The mission of the NAFEMS Food and Drink Industry Community (FDIC) is to provide a vendor-neutral, end-user driven consortium that promotes the advancement of the technology and practices associated with all aspects related to simulation of processing operations in these Industries. This includes education, communication, promotion of standards, and development of requirements that will have general benefits to the simulation and analysis community with the identification of benchmarks and major strategic issues (grand challenges).
The scope of this group extends to Foods, Snacks and Beverages (Refreshments) sectors. It will focus on manufacture of the products and associated packaging and usage.
The purpose of this group is to establish the current methods/processes and challenges in the food and drinks industries and how engineering simulation can provide benefits. The aim is to establish best practice, organize and run events such as seminars, webinars, tracks at NAFEMS conferences, provide a platform for the simulation community to share ideas and support new developments.
The Food and Drink Industry Community is interested in their processing at length scales beyond only the continuum mechanics scale. Often subscale models are required to truly capture the complex behaviour of these products. Therefore, such sub-models, in the form of RVEs (Representative Volume Elements) are important to inform the larger scale homogenised continuum mechanics models however, there is no exact cut-off scale. The scale of interest is whatever is useful and informative for the continuum scale and is dependent on the properties of material such as the micro-structure. In addition, to this multiscale strategy, it is often necessary to employ multiphysics treatments due to the multiple physical phenomena that may occur in processing operations.
Time scales are also important for simulation of food and drink products. Challenges can arise when linking different length scales or different physics which operate at different time scales and often the smallest time scale has to be used which creates computational challenges.