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X-WR-CALNAME:Simplify Complex Engineering | oorja
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X-WR-CALDESC:Events for Simplify Complex Engineering | oorja
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BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
TZOFFSETFROM:+0530
TZOFFSETTO:+0530
TZNAME:IST
DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260219T160000
DTEND;TZID=Asia/Kolkata:20260219T170000
DTSTAMP:20260905T211953
CREATED:20251209T101338Z
LAST-MODIFIED:20260123T071042Z
UID:12477-1771516800-1771520400@oorja.energy
SUMMARY:Virtual Battery SIL Integration: Fault Injection\, Diagnostics\, and System Behaviour
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/virtual-battery-sil-integration-fault-injection-diagnostics-and-system-behaviour/
LOCATION:Zoho Webinars
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2025/12/Webinar-BannerMaster.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260331T143000
DTEND;TZID=Asia/Kolkata:20260331T153000
DTSTAMP:20260905T211955
CREATED:20260323T020935Z
LAST-MODIFIED:20260323T091830Z
UID:12763-1774967400-1774971000@oorja.energy
SUMMARY:LFP vs NMC: Beyond the Flat Curve — Rethinking Battery Design\, BMS\, and Monitoring
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/lfp-vs-nmc-beyond-the-flat-curve-rethinking-battery-design-bms-and-monitoring/
LOCATION:Zoho Webinars
CATEGORIES:Upcoming
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2026/03/31st-March-Webinar-Banner-Updated.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260519T143000
DTEND;TZID=Asia/Kolkata:20260519T153000
DTSTAMP:20260905T211956
CREATED:20260516T065004Z
LAST-MODIFIED:20260516T070331Z
UID:12807-1779201000-1779204600@oorja.energy
SUMMARY:Pack degradation using Physics and data based approach: From Cell Variability to System-Level Insights
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/pack-degradation-using-physics-and-data-based-approach-from-cell-variability-to-system-level-insights-copy/
LOCATION:Zoho Webinars
CATEGORIES:Upcoming
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2026/05/19th-Pack-Webinar-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260716T143000
DTEND;TZID=Asia/Kolkata:20260716T153000
DTSTAMP:20260905T211956
CREATED:20260703T051616Z
LAST-MODIFIED:20260730T082828Z
UID:12762-1784212200-1784215800@oorja.energy
SUMMARY:Battery Health Intelligence Across The Lifecycle
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/battery-health-intelligence-across-the-lifecycle/
LOCATION:Zoho Webinars
CATEGORIES:Upcoming
ATTACH;FMTTYPE=image/png:https://oorja.energy/wp-content/uploads/2026/03/1Untitled-design-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260813T143000
DTEND;TZID=Asia/Kolkata:20260813T153000
DTSTAMP:20260905T211957
CREATED:20260730T085102Z
LAST-MODIFIED:20260730T085726Z
UID:12840-1786631400-1786635000@oorja.energy
SUMMARY:Predict Before It Fails: The future of Battery Service and Maintenance
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/predict-before-it-fails-the-future-of-battery-service-and-maintenance/
LOCATION:Zoho Webinars
CATEGORIES:Upcoming
ATTACH;FMTTYPE=image/jpeg:https://oorja.energy/wp-content/uploads/2026/07/Predict-Before-It-Fails-The-future-of-Battery-Service-and-Maintenance.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260917T143000
DTEND;TZID=Asia/Kolkata:20260917T153000
DTSTAMP:20260905T211957
CREATED:20260828T120150Z
LAST-MODIFIED:20260828T121032Z
UID:12859-1789655400-1789659000@oorja.energy
SUMMARY:Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications
DESCRIPTION:« All Events\n 				\n				\n				\n				\n					\n	Thermal Modeling with PINNs: Bringing Physics-Based Simulation to Real-Time and Edge Applications				\n				\n				\n				\n					\n	\n	Date & Time:	\n			September 17\, 2026\n\n	\n\n	  @  \n\n\n2:30 pm\n\n		\n\n\n\n	\n	  -  \n\n3:30 pm\n\n\nIST\n	\n				\n				\n				\n				\n					\n			\n		Mode	\n				\n		Online (Zoho)			\n			\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n				\n									Thermal modeling is critical across engineering systems—from battery packs and power electronics to automotive\, aerospace\, energy storage and industrial equipment. Today\, FEM\, FVM and CFD remain the backbone of high-fidelity thermal simulation. They are trusted\, well understood and essential for design and validation. But engineering teams are now facing two related challenges. The first is speed. Thermal design often requires multiple iterations and parametric studies across geometry\, materials\, boundary conditions\, cooling strategies\, duty cycles and operating environments. Running these studies through conventional high-fidelity simulation can become time-consuming when teams need to explore large design spaces quickly. The second is deployment. How do we take validated physics models beyond the simulation environment and use them for faster what-if studies\, near real-time prediction\, field diagnostics or even edge deployment? This webinar explores the role of Physics-Informed Neural Networks (PINNs) in thermal modeling and how they can complement existing simulation workflows by making physics-based models faster\, lighter and easier to deploy. We will discuss how PINNs combine governing equations\, boundary conditions\, simulation data and experimental measurements to build fast\, physics-consistent surrogate models for temperature prediction\, thermal reconstruction\, inverse heat-transfer problems\, digital twins and near real-time thermal intelligence. The session will also address the practical considerations: where PINNs work well\, where caution is needed\, and how to approach validation\, training effort\, extrapolation risk\, boundary conditions and accuracy compared with conventional simulation. For teams working across batteries\, mobility\, aerospace\, energy and industrial systems\, this webinar offers a practical perspective on moving thermal modeling from offline simulation to deployable engineering intelligence. 								\n				\n					\n				\n		\n					\n				\n				\n									\n					\n						\n									Register Now\n					\n					\n				\n								\n				\n				\n				\n							\n			\n		\n						\n				\n					\n				\n		\n					\n				\n				\n					Meet The Speakers				\n				\n					\n				\n		\n					\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Dr. Vineet Dravid	\n			CEO\, oorja \n	\n				\n				\n				\n				\n									Vineet is a keen problem solver who is passionate about physics\, sports\, and music. Armed with a PhD in mechanical engineering from Purdue\, he dove headfirst into the world of computer-aided engineering and helped establish COMSOL’s Indian wing before starting oorja. At oorja\, he is focused on going beyond the traditional software model and working closely with customers to unlock business value. In his free time\, he enjoys hands-on activities like carpentry.								\n				\n				\n		\n				\n				\n																														\n				\n				\n				\n					\n						\n		Prashant Srivastava	\n			CTO\, oorja \n	\n				\n				\n				\n				\n									Prashant is passionate about mathematics\, machine learning\, and physics. He completed his PhD in Aerospace\, Aeronautical\, and Astronautical Engineering from IISc\, Bangalore\, and shortly after that\, started working at COMSOL\, where he was responsible for building and overseeing several applications. At oorja\, Prashant spearheads our R&D and technological efforts.								\n				\n				\n		\n				\n					\n				\n		\n					\n				\n				\n					\n	\n		\n\n	\n	Add to calendar	\n		\n	\n\n		\n			\n									\n	Google Calendar\n\n									\n	iCalendar\n\n									\n	Outlook 365\n\n									\n	Outlook Live\n\n							\n		\n\n		\n	\n\n				\n				\n				\n				\n					\n	\n		\n\n				Predict Before It Fails: The future of Battery Service and Maintenance
URL:https://oorja.energy/event/thermal-modeling-with-pinns-bringing-physics-based-simulation-to-real-time-and-edge-applications/
LOCATION:Zoho Webinars
CATEGORIES:Upcoming
ATTACH;FMTTYPE=image/jpeg:https://oorja.energy/wp-content/uploads/2026/08/979cfc80-94bf-43c0-9075-77293cd7f8e7.jpg
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