A Review of Experimental and Numerical Studies of Lithium Ion Battery Fires

Lithium-ion batteries (LIBs) are used extensively worldwide in a varied range of applications. However, LIBs present a considerable fire risk due to their flammable and frequently unstable components. This paper reviews experimental and numerical studies to understand parametric factors that have the greatest influence on the fire risks associated with LIBs. The LIB chemistry and the state of charge (SOC) are shown to have the greatest influence on the likelihood of a LIB transitioning into thermal runaway (TR) and releasing heats which can be cascaded to cause TR in adjacent cells. The magnitude of the heat release rate (HRR) is quantified to be used as a numerical model input parameter (source term). LIB chemistry, the SOC, and incident heat flux are proven to influence the magnitude of the HRR in all studies reviewed. Therefore, it may be conjectured that the most critical variables in addressing the overall fire safety and mitigating the probability of TR of LIBs are the chemistry and the SOC. The review of numerical modeling shows that it is quite challenging to reproduce experimental results with numerical simulations. Appropriate boundary conditions and fire properties as input parameters are required to model the onset of TR and heat transfer from thereon.

2014 Canadian Geotechnical Colloquium: Landslide runout analysis — current practice and challenges

Flow-like landslides, such as debris flows and rock avalanches, travel at extremely rapid velocities and can impact large areas far from their source. When hazards like these are identified, runout analyses are often needed to delineate potential inundation areas, estimate risks, and design mitigation structures. A variety of tools and methods have been developed for these purposes, ranging from simple empirical–statistical correlations to advanced three-dimensional computer models. This paper provides an overview of the tools and methods that are currently available and discusses some of the main challenges that are currently being addressed by researchers, including the need for better guidance in the selection of model input parameter values, the challenge of translating model results into vulnerability estimates, the problem with too much initial spreading in the simulation of certain types of landslides, the challenge of accounting for sudden channel obstructions in the simulation of debris flows, and the sensitivity of models to topographic resolution and filtering methods.

Polar F-layer model-observation comparisons: a neutral wind surprise

The existence of a month-long continuous database of incoherent scatter radar observations of the ionosphere from the EISCAT Savlbard Radar (ESR) at Longyearbyen, Norway, provides an unprecedented opportunity for model/data comparisons. Physics-based ionospheric models, such as the Utah State University Time Dependent Ionospheric Model (TDIM), are usually only compared with observations over restricted one or two day events or against climatological averages. In this study, using the ESR observations, the daily weather, day-to-day variability, and month-long climatology can be simultaneously addressed to identify modeling shortcomings and successes. Since for this study the TDIM is driven by climatological representations of the magnetospheric convection, auroral oval, neutral atmosphere, and neutral winds, whose inputs are solar and geomagnetic indices, it is not surprising that the daily weather cannot be reproduced. What is unexpected is that the horizontal neutral wind has come to the forefront as a decisive model input parameter in matching the diurnal morphology of density structuring seen in the observations.