Pressure Curves Research Articles

Modeling and Simulation of Multi‐Material and Complex‐Shaped Gun Propellant Combustion in Closed Vessels

AbstractThe geometric shape and material structure of gun propellant grains control the pressure evolution during combustion and, consequently, the performance of the ammunition. Due to the large number of degrees of freedom, additive manufacturing offers novel opportunities for grain shape and structure design. However, this new freedom necessitates the development of new algorithms for modeling and simulation of surface regression. In traditional combustion models, it is assumed that the propellant′s burn rate is a global quantity on its surface, which enables separate simulation of the surface regression and pressure evolution. To exploit the full potential of additive manufacturing and optimize designs for different applications, it is necessary to simulate grain structures with locally different burn rates on the surface. This work presents a model to simulate quantitatively the combustion of multi‐material and complex‐shaped solid propellant grains in a closed vessel for the first time. A lumped parameter pressure model is coupled with a surface regression simulation based on the level set method. The model is validated by comparison to analytical surface regression. Then, for the first time, a combustion simulation of a multi‐material ball propellant grain consisting of two hemispheres in a closed vessel is presented. Compared to a combustion simulation using global and weighted mean burn rate values, the pressure and vivacity curve shows significant differences. This demonstrates impressively that for predicting the performance potential of multi‐material and complex‐shaped solid gun propellant grains, a quantitative and accurate combustion simulation is indispensable.

Abstract 4143219: Pressure-Volume Analysis by Three-Dimensional Echocardiography: A Novel Method to Estimate Left Ventricular Efficiency

Background: Left ventricular (LV) efficiency is a key pathophysiological marker in heart failure (HF). LV pressure curve estimation and three-dimensional (3D) volumes via echocardiography allows for non-invasive pressure-volume (PV) analysis and calculation of an index of efficiency (Figure 1). Aim: Validate efficiency index by 3D echocardiography by comparing it to invasive measurements and efficiency derived from Positron Emission Tomography (PET) metabolism. Methods: Two experimental models were utilized - one with canines (n=21) and another with sheep (n=12). In canines, echocardiography provided 3D LV volumes and valve event timings. The pressure curve was estimated by adjusting the time axis of a reference pressure curve to the valve events and its amplitude to measured peak LV pressure, which in clinical practice would be approximated as systolic brachial cuff pressure. Invasive pressure was measured by micromanometer and volume by subendocardial piezoelectric crystals. Non-invasive and invasive efficiency indices, calculated as the ratio of stroke work to total mechanical energy (Figure 1), were compared during baseline, right ventricular pacing, aortic constriction and dobutamine infusion. Twelve sheep implanted with a pacemaker underwent 8 weeks of rapid dyssynchronous DDD pacing to induce dilated HF. LV efficiency index was calculated as in Figure 1, using measurements from a PV-catheter calibrated to end-diastolic volume by cardiac MRI, and compared to efficiency calculated as stroke work divided by total LV glucose metabolism via PET/CT. Recordings were performed during AAI and DDD pacing, at baseline (n=3) and following 8 weeks pacing-induced HF (n=12). Results: In canines, non-invasive and invasive efficiency indices showed excellent agreement (r=0.95, p<0.0001; mean difference 0.4%, SD 3.4%) (Figure 2). In sheep, the efficiency index showed similar decline compared to efficiency by PET/CT after induction of HF and after switching from AAI to DDD pacing (p<0.05 for all interventions). Overall correlation between the methods was moderate (r=0.67, p=0.0001) but excellent in animals with longitudinal data (r=0.89, p=0.0001) (Figure 3). Conclusions: Efficiency index by 3D echocardiography is accurate and reflects changes in efficiency measured by PET/CT. It may thus be of interest for clinical use.

A Method for Determining Yield Stress of Unsaturated Soils from Lateral Pressure

Abstract Predicting the stress–strain behavior of unsaturated soils is essential for determining yield stress. This paper explores a new method for determining the yield stress of unsaturated soils from the lateral pressure curve. A series of earth pressure at rest (K0) ondometer tests were conducted on unsaturated Yangqin silt clay. Lateral stress was obtained under different saturations and compactness. The relationship curves between lateral and vertical net stress were drawn for each condition. An obvious turning point was observed in the curve, which can be used to determine the yield stress. The oedometer tests were conducted, and the Casagrande and the bilogarithmic methods were used for comparison purposes. The difference between the proposed and traditional methods was less than 17 %. The initial saturation and compactness influence on the yield stress was discussed. The yield stress increased with the decrease in saturation and increases in compactness, which is consistent with that of the classic method. The test results and comparison prove the rationality of the proposed method. No coordinate transformation is required in the proposed method, which is more convenient for data processing. It can be used to determine the yield stress of unsaturated soils from another perspective.

Numerical Modeling of Two-Phase Fluid Filtration for Carbonate Reservoir in Two-Dimensional Formulation

This work considers the isothermal process of incompressible viscous fluid filtration in an oil-saturated, fractured-porous reservoir. A study of the pressure and water saturation distribution process is carried out for a case in which a production well is put into operation. For this problem, i.e., a mathematical model in a two-dimensional formulation, a numerical method and a parallel algorithm are proposed. The mathematical model of two-phase filtration is written in accordance with the classical laws of continuum mechanics and Darcy’s law and also includes a function of fluid exchange between low-permeability pores and high-permeability natural fractures within the framework of the Warren–Root model. The numerical solution is based on the finite-difference method and a splitting scheme of physical processes and spatial coordinates. For a split system with respect to piezoconductivity, an implicit finite-difference scheme with fixed saturations is constructed, and with respect to saturation transfer, explicit and implicit difference schemes are constructed. For parallel implementation of the developed numerical approach, a method based on geometric parallelism is selected. Testing of the developed method is performed using the example of calculating liquid mass transfer for a wide range of parameters. To verify the model, the obtained calculated pressure curves are compared with field data recorded by a deep-well measuring device. The results allow for estimation of the distribution of reservoir pressure and water saturation depending on the permeability of the fracture set and the pore part. The obtained results allow for monitoring of well operations, reducing unexpected accident risks and optimizing the development system in order to increase oil production in fractured-porous reservoirs. Computational experiments confirm the efficiency of the developed numerical algorithm and its parallel implementation.

Novel clinical method: left ventricular diastolic pressure curve by echocardiography

Abstract Background A non-invasive clinical method for construction of the systolic part of the left ventricular (LV) pressure curve was recently introduced. There is, however, no clinical method available to construct the LV diastolic pressure curve. Purpose The aim of this study was construction of patient-specific LV diastolic pressure curves from echocardiographic data and have initial validation against simultaneously acquired pressure curves by high-fidelity LV pressure catheters (micromanometers). Methods The study included 108 patients referred for diagnostic left heart catheterization due to suspected coronary artery disease. 81 patients were used as a training cohort. The construction of a diastolic pressure curve is based on a reference unitless pressure trace and seven key pressure-time diastolic events estimated in each patient. The reference diastolic pressure trace was generated from a group of 8 patients with LV pressures recorded by micromanometer. Each individual pressure trace from the reference cohort was first annotated with the occurrence of the key diastolic events: mitral valve (MV) opening, minimum LV pressure, peak of early-diastolic mitral flow velocity (E) and start and peak of atrial contraction-induced velocity (A), and MV closure. Then the temporal intervals between these events were normalized before calculating an averaged pressure curve (Figure 1, panels A-C). A patient-specific LV diastolic pressure curve was constructed by adjusting the standard curve according to estimated LV pressure at the key diastolic events (shown in Figure 1D). The estimation of the pressure-time instants is based on the LV volume temporal transient, used to estimate filling flow rate (Q=dV/dt) and flow acceleration and deceleration (dQ/dt=d2V/dt2), as well as a set of biomarkers including left atrial reservoir strain, peak systolic LV pressure, and body mass index. LV volume temporal traces were generated by combining global 2D volumes with global longitudinal strain. The ability to generate patient-specific diastolic LV pressure curves was validated in a second cohort of 7 patients studied with micromanometer-tipped catheters. Echocardiography and LV pressure were recorded from the same series of beats and recordings were done during breath-hold at end-expiration. The agreement was accessed qualitatively and considering the mean diastolic LV pressure. Results There was good agreement between measured and estimated LV diastolic pressure curves, qualitatively and quantitatively, via mean diastolic PLV: Bias 0.2 mmHg, limits of agreement <3.2 mmHg (Figure 1D-F). Conclusions The results suggest that the LV diastolic pressure curve can be estimated by echocardiography. The method needs validation in larger populations.Non-invasive diastolic LV pressure curve

Right ventricular myocardial work in heart failure with preserved ejection fraction: insights from invasive cardiopulmonary exercise testing

Abstract Backgrounds Symptoms of heart failure with preserved ejection fraction (HFpEF) is closely related to elevated pulmonary capillary wedge pressure (PCWP) during exercise. The understanding of right ventricle myocardial work, assessing of right ventricular (RV) function utilizing RV pressure–strain loops, in HFpEF is lacking. Methods The study population underwent invasive cardiopulmonary exercise tests, measuring pressures at rest and during exercise to identify HFpEF. Echocardiography assessed LV and RV parameters. Right ventricular myocardial work was calculated using strain-rate and pressure curves, matching them with ECG data. RV global constructive work (RVGCW), RV global work index (RVGWI), RV global wasted work (RVGWW), and RV global work efficiency (RVGWE) were analysed and compared with invasively measured PCWP at resting and peak exercise. Results Between November 2017 and July 2023, 41 patients with adequate data were enrolled, and 21 were diagnosed with HFpEF. There were no significant differences in various echocardiographic parameters between HFpEF and non-HFpEF groups, except higher post-exercise PCWP and mean pulmonary artery pressure. HFpEF patients had higher RVGWW and lower RVGWE. RVGWW and RVGWE had higher predictive ability for HFpEF diagnosis compared to other echocardiographic parameters. While RVGCW (r = 0.0.504, P = 0.001 and r = 0.430, P = 0.006, respectively) and RVGWW correlated (r = 0.408, P = 0.008 and r = 0.621, P <0.001, respectively) with post-exercise ∆PCWP and exercise PCWP, only RVGWW (β=1.981, P=0.044 and β=4.323, p<0.001) being independently associated with both after adjustment for confounding factors. Conclusions RVGWW is a novel parameter that provides an integrative analysis of RV systolic function and correlates more closely with post-exercise ∆PCWP than other standard echocardiographic parameters in HFpEF.

Obesity plays a key role in inducing myocardial and vascular dysfunction in a translational model of heart failure with preserved ejection fraction in rats

Abstract Background Exploring experimental models of heart failure with preserved ejection fraction (HFpEF) may help to understand the mechanisms leading to this challenging condition. Purpose In a translational model, we aimed to assess the relative contribution of hypertension and obesity in inducing structural, functional and hemodynamic changes associated to the HFpEF phenotype. Methods We investigated 3 groups of male 40 weeks old rats: control Wistar Kyoto (WKY, n=10), Spontaneous Hypertensive Rats (SHR, n=10) and SHR with obesity induced by consumption of cafeteria diet during 28 weeks (Ob-SHR, n=9). Animals were submitted to assessment of: body weight, systolic (SBP) and diastolic (DBP) blood pressure; in vivo structural and functional changes evaluated by high resolution Echocardiography including left atrial dimension (LA), left ventricle (LV) diastolic dimension (LVDD), LV posterior wall thickness (LVPW), LV wall relative thickness (LVWRT), LV ejection fraction (LVEF). Invasive hemodynamic evaluation assessed the intraventricular pressure curves obtaining LV end diastolic pressure (LVEDP) and calculation of LV diastolic time constant (Tau). After euthanasia, thoracic aorta was used for vascular function assessment by measuring the maximal cumulative concentration-effect curves of contraction to phenylephrine (PE), expressed as Emax (%). Protein expression of Intercellular Adhesion Molecule 1 (ICAM-1) was determined in myocardial tissue (% in relation to WKY). Results were expressed as mean ± SEM and effects of groups vs time were compared with mixed ANOVA. Results The results are shown in the table. We observed higher levels of SBP and DBP in SHR and Ob-SHR when compared to WKY, but with similar values between SHR and Ob-SHR groups. Regarding the structural LV changes, we observed LV remodeling and LA dilation in both SHR and Ob-SHR groups, but with no difference between both hypertensive groups. The Ob-SHR was the only group showing increased LVEDP in comparison to other groups. The Tau was also increased in the Ob-SHR animals. Concordantly, the Ob-SHR group showed increased expression of ICAM-1 (figure - A) that was concomitant to abnormal vascular response with increased contraction to PE (figure - B) as compared to SHR and WK groups. Conclusions In this translational model of HFpEF in rats, the structural changes related to LV remodeling were similar in SHR and Ob-SHR, probably reflecting comparable higher levels of blood pressure observed in both groups. In contrast, elevated EDP, a hallmark of HFpEF, was only seen in the Ob-SHR group and this was concomitant to diastolic dysfunction, endothelial inflammatory activation and altered vascular function. Our results indicate that obesity is a key factor inducing vascular and myocardial changes that triggers HFpEF phenotype in this model.

Artificial intelligence-enabled reconstruction of the right ventricular pressure curve using the peak pressure value: a proof-of-concept study

Abstract Aims Conventional echocardiographic parameters of right ventricular (RV) function are afterload-dependent. Therefore, incorporating RV pressures may enable the formulation of new parameters that reflect intrinsic RV function accurately. Accordingly, we sought to develop an artificial intelligence–based method to reconstruct the RV pressure curve based on the peak RV pressure. Methods and Results We invasively acquired RV pressure in 29 heart failure patients before and after implanting a left ventricular (LV) assist device. Using these tracings, we trained various machine learning models to reconstruct the RV pressure curve of the entire cardiac cycle based on the peak value of the curve. The best-performing model was compared with two other methods that estimated RV pressures based on a reference LV and RV pressure curve, respectively. Seventeen consecutive patients from another centre who underwent right heart catheterization and simultaneous echocardiography served as an external validation cohort. Among the evaluated algorithms, multilayer perceptron (MLP) achieved the best performance with an R2 of 0.887 (0.834–0.941). The RV and LV reference curve–based methods achieved R2 values of 0.879 (0.815–0.943) and 0.636 (0.500–0.771), respectively. During external validation, MLP exhibited similarly good performance [R2 0.911 (0.873–0.948)], which decreased only modestly if the echocardiography-derived peak RV pressure was used instead of the invasively measured peak RV pressure [R2 0.802 (0.694–0.909)]. Conclusions The proposed method enables the reconstruction of the RV pressure curve using only the peak value as input. Thus, it may serve as a fundamental component for developing new echocardiographic tools targeting the afterload-adjusted assessment of RV function.

Anesthetic Gas Scavenging System for Gas Evacuation in the ICU.

Inhaled sedation is increasing in ICUs, with active carbon filters (ACFs) commonly used for evacuating halogenated gases. However, the potential benefits of a waste anesthetic gas system (WAGS) similar to the ones used in operating rooms should be explored. To limit the suction over the flow sensor where the WAGS is connected on ICU ventilators, an anesthetic gas receiving system (AGRS) is required, constituting with the WAGS an active gas receiving and scavenging system (AGRSS). Ensuring that this whole device does not compromise the flow sensor reliability is crucial. The aim of this study was to compare various gas evacuation devices and assess the reliability of AGRSS on ICU ventilators. In this experimental study, pressures and flows were recorded during the ventilation of a test lung using various ventilator settings and gas evacuation methods: no device (reference condition), ACF, the WAGS alone, AGRSS (WAGS and AGRS together), and the expiratory valve connected to the medical vacuum system with the AGRS in between. Visual comparisons of the pressure and flow curves followed by a statistical analysis comparing median pressures and flows of each device to the reference were performed. The test lung model demonstrated consistent comparability in pressures and flows among all devices, except for the WAGS alone, which exhibited discordance through significant overestimation or underestimation. These findings indicate that using a WAGS with the AGRS system appeared to be reliable for managing gas evacuation in ICUs without compromising pressure or flow delivery. The data from this experimental trial should be confirmed with clinical studies involving human subjects. Given the increasing use of inhaled sedation in ICUs, these results support the daily application of the WAGS with the AGRS for gas evacuation, similar to its established use in anesthesiology.

Research on Air Cushion Flow Field and Bearing Characteristics of Single Row Hole Air Cushion Belt Conveyor

In order to obtain information regarding changes in the air cushion flow field and load-bearing characteristics of a single row hole air cushion belt conveyor, a structural model of the air cushion of the belt conveyor was established, with the single row hole air cushion belt conveyor as the research object. Firstly, according to the theory of fluid lubrication, a mathematical model of the air cushion was established. Then, the effects of air cushion thickness, pore velocity, and belt velocity on the pressure and bearing characteristics of the air cushion flow field were studied using FLUENT software. In addition, the equivalent stress, displacement, and pressure curves between the air cushion flow field and the conveyor belt and the material were analyzed using the two-way fluid–solid coupling method. Finally, the experimental platform of a single row hole air cushion belt conveyor was built, and the flow field and bearing characteristics of the belt were verified through experiments. The results show that reducing the thickness of the air cushion and increasing the pore flow rate can improve the pressure and bearing characteristics of the air cushion, while speed has little effect at lower belt speeds.

Prediction of Capillary Pressure Curves Based on Particle Size Using Machine Learning

Capillary pressure curves are usually obtained through mercury injection experiments, which are mainly used to characterize pore structures. However, mercury injection experiments have many limitations, such as operation danger, a long experiment period, and great damage to the sample. Therefore, researchers have tried to predict capillary pressure data based on NMR data, but NMR data are expensive and unstable to obtain. This study aims to accurately predict capillary pressure curves. Based on rock particle size data, various machine learning methods, such as traditional machine learning and artificial neural networks, are used to build prediction models and predict different types of capillary pressure curves, aiming at studying the best prediction algorithm. In addition, through adjusting the amount of particle size characteristic data, the best amount of particle size characteristic data is explored. The results show that three correlation coefficients of the four optimal algorithms can reach more than 0.92, and the best performance is obtained using the Levenberg–Marquardt method. The prediction performance of this algorithm is excellent, with the three correlation coefficients being all higher than 0.96 and the root mean square error being only 5.866. When partial particle size characteristics are selected, the training performance is gradually improved with an increase in the amount of feature data, but it is far less than the performance of using all the features. When the interpolation increases the particle size characteristics, the best performance is achieved when the feature data volume is 50 groups and the root mean square error is the smallest, but the Kendall correlation coefficient decreases. This study provides a new way to obtain capillary pressure data accurately.

Molecular insight into the interfacial microstructural and miscible behavior of CO2 flooding in tight reservoir

In this study, the interfacial microstructure of CO2 flooding in tight reservoirs was investigated by molecular dynamics simulations. Initially, the study focused on four systems: membrane, cluster, dead-end and channel. The evolving properties of the oil-gas and oil-solid interfaces within the static swelling system were analyzed. By examining interaction energy and pressure curves, it was revealed that CO2 permeability at the oil-gas interface and accumulation at the oil-solid interface play crucial roles in the swelling process, subsequently impacting competitive adsorption behaviors with alkanes. Secondly, the oil-gas interface characteristics of the dynamic driving system are analyzed through comparison of tangential and vertical drive. The mechanism underlying the degradation of miscibility is revealed by evaluating the interfacial thickness and energy. Moreover, the addition of different co-solvents identifies key influencing factors on miscible zone stability, which serve as an improvement for the subsequent miscible optimization. The study provides certain guiding significance for improving oil recovery in CO2 flooding projects.

Using the total chemical potential to generalize the capillary pressure concept and therefrom derive a governing equation for two-phase flow in porous media

This work presents a governing equation (GE) for two-phase flow in porous media connecting capillary pressure to frictional pressure loss and external chemical potential supplied to a system in either stationary or diffusive equilibrium. It is based on the difference between non-wetting and wetting phase chemical potential (physically, pressure or energy density), which leads to a generalization of the capillary pressure concept. The difference in phase internal chemical potentials is characterized by changes in both interfacial areas and entropy densities due to variation in fluid saturations and is balanced by the system external chemical potential supplied. A definition of the capillary pressure concept is formulated based on the diffusive equilibrium criterion. The GE can explain the origin of the dynamic capillary pressure term, hysteresis, and connect the shift in the capillary pressure curve upon injecting water phases with varying salinities to all the other chemical potentials acting. It can connect, constrain, and potentially quantify all effects which can be formulated in terms of chemical potentials since it is based on a balance equation all two-phase flow systems must obey when either in stationary or diffusive equilibrium.

Research on Denoising Algorithm of Standpipe Pressure Signal in FCC Device Based on Tortuosity and Denoising Intensity.

The pressure signal of the standpipe in the regeneration device for the catalytic cracking reaction is commonly used as a basis for equipment fault diagnosis. The device operates in environments of high temperature, strong vibration, and high flow rate. The standpipe pressure signal is easily interfered with by noise, making it difficult to extract pressure characteristics. In this study, a signal denoising algorithm based on pressure curve tortuosity and denoising intensity is proposed. A power spectrum threshold vector is utilized to filter the pressure in the circulating standpipe, and the denoising intensity and tortuosity after denoising are calculated. Taking the ratio of noise reduction intensity and tortuosity as the objective function, the noise reduction scheme of the pressure signal at different heights of the standpipe is determined. The denoised pressure signals are reconstructed, and the characteristic pressure signals of the circulating standpipe are extracted. The results indicate that the method suppressed the noise, enhanced the significance of characteristic parameters, and improved the accuracy of the fault diagnosis in the FCC units.

Enhancing Oil Recovery in Eagle Ford Shale: A Multiscale Simulation Study of Surfactant Huff ’n’ Puff Methodology

In this paper, we present a simulation case study of a surfactant huff ’n’ puff pilot in the black oil window of the Eagle Ford (EF) Shale. The target horizontal well, which had been depleted for nearly 8 years, underwent stimulation via a surfactant huff ’n’ puff treatment. The surfactant was selected through laboratory screening using reservoir rock and fluid samples. After a 17-hour injection and a 1-month shut-in period, the well’s production increased fivefold from the baseline oil rate, sustaining incremental oil production for at least 2 years. The surfactant enhances oil recovery by altering rock wettability toward a more water-wet state and moderating oil/water interfacial tension (IFT). This process is modeled by surfactant adsorption in the simulator, indicating the degree of dynamic changes in relative permeability (krl) and capillary pressure (Pc) curves. We propose a comprehensive workflow comprising three stages: development of core-scale and field-scale models, sequential model calibrations, and multiobjective optimization to integrate laboratory measurements and field data from this pilot into multiscale numerical simulations. By matching oil recoveries from imbibition experiments on the core model and field production histories on the field model, krl and Pc profiles of two extreme states, basic reservoir properties, and additional reservoir properties altered during huff ’n’ puff operations are characterized. The matched core model reproduces a 15.1% incremental oil recovery for surfactant-assisted spontaneous imbibition (SASI) process relative to pure brine imbibition process. The matched reservoir model predicts the surfactant huff ’n’ puff treatment increases the oil production by 21.9% relative to water huff ’n’ puff treatment and by 52.9% relative to primary depletion for a 4-year period. The calibrated reservoir model also serves as a base case for optimizing well operation schedules through the implementation of a multiobjective genetic algorithm. The surfactant injection rate, injection time, and well shut-in time of the base case are varied to achieve higher oil production and reduced surfactant usage. Statistical analysis of eight trade-off cases indicates that optimal well operations, compared with existing practices, frequently involve increased injection rates [16.6–18.9 barrels per minute (bpm)], shorter injection periods (10–11.3 hours), and prolonged shut-indurations (49–65 days). This workflow offers valuable insights into surfactant huff ’n’ puff treatments for unconventional reservoirs, thereby facilitating the optimization of well operations and maximizing tertiary oil recovery.

Numerical Modelling of a Pulsating Flow Generator for Simulating Blood Pressure

Abstract Hypertension is a leading risk factor that deserves to be taken seriously, therefore researches on blood pressure measurement play a critical role. In this work, a liquid-operated pulsating flow circulation system with a bionic arm is set as a blood pressure simulator and a related numerical model is built to analyse the flow under different settings. The motion patterns of the flow generator and the medium used are two of the main factors discussed in this work. By comparing the pressure curves under different conditions and actual experimental data, the numerical model is validated, and so as to find the suitable parameters of the actual system.

A New model of gas-water two-phase seepage based on Newton's law of motion

The pore throat size, structure distribution, and lithology of porous media in gas reservoirs are varied, and the gas-water two-phase seepage law is complex, making it difficult to describe the seepage model. Newton's law of motion is a basic law of motion in classical mechanics, and its application in gas-water two-phase seepage modeling is an innovative practice of classical mechanics in seepage mechanics systems. Based on Newton's three laws of motion, a gas-water two-phase seepage model was established from the force analysis of fluid, and the relationship between velocity and pressure difference, pipe radius, water film thickness, viscosity, etc. was derived under the condition that the model reached a stable state, i.e., force balance. The relationship is referred to as the steady-state model. Subsequently. the equivalent permeability representation model was derived based on the steady-state model to calculate the permeability of rock samples with different channel distribution characteristics. The results were consistent with the measured values, and there is a good correspondence between channel distribution characteristics and permeability. The relative permeability calculation method was established based on the steady-state model and capillary pressure curve. The obtained relative permeability curve aligned with the two-phase seepage law and coincides with the relative permeability curve obtained by Poiseuille's law. Finally, a new productivity equation was derived based on the steady-state model, and the Inflow Performance Relationship (IPR) curve calculated by the gas well example was consistent with the traditional equation. The research results were based on the force analysis of fluid in porous media and fundamentally explored the law of fluid flow. The derived seepage model can be used to calculate reservoir permeability, the gas-water relative permeability curve, and gas well productivity analysis and to effectively guide gas reservoir development. The study was a successful application of the basic theory of mechanics in gas-water two-phase seepage in gas reservoirs.

Flow characteristics inside rectangular Tesla valve with different width-to-narrow ratios

To investigate the influence of the flow channel’s width-to-narrow ratio on the Tesla valve’s flow characteristics, this paper establishes five Tesla valve models with different width-to-narrow ratios. Employing the laminar flow model, CFD methods were used to numerically simulate both the forward and reverse flows through the Tesla valve across a spectrum of width-to-narrow ratios, ranging from 0.2 to 1. The results reveal the flow trends in the straight or arc channels show opposite variation patterns when flowing in forward and reverse directions. The flow rate passing through straight channel is more sensitive to the response of a small width-to-narrow ratio. Irrespective of the flow direction, as the width-to-narrow ratio increases, the fluid flow within the valve demonstrates increasingly pronounced stratification. The pressure curve of the diversion section assumes an “∞” shape in forward flow, whereas in reverse flow, it assumes a “flat plate” shape.

Probabilistic Estimation of Parameters for Lubrication Application with Neural Networks

This paper investigates the use of neural networks to predict characteristic parameters of the grease application process pressure curve. A combination of two feed-forward neural networks was used to estimate both the value and the standard deviation of selected features. Several neuron configurations were tested and evaluated in their capability to make a probabilistic estimation of the lubricant’s parameters. The value network was trained with a dataset containing the full set of features and with a dataset containing its average values. As expected, the full network was able to predict noisy features well, while the average network made smoother predictions. This is also represented by the networks’ R2 values which are 0.781 for the full network and 0.737 for the mean network. Several further neuron configurations were tested to find the smallest possible configuration. The analysis showed that three or more neurons deliver the best fit over all features, while one or two neurons are not sufficient for prediction. The results showed that the grease application process pressure curve via pressure valves can be estimated by using neural networks.

Modified Low-Field NMR Method for Improved Pore Space Analysis in Tight Fe-Bearing Siliciclastic and Extrusive Rocks

Abstract Understanding the filtration and storage properties of tight reservoirs is crucial for efficient resource exploitation, particularly in unconventional formations. This study presents two low-field nuclear magnetic resonance (LF-NMR) techniques: standard cut-off and modified differential approaches combined with mercury injection capillary pressure (MICP) and X-ray diffraction (XRD) studies to evaluate porosity and pore size distribution (PSD) in such formations. The differential technique involves subtracting the dry sample signal from a 100% water-saturated one, allowing the chemically bound water compound to be eliminated and facilitating PSD analysis. Through the application of the percolation theory, we established a power–law relationship between LF-NMR transverse relaxation time (T2) and MICP pore-throat diameter, enabling the derivation of PSD and pseudo capillary pressure curves. Our methodology was validated on a sample set representing tight sandstones, conglomerates, and extrusive rocks with high clay and iron mineral content, demonstrating the superior accuracy of the modified differential method in estimating effective porosity and absolute PSD in comparison with the standard approach. While the use of the percolation theory in PSD conversion was successful for rocks with unimodal distributions, it often failed for rocks with larger voids. The study also revealed that the relationship between the LF-NMR transverse relaxation times and MICP pore sizes is both nonlinear and challenging to describe with a universal equation, especially in the presence of para- and ferro-magnetic elements in the rock matrix. Despite obstacles to the complete elimination of the influence of these minerals on the T2 distribution, employing the modified differential LF-NMR method significantly mitigated this effect and offered a precise and noninvasive way of characterizing the petrophysical properties of tight reservoir rocks. Consequently, our studies offer a significant step toward a more precise assessment of pore structures in unconventional reservoirs that could be translated into more efficient strategies for locating geothermal heat and hydrocarbon resources.