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During times of crisis such as the Covid-19 pandemic, digital platforms are under public scrutiny to guarantee users’ online safety and wellbeing. Following inconsistencies in how platforms moderate online content and behavior, governments around the world are putting pressure on them to curb the spread of illegal and lawful harmful content and behavior (e.g., UK’s Draft Online Safety Bill). These efforts, though, mainly focus on overt abuse and false information, which misses more mundane social media practices such as racial stereotyping that are equally popular and can be inadvertently harmful. Building on Stoever’s (2016) work on the “sonic color line,” this article problematizes sound, specifically, as a key element in racializing memetic practices on the popular short-video platform TikTok. We examine how humorous audio-visual memes about Covid-19 on TikTok contribute to social inequality by normalizing racial stereotyping, as facilitated through TikTok’s “Use This Sound” feature. We found that users’ appropriations of sounds and visuals on TikTok, in combination with the platform’s lack of clear and transparent moderation processes for humorous content, reinforce and (re)produce systems of advantage based on race. Our article contributes to remediating the consistent downplaying of humor that negatively stereotypes historically marginalized communities. It also advances work on race and racism on social media by foregrounding the sonification of race as means for racism’s evolving persistence, which represents a threat to social cohesion.

The present work presents methodology and development of a mathematical model for prediction of the influence of oxide scale on heat transfer during reheating of steel in an industrial furnace. In this developed model, temperatures inside the steel billet were measured and with thermocouples at selected places and were collected by a water cooled computer that was traveling inside the slab. CFD is used to calculate the flow field inside of a furnace. The mass‐transfer coefficient of the scale formation is obtained by solving the convection mass‐diffusion equation across a boundary layer to the surface of a flat plate. A model for inverse heat conduction is employed to calculate the local surface temperature and heat flux on top of the growing oxide scale layer on a slab moving through a walking beam reheating furnace. By using the inverse method, the transient temperature and heat flux was firstly determined on the surface of the steel. During subsequent computations, the growth of the scale was calculated and the surface temperature of the oxide scale was extracted by using the Cauchy data from the previous calculations. The sensibility of the model on steel physical parameters is studied, and suitable parameters were obtained for heating a low carbon steel plate in the reheating furnace. Results show that the oxide scale layer should not be neglected in reheating models.