Motivation for STKO to STKO - Opensees Berkeley.pdf · Opensees, it creates an input (Tool Command...

STKO: a revolutionary toolkit for OpenSees

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• Motivation for STKOAn openbox tool to build and analyze models

• HDF5 databaseManage efficiently large I/O data

• STKO scripting interfaceImplement new tools with a Python Interface

• Computational efficiencyImplement large and complex models

SEMINAR OBJECTIVE


• Introduction to STKO

STKO Scripting interface

Computational efficiency.

Parallel computation (OpenSEES MP)

and IMPL-EX algorithm

OUTLINE


• Motivations

STKO Pre and post processor

Adopted database: HDF5

Proposed file format: MPCO

New recorder class: MPCORecorder

INTRODUCTION TO STKO

STKO: a revolutionary toolkit for OpenSeesIntroduction to STKO

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MOTIVATIONSFE codes research vs profession

Linear, automatic checks, automatic

drawings or BIM (ifc or proprietary),

pre and post processor Black Box

Linear with some basic nonlinearities, automatic

checks, automatic drawings or BIM (ifc or

proprietary), pre and post processor

Black Box some interface with API

Black Box Linear and nonlinear, automatic mesh algorithms,

pre and post processor with some scripting capabilites

(Python, fortran etc.)

Professionals

No research

Professionals

Basic research

High level professionals

Research limited (black box)

OpenseesOpen Box, OpenSource, no mesh algorithms, no pre

and post-processor, TCL scriptsVery limited for professionals

Research limited (no GUI)


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MOTIVATIONSFE codes research vs profession

Linear, automatic checks, automatic

drawings or BIM (ifc or proprietary),

pre and post processor Black Box

Linear with some basic nonlinearities, automatic

checks, automatic drawings or BIM (ifc or

proprietary), pre and post processor

Black Box some interface with API

Black Box Linear and nonlinear, automatic mesh algorithms,

pre and post processor with some scripting capabilites

(Python, fortran etc.)

Professionals

No research

Professionals

Basic research

High level professionals

Research limited (black box)

Open Box, OpenSource, mesh algorithms, pre and

post-processor, TCL scriptsHigh level professionals

Research oriented with GUI


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STKO is a cutting-edge complex data visualization tool for

Opensees, it creates an input (Tool Command Language, TCL)

and output file which can be read with its advanced openGL

graphic interface.

STKO is the only pre and post processor that includes ALL

materials, elements, conditions and interactions offered in

Opensees.

STKO adopts HDF5 database library and Python-based

scripting interface for manipulation and customization of results.

MOTIVATIONSWhat is STKO


Pre-processing

– Real-life structures often leads to complex models

– Input TCL files cannot always be written by hand

– We need an open box scriptable GUI to produce input files

Post-processing issues– High-volume output data

– Heterogeneous results

– Lack of visualization tools for results on fibers

– We need to manipulate and visualize large volume of complex data

Testing– Verification & Validation (NAFEMS)

MOTIVATIONSWhy we need a new tool


Verification

– The process of determining that a computational model accurately

represents the underlying mathematical model and its solution.

– Code Verification – the mathematical model and solution algorithms are

working correctly. Among the Code Verification techniques, the most

popular method is to compare code outputs with analytical solutions;

– Calculation Verification - the discrete solution of the mathematical model is

accurate. Estimating the errors in the numerical solution due to

discretization

Validation

– The process of determining the degree to which a model is an accurate

representation of the real world from the perspective of the intended uses

of the model.

MOTIVATIONSVerification & Validation

What is Verification & Validation? NAFEMS. www.nafems.org

https://www.nafems.org/downloads/wt01v2.pdf


MOTIVATIONSVerification & Validation

Real problem

Conceptualmodel

Mathematical model

Physical model

Computationalmodel

Simulationresults

Simulationoutcome

Ok?

Experiment design

Experimental data

Experimental outcome

Mathematical modeling

Physicalmodeling

Implementation

Implementation

Calculation

Experimentation

UQ

UQ

Code verification

Calculationverification

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Pre

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Revise model or experiment

NO

Adapted from:

What is Verification & Validation?

NAFEMS. www.nafems.org




Motivations

• STKO Pre and post processor






http://opensees.berkeley.edu/OpenSees/manuals/usermanual

Responsible for storing the objects created by

the ModelBuilder object and for providing

the Analysis and Recorder objects access to

these objects.

DomainModelBuilder Analysis

Recorder

Constructs the objects

in the model and adds

them to the domain

Monitors user-defined

parameters in the model

during the analysis

Responsible for

performing the

analysis

STKO PRE AND POST PROCESSOROpensees main abstractions

http://opensees.berkeley.edu/OpenSees/manuals/usermanual/207.htm




Constructs the model (model builder), stores the objects (domain), selects the

parameters to record (recorder) and defines the analysis (analysis)

CAD importer, modeler and mesher

Based on OpenCascade library (https://www.opencascade.com/)

Scripting interface for linking with the external solver

Write tcl files

STKO PRE AND POST PROCESSORPre-processor

https://www.opencascade.com/


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Geometry/Interaction/properties/conditions

Advanced structured and

unstructured meshing tools

Complex nonlinear model analysis,

creation and visualization




Constructs the objects in the model

and store them in the domain


Recorder



Element Node MP_Constraint SP_Constraint LoadPattern Timeseries

Domain

DefinitionCondition

Geometry

Interaction (elements and nodes)

Local axes

Physical properties

Element properties

Mesh


STKO PRE AND POST PROCESSORPre-processor - Domain



Domain

DefinitionCondition

Geometry


Local axes

Physical properties

Element properties

Mesh


STKO PRE AND POST PROCESSORPre-processor –Domain – Element and node


Exchange

Edit

Sets

Points

Curves

Surfaces

Solids

Boolean

STKO PRE AND POST PROCESSORPre-processor - Geometry

Geometry is divided

into eight sections:


Interaction Modeling defines the links

among nodes or elements.

It is used to simulate the relationship

among elements like beam-column,

beam-beam, solid-beam, general

structural constraints etc.

STKO PRE AND POST PROCESSORPre-processor - Interaction


STKO PRE AND POST PROCESSORPre-processor - Interaction

Example Interaction Type:

Node-to-Node links

Slave geometries (faces)

Master Geometry (line)


STKO PRE AND POST PROCESSORPre-processor – Local Axes


STKO PRE AND POST PROCESSORPre-processor – Physical Properties


STKO PRE AND POST PROCESSORPre-processor – Physical Property -Materials

nD Materials

Uniaxial

Materials


STKO PRE AND POST PROCESSORPre-processor – Physical Property - Sections

Sections


STKO PRE AND POST PROCESSORPre-processor – Physical Property –Special purpose

Special Purpose is a

“container” in which more

physical properties coexist


STKO PRE AND POST PROCESSORPre-processor – Physical Property –Element property

All the element in Opensees


STKO PRE AND POST PROCESSORPre-processor – Physical Property –Element property

Order:

Linear (2 or 3 nodes),Triangle (3 or 6 nodes)Quadrilateral (4, 8 or 9 nodes),Tetrahedra (4 or 10 nodes)Hexahedra (8, 20 or 27 nodes –Serendipity)

Algorithm:

StructuredUnstructured

Topology:

Triangular/TetrahedralQuadrilateral/Hexahedral



Domain

DefinitionCondition

Geometry


Local axes

Physical properties

Element properties

Mesh


STKO PRE AND POST PROCESSORPre-processor –Domain – Timeseries


STKO PRE AND POST PROCESSORPre-processor –Definition



Domain

DefinitionCondition

Geometry


Local axes

Physical properties

Element properties

Mesh


STKO PRE AND POST PROCESSORPre-processor –Domain – MP/SP_Constraint, LoadPattern


STKO PRE AND POST PROCESSORPre-processor –Condition




Recorder

Responsible for

performing the

analysis

STKO PRE AND POST PROCESSORPre-processor –Analysis


Introduction to OpenSees and Tcl/Tk OpenSees Days Shanghai 2011, 1Frank McKennaUC Berkeley

STKO PRE AND POST PROCESSORPre-processor – what is an analysis in Opensees


STKO PRE AND POST PROCESSORPre-processor –Analysis - Static


STKO PRE AND POST PROCESSORPre-processor –Analysis - Transient


STKO is implemented for all OpenSees interpreters:

OpenSees.exe

OpseseesSP.exe

OpenSeesMP.exe

STKO PRE AND POST PROCESSORPre-processor –Analysis - Interpreters


STKO PRE AND POST PROCESSORPre-processor –Analysis – OpenseesMP Domain decomposition

10 Partitions


30 Partitions

STKO PRE AND POST PROCESSORPre-processor –Analysis – OpenseesMP Domain decomposition




Recorder

Monitors user-defined

parameters in the

model during the

analysis

STKO PRE AND POST PROCESSORPre-processor –Recorder


_ HDF5-based output database (https://www.hdfgroup.org/)

(originally developed at the National Center for Supercomputing

Applications)

_ Standard plot tools

_ Advanced plot tools for beam elements (fibers, zero-length etc.)

_ Scripting interface for interaction with the Database (in process)

STKO PRE AND POST PROCESSORPost-processor

https://www.hdfgroup.org/


Motivations


• Adopted database: HDF5




For more info:

The HDF Group, "Hierarchical Data Format, version 5," 1997-2017. [Online]. Available: http://www.hdfgroup.org/HDF5/

http://www.hdfgroup.org/HDF5/


_ Opensource (BSD license) library

_ Completely portable file format

_ No limits on the number or size of data objects in the collection

_ Runs on a range of computational platforms, from laptops to massively parallel systems

_ Several languages: C, C++, Fortran90, Java, Python

_ Parallel I/O

STKO ADOPTED DATABASEHDF5 – Why HDF5?


HDF. Hierarchical Data Format is

a set of file formats designed to store

and organize large amounts of data

_ Hierarchical structure

_ Groups (directories)

_ Datasets (data)

_ Attributes (metadata)

STKO ADOPTED DATABASEHDF5 - What does a HDF5 file look like?


Motivations



• Proposed file format: MPCOHow to lay out complex data



For more info:

The HDF Group, "Hierarchical Data Format, version 5," 1997-2017. [Online]. Available: http://www.hdfgroup.org/HDF5/

http://www.hdfgroup.org/HDF5/


Model (+ model stages)

_ Nodes

_ Elements

Geometries + standard and custom integration rules

_ Sections and materials + assignments

Results

_ Results stored on nodes

_ Results stored on elements

On element nodes

On integration points

On sub-integration points (fibers)

PROPOSED FILE FORMATMPCO - What do we need to store in our output file?


• Changes in the original model

• Added/removed elements/nodes

From OpenSees Structural Examples

Infill Wall Model and Element Removal

M. Selim Gunay and Khalid M. Mosalam, University of

California, Berkeley

http://opensees.berkeley.edu/wiki/index.php/Infill_Wall_Mode

l_and_Element_Removal

PROPOSED FILE FORMATMPCO – Multi stages

http://opensees.berkeley.edu/wiki/index.php/Infill_Wall_Model_and_Element_Removal


PROPOSED FILE FORMATMPCO – Each model stage group contains

_ Model information

_ Results


Gauss points Fibers

PROPOSED FILE FORMATMPCO – Model information

• Nodes• Elements

_ Geometry

_ Standard and/or custom

integration rules

• Section assignments_ Element and gauss assignments

_ Fiber data

_ Fiber materials


PROPOSED FILE FORMATMPCO – Results

_ Results on nodes

_ Results on elements

On element nodes

On integration points

On sub-integration points

(fibers)


_ Results on nodes

Displacement/Rotation/Reaction

1 Dataset with selected node IDs

1 Data group

1 Dataset for each time step

PROPOSED FILE FORMATMPCO – Results on nodes


• Groups based on:_ Element type

_ Size of connectivity

_ Type of integration rule

_ Type of cross sections

• Each group contains:_ Metadata group with:

Number of components + labels

Node or gauss ID

Multiplicity

_ 1 Dataset with selected element IDs

_ 1 Data group

_ 1 Dataset for each time step

PROPOSED FILE FORMATMPCO – Results on elements


Motivations




New recorder class: MPCORecorderImplementation of the HDF5 based recorder in OpenSees



NEW RECORDER CLASSMPCORecorder

Implemented in version 3.0.0 of Opensees


Displacements/velocity/acceleration Gauss plots/Strain stresses/Lumped plasticity

Distributed plasticity / fiber model/strain stresses

PROPOSED FILE FORMATMPCO – Plots

STKO: a revolutionary toolkit for OpenSeesScripting Interface

Introduction to STKO

• STKO Scripting interface

Example: automatic calibration of constitutive models in

STKO Pre-Processor

Computational efficiency.

OUTLINE


STKO SCRIPTING INTERFACE

STKO Scripting interface: the X-Object

Adopted constitutive model

Automatic calibration of material parameters

Automatic confinement


Built-in CAD environment

• Create geometries

• Mesh the model

• Define local axes

X-Object components

• Link the STKO pre

processor to OpenSEES

• Uses Python scripting

language

• Customizable: new

components can be

implemented by users

STKO SCRIPTING INTERFACEThe X-Object


Mandatory methods

makeXObjectMetaData

writeTcl

Optional methods

onEditBegin

onAttributeChanged

What an X-Object plug-in look like?

Custom component in OpenSEES

ConcreteDamage.dll

Write a X-Object to link with STKO pre-processor

ConcreteDamage.py

STKO SCRIPTING INTERFACEThe X-Object


ConcreteDamage.py

(Mandatory)

makeXObjectMetaData

• Define a prototype of the new component

• Create all attributes (1 for eachmaterial paramter)

• Add all attributes to the X-Object meta data

STKO SCRIPTING INTERFACEHow to write the X-Object

(Optional)

onEditBegin

onAttributeChanged

• To support inter-parameterdependency

• To improve visual experience


ConcreteDamage.py

(Mandatory)

writeTcl

• Get values of parameters of

the current instance of X-

Object

• Do some processing…

• Write to TCL file

STKO SCRIPTING INTERFACE:How to write the X-Object


Problem

–Non-linear constitutive models have parameters difficult to identify

Objectives

– Create 2 automatic plug-ins for STKO pre-processor:

• Automatic calibration of material parameters from experimental

results

• Automatic calculation of confined materials starting from their

unconfined counterparts and the cross section layout

– The time required to build a model and the possibility of error

STKO SCRIPTING INTERFACEExample: parameter calibration with genetic algorithm

Luisa Berto, Guido Camata, Massimo Petracca, Anna Saetta, Diego Talledo. 2019. Automatic Calibration of

Constitutive Models in STKO Pre-Processor. Opensees Days Eurasia, Hong Kong,20-21 June.


Adopted constitutive model:

_ 2-parameter continuum damage model (d+, d-)

_ Uniaxial version of the model presented in: Tesser L., Filippou F.C., Talledo D.A., Scotta R., Vitaliani R. 2011. Nonlinear Analysis Of R/C Panels By A Two Parameter Concrete

Damage Model. COMPDYN 2011 III ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake

Engineering M. Papadrakakis, M. Fragiadakis, V. Plevris (eds.) Corfu, Greece, 25–28 May.

_ Captures the unilateral effect and stiffness recovery on crack closure

_ A+, A- and B- parameters are complex to calibrate

A genetic algorithm is a stochastic method for function optimization

based on the mechanics of natural genetics and biological evolution



Cauchy stress

Damage thresholds

Damage indices




Notion of Natural Selection

Selection of fittest individuals from

a population.

They produce offspring which inherit

the characteristics of the parents and

will be added to the next

generation.

If parents have better fitness, their

offspring will have a better chance to

survive.

Iterate and at the end, a generation

with the fittest individuals will be

found.


.

Here a genetic algorithms is

used to find input parameters

that best match the

experimental results



STKO SCRIPTING INTERFACEExample: automatic confinement

User input and automatic computation

• Concrete exhibits higher strength and ductility under triaxial stress

states

• The softening branch is less steep when confined

• User input of cross section and reinforcement layout

• User input of unconfined concrete model

• Automatic calculation of the confined concrete model for the core

using:

• Eurocode 2

• Eurocode 8 part 3

• Italian Standard



Pseudo-Code:

write unconfined material;

for each section {

compute confinement parameters;

write confined material;

write core fiber with confined material;

write cover fibers with unconfined material;


Introduction to STKO

STKO Scripting interface

• Computational efficiency Parallel computation (OpenSEES MP) and IMPL-EX

algorithm

OUTLINE

STKO: a revolutionary toolkit for OpenSeesComputational Efficiency

COMPUTATIONAL EFFICIENCY

Approaches for modeling of masonry structures

Tension-Compression Damage model

IMPL-EX algorithm

Numerical application

Conclusions


Macro-modelingMicro-modeling

ComputationalHomogenization

COMPUTATIONAL EFFICIENCYMicro/Macro Modeling of materials


Micro-modeling

Pros:

Easy to model

Low computational costs

Cons:

Complex constitutive models (damage-

induced anisotropy) not available in most

software

Mesh dependent with softening material

models

Pros:

Simple constitutive models for micro-

structural components

Mesh independent

Cons:

Complex to model the whole micro-

structure

High computational costs

VS


Macro-modeling


Micro-modeling

STKO GUI

STKO PARTITIONER

OPENSEES MP


Pros:

Simple constitutive models for

micro-structural components

Mesh independent

Cons:

Complex to model the whole

micro-structure

High computational costs




• Tension-Compression Damage model

IMPL-EX algorithm


Conclusions


• 2-parameter continuum damage model (d+, d-)

• Reference: Cervera M., Oliver J., Faria R., 1995. Seismic evaluation of concrete dams via continuum damage models. Earthquake Engineering and

structural Dynamics. Vol. 24, Issue 9. September. Pag. 1225-1245

• Tension/Compression stress split based on a spectral decomposition of the

effective stress tensor

• Captures the unilateral effect and stiffness recovery on crack closure

where:

COMPUTATIONAL EFFICIENCYTension-Compression damage model with IMPL-EX algorithm for

micromodeling of Masonry/Concrete materials


• 2 independent failure criteria for the tensile and compressive parts

• Failure criteria based on: Lubliner J., Oliver J., Oller S., Oñate E. 1989 A plastic-damage model for concrete. International Journal of Solids and Structures.

Volume 25, Issue 3, Pages 299-326

two scalar measures, termed as

equivalent stresses τ+ and τ−

COMPUTATIONAL EFFICIENCYTension-Compression damage model failure criteria


• Damage growth is an irreversible process

• r, damage thresholds represent the largest values ever attained by the equivalent

stresses (τ-, τ+)

• Damage indices (d+, d-) are functions of the damage thresholds (r-, r+)

COMPUTATIONAL EFFICIENCYTension-Compression damage model thresholds (r-,r+) and damage

indeces (d-, d+)





• IMPL-EX algorithm


Conclusions


2-stage integration

• Explicit extrapolation:

• internal variables at the current time step are explicitly extrapolated

from those at the two previous time steps.

• Used to compute global equilibrium (OpenSEES: in method

‘setTrialStrain’)

• No dependency on the current strain

• Step-wise linear

• Tangent matrix remains symmetric and positive definite (secant

matrix)

• Implicit correction:

• Replaces explicit internal variables with their implicit counterparts

(OpenSEES: in method ‘commitState’)

• Reduces the error generated by the explicit stage

COMPUTATIONAL EFFICIENCYIMPL-EX algorithm Mixed Implicit-Explicit Integration Scheme


COMPUTATIONAL EFFICIENCYIMPL-EX algorithm Mixed Implicit-Explicit Integration Scheme

Oliver J., Huespe A.E., Cante C. 2008. An implicit/explicit integration scheme to increase computability of non-linear material and

contact/friction problems. Computer Methods in Applied Mechanics and Engineering. Volume 197, Issues 21–24, 1 April, Pag. 1865-

1889

Explicit extrapolation at material level





IMPL-EX algorithm

• Numerical application

Conclusions


Two-story masonry building tested at the university of PaviaMagens G, Kingsley G., Calvi G.M. 1995 Seismic testing of a full-scale two-story masonry building: Test procedure and measured experimental

response. ruppo nazionale Difesa dai terremoti (Italy) 41 pages

COMPUTATIONAL EFFICIENCYNumerical applications


COMPUTATIONAL EFFICIENCYNumerical applications. Pre-processor


COMPUTATIONAL EFFICIENCYNumerical applications. Post-processor


Numerical prediction of the d+/d- damage micro-model

COMPUTATIONAL EFFICIENCYNumerical applications. Pre-processor


Numerical prediction of the d+/d- plastic-damage micro-model

𝜎 = 1 − 𝑑𝑝+ 𝜎𝑒

+ + 1 − 𝑑𝑝− 𝜎𝑒

−

𝜎𝑒 = 𝐶0: (𝜀 − 𝜀𝑝)

𝜎 = 1 − 𝑑𝑝+ 𝜎+ + 1 − 𝑑𝑝

− 𝜎−

𝜀𝑝 = 𝜀𝑝 + 𝜆+ 𝜎+

𝜎++ 𝜆−

𝜎−

𝜎−

COMPUTATIONAL EFFICIENCYPlastic damage model





IMPL-EX algorithm


• Conclusions


• Micro-modeling is very accurate even if using simple

constitutive models

• Computational costs of micro-modeling can be drastically

lowered:

– Using parallel computation (OpenSEES MP)

– Using appropriate integration algorithms (IMPL-EX)

COMPUTATIONAL EFFICIENCYConclusions

Motivation for STKO to STKO - Opensees Berkeley.pdf · Opensees, it creates an input (Tool Command...

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