Avoiding Sedimentation and Air Entrainment in Pump Sump for Wet Pit Pumping Stations

2015 ◽  
Author(s):  
Raja Abou Ackl ◽  
Andreas Swienty ◽  
Flemming Lykholt-Ustrup ◽  
Paul Uwe Thamsen
Keyword(s):  
Physical Model ◽  
Air Entrainment ◽  
Flow Patterns ◽  
Operating Conditions ◽  
Design Criteria ◽  
Flow Conditions ◽  
Pumping Station ◽  
Pumping Stations ◽  
Pump Sump ◽  
Pump Stations

In many places lifting systems represent central components of wastewater systems. Pumping stations with a circular wet-pit design are characterized by their relatively small footprint for a given sump volume as well as their relatively simple construction technique [1]. This kind of pumping stations is equipped with submersible pumps. These are located in this case directly in the wastewater collection pit. The waste water passes through the pump station untreated and loaded with all kind of solids. Thus, the role of the pump sump is to provide an optimal operating environment for the pumps in addition to the transportation of sewage solids. Understanding the effects of design criteria on pumping station performance is important to fulfil the wastewater transportation as maintenance-free and energy efficient as possible. The design of the pit may affect the overall performance of the station in terms of poor flow conditions inside the pit, non-uniform und disturbed inflow at the pump inlet, as well as air entrainment to the pump. The scope of this paper is to evaluate the impact of various design criteria and the operating conditions on the performance of pump stations concerning the air entrainment to the pump as well as the sedimentation inside the pit. This is done to provide documentation and recommendations of the design and operating of the station. The investigated criteria are: the inflow direction, and the operating submergence. In this context experiments were conducted on a physical model of duplex circular wet pit wastewater pumping station. Furthermore the same experiments were reproduced by numerical simulations. The physical model made of acrylic allowed to visualize the flow patterns inside the sump at various operating conditions. This model is equipped with five different inflow directions, two of them are tangential to the pit and the remaining three are radial in various positions relative to the pumps centerline. Particles were used to enable the investigation of the flow patterns inside the pit to determine the zones of high sedimentation risk. The air entrainment was evaluated on the model test rig by measuring the depth, the width and the length of the aerated region caused by the plunging water jet and by observing the air bubbles entering the pumps. The starting sump geometry called baseline geometry is simply a flat floor. The tests were done at all the possible combinations of inflow directions, submergence, working pump and operating flow. The ability of the numerical simulation to give a reliable prediction of air entrainment was assessed to be used in the future as a tool in scale series to define the scale effect as well as to analyze the flow conditions inside the sump and to understand the air entrainment phenomenon. These simulations were conducted using the geometries of the test setup after generating the mesh with tetrahedral elements. The VOF multiphase model was applied to simulate the interaction of the liquid water phase and the gaseous air phase. On the basis of the results constructive suggestions are derived for the design of the pit, as well as the operating conditions of the pumping station. At the end recommendations for the design and operating conditions are provided.

scholarly journals Robust model for estimating pumping station characteristics and sewer flows from standard pumping station data

2019 ◽  
Vol 79 (9) ◽  
pp. 1739-1745
Author(s):  
Martin Fencl ◽  
Morten Grum ◽  
Morten Borup ◽  
Peter Steen Mikkelsen
Keyword(s):  
Optimization Procedure ◽  
Water Levels ◽  
Flow Conditions ◽  
Flow Estimation ◽  
Pumping Station ◽  
Sewer Systems ◽  
Robust Model ◽  
Pumping Stations ◽  
Upstream Station ◽  
Pump Sump

Abstract Flow data represent crucial input for reliable diagnostics of sewer functions and identification of potential problems such as unwanted inflow and infiltration. Flow estimates from pumping stations, which are an integral part of most separate sewer systems, might help in this regard. A robust model and an associated optimization procedure is proposed for estimating inflow to a pumping station using only registered water levels in the pump sump and power consumption. The model was successfully tested on one month of data from a single upstream station. The model is suitable for identification of pump capacity and volume thresholds for switching the pump on and off. These are parameters which are required for flow estimation during periods with high inflows or during periods with flow conditions triggering pump switching on and off at frequencies close to the temporal resolution of monitored data. The model is, however, sensitive within the transition states between emptying and filling to observation errors in volume and on inflow/outflow variability.

Prediction of Threshold Sand Rates from Acoustic Monitors Using Artificial Intelligence

2021 ◽  
Author(s):  
Ronald E. Vieira ◽  
Bohan Xu ◽  
Asad Nadeem ◽  
Ahmed Nadeem ◽  
Siamack A. Shirazi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Noise Level ◽  
Background Noise ◽  
Pipe Wall ◽  
Flow Patterns ◽  
Operating Conditions ◽  
Flow Conditions ◽  
Background Noise Level ◽  
Input Parameters

Abstract Solids production from oil and gas wells can cause excessive damage resulting in safety hazards and expensive repairs. To prevent the problems associated with sand influx, ultrasonic devices can be used to provide a warning when sand is being produced in pipelines. One of the most used methods for sand detection is utilizing commercially available acoustic sand monitors that clamp to the outside of pipe wall and measures the acoustic energy generated by sand grain impacts on the inner side of a pipe wall. Although the transducer used by acoustic monitors is especially sensitive to acoustic emissions due to particle impact, it also reacts to flow induced noise as well (background noise). The acoustic monitor output does not exceed the background noise level until a sufficient sand rate is entrained in the flow that causes a signal output that is higher than the background noise level. This sand rate is referred to as the threshold sand rate or TSR. A significant amount of data has been compiled over the years for TSR at the Tulsa University Sand Management Projects (TUSMP) for various flow conditions with stainless steel pipe material. However, to use this data to develop a model for different flow patterns, fluid properties, pipe, and sand sizes is challenging. The purpose of this work is to develop an artificial intelligence (AI) methodology using machine learning (ML) models to determine TSR for a broad range of operating conditions. More than 250 cases from previous literature as well as ongoing research have been used to train and test the ML models. The data utilized in this work has been generated mostly in a large-scale multiphase flow loop for sand sizes ranging from 25 to 300 μm varying sand concentrations and pipe diameters from 25.4 mm to 101.6 mm ID in vertical and horizontal directions downstream of elbows. The ML algorithms including elastic net, random forest, support vector machine and gradient boosting, are optimized using nested cross-validation and the model performance is evaluated by R-squared score. The machine learning models were used to predict TSR for various velocity combinations under different flow patterns with sand. The sensitivity to changes of input parameters on predicted TSR was also investigated. The method for TSR prediction based on ML algorithms trained on lab data is also validated on actual field conditions available in the literature. The AI method results reveal a good training performance and prediction for a variety of flow conditions and pipe sizes not tested before. This work provides a framework describing a novel methodology with an expanded database to utilize Artificial Intelligence to correlate the TSR with the most common production input parameters.

Physical Model Study of Chicago's New Calumet Influent Pumping Station

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
D. Brocard ◽  
M. Garcia ◽  
T. Kunetz ◽  
J. Sobanski ◽  
A. Waratuke ◽  
...  
Keyword(s):  
Physical Model ◽  
Air Entrainment ◽  
Design Guidelines ◽  
Water Levels ◽  
Maintenance Cost ◽  
Optimized Design ◽  
Original Design ◽  
Pumping Station ◽  
Model Study ◽  
Wide Range

A new raw wastewater influent pumping station was designed for the Calumet Water Reclamation Plant in Chicago. The new station could not be designed to be in full compliance with design guidelines of the Hydraulic Institute due to site constraints. Proper operation of the pumping station and optimum operational flexibility are goals for the successful long term performance of the new station. A physical model study was used to identify deficiencies in the original design relative to flow characteristics. The model enabled development of design modifications to address hydraulic flow deficiencies. The optimized design resulted in pump approach flow conditions that provide proper pump performance under a wide range of varying water levels and different combinations of operating pumps and screen channels. Other benefits of the model included improvement in pump efficiency, lack of air entrainment, decreased pump wear, and decreased scour of concrete surfaces. Optimized design also results in operation and maintenance cost savings which, in the long run, will greatly surpass the cost of the physical model study. The required elements to optimize the performance were integrated with the design of the facility, thereby avoiding potentially costly retrofits if the deficiencies had not been mitigated prior to construction.

Supervision of Pumps and their Operating Conditions in Sewage Pumping Stations

2010 ◽  
Vol 5 (2) ◽  
Author(s):  
Carsten Skovmose Kallesøe ◽  
Mick Eriksen
Keyword(s):  
Energy Consumption ◽  
Operating Conditions ◽  
Optimal Scheduling ◽  
Pumping Station ◽  
Sewer Network ◽  
Pump Station ◽  
Pumping Stations ◽  
Innovative Solutions ◽  
System Optimal ◽  
Sewer Networks

The main energy consumers in sewer networks are the sewage pumps. Therefore, to minimize the energy consumption, it is essential that these pumps operate under satisfactory conditions. Knowledge about the efficiency of the pumps and their operating conditions can help the pump station management to operate the system optimal. In the search for innovative solutions that can help the sewer management with this information, we propose a method that provides information on the pump flows, the inflow to a sewage pit, and an online estimate of the efficiency of the pump. All these information are obtained without a flow sensor. We argued that the calculated flow values can be used by the sewer management to optimize the operation on the sewer pumps, and the efficiency estimate can be used for optimal scheduling of maintain procedures. The flow and the efficiency estimations are exemplified on a pumping station of the sewer network in Herning, Denmark.

Control Optimization Through Prediction-Based Wastewater Management

2021 ◽  
Author(s):  
David Konstantin Tilcher ◽  
Florin Popescu ◽  
Harald Sommer ◽  
Lauritz Thamsen ◽  
Paul Uwe Thamsen
Keyword(s):  
Energy Savings ◽  
Minimum Energy ◽  
Operating Conditions ◽  
Wastewater Management ◽  
Research Project ◽  
Level Curves ◽  
Pumping Station ◽  
Minimum Energy Consumption ◽  
Pumping Stations ◽  
The Individual

Abstract As part of a collaborative research project (OPTIMA) by Fraunhofer FOKUS, Engineering Company Prof. Dr. Sieker mbH, Department of Distributed and Operating Systems and Department of Fluid System Dynamics, TU Berlin, an „Intelligent Pumping Station” is being developed. In this research project, the operation of wastewater pumping stations is to be optimized by integrating precipitation forecasts and recording operating conditions on one hand, and by integrating historical data on use and operation on the other. The individual strategies for optimizing the operation of pumping stations and the possibilities of data integration will be systematically investigated. The focus of this paper is on the method for developing an optimized pump control. It examines how knowledge of predicted inflow can be used to achieve energy savings and a reduction in wastewater overflows. This method is based on the development of an algorithm in which detailed consideration of pump specifics and future pumping station inflow can be used to predict all possible suction head level curves for the considered period of time. Depending on the target criterion — minimum energy consumption per transported cubic meter or minimum overflow volume — the algorithm calculates the optimum path from all possible suction chamber level curves.

scholarly journals Experimental Vortex Flow Patterns in the Primary and Secondary Pump Intakes of a Model Underground Pumping Station

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1790 ◽  
Author(s):  
Miao Guo ◽  
Zhigang Zuo ◽  
Shuhong Liu ◽  
Huijun Zou ◽  
Baoyu Chen ◽  
...  
Keyword(s):  
Fluid Mechanics ◽  
Phase Diagrams ◽  
Experimental Model ◽  
Vortex Flow ◽  
Flow Patterns ◽  
Design Guidelines ◽  
Dimensionless Numbers ◽  
Pumping Station ◽  
Pumping Stations ◽  
Current Design

In order to provide specific references and suggestions for the design and operation of underground pumping stations, in this paper, an experimental model of an underground pumping station, including 4 pumps and 2 pump intakes (primary and secondary), was obtained through similitude of fluid mechanics. The phase diagrams of various vortices, in terms of different dimensionless numbers are presented, which can reveal their appearance and evolution process. Three specific cases with different vortex flows were analyzed. The experiment results may provide a reference for the current design guidelines for underground pumping stations.

A New Risk and Reliability Model for Compressor and Pump Installations

2014 ◽  
Author(s):  
Augusto Garcia-Hernandez ◽  
Hector Delgado-Garibay ◽  
Rubén Rivera Reyes ◽  
Jose Luis Martínez ◽  
Lorenzo Martínez Gomez
Keyword(s):  
Failure Probability ◽  
Probability Of Failure ◽  
Operating Conditions ◽  
Graphical Form ◽  
Original Design ◽  
Reliability Data ◽  
Weighting Factors ◽  
Pumping Stations ◽  
Wide Range ◽  
Pump Stations

Compression and pumping systems are constantly changing infrastructures, with many of the older compressor/pumping stations requiring updates, repairs and inspections to maintain safe and efficient operations. These stations operate over a wide range of pressures, flows, and working fluids under varying environmental conditions. Operating condition factors, as well as original design and materials, can significantly affect corrosion rates, structural integrity, and the flow capability of these compressor/pumping stations. Station equipment can be logically inter-related using failure trees and each critical sub-component be assigned a mean time between failure and failure probability using acceptable industry standards. These individual components are then allowed to interact to determine sub-system, system, and full station level failure probabilities. This type of analysis has historically not been utilized by the oil and gas industry but is common to other industries, such as the aerospace and nuclear power industries. This paper presents a new, comprehensive, consistent, and effective process for predicting risk, integrity, and reliability of the compressor and pump stations as well as each major subsystem and component within these stations. The model considers predefined “threats” such as mechanical, materials, electrical, third party, environment and external forces, improper maintenance, and operation of all its components; thus, typical failures modes are included in these threats. A semi-quantitative methodology with factored risk indices is applied where weighting factors are used to adjust the model with operational data. These factors are generated from reliability data extracted from the station. Comparisons between the model predictions and the reliability data will allow tuning of the weighting factors. Weighting factors are defined for each of the identified threats. The probability of failure is computed at a component level; however, it can be obtained at any level in the system based upon the specified categorization. The probability of failure is represented as a function of three factors: exposure, resistance, and mitigation, while the consequence of failure is estimated using the same approach based on three factors: receptor, hazard, and reduction. This predictive risk and failure model has been defined based on international specifications and is consistent with actual operating conditions, capacity planning, and remaining life expectations, while assuring that the stations meet the day-to-day operational demands of the system. The model also is able to predict each individual equipment failure probability within the station systems and provides for easy output of the data in graphical form for proper operating, maintenance, repair, and testing decisions.

Optimization of Approach Flow Conditions of Vertical Pumping Systems by Computational Analysis and Physical Model Investigation

2010 ◽  
Author(s):  
Kilian Kirst ◽  
D.-H. Hellmann
Keyword(s):  
Free Surface ◽  
Physical Model ◽  
Computational Analysis ◽  
State Of The Art ◽  
Mechanical Load ◽  
Energy Content ◽  
Operating Conditions ◽  
Flow Conditions ◽  
Acceptance Criteria ◽  
Application Range

Approach flow conditions of intake structures should be in compliance with state of the art acceptance criteria for all operating conditions, to provide the required flow rates of cooling or circulating water properly. Specially for high specific speed vertical pumps the direct inflow should be vortex free, with low prerotation and symmetric velocity distribution. Flow separation in front of open and covered intake structures can lead to free surface vortices. Depending on the strength, vortices can emerge a coherent air core, starting from the surface and entering the inlet nozzle directly. High mechanical load of the pump and decreasing hydraulic performance are an immediate consequence. Energy content, stability and position of a free surface vortex are determinated by intake system geometry and operating conditions. By installing flow guiding devices, the generation of vortex formations can be prevented. Optimization steps should be accomplished with respect to installation costs and complexity on-site. Therefore the effectiveness of the improvements has to be verified. Physical model investigations are common practice and state of the art to evaluate, to optimize and to document flow conditions inside intake structures. Nowadays, computational analysis is more and more adopted in this work field. A combination of both leads to well-defined and reproducible results within a wide application range. By this means prototype intake structures can be investigated and, if necessary, optimized for their best approach flow conditions. In the report the optimization of insufficient approach flow by computational analysis and physical model tests is presented. Therefore various intake structures for cooling water systems — all having approach flow not in compliance with the acceptance criteria of common standards — were physically modeled and investigated. Simultaneously initial and optimized layouts were reviewed by numerical calculations of different kinds. Calculated results are compared with model test and prototype data for different cases and operating points. Focusing on the occurrence of free surface vortices, methods of reproducing free surface vortices with numerical approaches will be presented and evaluated.

Numerical Investigation on the Leakage and Static Stability Characteristics of Pocket Damper Seals at High Eccentricity Ratios

2017 ◽  
Vol 140 (4) ◽  
Author(s):  
Zhigang Li ◽  
Jun Li ◽  
Zhenping Feng
Keyword(s):  
Static Stability ◽  
Operating Conditions ◽  
Eccentricity Ratio ◽  
Static Stiffness ◽  
Flow Conditions ◽  
Experiment Data ◽  
High Eccentricity ◽  
Stiffness Coefficients ◽  
Direct Stiffness ◽  
Gas Seals

Annular gas seals for compressors and turbines are designed to operate in a nominally centered position in which the rotor and stator are at concentric condition, but due to the rotor–stator misalignment or flexible rotor deflection, many seals usually are suffering from high eccentricity. The centering force (represented by static stiffness) of an annular gas seal at eccentricity plays a pronounced effect on the rotordynamic and static stability behavior of rotating machines. The paper deals with the leakage and static stability behavior of a fully partitioned pocket damper seal (FPDS) at high eccentricity ratios. The present work introduces a novel mesh generation method for the full 360 deg mesh of annular gas seals with eccentric rotor, based on the mesh deformation technique. The leakage flow rates, static fluid-induced response forces, and static stiffness coefficients were solved for the FPDS at high eccentricity ratios, using the steady Reynolds-averaged Navier–Stokes solution approach. The calculations were performed at typical operating conditions including seven rotor eccentricity ratios up to 0.9 for four rotational speeds (0 rpm, 7000 rpm, 11,000 rpm, and 15,000 rpm) including the nonrotating condition, three pressure ratios (0.17, 0.35, and 0.50) including the choked exit flow condition, two inlet preswirl velocities (0 m/s, 60 m/s). The numerical method was validated by comparisons to the experiment data of static stiffness coefficients at choked exit flow conditions. The static direct and cross-coupling stiffness coefficients are in reasonable agreement with the experiment data. An interesting observation stemming from these numerical results is that the FPDS has a positive direct stiffness as long as it operates at subsonic exit flow conditions; no matter the eccentricity ratio and rotational speed are high or low. For the choked exit condition, the FPDS shows negative direct stiffness at low eccentricity ratio and then crosses over to positive value at the crossover eccentricity ratio (0.5–0.7) following a trend indicative of a parabola. Therefore, the negative static direct stiffness is limited to the specific operating conditions: choked exit flow condition and low eccentricity ratio less than the crossover eccentricity ratio, where the pocket damper seal (PDS) would be statically unstable.

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