Effect of Liquid and Gas Velocities on Magnitude and Location of Maximum Erosion in U-Bend

Solid particle erosion is a micromechanical process that is influenced by flow geometry, material of the impacting surface, impact angle, particle size and shape, particle velocity, flow condition and fluid properties. Among the various factors, particle size and velocity have been considered to be the most important parameters that cause erosion. Particle size and velocity are influenced by surrounding flow velocities and carrying fluid properties. Higher erosion rates have been observed in gas-solid flow in geometries where the flow direction changes rapidly, such as elbows, tees, valves, etc, due to local turbulence and unsteady flow behaviors. This paper presents the results of a Computational fluid dynamic (CFD) simulation of dilute gas-solid flow through a U-Bend and the dynamics behavior of entrained solid particles in the flow. The effect of liquid and gas velocities on location of erosion were investigated for 50, 100, 150, 200, 250 and 300 microns sand particles. Three different fluid velocities of 15, 30.48 and 45 m/s were used in the CFD analysis. The magnitude and location of erosion presented in the paper can be used to determine the areas susceptible to maximum erosive wear in elbows and U-bends, along with corresponding rate of metal loss in these areas.

Numerical Investigation on Detonation Wave through U-bend

Pulse detonation engine (PDE) is expected for a next-generation propulsion system. PDE is a promising engine that can generates power and thrust by using intermittent detonation. Promotion of deflagration to detonation transition (below DDT) is a key issue to realize this system. PDE has experimentally been investigated, and it was confirmed that detonation tubes with U-shaped bends are useful for fast DDT. However, the mechanism of DDT promotion due to U-bends has not been well clarified. In the present study, the influence of a U-bend on detona-tion wave propagation is researched with computational fluid dynamics (CFD). The numerical results show that detonation wave disappears once near the U-bend inlet and restarts after passing through it. In addition, it was found that the use of the U-bend with small channel width and curvature radius can induce fast DDT.

Two-Phase Flow Pressure Drop of Liquid Nitrogen Boiling in the Straight Section Downstream of U-Bend

The gas-liquid(two-phase) flow pressure drop of liquid nitrogen boiling in the straight section downstream of U-bend is investigated experimentally. The mass flux ranges from 32 to 280 kg/(m2· s). The inlet pressure of U-tube is from 140 to 272 kPa. And the curvature ratio is from 6.67 to 15. The tube wall including the U-bend is heated uniformly and the heat flux ranges from 0 to 22 kW/m2. The tube with higher inlet pressure has higher pressure drop in the downstream section of the bend. The bended degree of the U-bend influences the pressure drop in the downstream straight section of U-bend. A new correlation taking the effect of the secondary flow into account is proposed for the two-phase slip speed ratio. The pressure drop in the straight section downstream of U-bend calculated by the new correlation agrees well with experimental measurements.

Comparison between conventional and deep learning-based surrogate models in predicting convective heat transfer performance of U-bend channels

Deep neural networks are efficient methods to achieve real-time visualization of physics fields.The main concerns that prevented deep learning from being implemented in the field of energy conversion were the risks of overfitting and the lack of data.Therefore,it is necessary to evaluate different kinds of surrogate modeling methods and provide guidelines for designers to choose models.In this study,three conventional models(Artificial Neural Network,Radial Bias Function,and Kriging),and two deep learning-based models(Convolutional Neural Network and Conditional Generative Adversarial Neural Network)were established to predict the flow and heat transfer performance of a U-bend with variable geometries.The models were detailly compared in terms of the single-point prediction accuracy,response accuracy,sensitivity to sample size,and other characteristics of interest.Results showed that the conventional models had slightly higher single point accuracy and the relative error of pressure loss and heat transfer were within±6.6%and±5.7%respectively,while those of the deep learning-based models were within±8.0%and±6.3%respectively.Nevertheless,the deep learning-based models had higher response accuracy and could reconstruct the distributions of surface pressure and wall heat flux with the pixel-wise absolute error within±2.0 Pa and±45 W/m^(2) respectively.The results indicated that deep learning was a promising surrogate modeling approach due to its acceptable prediction error and ability to reconstruct physical fields.This effort was expected to serve as a guide for establishing more reliable data-driven surrogate models for energy conversion and heat transfer problems.

Stress corrosion cracking failure of X80 carbon steel U-b end cause d by Desulfovibrio vulgaris biocorrosion

Sulfate reducing bacteria(SRB)are widely present in oil and gas industry,causing pitting corrosion on pipeline steel.Stress corrosion cracking(SCC)often occurs in the presence of mechanical stress before pit-ting perforation failure,leading to economic losses and even catastrophic accidents.In this study,stress distribution simulation using the finite element method(FEM),corrosion analysis techniques and elec-trochemical corrosion measurements were employed to investigate the SCC mechanism of X80 pipeline steel caused by Desulfovibrio vulgaris,which is a common SRB strain used in microbiologically influenced corrosion(MIC)studies.It was found that D.vulgaris MIC caused sharp microcracks on an X80 U-bend coupon after only 2 weeks of immersion at 37℃in the deoxygenated ATCC 1249 culture medium inocu-lated with D.vulgaris.The X80 U-bend coupon’s weight loss-based uniform corrosion rate for the 12 cm^(2)surface was 60%of that for the unstressed flat square coupon(2.3 mg cm^(−2)vs.3.8 mg cm^(−2)).This was likely because the square coupon had wide MIC pits,providing a larger effective surface area for more sessile cells(4.2×10^(8)cells cm^(−2)on square coupon vs.2.4×10^(8)cells cm^(−2)on U-bend coupon)to attach and harvest more electrons.An SCC failure occurred on an X80 U-bend pre-cracked at the outer bottom after a 6-week immersion in the D.vulgaris broth.Apart from MIC damage,this could also be because D.vulgaris metabolism increased the availability hydrogen atoms on the steel surface,and promoted the diffusion of hydrogen atoms into the metal lattice,thus increasing the brittleness of the steel.