Real Time 24/7 Integrity Monitoring of Mooring Lines, Risers and Umbilicals on an FPSO using 360 degree Multibeam Sonar Technology

2013 ◽  
Author(s):  
Angus Lugsdin
Keyword(s):  
Real Time ◽  
Mooring Lines ◽  
Integrity Monitoring ◽  
Multibeam Sonar

scholarly journals Real-time Container Integrity Monitoring for Large-Scale Kubernetes Cluster

2021 ◽  
Vol 29 (0) ◽  
pp. 505-514
Author(s):  
Hirokuni Kitahara ◽  
Kugamoorthy Gajananan ◽  
Yuji Watanabe
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Integrity Monitoring

scholarly journals New techniques for real-time monitoring of reverse osmosis membrane integrity for virus removal

2018 ◽  
Vol 13 (4) ◽  
pp. 947-957 ◽  
Author(s):  
V. S. Frenkel ◽  
Y. Cohen
Keyword(s):  
Real Time ◽  
Reverse Osmosis ◽  
Health Hazard ◽  
Membrane Damage ◽  
Membrane Integrity ◽  
Enteric Viruses ◽  
Water Stream ◽  
Potential Health ◽  
Integrity Monitoring ◽  
Virus Removal

Abstract This paper presents methodology, concept and results of the WateReuse Foundation project WFR – 09 – 06b when developing a high pressure membrane, reverse osmosis (RO) and nanofiltration (NF) online membrane integrity testing (MIT) technique. The use of pressure-driven membrane processes, particularly RO, has grown significantly over the past few decades in water treatment and reuse applications to safeguard water supplies against harmful pathogens and impurities. In principle, RO membranes should provide a complete physical barrier to the passage of nanosize pathogens (e.g., enteric viruses). However, in the presence of imperfections and/or membrane damage, membrane breaches as small as 20 to 30 nm can allow enteric viruses to pass through the membrane and contaminate the product water stream, thereby posing a potential health hazard that is of particular concern for potable water production. This project was focused on evaluating a pulsed-marker membrane integrity monitoring (PM-MIMo) approach for RO processes on the basis of the use of a fluorescent marker. The monitoring approach employs pulsed dosing (via a precision metering pump) of a marker into the RO feed stream coupled with online marker concentration monitoring in the RO permeate by an inline spectrofluorometer. Membrane integrity is then inferred on the basis of real-time analysis of the marker permeate time − profile concentration in response. The basic concept of the PM-MIMo approach for detecting membrane breaches was successfully demonstrated, by comparing intact and damaged membranes, in a series of experiments using a diagnostic plate-and-frame RO system and spiral-wound RO pilot system. Results of the developed technique are presented in the project report to allow the industry to consider adopting this technique for RO/NF online integrity monitoring.

scholarly journals Integrity Monitoring for Carrier Phase Ambiguities

2011 ◽  
Vol 65 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Shaojun Feng ◽  
Washington Ochieng ◽  
Jaron Samson ◽  
Michel Tossaint ◽  
Manuel Hernandez-Pajares ◽  
...  
Keyword(s):  
Least Squares ◽  
Real Time ◽  
Ambiguity Resolution ◽  
Carrier Phase ◽  
Integer Number ◽  
Integrity Monitoring ◽  
Level Of Confidence ◽  
F Distribution ◽  
Position Solution ◽  
T Distribution

The determination of the correct integer number of carrier cycles (integer ambiguity) is the key to high accuracy positioning with carrier phase measurements from Global Navigation Satellite Systems (GNSS). There are a number of current methods for resolving ambiguities including the Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) method, which is a combination of least-squares and a transformation to reduce the search space. The current techniques to determine the level of confidence (integrity) of the resolved ambiguities (i.e. ambiguity validation), usually involve the construction of test statistics, characterisation of their distribution and definition of thresholds. Example tests applied include ratio, F-distribution, t-distribution and Chi-square distribution. However, the assumptions that underpin these tests have weaknesses. These include the application of a fixed threshold for all scenarios, and therefore, not always able to provide an acceptable integrity level in the computed ambiguities. A relatively recent technique referred to as Integer Aperture (IA) based on the ratio test with a large number of simulated samples of float ambiguities requires significant computational resources. This precludes the application of IA in real time.This paper proposes and demonstrates the power of an integrity monitoring technique that is applied at the ambiguity resolution and positioning stages. The technique has the important benefit of facilitating early detection of any potential threat to the position solution, originating in the ambiguity space, while at the same time giving overall protection in the position domain based on the required navigation performance. The proposed method uses the conventional test statistic for ratio testing together with a doubly non-central F distribution to compute the level of confidence (integrity) of the ambiguities. Specifically, this is determined as a function of geometry and the ambiguity residuals from least squares based ambiguity resolution algorithms including LAMBDA. A numerical method is implemented to compute the level of confidence in real time.The results for Precise Point Positioning (PPP) with simulated and real data demonstrate the power and efficiency of the proposed method in monitoring both the integrity of the ambiguity computation and position solution processes. Furthermore, due to the fact that the method only requires information from least squares based ambiguity resolution algorithms, it is easily transferable to conventional Real Time Kinematic (RTK) positioning.

Artificial Neural Networks for Reducing Computational Effort in Active Truncated Model Testing of Mooring Lines

2015 ◽  
Author(s):  
Niels Hørbye Christiansen ◽  
Per Erlend Torbergsen Voie ◽  
Jan Høgsberg
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Real Time ◽  
Physical Model ◽  
Hybrid Method ◽  
Numerical Models ◽  
Computational Effort ◽  
Computational Power ◽  
Mooring Lines ◽  
Numerical Efficiency

As oil and gas exploration moves to deeper waters the need for methods to conduct reliable model experiments increases. It is difficult obtain useful data by putting a scaled model of an entire mooring line systems into an ocean basin test facility. A way to conduct more realistic experiments is by active truncated models. In these models only the very top part of the system is represented by a physical model whereas the behavior of the part below the truncation is calculated by numerical models and accounted for in the physical model by active actuators applying relevant forces to the physical model. Hence, in principal it is possible to achieve reliable experimental data for much larger water depths than what the actual depth of the test basin would suggest. However, since the computations must be faster than real time, as the numerical simulations and the physical experiment run simultaneously, this method is very demanding in terms of numerical efficiency and computational power. Therefore, this method has not yet proved to be feasible. It has recently been shown how a hybridmethod combining classical numerical models and artificial neural networks (ANN) can provide a dramatic reduction in computational effort when performing time domain simulation of mooring lines. The hybrid method uses a classical numerical model to generate simulation data, which are then subsequently used to train the ANN. After successful training the ANN is able to take over the simulation at a speed two orders of magnitude faster than conventional numerical methods. The AAN ability to learn and predict the nonlinear relation between a given input and the corresponding output makes the hybrid method tailor made for the active actuators used in the truncated experiments. All the ANN training can be done prior to the experiment and with a properly trained ANN it is no problem to obtain accurate simulations much faster than real time — without any need for large computational capacity. The present study demonstrates how this hybrid method can be applied to the active truncated experiments yielding a system where the demand for numerical efficiency and computational power is no longer an issue.

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