Investigation of Condensate Retention on Horizontal Pin-Fin Tubes Using Water-Propanol Mixture

Condensers are an integral part of air conditioning systems. The thermal efficiency of condensers solely depends on the rate of heat transfer from the cooling medium. Fin tubes are extensively used for heat transfer applications due to their enhanced heat transfer capabilities. Fins provide appreciable drainage because surface tension produces pressure gradients. Much research, contributed by several scientists, has focused on adjusting parameters, such as fin design, flow rates and retention angles. In this study, a setup with an observing hole was used to inspect the influence on retention angle of adjusting the flow rates of the fluid. The increase in retention angle was examined using several velocities and concentration mixtures. Pin-fin tubes were used to obtain coherent results using a photographic method. The experimental setup was designed to monitor the movement of fluid through the apparatus. The velocity was varied using dampers and visibility was enhanced using dyes. Photographs were taken at 20 m/s velocities after every 20 s. and 0.1% concentration and the flooding point observed. The experimental results were verified by standard observation which showed little variation at lower velocity. For water/water-propanol mixtures, a vapor velocity of 12 m/s and concentration ratio of 0.04% was the optimal combination to achieve useful improvement in retention angle. With increase of propanol from 0% to 0.04%, the increase in retention angle was greater compared to 0.04% to 0.1%. For velocities ranging from 0 to 12 m/s, the increase in retention angle was significant. A sharp change was observed for concentration ratios ranging from 0.01% to 0.05% compared to 0.05% to 0.1%.

Effects of an impermeable layer on pore pressure response to tsunami-like inundation

Tsunami hazards have been observed to cause soil instability resulting in substantial damage to coastal infrastructure. Studying this problem is difficult owing to tsunamis’ transient, non-uniform and large loading characteristics. To create realistic tsunami conditions in a laboratory environment, we control the body force using a centrifuge facility. With an apparatus specifically designed to mimic tsunami inundation in a scaled-down model, we examine the effects of an embedded impermeable layer on soil instability: the impermeable layer represents a man-made pavement, a building foundation, a clay layer and alike. The results reveal that the effective vertical soil stress is substantially reduced at the underside of the impermeable layer. During the sudden runup flow, this instability is caused by a combination of temporal dislocation of soil grains and an increase in pore pressure under the impermeable layer. The instability during the drawdown phase is caused by the development of excess pore-pressure gradients, and the presence of the impermeable layer substantially enhances the pressure gradients leading to greater soil instability. The laboratory results demonstrate that the presence of an impermeable layer plays an important role in weakening the soil resistance under tsunami-like rapid runup and drawdown processes.

Physiological Mechanisms Regulating Lens Transport

The transparency and refractive properties of the lens are maintained by the cellular physiology provided by an internal microcirculation system that utilizes spatial differences in ion channels, transporters and gap junctions to establish standing electrochemical and hydrostatic pressure gradients that drive the transport of ions, water and nutrients through this avascular tissue. Aging has negative effects on lens transport, degrading ion and water homeostasis, and producing changes in lens water content. This alters the properties of the lens, causing changes in optical quality and accommodative amplitude that initially result in presbyopia in middle age and ultimately manifest as cataract in the elderly. Recent advances have highlighted that the lens hydrostatic pressure gradient responds to tension transmitted to the lens through the Zonules of Zinn through a mechanism utilizing mechanosensitive channels, multiple sodium transporters respond to changes in hydrostatic pressure to restore equilibrium, and that connexin hemichannels and diverse intracellular signaling cascades play a critical role in these responses. The mechanistic insight gained from these studies has advanced our understanding of lens transport and how it responds and adapts to different inputs both from within the lens, and from surrounding ocular structures.

Pulmonary Interstitial Matrix and Lung Fluid Balance From Normal to the Acutely Injured Lung

This review analyses the mechanisms by which lung fluid balance is strictly controlled in the air-blood barrier (ABB). Relatively large trans-endothelial and trans-epithelial Starling pressure gradients result in a minimal flow across the ABB thanks to low microvascular permeability aided by the macromolecular structure of the interstitial matrix. These edema safety factors are lost when the integrity of the interstitial matrix is damaged. The result is that small Starling pressure gradients, acting on a progressively expanding alveolar barrier with high permeability, generate a high transvascular flow that causes alveolar flooding in minutes. We modeled the trans-endothelial and trans-epithelial Starling pressure gradients under control conditions, as well as under increasing alveolar pressure (Palv) conditions of up to 25 cmH2O. We referred to the wet-to-dry weight (W/D) ratio, a specific index of lung water balance, to be correlated with the functional state of the interstitial structure. W/D averages ∼5 in control and might increase by up to ∼9 in severe edema, corresponding to ∼70% loss in the integrity of the native matrix. Factors buffering edemagenic conditions include: (i) an interstitial capacity for fluid accumulation located in the thick portion of ABB, (ii) the increase in interstitial pressure due to water binding by hyaluronan (the “safety factor” opposing the filtration gradient), and (iii) increased lymphatic flow. Inflammatory factors causing lung tissue damage include those of bacterial/viral and those of sterile nature. Production of reactive oxygen species (ROS) during hypoxia or hyperoxia, or excessive parenchymal stress/strain [lung overdistension caused by patient self-induced lung injury (P-SILI)] can all cause excessive inflammation. We discuss the heterogeneity of intrapulmonary distribution of W/D ratios. A W/D ∼6.5 has been identified as being critical for the transition to severe edema formation. Increasing Palv for W/D > 6.5, both trans-endothelial and trans-epithelial gradients favor filtration leading to alveolar flooding. Neither CT scan nor ultrasound can identify this initial level of lung fluid balance perturbation. A suggestion is put forward to identify a non-invasive tool to detect the earliest stages of perturbation of lung fluid balance before the condition becomes life-threatening.

Buoyancy-driven algebraic (localised) boundary-layer disturbances

We show that a new class of steady linear eigenmodes exist in the Falkner–Skan boundary layer, associated with an algebraically developing, thermally coupled three-dimensional perturbation that remains localised in the spanwise direction. The dominant mode has a weak temperature difference that decays (algebraically) downstream, but remains sufficient (for favourable pressure gradients that are below a critical level) to drive an algebraically growing disturbance in the velocity field. We determine the critical Prandtl number and pressure gradient parameter required for downstream algebraic growth. We also march the nonlinear boundary-region equations downstream, to demonstrate that growth of these modes eventually gives rise to streak-like structures of order-one aspect ratio in the cross-sectional plane. Furthermore, this downstream flow can ultimately become unstable to a two-dimensional Rayleigh instability at finite amplitudes.

A Machine Learning Approach to Predict the Pressure Gradient of Different Oil-Water Flow Patterns in a Horizontal Wellbore

Fluid pressure gradient in a wellbore plays a significant role to efficiently transport between source and separator facilities. The mixture of two immiscible fluids manifests in various flow patterns such as stratified, dispersed, intermittent, and annular flow, which can significantly influence the fluid’s pressure gradient. However, previous studies have only used limited flow patterns when developing their data-driven model. The aim of this study is to develop a uniform data-driven model using machine-learning (ML) algorithms that can accurately predict the pressure gradient for the oil-water flow with two stratified and seven dispersed flow patterns in a horizontal wellbore. Two different machine-learning algorithms, Artificial Neural Network (ANN) and Random Forest (RF), were employed to predict the pressure gradients. A total of 662 experimental points from nine different flow patterns were extracted from five sources that include twelve variables for different physical properties of oil-water, wellbore’s surface roughness, and input diameter. The variables are entrance length to diameter ratio, oil and water viscosity, density, velocity, and surface tension, between oil and water surface tension, surface roughness, input diameter, and flow pattern. The algorithms’ performance was evaluated using median absolute percentage error (MdAPE) and root mean squared error (RMSE). A repeated train-test split strategy was used where the final MdAPE and RMSE were computed from the average of all repetitions. The MdAPE and RMSE for the prediction of pressure gradients are 13.89% and 0.138 kPa/m using RF and 12.17% and 0.088 kPa/m using ANN, respectively. The ML algorithms’ ability to model the pressure gradient is demonstrated using measured vs. predicted analysis where the experimental data points are mostly located in close proximity of the diagonal line, indicating a suitable generalization of the models. Comparing the performance between RF and ANN shows that the latter algorithm’s prediction accuracy is significantly better (p<0.01).

DESIGN OF LOW-DRAG AUTONOMOUS UNDERWATER VEHICLES AND FLOW CONTROL

Design of autonomous underwater vehicles (AUV) met the opposite challenges. Their achievable route can be enhanced with drag reduction due to an increase of AUV slenderness. However, blunt short AUV have others operational advantages. The possibility to design low-drag bodies for Reynolds numbers employed by contemporary AUV (2×106<Re<107) is based on a combination of known facts. First, blunt bodies experience a drag crisis associated with laminar-turbulent transition in their boundary layers and some boundary layer suction additionally reduces their drag. Second, the transition can be delayed till much higher Re for bodies without adverse pressure gradients over their forward and medium parts. Suction on sterns of such bodies allows for the very substantial drag reduction. Several body shapes with distributed suction with extremely low slenderness (L/B<1.5) are presented. Their drag coefficients are between 0.007 and 0.02, whereas for ellipsoid of the same slenderness it exceeds 0.08.