL of gas; x = gas pressure PSI). Subsequently, pH was measured, and subsamples for analysis of volatile fatty acids (VFA) by gas chromatography were collected. Methane was analyzed with a Crowcon Gas-Pro detector, while ammoniacal nitrogen with a hybrid multimodal microplate reader. The data were analyzed with the MIXED procedure of SAS, and the comparison of means was analyzed with Tukey and with orthogonal polynomials for doses. An interaction (P < 0.05) was observed between diets and PE levels for CH4 concentration (%), where the diet with a greater level of forage and the greatest level of PE (0.75%), showed the least concentration (30%, P < 0.05) compared with the control diet of dairy cattle. On average, CH4 production [mL CH4/g dry matter (DM)] were 83.3, 63.6, and 35.3 for LFD, MFD, and HFD, respectively (Table 2). As the dose of PE increased, rumen pH and N-NH3decreased (P < 0.05), and the total VFA concentration increased (linear effect, P < 0.05; Table 3). Methane production was less (30%) with the grass-based diet and the greatest level of quebracho-based product with condensed tannins, compared with the dairy cattle diet with 0% condensed tannins. The diet for feedlot cattle was more digestible and, therefore, produced more gas and a greater concentration of CH4, in contrast to the grass-based diet, which produces less CH4. It is necessary to carry out in vivo trials, particularly in grazing cattle, to evaluate the effect of the quebracho-based product on performance and in vivo methane emission. This study was partially funded by PAPIIT-DGAPA-UNAM (grant IN212523).

Transient pressure characteristic investigation and performance analysis of a novel three-port gas pressure dividing (GPD) device

The wave-rotor based gas pressure dividing (GPD) is a novel concept to allocate and utilize the pressure energy of gases, presenting significant potential in engineering fields. However, studies about GPD devices are rare, and related mechanism analysis and performance investigations are almost blank. In this study, an experimental platform upon a novel three-port GPD device is established. The transient pressure distribution characteristics in passages of GPD wave rotor are determined experimentally with the customized pressure acquisition system. Besides, the effects of rotation speed, compression ratio (β), and expansion ratio (α) on the pressure dividing performance of the GPD device are systematically examined via experiments and numerical simulations. The results indicate that the interaction of shock waves and expansion waves in passages can enable the medium-pressure gas to divide into high-pressure and low-pressure gases. The rotation speed of 2340 rpm is optimized, determining the greatest gas compression and expansion. The compression ratio increase can improve the compression efficiency and reduce the expansion depth, while the expansion ratio increase can present an opposite regulation. The flow rate efficiency of LP port is decreased with the compression ratio and expansion ratio increase.

Dehardening of carbon dioxide: A highly efficient chemical precipitant used for the dehardening of deep coalbed methane produced water

The greenhouse gas CO2 is used as a precipitant to deharden the deep coalbed methane produced water (PW), allowing it to meet the reuse requirements. The pH of PW is the key factor affecting the absorption and dissolution of CO2. High raw water pH leads to higher CO2 absorption, callback pH, and CO32− release. The aeration rate and aeration time determine how quickly and how much CO2 is absorbed and dissolved. Increasing temperature enhances the removal effect. Smaller CO2 bubble facilitates more rapid CO2 absorption, and high CO2 gas pressure increases the final CO2 dissolution. Under normal temperature and pressure, the pH of raw water is adjusted to 11, with an aeration rate of 200 mL/min for 16 min. In addition, the callback pH is equal to 12.80, resulting in a final dehardening effect of 99.77 %, making the treated PW suitable for reuse. Mechanistic studies have shown that at the first level of dehardness, CO2 is not dissolved enough under constant pressure, causing some Ca2+ to precipitate as Ca(OH)2, which enhances hardness removal. To improve the dehardening effect, excessive callback pH can be used, and multi-stage dehardening ensures that Ca2+ precipitates as CaCO3. Meanwhile, Mg2+ is predominantly removed as Mg(OH)2 in the first stage. Dehardening can produce small CaCO3 microsphere by-products, which can be considered for further recycling. The cost of CO2 as a dehardening agent is 23.83 % better than Na2CO3, which not only achieves the dehardening of deep coalbed methane PW at a low cost, but also provides a feasibility reference for the early realization of the “dual carbon” target to a certain extent.

PSXI-12 Effects of Flint corn with or without high concentration of amylase and particle size on in vitro fermentation parameters, gas production and methane emission

Abstract The objective of this trial was to evaluate the fermentation parameters, gas production and dry matter (DM) disappearance in vitro of two corn hybrids with two particle sizes. A 2 × 2 factorial design study was carried out to evaluate two types of Flint corn with or without high amylase concentration (Enogen flint or Tropical Flint, respectively), and two particle sizes (1.5 or 2.5 mm). Incubations were carried out for a total period of 24 h using the automatic gas pressure system (ANKOM, RF). The ruminal liquid was combined with buffer in a 1:4 ratio respectively and each bottle received 150 mL of this mixture plus 1.5 g of DM corn sample. At the end of the 24-h period, a gas sample was taken for methane analysis, a sample was taken for short chain fatty acid (SCFA) analysis, and DM was performed on the final residue from the bottles to estimate the disappearance of DM. Data were analyzed using SAS Proc Mixed (9.4). There was no interaction effect between corn hybrid and particle size for the variables evaluated. Enogen Flint corn increased the proportion of propionate (30.7 vs. 28.1 mM/100 mM; P = 0.03) and reduced isovalerate (1.23 vs. 1.65 mM/100 mM; P = 0.01), and acetate:propionate ratio (1.85 vs. 2.11; P = 0.04), with no effect on the other fermentation variables evaluated. The particle size affected the pH of the fluid, with lower pH observed when using 1.5 mm particle size (6.64 vs. 6.70; P < 0.01). Regarding the disappearance of DM, Enogen Flint corn increased disappearance compared with Tropical Flint (80.8 vs. 77.5%; P < 0.01), and the 1.5 mm particle size also resulted in an increase in DM disappearance (81.9 vs. 76.4%; P < 0.01), with no interaction between the factors studied. (P = 0.80). Corn hybrids did not affect total gas production and methane production. However, the 1.5 mm particle size increased the total gas production (117.5 vs. 103.2 mL/24 h; P < 0.01), with no effect on methane production. In conclusion, Enogen technology optimizes the rumen fermentation process and increases corn dry matter degradability, and 1.5 mm particle size of the corn grain also increases degradability.

PSXI-14 Effects of diets with high and low inclusion of corn with or without high concentration of amylase on in vitro fermentative parameters and gas production

Abstract The study aimed to evaluate the effects of corn hybrids and the level of inclusion in the diet on in vitro fermentative parameters, DM disappearance, total gas and methane production. A 3 × 2 factorial design study was carried out to evaluate the Tropical Flint corn (TFC), Enogen Flint corn (EFC) and Enogen Dent corn (EDC), and the corn inclusion content in the diet (H: 71%; L: 42.5% of DM). The experiment was carried out using automatic gas pressure detection modules (ANKOM, RF). Rumen fluid was collected from two animals fitted with a rumen cannula and fed a diet containing 60% forage. The ruminal liquid was combined with buffer in a 1:4 ratio respectively and each bottle received 150 mL of this mixture plus 1.5 g of DM corn sample. Gas production was evaluated at the end of 24 h of incubation and a gas sample was taken for methane analysis. Furthermore, the pH of the liquid was measured at the end of 24 h and a sample was obtained for analysis of short chain fatty acids (SCFA), ammonia concentration and the final residue was used to determine de DM disappearance. The data were analyzed using Proc Mixed of SAS (9.4). There was an interaction between corn hybrid and inclusion level for the variable total SCFA (H-TFC: 70.5; H-EFC: 41.5; H-EDC: 40.7; L-TFC: 43.7; L-EFC: 38.8; L-EDC: 39.7 mM; P = 0.02) and proportion of butyrate (H-TFC: 9.25; H-EFC: 5.53; H-EDC: 6.01; L-TFC: 5.80; L-EFC: 5.41; L-EDC: 5.99 mM/100mM; P = 0.02), with greater values observed for the inclusion of TFC in relation to the other treatments. The inclusion of Enogen corn (Flint or Dent) increased propionate (TFC: 32.1; EFC: 36.3; EDC: 36.7 mM/100mM; P < 0.01) and reduced acetate (TFC: 56.7; EFC: 55.1; EDC: 54.8 mM/100mM; P = 0.02) and the acetate:propionate ratio (TFC: 1.83; EFC: 1.56; EDC: 1.53; P < 0.01). On the other hand, greater inclusion of corn in the diet increased propionate (H: 36.8; L: 33.3 mM/100mM; P < 0.01) and reduced acetate (H: 53.5; L: 57.6 mM/100mM; P < 0.01), acetate:propionate ratio (H: 1.50; L: 1.77; P < 0.01), and fluid pH (H: 6.39; L: 6.46; P < 0.01). Corn hybrids with Enogen technology increased the DM disappearance (TFC: 70.5; EFC: 73.3; EDC: 74.3%; P < 0.01), without affecting the production of gases and methane. Furthermore, greater inclusion of corn in the diet increased the DM disappearance (H: 74.1; L: 71.2%; P < 0.01) and gas production (H: 193.8; L: 160.5 mg/24 h; P < 0.01), without effect on methane production. Enogen technology and increasing corn in the diet improve fermentation and increase degradation of dry matter; however, methane production increases with greater corn inclusion in the diet.

Закономерности износа плазмотронов при плазменной резке толстолистового проката на токе обратной полярности

The introduction describes the features of the process of plasma cutting of various metals and alloys using reverse-polarity plasma torches with and the features of cutting thick sheets. The purpose of the work is to study the wear process of plasma torches operating on reverse polarity current when cutting thick rolled sheets of aluminum and titanium alloys. Research methods include optical and scanning electron microscopy, filming of the cutting process and visual inspection of plasma torch elements after receiving specimens. Results and discussion. The section shows the appearance of the main working elements of the plasma torch after cutting in various modes, which led to both stable and gradual wear and to catastrophic failure of the plasma torch. The results of structural studies of the main characteristic zones of nozzles and electrodes after cutting are presented. The studies carried out made it possible to establish the main reasons for the failure of the working elements reverse-polarity plasma torches. The causes of catastrophic failure of plasma torches include failure to maintain the gap between the nozzle and the electrode and melting of the channel of gas supply into the discharge chamber. The wear of nozzles and electrodes in a stable mode can be intensified due to abnormal operation of the starting arc, the presence of manufacturing inaccuracies and excess gas pressure. In conclusion, the main conclusions based on the results of the research are formulated. The process of wear of electrodes, nozzles and body elements of plasma torches during operation at high electric arc power values is described.

Flexible FPI sensor fabricated by fiber end photopolymerization and integration for high sensitivity gas pressure sensing

This work presents a new design framework for highly sensitive fiber gas pressure sensor. We construct a Flexible Fabry–Perot Interferometer (F-FPI), which consists of three polymer pillars and an end cap, on a fiber end face. A unique fiber-end photopolymerization and integration (FEPI) technique is adopted for fabricating the device. The varied gas pressure in the enclosed space not only changes the refractive index (RI) of the gas but also the length of the pillars. Therefore the difference in the optical path length of the FPI is more sensitive to pressure changes. Experimental results indicate that the F-FPI realizes a gas pressure sensitivity up to 79.0 pm/kPa in the range of 0–200 kPa. In addition, the Vernier effect is introduced to amplify the sensitivity to −409.7 pm/kPa. The temperature compensation is achieved by cascading a Fiber Bragg Grating (FBG) behind the F-FPI. Such a design framework provides a new idea for highly sensitivity gas pressure sensing.

Effect of continuous and random multi-particle impaction on the aluminum coating and copper substrate in cold spraying

In this study, the process of multi-particle cold spraying has been numerically simulated and compared with the actual cold spraying results. The results show that in the continuous multi-particle models, the maximum depths of compressive residual stress reached 4.90 μm, 3.99 μm, 4.78 μm, and 5.19 μm for each increment in particle number. The penetration depth of residual stress increases then decreases, due to two opposite factors effects on the penetration depth of residual stress. the maximum compressive residual stresses on the substrate are 438.14 MPa, 293.57 MPa, 286.19 MPa, and 279.30 MPa respectively, declining as the number of impacting particles grows. With the subsequent deposition of particles, the further deformation of the substrate causes the stress on the side to gradually homogenize, and the peak value decreases. Surface stress of the workpiece alleviates after multiple Al particles impact Cu substrate. In all random multi-particle models of different gas pressure, the residual stress begins to disappear at about 100 μm from the surface, and basically disappear at about 300 μm. As the collision speed of particles increases, the substrate deformation increases, but the growth rate of deformation decreases. The influence of coating thickness on the substrate deformation gradually decreases with the increase of coating thickness.

Influence factors and improvement scheme on the breakdown behavior of pseudospark switch

Abstract High-power pulse generators are widely used in civil and military fields. The main switch directly determines the output characteristics of the high-power pulse generators, such as the voltage front time (tf). Pseudospark switches (PSS) show a promising future for middle voltage, high repetitive frequency pulse power applications. However, how to further improve the breakdown behavior without reducing its advantages is a challenging task. In this paper, the influence of operating parameters (anode voltage UA and gas pressure p) and structural parameter (number of cathode holes) on the breakdown behavior are investigated, the related mechanism are explained, and specific improvement schemes are proposed. It is found that the tf of the single channel PSS (SCPSS) decreased significantly with increasing p, but hardly varied with UA under moderate p. However, it is not a sound solution to increase the p excessively to reduce tf. Besides, increasing the number of cathode holes can obtain a shorter tf at low pressures (which implies superior repetition frequency performance). However, at 25 Pa, the jitter (which is defined as the standard deviation of tf in multiple tests) of the 2-channel PSS is larger than that of the SCPSS. And the jitter of the 4-channel and 8-channel PSS is also greater than 6 ns and 2 ns, respectively. Through experimental and simulation analyses, it can be explained as the stepwise penetration of the virtual anode and the non-simultaneous ignition of the channels. A scheme to increase the trigger energy (ε) has been adopted to improve the simultaneous ignition probability, while shortening tf and reducing jitter. After optimization, the good ignition probability of the 4-channel PSS has been improved to 82% and the jitter has been reduced to less than 1 ns at 25 Pa and 14.7 mJ.

Study on the condensate gas phase behavior in Nano-porous media

The pore size in shale has reached the nanoscale. The phase behavior of fluids in nanopores deviates from classical theory, making conventional phase theory inapplicable to shale reservoirs. It is thus of great significance to clarify the phase behavior at the nanometer pore scale in shale. Based on the shale reservoir in the Kaybob of the Duvernay shale, Canada, 6 nm and 10 nm cubic model systems were constructed, and a microscopic physical model was prepared included pathways at 10 nm, 40 nm, 500 nm, and micrometer scale. The fluid phase behavior in nanopores was studied using molecular simulations and nanofluidic chip experiments. The results show that during the retrograde condensation process, the condensate gas in small-scale pores condenses first and is less likely to evaporate as the pressure decreases. The conclusions drawn are: (1) In nanopores, the dew point pressure of condensate gas is higher than that of the bulk phase, and the smaller the scale of nanopores, the higher the dew point pressure. (2) The volume ratio of condensate in nanopores is higher, increasing as pore size decreases. (3) The condensation rate of condensate in nanoporous media varies slowly with pressure drop; During evaporation, the condensation rate of condensate in small pores varies more slowly with pressure drop compared to the bulk phase but is faster in large pores.

U-DeepONet: U-Net enhanced deep operator network for geologic carbon sequestration

Learning operators with deep neural networks is an emerging paradigm for scientific computing. Deep Operator Network (DeepONet) is a modular operator learning framework that allows for flexibility in choosing the kind of neural network to be used in the trunk and/or branch of the DeepONet. This is beneficial as it has been shown many times that different types of problems require different kinds of network architectures for effective learning. In this work, we design an efficient neural operator based on the DeepONet architecture. We introduce U-Net enhanced DeepONet (U-DeepONet) for learning the solution operator of highly complex CO2-water two-phase flow in heterogeneous porous media. The U-DeepONet is more accurate in predicting gas saturation and pressure buildup than the state-of-the-art U-Net based Fourier Neural Operator (U-FNO) and the Fourier-enhanced Multiple-Input Operator (Fourier-MIONet) trained on the same dataset. Moreover, our U-DeepONet is significantly more efficient in training times than both the U-FNO (more than 18 times faster) and the Fourier-MIONet (more than 5 times faster), while consuming less computational resources. We also show that the U-DeepONet is more data efficient and better at generalization than both the U-FNO and the Fourier-MIONet.

Performance enhancement on the three-port gas pressure dividing device by flow channel optimization of wave rotor

Wave-rotor-based gas pressure dividing (GPD) is a potential technology that can synchronously conduct gas compression and expansion. This study, proposes a novel curving flow channel of wave rotor (C-FCWR) for the three-port GPD device, aiming to settle the technical problem of traditional width-constant straight flow channels (WS-FCWR). A series of comparative hydrodynamics and thermodynamic analyses are conducted. For the optimized C-FCWR with a forward-curving angle of +10°, the flow vortex generation in the medium-pressure (MP) and low-pressure (LP) ports is rather limited, the shaft power is as low as -0.45 kW, the shock wave efficiency is beyond 99.8 %, and the expansion depth remains above 26.4 K, proving a great technical advantage. For the application feasibility of the optimized C-FCWR to working conditions, a compression ratio below 1.2 and an expansion ratio of 1.8 are conducive to the overall performance of the GPD device.