Every process can be captured within the framework of computational modelling, provided the process parameters are measured with accuracy in the manufacturing of primary aluminium.<\/p>\n\n\n\n
Since the production of primary aluminium is an energy guzzler and emitter of large quantities of CO2, even a small savings in energy consumption can lead to savings in CO2 emission. It aids in the sustainable development of innovative aluminium products across various sectors, including Automotive, Aerospace, Building, and Construction.<\/p>\n\n\n\n
I am making this context very clear to discuss carbon anodes, for which a higher density easily indicates a lesser voltage drop in electrolytic cells.<\/p>\n\n\n\n
The question remains: Is it not too much to disrupt the existing level and achieve a better number with the current methodology and equipment? This is where computational techniques will reveal whether we have already reached the boundary conditions or if there is still some room worth investigating.<\/p>\n\n\n\n
The deeper we delve into the subject matter, the more complex the question becomes. Which technique needs to be deployed to understand and stretch the process? Just as we need to set stretched targets in KRA for a team, the science behind a process can be investigated to set stiffer targets.<\/p>\n\n\n\n
We will consider, for example, the anode manufacturing process. Particle packing and viscous deformation-assisted flow behaviour of carbon particles to realign and give rise to denser Anodes is an area which needs to be better studied. <\/p>\n\n\n\n
Discrete Element Modelling (DEM) is a numerical method particularly effective for simulating the behaviour of particulate materials and their interactions under an applied external load. DEM’s excellent ability to model individual particle interactions makes it a valuable tool for understanding and optimising systems involving discrete particles. <\/p>\n\n\n\n
Optimising particle size fractions, their irregular geometries, and tribological conditions is a challenging area that can only be achieved through numerical simulation.<\/p>\n\n\n\n
Sometimes, Innovation and disruption may come in small packets completely unnoticed. It may not be an entirely different technology; the same technology with better control and optimised conditions may offer a practical possibility for consistent performance and optimised asset utilisation.<\/p>\n\n\n\n
Sometimes, Innovation and disruption may come in small packets completely unnoticed. It may not be an entirely different technology; the same technology with better control and optimised conditions may offer a practical possibility for consistent performance and optimised asset utilisation.<\/p>\n","protected":false},"excerpt":{"rendered":"
Every process can be captured within the framework of computational modelling, provided the process parameters are measured with accuracy in the manufacturing of primary aluminium. Since the production of primary aluminium is an energy guzzler and emitter of large quantities of CO2, even a small savings in energy consumption can lead to savings in CO2 […]<\/p>\n","protected":false},"author":88,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":{"0":"post-7332","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-open-forum-for-aluminum-community-blog"},"yoast_head":"\n