Decision making through a Bayesian network for a pipeline in design

2019 ◽  
Vol 59 (1) ◽  
pp. 156
Author(s):  
Francois Ayello ◽  
Guanlan Liu ◽  
Jiana Zhang
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Explicit Knowledge ◽  
Construction Material ◽  
Microbiologically Influenced Corrosion ◽  
Design Stage ◽  
Uniform Corrosion ◽  
Internal Corrosion ◽  
Brine Chemistry ◽  
Corrosion Mechanisms

Decision making for investing in a new pipeline project can be a long and costly process. This is usually due to the uncertainty and missing information regarding the interactions of parameters (e.g. brine chemistry, flow conditions or scale deposition) during internal corrosion assessment. In addition, these interactions result in multiple forms of internal corrosion threats (i.e. uniform corrosion, localised corrosion, erosion-corrosion and microbiologically influenced corrosion). Currently, there are no corrosion models in the market that consider all the different corrosion threats, and the predicted corrosion rates are normally conservative, leading to high overall project cost from the usage of higher grade construction material or strict maintenance regime. To predict a much more accurate internal corrosion rate with consideration of all possible corrosion mechanisms in a pipeline, a Bayesian network (BN) model was created that identifies and quantifies the causal relationships between parameters influencing internal corrosion. The model had previously proven its accuracy in predicting the internal condition of operational pipelines where explicit knowledge is available. However, the model has never been applied for a pipeline in design stage, where the design is based on tacit knowledge. In this study, to evaluate the applicability of this BN model on the pipeline at design stage, an offshore pipeline was assessed for internal corrosion.

The Application of Bayesian Network Threat Model for Corrosion Assessment of Pipeline in Design Stage

2018 ◽  
Author(s):  
Guanlan Liu ◽  
Francois Ayello ◽  
Jiana Zhang ◽  
Peter Stephens
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Threat Assessment ◽  
Operating Conditions ◽  
Microbiologically Influenced Corrosion ◽  
Data Uncertainty ◽  
Design Stage ◽  
Uniform Corrosion ◽  
Bayesian Network Model ◽  
Internal Corrosion

Internal corrosion modeling of oil and gas pipelines requires the consideration of interactions between various parameters (e.g. brine chemistry, flow conditions or scale deposition). Moreover, the number of interactions increases when we consider that there are multiple types of internal corrosion mechanisms (i.e. uniform corrosion, localized corrosion, erosion-corrosion and microbiologically influenced corrosion). To better describe the pipeline internal corrosion threats, a Bayesian network model was created by identifying and quantifying causal relationships between parameters influencing internal corrosion. One of the strengths of the Bayesian network methodology is its capability to handle uncertain and missing data. The model had previously proven its accuracy in predicting the internal condition of existing pipelines. However, the model has never been tested on a pipeline in design stage, where future operating conditions are uncertain and data uncertainty is high. In this study, an offshore pipeline was selected for an internal corrosion threat assessment. All available information related to the pipeline were collected and uncertainties in some parameters were estimated based on subject matter expertise. The results showed that the Bayesian network model can be used to quantify the value of each information (i.e. which parameters have the most effect now and in the future), predict the range of possible corrosion rates and pipeline failure probability within a given confidence level.

Piping Anti–Corrosion Coating Life Assessment

2014 ◽  
Author(s):  
Bahman Modiri ◽  
Mohammad Pourgol Mohammad ◽  
Mojtaba Yazdani ◽  
Farzad Nasirpouri ◽  
Farzin Salehpour
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Pitting Corrosion ◽  
Probabilistic Analysis ◽  
Reliability Index ◽  
Life Assessment ◽  
Uniform Corrosion ◽  
Analysis Framework ◽  
Internal Corrosion ◽  
Corrosion Mechanisms

The pitting corrosion is influential mechanism in determining life of pipes and coatings. Many researches have been conducted on pitting corrosion in the pipelines, resulting in development of some corrosion models. For internal corrosion, there is one main mechanism and it is the uniform corrosion, because dynamic corrosion occurs inside the pipe. However outside the pipe, two corrosion mechanisms are considered for gas pipelines: i) uniform corrosion and ii) pitting corrosion. Effect of uniform corrosion is less than the pitting corrosion, so just pitting corrosion is investigated. Calculating the depth of corroded area is the most important part in this research. This parameter is calculated with two deferent equations for pitting and uniform corrosion. Monte Carlo simulation is used for sampling and calculation of the reliability index. This index is utilized for estimating of reliability. The extended probabilistic analysis framework is applied to a typical gas pipeline.

Hazard Assessment of the Internal Carbon Dioxide Corrosion of the Field Pipelines at the Gas and Gas Condensate Fields

2021 ◽  
pp. 56-62
Author(s):  
R.R. Kantyukov ◽  
◽  
D.N. Zapevalov ◽  
R.K. Vagapov ◽  
◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Gas Condensate ◽  
Design Stage ◽  
Carbon Dioxide Corrosion ◽  
Safe Operation ◽  
Internal Corrosion ◽  
Operating Environments ◽  
Facilities Design ◽  
Equipment And Pipelines ◽  
Intensive Development

At many gas and gas condensate fields in operation, carbon dioxide (СО2) is present in the scope of the produced products, which, in combination with the natural and technological factors, stimulates intensive development of the internal corrosion processes in the pipelines and equipment. The relevance of the development of native regulatory documentation aimed at the assessment of the corrosion effects and development of the practical recommendations for protection against carbon dioxide corrosion in the last decade is due to the development of new gas fields in Russia with a high CO2 content (including on the Russian offshore), where there is a risk of local corrosion development with a high flow rate. The presence of CO2 in the produced gas in combination with the moisture and other factors stimulates the intensive development of corrosion processes and requires careful attention to the assessment of the corrosion aggressiveness of operating environments for selecting an efficient anti-corrosion protection. This is required to ensure reliable and safe operation of the equipment and pipelines made of carbon steel. Pipe low-alloy steel of 09G2S (09Mn2Si) grade, which is the most widely used at the domestic gas facilities, is not resistant to carbon dioxide corrosion. The experience of operating foreign deposits under conditions of carbon dioxide corrosion confirms the need and efficiency of considering this corrosion aspect at the facilities design stage. Incorrect assessment and underestimation of CO2 hazard in the produced hydrocarbons in relation to steel equipment and pipelines can lead to unaccounted corrosion risks (up to the facility shutdown), significant costs for the elimination of corrosion consequences (repairs, etc.), and the need to select and justify urgent corrective measures. Accounting the Russian and international experience allows to make a reasonable choice of rational technical solutions for efficient and safe operation of the deposits in conditions of carbon dioxide corrosion.

scholarly journals Material Origins of Accelerated Operational Wear of RD-33 Engine Blades

2020 ◽  
Author(s):  
Adam Kozakiewicz ◽  
Stanislaw Jóźwiak ◽  
Przemysław Jóźwiak ◽  
Stanisław Kachel
Keyword(s):  
Chemical Composition ◽  
Construction Material ◽  
Operating Conditions ◽  
Design Stage ◽  
Strength Analysis ◽  
Jet Engine ◽  
Emergency Situations ◽  
Low Pressure Turbine ◽  
Propulsion Unit ◽  
Selection Of

The structural and strength analysis of the material used to construct such an important engine element as the turbine is of great significance, both at the design stage as well as during tests and expertises related to emergency situations. Bearing in mind the conditions above mentioned, the paper presents the results of research on the chemical composition, morphology and phased structure of the metallic construction material used to produce the blades of the high and low pressure turbine of the RD-33 jet engine, which is the propulsion unit of the MiG-29 aircraft. The data obtained as a result of the material tests of the blades allowed, on the basis of the analysis of chemical composition and phased structure, to determine the grade of the alloy used to construct the tested elements of the jet engine turbine. The structural stability of the material was found to be lower in comparison with engine operating conditions, which manifested itself as a clear decrease in the resistance properties of the blade material. The results obtained can be used as a basis for analyzing the life span of an object or a selection of material replacements, which enable to produce the analyzed engine element.

scholarly journals Design of Pre Blasting (Pre-Splitting) in Tan Cang Quarry NO.1 in Vietnam

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Nguyen An Dinh ◽  
Thai Hop PHAM ◽  
Cong Dien LE ◽  
Quang Hieu TRAN ◽  
Dinh Bao TRAN
Keyword(s):  
Rock Mass ◽  
Construction Material ◽  
Slope Angle ◽  
Design Stage ◽  
Surrounding Area ◽  
Annual Output

Nowadays, construction material quarries in Dong Nai Province are exploiting with large quarrying depth, and the annual output could reach to tens of million cubic meters. The blasting frequency could be reached to hundreds of times, so the frequency is the major reason decreasing the cohesion of rock mass. Therefore, the surrounding area of blasting holes is broken, especially the area next to the final border where bench slope angle is not implemented as that of design stage, as well as the back break, also causes fractures on the bench slope, resulting in instability and unsafety due to falling rock. In this paper, the author also wants to introduce the pre blasting and the method to define blasting parameters to increase the stabilization of Slopes in Tan Cang quarry NO.1 in Vietnam.

scholarly journals AN INTEGRATED FRAMEWORK UTILISING SOFTWARE AGENT REASONING AND ONTOLOGY MODELS FOR SENSOR BASED BUILDING MONITORING

2015 ◽  
Vol 21 (3) ◽  
pp. 356-375 ◽  
Author(s):  
Michael Dibley ◽  
Haijiang Li ◽  
Yacine Rezgui ◽  
John Miles
Keyword(s):  
Decision Making ◽  
Sensor Network ◽  
Explicit Knowledge ◽  
Knowledge Bases ◽  
Software Agent ◽  
Facility Management ◽  
Good Opportunity ◽  
Integrated Framework ◽  
Intelligent Software ◽  
Building Monitoring

Smart building monitoring demands a new software infrastructure that can elaborate building domain knowledge in order to provide advanced and intelligent functionalities. Conventional facility management (FM) software tools lack semantically rich components, and that limits the capability of supporting software for automatic information sharing, resource negotiation and to assist in timely decision making. Recent hardware innovation on compact ZigBee sensor devices, software developments on ontology and intelligent software agent paradigms provide a good opportunity to develop tools that can further improve current FM practices. This paper introduces an integrated framework which includes a ZigBee based sensor network and underlying multi-agent software (MAS) components. Several different types of sensors were integrated with the ZigBee host devices to produce compact multi-functional sensor units. The MAS framework incorporates the belief-desire-intention (BDI) abstraction with ontology support (provided via explicit knowledge bases). The different software agent types have been developed to work with sensor hardware to conduct resource negotiation, to optimize battery utilization, to monitor building space in a non-intrusive way and to reason about its usage through real time ontology model queries. The deployed sensor network shows promising intelligent characteristics, and it has been applied in several on-going research projects as an underlying decision making service. More applications and larger deployments have been planned for future work.

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