Explore the vast range of titles available.

Guidewire-based pressure measurement is essential for diagnosing coronary artery disease. However, the impact of the guidewire on local hemodynamics and diagnostic outcomes is not fully understood. In this study, we propose a generalized reduced-order model (ROM) to accurately predict the trans-stenotic pressure drop in arteries. A key advantage of this model is that the viscous term does not rely on empirical parameters, making it applicable to both scenarios with and without guidewire insertion, and across varying stenosis severities. The proposed model demonstrates good accuracy compared to 3D idealized numerical models, achieving an average prediction error of 3.61% for cases without a guidewire and 4.53% for cases with a guidewire. Furthermore, when applied to a patient-specific model, it achieves comparable or better results than previously published ROMs. Finally, this ROM is employed to investigate the shifting relative importance of different components of the trans-stenotic pressure drop at various stenosis severities, and to provide further insights into the guidewire’s influence on FFR measurements.

The morphological vulnerability of atherosclerotic plaques, such as fluttering motion under pulsatile flow, poses diagnostic challenges in conventional fractional flow reserve (FFR) assessment. In this study, we investigate the hemodynamic impact of a fluttering plaque using a physical model of mild (40%) stenosis with and without an elastic plaque under stenotic flow. High-speed particle image velocimetry (PIV) and differential pressure measurements were employed to characterize flow patterns and pressure drop waveforms. While both models produced comparable time-averaged pressure drops, the Fluttering Plaque model exhibited extended recirculation zones, and elevated root-mean-square (RMS) fluctuations in pressure drop waveforms. The effects of the fluttering plaque on the distribution of turbulent kinetic energy (TKE) provides insight into the observed results. Our findings suggest that waveform-derived metrics, particularly the RMS amplitude of pressure drop fluctuations, may serve as novel hemodynamic indicators for detecting vulnerable plaques that remain undetected by time-averaged indices such as FFR.

Predicting pressure drop in multiphase flow is crucial for optimizing tubing size, wellhead pressure (WHP), completion design, cost management, and other production-phase objectives. While various correlations and models exist to calculate pressure drops, their accuracy diminishes significantly when applied to outlier datasets beyond their intended parameter ranges. Not only that, as reported by many studies, most of the empirical correlations and mechanistic models have an error, which is quite high and intolerable. This study introduces a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) model for accurately predicting pressure drops in vertical wells carrying multiphase fluids. A comprehensive dataset of 335 experimental records was compiled from diverse sources to encompass a wide range of parameters, ensuring the robustness of the proposed model. Key input parameters include WHP, oil rate, water rate, gas rate, inner diameter, surface temperature, and flow length. The ANFIS model was rigorously evaluated using different methods, such as cross plot, error distribution, Kruskal-Wallis (KW) test, error boxplot and violin graphs, Confidence Interval (CI), and statistical error metrics. The latter includes Average Absolute Percentage Error (AAPE), Root Mean Square Error (RMSE), and the coefficient of determination (R²) to prove the ANFIS model’s performance. The proposed ANFIS model was compared with the most commonly used published models. Results demonstrate that the ANFIS model outperforms existing methods, achieving an AAPE of 2.92%, an RMSE of 1.9638%, and an R² of 0.9645. KW test, error boxplot, violin graphs, and CI results indicated that the best model for predicting pressure drops is the proposed ANFIS model. These findings establish the ANFIS model as a reliable and superior tool for predicting pressure drops in vertical wells with multiphase flow, offering significant advancements in design accuracy and operational efficiency.

Accurately calculating the bottom hole flow pressure of a multi-layer stacked sandstone reservoir (hereinafter referred to as a multi-layer reservoir) is the basis for production splitting, oil well dynamic analysis, and reasonable work system determination in the development of multi-layer reservoirs. The bottomhole flow pressure model for single-layer oil reservoirs does not consider interlayer interference and the pressure drop caused by fluid flow in the wellbore, which doesn’t comply with the characteristics of multi-layer combined production, and the use of the maximum bottomhole flow pressure of the oil layer as the bottomhole flow pressure of each oil layer to adjust the production system of each oil layer doesn’t meet the requirements of other oil layer regulation. Firstly, starting from fluid mechanics, the frictional effect generated by fluid flow in the wellbore is systematically considered, and the relationship between wellbore frictional pressure drop and flow distance is established. The pressure drop formula generated by fluid flow in the wellbore is derived; Secondly, from the perspective of seepage mechanics, a formula for the bottom hole flow pressure of a single-layer reservoir was obtained. Combined with the expression for the difference in bottom hole flow pressure of each oil layer in the development of a multi-layer reservoir and the pressure drop expression for fluid flow in the wellbore, a bottom hole flow pressure model for each oil layer in the development of a multi-layer reservoir was established (hereinafter referred to as the multi-layer reservoir bottom hole flow pressure model). Substitute various parameters into the bottomhole flow pressure model of multi-layer oil reservoirs, and the error between the calculated values and the actual test values in the field is 0.10%~1.30%, with an average error of 0.82%, meeting the actual needs of the site. There is a significant difference in the bottom hole flow pressure values of each oil layer in the co production reservoir. The multi layer reservoir bottom hole flow pressure model can accurately calculate the bottom hole flow pressure of each oil layer, avoiding the inability to accurately adjust the production system of multiple oil layers for the same bottom hole flow pressure. It can provide technical support for the development of a reasonable drainage system for on-site co production oil wells and the realization of high and stable production.

An investigation of steady laminar flow in transversely corrugated conduits is presented, with the velocity distribution and frictional resistance being characterized for the fully developed region, while the incremental pressure drop, and hydrodynamic entrance length are examined for the developing region. The velocity field throughout both flow regimes is modeled using an innovative analytical approach based on epitrochoidal coordinate transformations. It is demonstrated that in fully developed flow, the Fanning friction factor is reduced with either an increase in corrugation count at fixed amplitude or with larger corrugation amplitude at fixed wave number. Conversely, in the developing flow region, both the incremental pressure drop, and entrance length are found to increase with greater corrugation amplitude or number of boundary waves. These findings are shown to provide valuable insights for the optimization of corrugated conduit designs in applications where entrance effects are significant, such as in compact heat exchangers and microfluidic systems.

The depletion of fossil fuels and climate change are major worldwide problems. Unlike hydrocarbon resources, solar energy is a clean, inexhaustible, and sustainable power source to meet all of humankind’s energy demands. Solar chimney power plants (SCPPs) having a simple design are capable of generating large‐scale solar powered electricity. The systems have three primary components: a chimney, turbine, and collector. The optimization of the chimney geometry plays a key role in achieving the peak efficiency of SCPPs. In the current work, a three‐dimensional (3D) model on the basis of the Manzanares prototype with a chimney height ( H ) of 194.6 m and radius ( R ) of 5.08 m is developed to identify optimal height for the innovative constricted chimney section configurations via ANSYS FLUENT. The height of the narrowed chimney sections varies as 1/4, 1/8, 1/16, and 1/32 of H for a fixed radius as 1/3 of R . The findings indicate that the power output ( P o ) increases with decreasing the narrowed section height from H /4 to H /32 owing to enhanced mass flow rate and turbine pressure drop. The highest P o of 65.9 kW is gained with the configuration with the height of H /32 and P o enhances by 43.3% compared to the base case at 1000 W/m 2 . The novel equations are improved from the numerical data to estimate the performance features. Besides, the impact of the narrowed section radius on the performance is examined to optimize the dimensions of the constricted section. It is found that a decrease in the narrowed section radius from R /3 to R /5 for a constant height of H /32 leads to a reduction in P o by 1.2% because of a remarkable decrease in mass flow rate. H /32 and R /3 can be optimum height and radius value for the reduced chimney section to augment system efficiency.

This study investigates in-station pressure drop mechanisms in a shale gas gathering system, providing a quantitative basis for flow system optimization. Computational fluid dynamics (CFD) simulations, based on field-measured parameters related to a representative case (a shale gas platform located in Sichuan, China) are conducted to analyze the flow characteristics of specific fittings and manifolds, and to quantify fitting resistance coefficients and manifold inlet interference. The resulting coefficients are integrated into a full-station gathering network model in PipeSim, which, combined with production data, enables evaluation of pressure losses and identification of equivalent pipeline blockages. The results indicate that the resistance coefficients, valid only for fittings under the studied field-specific geometries, are 0.21 for 90° elbows in the fully open position, 0.16 for gate valve passages in the fully open position, and 2.3 for globe valve passages. Manifold interference decreases with lower high-pressure inlet values, whereas inlets farther from the high-pressure side experience stronger disturbances. Interestingly, significant discrepancies between simulated and measured pressure drops reveal partial blockages, corresponding to effective diameter reductions of 65 mm, 38 mm, 44 mm, 38 mm, and 28 mm for Wells 1#, 3#, 5#, and 6#, respectively.

The flow through a 4:1 planar contraction has  been investigated using different rheological models having the same shear viscosity, namely, the inelastic Carreau-Yasuda model (CY), the enhanced Bautista-Manero-Puig (eBMP), and the exponential version of the Phan-Thien/Tanner (PTT). Noticeable discrepancies were observed with the CY model and the eBMP in terms of the velocity profiles along the centerline and in the exit channel (near the end of the geometry) normal to the flow direction. Transient planar extensional viscosity shows a large effect on vortex dynamics although the effect of transient and steady elongation on pressure drop seems negligible. Simulation results allowed gathering that pressure drop is largely influenced by the shear-thinning behavior of the fluid, noticeably affected by elasticity, and less by extensional viscosity. Graphical Abstract

Decisions in the management of aortic stenosis are based on the peak pressure drop, captured by Doppler echocardiography, whereas gold standard catheterization measurements assess the net pressure drop but are limited by associated risks. The relationship between these two measurements, peak and net pressure drop, is dictated by the pressure recovery along the ascending aorta which is mainly caused by turbulence energy dissipation. Currently, pressure recovery is considered to occur within the first 40–50 mm distally from the aortic valve, albeit there is inconsistency across interventionist centers on where/how to position the catheter to capture the net pressure drop. We developed a non-invasive method to assess the pressure recovery distance based on blood flow momentum via 4D Flow cardiovascular magnetic resonance (CMR). Multi-center acquisitions included physical flow phantoms with different stenotic valve configurations to validate this method, first against reference measurements and then against turbulent energy dissipation (respectively n = 8 and n = 28 acquisitions) and to investigate the relationship between peak and net pressure drops. Finally, we explored the potential errors of cardiac catheterisation pressure recordings as a result of neglecting the pressure recovery distance in a clinical bicuspid aortic valve (BAV) cohort of n = 32 patients. In-vitro assessment of pressure recovery distance based on flow momentum achieved an average error of 1.8 ± 8.4 mm when compared to reference pressure sensors in the first phantom workbench. The momentum pressure recovery distance and the turbulent energy dissipation distance showed no statistical difference (mean difference of 2.8 ± 5.4 mm, R2 = 0.93) in the second phantom workbench. A linear correlation was observed between peak and net pressure drops, however, with strong dependences on the valvular morphology. Finally, in the BAV cohort the pressure recovery distance was 78.8 ± 34.3 mm from vena contracta, which is significantly longer than currently accepted in clinical practise (40–50 mm), and 37.5% of patients displayed a pressure recovery distance beyond the end of the ascending aorta. The non-invasive assessment of the distance to pressure recovery is possible by tracking momentum via 4D Flow CMR. Recovery is not always complete at the ascending aorta, and catheterised recordings will overestimate the net pressure drop in those situations. There is a need to re-evaluate the methods that characterise the haemodynamic burden caused by aortic stenosis as currently clinically accepted pressure recovery distance is an underestimation.

Extensional rheology of a variety of linear and branched polymer melts is investigated using entry flow measurements and 15:1 axisymmetric contraction flow simulations. Using a Cogswell model analysis, we show that log−log plots of entrance pressure drop versus wall shear stress display three distinct power-law regimes, the intermediate one of which is observed beyond a critical stress associated with the onset of chain stretching effects. Our observations suggest that this stress threshold is a chain architecture-dependent property characteristic of entangled polymers. Converging flow methods are used to analyze the excess pressure losses to predict the uniaxial extensional viscosity. As the temperature is increased, the progressive shift of the kink to higher strain rates seen in the flow curves can be captured by a proposed Trouton ratio model, where the characteristic time of the fluid is assumed to follow the empirical William–Landel–Ferry (WLF) equation. Experimental pressure drops in converging flows for Weissenberg numbers up to about 10 5 are used to evaluate predictions of an extended generalized Newtonian fluid (GNF-X) model, where a weighted viscosity for mixed flows has recently been derived and a weighting function classifies flows intermediate between shear and shearfree flows. Judging from its success in predicting the nonlinear extensional response of both linear and branched polymers, as well as its ability to differentiate the respective flow patterns, the GNF-X model should be useful for simulations of commercial polymer processing. Graphical abstract