The presentation describes how to integrate Laser Scan Data into FEA Model and Perform Level 3 Fitness-for-Service Assessment of Critical Assets in Refinery & Process Industries. It also, talks about an engineer friendly plugin that helps in the data import with insights from the asset owners and FEA consultants.

1. FEA Based Level 3 Assessment of Deformed Tanks
Arindam Chakraborty, PhD, PE, CTO
Murthy Lakshmiraju, PhD, CFD Technical Director
Georgiy Makedonov, FEA Engineer
Glenn Larson, Senior Design Engineer
Contact: achakraborty@vias3d.com

2. Who We Are
• Multiple Industry Experience – Processing & Refinery, Oil & Gas, Marine and Offshore,
Manufacturing, Machinery & Equipment and other industries.
• Global Presence with HQ in Houston, USA
• Global team of +170 professional with Engineering Services team consisting of +30
professional with majority having PhDs and MSc/MTechs with expertise in Design &
Manufacturing, Structural & Solid Mechanics, Fluid Mechanics, Electromagnetics,
Optimization & Reliability, Data Analytics, System Architecture​, Bioscience and
Materials, Automation, ..
• Dassault Systèmes Platinum Partner – Global Presence – Part of DS Advisory Group
• Provide Software Sales and Support, Training, Engineering services & technical
resource augmentation, PLM implementation, Automation and Customization
Engineering
Services
Training
Automation &
Customization
Software

3. Industries We Serve - ALL
Marine & Offshore
Oil & Gas
Industrial Equipment
Aerospace and Defense
High-Tech
Geotech & Geomech
Consumar Product Goods
Life Sciences
Energy, Process, Utilities
Nuclear: New Construction,
In-Service, Decommissioning
Architecture, Engineering
and Construction
Transportation & Mobility

4. • “Oil and gas industry is playing a significant role in the growth of Storage Tank Market”
• “The Global Storage Tank Market appraised at USD 12.56 billion in 2019 is expected to touch USD 16.87 billion by 2027”, – Global
Storage Market Size, Report, 2020
Since 1965:
• ~74% of storage tank accidents occurred in petroleum refineries or oil terminals.
• ~30% of all storage tank accidents worldwide occurred due to poor operation and maintenance
Guru Gobind Singh Refinery, India (2012)
“Disaster at Pittsburgh”
Oil Tank Collapse (1988)
Design Codes
API 650 (2019) – Welded Tanks for Oil Storage
API 579 (2016) – Fitness for Service
ASME BPVC VIII – Division 2 - Alternative Rules
ASME BPVC II – Materials - Part D – Properties

5. Objective
Integrate Laser Scan Data into FEA
Model to Perform Level 3 Fitness-for-
Service Assessment of Critical Assets in
Refinery & Process Industries
5

6. What is FFS?
• Methodology and procedures determines whether an existing engineering
structure is able to perform its intended function under operating loads.
• There are calculation methods and procedures to assess whether a structure is
operable as it is, needs repair or should be replaced altogether.
• FFS assessments usually require a standard list of information such as original
design conditions, materials of construction, and operation and maintenance
history.

7. Benefits of FFS Assessment
OPERATIONAL AND
MAINTENANCE
REDUCED COSTS
MAINTAIN MECHANICAL
INTEGRITY OF ASSETS
EXTENSION OF ASSETS
SERVICE LIFE
COMPLIANCE OF
REGULATION FOR A
SAFE OPERATION

8. Workflow
Overview
Importing Scan
Data and Navigate
Cleaning Data
Shape
Regeneration
Geometry import to
Abaqus
Assigning Material
Properties and
Sections
Meshing
Application of
Loads and BCs
Analysis
Post-processing /
Integrity
Assessment

9. Workflow (Steps 1 and 2)
Step 1 – Import and Navigate
• Import 10mm x 10mm filtered laser scan data.
• Original data is in ASCII format.
• Scale and trim the data using Digital Shape Preparation app.
Step 2 – Cleaning Data
• The surface generated was based on the down-sampling of the point
cloud data to achieve a smother surface with least deviation.
• The laser scan data is so accurate that you can see the heat radiation
from welding.
• Trim and clean the data to remove erroneous points.
Step 1: Import and Navigate
Step 2: Cleaning Data

10. Tank Surface Generation Analysis
• Catia Digital Shape Editor uses an algorithm to homogenize the data to find the tangent results needed to create the
surface
• This method removes points that cannot possibly be part of a manufactured surface.
• The result is checked against the original unfiltered point cloud for deviation.
• This ensures that you can see what we are removing, making a clean surface that represents the actual manufactured
surface.
The deviation analysis in shows that
the majority of points on the surface
deviate from the point cloud data
between 0 to 25 mm.

11. Workflow (Steps 3 and 4)
Step 3 – Shape Regeneration
• Easily transform a 3D scan into a clean surface.
• The Reverse Engineering role contains also all the features needed to
work with cloud points and scan, such as smoothing, surface network,
etc.
Step 4 – Geometry Import to Abaqus
• Tank surface was imported in Abaqus/CAE as a .STP file to
• Nozzles, appurtenances and rafters were not included in the FEA.
• Bottom plate added to the tank bottom as a shell extension
Step 3: Shape Regeneration
Step 4: Geometry Import to Abaqus

12. Workflow (Steps 5 and 6)
Step 5 – Assigning Material Properties and Section
• Assign the section to the part with appropriate thickness (cloud
thickness data can be used)
• Assign the material properties (SA-387)
• Elastic modulus =200 GPa
• Yield Strength = 245 MPa
Step 6 – Meshing
• Assign the mesh to the part.
• Refine the mesh in the areas of high concern (create partitions if
necessary).
• Number of surface elements S4R, shell reduced integration,
quadrilateral) ~ 350,000
Step 5: Assigning Material Properties and Section
Step 6: Meshing

13. Evaluation Criteria
• Level 3 FFS assessment requires plastic collapse, local failure and nonlinear buckling checks for mechanical integrity of a structure
• Plastic collapse – structure’s global capacity to sustain the applied loads
• Criteria – complete convergence of analysis (structure can sustain the applied loads)
• Local failure – a measure of a structure’s plastic strain against a plastic strain limit.
• Criteria – equivalent plastic strain must be lower the plastic strain limit.
• Nonlinear buckling – determines the local cross-sectional buckling capacity of the structure under the given loads
• Criteria – a load proportionality factor (LPF) greater than 1.0 indicates that the structure will not buckle until load greater the
applied loads is achieved.
Analysis Case Analysis LF (D,P,Ps) LF (W) LF (Ss) LF (E)
Case 1 – Plastic Collapse Linear Elastic 1.0 1.0 1.0 N/A
Case 2a – Plastic Collapse Elastic-Plastic 2.2 N/A N/A N/A
Case 2b – Plastic Collapse Elastic-Plastic 2.0 0.8 2.5 N/A
Case 2c – Plastic Collapse Elastic-Plastic 2.0 1.5 0.8 N/A
Case 2d – Plastic Collapse Elastic-Plastic 2.0 1.5 0.8 N/A
Case 2e – Plastic Collapse Elastic-Plastic 2.0 N/A 0.8 1.5
Case 3 – Local Failure Elastic-Plastic 1.5 N/A N/A N/A
Case 4 – Nonlinear
Buckling
Elastic-Plastic 2.0 1.5 0.8 N/A

14. Workflow (Steps 7 and 8)
Step 7 – Application of Boundary Conditions
• Apply the appropriate boundary conditions
• Bottom surface is fixed (no translation, no rotation)
Step 8 – Application of Loads
• Force is applied at a reference point coupled to inner surface of tank​
• Apply the appropriate loading conditions (in addition to gravity):
• Wind design speed
• Wind pressure load
• Internal Hydrostatic Pressure
• Design Temperature
• Vacuum Pressure
• Snow Load
• Seismic load
Steps 7 and 8: Application of Loads and BC
Load Cases

15. Workflow (Steps 9)
Step 9 – Results Analysis
• The results show that the tank passes plastic collapse, local failure and buckling
checks assessment as stipulated in API 579.
• Some plastically deformed areas​ are observed in tank shell (shown by red colors).
• The governing load for plastic collapse turned out to be the hydrostatic load case.
Plastic Collapse (Elastic-Plastic) Bottom Ring
Local Failure (Elastic-Plastic)
NL Buckling Analysis
Plastic Collapse (Linear Elastic)

16. Conclusions
• The tank shell passes the FFS criteria of API 579 code (plastic collapse,
local failure, buckling). ​
• Tank is fit for service at design conditions.
• No repairs or reinforcements are required to operate the tank based on
assessed conditions.
• It is recommended that non-destructive testing (NDT) of high distortion points
throughout the tank be performed.
Analysis Case Analysis Result
LC 2a (Dead weight,
pressure)
Pass
LC 2b (Dead weight,
pressure, snow, wind)
Pass
LC 2c (Dead weight,
pressure, snow, wind)
Pass
LC 2d (Dead weight, external
pressure, snow, wind)
Pass
LC 2e (Dead weight, external
pressure, snow, seismic)
Pass
Local Failure Pass
Nonlinear Buckling Pass

17. Efficient Simulation using AI-ML
RAW DATA
(INPUT)
DATA
STRUCTURING TRAINING
ML, ANN
PREDICTIONS Output of
Interest (stress,
deformation,
pressure,..)
ML, ANN,
autoencoder
CNN, RNN

18. Liquid Sloshing
Convective Model Analysis of Fluid Sloshing
(From Literature)
• The study will be extended to simulate the effects of combined tank
deformations and fluid sloshing due to seismic ground excitations to estimate
the deformations of the critical structural components due to fluid loading
• Fluid-structure interaction between the fluid and structural components (tank
wall, bottom plate, and roof structure) shall be modeled using a two-way
coupled approach
Image Source: Çelik, Ali & KÖSE, Mehmet & Akgül, Tahir & APAY, Ahmet. (2018).
DIRECTIONAL-DEFORMATION ANALYSIS OF CYLINDRICAL STEEL WATER TANKS
SUBJECTED TO EL-CENTRO EARTHQUAKE LOADING. 1033-1046.

19. Plugin Development
• Workflow automation provides a parametric
flexibility for repetitive tasks and makes the
process more efficient.
• Plug-in development of customized interface
based on user input data
• Inputs that can be easily modified:
• Scan data file selection
• Origin shift
• Node move process
• Node smooth process
• etc.
Contact us for more information on how we can help.

20. Summary
Accurately capturing surface distortion through laser scan
data is of paramount importance.
Multiple load combinations can be assessed efficiently to
determine worst combination of directional loads and surface
distortions.
Using 3DEXPERIENCE platform, geometrical surface derived
from point cloud data can be seamlessly integrated into the
FEA workflow to perform high fidelity FFS assessment using
Abaqus.
The workflow presented here can be used for reliability
studies by introducing variances in measured data and or by
introducing surface profiles for areas lacking measurements.
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21. Questions?
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