How Bulk Modulus Errors Can Affect Leak Detection

1996 ◽  
Author(s):  
Henry H. Rachford ◽  
Andrew Wike
Keyword(s):  
Bulk Modulus ◽  
Measurement Data ◽  
Leak Detection ◽  
Operating Conditions ◽  
Time Data ◽  
Transient Model ◽  
Property Data ◽  
Wide Range ◽  
Fluid Properties ◽  
On Line

Liquid pipeline operators look to leak detection systems to provide continuous surveillance of their pipelines across a wide range of operating conditions; this is particularly the case for batch pipelines. Operators frequently anticipate that on-line transient modeling systems can satisfy this requirement, which they can, but have little exposure to the on-line measurement data requirements of such systems. There can be a mistaken focus on improving the quality of the real-time data normally available to facilitate pipeline operations, without due regard to providing the measurement data that the model needs. Pipeline operators are normally not concerned with a detailed characterization of fluid properties, other than in the most general sense regarding the susceptibility of adjacent fluids to mix at their interface. This paper illustrates how the lack of reliable fluid property data (specifically, bulk modulus data) can substantially impede the effectiveness of a transient model charged with the task of leak detection.

scholarly journals Multibody dynamic modelling of a direct wind turbine drive train

2019 ◽  
Vol 44 (5) ◽  
pp. 519-547
Author(s):  
Saeed Asadi ◽  
Håkan Johansson
Keyword(s):  
Wind Turbine ◽  
Measurement Data ◽  
Dynamic Modelling ◽  
Simulation Software ◽  
Operating Conditions ◽  
Drive Train ◽  
Operational Experience ◽  
Main Bearing ◽  
Wide Range ◽  
Turbine Drive

Wind turbines normally have a long operational lifetime and experience a wide range of operating conditions. A representative set of these conditions is considered as part of a design process, as codified in standards. However, operational experience shows that failures occur more frequently than expected, the costlier of these including failures in the main bearings and gearbox. As modern turbines are equipped with sophisticated online systems, an important task is to evaluate the drive train dynamics from online measurement data. In particular, internal forces leading to fatigue can only be determined indirectly from other locations’ sensors. In this contribution, a direct wind turbine drive train is modelled using the floating frame of reference formulation for a flexible multibody dynamics system. The purpose is to evaluate drive train response based on blade root forces and bedplate motions. The dynamic response is evaluated in terms of main shaft deformation and main bearing forces under different wind conditions. The model was found to correspond well to a commercial wind turbine system simulation software (ViDyn).

An Intelligent Sensor Validation and Fault Diagnostic Technique for Diesel Engines

1999 ◽  
Vol 123 (1) ◽  
pp. 141-144 ◽  
Author(s):  
Ehsan Mesbahi
Keyword(s):  
Fault Diagnosis ◽  
Confidence Level ◽  
Diagnostic Technique ◽  
Operating Conditions ◽  
Sensor Reading ◽  
Intelligent Sensor ◽  
Sensor Validation ◽  
Wide Range ◽  
On Line ◽  
Artificial Neural Network Ann

Abstract An intelligent sensor validation and on-line fault diagnosis technique for a 6 cylinder turbocharged diesel engine is proposed and studied. A single auto-associative 3-layer Artificial Neural Network (ANN), is trained to examine the accuracy of the measured data and allocate a confidence level to each signal. The same ANN is used to recover the missing or faulty data with a close approximation. For on-line fault detection a feed-forward ANN is trained to classify and consequently recognize faulty and healthy behavior of the engine for a wide range of operating conditions. The proposed technique is also equipped with an on-line learning mechanism, which is activated when the confidence level in predicted fault is poor. It is hoped that a feasible, practical, and reliable sensor reading, as well as highly accurate fault diagnosis system, would be achieved.

Experimental Chatter Modeling of Milling Operations

2007 ◽  
Author(s):  
Giuseppe Catania ◽  
Nicolo` Mancinelli
Keyword(s):  
Ad Hoc ◽  
Dynamical Behavior ◽  
Measurement Data ◽  
Period Doubling ◽  
Experimental Tests ◽  
Cutting Parameters ◽  
Operating Conditions ◽  
Depth Of Cut ◽  
Wide Range ◽  
Excited Vibration

This study refers to the investigation on the critical operating condition occurring on high productivity milling machines, known as chatter. This phenomenon is generated by a self-excited vibration, associated with a loss of stability of the system, causing reduced productivity, poor surface finish and noise. This study consists of the theoretical and experimental modeling of machining chatter conditions, in order to develop a real-time monitoring system able to diagnose the occurrence of chatter in advance and to dynamically modify the cutting parameters for process optimization. A prototype NC 3-axis milling machine was ad hoc realized to accomplish this task. The machine was instrumented by a dynamometer table, and a series of accelerometer sensors were mounted in the proximity of the tool spindle and the workpiece. An analytical model was developed, taking into account the periodic cutting force arising during interrupted cutting operation in milling. The system dynamical behavior was described by means of a set of delay differential equations with periodic coefficients. The stability of this system was analyzed by the semi discretization approach based on the Floquet theory. Lobe stability charts were evaluated and associated with frequency diagrams. Two chatter types were analytically and experimentally detected: period-doubling bifurcations and secondary Hopf bifurcations. Measurement data were acquired and analyzed in the time and frequency domain. Several tests were conducted in a wide range of operating conditions, such as radial immersion, depth of cut and spindle speeds and using different tools. Results are reported showing agreement between the numerical analysis and the related experimental tests.

Perdido Development: Unified Fluid Model for Integrated-Production-System Modeling

2015 ◽  
Vol 18 (03) ◽  
pp. 303-317 ◽  
Author(s):  
D.. Galvan ◽  
G.. McVinnie ◽  
B.. Dindoruk
Keyword(s):  
Production System ◽  
Oil And Gas ◽  
Fluid Model ◽  
Wide Spectrum ◽  
System Modeling ◽  
Operating Conditions ◽  
Fluid Composition ◽  
Integrated Production ◽  
Wide Range ◽  
Fluid Properties

Summary The Perdido development is one of the most-complex deepwater projects in the world. It is operated by Shell in partnership with Chevron and BP. It currently produces hydrocarbons from 12 subsea wells penetrating four separate reservoirs. The properties of produced fluid vary per reservoir as well as spatially. The producing wells display a relatively wide range of fluid gravities, between 17 and 41 °API, and producing gas/oil ratios (GORs), between 480 and 3,000 scf/bbl. The fluids produced from the subsea wells are blended in the subsea system and lifted to the topside facilities by means of five seabed caisson electrical submersible pumps. In the topside facility, gas and oil are separated, treated, and exported by means of dedicated subsea pipelines. The fluid compositions and properties across the various elements of the production system are used as input data to the respective simulation models, and the corresponding outcomes (e.g., fluid properties, compositions) vary upon the well/caisson lineup and daily operating conditions. Given the wide spectrum of fluids produced through the Perdido spar, a special equation-of-state (EOS) characterization of the fluids had to be developed. Because a common EOS model was used to characterize the fluids, we will call this the unified fluid model (UFM) throughout this study. This approach enables accurate and efficient prediction of the properties of blended fluids and is suitable for use in an integrated-production system model (IPSM) that connects reservoirs, wells, subsea-flowline networks, and topside-facilities models. Such a modeling scheme enables effective integration among relevant engineering disciplines and can represent production and fluid data from field history with high confidence. The IPSM uses a black-oil fluid description for the well and subsea-flowline network models. By use of the initial composition and producing GOR of each well, the fluid composition is estimated by means of a simple delumping scheme. The resulting composition is tracked through the subsea network to the topside-facilities model, where compositional flash calculations are performed. The IPSM can forecast production rates together with fluid properties and actual oil- and gas-volumetric rates across the whole production system. The model can be used to optimize production under constrained conditions, such as limited gas-compression capacity or plateau oil production.

scholarly journals GE ENERGY Jenbacher gas engine technology – preventive maintenance by means of highly sophisticated control systems

2006 ◽  
Vol 125 (2) ◽  
pp. 82-86
Author(s):  
Thomas ELSENBRUCH
Keyword(s):  
Control Systems ◽  
Data Transmission ◽  
Operating Conditions ◽  
Engine Operation ◽  
Actual Operating ◽  
Wide Range ◽  
Control Concept ◽  
On Line ◽  
Optimal Adjustment ◽  
And Control

Data collection and control concept of Jenbacher gas engines has been presented in the paper. Internet data transmission allow on-line control of the engine operation, early detection of defects and optimal adjustment to engine actual operating conditions. The system offers both customers and GE Jenbacher maintenance staff a wide range of functionalities for commissioning, monitoring and maintaining installations and for diagnostic purposes.

Experimental and Numerical Investigation of the Flow in a LP Industrial Steam Turbine With Part-Span Connectors

2015 ◽  
Author(s):  
M. Häfele ◽  
C. Traxinger ◽  
M. Grübel ◽  
M. Schatz ◽  
D. M. Vogt ◽  
...  
Keyword(s):  
Flow Field ◽  
Steam Turbine ◽  
Numerical Study ◽  
Resonance Condition ◽  
Three Dimensional ◽  
Measurement Data ◽  
Detailed Comparison ◽  
Operating Conditions ◽  
Engineering Practice ◽  
Wide Range

An experimental and numerical study on the flow in a three stage low pressure (LP) industrial steam turbine is presented and analyzed. The investigated LP section features conical friction bolts in the last and a lacing wire in the penultimate rotor blade row. These part-span connectors (PSC) allow safe turbine operation over an extremely wide range and even in blade resonance condition. However, additional losses are generated which affect the performance of the turbine. In order to capture their impact on the flow field, extensive measurements with pneumatic multi-hole probes in an industrial steam turbine test rig have been carried out. State-of-the-art three-dimensional CFD applying a non-equilibrium steam (NES) model is used to examine the aero-thermodynamic effects of the PSC on the wet steam flow. A detailed comparison between measurement data and CFD results is performed for several operating conditions. The investigation shows that the applied CFD model is able to capture the three-dimensional flow field in LP steam turbine blading with PSC and the total pressure reduction due to the PSC with a generally good agreement to measured values and is therefore sufficient for engineering practice.

scholarly journals Monitoring and diagnostics of special-purpose turbomachines

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Małgorzata Gizelska
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Magnetic Bearing ◽  
Operating Conditions ◽  
Active Magnetic Bearing ◽  
Diagnostic Tools ◽  
Compression Process ◽  
Rotating System ◽  
On Line ◽  
Monitoring And Diagnostics

Abstract In the operation of special-purpose turbomachines, diagnostic tools are necessary. They enable control of the machine technical state and its operation parameters in the on-line mode. The acquisition and processing of the measurement data in real time is crucial as they are indicators of the machine functioning under various operating conditions. The paper presents two types of computer designed diagnostic tools to monitor in real time the dynamic and thermodynamic parameters of special-purpose turbomachines. The first one monitors the dynamics of the rotating system with an active magnetic bearing, the second - monitors the instant value of polytropic efficiency of the compression process, which was designed for the industrial machine.

A Novel Approach for the Prediction of Dynamic Features of Air Release and Absorption in Hydraulic Oils

2013 ◽  
Vol 135 (9) ◽  
Author(s):  
Junjie Zhou ◽  
Andrea Vacca ◽  
Bernhard Manhartsgruber
Keyword(s):  
Bulk Modulus ◽  
Saturation Pressure ◽  
Measurement Data ◽  
Fluid Density ◽  
Hydraulic Systems ◽  
Dynamic Features ◽  
Liquid Phases ◽  
Novel Approach ◽  
Fluid Properties ◽  
Computational Fluid Dynamics Cfd

An accurate evaluation of fluid density and bulk modulus is essential for predicting the operation of hydraulic systems and components. Among the models reported in literature to describe fluid properties, of particular success in the fluid power field are the continuous methods that assume the gas and liquid phases to be the same fluid. However, these models are typically based on steady-state equilibrium relations and, consequently, they fail in correctly predicting the dynamic features of both air release and air absorption processes. These phenomena are particularly important for machines based on open-system hydraulic circuits, in which a significant part of the system can operate with a fluid below the saturation pressure. This paper addresses this topic by proposing a novel approach suitable to describe the dynamic features of both vaporization and air release processes. The approach is based on simplified transport equations to evaluate the phase change rate and the air release/dissolve rate. These transport equation are obtained from the well-known theoretical “full cavitation model” previously developed for computational fluid dynamics (CFD). Specific tests were performed to validate particularly as concerns the air release/absorption features using a standard ISO32 mineral oil. Comparisons between model predictions and measurement data are presented for compression/decompression cycles as concerns transient fluid density and bulk modulus, and a good agreement between the two trends is found, showing the potentials of the new approach to describe typical cavitation phenomena in hydraulic systems.

Inline Drilling Fluid Property Measurement, Integration, and Modeling to Enhance Drilling Practice and Support Drilling Automation

2021 ◽  
Author(s):  
Sanjit Roy ◽  
Saiyid Z. Kamal ◽  
Richard Frazier ◽  
Ross Bruns ◽  
Yahia Ait Hamlat
Keyword(s):  
Real Time ◽  
Drilling Fluid ◽  
Measurement Data ◽  
Lessons Learned ◽  
Valuable Insight ◽  
Drilling Process ◽  
Time Data ◽  
Fluid Property ◽  
Real Time Data ◽  
Fluid Properties

Abstract Frequent, reliable, and repeatable measurements are key to the evolution of digitization of drilling information and drilling automation. While advances have been made in automating the drilling process and the use of sophisticated engineering models, machine learning techniques to optimize the process, and lack of real-time data on drilling fluid properties has long been recognized as a limiting factor. Drilling fluids play a significant function in ensuring quality well construction and completion, and in-time measurements of relevant fluid properties are key to automation and enhancing decision making that directly impacts well operations. This paper discusses the development and application of a suite of automated fluid measurement devices that collect key fluid properties used to monitor fluid performance and drive engineering analyses without human involvement. The deployed skid-mounted devices continually and reliably measure properties such as mud weight, apparent viscosity, rheology profiles, temperatures, and emulsion stability to provide valuable insight on the current state of the fluid. Real-time data is shared with relevant rig and office- based personnel to enable process monitoring and trigger operational changes. It feeds into real-time engineering analyses tools and models to monitor performance and provides instantaneous feedback on downhole fluid behavior and impact on drilling performance based on current drilling and drilling fluid property data. Equipment reliability has been documented and demonstrated on over 30 wells and more than 400 thousand ft of lateral sections in unconventional shale drilling in the US. We will share our experience with measurement, data quality and reliability. We will also share aspects of integrating various data components at disparate time intervals into real-time engineering analyses to show how real-time measurements improve the prediction of well and wellbore integrity in ongoing drilling operations. In addition, we will discuss lessons learned from our experience, further enhancements to broaden the scope, and the integration with operators, service companies and other original equipment manufacturer in the domain to support and enhance the digital drilling ecosystem.

scholarly journals Detection of drinking water contamination event with Mahalanobis distance method, using on-line monitoring sensors and manual measurement data

2018 ◽  
Vol 18 (6) ◽  
pp. 2133-2141 ◽  
Author(s):  
S. Dejus ◽  
A. Nescerecka ◽  
G. Kurcalts ◽  
T. Juhna
Keyword(s):  
Drinking Water ◽  
Real Time ◽  
Mahalanobis Distance ◽  
Measurement Data ◽  
Early Warning Systems ◽  
Operating Conditions ◽  
Distance Method ◽  
Biological Contamination ◽  
On Line ◽  
Contamination Events

Abstract Concerns about drinking water (DW) quality contamination during water distribution raise a need for real-time monitoring and rapid contamination detection. Early warning systems (EWS) are a potential solution. The EWS consist of multiple conventional sensors that provide the real-time measurements and algorithms that allow the recognizing of contamination events from normal operating conditions. In most cases, these algorithms have been established with artificial data, while data from real and biological contamination events are limited. The goal of the study was the event detection performance of the Mahalanobis distance method in combination with on-line DW quality monitoring sensors and manual measurements of grab samples for potential DW biological contamination scenarios. In this study three contamination scenarios were simulated in a pilot-scale DW distribution system: untreated river water, groundwater and wastewater intrusion, which represent realistic contamination scenarios and imply biological contamination. Temperature, electrical conductivity (EC), total organic carbon (TOC), chlorine ion (Cl-), oxidation–reduction potential (ORP), pH sensors and turbidity measurements were used as on-line sensors and for manual measurements. Novel adenosine-triphosphate and flow cytometric measurements were used for biological water quality evaluation. The results showed contamination detection probability from 56% to 89%, where the best performance was obtained with manual measurements. The probability of false alarm was 5–6% both for on-line and manual measurements. The Mahalanobis distance method with DW quality sensors has a good potential to be applied in EWS. However, the sustainability of the on-line measurement system and/or the detection algorithm should be improved.

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