Conference Agenda

Ventilation rate in naturally ventilated (NV) livestock houses is a critical parameter for ammonia emission factor estimation and microclimate management, particularly in barns with large side openings where spatial non-uniformity limits single-point measurement approaches. This study suggested the optimised VR measurement in a NV beef cattle barn using computational fluid dynamics (CFD) modelling and in-situ measurements and evaluated the effect of animal representation on VR determination. A model excluding animals, a simplified porous-medium model representing the animal-occupied zone (AOZ), and a detailed model explicitly including animal geometry were developed and validated using measured data at all openings. The model without animals overestimated total VR by 43.2–110.5%, while the porous-medium model partially improved prediction accuracy. The model including animal geometry achieved the highest accuracy, with total VR errors of 12.2–28.3%. Additional analyses for standard barns with capacities of 80 and 120 head optimised sensor number and placement. Simulations under eight wind directions showed that VR representativeness was primarily governed by side openings. Four sensors achieved an average relative error below 1%, whereas two sensors were sufficient at entrances. This study presents an optimised sensor placement strategy for reliable VR prediction in NV beef cattle barns.

Vertical multi-layer farming increases crop production within limited space. However, dense rack arrangement and improper circulation-fan arrangement can induce stagnant zones and spatial microclimate gradients, reducing environmental control efficiency. This study evaluated the effects of circulation-fan arrangement and multi-layer vertical spacing on airflow distribution in a vertical farming greenhouse. Field measurements of fan outlet velocity, air temperature, and relative humidity (RH) at 1.5 m height were conducted to quantify spatial heterogeneity and to provide boundary conditions for computational fluid dynamics (CFD) model development and validation. Fan outlet velocities vary notably (3.23-5.00 m/s). Air temperature showed moderate spatial heterogeneity (21.47-25.78°C, CV: 6.5%) consistently higher in central zones, while RH (43.74-54.06%, CV: 7.7%) displayed an inverse pattern. The CFD model was validated using the measured air velocity and temperature data, achieving a temperature error of 1.29°C, and was subsequently used for fan reorientation and multi-layer spacing scenario analysis. Fan reorientation and spacing reduced low-velocity regions (<0.5 m/s) caused by exhaust air interference. Increasing the multi-layer vertical spacing from 0.45 m to 0.65 m did not significantly change overall airflow magnitude, but it enhanced the vertical mixing within the cultivation layers. Fan arrangement was identified as the dominant factor governing airflow uniformity.

This study aims to develop regression models for predicting heat stress, expressed as the Temperature–Humidity Index (THI), inside mechanically ventilated swine houses using weather forecast data. Because long-term measurements across diverse regions and housing types are practically limited, a Building Energy Simulation (BES) approach was employed to generate foundational data for model development. The BES model was validated against monitoring data, demonstrating high accuracy with a mean absolute percentage error of 1.254% to 2.003%. To identify significant predictors, a full factorial simulation was conducted considering building size (3 levels), region (16 locations), climate condition (2 levels), cooling pad operation (2 levels), and insulation level (4 levels). Based on ANOVA and global sensitivity analysis, which identified climate conditions and cooling operation as the most influential factors, the regression models were constructed using outdoor temperature and relative humidity as key predictors. These models enable the prediction of internal THI using forecasted weather data. The results demonstrated that this approach can effectively support anticipatory heat stress management and climate change adaptation in swine production.

A naturally ventilated pig barn with an outdoor exercise yard has the potential to improve pig welfare by combining an indoor housing area with access to an outdoor exercise yard. Compared with conventional pig barns, two building configurations are different in this system: the presence of a yard and the inclusion of cubicles inside the indoor housing area. The yard provides pigs with space for activity and contact with the outdoor environment, while the cubicles offer a stable and sheltered area for resting. To assess the influence of the yard and cubicles on the ventilation system, CFD simulations were conducted to evaluate ventilation performance under four configurations: with or without the yard, and with or without the cubicles. Two seasons (hot and cold) were considered, as the configurations serve different purposes in different seasons. The results showed that: 1) The presence of the yard significantly influenced the ventilation pattern, guiding wind effectively into the indoor housing area during hot seasons; 2) Cubicles provided a warmer sub-area within the animal-occupied zone during winter. Overall, this study demonstrates the positive effect of the two configurations on ventilation organisation and highlights its potential for a better indoor environment to improve animal welfare.

Energy efficiency and animal welfare are critical concerns for dairy farms in the Po Valley, where summer heat waves severely impact cow health and milk production. Ventilation systems in dairy barns are commonly con-trolled using THI, typically measured at a single central point and applied uniformly across multiple zones. However, this approach does not account for spatial variability within the barn microclimate and may limit opportu-nities for energy optimization.
The aim of this work is to evaluate whether replacing THI-based control with a more comprehensive thermal index, i.e., the Equivalent Temperature Index (ETI), could improve the energy efficiency of mechanical ventilation systems while maintaining adequate thermal conditions for dairy cows.
A multi-point Smart Monitoring System was used to collect temperature, relative humidity, and air velocity in three predefined barn zones, enabling calculation of ETI. Energy consumption was analyzed under two scenarios: (I) actual fan operation controlled by THI-based setpoints, and (II) a simu-lated control strategy depending on ETI.
The simulations showed that ETI-based control would reduce fan operat-ing time and power use, with 30% energy saving. Thus, ventilation control through ETI provides a more accurate representation of the thermal load ex-perienced by cows and enables substantial energy efficiency.

During the cold season, natural airflow could fail to ensure proper microclimate conditions, potentially leading to the accumulation of harmful and greenhouse gases. In naturally ventilated dairy barns, airflow patterns are strongly influenced by external wind conditions, barn geometry, and animal distribution, resulting in significant spatial variability in air quality and microclimatic conditions. Computational Fluid Dynamics (CFD) provides a powerful approach to investigate these complex airflow processes and emissions distribution. In this study, CFD simulations are used to analyze airflow patterns and distribution of methane (CH₄), ammonia (NH₃), and carbon dioxide (CO₂) inside a naturally ventilated dairy barn under representative cold-season wind conditions derived from local meteorological data. The results provide insights into gas dispersion within the barn and support the identification of suitable locations for experimental measurements and emission monitoring, demonstrating the potential of CFD as a tool for improving ventilation management in dairy housing.

Environmental control is essential for ensuring stable year-round greenhouse production. In particular, thermal curtains are critical for maintaining optimal growth temperatures by minimizing heat loss during the winter season. However, their performance depends on operational factors beyond simple opening or closing, such as the opening ratio, location, and direction. Therefore, this study aimed to analyze the internal air temperature distributions based on the opening direction and degree of the curtains, utilizing Computational Fluid Dynamics (CFD) as the primary analytical tool. The target greenhouse is a four-span plastic structure(18.6m wide, 37.0m long, and 5.6m eave height). Within this structure, the airflow and thermal environment were analyzed under various curtain-opening conditions(east-west, north-south direction, etc.). The results showed that at an outdoor air temperature of 5 °C, the internal air temperature under the north-south opening condition was 6.24 °C at 50% opening and 9.65 °C at 25% opening, showing a significant difference of 3.41°C. Furthermore, reducing the opening rate from 25% to 12.5% lowered the air temperature to 9.35°C. This decline was attributed to strong vertical temperature gradients and thermal non-uniformity, highlighting the necessity of determining optimal opening conditions to achieve both energy efficiency and thermal uniformity.