Workshops Agenda
Jun 6, 2024 | ESTECO Headquarters, Trieste, ItalyLimited seats available for Users' Meeting attendees: please select the workshops you're interested in when filling out the UM24 registration form.
Master Business Process Management in VOLTA for collaborative design optimization
In this workshop, you'll gain hands-on experience navigating VOLTA's core functionalities for SPDM and design optimization. We will walk you through the entire process from simulation models automation to an optimized design all within an intuitive collaborative web-environment empowered with data analytics.
You will get familiar with VOLTA’s Business Process Management (BPM) technology to map business processes. We will demonstrate how to automate human interactions and integrate simulation execution in a business process workflow, including design optimization.
This workshop is ideal for anyone who needs real time collaboration with peers on simulation-driven design projects in real-time.
- Exchange cross-team simulation data.
- Make simulation workflows available to broader audience of engineers.
- Scale up design optimization across the organization.
- Turn simulation data into actionable insights for collaborative decision-making.
- Model engineering design processes with BPMN 2.0 workflow editor.
- Automate human-in-the-loop and simulation tasks in the business process workflow.
- Execute and monitor engineering design processes.
- Efficiently generate RSMs with the least amount of data.
- Judge and pick the perfect RSM for your engineering problem.
- Take advantage of Machine Learning algorithms.
Unleash the power of surrogate modeling
In this workshop, you will develop the knowledge and trust needed to generate and use Response Surface Models (RSM) to tackle the challenges of heavy simulations or other engineering problems. This workshop is suitable whether you are new to these methodologies or are already an experienced modeFRONTIER user.
- Efficiently generate RSMs with the least amount of data.
- Judge and pick the perfect RSM for your engineering problem.
- Take advantage of Machine Learning algorithms.
- Select the right approach for your multidisciplinary and multiobjective optimization problem.
- Choose among a full suite of deterministic, stochastic and heuristic algorithms.
- Use the self-initializing or autonomous algorithms mode.
Avoid headaches while choosing the optimization strategy
In this workshop, you will discover tips and tricks for choosing and setting-up optimization strategies for different engineering problems. This workshop is dedicated to those modeFRONTIER users who are looking to make the most of their computational time and resources to obtain the best design solution.
- Select the right approach for your multidisciplinary and multiobjective optimization problem.
- Choose among a full suite of deterministic, stochastic and heuristic algorithms.
- Use the self-initializing or autonomous algorithms mode.
- Automate specific solvers and drive simulation chains in modeFRONTIER workflow (Cypython node).
- Exchange data between Python interpreters and modeFRONTIER (pyFRONTIER).
- Use built-in Python algorithms to create a set of DOE design configurations (pyDOE).
- Perform RSM analysis with external Python ML libraries.
- Import your own Python-based algorithm and use it as native modeFRONTIER optimizer(pySCHEDULER).
- Post-process optimization results (pyCONSOLE).
Make use of Python in modeFRONTIER for AI-data driven modeling
In this workshop, you will gain a deep dive into the modeFRONTIER Python ecosystem. Specifically, you will learn how to leverage your Python scripting skills to create custom simulation workflows as well as perform Machine Learning-based data analysis and predictive modeling in modeFRONTIER. This workshop is designed for advanced users willing to exploit the powerful and widely diffused Python libraries to interact with any components of the design project such as tables, RSM, charts, algorithms and process.
- Automate specific solvers and drive simulation chains in modeFRONTIER workflow (Cypython node).
- Exchange data between Python interpreters and modeFRONTIER (pyFRONTIER).
- Use built-in Python algorithms to create a set of DOE design configurations (pyDOE).
- Perform RSM analysis with external Python ML libraries.
- Import your own Python-based algorithm and use it as native modeFRONTIER optimizer(pySCHEDULER).
- Post-process optimization results (pyCONSOLE).
- Perform optimization with data affected by uncertainty.
- Optimize the mean value and minimize the standard deviation of the objective functions.
- Estimate percentile values of objectives and constraints.
Manage uncertainties with robust and reliability-based optimization
In this workshop, you will get an introduction to how modeFRONTIER’s stochastic robust design approach allows you to find so-called “robust” (i.e., more stable at the variation of the uncertain parameters) optimal solutions. This workshop is dedicated to advanced users who want to benefit from robust and reliability-based design optimization strategies to select designs that perform better in the real-world and have the lowest failure rate possible.
- Perform optimization with data affected by uncertainty.
- Optimize the mean value and minimize the standard deviation of the objective functions.
- Estimate percentile values of objectives and constraints.
Limited seats available for Users' Meeting attendees: please select the workshops you're interested in when filling out the UM24 registration form.