BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240412T201243Z UID:85C3658D-B1BF-4136-A0DB-E59B46FAA60C DTSTART;TZID=America/New_York:20240412T150000 DTEND;TZID=America/New_York:20240412T160000 DESCRIPTION:Simulation-driven design changed product development forever\, enabling engineers to reduce design\, iterations\, and prototype testing. Increasing scientific computing power expanded the opportunity to apply an alysis\, making large design studies possible within the timing constraint s of a program. Now engineering adoption of Artificial Intelligence (AI) a nd Machine Learning (ML) is transforming product development again. Combin ation of physics-based simulation-driven design with machine learning\, le veraging the latest in high-performance cloud computing\, enables industry to explore more and identify high-potential designs – while rejecting l ow-potential concepts – even earlier in development cycles as well as he lp create “Digital Twins”. With the increase in connected devices and platforms (such as 5G\, 6G\, C-V2X\, ADAS etc.)\, advanced computational e lectromagnetic (CEM) tools have become part of the product design cycle. N ow numerical simulations can be performed to evaluate the effects of anten na design\, placement\, radiation hazard\, EMC/EMI\, etc. for wide ranging industry applications. Interfacing with propagation tools\, system level design can be accomplished that includes operating environment of the devi ces for device connectivity and throughput. Advent of cloud computing and AI/ML\, and convergence with CEM simulations made connected\, smart device design faster with reduced time from concept to the market propelling pro ductivity and innovation. This talk will focus on advanced CEM simulation tools that incorporate numerical methods\, such as Method of Moments (MoM) \, Multilevel Fast Multipole Method (MLFMM)\, Finite Element Method (FEM)\ , Finite Difference Time Domain (FDTD)\, Physical Optics (PO)\, Ray Lunchi ng Geometrical Optics (RL-GO)\, and Uniform Theory of Diffraction (UTD). A s the complexity of connected devices increases each day\, designers are t aking advantage of AI/ML to generate trained models for their physical ant enna designs and perform fast and intelligent optimization on these traine d models. Using the trained models\, different optimization algorithms and goals can be run quickly\, in seconds\, that can be utilized for comparis on studies\, stochastic analysis for tolerance studies etc. Use of cloud c omputing combined with AI/ML\, many design iterations can be performed in a short period and reducing the time to market. This talk will also focus on future trends in cloud computing for physics-based simulations and the emerging topics such as Digital Twins.\n\nCo-sponsored by: Wright-Patt Mul ti-Intelligence Development Consortium (WPMDC)\, The DOD & DOE Communities \n\nSpeaker(s): C.J. Reddy\n\nAgenda: \nSimulation-driven design changed p roduct development forever\, enabling engineers to reduce design\, iterati ons\, and prototype testing. Increasing scientific computing power expande d the opportunity to apply analysis\, making large design studies possible within the timing constraints of a program. Now engineering adoption of A rtificial Intelligence (AI) and Machine Learning (ML) is transforming prod uct development again. Combination of physics-based simulation-driven desi gn with machine learning\, leveraging the latest in high-performance cloud computing\, enables industry to explore more and identify high-potential designs – while rejecting low-potential concepts – even earlier in dev elopment cycles as well as help create “Digital Twins”. With the incre ase in connected devices and platforms (such as 5G\, 6G\, C-V2X\, ADAS etc .)\, advanced computational electromagnetic (CEM) tools have become part o f the product design cycle. Now numerical simulations can be performed to evaluate the effects of antenna design\, placement\, radiation hazard\, EM C/EMI\, etc. for wide ranging industry applications. Interfacing with prop agation tools\, system level design can be accomplished that includes oper ating environment of the devices for device connectivity and throughput. A dvent of cloud computing and AI/ML\, and convergence with CEM simulations made connected\, smart device design faster with reduced time from concept to the market propelling productivity and innovation. This talk will focu s on advanced CEM simulation tools that incorporate numerical methods\, su ch as Method of Moments (MoM)\, Multilevel Fast Multipole Method (MLFMM)\, Finite Element Method (FEM)\, Finite Difference Time Domain (FDTD)\, Phys ical Optics (PO)\, Ray Lunching Geometrical Optics (RL-GO)\, and Uniform T heory of Diffraction (UTD). As the complexity of connected devices increas es each day\, designers are taking advantage of AI/ML to generate trained models for their physical antenna designs and perform fast and intelligent optimization on these trained models. Using the trained models\, differen t optimization algorithms and goals can be run quickly\, in seconds\, that can be utilized for comparison studies\, stochastic analysis for toleranc e studies etc. Use of cloud computing combined with AI/ML\, many design it erations can be performed in a short period and reducing the time to marke t. This talk will also focus on future trends in cloud computing for physi cs-based simulations and the emerging topics such as Digital Twins.\n\nVir tual: https://events.vtools.ieee.org/m/410052 LOCATION:Virtual: https://events.vtools.ieee.org/m/410052 ORGANIZER:a.j.terzuoli@ieee.org SEQUENCE:4 SUMMARY:Pushing the Boundaries of Computational Electromagnetics – Applic ation to Antenna Designs\, Placement\, Co-site Interference Simulations an d Digital Twins URL;VALUE=URI:https://events.vtools.ieee.org/m/410052 X-ALT-DESC:Description: <br /><p>Simulation-driven design changed product d evelopment forever\, enabling engineers to reduce design\, iterations\, an d prototype testing. Increasing scientific computing power expanded the op portunity to apply analysis\, making large design studies possible within the timing constraints of a program. Now engineering adoption of Artificia l Intelligence (AI) and Machine Learning (ML) is transforming product deve lopment again. Combination of physics-based simulation-driven design with machine learning\, leveraging the latest in high-performance cloud computi ng\, enables industry to explore more and identify high-potential designs &ndash\; while rejecting low-potential concepts &ndash\; even earlier in d evelopment cycles as well as help create &ldquo\;Digital Twins&rdquo\;. Wi th the increase in connected devices and platforms (such as 5G\, 6G\, C-V2 X\, ADAS etc.)\, advanced computational electromagnetic (CEM) tools have b ecome part of the product design cycle. Now numerical simulations can be p erformed to evaluate the effects of antenna design\, placement\, radiation hazard\, EMC/EMI\, etc. for wide ranging industry applications. Interfaci ng with propagation tools\, system level design can be accomplished that i ncludes operating environment of the devices for device connectivity and t hroughput. Advent of cloud computing and AI/ML\, and convergence with CEM simulations made connected\, smart device design faster with reduced time from concept to the market propelling productivity and innovation. This ta lk will focus on advanced CEM simulation tools that incorporate numerical methods\, such as Method of Moments (MoM)\, Multilevel Fast Multipole Meth od (MLFMM)\, Finite Element Method (FEM)\, Finite Difference Time Domain ( FDTD)\, Physical Optics (PO)\, Ray Lunching Geometrical Optics (RL-GO)\, a nd Uniform Theory of Diffraction (UTD). As the complexity of connected dev ices increases each day\, designers are taking advantage of AI/ML to gener ate trained models for their physical antenna designs and perform fast and intelligent optimization on these trained models. Using the trained model s\, different optimization algorithms and goals can be run quickly\, in se conds\, that can be utilized for comparison studies\, stochastic analysis for tolerance studies etc. Use of cloud computing combined with AI/ML\, ma ny design iterations can be performed in a short period and reducing the t ime to market. This talk will also focus on future trends in cloud computi ng for physics-based simulations and the emerging topics such as Digital T wins.</p><br /><br />Agenda: <br /><p>Simulation-driven design changed pro duct development forever\, enabling engineers to reduce design\, iteration s\, and prototype testing. Increasing scientific computing power expanded the opportunity to apply analysis\, making large design studies possible w ithin the timing constraints of a program. Now engineering adoption of Art ificial Intelligence (AI) and Machine Learning (ML) is transforming produc t development again. Combination of physics-based simulation-driven design with machine learning\, leveraging the latest in high-performance cloud c omputing\, enables industry to explore more and identify high-potential de signs &ndash\; while rejecting low-potential concepts &ndash\; even earlie r in development cycles as well as help create &ldquo\;Digital Twins&rdquo \;. With the increase in connected devices and platforms (such as 5G\, 6G\ , C-V2X\, ADAS etc.)\, advanced computational electromagnetic (CEM) tools have become part of the product design cycle. Now numerical simulations ca n be performed to evaluate the effects of antenna design\, placement\, rad iation hazard\, EMC/EMI\, etc. for wide ranging industry applications. Int erfacing with propagation tools\, system level design can be accomplished that includes operating environment of the devices for device connectivity and throughput. Advent of cloud computing and AI/ML\, and convergence wit h CEM simulations made connected\, smart device design faster with reduced time from concept to the market propelling productivity and innovation. T his talk will focus on advanced CEM simulation tools that incorporate nume rical methods\, such as Method of Moments (MoM)\, Multilevel Fast Multipol e Method (MLFMM)\, Finite Element Method (FEM)\, Finite Difference Time Do main (FDTD)\, Physical Optics (PO)\, Ray Lunching Geometrical Optics (RL-G O)\, and Uniform Theory of Diffraction (UTD). As the complexity of connect ed devices increases each day\, designers are taking advantage of AI/ML to generate trained models for their physical antenna designs and perform fa st and intelligent optimization on these trained models. Using the trained models\, different optimization algorithms and goals can be run quickly\, in seconds\, that can be utilized for comparison studies\, stochastic ana lysis for tolerance studies etc. Use of cloud computing combined with AI/M L\, many design iterations can be performed in a short period and reducing the time to market. This talk will also focus on future trends in cloud c omputing for physics-based simulations and the emerging topics such as Dig ital Twins.</p> END:VEVENT END:VCALENDAR