The Experts below are selected from a list of 4656 Experts worldwide ranked by ideXlab platform
Smrutiranjan Parida - One of the best experts on this subject based on the ideXlab platform.
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Pipe Wall Thickness prediction with CFD based mass transfer coefficient and degradation feedback for flow accelerated corrosion
Progress in Nuclear Energy, 2018Co-Authors: Mahendra Prasad, V. Gopika, Arunkumar Sridharan, Smrutiranjan ParidaAbstract:Abstract Pipe Wall Thickness reduction due to Flow Accelerated Corrosion (FAC) depends on mass transfer coefficient (MTC), temperature, pH and roughness. The purpose of this research work is to predict the Wall Thickness reduction due to FAC in bends and orifice. The paper proposes a model for temporal Wall Thickness prediction in Pipe bend and orifice taking into account the positive feedback from FAC induced roughness and spatial MTC. This is applied for two geometrical configurations (i) FAC experiment performed on 58° carbon steel Pipe bend (ii) FAC experiment in an orifice with gypsum. In the 58° carbon steel Pipe, the predictions were in good comparison with the experimental values at different locations with percentage error between the predicted and experimental Wall Thickness in the range (−5%, +12%) at all locations on Pipe extrados. For the orifice, the error was in the range of (−0.3 mm, +0.6 mm) at all measured locations. The MTC was estimated using computational fluid dynamics (CFD) with k-w SST (shear stress transport) model for both configurations. The comparison of predicted values of Wall Thickness with experimental values shows that errors in prediction are moderate to low.
Mahendra Prasad - One of the best experts on this subject based on the ideXlab platform.
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Pipe Wall Thickness prediction with CFD based mass transfer coefficient and degradation feedback for flow accelerated corrosion
Progress in Nuclear Energy, 2018Co-Authors: Mahendra Prasad, V. Gopika, Arunkumar Sridharan, Smrutiranjan ParidaAbstract:Abstract Pipe Wall Thickness reduction due to Flow Accelerated Corrosion (FAC) depends on mass transfer coefficient (MTC), temperature, pH and roughness. The purpose of this research work is to predict the Wall Thickness reduction due to FAC in bends and orifice. The paper proposes a model for temporal Wall Thickness prediction in Pipe bend and orifice taking into account the positive feedback from FAC induced roughness and spatial MTC. This is applied for two geometrical configurations (i) FAC experiment performed on 58° carbon steel Pipe bend (ii) FAC experiment in an orifice with gypsum. In the 58° carbon steel Pipe, the predictions were in good comparison with the experimental values at different locations with percentage error between the predicted and experimental Wall Thickness in the range (−5%, +12%) at all locations on Pipe extrados. For the orifice, the error was in the range of (−0.3 mm, +0.6 mm) at all measured locations. The MTC was estimated using computational fluid dynamics (CFD) with k-w SST (shear stress transport) model for both configurations. The comparison of predicted values of Wall Thickness with experimental values shows that errors in prediction are moderate to low.
De Jong N. - One of the best experts on this subject based on the ideXlab platform.
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Towards a calibration-free ultrasonic clamp-on flow meter: Pipe geometry measurements using matrix arrays: Pipe geometry measurements using matrix arrays
'Acoustical Society of America (ASA)', 2020Co-Authors: Massaad Mouawad J.m., Van Neer P.l.m.j., Van Willigen D.m., Pertijs M.a.p., De Jong N.Abstract:Current ultrasonic clamp-on flow meters are manually calibrated. This process is based on manual placement of two single-element transducers along a Pipe Wall. Due to the usually unknown Pipe properties and inhomogeneities in the Pipe geometry, the axial distance of the transducers needs to be manually calibrated to align the location of the emitted beam on the receiver. In this work it is presented an automatic calibration procedure, based on matrix transducer arrays, to provide calibration information that would normally be entered into the instrument manually prior to ultrasonic clamp-on flow measurements. The calibration consists of two steps: First, along the axial direction of the Pipe, Lamb waves are excited and recorded. Then, the measured time signals are combined with the Rayleigh-Lamb dispersion equation to extract Pipe Wall Thickness and bulk wave sound speeds. Second, along the circumferential direction of the Pipe, a specific Lamb wave mode is excited and recorded, from which the Pipe diameter is estimated. The potential of both calibration procedures is shown, and the necessity of a matrix transducer array (i.e. small elements) is highlighte
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Towards a calibration-free ultrasonic clamp-on flow meter: Pipe geometry measurements using matrix arrays: Pipe geometry measurements using matrix arrays
'Acoustical Society of America (ASA)', 2020Co-Authors: Massaad Mouawad J.m., Van Neer P.l.m.j., Van Willigen D.m., Pertijs M.a.p., De Jong N.Abstract:Current ultrasonic clamp-on flow meters are manually calibrated. This process is based on manual placement of two single-element transducers along a Pipe Wall. Due to the usually unknown Pipe properties and inhomogeneities in the Pipe geometry, the axial distance of the transducers needs to be manually calibrated to align the location of the emitted beam on the receiver. In this work it is presented an automatic calibration procedure, based on matrix transducer arrays, to provide calibration information that would normally be entered into the instrument manually prior to ultrasonic clamp-on flow measurements. The calibration consists of two steps: First, along the axial direction of the Pipe, Lamb waves are excited and recorded. Then, the measured time signals are combined with the Rayleigh-Lamb dispersion equation to extract Pipe Wall Thickness and bulk wave sound speeds. Second, along the circumferential direction of the Pipe, a specific Lamb wave mode is excited and recorded, from which the Pipe diameter is estimated. The potential of both calibration procedures is shown, and the necessity of a matrix transducer array (i.e. small elements) is highlightedImPhys/Medical ImagingElectronic Instrumentatio
Jaime Valls Miro - One of the best experts on this subject based on the ideXlab platform.
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non destructive evaluation of ferromagnetic material Thickness using pulsed eddy current sensor detector coil voltage decay rate
Ndt & E International, 2018Co-Authors: Nalika Ulapane, Alen Alempijevic, Jaime Valls Miro, Teresa VidalcallejaAbstract:Abstract A ferromagnetic material Thickness quantification method based on the decay rate of the Pulsed Eddy Current sensor detector coil voltage is proposed. An expression for the decay rate is derived and the relationship between the decay rate and material Thickness is established. Pipe Wall Thickness estimation is done with a developed circular sensor incorporating the proposed method, and results are evaluated through destructive testing. The decay rate feature has a unique attribute of being lowly dependent on properties such as sensor shape and size, and lift-off, enabling the method to be usable with any detector coil-based sensor. A case study on using the proposed method with a commercial sensor is also presented to demonstrate its versatility.
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pulsed eddy current sensing for critical Pipe condition assessment
Sensors, 2017Co-Authors: Nalika Ulapane, Alen Alempijevic, Teresa Vidal Calleja, Jaime Valls MiroAbstract:Pulsed Eddy Current (PEC) sensing is used for Non-Destructive Evaluation (NDE) of the structural integrity of metallic structures in the aircraft, railway, oil and gas sectors. Urban water utilities also have extensive large ferromagnetic structures in the form of critical pressure Pipe systems made of grey cast iron, ductile cast iron and mild steel. The associated material properties render NDE of these Pipes by means of electromagnetic sensing a necessity. In recent years PEC sensing has established itself as a state-of-the-art NDE technique in the critical water Pipe sector. This paper presents advancements to PEC inspection in view of the specific information demanded from water utilities along with the challenges encountered in this sector. Operating principles of the sensor architecture suitable for application on critical Pipes are presented with the associated sensor design and calibration strategy. A Gaussian process-based approach is applied to model a functional relationship between a PEC signal feature and critical Pipe Wall Thickness. A case study demonstrates the sensor’s behaviour on a grey cast iron Pipe and discusses the implications of the observed results and challenges relating to this application.
Arunkumar Sridharan - One of the best experts on this subject based on the ideXlab platform.
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Pipe Wall Thickness prediction with CFD based mass transfer coefficient and degradation feedback for flow accelerated corrosion
Progress in Nuclear Energy, 2018Co-Authors: Mahendra Prasad, V. Gopika, Arunkumar Sridharan, Smrutiranjan ParidaAbstract:Abstract Pipe Wall Thickness reduction due to Flow Accelerated Corrosion (FAC) depends on mass transfer coefficient (MTC), temperature, pH and roughness. The purpose of this research work is to predict the Wall Thickness reduction due to FAC in bends and orifice. The paper proposes a model for temporal Wall Thickness prediction in Pipe bend and orifice taking into account the positive feedback from FAC induced roughness and spatial MTC. This is applied for two geometrical configurations (i) FAC experiment performed on 58° carbon steel Pipe bend (ii) FAC experiment in an orifice with gypsum. In the 58° carbon steel Pipe, the predictions were in good comparison with the experimental values at different locations with percentage error between the predicted and experimental Wall Thickness in the range (−5%, +12%) at all locations on Pipe extrados. For the orifice, the error was in the range of (−0.3 mm, +0.6 mm) at all measured locations. The MTC was estimated using computational fluid dynamics (CFD) with k-w SST (shear stress transport) model for both configurations. The comparison of predicted values of Wall Thickness with experimental values shows that errors in prediction are moderate to low.