Dairy cattle are particularly sensitive to heat stress due to the higher metabolic rate needed for milk production. In recent decades, global warming and the increase in dairy production in warmer countries have stimulated the development of a wide range of environmental control systems for dairy farms. Despite their proven effectiveness, the associated energy and water consumption can compromise the viability of dairy farms in many regions, due to the cost and scarcity of these resources. To make these systems more efficient, they should be activated in time to prevent thermal stress and switched off when that risk no longer exists, which must consider environmental variables as well as the variables of the animals themselves. Nowadays, there is a wide range of sensors and equipment that support farm routine procedures, and it is possible to measure several variables that, with the aid of algorithms based on predictive models, would allow anticipating animals’ thermal states. This review summarizes three types of approaches as predictive models: bioclimatic indexes, machine learning, and mechanistic models. It also focuses on the application of the current knowledge as algorithms to be used in the management of diverse types of environmental control systems.

A Computation Fluid Dynamics (CFD) study for micro-scale gas–liquid flow was performed by using two different software packages: OpenFOAM^® and ANSYS Fluent^®. The numerical results were compared to assess the capability of both options to accurately predict the hydrodynamics of this kind of system. The focus was to test different methods to solve the gas–liquid interface, namely the Volume of Fluid (VOF) + Piecewise Linear Interface Calculation (PLIC) (ANSYS Fluent^®) and MULES/isoAdvector (OpenFOAM^®). For that, a single Taylor bubble flowing in a circular tube was studied for different co-current flow conditions (0.01 < Ca_B < 2.0 and 0.01 < Re_B < 700), creating representative cases that exemplify the different sub-patterns already identified in micro-scale slug flow. The results show that for systems with high Capillary numbers (Ca_B > 0.8) each software correctly predicts the main characteristics of the flow. However, for small Capillary numbers (Ca_B < 0.03), spurious currents appear along the interface for the cases solved using OpenFOAM^®. The results of this work suggest that ANSYS Fluent^® VOF+PLIC is indeed a good option to solve biphasic flows at a micro-scale for a wide range of scenarios becoming more relevant for cases with low Capillary numbers where the use of the solvers from OpenFoam^® are not the best option. Alternatively, improvements and/or extra functionalities should be implemented in the OpenFOAM^® solvers available in the installation package.