Upload
homer-charles
View
223
Download
0
Tags:
Embed Size (px)
Citation preview
Reliability Modeling of an ADS Accelerator SNS-ORNL/Myrrha Linac
(MAX project)
EuCARD2, GENEVA (20-21 March 2014 )
CERN
Step 1. SNS Linac modeling (MAX Task 4.2)
– Input Data
– Methodology
– SNS Fault Tree
– Reliability Analysis
– Modeling results evaluation; SNS Logbook Data
– Conclusions
Step 2. Myrrha Linac modeling (MAX Task 4.4)
– Model Assumptions
– Fault tree; Quantification data
– Control System; Fault tolerance
SNS Linac reliability analysis
- feedback on SNS Linac reliability performance
- modeling tool for Myrrha Linac (Task 4.4).
Draft preliminary conclusions and recommendations:
- Maximize the reliability/availability and the safety of the MYRRHA accelerator
- Guidance for designing MYRRHA accelerator.
MAX Task 4.2 - Existing accelerator reliability modeling (methodology currently applied for NPPs – modeling with Risk Spectrum)
The Spallation Neutron Source (SNS – ORNL) Linac was selected
1. SNS Linac Modeling (MAX Task 4.2)
SNS Linac Modeling – Input Data
SNS Design (Systems and Functions)
System functions and interfaces
Components No. (by type)
Degree of redundancy
Data Source:
SNS public info; SNS Design Control Documents (DCDs)
Reliability Data (Quantifying model )
Failure - MTTF and repair times – MTTR
Data Source:
SNS Operation team (SNS BlockSim model – George Dodson, John Galambos)
SNS Operating Data
Component failures modes - cause, type of component, time to repair, etc
Failures causing acc. trips: cause, component and system concerned, duration of trip (Availability data)
Data Source:
SNS Operation Data collection (http://status.sns.ornl.gov/beam.jsp)
SNS BlockSim Model
SNS Linac Modeling – Input Data
http://status.sns.ornl.gov/beam.jsp
The Results from modeling - evaluated with respect to the SNS Logbook operational data - accelerator trip failures and overall availability - recorded during the period October 2011 – June 2012.
General Assumptions
Not modeled – SNS Ring - RTBT, stripper foil, etc. (not relevant for Max project purposes)
Risk Spectrum Type 1 reliability model – Repairable (continuously monitored) – for all SNS Linac components
• Failure/Repair processes – exponential distributions; failure/repair rates ct.
• It is assumed q=0
¨Mean Unavailability¨ type of calculation (unavailability values for the basic events):
Q=λ/(λ+µ
(Long-term average unavailability Q is calculated for each basic event)
SNS Linac Modeling – Methodology
SNS Module 1- first modeling step: RFQ + MEBT + DTL
Gradual development of the SNS Linac model
In-depth understanding of the SNS design and functioning for an accurate model.
SNS Fault Tree (complete model) - graphical representation of the SNS systems functional structure describing undesired events (“ system failures") and their causes.
SNS Linac Modeling – Model development
SNS Linac Fault Tree – main level
SNS Linac Modeling – Fault Tree
DTL RF Fault Tree Structure
SNS Linac Modeling – Fault Tree
1. SNS Linac Modeling
Analysis Case – Results Q = 2.60E-01 = 0.26; Q = 26 %
A = 1 - Q = 73 % (Mean Availability)
Minimal cut set (MCS) analysis - generate minimal cut sets of the fault tree and perform a point-estimate quantification of the top event.
SNS Linac Modeling – Reliability Analysis
SNS Linac Modeling – Analysis Results
In line with the conclusions from the SNS RS Model runs:
RF system and electrical system failures - most frequent
Electrical systems failures - most contributing to accelerator downtime
Accelerator trip failures frequency (by system)
SNS Linac Modeling – Results evaluation; SNS Logbook data (Accelerator trip failures)
Accelerator downtime contribution (by system)
RF System failures (no. & duration-hours)
In accordance with the SCL RS analysis: Most affected subsystems of the SNS Linac (by failures leading to accelerator trips):
SCL-HPRF (Superconducting Linac - High Power Radiofrequency) - short failures frequency
HVCM (High Voltage Converter Modulator - duration of trips
SNS Linac Modeling – Results evaluation; SNS Logbook data (Accelerator trip failures)
The reliability results show that the most affected SNS Linac parts/systems are:
SCL, Front-End systems (IS, LEBT, MEBT), Diagnostics & Controls RF systems (especially the SCL RF system) Power Supplies and PS Controllers
These results are in line with the records in the SNS Logbook
Reliability issue that most needs to be enforced in the linac design is the redundancy of systems, subsystems and components most affected by failures
Need for intelligent fail-over redundancy implementation in controllers, for compensation purposes
Enough diagnostics have to be implemented to allow reliable functioning of the redundant solutions and to ensure the compensation function.
SNS Linac Modeling – Conclusions
1. SNS Linac Modeling
Activities Design & reliability data base (Sources: SNS, Max team, suppliers, conservative assumptions / reliability targets)
Myrrha Linac model - based on the SNS RS Model; considering the SNS reliability analysis results and conclusions.
Iterative process – Myrrha Linac Model updating during design work
Myrrha Linac Risk Spectrum fault tree – 95% completed; preliminary results in line with previous
Reliability analysis to be performed, with due consideration of reliability challenges
Special attention - design of advanced Diagnostics and Control systems
Overall approach
Fault Tree, based on SNS model + Max design
Basic Events: Component / Function failures
Undeveloped Events/Systems: Reliability targets
Reliability model: Availability / Failure frequency (Linac shutdown)
Reliability Analysis: Design Optimization
Myrrha linac - Reliability challenges:
Injector Switch
Fault tolerance/compensation function
SSAs (Solid State Amplifiers) reliability
2. Myrrha Linac Modeling (MAX Task 4.4)
1. SNS Linac Modeling
Myrrha Linac Modeling – General Assumptions
Modeling Assumptions
- RF System: considered SNS (except Klystrons, modulators, & related) SSAs
(spec. RFQ: Myrrha 4-rod (176MHz) vs. SNS RFQ (4-vane))- AUX syst SNS, modified for Myrrha (current design)
- Missing Reliability data
Assumptions
(Equipment overall Reliability data from manufacturer available? (IS ECR, RFQ, SSAs)
Targets
(to be further considered)
/// (detailed design developing the fault trees (rel. data?)
1. SNS Linac Modeling
Myrrha Linac Modeling (Fault tree; quantification data)
Missing Data:
- No significant impact expected - (Comps/Assemblies level of details) - Undeveloped Events
- Relevant impact (INJ switch-magnet, Fault tolerance/Comp. syst., Control syst) – Assumptions/Targets
1. SNS Linac Modeling
Myrrha Linac Modeling (Control Syst.; Fault tolerance)
CTRL System modeling
- Fault tree development (Myrrha control philosophy)
- Rel. Targets to be assigned for: Diagnostics, Data Acquisition & Processing, C-C signals transm., local Control modules, etc.)
- Defined Diagnostics are currently being included in the general CTRL syst. fault tree
1. SNS Linac Modeling
ACKNOWLEDGMENTWe would like to thank G. Dodson and J. Galambos (SNS) for their help in completing the SNS Reliability Study.
Thank you
A.E. PITIGOI – EA ([email protected])
P. FERNANDEZ RAMOS – EA ([email protected])