Improving the Performance of Centrifugal Pumps in Serial and Parallel Configurations Using Digital Twins

2019 ◽  
Author(s):  
Andrés L. Carrillo Peña ◽  
Jeffer S. Eugenio Barroso ◽  
Alberto A. Martínez Vesga ◽  
Sebastián Roa Prada ◽  
Victor A. Ardila Acuña
Keyword(s):  
Experimental Data ◽  
Operating Conditions ◽  
Water Supply Systems ◽  
Strong Impact ◽  
Simulation Environment ◽  
Centrifugal Pumps ◽  
Digital Twin ◽  
Pumping System ◽  
Digital Twins ◽  
Hydraulic Machines

Abstract Centrifugal pumps are devices commonly used in countless industrial and residential applications, from water supply systems to oil and gas processing plants. These rotatory hydraulic machines have a strong impact on the energy consumption of industry worldwide, not only because of their vast amount but also because of their continuous operation. Therefore, developing techniques to improve the efficiency of pumping systems is of great help to make communities and industrial activity more sustainable. The overall performance of these pieces of machinery cannot be fully predicted by means of analytical procedures due to the complexity of the fluid flow phenomena that occurs in their interior, so it is common practice to resort to alternate modeling techniques, such as computer aided numerical analysis, which can predict the performance of a pump, given its CAD computer model. However, the performance of an actual centrifugal pump may deviate from its ideal behavior due to multiple causing factors which may alter the performance curves given by the manufacturers in the corresponding data sheets. The discrepancies between the real and the simulated responses of centrifugal pumps demand for better modeling and simulation techniques to improve the design of more efficient pumping systems. Digital twins have the ability to bring the simulation environment closer to reality, by replicating the behavior of the physical system in a simulation environment with the support of experimental data. The digital twin of a multiple pumps system with serial and parallel configurations was developed, based on two identical industrial centrifugal pumps available in the laboratory. Experimental data was collected to calibrate the digital twin system so that the simulated system can predict the response under changing operating conditions. The simulation environment was developed with the assistance of a commercial Computational Fluid Dynamics computer program. After validating the behavior of the virtual components, with respect to the behavior of their actual counterparts, tests were carried out to predict the behavior of the pumping system in case of downstream disturbances which can affect the operating point of the overall pumping system and its corresponding efficiency. The development of the digital twin for the pumping system allowed visualizing how the pumps connected in series or in parallel can be maneuvered to adjust its operating conditions to achieve higher efficiency operating conditions in response to changes in the conditions downstream in the pipeline.

Machine learning-based digital twins reduce seasonal remapping in aeroderivative gas turbines

2021 ◽  
pp. 1-7
Author(s):  
Nick Petro ◽  
Felipe Lopez
Keyword(s):  
Machine Learning ◽  
Ambient Temperature ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Pilot Site ◽  
Digital Twin ◽  
Digital Twins ◽  
Machine Learning Model ◽  
Unacceptable Behavior ◽  
External Conditions

Abstract Aeroderivative gas turbines have their combustion set points adjusted periodically in a process known as remapping. Even turbines that perform well after remapping may produce unacceptable behavior when external conditions change. This article introduces a digital twin that uses real-time measurements of combustor acoustics and emissions in a machine learning model that tracks recent operating conditions. The digital twin is leveraged by an optimizer that select adjustments that allow the unit to maintain combustor dynamics and emissions in compliance without seasonal remapping. Results from a pilot site demonstrate that the proposed approach can allow a GE LM6000PD unit to operate for ten months without seasonal remapping while adjusting to changes in ambient temperature (4 - 38 °C) and to different fuel compositions.

scholarly journals Dimensionless curves of centrifugal pumps for water supply systems: development and case study

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Jóice Cristini Kuritza ◽  
Giovani Camponogara ◽  
Marcelo Giulian Marques ◽  
Daniela Guzzon Sanagiotto ◽  
Cristiane Battiston
Keyword(s):  
Water Supply ◽  
Maximum Yield ◽  
Electricity Consumption ◽  
Operating Conditions ◽  
Water Supply Systems ◽  
Centrifugal Pumps ◽  
Water Pumping ◽  
Performance Curves ◽  
Supply Systems

ABSTRACT Centrifugal pumps are widely used in water supply systems and account for more than 90% of the electricity consumption of water pumping stations. Studies that seek to generalize the characterization of performance curves of centrifugal pumps are extremely useful. A study was carried out on the dimensionless characteristics of the operating conditions of centrifugal pumps for preliminary design estimations of water supply systems aiming at energy efficiency. The research consisted of the analysis of performance curves of centrifugal pumps from which data was collected regarding the point of maximum yield (PMY). The curves and the equations obtained were made dimensionless so that the information could be extrapolated to other situations. A case study was conducted in the Water Supply System of Vale Campus of the Federal University of Rio Grande do Sul (UFRGS) to demonstrate the application of those equations and curves developed. The dimensionless equations were useful to determine which discharge should be adopted so that the system would be more efficient hydro and energetically and, also, to determine how much more energy would be consumed in the case of alteration of the point of operation of the pump by a throttling valve.

scholarly journals Experimental Investigation of Power Signatures for Cavitation and Water Hammer in an Industrial Parallel Pumping System

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1351 ◽  
Author(s):  
V.K. Arun Shankar ◽  
Umashankar Subramaniyan ◽  
Padmanaban Sanjeevikumar ◽  
Jens Bo Holm-Nielsen ◽  
Frede Blaabjerg ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Quality ◽  
Harmonic Distortion ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Fault Prediction ◽  
Normal Operation ◽  
Centrifugal Pumps ◽  
Total Energy Consumption ◽  
Pumping System

Among the total energy consumption by utilities, pumping systems contribute 30%. It is evident that a tremendous energy saving potential is achievable by improving the energy efficiency and reducing faults in the pumping system. Thus, optimal operation of centrifugal pumps throughout the operating region is desired for improved energy efficiency and extended lifetime of the pumping system. The major harmful operations in centrifugal pumps include cavitation and water hammering. The pump faults are simulated in a real-time experimental setup and the operating point of the pump is estimated correspondingly. In this article, the experimental power quality and vibration measurements of cascade pumps during cavitation and water hammering is recorded for different operating conditions. The results are compared with the normal operating conditions of the pumping system for fault prediction and parameter estimation in a cascade water pumping system. Moreover, the Fast Fourier Transform (FFT) analysis comparison of normal and water hammering (faulty condition) highlights the frequency response of the pumping system. Also, the various power quality issues, i.e., voltage, current, total harmonic distortion, power factor, and active, reactive, and apparent power for a cascade multipump control is discussed in this article. The vibration, FFT, and various power quality measurements serve as input data for the classification of faulty pump operating condition in contrast with the normal operation of pumping system.

Predictive Maintenance Using the Executable Digital Twin xDT

2021 ◽  
Author(s):  
Kevin Goodheart ◽  
Peter Mas ◽  
Maged Ismail ◽  
Umberto Badiali ◽  
Wim Hendicx
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Order Reduction ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Predictive Maintenance ◽  
Field Equipment ◽  
Loop Control ◽  
Digital Twin ◽  
Digital Twins

Abstract Through the introduction of programmable logic controller (PLCs), Dynamic Process & Controls modeling, integrating with Multiphysics Mechatronics & 3D equipment simulation modeling, companies can work in the online real-time environment. This modeling of equipment or processes builds the foundation for digital transformation of subsea, topside, onshore and plant environments. In the design and operation of field equipment, the physics based Digital Twin is getting more and more traction to develop virtually the equipment because of recent prediction accuracy improvement and faster calculation times. Such digital twins allow to find the optimal operating conditions and predictive maintenance schedules for operation. In this timeslot we will explain, based on few industrial examples, a new set of capabilities that allow companies to get the maximum out of digital twins to be able to use them on their equipment. By applying a structured process using Digital Twins to be able to convert the existing knowledge & data at Companies into solution to be more predictive on their equipment. This will deliver substantial return on investment (ROI) for the Oil and Gas Industry. An AI based methodology to perform Model Order Reduction on the digital twin to be able to get real time response in connection to online unit information An AI based methodology to convert the reduced model into a virtual sensor for online quality predictions or predictive maintenance scheduling as well as to use it for creating an optimal controller of the unit based on the product requirements Fast edge computing hardware that can collect data from sensors and, in real time, run the Executable Digital Twin (xDT) and suggest corrective action to the operator or run in closed loop control

A correlation to predict the performance characteristics of centrifugal pumps handling slurries

1997 ◽  
Vol 211 (2) ◽  
pp. 147-157 ◽  
Author(s):  
K A Kazim ◽  
B Maiti ◽  
P Chand
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Suspended Solids ◽  
Reduction Factor ◽  
Performance Characteristics ◽  
Centrifugal Pumps ◽  
Pump Performance ◽  
New Correlation ◽  
Effect Of Particle Size ◽  
The Individual

Centrifugal pumps are being used increasingly for transportation of slurries through pipelines. To design a slurry handling system it is essential to have a knowledge of the effects of suspended solids on the pump performance. A new correlation to predict the head reduction factor for centrifugal pumps handling solids has been developed. This correlation takes into account the individual effect of particle size, particle size distribution, specific gravity and concentration of solids on the centrifugal pump performance characteristics. The range of validity of the correlation has been verified by experiment and by using experimental data available from the literature. The present correlation shows better agreement with the experimental data than existing correlations.

Effect of Density, Size Distribution, and Concentration of Solid on the Characteristics of Centrifugal Pumps

1992 ◽  
Vol 114 (3) ◽  
pp. 386-389 ◽  
Author(s):  
V. K. Gahlot ◽  
V. Seshadri ◽  
R. C. Malhotra
Keyword(s):  
Experimental Data ◽  
Size Distribution ◽  
Empirical Relationship ◽  
Maximum Size ◽  
Centrifugal Pumps ◽  
Pump Performance ◽  
Size Of Particles

Experimental data on the performance of the centrifugal pumps pumping mixtures of solids and water have been presented. The solids used were coal of density 1480 kg/m3 and zinc tailings of density 2850 kg/m3. Maximum size of particles was approximately 3 mm. Tests have been conducted with a rubber lined impeller pump and a metal impeller pump. Effects of solid properties (viz: density, size, and size distribution as well as concentration of solids) on the performance of the pumps have been studied. The measured performance of pumps is compared with the predictions based on the correlations available in literature and a modified empirical relationship has been proposed for the prediction of the pump performance with slurries.

Modeling and Experimental Validation of the Effective Bulk Modulus of a Mixture of Hydraulic Oil and Air

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Hossein Gholizadeh ◽  
Doug Bitner ◽  
Richard Burton ◽  
Greg Schoenau
Keyword(s):  
Experimental Data ◽  
Bulk Modulus ◽  
Theoretical Models ◽  
Operating Conditions ◽  
Air Bubbles ◽  
Pressure Sensitivity ◽  
Hydraulic Oil ◽  
Effective Bulk Modulus ◽  
Experimental Apparatus ◽  
Major Factors

It is well known that the presence of entrained air bubbles in hydraulic oil can significantly reduce the effective bulk modulus of hydraulic oil. The effective bulk modulus of a mixture of oil and air as pressure changes is considerably different than when the oil and air are not mixed. Theoretical models have been proposed in the literature to simulate the pressure sensitivity of the effective bulk modulus of this mixture. However, limited amounts of experimental data are available to prove the validity of the models under various operating conditions. The major factors that affect pressure sensitivity of the effective bulk modulus of the mixture are the amount of air bubbles, their size and the distribution, and rate of compression of the mixture. An experimental apparatus was designed to investigate the effect of these variables on the effective bulk modulus of the mixture. The experimental results were compared with existing theoretical models, and it was found that the theoretical models only matched the experimental data under specific conditions. The purpose of this paper is to specify the conditions in which the current theoretical models can be used to represent the real behavior of the pressure sensitivity of the effective bulk modulus of the mixture. Additionally, a new theoretical model is proposed for situations where the current models fail to truly represent the experimental data.

Digital Twin for Smart Manufacturing: The Practitioner’s Perspective

2020 ◽  
Author(s):  
Maja Bärring ◽  
Björn Johansson ◽  
Goudong Shao
Keyword(s):  
Conceptual Development ◽  
Production Systems ◽  
Manufacturing Sector ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Adoption And Implementation ◽  
New Information ◽  
Digital Twins ◽  
Discrete Manufacturing ◽  
Design Production

Abstract The manufacturing sector is experiencing a technological paradigm shift, where new information technology (IT) concepts can help digitize product design, production systems, and manufacturing processes. One of such concepts is Digital Twin and researchers have made some advancement on both its conceptual development and technological implementations. However, in practice, there are many different definitions of the digital-twin concept. These different definitions have created a lot of confusion for practitioners, especially small- and medium-sized enterprises (SMEs). Therefore, the adoption and implementation of the digital-twin concept in manufacturing have been difficult and slow. In this paper, we report our findings from a survey of companies (both large and small) regarding their understanding and acceptance of the digital-twin concept. Five supply-chain companies from discrete manufacturing and one trade organization representing suppliers in the automotive business were interviewed. Their operations have been studied to understand their current digital maturity levels and articulate their needs for digital solutions to stay competitive. This paper presents the results of the research including the viewpoints of these companies in terms of opportunities and challenges for implementing digital twins.

Digital Twins: Review and Challenges

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret
Keyword(s):  
Computer Science ◽  
Industry 4.0 ◽  
Multi Agent System ◽  
Agent System ◽  
Digital Twin ◽  
Digital Twins ◽  
Science Approach ◽  
Multi Agent ◽  
Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

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