Itsas Memoria: Revista de Estudios Marítimos del País Vasco 1

El Museo Naval de San Sebastián publica el primer número de esta revista dedicada a la historia marítima

Improve reliability using hotelling T2 technique in a liquefied natural gas plant

A method for improve the reliability in a gas liquefied plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when its working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented.Peer Reviewe

Determining the likelihood of incidents caused by human error during dynamic positioning drilling operations

[EN] The probability of a human-caused incident occurring during dynamic positioning (DP) drilling operations is determined in this paper using binary logistic regression models built with data on 42 incidents that took place during the period 2011–2015. For each case, a range of variables characterising the configuration of the DP system, weather conditions and water depth are taken into account. These variables are taken into account to develop a logistic regression model that shows the likelihood of an incident being caused by human error. The results obtained show that human-based incidents are significantly more likely to occur when there is a lower usage of thrusters. These results are useful for focusing our attention on variables that may be associated with incidents attributable to human error, as well as for setting operational limits that could help to prevent these incidents and improve safety during these operations.This research received no specific grant from any funding agency, commercial or not-for-profit sectors

Prediction of Loss of Position during Dynamic Positioning Drilling Operations Using Binary Logistic Regression Modeling

The prediction of loss of position in the offshore industry would allow optimization of dynamic positioning drilling operations, reducing the number and severity of potential accidents. In this paper, the probability of an excursion is determined by developing binary logistic regression models based on a database of 42 incidents which took place between 2011 and 2015. For each case, variables describing the configuration of the dynamic positioning system, weather conditions, and water depth are considered. We demonstrate that loss of position is significantly more likely to occur when there is a higher usage of generators, and the drilling takes place in shallower waters along with adverse weather conditions; this model has very good results when applied to the sample. The same method is then applied for obtaining a binary regression model for incidents not attributable to human error, showing that it is a function of the percentage of generators in use, wind force, and wave height. Applying these results to the risk management of drilling operations may help focus our attention on the factors that most strongly affect loss of position, thereby improving safety during these operations

Risk Analysis of DP Incidents During Drilling Operations

This paper aims to present a method to determine the type of dynamic positioning (DP) incidents that have a more significant risk during drilling operations in the period 2007-2015, according to the element or the type of failure that causes the DP system to fail. Two different classifications are made: 1) according to the element that produces the incident (which has been the traditional classification in the industry) and 2) according to the type of error that arises, the latter being an alternative classification proposed in this paper. The predictable financial losses for each level of severity are used to define the resulting consequences for each case. A risk analysis is performed with the data obtained, showing the potentially more dangerous incidents, either because of their higher number of occurrences or because their consequences are remarkable. According to the classification proposed, the main causes with the higher risk results were power and environmental, according to the traditional classification, and fault/failure. Thus, the power segment’s combination of failures is the riskiest cause during the DP drilling operations

Improve reliability using hotelling T2 technique in a liquefied natural gas plant

A method for improve the reliability in a gas liquefied plant using Hotelling T2 is showed in this paper. The stationery work in this manufacture facilities during a few moths in a year involve a heavy duty service of gas diesel engines and ammonia gas plant for processing the methane gas and extract the condensate fluid of it. Then, a predictive maintenance plan is necessary to prevent a possible malfunction or shut down of the plant and avoid an operational cost increased. We are just sampling the signals from the plant when its working in optimal condition and then we will compare the next incoming data from the machinery versus the previous historical data set. An statistical process control algorithm Hotelling T2 based for monitoring the condition of gas engines and ammonia gas plant will be implemented

Risk Analysis of DP Incidents During Drilling Operations

This paper aims to present a method to determine the type of dynamic positioning (DP) incidents that have a more significant risk during drilling operations in the period 2007-2015, according to the element or the type of failure that causes the DP system to fail. Two different classifications are made: 1) according to the element that produces the incident (which has been the traditional classification in the industry) and 2) according to the type of error that arises, the latter being an alternative classification proposed in this paper. The predictable financial losses for each level of severity are used to define the resulting consequences for each case. A risk analysis is performed with the data obtained, showing the potentially more dangerous incidents, either because of their higher number of occurrences or because their consequences are remarkable. According to the classification proposed, the main causes with the higher risk results were power and environmental, according to the traditional classification, and fault/failure. Thus, the power segment’s combination of failures is the riskiest cause during the DP drilling operations

Principal component analysis to compress acquired data offshore

Telecommunications offshore have connectivity in virtually all parts of the globe via satellite, with increasing bandwidth and lower cost, but still far from levels that are onshore. The principal component analysis (PCA) is a statistical technique that has found application in fields such as biometrics or compression of images, being a common tool for finding patterns in multidimensional data sets. The hypothesis for this work was that it was possible to use the theory of PCA to compress, with sufficient accuracy, the large amount of data that are collected on board to a vessel and then sent by satellite in a more economical or rapid way than the traditional one. The material used were 44 samples of 182 different signals, collected from 19 different equipment on board to “Castillo de Villalba” Liquid Natural Gas carrier vessel. With these data, the PCA algorithm was applied using a computer program developed by the authors, generating new data packets to send by satellite. Different strategies were used in order to ensure that the coefficient of correlation r between original and reconstructed data onshore were equal or greater than 0.95. The results showed that it was possible to save 46.9% in the number of data sent via satellite, in the case of grouping all the 182 signs, with a mean r = 0.95 ± 0.08. This strategy is appropriate for onshore vessel equipment telediagnostic and maintenance decision making, with telecommunication cost or time savings

In vitro surfactant and perfluorocarbon aerosol deposition in a neonatal physical model of the upper conducting airways.

OBJECTIVE: Aerosol delivery holds potential to release surfactant or perfluorocarbon (PFC) to the lungs of neonates with respiratory distress syndrome with minimal airway manipulation. Nevertheless, lung deposition in neonates tends to be very low due to extremely low lung volumes, narrow airways and high respiratory rates. In the present study, the feasibility of enhancing lung deposition by intracorporeal delivery of aerosols was investigated using a physical model of neonatal conducting airways. METHODS: The main characteristics of the surfactant and PFC aerosols produced by a nebulization system, including the distal air pressure and air flow rate, liquid flow rate and mass median aerodynamic diameter (MMAD), were measured at different driving pressures (4-7 bar). Then, a three-dimensional model of the upper conducting airways of a neonate was manufactured by rapid prototyping and a deposition study was conducted. RESULTS: The nebulization system produced relatively large amounts of aerosol ranging between 0.3±0.0 ml/min for surfactant at a driving pressure of 4 bar, and 2.0±0.1 ml/min for distilled water (H2Od) at 6 bar, with MMADs between 2.61±0.1 µm for PFD at 7 bar and 10.18±0.4 µm for FC-75 at 6 bar. The deposition study showed that for surfactant and H2Od aerosols, the highest percentage of the aerosolized mass (∼65%) was collected beyond the third generation of branching in the airway model. The use of this delivery system in combination with continuous positive airway pressure set at 5 cmH2O only increased total airway pressure by 1.59 cmH2O at the highest driving pressure (7 bar). CONCLUSION: This aerosol generating system has the potential to deliver relatively large amounts of surfactant and PFC beyond the third generation of branching in a neonatal airway model with minimal alteration of pre-set respiratory support