Rams Analysis for Different XT Technologies

2021 ◽  
Author(s):  
Markus Glaser ◽  
Tobias Winter
Keyword(s):  
Probability Of Failure ◽  
Hydraulic Actuator ◽  
System Architectures ◽  
Electric Actuator ◽  
Availability Analysis ◽  
On Demand ◽  
Roller Screw ◽  
Critical Components ◽  
Valve Operation ◽  
Reliability And Availability

Abstract This paper analyses the probability of failure on demand of different subsea christmas tree actuation principles and their related control system architectures. The all-electric technology has limited or insufficient field data available. This means that the reliability and availability analysis is based on theoretical analysis from data provided in reliability handbooks for mechanical and electronic components. The analysis includes the probability of failure on demand to isolate the well and the availability of each equipment type until a first failure causes the need for repair. The following different actuator and system designs were chosen for this analysis: – Spring based hydraulic actuator – Spring based electric actuator – Electric power screw actuator – Electric planetary roller screw actuator All Electric Systems (except the spring based electric actuator) utilize a battery to provide the energy for the valve operation. The reliability analysis provides detailed information about the major contributors that limit the reliability of the actuators and systems. With this knowledge, qualification activities can focus on the improvement of the reliability of the critical components and the actuator elements within the system. The power screw actuator and the corresponding system provides the best reliability and availability compared to other systems. The electric with spring design provides better results than the hydraulic with spring design. Generally, the battery-based systems provide a better reliability than spring-based designs. The most critical elements are the mechanical springs, sealings, brakes and the spindle mechanisms. Another aspect is the analysis of an optimized operation strategy in order to utilize the redundant components to improve the availability and reduce the number of interventions by analysis of the second and third failure in the system.

scholarly journals Unavailability of K-out-of-N: G Systems with non-identical Components Based on Markov Model

2019 ◽  
Vol 2 (1) ◽  
pp. 25-35
Author(s):  
Ayodeji Akinsoji Okubanjo ◽  
Olasunkami oriola Akinyemi ◽  
Oluwadamilola Kehinde Oyetola ◽  
Olawale omopariola Olaluwoye ◽  
Olufemi Peter Alao
Keyword(s):  
Markov Model ◽  
Probability Of Failure ◽  
Process Industry ◽  
Redundant System ◽  
System Architectures ◽  
On Demand ◽  
Proposed Model ◽  
Challenging Tasks ◽  
Average Probability ◽  
Analytical Formulas

The process industry has always been faced with the challenging tasks of determining the overall unavailability of safety instrumented systems (SISs). The unavailability of the safety instrumented system is quantified by considering the average probability of failure on demand. To mitigate these challenges, the IEC 61508 has established analytical formulas for estimating the average probability of failure on demand for K-out-of-N (KooN) architectures. However, these formulas are limited to the system with identical components and this limitation has not been addressed in many researches. Hence, this paper proposes an unavailability model based on Markov Model for different redundant system architectures with non-identical components and generalised formulas are established for non-identical k-out-of-n and n-out-of-n configurations. Furthermore, the proposed model incorporates undetected failure rate and evaluates its impact on the unavailability quantification of SIS. The accuracy of the proposed model is verified with the existing unavailability methods and it is shown that the proposed approach provides a sufficiently robust result for all system architectures.  

scholarly journals Reliability, Availability, and Maintainability Usage in the Development of the 501F Combustion Turbine and Auxiliaries

1991 ◽  
Author(s):  
R. J. Engel ◽  
P. J. Tyler ◽  
L. R. Wood ◽  
D. T. Entenmann
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Conceptual Design ◽  
High Reliability ◽  
Full Range ◽  
Design Phase ◽  
Conceptual Design Phase ◽  
Critical Components ◽  
Tools And Techniques ◽  
Reliability And Availability

Westinghouse has been a strong supporter of Reliability, Availability, and Maintainability (RAM) principles during product design and development. This is exemplified by the actions taken during the design of the 501F engine to ensure that high reliability and availability was achieved. By building upon past designs, utilizing those features most beneficial, and improving other areas, a highly reliable product was developed. A full range of RAM tools and techniques were utilized to achieve this result, including reliability allocations, modelling, and effective redesign of critical components. These activities began during the conceptual design phase and will continue throughout the life cycle of these engines until they are decommissioned.

scholarly journals Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Ahmed H. Aburawwash ◽  
Moustafa Mohammed Eissa ◽  
Azza F. Barakat ◽  
Hossam M. Hafez
Keyword(s):  
Genetic Algorithm ◽  
Accurate Determination ◽  
Probability Of Failure ◽  
System Structure ◽  
Control Element ◽  
Algorithm Optimization ◽  
On Demand ◽  
Uncertainty Sources ◽  
Iec 61508 ◽  
Proposed Model

A more accurate determination for the Probability of Failure on Demand (PFD) of the Safety Instrumented System (SIS) contributes to more SIS realiability, thereby ensuring more safety and lower cost. IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas. However, these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources, which, including high redundant systems architectures, cannot be assessed, have perfect proof test assumption, and are neglegted in partial stroke testing (PST) of impact on the system PFD. On the other hand, determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time. This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem. A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor (DC) and common cause failures (CCF). In order to simulate the proof test effectiveness, the Proof Test Coverage (PTC) factor has been incorporated into the formula. Additionally, the system PFD value has been improved by incorporating PST for the final control element into the formula. The new developed formula is modelled using the Genetic Algorithm (GA) artificial technique. The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables. The proposed model has been applicated on SIS design for crude oil test separator using MATLAB. The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality. Furthermore, the cost and associated implementation testing activities are reduced.

ChunkSim

2010 ◽  
pp. 131-149
Author(s):  
Pedro Furtado
Keyword(s):  
Performance Analysis ◽  
Simulation Analysis ◽  
System Size ◽  
Analysis Tool ◽  
Data Allocation ◽  
Data Warehouses ◽  
Availability Analysis ◽  
On Demand ◽  
Self Tuning ◽  
Insight Into

Self-tuning physical database organization involves tools that determine automatically the best solution concerning partitioning, placement, creation and tuning of auxiliary structures (e.g. indexes), based on the workload. To the best of our knowledge, no tool has focused on a relevant issue in parallel databases and in particular data warehouses running on common off-the-shelf hardware in a sharednothing configuration: determining the adequate tradeoff for balancing load and availability with costs (storage and loading costs). In previous work, we argued that effective load and availability balancing over partitioned datasets can be obtained through chunk-wise placement and replication, together with on-demand processing. In this work, we propose ChunkSim, a simulator for system size planning, performance analysis against replication degree and availability analysis. We apply the tool to illustrate the kind of results that can be obtained by it. The whole discussion in the chapter provides very important insight into data allocation and query processing over shared-nothing data warehouses and how a good simulation analysis tool can be built to predict and analyze actual systems and intended deployments.

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