A Machine Learning Approach for the Mean Flow Velocity Prediction in Alluvial Channels

2015 ◽  
Vol 29 (12) ◽  
pp. 4379-4395 ◽  
Author(s):  
Vasileios Kitsikoudis ◽  
Epaminondas Sidiropoulos ◽  
Lazaros Iliadis ◽  
Vlassios Hrissanthou
Author(s):  
Christoph Jörg ◽  
Michael Wagner ◽  
Thomas Sattelmayer

The thermoacoustic stability of gas turbines depends on a balance of acoustic energy inside the engine. While the flames produce acoustic energy, other areas like the impingement cooling system contribute to damping. In this paper, we investigate the damping potential of an annular impingement sleeve geometry embedded into a realistic environment. A cold flow test rig was designed to represent real engine conditions in terms of geometry, and flow situation. High quality data was delivered by six piezoelectric dynamic pressure sensors. Experiments were carried out for different mean flow velocities through the cooling holes. The acoustic reflection coefficient of the impingement sleeve was evaluated at a downstream reference location. Further parameters investigated were the number of cooling holes, and the geometry of the chamber surrounding the impingement sleeve. Experimental results show that the determining parameter for the reflection coefficient is the mean flow velocity through the impingement holes. An increase of the mean flow velocity leads to significantly increased damping, and to low values of the reflection coefficient.


Owing to observational difficulties the distinction between a ‘suspended’ load of solids transported by a stream and a ‘ bed-load ’ has long remained undefined. Recently, however, certain critical experiments have thrown much light on the nature of bed-load transport. In particular, it has been shown that bed-load transport, by saltation, occurs in the absence of fluid turbulence and must therefore be due to a separate dynamic process from that of transport in suspension by the internal eddy motion of a turbulent fluid. It has been further shown that the forward motion of saltating solids is opposed by a frictional force of the same order as the immersed weight of the solids, the friction coefficient approximating to that given by the angle of slip. The maintenance of steady motion therefore requires a predictable rate of energy dissipation by the transporting fluid. The fluid thrust necessary to maintain the motion is shown to be exerted by virtue of a mean slip velocity which is predictable in the same way as, and approxim ates to, the terminal fall velocity of the solid. The mean thrust, and therefore the transport rate of saltating solids, are therefore predictable in terms of the fluid velocity close to the bed, at a distance from it, within the saltation zone, of a ‘centre of fluid thrust’ analogous to the ‘centre of pressure’. This velocity, which is not directly measurable in water streams, can be got from a knowledge of stream depth and mean flow velocity. Thus a basic energy equation is obtained relating the rate of transporting work done to available fluid transporting power. This is shown to be applicable to the transport both of wind-blown sand, and of water-driven solids of all sizes and larger than that of medium sand. Though the mean flow velocity is itself unpredictable, the total stream power, which is the product of this quantity times the bed shear stress, is readily measurable. But since the mean flow velocity is an increasing function of flow depth, the transport of solids expressed in terms of total stream power must decrease with increasing flow depth/grain size ratio. This considerable variation with flow depth has not been previously recognised. It explains the gross inconsistencies found in the existing experimental data. The theoretical variation is shown to approximate very closely to that found in recent critical experiments in which transport rates were measured at different constant flow depths. The theory, which is largely confirmed by these and other earlier experiments, indicates that suspension by fluid turbulence of mineral solids larger than those of medium sands does not become appreciable until the bed shear stress is increased to a value exceeding 12 times its threshold value for the bed material considered. This range of unsuspended transport decreases rapidly, however, as the grain size is reduced till, at a certain critical size, suspension should occur at the threshold of bed movement.


2020 ◽  
Vol 17 (5) ◽  
pp. 1221-1236
Author(s):  
Hui-Huang Fang ◽  
Shu-Xun Sang ◽  
Shi-Qi Liu

Abstract The three-dimensional (3D) structures of pores directly affect the CH4 flow. Therefore, it is very important to analyze the 3D spatial structure of pores and to simulate the CH4 flow with the connected pores as the carrier. The result shows that the equivalent radius of pores and throats are 1–16 μm and 1.03–8.9 μm, respectively, and the throat length is 3.28–231.25 μm. The coordination number of pores concentrates around three, and the intersection point between the connectivity function and the X-axis is 3–4 μm, which indicate the macro-pores have good connectivity. During the single-channel flow, the pressure decreases along the direction of CH4 flow, and the flow velocity of CH4 decreases from the pore center to the wall. Under the dual-channel and the multi-channel flows, the pressure also decreases along the CH4 flow direction, while the velocity increases. The mean flow pressure gradually decreases with the increase of the distance from the inlet slice. The change of mean flow pressure is relatively stable in the direction horizontal to the bedding plane, while it is relatively large in the direction perpendicular to the bedding plane. The mean flow velocity in the direction horizontal to the bedding plane (Y-axis) is the largest, followed by that in the direction horizontal to the bedding plane (X-axis), and the mean flow velocity in the direction perpendicular to the bedding plane is the smallest.


2009 ◽  
Vol 111 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Satoshi Tateshima ◽  
Kazuo Tanishita ◽  
Yasuhiro Hakata ◽  
Shin-ya Tanoue ◽  
Fernando Viñuela

Object Development of a flexible self-expanding stent system and stent-assisted coiling technique facilitates endovascular treatment of wide-necked brain aneurysms. The hemodynamic effect of self-expandable stent placement across the neck of a brain aneurysm has not been well documented in patient-specific aneurysm models. Methods Three patient-specific silicone aneurysm models based on clinical images were used in this study. Model 1 was constructed from a wide-necked internal carotid artery–ophthalmic artery aneurysm, and Models 2 and 3 were constructed from small wide-necked middle cerebral artery aneurysms. Neuroform stents were placed in the in vitro aneurysm models, and flow structures were compared before and after the stent placements. Flow velocity fields were acquired with particle imaging velocimetry. Results In Model 1, a clockwise, single-vortex flow pattern was observed in the aneurysm dome before stenting was performed. There were multiple vortices, and a very small fast flow stream was newly formed in the aneurysm dome after stenting. The mean intraaneurysmal flow velocity was reduced by ~ 23–40%. In Model 2, there was a clockwise vortex flow in the aneurysm dome and another small counterclockwise vortex in the tip of the aneurysm dome before stenting. The small vortex area disappeared after stenting, and the mean flow velocity in the aneurysm dome was reduced by 43–64%. In Model 3, a large, counterclockwise, single vortex was seen in the aneurysm dome before stenting. Multiple small vortices appeared in the aneurysm dome after stenting, and the mean flow velocity became slower by 22–51%. Conclusions The flexible self-expandable stents significantly altered flow velocity and also flow structure in these aneurysms. Overall flow alterations by the stent appeared favorable for the long-term durability of aneurysm embolization. The possibility that the placement of a low-profile self-expandable stent might induce unfavorable flow patterns such as a fast flow stream in the aneurysm dome cannot be excluded.


2012 ◽  
Vol 229-231 ◽  
pp. 22-25
Author(s):  
Zhong Qiang Zhang ◽  
Guang Gui Cheng ◽  
Jian Ning Ding ◽  
Zhi Yong Ling

Molecular dynamics simulations are carried out to explore the fluid flows in parallel-plate nanochannels. A “channel moving” pressure-driven model is utilized to study the planar Poiseuille flows. Considering the slip boundary conditions, relationships among the pressure gradient, mean flow velocity and the channel width are investigated to couple the atomistic regime to continuum. The results show that the mean flow velocity almost linearly increases with the increase of the pressure gradient. The slope of the linear relationship between the pressure gradient and the mean flow velocity is nonlinearly decreased with increasing the channel width. The results indicate that the approximate accuracy is reduced with decreasing the channel width while the pressure-driven flows confined in nanochannels are approximately described by the Navier-Stokes equations.


2018 ◽  
Vol 45 (5) ◽  
pp. E8 ◽  
Author(s):  
Todd C. Hollon ◽  
Adish Parikh ◽  
Balaji Pandian ◽  
Jamaal Tarpeh ◽  
Daniel A. Orringer ◽  
...  

OBJECTIVEPituitary adenomas occur in a heterogeneous patient population with diverse perioperative risk factors, endocrinopathies, and other tumor-related comorbidities. This heterogeneity makes predicting postoperative outcomes challenging when using traditional scoring systems. Modern machine learning algorithms can automatically identify the most predictive risk factors and learn complex risk-factor interactions using training data to build a robust predictive model that can generalize to new patient cohorts. The authors sought to build a predictive model using supervised machine learning to accurately predict early outcomes of pituitary adenoma surgery.METHODSA retrospective cohort of 400 consecutive pituitary adenoma patients was used. Patient variables/predictive features were limited to common patient characteristics to improve model implementation. Univariate and multivariate odds ratio analysis was performed to identify individual risk factors for common postoperative complications and to compare risk factors with model predictors. The study population was split into 300 training/validation patients and 100 testing patients to train and evaluate four machine learning models using binary classification accuracy for predicting early outcomes.RESULTSThe study included a total of 400 patients. The mean ± SD patient age was 53.9 ± 16.3 years, 59.8% of patients had nonfunctioning adenomas and 84.7% had macroadenomas, and the mean body mass index (BMI) was 32.6 ± 7.8 (58.0% obesity rate). Multivariate odds ratio analysis demonstrated that age < 40 years was associated with a 2.86 greater odds of postoperative diabetes insipidus and that nonobese patients (BMI < 30) were 2.2 times more likely to develop postoperative hyponatremia. Using broad criteria for a poor early postoperative outcome—major medical and early surgical complications, extended length of stay, emergency department admission, inpatient readmission, and death—31.0% of patients met criteria for a poor early outcome. After model training, a logistic regression model with elastic net (LR-EN) regularization best predicted early postoperative outcomes of pituitary adenoma surgery on the 100-patient testing set—sensitivity 68.0%, specificity 93.3%, overall accuracy 87.0%. The receiver operating characteristic and precision-recall curves for the LR-EN model had areas under the curve of 82.7 and 69.5, respectively. The most important predictive variables were lowest perioperative sodium, age, BMI, highest perioperative sodium, and Cushing’s disease.CONCLUSIONSEarly postoperative outcomes of pituitary adenoma surgery can be predicted with 87% accuracy using a machine learning approach. These results provide insight into how predictive modeling using machine learning can be used to improve the perioperative management of pituitary adenoma patients.


2021 ◽  
Vol 9 ◽  
Author(s):  
Viviana Clavería ◽  
Philippe Connes ◽  
Luca Lanotte ◽  
Céline Renoux ◽  
Philippe Joly ◽  
...  

Red blood cells in sickle cell anemia (sRBC) are more heterogeneous in their physical properties than healthy red blood cells, spanning adhesiveness, rigidity, density, size, and shape. sRBC with increased adhesiveness to the vascular wall would trigger vaso-occlusive like complications, a hallmark of sickle cell anemia. We investigated whether segregation occurs among sRBC flowing in micron-sized channels and tested the impact of aggregation on segregation. Two populations of sRBC of different densities were separated, labeled, and mixed again. The mixed suspension was flowed within glass capillary tubes at different pressure-drops, hematocrit, and suspending media that promoted or not cell aggregation. Observations were made at a fixed channel position. The mean flow velocity was obtained by using the cells as tracking particles, and the cell depleted layer (CDL) by measuring the distance from the cell core border to the channel wall. The labeled sRBC were identified by stopping the flow and scanning the cells within the channel section. The tube hematocrit was estimated from the number of fluorescence cells identified in the field of view. In non-aggregating media, our results showed a heterogeneous distribution of sRBC according to their density: low-density sRBC population remained closer to the center of the channel, while the densest cells segregated towards the walls. There was no impact of the mean flow velocity and little impact of hematocrit. This segregation heterogeneity could influence the ability of sRBC to adhere to the vascular wall and slow down blood flow. However, promoting aggregation inhibited segregation while CDL thickness was enhanced by aggregation, highlighting a potential protective role against vaso-occlusion in patients with sickle cell anemia.


2017 ◽  
Vol 26 (9) ◽  
pp. 999-1011
Author(s):  
Se-Chang Yang ◽  
◽  
Yong-Seok Kim ◽  
Sung-Kee Yang ◽  
Myung-Soo Kang ◽  
...  

Author(s):  
Volker Hans

Measurements of flow velocity with cross correlation functions of ultrasonic signals show that the travelling time of structures deviates from the mean flow velocity. This difference usually is explained by the difference between the line integral of measurement and the area integral of the mean flow velocity. A comparison of the probability distribution of velocity components shows that the most frequent components in the fluid are in accordance with the travelling time of structures. The explanation is given by systems theory. In vortex shedding flow meters an ultrasonic wave is modulated by vortices behind a bluff body. The frequency of the vortices is proportional to the flow velocity. It depends on the size and arrangement of bluff bodies. As ultrasound is very sensitive to all kinds of modulating effects the size of bluff bodies can be drastically reduced in comparison to measurements with pressure sensors. Additionally the sensitivity can be increased, pressure losses behind the bluff body are considerably decreasing.


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