BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Europe/Stockholm X-LIC-LOCATION:Europe/Stockholm BEGIN:DAYLIGHT TZOFFSETFROM:+0100 TZOFFSETTO:+0200 TZNAME:CEST DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220812T074357Z LOCATION:Boston 3 Room DTSTART;TZID=Europe/Stockholm:20220627T160000 DTEND;TZID=Europe/Stockholm:20220627T180000 UID:submissions.pasc-conference.org_PASC22_sess138@linklings.com SUMMARY:MS2H - HPC in Reduced Order Modelling for Advanced Mechanics Simul ations and Digital Twinning DESCRIPTION:Minisymposium\n\nComputational mechanics simulations offer a v aluable analysis tool for engineering applications ranging from design and conceptualization all the way to the operation and maintenance of enginee red systems. Such simulations often involve very detailed High-Fidelity Mo dels (HFM) accounting for complex physics, such as failure, nonlinearities and time-dependence, as well as multi-physics interactions. The resulting computational complexity can be prohibitive for several applications. Thi s is particularly true for Digital Twinning applications, where the digita l representation is often coupled with monitoring data derived from the ph ysical counterpart of the Twin. In this case, models have to be evaluated repeatedly for reliably updating the digital representation, in certain ca ses even in real-time. Reduced Order Modelling (ROM) techniques allow to s ubstantially reduce the involved computational cost, while preserving prec ision. These involve an offline stage, where a ROM is constructed based on information from the HFM, and an online stage where the ROM is deployed. The exploitation of HPC infrastructure is indispensable in both the offlin e and online phase, for ensuring robust training and real-time estimation capabilities, respectively. In this MS, recent advances in ROM methods, al gorithms, and application challenges will be discussed, with a particular focus on exploitation of HPC capabilities and assimilation with data.\n\nP robabilistic Physics-Based Machine Learning for Digital Twinning Enabled b y Bridging Supercomputing and Real-Time Computing\n\nFarhat, Azzi\n\nThis lecture will focus on the construction of a digital twin instance (DTI) – that is, a DT of an individual instance of a product after it has been manufactured and equipped with sensors that provide vital informatio n during its deployment. It can serve many purposes, including: ena...\n\n ---------------------\nLearning Operators with Coupled Attention\n\nKissas , Seidman, Guilhoto, Pappas, Perdikaris\n\nSupervised operator learning is an emerging machine learning paradigm with applications to modeling the e volution of spatio-temporal dynamical systems and approximating general bl ack-box relationships between functional data. We propose a novel operator learning method, LOCA (Learning Operators with...\n\n-------------------- -\nDigital Twinning Organoids, Engineering and Environmental Systems\n\nBo rdas, Skupin, Farina, Urcun, Koronaki...\n\nWe present recent advances in the field of digital twinning of environmental, engineering and biological systems.

We discuss recently developed methods for model orde r reduction, data assimilation, machine learning of severely non-linear an d time-dependent problems. We also discuss param...\n\n------------------- --\nEfficient Unsupervised Constitutive Law Identification and Discovery\n \nFlaschel, Kumar, De Lorenzis\n\nWe propose a new approach for data-drive n automated discovery of constitutive laws in continuum mechanics. The app roach is unsupervised, i.e., it requires no stress data but only displacem ent and global force data, which can be realistically obtained from mechan ical testing and digital image or volu...\n\n\nDomain: Chemistry and Mater ials, Computer Science and Applied Mathematics, Engineering END:VEVENT END:VCALENDAR