From modeling how to optimize fish farming to modeling semiconductor design, to modeling how coffee brewing works, mathematics governs all sorts of industrial processes.
One of the goals of the European Consortium for Mathematics in Industry is to help bridge the gap between industrial practitioners and academic mathematicians working in these areas; and one of the tools the Consortium uses to accomplish this goal is the journal they publish with us, the Journal of Mathematics in Industry. (They also publish a book series with our Springer book publishing colleagues.)
Some articles of note the journal has published include:
- Coffee extraction kinetics in a well mixed system, by Kevin M. Moroney, William T. Lee, Stephen B. G. O’Brien, Freek Suijver, and Johan Marra
- Even in its simplest manifestation the brewing of coffee is a complex operation which is dependent a large number of process variables. Important parameters include the brew ratio (dry coffee mass to water volume used), grind size and distribution, brewing time, water temperature, agitation, water quality and uniformity of extraction . (From the introduction.)
- Chaos-based true random number generators, by Luis L. Bonilla, Mariano Alvaro, and Manuel Carretero
Secure communications, data transfer and storage, and electronic transactions rely on truly random number generators, yet software-driven random number generators aren’t truly random. Now, researchers have demonstrated a technique using spontaneous chaos in room temperature semiconductors to generate truly random numbers.
- Stochastic optimization model of aquacultured fish for sale and ecological education, by Hidekazu Yoshioka and Yuta Yaegashi
- The authors use a system of stochastic differential equations to model the best way to time and manage fish farms. For their example, they used the farming of ayu sweetfish in Japan.