Advances and challenges in thermal runaway modeling of lithium-ion batteries

The broader application of lithium-ion batteries(LIBs)is constrained by safety concerns arising from thermal runaway(TR).Accurate prediction of TR is essential to comprehend its underlying mechanisms,expedite battery design,and enhance safety protocols,thereby significantly promoting the safer use of LIBs.The complex,nonlinear nature of LIB systems presents substantial challenges in TR modeling,stemming from the need to address multiscale simulations,multiphysics coupling,and computing efficiency issues.This paper provides an extensive review and outlook on TR modeling technologies,focusing on recent advances,current challenges,and potential future directions.We begin with an overview of the evolutionary processes and underlying mechanisms of TR from multiscale perspectives,laying the foundation for TR modeling.Following a comprehensive understanding of TR phenomena and mechanisms,we introduce a multiphysics coupling model framework to encapsulate these aspects.Within this framework,we detail four fundamental physics modeling approaches:thermal,electrical,mechanical,and fluid dynamic models,highlighting the primary challenges in developing and integrating these models.To address the intrinsic trade-off between computational accuracy and efficiency,we discuss several promising modeling strategies to accelerate TR simulations and explore the role of AI in advancing next-generation TR models.Last,we discuss challenges related to data availability,model scalability,and safety standards and regulations.

Revealing the residual stress distribution in laser welded Eurofer97 steel by neutron diffraction and Bragg edge imaging

Eurofer97 steel is a primary structural material for applications in fusion reactors. Laser welding is a promising technique to join Eurofer97 plasma-facing components and overcome remote handling and maintenance challenges. The interaction of the induced residual stress and the heterogeneous microstructure degrades the mechanical performance of such fusion components. The present study investigates the distribution of residual stress in as-welded and post-heat treated Eurofer97 joints. The mechanistic connections between microstructure, material properties, and residual stress are also studied. Neutron diffraction is used to study the through-thickness residual stress distribution in three directions,and neutron Bragg edge imaging(NBEI) is applied to study the residual strain in high spatial resolution.The microstructures and micro-hardness are characterised by electron backscatter diffraction and nanoindentation, respectively. The M-shaped residual stress distribution through the thickness of the as-welded weldment is observed by neutron diffraction line scans over a region of 1.41 × 10 mm^(2). These profiles are cross-validated over a larger area(∼56 × 40 mm^(2)) with the higher spatial resolution by NBEI. The micro-hardness value in the fusion zone of the as-welded sample almost doubles from 2.75 ± 0.09 GPa to 5.06 ± 0.29 GPa due to a combination of residual stress and cooling-induced martensite. Conventional post weld heat treatment(PWHT) is shown to release ∼90% of the residual stress but not fully restore the microstructure. By comparing its hardness with that of stress-free samples, it is found that the microstructure is the primary contribution to the hardening. This study provides insight into the prediction of structural integrity for critical structural components of fusion reactors.

Development of a Concentration Measurement Technique for Steady State Solid-liquid Mixing using a Neural Network

A measurement technique that can measure the concentration of the solid particles in liquid flow was developed.The measurement system consists of a color camera and three LCD displays.The solid particles were put at the bottom of a cylindrical mixing tank in which JetA1 oil was filled.Transient mixing of the solid particles was performed by rotating a propeller type agitator with three different rotation speed(500,600,700 r/min).Mixing state was visualized by the LCD displays and a color camcorder.The color intensity of the glass particles changes with their concentration.The color information was decoded into three principle colors R,G,and B so that,the calibration curve of color-to-concentration was performed using these information.A neural network was used for this calibration.The transient concentration field of the solid particles was quantitatively visualized.

Performance Analyses for a Cyclone Type Filter

Flow characteristics inside a cyclone filter were investigated by the use of computational fluid dynamics(CFD). For computations, SST model was adopted. Parametric study was carried out considering the filtering performance. Revolution speeds were changed from 100 to 550 with 50 increments. A skirt is the driving source for cyclone operation. The influence of several design factors, such as the skirt length, the skirt gap and the return length to filtering performance was investigated under the particle diameter 100μm of debris material(Al, s.g.=2.7). The filtering performance was also investigated with the skirt length 28 mm changing the debris diameters from 1μm to 50μm. The flow rate of the working fluid was maintained at 0.55kg/s. It has been verified that the most influential factors to the filtering efficiencies was the skirt gap between the cyclone generator and the cyclone vessel.