Conference Agenda

In this session, Dario Campagna walks attendees across ESTECO's AI research landscape — from Agentic AI and Copilot prototypes in modeFRONTIER, through AI-enabled interoperability at the edges of the digital thread, into LLM-assisted process modeling in Cardanit, and down to next-generation surrogate modeling with Geometric Deep Learning.

Bringing Agentic AI to engineering optimization: a new modeFRONTIER assistant

Francesco Occhioni, ESTECO

AI-driven insights in modeFRONTIER: prototyping the AI Copilot assistant and the Pareto navigator

Enrico Rigoni, ESTECO

2:30 - 2:50 PM

Conference Agenda

Welcome address

modeFRONTIER core updates | Key enhancements and product direction

Introducing nDAI: bridging engineering simulation and machine learning for instant design predictions

VOLTA product update | Data-governed collaborative MDO, future apps ecosystem and the journey to AI implementation

Using VOLTA's BPMN to manage and link engineering handoffs across product design

VOLTA as an enabler of Dumarey’s digital transformation and AI/ML adoption

Integrated CFD–optimization workflow for the hydrodynamic and aerodynamic development of AC75 foiling yachts

AI across the stack: research frontiers at ESTECO

Bringing Agentic AI to engineering optimization: a new modeFRONTIER assistant

AI-driven insights in modeFRONTIER: prototyping the AI Copilot assistant and the Pareto navigator

VOLTA MCP: bringing AI into the Digital Thread

From prompt to process: AI-powered BPMN workflow generation with Cardanit

Geometric deep learning for surrogate modeling

Hull resistance prediction with nDAI

Fast AI-driven simulation of the pantograph-catenary interaction using Reduced Order Models (ROM)

Optimization of rotor and stator geometries to reduce the specific time and space order electromagnetic forcing in IPMSM

Robustness analysis in the modeFRONTIER environment applied to the development of hydraulic pump components using CAE tools

Driving innovation in the Japanese industry: real-world applications of ESTECO Technology

From high fidelity CFD to Reduced Order Modeling for launcher aerodynamics using nDAI

Real-device real-time optimization for advanced DRAM circuit performance

Automation of composite cryogenic tank design and optimization for space launcher application

Automated objective transformation for improved MOGA-II workflows

Enhancements in the aircraft preliminary design methodologies: adoption of sustainable high-fidelity simulations

Sensitivity analysis of high-frequency system-level model of electric drivetrain for accurate common mode voltage and bearing current prediction

Accelerate blast resistance optimization coupling process automation, variability analysis and AI-based metamodels

Digital twin platform for integrated design of tokamak divertor components: a VOLTA-based workflow for multi-physics integration

Design optimization with ESTECO modeFRONTIER – Shaped charge device case study

RBF-FD meshless simulation of compressible flows

Enhancing resistance spot welding predictive accuracy through automated calibration and surrogate modeling

Numerical simulation of aerospace propulsion systems: research and teaching

The use of Cardanit for railway operations simulation: evidence from PORTRAIT project

Inverse calibration of the AA5754-H22 constitutive equation at high temperature

Simulation based product development at Cummins Inc. and the evolution of optimization, automation and robustness

Accelerating F1 engine development: an integrated multi-disciplinary approach to simulation and optimization

Making complexity invisible: accelerating value creation across the engineering lifecycle

Workflow standardization and modeFRONTIER customization

Design and optimization of CO2 capture utilization and storage system

Scaling simulation impact in a small team using modeFRONTIER, VOLTA and Runbox

Enhancing chemical process design and operation through modeFRONTIER: case studies from NEXTCHEM

Automating ADAS/AD validation – A structured approach to study SOTIF risk

Reduced Order Modeling of tubular reactors for synthetic methane production

The hybrid future of simulation engineers with AI

Closing remarks

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