Ralph Kristoffer B. Gallegos

Efficient feed management is essential in aquaculture, especially for bottom-feeding species such as shrimp that require feed delivery at the tank bottom. Most commercial automated feeders are designed for surface-feeding fish and are unsuitable for benthic organisms, leading to feed waste and uneven distribution. This study developed and evaluated an automatic bottom feeder capable of dispensing sinking pellets directly to the substrate. The system integrated a 3D-printed auger for precise feed metering and a closed-type centrifugal impeller positioned at the water surface to achieve radial dispersion of feed. An Arduino Uno microcontroller operated the impeller speed (285.98–586.85 rpm), feed mass (95.23–285.68 g), and dispersion time (2–8 s). A Box–Behnken response surface methodology was used to analyze the influence of these parameters on the mean radius spread of feed, supported by image-based uniformity assessment using OpenCV. Results identified impeller speed as the most significant factor (p = 0.010), with optimal dispersion observed at moderate speeds and longer spread durations. The system demonstrated reliable mechanical performance and precise control, providing a novel, programmable solution for uniform feed delivery in shrimp aquaculture and a promising foundation for scalable, automated bottom-feeding technologies.

Slurry transportation is an essential process in numerous industrial applications, widely studied for its efficiency in material conveyance. Despite substantial research, the impact of pipe wall roughness on critical metrics such as pressure drop, specific energy consumption (SEC), and the Nusselt number remains relatively underexplored. This study provides a detailed analysis using a three-dimensional computational model of a slurry pipeline, with a 0.0549 m diameter and 3.8 m length. The model employs an Eulerian multiphase approach coupled with the RNG k-ε turbulence model, assessing slurry concentrations C_w = 40–60% (by weight). Simulations were conducted at flow velocities V_m = 1–5 m/s, with pipe roughness (R_h) ranging between 10 and 50 µm. Computational findings indicate that both pressure drop and SEC increase proportionally with roughness height, V_m, and C_w. Interestingly, the Nusselt number appears unaffected by roughness height, although it rises corresponds to V_m, and C_w. These insights offer a deeper understanding of slurry pipeline dynamics, informing strategies to enhance operational efficiency and performance across various industrial contexts.

The study establishes two mathematical formulations to predict the pressure drop in a solid–liquid slurry flowing through a straight pipe. Employing the Eulerian–Eulerian RNG k-ε model, the computational investigation uses water as the carrier fluid and glass beads as solid particles. The analysis spans various particle sizes (d₅₀ = 75–175 μm), volumetric concentrations (C_vf = 10–50%), and velocities (V_m = 1–5 m/s). The first model, developed using the MATLAB curve-fitting tool, is complemented by a second empirical equation derived through non-polynomial mathematical formulation. Results from both models are validated against existing experimental and computational data, demonstrating accurate predictions for d₅₀ = 75–175 µm particles within a Reynolds number range of 20,000 ≤ Re ≤ 320,000.

In this study, a sophisticated three-dimensional computational model was developed to investigate the kinetic and thermal characteristics of a bi-model slurry. This model utilized the Eulerian–Eulerian Re-Normalization Group k–ε turbulence approach in conjunction with the kinetic theory of granular flow. The slurry, composed of different combinations of silica sand and fly ash, was transported through a straight pipeline under varying Prandtl numbers. Five different mixture combinations were considered, ranging from 65% silica sand and 35% fly ash to 100% silica sand. The slurry was transported using four different Prandtl fluids with varying temperatures. The pipe wall was maintained at a constant temperature of 400 K. The computational results yielded significant findings. A mixture with a higher proportion of fly ash (65:35) exhibited superior flow characteristics when combined with a low-viscosity Prandtl fluid (Pr = 2.88), resulting in a minimal pressure gradient and specific energy consumption. Enhanced energy efficiency was observed at lower Reynolds numbers and reduced efflux concentrations. Additionally, the 95:05 mixture demonstrated the highest heat transfer coefficient, with further improvements as flow Reynolds numbers and efflux concentrations increased. These results provide valuable insight into optimizing the transportation of bi-model slurries for various industrial applications, emphasizing the importance of composition and Prandtl numbers.

Spray drift leads to wastage of spraying material and poses a threat to non-targeted crops and the environment. Therefore, the spray drift characteristics of a Ronnie Baugh (RB) tractor-trailed boom sprayer were determined through computational fluid dynamics to assist in designing the tractor for boom spraying with minimized spray drift. The wake region of the RB tractor was characterized by investigating its velocity profile, turbulent kinetic energy, and drag coefficient at different forward speeds. Additionally, spray droplet sizes and drift distances from the boom sprayer were measured at forward speeds of 4, 6, and 8 km/h, along with different wind directions. The RB tractor exhibits an estimated drag coefficient of 0.7. The results further demonstrate that, at varying forward speeds, the wake experiences low turbulent kinetic energy and minimal velocity profile variations. No spray drift was observed at tractor speeds below 4 km/h, whereas a drift of 0.19 m and 0.33 m is predicted at 6 km/h and 8 km/h, respectively. The tractor's wake is significantly influenced by changes in wind direction, resulting in varying drift distances from each nozzle due to exposure to both free and obstructed airflow. To minimize drift at higher travel speeds, it is recommended that the tractor be operated in line with the prevailing wind direction.