CASE STUDY Digital Twin of Pressure Vessel Joint Industry Project - - PowerPoint PPT Presentation

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CASE STUDY Digital Twin of Pressure Vessel Joint Industry Project - - PowerPoint PPT Presentation

CASE STUDY Digital Twin of Pressure Vessel Joint Industry Project with The Oil and Gas Technology Centre 45% PROJECT DRIVERS REDUCTION IN EQUIPMENT IMPROVE INDUSTRY PRACTICE FOR INSPECTION AND DOWNTIME MAINTANANCE OF PRESSURE VESSELS


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SLIDE 1

CASE STUDY

Digital Twin of Pressure Vessel

Joint Industry Project with The Oil and Gas Technology Centre

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SLIDE 2
  • IMPROVE INDUSTRY PRACTICE FOR INSPECTION AND

MAINTANANCE OF PRESSURE VESSELS

  • UNLOCK THE FULL POTENTIAL OF OGTC’S ROBOTIC

INSPECTION

  • INCREASE ACCURACY/SPEED AND REDUCE

COST/CONSERVATISM OF ASSESSMENT

  • PRODUCE HIGHLY PREDICTIVE FRAMEWORK - FREQUENT

AUTOMATED INSPECTIONS – DETAILED COMPUTATIONAL ANALYSIS

  • THROUGH A PHYSICS-BASED INTERPRETATION OF

INSPECTION DATA.

  • FACILITATED BY AKSELOS STRUCTURAL DIGITAL TWIN

TECHNOLOGY

PROJECT DRIVERS

REDUCTION IN EQUIPMENT DOWNTIME

45%

MAINTENANCE COST REDUCTION

25%

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SLIDE 3

AKSELOS TIES IN PERFECTLY WITH THE FOCUS ON ROBOTICS AND AUTOMATION, HARNESSING THE POWER OF DATA AND TECHNOLOGY TO IMPROVE OVERALL ASSET EFFICIENCY.

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SLIDE 4

PRESSURE VESSELS STRUCTURAL DIGITAL TWINS

NEXT GENERATION SIMULATION TECHNOLOGY

  • 1000x faster than traditional technology
  • Parametric
  • Cloud

STRUCTURAL DIGITAL TWIN

  • Detailed and Physics Based replica of a Physical Asset
  • Sensor connected to reflect real world loading and condition
  • Continual prediction of structural integrity

CAPABILITIES

  • Guide optimization of Inspection, Maintenance & Repair

processes

  • Operational Scenario Planning Support
  • Life extension studies
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SLIDE 5

PRESSURE VESSELS DIGITAL TWIN

INCREASED ACCURACY INCREASED SPEED COST EFFICIENT STANDARDS BASED

FITNESS FOR SERVICE ASSESSMENT SINGLE DIGITAL THREAD FORM INSPECTION TO CALCULATION CALCULATIONS BASED ON HIGH FIDELITY, STRUCTURAL DIGITAL TWIN AUTOMATED DATA FLOW AND PROCESS ROBOTIC INSPECTION THROUGH TO STRUCTURAL ANALYSIS CONSISTENT PROCESS BASED ON SIMULATION (SKIP L1 AND L2 ASSESSMENT) NEW SIMULATION TECHNOLOGY INSPECTION AND REPAIR PLANNING PHYSICS BASED APPROACH USING STRUCTURAL DIGITAL TWIN API 579 ASSESSMENT

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SLIDE 6

CASE STUDY: JOINT INDUSTRY PROJECT SCOPE

  • Produce more accurate predictions for maintenance and inspection - including where and when

repairs will be needed.

  • Simulate robotics inspection data and flows, to enable accurate validation of the structural

integrity (FFS - Fitness For Service),

  • Deliver frameworks for a cost-efficient inspection and repair planning based on Digital Twin.
  • Akselos to demonstrate a new workflow within the API 579 standard that will be much faster than

conventional methods

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SLIDE 7

CASE STUDY: AKSELOS PROVIDES SUPPORT FOR FAST UPLOAD OF INSPECTION DATA

Workflows are accelerated by Akselos with many steps automated

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SLIDE 8

CASE STUDY: AKSELOS SUPPORTS A LEVEL 3 ASSESSMENT OF PRESSURE VESSELS IN AN OPERATIONAL CONTEXT

  • Most detailed evaluation that provides more precise results (within the required API 579 standard)
  • Evaluation equipment for plastic collapse, local failure, collapse from buckling and failure from cyclic

loading General Metal Loss

Elastic Analysis Elastic-plastic Analysis

Local Metal Loss

Elastic Analysis Elastic-plastic Analysis

Assessments

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SLIDE 9

Data inputs Shell component 2D UV mapping Scan plan Thickness profile Thicknesses mapped to Digital Twin

(a) (b) (c) (d) (e)

Automated re-analysis and reporting

(f)

DIGITAL TWIN FOR PRESSURE VESSELS

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SLIDE 10

DIGITAL TWIN IMPLEMENTATION

Digital Twin model creation for Pressure Vessel Fitness-For-Service evaluations based on API-579/ASME FFS-1[1] Full digital thread scenario and automation

REPORT

1X

AUTOMATICALLY REPEATED

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SLIDE 11

Automate Level 1 & Level 2 Assessments of General Metal Loss

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SLIDE 12

CASE STUDY: PRESSURE VESSEL AKSELOS ANALYSIS

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SLIDE 13

AUTOMATE LEVEL 1 ASSESSMENTS OF LOCAL METAL LOSS (2/4)

C-scan Data Marked Local Thin Areas (LTAs) and Grooves (larger than 50 mm2) Extracted Thickness Profile of LTAs and Grooves

  • Ignoring areas which are smaller than 50mm2 (7mm x 7mm)
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SLIDE 14

AUTOMATE LEVEL 2 ASSESSMENT OF GENERAL METAL LOSS

  • Automatically recognize flaws for an assessment
  • Ignoring flaws with area smaller than 500mm2 (23mm x 23mm)

#37 #49

C-scan Data Color Coded Continuous Corrosion Areas (Flaws) (larger than 500 mm2) Extracted Thickness Profile of Flaws

#61

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SLIDE 15

LEVEL 3 ASSESSMENT – EXAMPLE

Protection against Plastic Collapse and Local Failure using Elastic Analysis Method Elasticity results of the “as-is” (updated thickness) model Internal Pressure: 13BAR Internal Pressure: 19BAR

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SLIDE 16

LEVEL 3 ASSESSMENT – IDENTIFICATION OF CRITICAL AREAS

Stress Classification Lines (SCLs) at Critical Locations are identifying manually

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SLIDE 17

LEVEL 3 ASSESSMENT EXAMPLES

Stress Classification Lines (SCLs) at Local Thin Areas are identifying manually

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SLIDE 18

CASE STUDY: PRESSURE VESSEL AKSELOS ANALYSIS

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SLIDE 19

Pristine Model Shell component 2D UV mapping Scan plan Thickness profile Thicknesses mapped to Digital Twin

(a) (b) (c) (d) (e)

Automated re-analysis and reporting

(f)

DIGITAL TWIN FOR PRESSURE VESSELS

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SLIDE 20

PRESSURE VESSEL DIGITAL TWIN: SUMMARY

  • Akselos has demonstrated a new workflow within the API

579 standard that will be much faster than conventional workflows.

  • Produce more accurate predictions for maintenance and

inspection - including where and when repairs will be needed.

  • Integrate robotic inspection data and flows, to enable

accurate validation of the structural integrity (FFS - Fitness For Service assessment into operations),

  • Deliver frameworks for a cost-efficient inspection and repair

planning based on Digital Twin.

  • Industry Research estimate that these improvements with be

a game changer for Inspection planning saving over £140 million across the UK sector alone.

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