Projects

LASAR is a partner of the following National and International Projects.

NATIONAL PROJECTS

Manutenzione intelligente di impianti industriali e opere civili mediante tecnologie di monitoraggio 4.0 e approcci prognostici (MAC4PRO) (link)

INTERNATIONAL PROJECTS

  • Reliable Energy and Cost-Efficient Traction system for Railway (RECET4Rail) (link)
  • Electrical powertrain Health Monitoring for Increased Safety of FEVs (HEMIS) (link)
  • Innovation through Human Factors in risk analysis and management (INNHF) (link)
  • ARISTOTELES: ARtificial Intelligence and STOchasTic simulation for the rEsiLience of critical infrastructurES
    ARISTOTELES is a scientific project that aims to develop a framework to assess the resilience of CEIs by integrating natural hazard and climate change modeling with the stochastic modeling of the cascading process of failures induced by natural events. By integrating artificial intelligence and stochastic simulation, ARISTOTELES provides a scalable approach to quantify, simulate, and optimize the performance of CEIs during such events, to evaluate infrastructure vulnerability and operational performance under uncertainty. More information available here.

  • Safer and More Reliable WBG/UWBG-Based MVDC Power Converters (SAFEPOWER) (link).
    • The SAFEPOWER project is revolutionizing energy systems with the development of next-generation Medium-Voltage Direct Current (MVDC) converters. These compact, sustainable, and secure solutions aim to enhance efficiency, reliability, and power density while reducing environmental impact and costs. By leveraging advanced Silicon Carbide (SiC) devices, β-Ga₂O₃ as an Ultra-Wide Band Gap (UWBG) material, and cutting-edge Control and Health Management (C&HM) techniques, SAFEPOWER is setting new benchmarks in energy technology. The project’s focus on cost-effective and environmentally friendly designs paves the way for greater renewable energy adoption, particularly solar power, and aligns with Europe’s transition to a climate-neutral, circular economy.
      SAFEPOWER’s innovations will make energy systems more efficient, reliable, and affordable, supporting societal needs while fostering Europe’s leadership in green and digital technologies.
      We at LASAR3 are excited to share our role in advancing Machine Learning, Condition and Health Monitoring, and Semiconductor Reliability. These cutting-edge technologies will ensure predictive diagnostics, extended system lifespans, and robust energy performance. As one of the 10 partners from 5 countries, we are proud to contribute to Europe’s transition toward a climate-neutral, circular economy, paving the way for greater adoption of renewable energy and sustainable solutions. Follow the project on LinkedIn: SAFEPOWER EU Project
  • The EU-funded project ResilientGas: A Framework for Modelling and Optimising the Resilience of the Integrated Natural Gas Production and Transmission Network System
    • ResilientGas is a scientific project that aims to develop a model-based optimisation framework for increasing the overall gas supply resilience of integrated natural gas production and transmission (NGPT) networks
    • Natural gas plays a key role in coal-to-gas switching of power generation in the EU, where existing gas capacity could replace up to 50% of the EU’s coal-fired power, equivalent to 20% of the EU’s power sector emissions. And due to the growing global energy demand, expected to increase to 4200 bcm/year by 2050, NGPT networks are critical infrastructures.
    • However, unexpected gas supply interruptions have occurred in the past, leading to huge economic losses. In Europe, during the past two decades, more than 388 incidents in natural gas transmission pipelines have been reported. Furthermore, 39 out of 135 million tonnes of energy-related emissions are from natural gas industry, including emissions from pipelines that can be mitigated by efficient repair programmes, as emphasized by the European Council. Thus, the operation and maintenance (O&M) of gas pipeline networks for energy security, and reliable and continuous supply of natural gas has become a worldwide concern.
    • Methodologically, ResilientGas is constituted by a Markov Decision Process (MDP) model for making sequential decisions under uncertainty while accounting for the dynamics of the system, including network topology and functionality changes upon O&M interventions. Specifically, the project has three research objectives (Os):
      • RO1: Development of a dynamic Graph Neural Network (GNN)-based model to assess the network capacity and estimate the gas supply of an integrated NGPT network as a large system of systems, given the structural and functional limitations of dynamically evolving networks.
      • RO2: Development of a methodological framework for sequential decision making under uncertainty using MDP and solved by advanced Reinforcement Learning (RL) algorithms, considering the NGPT network dynamic structure and functionality, and the dynamic and sequential characteristics of the O&M decisions.
      • RO3: Use of the developed MDP model to propose the optimal strategies of gas supply resilience enhancement for improved decision support to NGPT networks operation and maintenance.
    • ResilientGas has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowships (January 2025 – July 2027) [Grant agreement ID: 101148983] and is positioned within the Laboratory of Analysis of Systems for the Reliability, Risk and Resilience (LASAR3) at the Department of Energy of the Politecnico di Milano, Italy.
    • Researcher: Dr. Masoud Naseri
    • Supervisor: Prof. Enrico Zio

Loading