Investigation of Complex Characteristics of Waterjet Propulsion Device with Intake Grid

The intake grid is always installed technically to protect the impeller at the entrance of the waterjet propulsion device’s inlet duct affecting its performance. Therefore, this study discussed the complex features of the circular, rectangular, and streamlined intake grid. Consistent geometry size of the intake grid mentioned above is to be maintained to guarantee the identical flow capacity at the entrance of inlet duct. Using experimental and simulated method, the outcomes are drawn as below. Rather than the circular and rectangular intake grid, the streamlined intake grid can improve the hydraulic performance of the waterjet propulsion device. The numerical method is proved to be correct as the consistence of the hydraulic characteristic between the test and simulated results. The causes of hydraulic loss in the contraction segment and straight pipe segment are the intake grid and the inflow velocity, respectively; meanwhile, the loss in the belt pipe segment owes to the vortex, flow separation, and impact on the back. The intake grid has a positive effect on the depth of the inlet velocity profile, but a negative effect on the width of it. The intake grid installation results in thrust reduction, the progress of velocity-weighted average angle, and the regress of axial velocity uniformity. The performance of waterjet propulsion device is complex and evaluated by the hydraulic performance index (HPI), thrust performance index (TPI), and characteristic of flow pattern index (CFPI). Based on the three evaluation indexes, the streamlined scheme is raised to be the recommended scheme.

Vibration Analysis in Multiple Close Proximity Flow Restrictions

In this study, a segment of water conveyance system at a chemical manufacturing facility is under investigation. The pipe segment under investigation conveys a daily average flow of five million gallons of water per day (MGD) from the river to a water treatment plant. The exact age of the pipe system is unknown as limited construction or maintenance information exists. The study area is a pipe segment near the treatment plant where three flow restrictions exist within a 30-foot distance bounded by a T-junction and a water filtration plant. These restrictions include two self-actuated butterfly valves and an orifice plate on a 16-inch diameter steel pipe, buried approximately three feet below ground surface. When standing in the study area, heavy vibrations are felt at the ground surface. The valves and orifice plate are to control flowrate and reduce pressure from 80 PSI to 45PSI as the flow enters the water treatment plant. Flow restrictions in close proximity can cause cavitation, water hammer and other flow phenomena within a pipe system. This can result in excessive wear of the pipe’s inner walls and valves which may compromise the structural integrity and/or function of the system. Computational fluid dynamics (CFD) software is a useful tool for determining if the conditions for the various flow phenomena are present in a system. The flow characteristics were numerically calculated in MATLAB then computationally modeled in AFT Fathom. The purpose of the numerical analysis was to describe the stability of the fluid flow at discrete points in the pipe network and identify the network segments with significantly unstable flow profiles. The purpose of the AFT Fathom CFD model purpose was to provide a continuous simulation of the flow stability in the pipe segment and provide a more robust description of the flow profiles in the network. While Fathom cannot explicitly predict cavitation or water hammer, the kinematic parameters produced by the Fathom model and the physical conditions observed in the study indicate that water hammer is likely occurring.

Study on the Distribution of Submarine Pipeline Corrosion Defects Based on Internal Inspection Data and Data Mining Method

Submarine pipelines in the sea are applied for oil, gas, water and mixed transportation. Among them, 91% of the pipes contain CO2. Here, based on the existing pipeline internal inspection data of submarine pipeline, the APRIORI algorithm and least-square-support-vector-machine (LSSVM) are applied to analyze the distribution rules and defect characteristics of internal defects along the pipeline. The corrosion defects are divided into 7 types and the pipeline section is divided into 12 intervals. Also, the pipe segment has been defined as J (general pipe), W (weld) and C (close to weld). The contents include the analysis of the characteristics and types of defects, the distribution of defects along the pipe, the severity of the corrosion defects, the size characteristics of defects, and the comparison of the data detected in multiple rounds. The defect depth of four kinds of pipelines is mostly 10%–20% of the wall thickness, hereby the severity of defects is studied via the percentage distribution of corrosion depth. The data of multi-round inspection shows that the corrosions in the mixed pipeline are active and the defects are increasing. The methods and results in this paper can be employed to predict the most likely defect type, mileage location, clock orientation, and shape size of submarine pipeline corrosion. This is helpful for the integrity management of submarine pipelines.

Relaminarising pipe flow by wall movement

Following the recent observation that turbulent pipe flow can be relaminarised by a relatively simple modification of the mean velocity profile, we here carry out a quantitative experimental investigation of this phenomenon. Our study confirms that a flat velocity profile leads to a collapse of turbulence and in order to achieve the blunted profile shape, we employ a moving pipe segment that is briefly and rapidly shifted in the streamwise direction. The relaminarisation threshold and the minimum shift length and speeds are determined as a function of Reynolds number. Although turbulence is still active after the acceleration phase, the modulated profile possesses a severely decreased lift-up potential as measured by transient growth. As shown, this results in an exponential decay of fluctuations and the flow relaminarises. While this method can be easily applied at low to moderate flow speeds, the minimum streamwise length over which the acceleration needs to act increases linearly with the Reynolds number.

Application of Machine Learning to Distributed Temperature Sensing (DTS) Systems

The timely detection of small leaks from liquid pipelines poses a significant challenge for pipeline operations. One technology considered for continual monitoring is distributed temperature sensing (DTS), which utilizes a fiber-optic cable to provide distributed temperature measurements along a pipeline segment. This measurement technique allows for a high accuracy of temperature determination over long distances. Unexpected deviations in temperature at any given location can indicate various physical changes in the environment, including contact with a heated hydrocarbon due to a pipeline leak. The signals stemming from pipeline leaks may not be significantly greater than the noise in the DTS measurements, so care must be taken to configure the system in a manner that can detect small leaks while rejecting non-leak temperature anomalies. There are many factors that influence the frequency and intensity of the backscattered optical signal. This can result in noise in the fine-grained temperature sensing data. Thus, the DTS system must be tuned to the nominal temperature profile along the pipe segment. This customization allows for significant sensitivity and can utilize different leak detection thresholds at various locations based on normal temperature patterns. However, this segment-specific tuning can require a significant amount of resources and time. Additionally, this configuration exercise may have to be repeated as pipeline operating conditions change over time. Thus, there is a significant need and interest in advancing existing DTS processing techniques to enable the detection of leaks that today go undetected by DTS due to their signal response being too close to the noise floor and/or requiring significant resources to achieve positive results. This paper discusses the recent work focused on using machine learning (ML) techniques to detect leak signatures. Initial proof-of-concept results provide a more robust methodology for detecting leaks and allow for the detection of smaller leaks than are currently detectable by typical DTS systems, with low false alarm rates. A key use of ML approaches is that the system can “learn” about a given pipeline on its own without the need to utilize resources for pipeline segment-specific tuning. The potential to have a self-taught system is a powerful concept, and this paper discusses some key initial findings from applying ML-based techniques to optimize leak detection capabilities of an existing DTS system.

Numerical Analysis and Strength Evaluation of an Exposed River Crossing Pipeline with Casing Under Flood Load

Pipelines in service always experience complicated loadings induced by operational and environmental conditions. Flood is one of the common natural hazard threats for buried steel pipelines. One exposed river crossing X70 gas pipeline induced by flood erosion was used as a prototype for this study. A mechanical model was established considering the field loading conditions. Morison equations were adopted to calculate distributional hydrodynamic loads on spanning pipe caused by flood flow. Nonlinear soil constraint on pipe was considered using discrete nonlinear soil springs. An explicit solution of bending stiffness for pipe segment with casing was derived and applied to the numerical model. The von Mises yield criterion was used as failure criteria of the X70 pipe. Stress behavior of the pipe were analyzed by a rigorous finite element model established by the general-purpose Finite-Element package ABAQUS, with 3D pipe elements and pipe-soil interaction elements simulating pipe and soil constraints on pipe, respectively. Results show that, the pipe is safe at present, as the maximum von Mises stress in pipe with the field parameters is 185.57 MPa. The critical flow velocity of the pipe is 5.8 m/s with the present spanning length. The critical spanning length of the pipe is 467 m with the present flow velocity. The failure pipe sections locate at the connection point of the bare pipe and the pipe with casing or the supporting point of the bare pipe on riverbed.

Probability of network disconnection of water distribution system for maintenance prioritization

Unexpected pipe breaks in municipal water distribution systems may cause isolation of parts of the network or reduction of redundancy, leading to reduced system reliability. While a network with less redundancy implies less tolerance to further breaks, the isolation of nodes explicitly indicates unavailability of the system to service the nodes. This paper presents a method of measuring these topological changes using algebraic connectivity (AC). AC is a parameter that can be used to assess robustness and redundancy of a network. The changes in AC associated with pipe breaks are compared with the AC of intact networks to assess whether the removal of the pipe causes reduction of redundancy or isolation in the network. An AC of 1.5625 × 10−5 is calculated for an intake of a medium-sized water distribution network (WDN). The fluctuation in AC is used to assess the criticality of each pipe segment to the overall structure of the network. This study also evaluates the failure probability of the WDN, assuming that the network failure probability is equivalent to the probability of isolation of parts of the system due to pipe breaks. The breaks leading to the failure are identified using the method of the minimum cut-sets.

Determination and Application of Comprehensive Specific Frictional Resistance in Heating Engineering

In this study, we analyze the deficiencies of specific frictional resistance in heating engineering. Based on economic specific frictional resistance, we put forward the concept of comprehensive specific frictional resistance, which considers the multiple factors of technology, economy, regulation modes, pipe segment differences, and medium pressure. Then, we establish a mathematical model of a heating network across its lifespan in order to develop a method for determining the comprehensive specific frictional resistance. Relevant conclusions can be drawn from the results. As an application, we have planned the heating engineering for Yangyuan County in China, which demonstrates the feasibility and superiority of the method.