Changes

Jump to: navigation, search

Dimethyl Sulfide

15 bytes added, 18:25, 1 May 2016
m
no edit summary
===Numerical Modeling Using Updated DMS Volatility Data===
[https://www.facebook.com/mark.hammond.1253 Mark Hammond] from MTF used a computer program to model the conversion of SMM to DMS based on taking into account the [[Dimethyl_Sulfide#Mashing_and_Boiling|SMM half-life]] at any given time different times and temperature temperatures during different various methods of the "no boil" process. Rather than using Fix's average half-life approach, numerical modeling divides the heating, boiling and cooling times into very small time steps (for the work below, a time step of 0.6 seconds was used), during which the temperature is approximated to be constant. The computer program calculates the amount of SMM converted to DMS during the time step, the amount of DMS volatilized during the time step, then plots the total DMS and SMM in the wort at the end of the time step. Finally, the program calculates a new temperature, which depends on whether the wort is heating up, being held at a constant temperature, or cooling. The program then loops through all the calculations at this new temperature, calculating all the same quantities for the next time step.
The new equations from [http://onlinelibrary.wiley.com/doi/10.1002/jib.301/full "Scheuren, Baldus, Methner and Dillenburge (2016): Evaporation behaviour of DMS in an aqueous solution at infinite dilution – a review"] were used to determine the evaporation of DMS during the cooling time (this assumes an open cooling system; closed cooling systems will retain this DMS). Hammond assumed a linear heating rate and used Newton's Law of Cooling with constants based on empirical data taken from his own homebrewing equipment. Evaporation rates were likewise modeled using thermodynamic equations and empirical data from Hammond's equipment. By observing these estimations, it can be seen that no-boil or "raw ale", and wort boiled for short durations, Hammond predicts less DMS than what is predicted using the traditional model.

Navigation menu