The study, published in the Journal of Agriculture and Food Research, focused on suction-type pneumatic conveying, the vacuum-driven method most widely used in modern recirculating aquaculture systems to move feed from storage silos to fish tanks. While positive-pressure blowing systems have been studied extensively, suction conveying has received far less scientific attention, even though it dominates the aquaculture sector. The researchers, Hasan Ghafori and Sadegh Ataei, set out to close that gap with an unusually comprehensive experimental campaign covering twelve commercial pellet types spanning three species: rainbow trout, common carp, and sturgeon, each at four growth stages from pre-starter to fattening.

The physical test rig was a six-meter-long transparent Plexiglas pipeline with a 60-millimeter internal diameter, engineered for a conveying capacity of one ton per hour. A calibrated feeder valve dispensed pellets at mass flow rates ranging from 0.2 to 0.8 kilograms per second, while a variable-speed centrifugal blower pushed air velocities from 10 to 25 meters per second. Because the pipe was transparent, the team could watch the flow patterns directly, but they also backed up their eyes with instrumentation: digital manometers measured pressure drop at three points along the line, a high-precision differential pressure transmitter recorded instantaneous pressure fluctuations at the pipe midpoint, and a two-stage sieving procedure based on the ASABE S269.4 standard quantified mechanical damage by weighing the fines generated during each run.

One of the study’s most significant contributions is a quantitative method for classifying flow regimes, replacing the traditional reliance on visual observation with an objective statistical indicator. The researchers used the coefficient of variation of pressure fluctuations, calculated from 30-second recordings at 3 Hz, to draw hard numerical boundaries between four distinct flow regimes. When the coefficient stayed below 5 percent, the flow was classified as dilute phase, meaning pellets were fully suspended and moving uniformly. Values between 5 and 11 percent marked a transition zone, 11 to 16 percent signaled an unstable zone with a stationary layer at the pipe bottom and strand flow above, and values above 16 percent indicated dense phase, where plug-type flow and frequent particle collisions produce intense pressure fluctuations. These thresholds, validated against both visual observations and simulations, turn regime identification from an art into a reproducible measurement.

The experiments revealed a characteristic U-shaped relationship between air velocity and pressure drop for every pellet type. At low velocities in the dense phase, pressure drops were high, reaching 1100 to 1475 pascals per meter across species, but mechanical damage was minimal, between 1.2 and 4.2 percent, because pellets moved gently as slow-moving slugs. As velocity increased, pressure drop fell to a minimum at roughly 15 to 16 meters per second, the point of highest conveying efficiency, where flow was fully suspended and stable. Beyond that sweet spot, pressure drop climbed again and pellet damage rose sharply, reaching up to 8 percent for fragile pre-starter pellets at 25 meters per second, driven by increasingly violent impacts against walls and neighboring particles.

Species and growth stage mattered enormously. Pre-starter pellets, which are crushed and compacted into small diameters, suffered the worst damage, between 2.8 and 3.1 percent even at the gentle velocity of 10 meters per second, while robust fattening pellets lost only 0.7 to 0.8 percent under the same conditions. Sturgeon pellets, with the highest bulk densities at 590 to 650 kilograms per cubic meter, consistently demanded the most fan power, up to 677 watts at 25 meters per second, while common carp pellets, the lightest and most free-flowing, entered the dilute phase at lower velocities and showed the lowest pressure drops overall. These differences, rooted in measurable properties such as pellet diameter, sphericity, terminal velocity, and drag coefficient, were carefully characterized using digital calipers, a vertical wind tunnel, and universal testing machine measurements of Poisson’s ratio, shear modulus, and friction coefficients.

To capture the physics that experiments alone cannot resolve, the team built a coupled computational fluid dynamics and discrete element method simulation. The gas phase was solved with the standard k-epsilon turbulence model in ANSYS FLUENT, while each pellet’s translational and rotational motion was tracked with Newton’s second law, using the Hertz-Mindlin contact model for particle interactions and the Gidaspow drag model for gas-solid coupling. Crucially, the pellets were not treated as indestructible spheres: a Bonded Particle Model represented each pellet as an assembly of sub-particles connected by breakable bonds, so that fracture occurred whenever impact energy exceeded the pellet’s specific fracture energy, calibrated against single-particle impact tests that measured critical breakage velocities between 16.1 and 19.8 meters per second. A particle replacement model then swapped fractured pellets for fragments, allowing the simulation to compute breakage ratios under every operating condition.

The simulations validated well against experiments, with relative errors of 10.5 to 15.7 percent for pressure drop and 2.50 to 3.23 percent for particle velocity across the full operating range. But full CFD-DEM runs are computationally expensive, which limits their usefulness for the rapid, repeated evaluations that real optimization demands. To overcome this, the researchers trained a surrogate artificial neural network on 480 data points, combining 384 simulation-derived records with 96 experimental measurements. The network, a multi-layer perceptron with an 8-20-12-4 architecture, dropout regularization, and batch normalization, predicts four key outputs at once: pressure drop, average particle velocity, mechanical damage, and power consumption. It achieved a coefficient of determination above 0.96 across all outputs, with test-set mean absolute errors of roughly 12.8 pascals per meter for pressure drop and 0.32 percent for damage, while cutting computation time by several orders of magnitude.

Interpretability analyses confirmed that the network had learned genuine physics rather than statistical artifacts. SHAP analysis identified inlet air velocity as the dominant input, followed by mass flow rate and pellet type, together explaining over 70 percent of predictive variance. Sobol variance-based sensitivity analysis with 65,536 quasi-Monte Carlo samples echoed this ranking, assigning total-order indices of about 0.51 to air velocity for pressure drop and 0.47 for mechanical damage. Even more impressively, the model held up under out-of-distribution testing: when challenged with eight extrapolated scenarios, including air velocities up to 30 meters per second and flow rates outside the training envelope, relative errors stayed below 9.1 percent, defining a reliable operating boundary of 8 to 28 meters per second and 0.1 to 1.0 kilograms per second.

The practical upshot is a set of design guidelines that aquaculture engineers can act on immediately, with an important caveat. For most pellet types, the dilute-phase window around 15 to 16 meters per second offers the best multi-objective compromise: minimum pressure drop, fully suspended stable flow, and acceptable damage. When pellet integrity is the overriding priority, as with fragile pre-starter feeds, controlled dense-phase operation near 10 meters per second minimizes breakage despite higher pressure drop and blockage risk, while the unstable zone should always be avoided. The authors stress that all quantitative boundaries come from a six-meter laboratory pipeline, so industrial installations with longer runs, bends, and higher throughputs will need further validation before these numbers become set-points. Still, the framework itself, experiments feeding simulations feeding an interpretable AI surrogate, offers a template for making one of aquaculture’s most invisible losses visible, measurable, and ultimately controllable.

Subject of Research: Hybrid CFD-DEM and machine learning modeling of mechanical damage and flow regimes in pneumatic conveying of aquaculture feed pellets

Article Title: Hybrid CFD-DEM and ANN modeling of pneumatic conveying of aquaculture feed pellets: Flow regimes, mechanical damage, and performance optimization

Article References: Hybrid CFD-DEM and ANN modeling of pneumatic conveying of aquaculture feed pellets: Flow regimes, mechanical damage, and performance optimization. (n.d.). https://doi.org/10.1016/j.jafr.2026.103285

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103285

Keywords: pneumatic conveying, aquaculture, fish feed pellets, CFD-DEM, artificial neural network, flow regimes, mechanical damage, pressure drop, SHAP analysis, Sobol sensitivity, suction conveyor, feed conversion ratio

The target resource is water ice buried beneath Martian soil and rock. Orbital observations indicate that extensive deposits occur in the planet’s mid-latitudes, sometimes beneath only centimeters to meters of regolith. At some scarps, exposed ice sheets begin roughly one to two meters below the surface and extend more than 100 meters downward. Such deposits could eventually supply water for life-support systems and for producing rocket propellant. The quantities involved are substantial: previous mission studies have estimated that a Mars ascent vehicle could require about 150 metric tons of water, while refueling a Starship-class vehicle could require approximately 600 metric tons. Reaching ice is therefore not simply a matter of finding it from orbit. A practical system must penetrate uncertain mixtures of rock, sediment, dust, and ice, remove the debris continuously or in controlled pulses, and then establish a subsurface reservoir. RedWater combines a rotary-percussive drill with a later melting and pumping sequence based on Rodriguez Well, or Rodwell, technology developed for extracting water from terrestrial polar ice.

During the drilling phase, a bottom-hole assembly breaks the formation into small particles. A hollow metallic coiled tube deploys the assembly and carries electrical, pneumatic, and hydraulic lines from the surface. Gas released near the drill bit entrains the particles and pushes them upward through the annulus. RedWater uses direct circulation: gas travels down the drill string, exits at the bit, and returns through the surrounding borehole space with the cuttings. This arrangement is simpler than reverse circulation, in which debris travels up the center of the drill pipe through a more complicated flow path. The choice is important because the gas must do two jobs. It must first pick up newly created particles at the bottom, then sustain a dilute flow capable of transporting them through the full depth of the hole. If the gas speed is too low, the particles can settle, form dense regions, and recirculate rather than leave the borehole. Accumulating debris increases the energy required to drill and can ultimately cause the drill to stall.

The model treats that transition using empirical correlations for vertical pneumatic conveying. Its central quantity is the choking velocity, the approximate gas speed below which particle transport becomes inefficient. The calculation accounts for borehole geometry, gas density and viscosity, temperature, pressure, gravity, particle density, particle diameter, particle sphericity, and the rate at which the drill advances. Because the borehole is an annulus rather than a round pipe, the researchers use a hydraulic diameter equal to the borehole diameter minus the diameter of the RedWater assembly or coiled tubing. The model estimates the mass flux of cuttings from the borehole area, penetration rate, and density of the material being drilled. It then calculates particle free-fall speed from drag relationships and corrects that speed for the irregular shape of real drill chips. Voidage, the fraction of the conveying volume occupied by gas, is coupled to the choking velocity, so the equations are solved iteratively. A further iteration estimates gas density from bottom-hole pressure using the ideal gas law, including environmental pressure, gas-solid hydrostatic pressure, and frictional losses.

To connect the predicted velocity with hardware, the study converts the result into a required gas mass flow rate. That flow can be controlled using the upstream pressure, gas type, orifice area, and discharge coefficient. The researchers also apply a safety factor of 1.5 to the estimated choking velocity when defining a design condition. The approach was tested in three different settings. In a dedicated vacuum experiment, a 2.44-meter vertical annulus used a 38.1-millimeter inner tube and a 57.2-millimeter transparent outer tube. Sieved silica sand represented drill chips, while nitrogen entered at the bottom through a long supply line. The chamber pressure was maintained at 1.3 kilopascals, and a camera recorded particle motion at 30 frames per second. Steady flow tests used rates of 0.25, 0.4, and 1.0 grams per second. At 1.0 grams per second, the sand was immediately entrained and left the observed section in less than half a second. At the two lower rates, particles recirculated and some remained after the gas was shut off.

The two other experiments used the RedWater system itself. In a freezer test, the drill operated in a 1.4-meter crystalline ice tower at approximately minus 10 degrees Celsius. The system reached an average penetration rate of 0.59 millimeters per second, with instantaneous rates between about 0.35 and 0.75 millimeters per second. Nitrogen was supplied at 550 kilopascals, corresponding to a calculated flow of 16.7 grams per second, but some chips continued to recirculate. After the supply was increased to 690 kilopascals and 18.5 grams per second, the chips were observed to blow out with minimal recirculation. In a separate thermal-vacuum test, the ice was cooled to roughly 210 kelvin and the chamber pressure was reduced to 1.0 kilopascal. Carbon dioxide flowed continuously at a directly measured 0.55 grams per second, and the system cleared the brittle ice chips without visible difficulty. That test also demonstrated end-to-end operation, with liquid water delivered to a container outside the vacuum chamber, although the experiment was designed primarily as a system demonstration rather than a dedicated threshold measurement.

When measured conditions were supplied to the model, its estimates broadly matched the observed transitions. For the sand experiment, the predicted minimum was 0.97 grams per second, within the observed range between inefficient transport at 0.4 grams per second and effective clearing at 1.0 grams per second. For the thermal-vacuum experiment, the model predicted 0.45 grams per second, slightly below the 0.55 grams per second that successfully cleared the chips. The freezer prediction was 16.4 to 16.9 grams per second, close to the 16.7 grams per second at which recirculation was still visible and just below the 18.5 grams per second that cleared the borehole. Because no intermediate rates were tested, the exact threshold remains uncertain. The comparison nevertheless spans different gases, pressures, geometries, and particle conditions. The researchers report that the more than 30-fold difference between the freezer and thermal-vacuum flow rates is driven mainly by ambient pressure and its effect on gas density. At near-Martian pressure, a given gas supply can produce high velocities near the drill bit, increasing drag and momentum transfer to the particles.

The results have direct implications for mission architecture, but they do not represent a final qualification of the drilling system. The model indicates that an optimized RedWater design could require less than one kilogram of gas to drill through a meter of rocky overburden under the projected Martian conditions. Gas could be transported from Earth or compressed from the Martian atmosphere, an approach made more credible by the demonstrated operation of the MOXIE instrument’s atmospheric gas compressor. The calculations also suggest that the minimum instantaneous flow rate is not strongly controlled by the drilling penetration rate, because the gas-solid mixture remains highly dilute even as more cuttings are generated. Faster drilling can still reduce total gas consumed per meter by shortening the time the flow must operate. A pulsed system could offer another efficiency benefit: chips might be allowed to accumulate briefly before a gas pulse carries them to the surface. The pulse would need to last long enough for particles to travel the increasing distance as the borehole deepens.

Important uncertainties remain. All three experiments were performed in Earth gravity, whereas Martian gravity is about 38 percent as strong, and the model predicts that lower particle weight should reduce the required gas flow. The tests also used prepared sand or relatively homogeneous ice, not fractured, porous, dusty, or mixed Martian formations. Gas could leak into surrounding rock or ice instead of returning through the annulus, raising the supply requirement. Particle size and sphericity were estimated, even though drill chips can be irregular and span a broad distribution; the largest particles may determine whether clearing succeeds. The model also stops at the borehole exit and does not address how discharged cuttings will be diverted from the surface opening. The researchers recommend full-scale tests at depths approaching 25 meters, experiments that resolve the transition between recirculation and clearing more finely, computational-fluid-dynamics simulations, reduced-gravity testing, and trials using realistic regolith and ice mixtures. Despite these limitations, the agreement between model and observations supports pneumatic chip clearing as a plausible component of future Martian water-mining systems.

Subject of Research: Pneumatic removal of drill cuttings during Martian water-ice extraction

Article Title: Deep drilling on Mars: pneumatic chip clearing model for the RedWater mining system

Article References: Stolov, L., Palmowski, J., Zacny, K., Yen, B., Mellerowicz, B., Mank, Z., Sanasarian, L., & Schultz, J. (2026). Deep drilling on Mars: pneumatic chip clearing model for the RedWater mining system. Space and Planetary Resources, 2(1), Article 7. https://doi.org/10.1007/s44461-026-00013-y

Image Credits: AI Generated

DOI: 10.1007/s44461-026-00013-y

Keywords: Mars, water ice mining, planetary drilling, pneumatic conveying, RedWater, in-situ resource utilization, coiled tubing, thermal-vacuum testing, Deep, drilling, pneumatic, chip