Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Andrew Kurzawski"'
Publikováno v:
2022 IEEE Energy Conversion Congress and Exposition (ECCE).
Characterization of Vented Gas Predictions in Lithium-Ion Modeling With 1-D Thermal Runaway (LIM1TR)
Autor:
Ala' E. Qatramez, Andrew Kurzawski, John Hewson, Michael Parker, Adam Porter, Daniel Foti, Alexander J. Headley
Publikováno v:
ASME 2022 Heat Transfer Summer Conference.
Thermal runaway and its propagation are major safety issues in containerized lithium-ion battery energy storage systems. While conduction-driven propagation has received much attention, the thermal hazards associated with propagation via hot gases ve
Publikováno v:
Fire Technology. 57:2859-2885
This work describes a deep learning methodology for “emulating” temperature outputs produced by the Fire Dynamics Simulator (FDS), a CFD software. An array of artificial neural networks (ANNs) is trained to predict transient temperatures at speci
Publikováno v:
Proposed for presentation at the 2021 DOE OE Energy Storage Peer Review held October 26-28, 2021 in.
Publikováno v:
Proposed for presentation at the DOE Office of Electricity Energy Storage Program Annual Peer Review held October 26-28, 2021 in.
Autor:
Jinyong Kim, Chuanbo Yang, Joshua Lamb, Andrew Kurzawski, John Hewson, Loraine Torres-Castro, Anudeep Mallarapu, Shriram Santhanagopalan
Publikováno v:
Journal of The Electrochemical Society. 169:110543
Cooling plates in battery packs of electric vehicles play critical roles in passive thermal management systems to reduce risks of catastrophic thermal runaway. In this work, a series of numerical simulations and experiments are carried out to unveil
Publikováno v:
Fire Technology. 56:445-467
Towards the development of a more rigorous approach for coupling collected fire scene data to computational tools, a Bayesian computational strategy is presented in this work. The Bayesian inversion technique is exercised on synthetic, time-integrate