Asset Integrity Management at Memorial University, St. Johns

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Asset Integrity Management at Memorial
University, St. Johns

• Faisal Khan
• Director, Oil Gas Engineering
• Seshu Adluri
• Asset Integrity Research

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Outline

• Brief account of AIM at Memorial
• Risk Based Integrity Management
• Asset Integrity Engineering- Advanced techniques

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AIM at Memorial Capabilities

• Asset Integrity Engineering
• Fitness-for-Service,
• Structural Mechanical Integrity of Assets
• Risk Based Integrity Management
• Risk Based Integrity Modeling
• Risk based inspection and maintenance planning

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AIM at Memorial Researchers
Canada Research Chair Dr. R. Seshadri

• Dr. Seshu Adluri
• Dr. Claude Daley
• Dr. A. Swamidas
• ..

• Dr. Faisal Khan
• Dr. M. Haddara
• Dr. Shawn Kenny
• .

• 25 Ph.D. M.Eng.
• 20 other students

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AIM at Memorial Collaborators Supporters

• PRAC
• Lloyds Register EMEA
• Hollyrood Power Plant
• MadRock Solution Inc
• Agip
• ExxonMobil
• Shell
• TransCanada
• WorleyParson

• Canada Research Chairs Program
• NSERC
• Terra Nova (Owners Group)
• CFI (Can. Found. Innovation)
• MUN
• Govt. of Newfoundland Lab.
• BMT, NRC, ACOA, TC, DRDC, SSC, ISSC, ABS, DNV,
  HHI, GL, Chalmers, TKK, ...)

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Major Funding (since 2002)

• CRC 1.4 Million
• PRAC 110,000
• DRDC Transport Canada - 500,000
• NSERC Discovery - 600,000
• CFI Co - 1.25 million
• Petro-Canada - 250,000
• MUN 280,000
• AIF (C-CORE) - 4 million

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AIM at Memorial Achievements

• New generation of Fitness-for-Service techniques
  (Level 2 3), rule development, lab testing,
  advanced numerical techniques
• New Risk Based Integrity Assessment, Inspection
  and Maintenance planning methodology and models
• Industry implementation of the developed
  techniques and continued interest
• Doctoral and Masters Graduate students

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Detailed Presentations of the Two Main Thrusts

• Risk Based Asset Integrity Management
• Faisal Khan

• Fitness-for-ServiceStructural Integrity
• Seshu Adluri

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Why Risk Based Approach?

• Traditional engineering methodology
• Deterministic
• Limited quantitative frameworks to assess
  condition relative to common datum or benchmark
• Difficult decision making
• Incentive
• Focus allocation to optimize risk, which is
  function of hazards and its likelihood
• Efficient and effective decision-making making
• Help to prioritize resources

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Risk Based Approach
It Involves Engineering and Management Science
Risk Based Asset Integrity Management
Risk Based Design
Risk Based Integrity Modeling
Risk Based Planning and Management
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Risk Based Approach

• Attempts to answer
• What may go wrong? Hazard
• How may it go wrong? Mechanism
• How likely is it to occur? Frequency
• What would be the impact? Consequences
• What measures (design, inspection, and
  maintenance) would reduce the likelihood of
  occurrence or impact? Risk Mitigation

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Industry Success

• A semi-quantitative model for risk based asset
  integrity management has been developed and
  successfully applied to
• Thermal power plant
• Ethylene Oxide plant
• A new quantitative RBAIM has been developed and
  applied to
• Process Pipelines
• Autoclave
• Separator
• A new Methodology developed for Risk Based
  Inspection and Maintenance Decision making inline
  with API 580/581 and ASME guidelines

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Future Direction

• Application of quantitative RBIAM to Offshore Oil
  and Gas operation
• Asset Management through Risk based design
• Integration of safety and integrity in holistic
  asset management framework
• Integrity Models for rotary equipment integrity
  assessment and maintenance planning
• Bring facility risk from unit/system level to
  component level
• Integration of human factor elements to risk
  based integrity management

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Fitness-for-Service Research

• Seshu Adluri

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Asset Integrity Eng. (AIE)

• Three major phases in AIE
• Monitoring and testing (NDE)
• Fitness-for-Service Evaluation
• Decision making (risk based)
• In the context of the Oil and Gas Sector,
  Mechanical and Structural Integrity Assessment is
  a multi-disciplinary effort involving
• process chemistry, process engineering,
  thermo-fluids, mechanics, materials, applied
  physics, and computational technology

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Asset Integrity Engineering

• Asset integrity decisions (whether probability
  based or otherwise) need the input regarding
  fitness for service of an existing component
  after some level of damage is suspected or
  detected.
• This input comes from Design and Analysis groups
  and needs to follow guide lines set out by API or
  other bodies.
• The procedures must be easy to apply with high
  confidence level.
• A Canada Research Chair (Dr. Seshadri) and
  several others are actively working in developing
  special techniques for mechanical structural
  integrity

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Asset Integrity Eng. (AIE)

• Industry organizes its activities into design,
  construction and post construction phases
• Post construction phase is further subdivided
  into operations, maintenance and restoration
  activities

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Asset Integrity Eng. (AIE)

• Level 1 Conservative Screening criteria that are
  used with a minimum quantity of inspection data
  or information about the component
• Level 2 Intended for use by facilities or plant
  engineers
• Level 3 Sophisticated analyses by experts where
  advanced computerized procedures are often
  carried out

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Asset Integrity Eng. (AIE)
Grouping of Failure modes

• Category 1 Failures that occur without warning
• Stringent design limits are placed since failures
  occur without warning

• Category 2 Failures that occur due to repeated
  application of loads
• Less stringent limits are placed since damage can
  be detected and inspection/ repairs are possible

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Res. Development Program

• A new generation of methods addressing modes of
  failures for components
• Methods involve advanced concepts (level 3) in
  plasticity and computational methods
• Develop simplified Level 2 methods for Limit
  Loads and Fitness for Service parameters.

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Res. Development Program

• A major thrust is the assessment of
  fitness-for-service of components
• Pressure vessels
• Piping,
• Other equipment,
• The defects include
• Corrosion (single and multiple sites)
• Thermal hotspots
• Fracture and fatigue, ..

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Res. Development Program

• Education and training of personnel
• 15 journal articles and presentations
• Four Ph.D. and two M.Eng. (completed)
• Four Ph.D. (current)
• Several Industry groups in Canada, UK and the US
  have continued interest in the work
• Interdisciplinary R D opportunities

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Advanced Numerical Tech.

• Advanced computational mechanics for Level 3
  verification
• Simplified concepts for interaction effects of
  defects in components (Level 2 methods)
• Shell and plate theory use for deriving simple
  formulas for decay lengths, etc.

• Advanced computational mechanics for Level 3
  verification
• Simplified concepts for interaction effects of
  defects in components (Level 2 methods)
• Shell and plate theory use for deriving simple
  formulas for decay lengths, etc.

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Civil Eng. Installations

• Storage Tanks Seismic demand mitigation
• Crack propagation
• Vibration techniques
• Steel, wood, and concrete structures
• NDE

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Ship Structures Research
ASPECTS DIRECTIONS

• Rule Development (IMO, IACS, SSC, TC)
• Arctic Shipping (LNG, Icebreakers, ...)
• Lab Experiments (frame, grillage, ..impact)
• Analytical Modeling (Limit states, energy
  methods)
• Numerical Modeling (ANSYS, LS-Dyna, cluster
  computer)
• Research Directions (limit states design, hybrid
  construction, sensors, loads, safety, aged
  structures, economics

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Ship Structures Research
Prof. Claude Daley, Director BMT Ocean and
Arctic Structures Research Program
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To sum-up

• Two main thrusts
• Structural Mechanical Integrity of Assets
  (fitness-for-service)
• Risk based Integrity Management
• Seven faculty over 25 grad students
• Total funding 5 million ()

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Questions?
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Qualitative Approach

• Qualitative Hazard Low, Medium, High
• Qualitative Probability Low, Medium, High
• Risk matrix

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Semi Quantitative Approach

• Hazard Estimated using simple empirical model
  based on the characteristics of the system
• Failure Probability Estimated using model as
  well as field observation
• Risk is estimated as HazardFailure probability
• Inspection interval is decided based on the Risk
  factor

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Quantitative Approach

• Hazard Estimated using detailed source model
  based on the characteristics of the system
• Failure Probability Estimated using
  reliability/statistical model as well as field
  observation
• Inspection interval is decided based on the Risk
  factor

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Divide the system into independent (process)
components
Select one component and identify degradation
mechanisms
Model component failure using Gamma Stochastic
process
Estimate the consequence using cost data for
inspection, failure, and replacement
Develop a prior for each degradation mechanism
Obtain Past Inspection results for the unit under
investigation
Determine Failure probability using a Posterior
and past inspection results
Risk Calculations
RBIM Methodology
Estimate optimal inspection and replacement
intervals
Have all components been considered?
Develop inspection plan for the integrity of the
process system
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AIM at Memorial Major Funding (since 2002)

• CRC 1.4 Million
• PRAC 110,000
• DRDC Transport Canada - 500,000
• NSERC Discovery - 600,000
• CFI Co - 1.25 million
• Petro-Canada - 250,000
• MUN 280,000
• AIF (C-CORE) - 4 million

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Risk Based Integrity Management
Consider one component
1
Identify degradation mechanism
Estimate failure probability/frequency
Estimate failure consequences
Estimate risk for the degradation mechanism
All degradation mechanism Assessed ?
No
Yes
Estimate Aggregate risk for the component
A
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RBIM Methodology
A
1
Is Risk within acceptable limit ?
Yes
No
Develop inspection plan based on Past inspection
result and risk profile
Are all units studied?
No
Yes
Units having acceptable risk profile Revise
inspection plan based on recent inspection
results and risk profile
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Risk Based Design

• Optimization and risk mitigation process
• Data, model uncertainty
• Technical, economic, environmental and safety
  targets
• Risk evaluation followed by design action
• Probabilistic methods for
• Process failure
• Explosion and fire modeling
• Environmental load effects
• Structural strength
• Collision and accidental loads

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Risk Based Integrity Modeling

• It aims to model integrity and decide inspection
  and maintenance tasks to satisfy requirements for
  safe operation at minimum cost
• Three main approaches
• Qualitative
• Semi Quantitative
• Quantitative

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Risk Based Planning and Decision Making

• Aggregative Hierarchical Risk Based Decision
  Making (AHR)
• Logical representation, easy to follow and
  assessed
• Relative importance of different degradation
  mechanism
• Contribution as per their active participation
• Easy to upgrade/revise the risk profile