Battery Vent Gas Hazard Analysis and Building Deflagration Dashboard Development
| dc.contributor.advisor | Ezekoye, Ofodike A. | |
| dc.creator | Trejo Martinez, Juan | |
| dc.date.accessioned | 2021-03-02T22:19:31Z | |
| dc.date.available | 2021-03-02T22:19:31Z | |
| dc.date.created | 2019-12 | |
| dc.date.issued | 2020-09-15 | |
| dc.date.submitted | December 2019 | |
| dc.date.updated | 2021-03-02T22:19:32Z | |
| dc.description.abstract | Lithium-ion battery failures can lead the battery cell to undergo what’s known as thermal runaway, resulting in a potentially catastrophic fire or explosion. During a thermal runaway event a series of chemical reactions take place, increasing the cell temperature and resulting in the generation of a flammable gas mixture. The University of Texas Fire Research Group has developed two models to evaluate fire and explosion hazard for lithium-ion batteries using the aforementioned studies. The first model aims to estimate the upper and lower flammability limits, laminar flame speed, and maximum overpressure of the gases released during thermal runaway. While the second model predicts the pressure time history of an explosion. Both of these models are intended to provide a framework for evaluating the overall safety of lithium-ion cells. To enable our researches to perform rapid data analysis as more experimental data becomes available, a web application that presents the above-mentioned models in the form of interactive dashboards was developed and deployed using Python and a framework for building data visualization web applications called Dash. The first part of development was building the application’s layout. The layout of a Dash application is built by assembling a hierarchical tree of components. These components are the building blocks of the application and can come from either the dash_html_components or dash_core_components modules. The second part of development involved creating and wiring up a MongoDB database to the application. This connection allows the application to access and perform operations on the stored data. Finally, deploying the application was done through Heroku, a Platform as a Service that provides the infrastructure and user interface to publish and manage a web application. The two dashboards deployed are the Vent Gas Hazard Analysis dashboard and the Building Deflagration dashboard. The Vent Gas Hazard Analysis dashboard summarizes key gas characteristics such as lower and upper flammability limits, laminar flame speed, and maximum over-pressure, which are essential in quantifying the overall hazard potential or the runaway event. While the Building Deflagration dashboard provides information on how room pressure changes over a period of time during a battery explosion event. | |
| dc.description.department | Mechanical Engineering | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/2152/84837 | |
| dc.identifier.uri | http://dx.doi.org/10.26153/tsw/11808 | |
| dc.language.iso | en | |
| dc.subject | Python | |
| dc.subject | Dash | |
| dc.subject | Heroku | |
| dc.subject | Docker | |
| dc.subject | Lithium-ion | |
| dc.subject | Dashboard | |
| dc.title | Battery Vent Gas Hazard Analysis and Building Deflagration Dashboard Development | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Mechanical Engineering | |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | The University of Texas at Austin | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science in Engineering |