Air-Fluidized Aggregates of Black Soldier fly Larvae

Abstract

Black soldier fly larvae are a sustainable protein source and play a vital role in the emerging food-waste recycling industry. One of the challenges of raising larvae in dense aggregations is their rise in temperature during feeding, which, if not mitigated, can become lethal to the larvae. We propose applying air-fluidization to circumvent such overheating. However, the behavior of such a system involves complex air-larva interactions and is poorly understood. In this combined experimental and numerical study, we show that the larval activity changes the behavior of the ensemble when compared to passive particles such as dead larvae. Over a cycle of increasing and then decreasing airflow, the states (pressure and height) of the live larva aggregates are single-value functions of the flow speed. In contrast, dead larva aggregates exhibit hysteresis characteristic of traditional fluidized beds, becoming more porous during the ramp down of airflow. This history-dependence for passive particles is supported by simulations that couple agent-based dynamics and computational fluid dynamics. We show that the hysteresis in height and pressure of the aggregates decreases as the activity of simulated larvae increases. To test if air fluidization can increase larval food intake, we performed feeding trials in a fluidization chamber and visualized the food consumption via x-ray imaging. Although the food mixes more rapidly in faster airflow, the consumption rate decreases. Our findings suggest that providing moderate airflow to larval aggregations may alleviate overheating of larval aggregations and evenly distribute the food without reducing feeding rates.

Fire ant rafts elongate under fluid flows

“…The fluid-like behavior we observed may only require activity, but not any planning or communication among the group. We found black soldier fly larvae do not require any sensing of their environment to reduce flow hysteresis; they only require random body motions, which generate rearrangement of the collective [33]. Could the streamlining behavior be a consequence of just random motion, or does it truly require sensing?…”

“…This is because of the interaction of the shape of the raft and the fluid stress . Due to the high computational cost, fluid-agent interaction simulations are rare in the literature (see [33] for an example).…”

Toward a 3D physical model of diffusive polymer chains

“…Future work could focus on increasing the length of chains and capturing a faster frame rate (as in [ 21 ]) to resolve motion blur issues. In addition, the magnitude of environmental forces in the simulation could be further calibrated by measuring the drift velocity of a single free bead (as in [ 22 ]) to correlate the strengths of the fluctuations to the magnitude of the dissipative force.…”

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots

“…An alternative method is by directly modelling the vortex street behind a two-dimensional swimmer [ 149 ]. In addition, adaptive mesh refinement and simplified agents have been used to conduct a parameter study of insect swarms under airflow [ 33 ]. Another promising approach that does not require significant sacrifice in flow field accuracy is to prescribe the trajectories and kinematics tracked from animal experiments.…”

“…However, the key notion stands: hydrodynamic interactions could lead to self-organizing effects in spite of social interactions. Coupling with these effects, movements of active agents can give rise to unexpected collective behaviours [ 33 ].…”