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DTSTART;TZID=Europe/Rome:20251128T090000
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CREATED:20251117T090714Z
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UID:31657-1764320400-1764334800@www.dica.polimi.it
SUMMARY:From Source to Sample: Mastering Water Monitoring Practices
DESCRIPTION:28 November\, 9:00 – 13:00\nAula Fassò\, Building 4A\, 1st floor\n\nAbstract:\nThe training provides a comprehensive overview of the key technologies and methods used to monitor water quality across a wide range of contexts — from natural ecosystems and urban environments to industrial and agricultural applications. Participants will explore practical tools\, data collection techniques\, and emerging innovations that help assess\, protect\, and manage water resources effectively.\nDesigned to be accessible to a broad audience\, this program does not require prior knowledge in environmental engineering. It is ideal for anyone interested in gaining a deeper understanding of water quality. The focus is on the Polimi community\, including students\, professors\, researchers\, and all interested members of the institution.\nLearning Objectives:\n\nProvide introductory and advanced concepts on monitoring surface and groundwater quality\nIntroduce laboratory analysis of physical\, chemical\, and microbiological parameters\n\nDuration: 4 hours\nMain Topics:\n\nIntroduction to water quality\nThe different uses of water and potability standards\nPreparation and collection of water samples\nPhysical\, chemical and microbiological analysis of water\nAdvanced quantitative analytical techniques: ion chromatography\, liquid chromatography\, and gas chromatography\nWater treatment systems for human and industrial consumption\nMonitoring systems\nThe use of artificial intelligence in water quality monitoring\n\nDiscussions:\n\nAdvanced Water Quality Sensor Technologies and Data Integration\nIsotope and Tracer Techniques in Hydrological and Pollution Studies\nAdvanced Data Analytics\, Modeling\, and Machine Learning in Water Monitoring\nEmerging Contaminants and Microbiological Risk Assessment\nRemote Sensing and Geospatial Analysis for Watershed Monitoring\n\n\nSpeaker’s bio:\nDr. Eva Ferreira completed her bachelor’s degree in Environmental Sanitation in 2012\, placing among the four best students in the group. Soon after\, she began her MBA in Environmental Planning and Management and in early 2013 she began her M.Sc. in Agronomy. Along with her Ph.D.\, she did another MBA in Waste and Wastewater Management. In 2016\, she was among five Brazilians selected by the Erasmus Mundus Association to receive the IBrasil scholarship to do a Sandwich Doctorate in Europe for 10 months. She was hired by the Erasmus Mundus Association to evaluate environmental management policies in Central Europe\, specifically in Slovakia and Austria. During this time\, she acquired in-depth knowledge about European Environmental Policies. With this opportunity she learned about different realities and presented Brazil at the International Conference of Young Scientists and Doctoral Students in Europe. Dr. Eva Ferreira has a Ph.D. in Sanitation\, Environment and Water Resources\, with M.Sc. in Agronomy\, an MBA in Project Management\, an MBA in Environmental Planning and Management and an MBA in Treatment and Final Disposal of Waste and Wastewater. She has been working as a Lecturer in Brazil (Federal University of Goiás and University of São Paulo)\, Vietnam (Vietnamese-German University)\, and Researcher in Portugal (University of Aveiro)\, the Netherlands (Royal Netherlands Academy of Arts and Sciences) and Czech Republic (Tomas Bata University). Her main topics are Environmental Management and Public Policy\, Soil Sciences and Water Management.\n\n\nRegistration:\nIf you are interested in attending either the seminar or the short course\, please register at the following link: https://forms.office.com/e/m7dTvk1Y65
URL:https://www.dica.polimi.it/en/evento/from-source-to-sample-mastering-water-monitoring-practices/
CATEGORIES:Seminari e conferenze
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DTSTART;TZID=Europe/Rome:20251128T110000
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DTSTAMP:20260428T195145
CREATED:20251121T082749Z
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UID:31663-1764327600-1764334800@www.dica.polimi.it
SUMMARY:Generative strategies to empower physics-based wave propagation with deep learning. Applications to earthquake engineering and non-destructive testing.
DESCRIPTION:Venerdì 28 novembre – ore 11:00 CETAula Grandori (Edificio 4)Stanza virtuale: https://politecnicomilano.webex.com/meet/alberto.corigliano \nIl seminario intitolato “Generative strategies to empower physics-based wave propagation with deep learning. Applications to earthquake engineering and non-destructive testing.” sarà tenuto dal Dr. Filippo Gatti\, Maître de Conférences presso CentraleSupélec. \nAbstract \nIn this study\, we present a quantitative evaluation of how elastodynamics simulations can substantially benefit from deep learning–based generative methods integrated with traditional numerical approaches. Two primary frameworks are explored: conditional generative models and neural operators. In the first\, a diffusion model is trained within a time-series super-resolution framework. Its objective is to enhance the outputs of 3D elastic wave numerical simulations—accurate up to 5 Hz in large-scale applications [1\,2]—by extrapolating them to higher frequencies (5–30 Hz) through learning the low-to-high frequency mapping from globally recorded seismograms [3\,4]. The generation process is conditioned on synthetic time histories from numerical simulations\, allowing rapid inference of new wave propagation solutions [4].The second framework demonstrates the effective application of neural operators as full replacements for computationally expensive 3D elastic wave propagation simulations in heterogeneous and anisotropic (polycrystalline) media [5\,6]. This approach paves the way toward real-time\, large-scale digital twins for complex elastodynamics problems [7\,8]\, including earthquake early warning and ultrasonic non-destructive testing in additive manufacturing.Finally\, we present the results of two hybrid strategies that combine diffusion models and neural operators. In these schemes\, zero-shot predictions from neural operators either guide the conditioning and fine-tuning of the super-resolution diffusion model described above or enable transfer learning using a pre-trained GenCFD diffusion model designed for generating solutions to the 3D Navier–Stokes equations [9]. \nSpeaker’s bio \nFilippo Gatti is Maître de Conférences at CentraleSupélec since 2019\, affiliated to Laboratoire de Mécanique des Sols\, Structures et Matériaux (MSSMat) until 2021 and to Laboratoire de Mécanique Paris-Saclay (LMPS) since 2022.He holds a PhD in Civil Engineering from Université Paris-Saclay and Politecnico di Milano (2017)\, as well as a MSc (2014) and BEng (2011) from Politecnico di Milano. He has been JSPS post-doctoral fellow at the Disaster Prevention Research Institute at Kyoto University (2018) and visiting researcher at the Earthquake Research Institute at The University of Tokyo (2021). \nResearch appointmentsSince 2022\, Filippo Gatti is in charge of Research Operation Jumeaux Hybrides: Simulation\, Apprentissage within the LMPS team OMEIR\, as well as LMPS representative for research valorization strategies. \nResearch ActivitiesFilippo Gatti’s research interests cover the physics-based simulation of wave propagation phenomena\, focusing on earthquake engineering and ultrasound wave propagation for non-destructive testing. Since 2014\, Filippo Gatti co-develops the high-performance software SEM3D and maintains its open-source release since 2023. SEM3D is CPU/GPU parallel implementation of the spectral element method applied to 3D elastoacoustic wave propagation in highly heterogeneous and non-linear media. SEM3D has been widely employed for blind earthquake simulation and seismic risk assessment of critical infrastructures\, such as Kashiwazaki-Kariwa nuclear power plant (Japan) and the Cadarache ITER facilities. In this context\, in 2023\, Dr. Gatti’s spin-off project\, EASYRISK\, has been selected as recipient of the POC’UP spin-off program by the SATT Paris-Saclay\, aiming at enabling non-expert users with the realism of SEM3D\, towards achieving physics-based seismic risk assessment.Since 2018\, Dr. Gatti research activities encompass the use of advanced machine learning to improve the fidelity of the numerical solutions of complex wave propagation problems\, by blending physics-based approaches with complex features learned from data.
URL:https://www.dica.polimi.it/en/evento/generative-strategies-to-empower-physics-based-wave-propagation-with-deep-learning-applications-to-earthquake-engineering-and-non-destructive-testing/
CATEGORIES:Seminari e conferenze
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