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Arcelormittal @ Scilab Conference 2018

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Diabolo, the ArcelorMittal framework for management of Scientific Models Lifecycle

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Arcelormittal @ Scilab Conference 2018

  1. 1. 1www.esi-group.com Copyright © ESI Group, 2018. All rights reserved.Copyright © ESI Group, 2018. All rights reserved. www.esi-group.com Welcome Stéphane Jimenez, ArcelorMittal global R&D November 20th, 2018
  2. 2. 2www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 2 The Diabolo Paradigm
  3. 3. 3www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 3 The Diabolo Paradigm ArcelorMittal R&D develop numerical models since more than 30 years Models are (very) heterogeneous in technology and structure … Developers are geographically distributed … Models are used and maintained by many different users over time … Models are not easily shared nor re-used  can be redeveloped instead Models Lifecycle is hard to manage  lost of [digital] knowledge  huge ‘Time to Industrial Use’ Ease models sharing and reuse Ease chaining and Multi-Domain simulation Support Models LifeCycle … enter a virtual circle to enhance our Digital Knowledge
  4. 4. 4www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 4 The Diabolo Paradigm A gateway between R&D and Industry worlds … from Innovation to industrialization … from exploratory to standards … to support Models Lifecycle Tools, methods (standards) and organization
  5. 5. 5www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 5 The Diabolo Solution
  6. 6. 6www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 6 Module Generator Scientific documentation Executable component Technical specification and user help C, FORTRAN, Java, Scilab, Python*, Excel** A centralized Model Repository and a Depot Model Publication Workflow
  7. 7. 7www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 7  Authenticated access to the ArcelorMittal ATOMS depot  Advanced user friendly tools : Data, Statistical, Analysis, Optimization, Plots  Model access is filtered according to the user role A centralized Model Repository and a Depot Diabolo Model block Diabolo Control (source) blocks Diabolo Visualization (sink) blocks
  8. 8. 8www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 8 A powerful and user friendly Toolbox set  Complete data port management thru a graphical interface Model blocks embed Input and Output data multiplexors  USER_BLOCK permit to easily program specific simulation blocks  Advanced blocks comes with a user friendly interface Edit source code
  9. 9. 9www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 9 A powerful user friendly Toolbox set In a simple (graphical) way  Model Chaining  Data Access  Tools for Parametric studies  Optimization and reverse analysis Evolution of the cooling profile associated to each individual Evolution of the cost associated to the population of one hundred individuals Optimizing cooling profile with genetic algorithm (NSGA II) bock Chaining ‘product model’ (flat carbon) with ‘process model’ (Pipe Forming) Analysis of Sensibility
  10. 10. 10www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 10  About 300 developers & users of model Diabolo today … 120 users, 80 models
  11. 11. 11www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 11 Advanced Use Cases The Building Physics simulator concept
  12. 12. 12www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 12 The Building Physics simulator concept Optimization for Advanced Design System Toolbox (optimADS)  Previously developed in an exploratory project in automotive by ArcelorMittal global R&D and INRIA  Multi-objective optimization based on surrogate model construction  A Non-dominated Sorting Genetic Algorithm is used to optimize the surrogate model  Non dominated solutions are extracted using Scilab pareto_filter  Easy configuration thanks to a user friendly interface DACE for generation of Surrogate model SVM-KM to reduce the number of variable of surrogate model NSGA II for fitting of Surrogate model A Java GUI o define  Name of the file to save the calculated DOE  List of optimization variables and their bounds  List of optimization objectives and their bounds  Scilab code for DOE discrete projection  Scilab code for constraints on optimization variables
  13. 13. 13www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 13 The Building Physics simulator concept Use of existing ArcelorMittal global R&D models, software and solvers for Buildings  Price and weigh estimation of Steel framed buildings  Mechanical constraints and thermal properties for “sandwich” panel facade  Heating and cooling Energy  LCA and Cost Modules Building dimensions Type of Slabs and Reinforce Weight and thickness of Slabs Total steel weight Total steel frame price Project definition Building use, time life, localization, type of facade, % opening, king of heating Grid span Façade Thickness Mechanic and Thermal properties of Façade
  14. 14. 14www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 14 The Building Physics simulator concept Use of existing ArcelorMittal global R&D models, software and solvers for Buildings  Price and weigh estimation of Steel framed buildings  Mechanical constraints and thermal properties for “sandwich” panel facade  Heating and cooling Energy  LCA and Cost Modules CO2 Total cost Heating + Cooling energy Energy consumption for heating and cooling CO2 quantity Primary Energy Demand Non dominated solutions
  15. 15. 15www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 15 The Building Physics simulator concept The global PIDO schema has been calculated in Diabolo  The whole optimization is an automated process  Calculation time is huge due to thermal calculation ( HPC !)  The use of surrogate is essential to explore wide range of the space of solution  Very promising results have demonstrated the Proof of Concept Original combination of grid span and façade thickness
  16. 16. 16www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 16 Advanced Use Cases (Quick release of) Rich GUI applications for Process Study use
  17. 17. 17www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 17 Rich GUI applications for Process Study use Generic architecture for a rich GUI application framework  Use Scilab Engine API for model running  Distribute Model as Diabolo Modules [Scilab Gateways]  Develop generic Qt widget to capitalize graphic components  Setup a Model Engine able to dynamically setup the GUI for a model  Significant speed up the model delivery process  20 single or chained models deployed in factories for Process Study Use  More than 200 users
  18. 18. 18www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 18 Advanced Use Cases The Statistical Model Toolbox
  19. 19. 19www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 19 The Statistical Model Toolbox ArcelorMittal Statistical Toolbox Automatic generation of linear and non linear models from industrial data  Previously developed in Splus (commercial implementation or R language)  Fully ported to Scilab V5 and currently porting to V6  Will be release under two form : A Diabolo Toolbox and a Windows rich GUI application NaN-toolbox for clustering and correlation XLS_link for data import / export and reporting Diabolo toolbox and Windows Rich GUI application  Vapnik model to estimate and order influence of data  Automated generation and optimization of models  Analysis and filtering tools Stixbox to calculate linear regression Stability SPC Vapnick curve Foolproof Performance
  20. 20. 20www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 20 The Statistical Model Toolbox Lifecycle mgmt. for Statistical Metallurgical Models Research Engineer Process Engineer Process data Study Refinement Validation Quality Control Product Qualification Configuration Manager for the Quality Platform Comit to Config Mgmt
  21. 21. 21www.esi-group.com Copyright © ESI Group, 2018. All rights reserved. 21 Thank you !

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